Sarah O’Keefe: How do you talk to executives about this? How do you find that balance between the promise of what these new tool sets can do for us, what automation looks like, and the risk that is introduced by the limitations of the technology? What’s the roadmap for somebody that’s trying to navigate this with people that are all-in on just getting the AI to do it?

Michael Iantosca: We need to remind them that the current state of AI still carries with it a probabilistic nature. And no matter what we do, unless we add more deterministic structural methods to guardrail it, things are going to be wrong even when all the input is right.

Related links:

• Scriptorium: AI and content: Avoiding disaster
• Scriptorium: The cost of knowledge graphs
• Michael Iantosca: The coming collapse of corporate knowledge: How AI is eating its own brain
• Michael Iantosca: The Wild West of AI Content Management and Metadata
• MIT report: 95% of generative AI pilots at companies are failing

LinkedIn:

• Michael Iantosca
• Sarah O’Keefe

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

SO: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Sarah O’Keefe: Hey everyone, I’m Sarah O’Keefe. In this episode, I’m delighted to welcome Michael Iantosca to the show. Michael is the Senior Director of Content Platforms and Content Engineering at Avalara and one of the leading voices both in content ops and understanding the importance of AI and technical content. He’s had a longish career in this space. And so today we wanted to talk about AI and content. The context for this is that a few weeks ago, Michael published an article entitled The coming collapse of corporate knowledge: How AI is eating its own brain. So perhaps that gives us the theme for the show today. Michael, welcome.

Michael Iantosca: Thank you. I’m very honored to be here. Thank you for the opportunity.

SO: Well, I appreciate you being here. I would not describe you as anti-technology, and you’ve built out a lot of complex systems, and you’re doing a lot of interesting stuff with AI components. But you have this article out here that’s basically kind of apocalyptic. So what are your concerns with AI? What’s keeping you up at night here? 

MI: That’s a loaded question, but we’ll do the best we can to address it. I’m a consummate information developer as we used to call ourselves. I just started my 45th year in the profession. I’ve been fortunate that not only have I been mentored by some of the best people in the industry over the decades, but I was very fortunate to begin with AI in the early 90s when it was called expert systems. And then through the evolution of Watson and when generative AI really hit the mainstream, those of us that had been involved for a long time were… there was no surprise, we were already pretty well-versed. What we didn’t expect was the acceleration of it at this speed. So what I’d like to say sometimes is the thing that is changing fastest is the rate at which the rate of change is changing. And that couldn’t be more true than today. But content and knowledge is not a snapshot in time. It is a living, moving organism, ever evolving. And if you think about it, the large language models, they spent a fortune on chips and systems to train the big large language models on everything that they can possibly get their hands and fingers into. And they did that originally several years ago. And the assumption is that, especially for critical knowledge, is that that knowledge is static. Now they do rescan the sources on the web, but that’s no guarantee that those sources have been updated. Or, you know, the new content conflicts or confuses with the old content. How do they tell the difference between a version of IBM database 2 of its 13 different versions, and how you do different tasks across 13 versions? And can you imagine, especially when it comes to software where most of us, a lot of us work, the thousands and thousands of changes that are made to those programs in the user interfaces and the functionality?

MI: And unless that content is kept up-to-date and not only the large language models, reconsume it, but the local vector databases on which a lot of chatbots and agenda workflows are being based. You’re basically dealing with out-of-date and incorrect content, especially in many doc shops. The resources are just not there to keep up with that volume and frequency of change. So we have a pending crisis, in my opinion. And the last thing we need to do is reduce the people that are the knowledge workers to update, not only create new content, but deal with the technical debt, so that we don’t collapse on this, I think, is a house of cards.

SO: Yeah, it’s interesting. And as you’re saying that, I’m thinking we’ve talked a lot about content debt and issues of automation. But for the first time, it occurs to me to think about this more in terms of pollution. It’s an ongoing battle to scrub the air, to take out all the gunk that is being introduced that has to, on an ongoing basis, be taken out. Plus, you have this issue that information decays, right? In the sense that when, I published it a month ago, it was up to date. And then a year later, it’s wrong. Like it evolved, entropy happened, the product changed. And now there’s this delta or this gap between the way it was documented versus the way it is. And it seems like that’s what you’re talking about is that gap of not keeping up with the rate of change.

MI: Mm-hmm. Yeah. I think it’s even more immediate than that. I think you’re right. But now we need to remember that development cycles have greatly accelerated. Now, when you bring AI for product development into the equation, we’re now looking at 30 and 60-day product cycles. When I started, a product cycle was five years. Now it’s a month or two. And if we start using AI to draft new content, for example, just brand new content, forget about the old content or update the old content. And we’re using AI to do that in the prototyping phase. We’re moving that more left upfront. We know that between then and CodeFreeze that there’s going to be a numerous number of changes to the product, to the function, to the code, to the UI. It’s always been difficult to keep up with it in the first place, but now we’re compressed even more. So we now need to start looking at AI to how does it help us even do that piece of it, let alone what might be a corpus that is years and years old, that’s not ever had enough technical writers to keep up with all the changes. So now we have a dual problem, including new content with this compressed development cycle.

SO: So the, I mean, the AI hype says we essentially, we don’t need people anymore and the AI will do everything from coding the thing to documenting the thing to, I guess, buying the thing via some sort of an agentic workflow. But what, I mean, you’re deeper into this than nearly anybody else. What is the promise of the AI hype, and what’s the reality of what it can actually do?

MI: That’s just the question of the day. Because those of us that are working in shops that have engineering resources, I have direct engineers that work for me and an extended engineering team. So does the likes of Amazon, other serious, not serious, but sizable shops with resources. We have a lot of shops that are smaller. They don’t have access to either their own dedicated content systems engineers or even their IT team to help them. First, I want to recognize that we’ve got a continuum out there, and the commercial providers are not providing anything to help us at this point. So it’s either you build it yourself today, and that’s happening. People are developing individual tools using AI where the more advanced shops are looking at developing entire agentic workflows. 

And what we’re doing is looking at ways to accelerate that compressed timeframe for the content creators. And I want to use content creators a little more loosely because as we move the process left, and we involve our engineers, our programmers in the early, earlier in the phase, like they used to be, by the way, they used to write big specifications in my day. Boy, I want to go into a Gregorian chant. “Oh, in my day!” you know, but, but they don’t do that anymore. And basically the, the role of the content professional today is that of an investigative journalist. And you know what we do, right? We, we scrape and we claw. We test, we use, we interview, we use all of the capabilities of learning, of association, assimilation, synthesis, and of course, communication. And turns out that writing’s only 15% roughly of what the typical writer does in an information developer or technical documentation professional role, which is why we have a lot of different roles, by the way, that if we’re gonna replace or accelerate with people with AI, have to handle all those capabilities of all those roles. So, so where we are today is some of the more leading-edge shops are going ahead, and we’re looking at ways to ingest knowledge, new knowledge, and use that new knowledge with AI to draft new or updated content. But there are limitations to that. So, I want to be very clear. I am super bullish on AI. I think I use it every single day. I’m using it to help me write my novel. I’m using it to learn about astrophotography. I use it for so much. When the tasks are critical, when they’re regulatory, when they’re legal-related, when there’s liability involved, that’s the kind of content that we cannot afford to be wrong. We have to be right. We have to be 100% in many cases.

Whereas with other kinds of applications, we can very well be wrong. I always say AI and large language models are great on general knowledge that’s been around for years and evolves very slowly. But things that move quickly and change very quickly, in my business, it’s tax rates. There’s thousands and thousands of jurisdictions. Every tax rate is different and they change them. So you have to be 100% accurate or you’re going to pay a heck of a penalty financially if you’re wrong. So we are moving left. We are pulling knowledge from updated sources, things like videos that we could record and extract and capture, Figma designs, code even, to a limited degree that there’s assets in there that can be caught, and other collateral, and we’re able to build out and initial drafts. It’s pretty simple. Several companies are doing this right now, including my own team. And then the question comes, how good could it be initially? What can we do to improve that, make it as good as it can be? And then what is the downstream process for ensuring validity and quality of that content? What are the rubrics that we’re going to use to govern that? And therein is where most of the leading edge or bleeding edge or even hemorrhaging edge is right now.

SO: Yeah, and I mean, this is not really a new problem, and it’s not a problem specific to AI either, but we’ve had numerous projects where the delta between what, let’s say, the product design docs and the engineering content and the code, the as-designed documentation and the actual reality of the product walking out the door. So the as-built product, there was the resources, all that source material that you’re talking about, right, that we claw and scrape at. And I would like to also give a shout-out to the role of the anonymous source for the investigative journalists, because I feel like there’s some important stuff in there. But you go in there, you get all this as-designed stuff, right? Here’s the spec, here’s the code, here are the code comments, whatever. Or here’s the CAD for this hardware piece that we’re walking out the door. But the thing that actually comes down the factory assembly line or through the software compiler is different than what was documented in the designs because reality sets in and changes get made. And in many, many, many cases, the role of the technical writer was to ensure that the content that they were producing represented reality and not the artifacts that they started from. So there’s a gap. And there jobs to close that gap so that that document goes out and it’s accurate, right? And when we talk about these AI or automated or any sort of workflow, any sort of automation, any automation that does not take into account the gap between design and reality is going to run into problems. The level of problem depends on the accuracy of your source materials. Now, I wrote an article the other day and referred to the 100% accurate product specifications. I don’t know about you, I have seen one of those never in my life. 

MI: Hahaha that’s absolutely true. That’s really true. 

SO: The promise we have here is, AI is going to speed things up and it’s going to automate things and it’s going to make us more productive. And I think you and I both believe that that is true at a certain level. How do you talk to executives about this? How do you find that balance between the promise of what these new tool sets can do for us and what automation looks like and the risk that is introduced by the limitations of you know, of the technology itself? What does that conversation look like? What are the points that you try to make? What’s the roadmap for somebody that’s trying to, as you said, know, maybe in a smaller organization, navigate this with people that are, you know, all-in on “just get the AI to do it.”

MI: That’s a great question too, because we need to remind them that the current state of AI still carries with it a probabilistic nature. And no matter what we do, unless we add more deterministic structural methods to guardrail it, things are going to be wrong even when all the input is right. AI can still take a collection of collateral and get the order of the steps wrong. It can still include things or do too much. We’ve been trained to write as professional writers in a minimalistic capability. And we can control some of that through prompting. Some of that can be done with guardrails. But when you think about writing tech docs, some people might think, we document. we’re documenting APIs or documenting tasks and we, you know, we’ve always been heavily task-oriented, but you can extract all the correct steps and all the correct steps in the right order, but what doesn’t come along with it all too frequently and almost universally is the context behind it, the why part of it. I always say we can extract great things from code for APIs like endpoints or puts and, you know, gets and puts and things like that. That’s a great for creating reference documentation for programmers. 

But if you want to know, it doesn’t tell you the why, it doesn’t tell you the steps, the exact steps, the code doesn’t tell you that. Now maybe your Figma does. And if your Figma has been done really well, your design docs have been done really well and comprehensively. That can mitigate it tremendously. But what have we done in this business? We’ve actually let go more UX people than probably even writers, you know, which is, which is counterproductive. And then you’ve got things like the happy path and the alternate paths that could exist, for example, through the use of a product or the edge cases, right? The what-ifs that occur. You might be able to, and we should, we are able to do better with the happy path, but the happy path is not the only path. These are multifunction beasts that we built. When we built iPhone apps, we often didn’t need documentation because they did one thing and they did one thing really well. You take a piece of middleware, and it can be implemented a thousand different ways. And you’re going to you’re going to document it by example and maybe give some variance, you’re not going to pull that from Figma design. You’re not going to pull that from code. There’s too much of it there that the human fact-baking capability can look at it and say, this is important, this is less important, this is essential, this is non-essential, to actually deliver useful information to the end user. And we need to be able to show what we can produce, continue to iterate and try to make it better and better, because someday we may actually get pretty darn close with support articles and completed support case payloads, we were able to develop an AI workflow that very often was 70% to 100% accurate and ready for publish. 

But when you talk about user guides and complex applications, it’s another story because somebody builds a feature for a product and that feature boils down into not a single article, but into an entire collection of articles that are typed into the kind of breakdown that we do for disclosure, such as concepts, tasks, references, Q&A. So AI has got to be able to do something much more complex, which is to look at content and classify it and apply structure to separate those concerns. Because we know that when we deliver content in the electronic world, we’re no longer delivering PDF. Well, of us are hopefully not delivering PDF books made up of long chapters that intersperse all of these different content types because of the type of consumption, certainly not for AI and AI bots. Then when we, so we need to document, maybe the bottom line here is we need to show what we can do. We need to show where the risks are. We need to document the risks, and then we need the owners, the business decision makers, to see those risks, understand those risks, and sign off on those risks. And if they sign off on the risks, then me, as a technology developer and an information developer, I can sleep at night because I was clear on what it can do today. And that is not a statement that says it’s not going to be able to do that tomorrow. It’s only a today statement so that we can set expectations. And that’s the bottom line. How do we set expectations when there’s an easy button that Staples put in our face, and that’s the mentality of what AI is. It’s press a button and it’s automatic.

SO: Yeah, and I did want to briefly touch on, you know, the knowledge base articles are really, really interesting problem because in many cases you have knowledge base articles that are essentially bug fixes or edge cases when I, you know, hold my finger just so and push the button over here, you know, it blue screens.

MI: Mm-hmm.

SO: And that article can be very context-specific in the sense of you’re only going to see it if you have these five things installed on your system. And/or it can be temporal or time-limited in the sense that, while we fixed the bug, it’s no longer an issue. Okay. Well, so you have this knowledge-based article and you feed it into your LLM as an information source going forward, but we fixed the bug. So how do we pull it back out again?

MI: I love that question. 

SO: I don’t!

MI: I love it. No, I’ve been, actually working for a couple of years on this very particular problem. The first problem we have, Sarah, is we’ve been so resource constrained that when doc shops built an operations model, the last thing they invested in is the operations and the operations automation. So when I’m in a conference and I have a big room of 300 professional technical doc folks. I love asking the simple question, how do you track your content? And inevitably, I get, yeah, well, we do it on Excel spreadsheets. To actually have a digital system of record, I get a few hands. And then I ask the question, well, does that digital system of record that you have for every piece of documentation you’ve ever published, does that span just the product doc or does that actually span more than product doc like your developer, your partner, your learning, your support, all these different things. Cause the customer doesn’t look at us as those different functions. They look at us as one company, one product. And inevitably, I’m lucky if I get one hand in the audience that says, yeah, we actually are doing that. So the first thing they don’t have is they don’t have a contemporary system of record that is digital that we can say, we know and can automate notifications as to when a piece of documentation should either be re-reviewed and revalidated or retired and taken out.

The other problem we have is that all of these AI implementations and companies, almost universally, not completely, but most of them, were based on building these vector databases. And what they did, was often to the completely ignoring the doc team, was just go out to the different sources they had available, Confluence, SharePoint. If you had a CCMS, they’d ask you for access to your CCMS or your content delivery platform, and they suck it in. They may date-stamp it, which is okay, but pretty rudimentary. And they may even have methods for rereading those sources every once in a while, but they’re not, unless they’re rebuilding the entire vector database, and then what did they do when they ingested the content? They shredded it up into a million different pieces, right? Because the context windows for large language models have limitations for token numbers and things like that. Maybe they’re bigger today, but they’re still limited. So how would they even replace a fragment of what used to be whole topics and whole collection of topics? And this is why we wrote the paper and did the implementation and share with the world what we call the document object model knowledge graph because we needed a way outside of the vector database to say go look over here and you can retrieve the original entire topic or collection of topics or related topics in their entirety to deliver to the user. And again, we’re still unless we update that content and it’s don’t treat it like a frozen snapshot in time, we’ll still have those content debt problems. But it’s becoming a bigger, bigger, a much bigger problem now. It wasn’t as big a problem when we put out chatbots. And the chatbots we’ve been building, what, for three, you know, two, three, four years now. And, you know, everybody celebrated, they popped the corks, you know, we can deflect X amount percentage of support cases. They can self-service. And I always talk about the precision paradox that once you reach a certain ceiling, it gets really hard to increment and get above that 70%, 80%, 85%, 90% window. And as you get closer and better, the tolerance for being wrong goes down like a rock. And you now have a real big problem.

So how do we do these guardrails to be more deterministic, to mitigate the probabilistic risk that we have and reality that we have? The problem is that people are still looking for fast and quick, not right. When I say right, I mean the building out of things like ontologies and leveraging our taxonomies that we labored over with all of that metadata that never even gets into the vector database because they strip it all away in addition to shredding it up. So if we don’t start building those things like knowledge graphs and retaining all of that knowledge, it’s even… now we’re compounding the problem. Now we have debt, and we have no way to fix the debt. And now when we get into the new world of agentic workflows, which is the true bleeding edge right now, when you have sequences of both agentic and agentive, and the difference between those two, by the way, is agentic is autonomous. There’s no human doing that task. It’s just doing it. And then agentive, which is a human in the loop, which is helping there. When you’ve got a mix of agentive and agentic processes in a business workflow, now you’ve got to worry about what happens if I get something wrong early in the chain of sequence in that workflow. And this doesn’t apply to just documentation, by the way. We’ll be seeing companies taking very complex workflows in finance and in marketing and in business planning and reporting and mapping out this is the workflow our humans do. And there’s hundreds, if not more steps and many roles involved in those workflows. And as we map those out and say, where can we inject AI, not as just individual tools, like just separately using a large language model or separately using a single agent, but stringing them together to automate a complex business workflow with dependencies upstream and downstream. How are we going to survive and make this work? And I think that’s why you saw the MIT study had come out where they said, you know, roughly only 5% or so of AI projects are succeeding. And I think that’s because we did the easy stuff first. We did the chatbots and they could be lossy in terms of accuracy. But when you now, when you get to these agenda workflows that we’re building, literally coding as we speak, now you’re facing a whole different experience and ballgame where precision and currency really matters.

SO: Yeah, and I think I mean, we’ve really only scraped the surface of this. Both of the articles that you’ve mentioned, the one that I started with and the one that you mentioned in this context, we’ll make sure we get those into the show notes. I believe they are on your is it Medium? On your website. So we’ll get those links in there. Any final parting words in the last? I don’t know. Fifteen seconds or so.

MI: No, that’s good. I want to give, I want to tell you the good news and the bad news for tech doc professionals. What I’m seeing in the industry hurts me. I think there’s a lot of excuse right now, not just in the tech doc space, but in all jobs where we’re seeing AI being used as an excuse to make business decisions, to scale back. It may take some time until the impact of some poor business decisions that are being made will reflect themselves, but there’s going to be reality that hits. And the question is, is how do we navigate the interim? I’m confident that we will. I’m confident that those of us that are building the AI, I feel like I’m evil and a savior at the same time. I’m evil because I’m building automation that can speed up and make people much more productive, meaning you need less people potentially. At the same time, I feel like we’re in a position when we do it, rather than an engineer that doesn’t even know the documentation space, we’re getting to redefine our space ourselves and not leave it to the whims of people that don’t understand the incredible intricacy and dependencies of creating what we know as high-quality content. So we’re in this tumult right now, I think we’re going to come out of it. I can’t tell you what that window looks like. There will be challenges through doing that, but I would rather see this community define their own, redefine their own future in this transformation that is unavoidable. It’s not going away. It’s going to accelerate and get more serious. But if we don’t define ourselves, others will. And I think that’s the message I want our community to take away. So when we go to conferences and we show what we’re doing and we’re open and we’re sharing all the stuff that we’re doing, that’s not, hi, look at us. That’s you come back to the next conference and the next webinar and show us what you took from us and made better and helped shape and mold that transformative industry that we know as knowledge and content. And I’m excited because I want to celebrate every single advance that I see as we share. And I think it’s incumbent upon us to share and be vocal. And I think when I write my articles, they’re aimed at not only our own community, they’re aimed at the executives and technologists themselves to educate them, so that if we don’t do it, who will? And it does fall on all of us to do that.

SO: I think I’m going to leave it there with a call for the executives to pay attention to what you are saying, and some of the rest of this community, many of the rest of this community are saying. So, Michael, thank you very much for taking the time. I look forward to seeing you at the next conference and seeing what more you’ve come up with. And we will see you soon.

MI: Thank you very much.

SO: Thank you.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Want more content ops insights? Download our book, Content Transformation.

The post Futureproof your content ops for the coming knowledge collapse appeared first on Scriptorium.

The blame stage: “It’s the tools. It’s the process. It’s the people.” Technical writers hear, “We’re going to put you into this department, and we’ll get this person to manage you with this new agile process,” or, “We’ll make you do things this way.” The finger-pointing begins. Tech teams blame the authors. Authors blame the CMS. Leadership questions the ROI of the entire content operations team. This is often where organizations say, “We’ve got to start making a change.” They’re either going to double down and continue building content debt, or they start looking for a scalable solution.

— Dipo Ajose-Coker

Related links:

• Scriptorium: Technical debt in content operations
• Scriptorium: AI and content: Avoiding disaster
• RWS: Secrets of Successful Enterprise AI Projects: What Market Leaders Know About Structured Content
• RWS: Maximizing Your CCMS ROI: Why Data Beats Opinion
• RWS: Accelerating Speed to Market: How Structured Content Drives Competitive Advantage (Medical Devices)
• RWS: The all-in-one guide to structured content: benefits, technology, and AI readiness

LinkedIn:

• Dipo Ajose-Coker
• Sarah O’Keefe

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

SO: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Sarah O’Keefe: Hey, everyone. I’m Sarah O’Keefe and I’m here today with Dipo Ajose-Coker. He is a Solutions Architect and Strategy at RWS and based in France. His strategy work is focused on content technology. Hey, Dipo.

Dipo Ajose-Coker: Hey there, Sarah. Thanks for having me on.

SO: Yeah, how are you doing?

DA-C: Hanging in there. It’s a sunny, cold day, but the wind’s blowing.

SO: So in this episode, we wanted to talk about moving forward with your content and how you can make improvements to it and address some of the gaps that you have in terms of development and delivery and all the rest of it. And Dipo’s come up with a way of looking at this that is a framework that I think is actually extremely helpful. So Dipo, tell us about how you look at content debt.

DA-C: Okay, thanks. First of all, I think before I go into my little thing that I put up, what is content debt? I think it’d be great to talk about that. It’s kind of like technical debt. It refers to that future work that you keep storing up because you’ve been taking shortcuts to try and deliver on time. You’ve let quality slip. You’ve had consultants come in and out every three months, and they’ve just been putting… I mean writing consultants.

SO: These consultants.

DA-C: And they’ve been basically doing stuff in a rush to try and get your product out on time. And over time, those sort of little errors, those sort of shortcuts will build up and you end up with missing metadata or inconsistent styles. The content is okay for now, but as you go forward, you find you’re building up a big debt of all these little fixes. And these little fixes will eventually add up and then end up as a big debt to pay.

SO: And I saw an interesting post just a couple of days ago where somebody said that tech debt or content debt, you could think of it as having principle and interest and the interest accumulates over time. So the less work you do to pay down your content debt, the bigger and bigger and bigger it gets, right? It just keeps snowballing and eventually you find yourself with an enormous problem. So as you were looking at this idea of content debt, you came up with a framework for looking at this that is at once shiny and new and also very familiar. So what was it?

DA-C: Yeah, really familiar. I think everyone’s heard of the five stages of grief, and I thought, “Well, how about applying that to content debt?” And so I came up with the five stages of content debt. So let’s go into it.

I’m not going to keep referring to the grief part of it. You can all look it up, but the first stage is denial. “Our content is fine. We just need a better search engine. We can actually put it into this shiny new content delivery platform and it’s got this type of search,” and so on and so forth. Basically what you’re doing is you’re ignoring the growing mess. You’re duplicating content. You’ve got outdated docs. You’re building silos, and then you’re ignoring that these silos are actually getting even further and further apart. No one wants to admit that the CMS or whatever system, bespoke system that you’ve put into place, is just a patchwork of workarounds.

This quietly builds your content debt until, actually the longer denial lasts, the more expensive that cleanup is. As we said in that first bit, you want to pay off the capital of your debt as quickly as possible. Anyone with a mortgage knows that. You come into a little bit of money, pay off as much capital as you can so that you stop accruing that debt, the interest on the debt.

SO: And that is where when we talk about AI-based workflows, I feel like that is firmly situated in denial. Basically, “Yeah, we’ve got some issues, but the AI will fix it. The AI will make it all better.” Now, we painfully know that that’s probably not true, so we move ourselves out of denial. And then what?

DA-C: There we go into anger.

SO: Of course.

DA-C: “Why can’t we find anything? Why does every update take two weeks?” And that was a question we used to get regularly where I used to work at a global medical device manufacturer. We had to change one short sentence because a spec change and it took weeks to do that. Authors are wasting time looking for reusable content if they don’t have an efficient CCMS. Your review cycles drag through because all you’re doing is giving the entire 600-page PDF to the reviewer without highlighting what’s in there. Your translation costs balloon and your project managers or leadership gets angry because, “Well, we only changed one word. Can’t you just use Google Translate? It should only cost like five cents.” Compliance teams then start raising flags. And if you’re in a regulated industry, you don’t want the compliance teams on your back, and especially you don’t want to start having defects out in the field. So eventually, productivity drops, your teams feel like they’re stuck. And the cracks are now starting to show across other departments and you’re putting a bad name on your doc team.

SO: Yeah. And a lot of this, what you’ve got here, is the anger that’s focused inward to a certain extent. It’s the authors that are angry at everybody. I’ve also seen this play out as management saying, “Where are our docs? We have this team, we’re spending all this money, and updates take six months.” Or people submit update requests, tickets, something, the content doesn’t get into the docs, the docs don’t get updated. There’s a six-month lag. Now the SOP, the standard operating procedure, is out of sync with what people are actually doing on the factory floor, which it turns out, again, if you’re in medical devices, is extremely bad and will lead to your factory getting shut down, which is not what you want generally.

DA-C: Yeah, it’s not a good position to be in.

SO: And then there’s anger.

DA-C: Yeah.

SO: “Why aren’t they doing their job?” And yet you’ve got this group that’s doing the best that they can within their constraints, which are, as you said, in a lot of cases, very inefficient workflows, the wrong tool sets, not a lot of support, etc. Okay, so everybody’s mad. And then what?

DA-C: Everyone’s mad, and eventually, actually this is a closed little loop because all you then do is say, “Okay, well, we’re going to take a shortcut,” and you’ve just added to your content debt. So this stage is actually one of the most dangerous of the parts of it because all you end up trying to do without actually solving the problem is just add to the debt. “Let’s take a shortcut here, let’s do this.”

The next stage is now the blame stage. “It’s the tools. It’s the process. It’s the people.” These here and then you get calls of technical writers or, “Well, we’re going to put you into this department and we’ll get this person to rule you with this new agile process,” or, “We’ll get you to be doing it in this way.” The finger-pointing begins. Tech teams will blame the authors. Authors will blame the CMS. Leadership questions the ROI of the entire content operations team. This is often where organizations see that we’ve got to start making a change. They’re either going to double down and continue building that content debt or they start looking for a scalable solution.

SO: Right. And this is the point at which people look at it and say, “Why can’t we just use AI to fix all of this?”

DA-C: Yep, and we all know what happens when you point AI at garbage in. We’ve got the saying, and this saying has been true from the beginning of computing, garbage in, garbage out, GIGO.

SO: Time.

DA-C: Yeah. I changed that to computing.

SO: Yeah. It’s really interesting though because the blame that goes around, I’ve talked to a lot of executives who, and we’re right back to anger too, it is sort of like, “We’ve never had to invest in this before. Why are you telling us that this organization, this group, this tech writers, content ops,” whatever you want to call it, “that they are going to need enterprise tools just like everybody else?” And they are just halfway astounded and halfway offended that these worker bees that were running around doing their thing…

DA-C: Glorified secretaries.

SO: Yeah, that whole thing, like, “How dare they?” And it can be helpful, sometimes it is and sometimes it isn’t, to say, “Well, you’ve invested in tools for your developers. You wouldn’t dream of writing software without source control, I assume,” although let’s not go down the rabbit hole of vibe coding.

DA-C: Let’s not go down that one.

SO: And the fact that there are already people with the job title of vibe coding remediation specialist.

DA-C: Nice.

SO: Yeah. So that’s going to be a growth industry.

DA-C: That’s what, if you can get it.

SO: But this blame thing is we are saying, “This is an asset. You need to invest in it. You need to manage it. You need to depreciate it just like anything else. And if you don’t invest properly, you’re going to have some big problems.” And to your-

DA-C: A lot of that-

SO: Yeah, they don’t want to do it. They’re horrified.

DA-C: Yeah. A lot of that comes to looking at docs departments as cost centers. They’re costing us money. We’re paying all these people to produce this stuff that people don’t read. The users don’t want to. But if you look at it properly, deeply, the documentation department can be classed as a revenue generator. What are your sales teams pointing prospects at? They’re pointing at docs. Where are they getting the information about how things work? They’re pointing at the docs. What are you using? Especially if you’re having people looking through trying to find a solution?

I know I do this. I go and look at the user manuals. And first thing that I want to see in there that is properly written, if I see something that does not describe the gadget or whatever I’m trying to buy properly, then I’m like, “Well, if you’ve taken shortcuts there, you’ve probably done the same with the actual thing that I’m going to buy.” So I’m going to walk away.

Reducing costs for online centers. If your customers can find the information very quickly that describes the exact problem that they’re trying to solve, then you’ve got fewer calls to your online help center. And then while escalating onto the next person, because the level, I don’t know how this goes, level three, two, one, let’s say the level three is the lowest level, if that person can not find the information that is true, clear, one source of truth, then they’re going to escalate it onto that person who you’re paying a lot more, is at that level two, that person can’t find it, moved on. So it’s basically costing you a lot of money not to have good documentation. It’s a revenue generator.

SO: So my experience has been that the blame phase is perhaps the longest of all the phases.

DA-C: Yeah.

SO: And some organizations just get stuck there forever and they blame different people every year. I’ve also, I’m sure you’ve seen this as well, we were talking about reorganizing. “Well, okay, the tech writers are all in one group. Let’s burst them out and put them all on the product team.”

DA-C: Yes.

SO: “So you go on product team A and you go on product team B and you go on product team C.” And I talk to people about this and they say, “This is terrible and I don’t want to do it.” I’m like, “It’s fine, just wait two years.”

DA-C: Yeah.

SO: Because it won’t work, and then they’ll put them all back together. Ultimately, I’m not sure it matters whether they’re together or apart because we fall into this sort of weird intermediate thing. What matters is that somebody somewhere understands the value, to your point, and isn’t making the investment. I don’t care if you do that in a single group or in a cross-functional matrix, blah, blah, but here we are. All right. So eventually, hopefully, we exit blame.

DA-C: And then we move into acceptance.

SO: Do we?

DA-C: “Okay, we need a better way to manage that.” And this is like when people start contacting you, Sarah, it’s like, “I’ve heard there’s a better way to manage this. Somebody’s talked to me about there’s something called the component content management system or the structured content,” and all of this.

So teams start to acknowledge, one, that they’ve got debt and that debt is growing. Then they start auditing that content and then really seeing that, “Oh, well, yes, things are really going bad. We’ve got 15 versions of this same document living in different spaces in different countries. The translations always cost us a bomb.” So leadership then starts budgeting for a transformation.

This is where they then start doing their research to find structured content, competent reuse, they enter the conversation. If they look at their software departments, software departments reuse stuff. You’ve got libraries of objects. Variables is the simplest form of that reuse. And they’ve been using this for years. And so, “Well, why aren’t we doing this? Oh, there’s DITA, there’s metadata. We can govern our content better. We can collaborate using this tool.” So there is a better way to do this. And then we know what to do.

SO: I feel like a lot of times the people that reach out to us are in stage four, they’ve reached acceptance, but their management is still back in anger and bargaining and denial and all the rest of that.

DA-C: They’re still blaming and trying to find a reason.

SO: Yeah, blaming and all of it, just, “How dare you?” All right, so we acknowledge that we have a problem, which I think is actually the first step in a different step process, but okay.

DA-C: Yeah.

SO: And then what?

DA-C: And then there’s action. Let’s start fixing this before it gets totally out of control, before it gets worse. Then they start investing in structured content authoring platforms like Tridion Docs, I work for RWS, I’ve got to mention it. They start speaking with experts, doing that research, listening to their documentation team leaders, speaking with content strategists to define what the content model is, first of all, and then where can we optimize efficiency by having a reuse strategy? A reuse without a strategy is just asking for trouble. You’re basically going to end up duplicating content.

And then you’ve got to govern how that is used. What rules have you got in place and what ways have you got to implement those rules? The old job of having an editor used to work in the good old days where you’d print something off and somebody would sign it off and so on and so forth. Now, we’re having to deliver content really quickly and we’re using a lot of technology to do that. And so, well, you need to use technology to govern how that content is being created.

Then your content becomes an asset. It’s no longer a liability. This is where that transformation happens, and then you start paying down your content debt. You’re able to scale the content that you’re creating a lot faster without raising the number of the headcount, without having to hire more people. And if you want to then really expand, let’s say, because you’ve got this really great operation now and you’re able to create that content that takes hours and not weeks, then you’re able to expand your market. You’re able to say, “Okay, well, now we’re going to tackle the Brazilian market. Now, we can move into China because they’ve got different regulations.”

Again, I speak a lot on the regulatory side of things. That’s where I passed most of my time as a technical writer. Having different content for different regulatory regimes and so on is just such a headache where you don’t have something that is helping you with that structure, applying structure to that content, applying rules to that content, making sure that your workflows are carried out in the way that you set it out six months ago and people have changed and so on and they’re not doing their own thing again. If your organization is stuck at stages one to three, as I just mentioned it, it’s basically time to move.

SO: Yeah, I think it’s interesting thinking about this in the larger context of when we talk about writers, the act of writing, right?

DA-C: Yes.

SO: Culturally, that word or that process is really loaded with this idea of a single human in an attic somewhere writing the great American or French or British novel, writing a great piece of literature or creating a piece of art on their own, by themselves, in solitude. And of course, we know that technical writing-

DA-C: Starting at A and going all the way to Z.

SO: And we know that technical writing is not that at all, but it does really feel as though when we describe what it means to be a writer or a content creator in a structured content environment, it is just the 180 degree opposite of what it means to be a writer. It’s not the same thing. You are a creator of these little components. They all get put together. We need consistent voice and tone. You have to kind of subordinate your own voice and your own style to the corporate style and to the regulatory and to all the rest of it. And so it’s just this sort of… I think we maybe sometimes underestimate the level of cultural push and pull that there is between what it is to be a writer and what it is to be a technical writer.

DA-C: Yes.

SO: Or a technical communicator or content creator, whatever you want to call that role. Okay, so we’ve talked about a lot of this and then we’ve not talked a lot about AI, but a big chunk of this is that when you move into an environment where you are using AI for end users to access your content, so they go through a chatbot to get to the content or they’re consulting ChatGPT or something like that, and asking, “Tell me about X.” All of the things that you’re describing in terms of content debt play into the AI not performing, the content not getting in there, not being delivered. So what does it look like? What are some of the specifics of good source content, of paying down the debt and moving into this environment where the content is getting better? What does that mean? What do I actually have to do? We’ve talked about tools.

DA-C: Yeah. So first, you’ve got to understand how AI accesses content and how large language models get trained. AI interprets patterns as meaning. If your content deviates from pattern predictability, then you’re going to get what we call hallucinations. And so asking the ChatGPT without having it plugged as an enterprise AI thing where you’ve really trained it on your own content, you get all sorts of hallucinations. Basically, they’ve taken two PDFs that have similar information, but two different conclusions. And so you’re looking for a conclusion in document A, but ChatGPT has given you the one in B. And it’s mixed and matched those because it does not know how one bit of information relates to the other.

So good source content needs to be accurate. Your facts are correct. They reflect the current state of the product or subject. It needs to be kept up to date. You need to have single copies of it, that’s what we talk about, a single source of truth. You can not have two sources of truth. It’s either black or it’s white. There are no gray zones with AI, it will hallucinate. You’ve got to have that consistency in style and tone.

How do you get that? Well, you’ve got the brand and the way we speak. In French, you would say, “Do you vouvoie or do you tutoie?” Do use the formal voice, formal tone, or do you speak like you’re speaking with your friends? How do you enforce some of that? Well, you can use controlled terminology. These are special terms that you’ve defined, a special voice. But the gold part of it is having that structured formatting and presentation. There’s always a logical structure and sequence to the way that you present that information. Your heading, subheading, steps, lists, are always displayed in the same way. You’ve defined an information architecture to then give that pattern. And the way AI then understands or creates relationships with those patterns is from the metadata that you’re adding onto it.

And so good source content is accurate, up to date, consistent in style and tone, uses control terminology, has structure in formatting. Forget the presentation because that you put on the end of things, in that what it looks like, how pretty it is. But the presentation in terms of I always start with a short description and then I follow up with the required tools. And then I describe any prerequisites, and that is the way every one of my writers are contributing towards this central repository of knowledge, this single repository of knowledge.

And you can do that as well if you’ve got a great CCMS by using templates, building templates into that CCMS so that it guides the author. And the author no longer has to think about, “Oh, how is this going to look? Should I be coloring my tables green, red, blue? Should they be this wide?” They’re basically filling in a template form. And some of the standards that we’ve developed like DITA allow you to do this, allow you to have a particular pattern for creating that information and the ability to put it into a template which is managed by your CCMS.

SO: Yeah, and that’s the roadmap, right? We talk about how as a human, if I’m looking at content and I notice that it’s formatted differently, like, “Oh, they bolded this word here but not there,” and I start thinking, “Well, was that meaningful?”

DA-C: Yeah.

SO: And at some point, I decide, “No, it was just sloppy and somebody screwed up and didn’t bold the thing.” But AI will infer meaning from pattern deviations.

DA-C: Yeah.

SO: And so the more consistent the information is in all the levels that you’ve described, the more likely it is that it will process it correctly and give you the right outcome. Okay, so that seems like maybe the place that we need to wrap this up and say, folks, you have content debt. Dipo is giving you a handy roadmap for how to understand your content debt and understand the process of coming to terms with your content debt, and then figuring out how and where to move forward. So any closing thoughts on that before we say good luck to everybody?

DA-C: Basically before, or, I mean, most enterprises today have already jumped on the AI bandwagon. They’re already trying to put it in, but at the same time, start taking a look at your content to ensure that it is structured and has semantic meaning to it. Because the day that you then start training your large language model on that, if you’ve not built those relationships into it, it’s like teaching a kid bad habits. They’re going to just continue doing it. It’s basically train your AI right the first time by having content that is structured and semantic, and you’ll find your AI outcomes are a lot more successful.

SO: So I’m hearing that AI is basically a toddler? Okay. Well, I think we’ll leave it there. Dipo, thanks, it’s great to see you as always.

DA-C: Thanks for having me.

SO: Everybody, thank you for joining us, and we’ll see you on the next one.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Want more content ops insights? Download our book, Content Transformation.

The post The five stages of content debt appeared first on Scriptorium.

The most common workflow shift in translation is to start with AI output, then have a human being review some or all of that output. It’s rare that enterprise-level companies want a fully human translation. However, one of the concerns that a lot of enterprises have about using AI is security and confidentiality. We have some customers where it’s written in our contract that we must not use AI as part of the translation process. Now, that could be for specific content types only, but they don’t want to risk personal data being leaked. In general, though, the default service now for what I’d call regular common translation is post editing or human review of AI content. The biggest change is that’s really become the norm.

—Steve Maule, VP of Global Sales at Acclaro

Related links:

• Scriptorium: AI in localization: What could possibly go wrong?
• Scriptorium: Localization strategy: Your key to global markets
• Acclaro: Checklist | Get Your Global Content Ready for Fast AI Scaling
• Acclaro: How a modular approach to AI can help you scale faster and control localization costs
• Acclaro: How, when, and why to use AI for global content
• Acclaro: AI in localization for 2025

LinkedIn:

• Steve Maule
• Bill Swallow

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

SO: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Bill Swallow: Hi, I’m Bill Swallow, and today I have with me Steve Maule from Acclaro. In this episode, we’ll talk about the benefits and pitfalls of AI in localization. Welcome, Steve.

Steve Maule: Thanks, Bill. Pleasure to be here. Thanks for inviting me.

BS: Absolutely. Can you tell us a little bit about yourself and your work with Acclaro?

SM: Yeah, sure, sure. So I’m Steve Maule, currently the VP of Global Sales at Acclaro, and Acclaro is a fast-growing language services provider. So I’m based in Manchester in the UK, in the northwest of England, and I’ve been now in this industry, and I say this industry, the language industry, the localization industry for about 16 years, always in various sales, business development, or leadership roles.

So like I say, we’re a language services provider. And I suppose the way we try and talk about ourselves is we try and be that trusted partner to some of the world’s biggest brands and the world’s fastest growing global companies. And we see it Bill as our mission to harness that powerful combination of human expertise with cutting edge technology, whether it be AI or other technology. And the mission is to put brands in the heads, hearts, and hands of people everywhere.

BS: Actually, that’s a good lead in because my first question to you is going to be where do you see AI and localization, especially with a focus of being kind of the trusted partner for human-to-human communication?

SM: My first answer to that would be it’s no longer the future. AI is the now. And I think whatever role people play in our industry, whether you’re like Acclaro, you’re a language services provider, offering services to those global brands, whether you are a technology provider, whether you run localization, localized content in an enterprise, or even if you’re what I’d call an individual contributor, maybe you’re a linguist or a language professional. I think AI is already changed what you do and how you go about your business. And I think that’s only going to continue and to develop. So I actually think we’re going to stop talking at some stage relatively soon about AI. It’s just going to be all pervasive and all invasive.

BS: It’ll be the norm. Yeah.

SM: Absolutely. We don’t talk any more about the internet in many, many industries, and we won’t talk about AI. It’ll just become the norm. And localization, I don’t think is unique in that respect. But I do think that if you think about the genesis of large language models and where they came from, I think localization is probably one of the primary and one of the first use cases for generative AI and for LLMs.

BS: Right. The industry started out decades ago with machine translation, which was really born out of pattern matching, and it’s just grown over time.

SM: Absolutely. And I remember when I joined the industry, what did I say? So 2009, it would’ve been when I joined the industry. And I had friends asking me, what do you mean people pay you for translation and pay for language services? I’ve just got this new thing on my phone, it’s called Google Translate. Why are we paying any companies for translation? So you’re absolutely right, and I think obviously machine translation had been around for decades before I joined the industry. So yeah, I think that question has come into focus a lot more with every sort of, I was going to say, every year that passes, quite honestly, it’s every three months.

BS: If that.

SM: Exactly, yeah. Why do companies like Acclaro still exist? And I think there are probably a lot of people in the industry who actually, if you think about the boom in Gen I over the last two, two and a half years, there’s a lot of people who see it as a very real existential threat. But more and more what I’m seeing amongst our client base and our competitors and other actors in the industry, the tech companies, is that there’s a lot more people who are seeing it as an opportunity actually for the language industry and for the localization industry.

BS: So about those opportunities, what are you seeing there?

SM: I think one of the biggest things, it doesn’t matter what role you play, whether you’re an individual linguist or whether you’re a company like ours, I think there’s a shift in roles and the traditional, I suppose most of what I dealt with 16 years ago was a human being doing translation, another human being doing some editing. There were obviously computers and tools involved, but it was a very human-led process. I think we’re seeing now a lot of those roles changing. Translators are becoming language strategists; they’re becoming quality guardians. Project managers are becoming sort of almost like solutions architects or data owners. So I think that there’s a real change.

And personally, I don’t think, and I guess this is what this podcast is all about. I don’t see the roles of a few things going away, but I do see those roles changing and developing. And in some cases, I think it’s going to be for the better. And I think what we’re seeing is a lot of, because there’s all this kind of doubt and uncertainty and sort of threat, people are wanting to be shown the way, and people are wanting companies like our company and other companies like it to sort of lead the way in terms of how people who manage localized content can kind of implement AI.

BS: Yeah. We’re seeing something similar in the content space as well. I know there was a big fear, certainly a couple of years ago, or even last year, that, oh, AI is going to take all the writing jobs because everyone saw what ChatGPT could do until they really started peeling back the layers and go, well, this is great. It spit out a bunch of words, it sounds great, but it really doesn’t say anything. It just kind of glosses over a lot of information and kind of presents you with the summary. But what we’re seeing now is that a lot of people, at least on the writing side, yeah, they’re using AI as a tool to automate away a lot of the mechanical bits of the work so that the writers can focus on quality.

SM: We’re seeing exactly the same thing. I had a customer say to me she wants AI to do the dishes while she concentrates on writing the poetry. So it is the mundane stuff, the stuff that has to be done, but it’s not that exciting. It’s mundane, it’s repetitive. Those have always been the tasks that have been first in line to be automated, first in line to be removed, first in line, to be improved. And I think that’s what we’re seeing with AI. 

BS: So on the plus side, you have AI potentially doing the dishes for you, while you’re writing poetry or learning to play the piano, what are some of the pitfalls that you’re seeing with regard to AI and translation?

SM: I think there’s a few, and I think it depends on whereabouts AI is used, Bill, in the workflow. I think the very active translation itself is a very, very common use now of AI. But I think there’s some kind of a, I’m going to call them translation adjacent tasks as well, like we’ve mentioned with the entire workflow. So I think the answer would depend on that. But I think one of the biggest pitfalls of AI, and it was the same again, 2009 when I joined the industry and friends of mine had this new thing in their pocket called Google Translate. One of the pitfalls was, well, it’s not always right. It’s not always accurate.

And even though the technology has come on leaps and bounds since then, and you had neural NT before large language models, it still isn’t always accurate. And I think you mentioned it before, it does almost always sound smooth and fluid and almost like it sounds like it’s very polished, and it sounds like it should be, right? I’m thinking, “I’m in sales myself. So it could be a metaphor for a salesperson, couldn’t it? Not always, right? But always sounds confident. But I think there’s a danger where in any type of translation, sometimes accuracy doesn’t actually matter. I mean, if the type of content we’re talking about is, I don’t know, some frequently asked questions on how I can get my speaker to work as a customer, you’re going to be very patient if it’s not perfect English or if you speaking to the language, if it’s not perfect, as long as it gets you to get your speaker to work, you’re not really going to mind. But there’s other content where accuracy is absolutely crucial. In some industries could even be life or death.

But I go back to my first year or two in the industry, and we had a customer that made really good digital cameras, and they had a huge problem because their camera was water resistant, and one of their previous translators had translated it as waterproof. And of course, the customer takes it scuba diving or whatever they were doing with the digital camera, and the camera stops working because it wasn’t waterproof, it was just water resistant.

So sometimes what would be a very kind of seemingly innocuous choice of term, it wasn’t life or death, but obviously it was the difference between a thousand-dollar camera working or not. So I think accuracy is really critical. And even though it sounds confident, it’s not always accurate. And I think that’s one of the biggest pitfalls. Language is subjective, and some things are sort of black and white or wrong, but other things are a lot more nuanced. And what we see is, especially because a lot of the large language models are trained in English and with English data, they don’t necessarily always get the cultural or the sort of linguistic specific nuances of different markets.

We’ve seen some examples, it could be any markets, but specifically Arabic requires careful handling because of the way certain language comes across. Japanese, the politeness Japanese and what do they say, 50 words for snow. Some things aren’t sort of black or white in terms of whether they’re right or wrong. So it’s very, very gray areas in language. And again, however confident the output sounds, sometimes it’s not always culturally balanced or culturally sensitive.

BS: You don’t want it to imply anything or have anyone kind of just take away the wrong message because it was unclear or whatnot.

SM: Absolutely, absolutely. And especially when you’re thinking of branded content. I mean, some of the companies we work with and some of the companies, I’m sure that people listen to the podcast, they’d spend millions on protecting building, first of all, but also protecting their brand in different markets and the wrong choice of language, the wrong translation can put that at risk.

BS: Yeah. With branding, I assume that there’s a tone shift that you need to watch for. There’s certainly what you can and can’t say in certain contexts regarding the brand.

SM: Well, I think with AI, when you are using GenAI to translate, the other thing is it’s because I think you mentioned before, the technology it is a pattern-based technology. The content could be quite inherently repetitive. And again, whilst they’ll be confident, whilst they’ll be polished, it doesn’t always take into account the creativity or the emotion. And it’s less and less now we’re seeing AI sort of properly trained on a specific brand’s content. The models are more, they’re too big really to be trained just on a brand-specific content. So sometimes the messaging can appear quite generic or not really in step with the identity that a brand wants to portray. I think most of our clients would be in agreement when it comes to brand. It can’t be left to the machines alone.

BS: And I would think that any use of AI or even machine translation in something with regard to branding, where you want to own that messaging and really tailor that messaging, you really don’t want to have other influences coming in from the wild. So I would imagine that with an AI model that’s trained to work in that environment, you really don’t want it to know that there’s an outside internet, there’s an outside world that it can harvest information from because you might be getting language from your competitors or what have you.

SM: Yeah, absolutely. Absolutely. Yeah, you’re sort of getting it from too many sources where it kind of needs to be beyond brand really. I think there’s other things as well that we see. I mean, there’s still quite common cases of bias and stereotyping because like you say, it, taking content if you like, or data from all sorts of sources. And if there’s bias in there, there’s misgendered language, especially with some target languages. I mean, you’ve got, in English, it’s kind of fine, really, but in Spanish and French and German, you’ve got to choose a gender for every noun, every adjective, in order to be accurate.

BS: Otherwise, it’s wrong.

SM: Yeah, absolutely. Yeah, absolutely. And it compounds because the models are built on such scale, it compounds over time. So again, without that sort of active monitoring and without that human oversight, what might be a problem today will compound, and it’d be even worse tomorrow in the months ahead.

BS: How about the way in which the translation process works? Have you seen AI really shifting a lot of those workflows?

SM: So the short answer is yes. So by far, the most common workflow, if you’re looking at translation by far, the most common workflow with our customers now is to start with AI output. And to have a human being review some or all of that output. It is very, very rare. Now, when we are working with the enterprise-level companies, it’s very, very rare that they’d want, well, actually I might hold that thought, but it’s very rare that they’d want, for most content, they would want a fully human translation. Except one of the pitfalls that we have seen is, or one of the concerns if you like, that a lot of enterprises have about using AI is security and confidentiality.

And in fact, we have some customers where it’s written in our contract that we must not use AI as part of the translation process. Now, that could be for some specific content types only, and a lot of the time it’s a factor of, if you like, the attitude to risk or the attitude to confidentiality that that particular customer might have. But a lot of people are still very, very paranoid about that. They don’t want to be risking personal data being effectively leaked or being used to train and being cross pollinated, like your previous example. But in general, the sort of default service now for what I’d call regular common translation is post editing or human review of AI content. So that, that’s probably the biggest change is that’s now really become the norm.

BS: Okay. We talked a lot about the pitfalls here, so let’s talk about some benefits that you get at of using AI and localization.

SM: Well, I think the first thing is scale. I think it just allows you to do so much more because it almost, well, it doesn’t remove, but it significantly reduces those budget and time constraints that the traditional translation process used to have. Yeah, you can translate content really, really fast, very, very affordably, and it’s huge volumes that you just couldn’t consider if that technology wasn’t there.

So you could argue you’ve always been able to do that since machine translation was available. But I think large language models, they do bring more fluency. They do bring more sort of contextual understanding than those sort of pattern-based machine translation models. They can, even though we’ve talked about how some of the challenges around nuance and tone, they can improve style and tone. So we’ve seen a lot of benefits and a good opportunity really in sort of pairing the two technologies, neural machine translation, large language models, and again, you can’t get away when they’re guided by the human expertise.

They can offer a really good balance of scale, but also quality that you weren’t able to achieve before. And this is what I would say to people who are sort of worried about the existential threat of, oh my gosh, I’m a translator, so AI is taking my job. Absolutely, it’s probably changing your job. But we see AI translation not replace human translation, but replacing no translation. So that mountain of content, the majority of content actually that was never translated before because of time and budget constraints can now be translated to a certain level of quality. And so we see the overall volume of content localize, exploding, and ideally a similar level of human involvement or even more, in some cases, human involvement than before, but as a proportion of the overall, it’s a lot less, if that makes sense.

BS: Yeah. So what about multimedia? So audio and video, I know those have been traditionally a more difficult format to handle in localization, particularly when you may need to change the visuals along the way.

SM: If you ask any project manager in our company, the most expensive, the most time-consuming type projects traditionally to deliver, and you’re absolutely right, you make a mistake with terminology and you’re doing a professional voiceover and the studio’s booked and the actor’s booked and you want to change three or four words or three or four terms. Okay, that’s fine. Rebook the studio, rebook the actor. Yeah. I mean, it was traditionally, and I say traditionally, we’re talking only three or four years ago, one of the most expensive forms of content to translate.

So I think what we see is it’s been revolutionized by AI, video localization, audio localization, and this is a great example of actually where it’s replacing no translation. I mean, we had customers who just wouldn’t, we don’t want to dub that video. We don’t want to localize their audio, we just can’t afford it. We haven’t got the time. And now with synthesized voice synthesized videos, the quality is sort of very natural, very expressive, and you can produce training videos and product demos and all those kind of marketing assets in various markets that used to cost you lots and lots of money for 10 times less the cost, and probably more than 10 times less the speed.

BS: Nice. Yeah. I know that one of the things that we saw, particularly with using machine translation is that there was a pretty good check for accuracy built into a lot of those systems, but they weren’t quite a hundred percent. How does AI compare with that because it does understand language a bit more. So with regard to QA, how is that being leveraged?

SM: Well, they can understand. It’s not just about accuracy and grammatical correctness and spelling errors and that sort of thing has always been around, like you say, with machine translation. But the LLMs now, they can evaluate that sort of fluency terminology, use adherence to brand guidelines, style guidelines, and they can do that. So what we see is that whereas before LLMs came around and you had neural machine translation, pretty much most of the machine, unless it was very low value output, and unless it was very invisible or less visible content, let’s say if it was something that the clients cared about, they would want a human review of every single segment or every single sentence effectively. Whereas now, LLMs can help you sort of hone in and identify that percentage of the content that might need looking at by a human. And actually, I mean, there’s no real pattern, but if an LLM as a first pass can look at a large volume of content and say, actually 70% of that is absolutely fine, it matches the instructions that we’ve given it.

Not only is it accurate, but also it adheres to fluency and terminology and so on. Why don’t you human beings focus on this 30%? I mean, that’s a huge benefit to a lot of companies, saves a lot of time, saves a lot of costs, and just again, allows them to localize a lot more of that content than they were ever able to do before. So it’s great as a first pass before an extra layer if you like, a technology-dead layer before any human involvement and focusing the humans on the work that matters and the work that’s going to have the most impact.

BS: Nice. So if someone is looking to adopt AI within their localization efforts, what are the first steps for building AI into a strategy that you would recommend?

SM: Just call me. No, I’m kidding. I think it is any new process bill or any new technology, I think, and it sounds kind of common sense, but I think when deciding on any new strategy, it’s kind of be clear about why you’re doing it. You asked earlier on how AI is changing the localization industry. I think one huge thing I see, I speak to enterprise buyers of localization services every day. That’s my job. That’s what me and my team do. And one of the things that they tell me is that all of a sudden the C-suite know who they are.

All of a sudden, the guys with the money, the people with the money, they know they exist. And oh, we’ve got a localization department because as we said, GenAI, one of the earliest adopters, one of the earliest use cases for this was localization and was translation. So now there’s a lot of pressure from people who previously didn’t even know you existed or sort of maybe just saw you as a cost of doing business. Now they’re putting pressure on you to use AI. How are you using GenAI in your workflow? What can we as a business learn from it? Where can we save costs? Where can we increase volume? How can we use it as a revenue driver? Those sort of things. So that being said, that’s a big opportunity, but where we see it not go right or where we see it go more wrong more often than not is where people are doing it just because of that pressure and they think, oh, I have to do it because I’m getting asked to do it. I’m getting asked to experiment.

Again, it sounds really obvious, but they don’t really know what they’re looking for. Are they looking for time to be saved? Are they looking for costs to be removed? Are they looking to increase efficiencies with in their overall workflow? So I think it’s like anything, isn’t it? Unless you know how you’re going to measure success, you probably won’t be successful. So I think that’s the first tip I’d give people. Be clear about what it is you’re looking for AI in localization to achieve. And again, one of the pitfalls is we see lots of people wanting to experiment and it’s good, and you want to encourage that. I suppose as a chief exec or even with our clients, we’d love to see experimentation, but when you see lots of people doing lots of different things just because it looks cool and they just want to experiment, unless it’s joined up and unless it’s with a purpose, it doesn’t always work well.

So I think what we see when people do it well is they have that purpose. They have it documented actually, they have that sort of agreed, if you like, with they have that executive buy-in, this is why we’re doing it, and this is what we’re hoping to see, not just because it’s cool because it might save us X dollars or it might save us X amount of time. And I think what we see well is when people do that and then they kind of embrace those small iterative tests. One of our solutions architects was on a call with me with a customer, just advise them not to boil the ocean. And again, I know this isn’t specific to AI, but just let’s not do everything all at once. Lots of localization workflows. They have legacy technology, they have legacy connectors to other content repositories, and you can’t just rip it out without a lot of pain and start again.

So you’ve got to decide where you’re going to have that impact. Start small, very small tests, iterate frequently, get the feedback. That’s one of the key things. And then it just becomes any other implementation of technology or implementation of a workflow. One of the things we did at Acclaro is actually publish a checklist to help companies answer that exact same question, but when you read it, there’s not going to be much there about specific AI technologies and this type of LLM is better for this, and that type of LLM is better for that. It’s not prescriptive. It’s just designed as a guide to actually say, okay, well don’t get ahead of yourselves. Just follow a really sensible process, prove that it works, and then choose the next experiment.

BS: Yeah, get people thinking about it.

SM: Absolutely,

BS: We hear a lot from people that, oh, it came down from the C-suite that we have to incorporate AI into our workflows in 2025, in 2026. And yeah, I mean that’s all the directive is usually. Usually there’s no foresight coming down from above saying, this is what we’re envisioning you doing with AI. So it really does come down to the people who are managing these processes to take a step back and say, okay, here’s where things are working, here’s where we could make improvements. Here are some potential footholds that we can start building with AI and see where it goes. But yeah, I think for a lot of people, the answer of how do I use AI? I think it’s going to be different for every company out there. I mean, it might be similar, but I think it might be very different and very unique from company to company as to what they’re actually doing.

SM: That’s what we see. Yeah, that’s what we see. And again, some of those pitfalls we’ve talked about, some companies have a different approach to information security and confidentiality. Some companies are just risk averse. Some company’s content is, they should be more sensitive about it than other company’s content. Some company’s content, think finance, life sciences, medical devices, there’s real-world problems. Let’s say if it’s not accurate, whereas other company’s contents, yeah, okay, it might take you an extra 30 seconds to get that speaker to work or it might not. But I think, yeah, that’s no surprise. One of our customers said to me, AI is like tea. You need to infuse it. You can’t just dump it. You need to infuse it. You need to let it breathe. You need to let it kind of circulate. You got to decide the strength. You’ve got to decide where you get it from. You’ve got to decide what the human being making it has to do to make a great cup. And it’s just going to be different for every single person.

BS: True.

SM: We have five in our house and we have five different types of tea, whoever’s making that tea has to know what everyone’s preferences are. And I think it’s the same with AI. And it’s the same with a lot of technologies, isn’t it?

BS: It is. So when let’s say someone running a localization department, their CEO says, “We need to incorporate AI. Here’s your mandate. Go run, figure it out, implement it.” Do you have any advice around how to report, I guess the results, the findings, the progress back up?

SM: Yeah. My first advice would be, if I was in that situation, to say to that person, listen, we’ve been doing this for 10 years. We just never used to call it AI. We used to call it neural machine translation or machine translation. But my second bit of advice is you’ve actually got to do that because whilst the opportunity is there for localization managers to really drive and shape how AI is implemented, if they don’t do that, or if you pretend it’s something different than it is obvious, if you pretend it’s going away or if you pretend it’s a fad that people are going to forget about, what’ll happen is that somebody else will be asked to implement AI and you won’t be. And it’s quite interesting. We’re seeing a lot now of the persona, if you like, of the people that we’re working with in those enterprise localization teams is getting wider, it’s getting more multidisciplinary.

It’s very, very rare that you’d have any decent sized company, a localization manager making decisions about partners, vendors, technology by themselves. It would always be now with a keen eye from the technology team, the IT team, because everyone’s laser-focused on getting this right. So that’d be my second piece of advice. But I think if you define the results that you’re looking for and you document those and you’re able to capture those, again, it is not rocket science. It’s really just basic project management then. And then try and report on those regularly and quickly in a way that you’re able to iterate. An AI pilot shouldn’t be a six-month project with results at the end of six months. I mean, you should be able to know if you’ve chosen the right size of pilots, you should be able to know within days or weeks whether it’s likely to bring the benefits you thought it would do.

BS: Very true. So you see the return on using it or the lack of return on using it much quicker?

SM: Yeah, well absolutely. Yeah. Again, I think from my own personal experience, we’ve done a lot of helping and guiding clients with pilots, with experiments. It’s not all great results. And again, we haven’t manufactured anything to make it not great results so we stay in a job and people still use the human service. But we have seen really good results. I’m thinking of one, it’s quite a specific use case to do with translation memories, but the client was using GenAI to improve the fuzzy match, if you’re familiar with that term, build a translation memory match, the fuzzy match enhancer, and they found that it improved about 80% of the segments in I think five languages.

So again, if I look at that one, they didn’t pick every single language that they had. They only picked five, probably picked five where they could get some quick feedbacks of five more commonly spoken languages. And they were able to measure in their tool, the post editing time and the accuracy. And yeah, they found it improved 80%. I mean, 20% didn’t improve, so not 100% success, but they were able to provide real data to the powers that be to decide whether to extend it to their other language sets or their other content types.

BS: Nice. Well, I think we’re at a point where we can wrap up here. Any closing thoughts on AI and localization? Good, bad, ugly, just do it.

SM: I think the biggest thing for me is that AI is today. It’s not the future. It’s here. I’m in the UK, like I say, and multi-billion dollar announcement in investments, all specifically to do with AI from companies like NVIDIA, from Microsoft. And AI is the now. So I think you don’t have a choice whether to adopt it, whether to adapt to it being here. It’s just about how you choose to do it really. That’s become our role as a language service provider. As a sort of trusted partner of brands, our role has become to help guide and give our opinions. It’ll continue to change and we’ll have new use cases. And you ask me those same questions, I think Bill, in six months or 12 months, I might give you some different answers because we’ll have found new experiments and new use cases.

BS: And that’s fair. Well, Steve, thank you very much.

SM: Thank you, Bill. I enjoyed the conversation.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

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The post Balancing automation, accuracy, and authenticity: AI in localization appeared first on Scriptorium.

There’s probably a training company out there that’d be happy to teach me how to use WordPress. I didn’t have the time, I didn’t have the resources, nothing. So I just did it on my own. That’s one example of how you can use AI to replace some training. And when I don’t know how to do something these days, I go right to YouTube and look for a video to teach me how to do it. But given that, there are some industries where you can’t get away with that. Healthcare is an example—you’re not going to learn how to do brain surgery that someone could rely on with AI or through a YouTube video.

— Kevin Siegel

Related links:

• Is live, instructor-led training dying? (Kevin’s LinkedIn post)
• AI in the content lifecycle (white paper)
• Overview of structured learning content
• IconLogic

LinkedIn:

• Kevin Siegel
• Sarah O’Keefe

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

SO: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

SO: Hi, everyone, I’m Sarah O’Keefe. I’m here today with Kevin Siegel. Hey, Kevin.

KS: Hey, Sarah. Great to be here. Thanks for having me.

SO: Yeah, it’s great to see you. Kevin and I, for those of you that don’t know, go way back and have some epic stories about a conference in India that we went to together where we had some adventures in shopping and haggling and bartering in the middle of downtown Bangalore, as I recall.

KS: I can only tell you that if you want to go shopping in Bangalore, take Sarah. She’s far better at negotiating than I am. I’m absolutely horrible at it.

SO: And my advice is to take Alyssa Fox, who was the one that was really doing all the bartering.

KS: Really good. Yes, yes.

SO: So anyway, we are here today to talk about challenges in instructor-led training, and this came out of a LinkedIn post that Kevin put up a little while ago, which will include in the show notes. So Kevin, tell us a little bit about yourself and IconLogic, your company and what you do over there.

KS: So IconLogic, we’ve always considered ourselves to be a three-headed dragon, three-headed beast, where we do computer training, software training, so vendor-specific. We do e-learning development, and I write books for a living as well. So if you go to Amazon, you’ll find me well-represented there. Actually, one of the original micro-publishers on this new platform called Amazon with my very first book posted there called, “All This PageMaker, the Essentials.” Yeah, did I date myself for that reference? Which led to a book on QuarkXPress, which led to Microsoft Office books. But my bread and butter books on Amazon even today are books on Adobe Captivate, Articulate Storyline, and TechSmith Camtasia. I still keep those books updated. So publishing, training, and development. And the post you’re talking about, which got a lot of feedback, I really loved it, was about training and specifically what I see as the demise of our training portion of our business. And it’s pretty terrifying. I thought it was just us, but I spoke with other organizations similar to mine in training, and we’re not talking about a small fall-off of training. 15, 20% could be manageable. You’re talking 90% training fall off, which led me to think originally, “Is it me?” Because I hadn’t talked to the other training companies. “Is it us? I mean, we’re dinosaurs at this point. Is it the consumer? Is it the industry?”

But then I talked to a bunch of companies that are similar to mine and they’re all showing the same thing, 90% down. And just as an example of how horrifying that is, some of our classes, we’d expect a decent-sized class, 10, a large class, 15 to 18. Those were the glory days. Now we’re twos and threes, if anyone signs up at all. And what I saw as the demise of training for both training companies and trainers, if you’re a training company and you’re hiring a trainer, one or two people in the room isn’t going to pay the bills. Got to keep the lights on with your overhead running 50%, 60%, you know this as a business person, but you’ve got to have five or six minimum to pay those bills and pay your trainer any kind of a rate.

SO: So we’re talking specifically about live instructor-led, in-person or online?

KS: Both, but we went more virtual long before the pandemic. So we’ve been teaching more virtual than on-site for 30 years. Well, not virtual 30 years, virtual wasn’t really viable until about 20 years ago. So we’ve been teaching virtual for 20 years. The pandemic made it all the more important. But you would think that training would improve with the pandemic, it actually got even worse and it never recovered. So the pandemic was the genesis of that spiral down. AI has hastened the demise. But this is instructor-led training in both forms, virtual and on-site. I think even worse for on-site.

SO: So let’s start with pandemic. You’re already doing virtual classes, along comes COVID and lockdowns and everything goes virtual. And you would think you’d be well-positioned for that, in that you’re good to go. What happened with training during the pandemic era when that first hit?

KS: When that pandemic first hit, people panicked and went home and just hugged their families. They weren’t getting trained on anything. So it wasn’t a question of, were we well-positioned to offer training? Nobody wanted training, period. And this was, I think if you pull all training companies, well, there are certain markets where you need training no matter what. Healthcare as an example, they need training. Security, needed training. But for the day-to-day operations of a business, people went home and they didn’t work for a long time. They were just like, “The world is ending.” And then, oh, the world didn’t end. So now they’ve got to go back to work, but they didn’t go back to work for a long time. Eventually people got back to work. Now, are you on-site back to work or are you at home? That’s a whole nother thing to think about.

But just from a training perspective, when panic sets in, when the economy goes bad, training is one of the first things, you get rid of it. Go teach yourself. And the teaching yourself part is what has led to the further demise of training, because you realize I can teach myself on YouTube. At least I think I can. And I think when you start teaching yourself on your own and you think you can, it becomes, the training was good enough. So if you said, “Let’s focus on the pandemic.” That’s what started it, the downward spiral. But we even saw the downward spiral before the pandemic, and it was the vendors that started to offer the training that we were offering themselves.

SO: So instead of a third-party, certainly a third-party, mostly independent organization offering training on a specific software application, the vendors said, “We’re going to offer official training.”

KS: Correct. And it started with some of these vendors rolling out their training at conferences. And I attended these conferences as a speaker. I won’t name the software, I won’t name the vendor, but I would just tell you I would go there and I would say, “Well, what’s this certificate thing you’re running there?” It’s a certificate of participation. But as I saw people walking around, they would say, “I’m now certified.” And I go, “You’re not certified after a three-hour program. You now have some knowledge.” They thought they were certified and experts, but they wouldn’t know they weren’t qualified until told to do a job. And then they would find out, “I’m not qualified to do this job.” But that certificate course, which was just a couple of hours by this particular vendor, morphed into a full day certificate. They were charging now a lot of money for it, which morphed into a multi-day thing, which now has destroyed any opportunity for training that we have. And that’s when I started noticing a downward spiral. Tracking finances, it would be your investments going down, down, down, down this thing. It’s like a plane, head and nose down.

SO: And we’ve seen something similar. I mean, back in the day, and I do actually… So for those of you listening at home that are not in this generation, PageMaker was the sort of grandparent of InDesign. I am also familiar with PageMaker and I think my first work in computer stuff was in that space. So now we’ve all dated ourselves. But back in the day we did a decent amount of in-person training. We had a training classroom in one of our offices at one point.

Now, we were never as focused on it as you are and were, but we did a decent business of public-facing, scheduled two-day, three-day, “Come to our office and we’ll train you on the things.” And then over time, that kind of dropped off and we got away from doing training because it was so difficult. And this is longer ago than you’re talking about. So the pattern that you’re describing where instructor-led in-person training, a classroom training with everybody in the same room kind of got disrupted a while back. We made a decent living doing that for a long time and there was-

KS: Made a great living doing that. Oh, my God. That was the thing.

SO: But we got away from it, because it got harder and harder to put the right people in the right classes and get people to travel and come to us. So then there’s online training, which we kind of got rid of training. You sort of pivoted to online/ virtual. And then ultimately, the pandemic has made it such, from my point of view, that the vast majority of what we do in this space is custom. We’re doing a big implementation project. We do some custom training that might be in-person, on-site, but much more often it is online, live online instructor-led, but custom. Because all of the companies that we’re dealing with, even if people did return to office, very much they’re fragmented, right? It’s two people here and five people there, and four people there and one in every state. And so, bringing them all together into a classroom is not just bring the instructor in, but bring everybody in and it costs a fortune. And that’s before we get into the question of, can they get across the borders and can they travel?

There’s visa issues, there’s admin issues, people have caregiving responsibilities, they can’t travel. There’s a whole bunch of stuff that goes into actually relocating from point A to point B to do a class at point B. So fine. Okay. So along comes the pandemic that really pushes on the virtualization, right? The virtual stuff. And then you’re saying the vendors get into it and they are clawing back some of this revenue for themselves. They’re basically saying, “We’re going to do official vendor-approved stuff, which then makes it very difficult as a third-party, because you have to walk that line, and I’ve been there, you have to walk that line between, we are delivering training on this product which belongs to somebody else, and we can be maybe a little more forthright about the issues in the product because it’s not our product. So we’re just going to say, “Hey, there’s an issue over here. It doesn’t really work. Do it this other way.” Not toeing the official party line. Okay, so we have all of that going on and all of those challenges already. And now along comes AI. So what does AI do to this environment that you’re describing?

KS: It further destroys it. I’ll give you an example. My blog, Typepad, we received an email September 1st, 2025, and we’re recording this September 4th, 2025, okay? So three days ago I got an email saying, “Hello, we’re shutting down. Sorry.” And I’m like, “What? Yeah, you’ve got 30 days to get your stuff out of here.” Basically being kicked out of your apartment or your house. So I’m like, “All right, well, go to AI and I asked AI, what is the top blog software?” They said, “WordPress.” Love it or hate it, okay. So I went to WordPress. I had no idea how to use WordPress. I had no staff available to help me. So I had to get my stuff out of Typepad and on and on it went. I went to AI, ChatGPT specifically, and I said, “Teach me how to use WordPress,” and specifically how to get my crap out of TypePad. I say crap, my stuff out of TypePad. In a matter of what? Two days I had everything transferred over.

So, didn’t need training, otherwise I would’ve had to go to training to learn how to do that and I didn’t have to. So that’s an example of there’s probably a training company out there that’d be happy to teach me how to use WordPress. I didn’t have the time, I didn’t have the resources, nothing. So I just did it on my own. That’s one example of how you can use AI to replace the training. There’s other examples of training that is not just good enough, it’s fine. It’s good. It’s good. It’s not lacking. When I don’t know how to do something these days, I go right to YouTube and look for a video to teach me how to do it. So given that, some industries where you can’t get away with that. Healthcare as an example, you’re not going to learn how to do brain surgery that you could rely on with AI or video through YouTube.

SO: We hope.

KS: We hope. “Hey, relax. I know this is your first time, Sarah, I’m your surgeon. I watched a video yesterday, I feel pretty good about it as I grab that saw.” I don’t believe you’re going to be comfortable with that. So listen, it’s bad enough. And you mentioned the vendor that is now offering training. So vendor pullback, they want that for a revenue source. This particular vendor is using it as a revenue tool, but there’s also vendors out there that are actively stopping you from offering training classes, and on it goes.

SO: Yeah, I do want to talk about that one a little bit. I know nothing about the specifics of your situation, but this is a losing battle. Because you were just talking about YouTube, I was doing some research for a very, very, very large company that makes farm equipment and I went looking for their content. And they had content on their website, it was like type in your product name or product number and it would give you the official user manual, which was of course ugly and terrible. But I discovered that if you typed in something like, “How do I fix the breaks on my X, Y, Z product?” It would take you to YouTube. And it would take you to this YouTube channel that had a lot of subscribers and was in fact not at all the official company YouTube channel.

KS: It was a dude who was working on it?

SO: It was a dude in Warsaw, North Carolina, which is not the same as Warsaw, Poland. It is a tiny, tiny, tiny little place, mostly known for me as being halfway between where I am and the beach. It’s where we stop to get gas and summer peaches and corn from the farm stand and fried chicken on our way to the beach, because that’s the thing we do. That’s where Warsaw is. It has a population of, I don’t know, 3,000 maybe.

KS: Okay, yeah.

SO: I have no idea. But there’s some guy who works for the dealership there who’s making these videos explaining how to do maintenance on these, in this case tractors, and he has got the audience. Not the official website, which by the way does not have a YouTube channel that I’m aware of, or at least that I could find now. This was five, 10 years ago. It has been a while. But so, there’s all this third-party content out there and there’s this ecosystem of content because it’s digital. You can’t really control that unless, we were talking about this earlier, unless you’re doing something like nuclear weapons, intelligence work, or maybe brain surgery. You can probably control those things. That’s about it. Clearly things are changing and not for the better. If your revenue is built on instructor-led, whether in-person or online, it sounds as though things are changing and not for the better in that space specifically, unless we’re training on brain surgery, which most of us are not. So what’s the path forward?

KS: I’m thinking about it, actually.

SO: I am not signing up for you to do my brain surgery.

KS: I need someone to practice on. Sarah, let me know if you’re available.

SO: Oh, I’m so sorry, you’re breaking up. I can’t hear you. Okay, so what does the path forward look like? I mean, what does it mean to be inside this disruption and where do you go from here?

KS: Okay, so every training company that I have contacts in, they’re all down significantly. The ones that are surviving have government contracts.

SO: Mm-hmm.

KS: And that is to develop training in all of its guises, that primarily they’re seeing a call for virtual reality training. That’s really, really hot right now. But not the virtual reality training that you can create with the Captivates and the Storylines of the world. That’s too lowbrow. They’re talking about immersive, almost gamification, where you build a world. So if that’s your expertise, you can create training in that. That’s what people want. It looks like augmented reality and virtual reality.

I can’t see it. Maybe I’m of a certain age that I’m like, “I’m not putting goggles on to take my training.” But that is pretty popular with other generations. So you can’t ignore it, I think, embrace it. So government contracts, if you can get that, you’ll be okay in the training business. Several of my colleagues have actually done that. So that’s a leg up. The other is to embrace asynchronous training and put your materials out there that live now forever. So I ignored for years these providers of asynchronous training where you put your content there and they sell it for you. I’ve got five classes on Udemy now, and each of them sells pretty well.

Matter of fact, my Captivate Udemy is one of their bestsellers. That does not translate into offsetting the revenue lost from your training gigs when you were bringing in six, seven, $800 a person for a training class. Our prices were between $695 and $895 per person to take a public class, but it certainly does bring in some revenue. So if you have the ability to create the asynchronous training, the video training, and make it really, really good training, really impactful, then that’s going to help you stay in the game as long as you can. I also think embracing AI versus getting under the covers and just, “I don’t want to see it,” is not the way to go.

I now use AI as a tool. I don’t think it replaces me, I think that I have more to offer in guiding the course than AI, but it gives me a nice, “Get me started here.” Maybe you’ve got a little writer’s block, maybe just getting started. It’s a beautiful day out, I can’t get started. Have AI start, you’ve started up. But if you’re going to go that route and you have AI make suggestions, you better fact check it. And just as an example, I was just curious, I asked ChatGPT to create an exam for Articulate Storyline. That is a tool I know really well, I’ve written exams for Storyline and Captivate and Camtasia. I said, “Write an exam. I want to see what you come up with.” And some of the questions were actually worded better than what I had done. They were very similar questions. And I go, “I kind of like the way you, AI, did that.” Which was kind of a bummer. But I would say a good 30% of what I read, while it was well-written, was completely wrong.

SO: Yes, confidently wrong.

KS: Yes, it was confidently wrong. Asking questions, “When you do this on storyline, what is the correct thing? What do you do?” And Storyline doesn’t do that thing. They were talking about Rise as an example. I’m like, “You’ve gone and combined Rise with Storyline.” So if you’re going to use AI, it’s the way you ask the question, your prompts. So get some training on engineering your prompts and fact-checking what you get from those prompts. But I use AI every day in my writing to make sure I don’t have grammar issues. So I’ll tell AI, “Check this for clarity and grammar.” So it’s my words, but it now is saying, “Well, there’s a couple typos, I fix that. And a couple of dangling modifiers, I fix that.” So it makes me feel like I’m writing better. But do keep in mind, if you put your stuff into ChatGPT, it’s now part of this mass of stuff that other people are going to get access to.

So you can’t copyright anything that you put in AI. I wrote a book about copyright and training materials and things to think about, because we have a lot of people finding an image of a nice puppy on Google and using it in their training, and that puppy was copyrighted. So anything you do on AI, any photos that get created, any artwork, anything, any writing can’t be copyrighted because only a human can get a copyright. So that’s something to think about. If you have something really, really good, you really didn’t create that, so you can’t copyright it.

You’re going to have to adapt. You’re going to have to adapt or you’re going to fail in the training industry, again, unless it’s very specific niche markets, or as you mentioned, custom training. If you don’t adapt, you’re going to fail. And that adaptation is going to be, embrace AI asynchronous training to put your training out there, available 24 hours a day, seven days a week when you can’t do it. And that’ll offset getting these onesies and twosies in your class.

SO: And it removes the time-bound, I have to set aside these two hours or these four hours of this day to be in the classroom, whether virtual or not if it’s live. I do think that this idea that we’re going to see a split between things that go higher and higher end that people are willing to pay nearly anything for versus the low-end where the price is going… There’s going to be downward pressure on the price for all the low-end stuff, because the barrier to entry to producing asynchronous training is pretty minimal and it gets lower every single day because there’s so many people out there that can potentially do that.

KS: Anybody can hang out a shingle and say that they’re an expert. So I mean, it’s the credentials of the trainer too, I think. Who is the person that’s teaching this? Is it what we call it, Chuck with a truck? Is it Chuck with a truck? Or is it someone who has actually done this? I wouldn’t want to get trained on handling my content by someone who hadn’t done it. I’d want you to handle that, right? So a content strategy. “I mean, who came up with that strategy? Oh, Bob. Has Bob ever done it? No, but he feels good about it. No, I want to get a Sarah who’s done it for years and years and years.”

SO: Yeah, I mean that’s an interesting point though, because at the end of the day, if you commoditize/ productized training, you’re going to have a product as the asynchronous training that’s a package, and you get what you get. When it’s live with an instructor, you’re going to get that instructor on that day in that context. They’re feeling good, they’re feeling bad. The classroom dynamics are good or bad or weird. Every experience is going to be different. Whereas with async, it’s always going to be the same. I mean, barring internet connectivity or something, as the learner, you’re going to get a consistent experience. Now, it’s not going to be the best possible experience, right? Because the best possible experience is you’re in a group with some other people in a room with an amazing instructor.

KS: That is the best.

SO: That is the best.

KS: There’s good too-

SO: It costs the earth.

KS: Yeah, there’s good too, the asynchronous training, because it’s always the same, it’s going to be consistent. How many times have you read a live class and the attendees, one of the attendees just spoiled the sauce? And you’re reminding me now, a colleague of mine, they were doing their certification as a certified technical trainer, CTT, and back in those days, you actually had to record yourself teaching.

SO: Oh, yes, there was a VHS tape of me and kids. That is video, pre-digital video.

KS: That is correct. VHS tape. And I had to do the same thing, but I remember for this one colleague of mine, and the students in this classroom, fake classroom, were other trainers that were also getting the recording done. And I remember she was being recorded and it was over her shoulder looking at the students, because she had to show the students. And one of these students, she made a comment that she knew was correct, and the student shook her head, “Nope, nope. That’s not right. Nope.” And the trainer is now, “What are you doing? Why are you shaking your head no and contradicting one of us? How about just nod?” And so, at some point God had turned around where the students started shaking their head, but realize, “Oh my God, you’re defeating all of us in this room.”

So yes, that was to your point, that the training can vary wildly in a live class, whether it’s virtual or on-site, based on the attendees. Because listen, I’ve been teaching Captivate since it was called RoboDemo, so years and years and years and years, and no class has ever been the same. No two classes are the same and it’s all based on the dynamics of the students in my live class. And you get one person in there who is stuck, can’t move forward, file open is a mystery. Go to the file menu, choose open. How do you do that? Okay, mouse skills. All of that can either derail or can help your class. Funny moments, whatever they may be. But asynchronous training, if you do it right, is always consistently good. The problem is there’s no live interaction. So you can’t ask that instructor, “Well, what do you think about this? What do you think about that?”

So yeah, you made me laugh when you mentioned that, that the dynamics of your live class, you better be fast on your feet to be a live trainer. So I am not saying, if you’re going to teach virtually, you shouldn’t know how to do it. Because listen, I think you’ll agree, there is a vast difference between teaching a class live on-site versus live online, or God forbid, live online and live on-site, where you’re doing both at the same time. Or if you’re going to do blended learning, you’ve got to mix all three, you better know what you’re doing as a facilitator and a trainer to do that or you’ll fall flat on your feet.

You’ll hear all kinds of complaints that people who teach these live classes on-site that now incorporate virtual, and they ignore the virtual audience completely. So the virtual audience is not included in the training, they feel like they’re watching a recording. So you’ve got to know how to engage this audience. I’m actually really stunned, Sarah, that conferences still survive on-site. We mentioned a couple of times before we turned on this recording, why are those conferences live on-site? People are going there to network face-to-face. I guess that’s the big one, but not the content that you’re learning. That content could have been taught virtually.

SO: Yeah, I’ve had the position for a long time that the most important part of a conference is the hallway track, right? The conversations at lunch, in the hallway, and in the exhibit hall and everywhere else. There’s a couple that are doing online in addition to in-person, and typically the-

KS: ATD does that. Yeah, does a good job at that. Yeah.

SO: Yeah, LavaCon is doing that, they’re coming up. But yeah, they have an online track with a chat, a pretty lively chat, and then they also have the in-person version if you can get there in-person.

KS: Which is successful only if the facilitator addresses the online chat, if the facilitator addresses someone who’s virtual. Yeah.

SO: And fun fact, Phylise Banner has been running that for years and years and years and has done a fantastic job of exactly that, of making sure that the online people get into the conversation, even when there’s 200 people in the room and another couple hundred on the chat, and she’s making sure that they get their questions into the discussion. Okay, so that was cheerful, and that made me feel better, because the first half hour of this was super not encouraging. So I think I’m going to close us out there because I’m pretty sure we could go on forever, but let’s leave it there. Kevin, thank you for coming and for giving us the inside information on what’s happening in training land. And hopefully I’ll see you again somewhere in-person at a conference.

KS: Or virtual, with the camera is fine. So yeah, great working with you, Sarah. Thanks for having me.

SO: Great to see you. Bye. 

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Questions about this episode? Let’s talk!

The post From classrooms to clicks: the future of training content appeared first on Scriptorium.

The good thing about structured authoring is that you have a structure. If this is the concept that we need to talk about and discuss, here’s all the background information that goes with it. With that structure comes consistency, and with that consistency, you have more of your information and knowledge documented so that it can then be distributed and repackaged in different ways. If all you have is a PowerPoint, you can’t give somebody a PowerPoint in the middle of an oil change and say, “Here’s the bare minimum you need,” when I need to know, “Okay, what do I do if I’ve cross-threaded my oil drain bolt?” That’s probably not in the PowerPoint. That could be an instructor story that’s going to be told if you have a good instructor who’s been down that really rocky road, but again, a consistent structure is going to set you up so that you have robust base content.

— Mike Buoy

Related links:

• AEM Guides
• Overview of structured learning content
• CompTIA accelerates global content delivery with structured learning content (case study)
• Structured learning content that’s built to scale (webinar)

LinkedIn:

• Mike Buoy
• Sarah O’Keefe

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Sarah O’Keefe: Hi everyone, I’m Sarah O’Keefe. I’m here today with Mike Buoy. Hey, Mike.

Mike Buoy: Good morning, Sarah. How are you?

SO: I’m doing well, welcome. For those of you who don’t know, Mike Buoy is the Senior Solutions Consultant for AEM Guides at Adobe since the beginning of this year of 2025. And before that had a, we’ll say, long career in learning.

MB: Long is accurate, long is accurate. There may have been some gray hair grown along the way, in the about 20-plus years.

SO: There might have been. No video for us, no reason in particular. Mike, what else do we need to know about you before we get into today’s topic, which is the intersection of techcomm and learning?

MB: Oh gosh, so if I think just quickly about my career, my background’s in instructional design, consulting, instructor, all the things related to what you would consider a corporate L&D, moving into the software side of things into the learning content management space. And so what we call now component content management, we, when I say we, those are all the different organizations I’ve worked for throughout my career, have been focused in on how do you take content that is usually file-based and sitting in a SharePoint drive somewhere, and how do you bring it in, get it organized so it’s actually an asset as opposed to a bunch of files? And how do you take care of that? How do you maintain it? How do you get it out to the right people at the right time and the right combination, all the rights, all the right nows, that’s really the background of where I come from.

And that’s not just in learning content; at the end of the day, learning content is often the technical communication-type content with an experience wrapped around it. So it’s really a very fun retrospective when you look back on where both industries have been running in parallel and where they’re really starting to intersect now.

SO: Yeah, and I think that’s really the key here. When we start talking about learning content, structured authoring, techcomm, why is it that these things are running in parallel and sitting in different silos? What’s your take on that? Why haven’t they intersected more until maybe now we’re seeing some rumblings of maybe we should consider this, but until now it’s been straight up, we’re learning and your techcomm, or vice versa, and never the twain shall meet, so why?

MB: Yeah, and it’s interesting, when you look at most organizations, the two major silos that you’re seeing, one is going to be product. So whether it’s a software product, a hardware product, an insurance or financial product, whatever that product is, technical communication, what is it? How do you do it? What are all the standard operating procedures surrounding it? That all tends to fall under that product umbrella. And then you get to the other side of the other silo, and that’s the hey, we have customers, whether those customers are our customers or the internal customers, our own employees that we need to trade and bring up the speed on products and how to use them, or perhaps even partners that sit there. And so, typically, techcomm is living under the product umbrella, and L&D is either living under HR or customer success or customer service of some sort, depending on where they’re coming from.

Now in the learning space you, over the last probably decade or so, seeing where there’s a consolidation between internal and external L&D teams and having them get smarter about, what are we building, how are we building it, who are we delivering it to, and what are all those delivery channels? And then when I think about why are they running in parallel, well, they have different goals in mind, right? techcomm has to ship with the product and service and training ideally is doing that, but is often, there’s a little bit of a lag behind, “Okay, we ship the thing, how long is it before we start having all the educational frameworks around it to support the thing that was shipped?”

And so I think leadership-wise, very different philosophies, very different principles on that. techcomm, very much focused on the knowledge side of things. What is it? How do you do it? What are all the SOPs? And L&D leans more towards creating a learning experience around, “Okay, well here’s the knowledge, here’s the information, how do we create that arc going from I’m a complete novice to whatever the next level is?” Or even, I may be an expert and I need to learn how to apply this to get whatever new changes there are in my world and help me get knowledgeable and then skilled in that regard.

So I think those are kind the competing mindsets and philosophies as well as, I won’t say competing, but parallel business organization of why we don’t usually see those two. And if we think about from a workflow perspective, you have engineering or whoever’s building the product, handing over documentation of what they’re building to techcomm and techcomm is taking all of that and then building out their documentation, and then that documentation then gets handed to L&D for them to then say, “Well, how do we contextualize this and build all the best practices around it and recommendations and learning experiences?” So there is a little bit of a waterfall effect for how a product moves through the organization. I think those are the things that really contribute to it being siloed and running in parallel.

SO: Yeah. And I mean many, many organizations, the presence of engineering documentation or product design documentation is also a big question mark, but we’ll set that aside. And I think the key point here is that learning content, and you’ve said this twice already, learning content in general and delivery of learning content is about experience. What is the learning experience? How does the learner interact with this information and how do we bring them from, they don’t understand anything to they can capably do their job? The techcomm side of things is more of a point of need. You’re capable enough but you need some reference documentation or you need to know how to log into the system or various other things. But techcomm to your point, tends to be focused much less on experience and much more on efficiency. How do we get this out the door as fast as possible to ship it with the product? Because the product’s shipping and if you hold up the product because your documentation isn’t ready, very, very bad things will happen to you.

MB: Bad, bad, very bad.

SO: Not a good choice.

MB: It’s not a good look. It’s not a good look.

SO: Now, what’s interesting to me is, and this sort of ties into some of the conversations we have around pre-sales versus post-sales marketing versus techcomm kinds of things, as technical content has moved into a web experience, online environment, and all the rest of it, it has shifted more into pre-sales. People read technical documentation, they read that content to decide whether or not to buy, which means the experience matters more.

And conversely, the learning content has fractured into classroom learning and online instructor led and e-learning a bunch of things I’m not even going to get into, and so they have fractured into multi-channel. So they evolved from classroom into lots of different channels for learning where techcomm evolved from print into lots of different channels, but online and so the two are kind of converging where techcomm needs to be more interested in experience and learning content needs to be more interested in efficiency, which brings us then to, can we meet in the middle and what does it look like to apply some of the structured authoring principles to learning content? We’ve talked a lot about making techcomm better and improving the experience. So now let’s flip it around and talk about how do we bring learning content into structured authoring? Is that a sensible thing to do? I guess that’s the first question: is that a sensible thing to do?

MB: Yeah, and here’s the thing that I like to keep in mind when talking about structured authoring, the context for why in the world would we even consider it? And when I think of traditional L&D training courses, whether it’s butts in seats at an instructor-led training event, whether I’m actually in a physical classroom or I’m sitting virtually in a Zoom class for example, or it’s self-paced e-learning, so much great content is built and encapsulated in that experience and is not able to be extracted out.

My favorite example of talking about this is I’ve got a big truck sitting in my driveway, I need to change the oil on it, it’s time. If it’s the first time I’ve ever changed oil, absolutely, I want all the learning. I want the scaffolding. I want the best practices, how I’m going to set up my work environment, the types of tools. How I’m going to need to deal with all the fluids, what I need to purchase. I’m going to dive into all that. In the real world, university of YouTube, I’m going to go watch videos on this and there’s going to be some bad content, there’s going to be some gems, and I’m going to pay attention to the ones that are good.

Now as I go from a novice, I’m going to build that knowledge of how to do it, I’m going to apply that knowledge. I’m actually going to go do it, now I’m probably going to make a mess and make mistakes my first time through, but that’s also building experience. So I’m moving from novice to knowledgeable to building skills to as I do it more and more, I move into that realm of being experienced.

Now as you move further up that chain, you need less and less support to the point where I’m like, “Crap, which oil do I need to buy? What are the torque specs on my drain plug?” I really only need three or four data points to do the job now. So that’s where as I move from a novice to an expert, I need to be able to skim and find exactly what I need in the moment of need, the just enough information. And so I’ll take the oil changing experience and let’s take that to any product or service training your customers, the people who are consuming your content are going through the same thing.

So learning-wise, why structured? Once I get to the expert level of things, I am not going to log into the LMS and I’m not going to launch that e-learning course, and I’m not going to click next 5 to 10 to 20 times to get to the answer that has the specification tables of, here’s what I need and what I need to do in order to accomplish the task at hand. Everybody’s nodding their head. Every time I ask, “When was the last time you logged into the LMS to get an answer to a question?” The only time I’ve ever had somebody go, “Oh, me,” it was actually an LMS administrator.

So learning is great at creating that initial experience, but their content’s trapped. It is stuck inside that initial learning experience. So getting back to the question, why structured authoring? Well, if you move to a structured authoring where you’re taking your content and building it in chunks, yes, you can create that initial learning experience where you’ve assembled that very crafted, we’re taking you from novice, getting you the knowledge, giving you the opportunities to practice the skill in a safe environment and fail well and learn from that and get you to a place where you move from novice to skilled. And then over time, this is where a lot of the L&D in general, because their content’s trapped in that initial learning experience, they can’t easily extract that information out and provide the things people need to move from skilled to experienced and experienced to mastery.

So that’s where when I think about, “Well, what does techcomm do really well? Techcomm supports that, I’ve got enough skills to do the job and I need to reference the very specific information, or the SOP, I’m on step four, I forget what are the things I need to enter in to get through step four, I can hop over the documentation and find that. So techcomm has figured out the structured authoring part. You mentioned creating new varied experiences for getting to the technical communication. Multi-channel delivery, I want to hop on and hit my search or hit my AI chatbot and pull up the information and just get me just enough to get through the tasks that I’m doing.

Learning’s still often stuck, if we equate it to the tech communication side, they’re still stuck in the, “I’m hand building a Microsoft Word based 500 page user guide that to get anything out of that, it’s a lot of work to build it, it’s a lot of work to maintain it, and it’s not easy to extract that information out to use it for other things.”

So why structured authoring, feature proof your content, make it more flexible. You’ve invested so much time and energy creating great content, great experiences, why not make it so it’s modular so you can pull things out and create new and different ways of consuming that content and delivering it in different bite size bits and pieces along the way?

SO: And I guess we have to tackle the elephant in the room, which is PowerPoint. So much learning and training, in particular, especially classroom training, is identified with an instructor standing at the front, running through a bunch of slides. And we like to say that PowerPoint is the black hole of content, that’s where content goes to die, and once it goes in, you never get it back out. So what do we say to the people that come in and they’re like, “You will pry PowerPoint from my cold, dead hands.”

MB: Such a great question. I’ll jokingly refer to PowerPoint as “My precious.” Here’s the reality: PowerPoint is not the knowledge chunk. That knowledge is actually sitting in the head of the instructor, the PowerPoint is providing the framework for them to deliver and impart that knowledge and impart those best practices. It’s there to provide guardrails so that it’s done in a consistent fashion, and there’s a bare minimum amount of structure that… There’s a bullet point there, they’re going to talk about it. The degree to the quality of how they’re going to talk about it and present it is going to vary based on the person delivering the content. So if you’ve got a bunch of PowerPoint slides, you don’t necessarily have all of your training material well documented. Now, if you’ve got parallel instructor guides and student guides that talk about the details of what should be said behind those bullet points, you’re a lot closer to having that information.

So why structured authoring? Well, it’s kind of, again, the good thing about structured authoring is you have a structure. You have a, if this is the concept that we need to talk about and discuss, here’s all the background information that goes with it. So with that structure comes consistency, and with that consistency, that means that you have more of your information and knowledge documented so that it can then be distributed and repackaged in different ways. Because if all you have is a PowerPoint, you can’t give somebody a PowerPoint when they’re in the middle of an oil change and say, “Here’s the bare minimum you need.” When I need to know, “Okay, what do I do if I’ve cross-threaded my oil drain bolt?” That’s probably not in there. That may be an instructor story that’s going to be told if you have a good instructor who’s been down that really rocky road. But again, structure and being consistent about it is going to set you up so that you have robust base content. 

We’ve got Legos in the house, I got two boys. Gosh, I’ve stepped on so many Legos in my life, it’s ridiculous. But the Lego metaphor works because you have a more robust batch of Legos that you can create new creations from, rather than a limited set if you’re only doing PowerPoint.

SO: And because you’re nice, and I’m not, I’ll say this, we can produce PowerPoint out of structured content, that is a thing we can do. I’m not saying it’s going to be award-winning, every page is a special snowflake PowerPoint, but we can generate PowerPoint out of structured content. And if you’re using it as a little bit of an instructor support in the context of a classroom or live training, that’s fine.

A lot of the PowerPoint that we see that people say, “This is what I want, and if you don’t allow me to do this,” and there’s this rainbow unicorn traipsing across the side of the page kind of thing, and no, we can’t do one-off slides, we can’t do crazy every slide is different stuff, but the vast majority of the content that I see that is PowerPoint based and kind of all over the place is not actually effective. So it’s like, this is not good. We have the same issue with InDesign. We see these InDesign pages that are highly, highly laid out, and it’s like, “We need this.” Well, why? It’s terrible. I mean, it’s awful. What are you doing here? No, we can give you a framework.

MB: Now, you’re telling somebody that their baby’s ugly when you say that, that’s somebody’s baby.

SO: I would never tell somebody that their baby is ugly, but I have seen a lot of really bad PowerPoint. Babies are wonderful.

MB: Yes.

SO: It’s so bad. So why does the PowerPoint exist, and how do we work around that? And also, are you delivering in multiple languages? Because if so, we need a way to localize this efficiently, and we’re right back to the structured content piece.

MB: And as soon as you’re talking about with PowerPoint, it is the poster child of pixel-perfect placement. As soon as I take a perfectly placed pixel product and have to translate it from English to let’s just say French, just the growth of the text alone, now I’ve got what was a perfectly placed pixel layout, my beautiful slide is now a jumbled mess. So just because you can doesn’t mean you should. And the thing is, PowerPoint and Microsoft Excel are the duct tape that runs business. Everybody has it. Everybody uses it. That’s the reality.

Now, the thing is, does everything have to be structured? I don’t believe it has to be. They are absolutely the one-off snowflake instances where, you know what? PowerPoint is the exact right tool for the job. Maybe it’s the one-off presentation that really is not going to see any reuse, it’s expendable, it’s disposable. We need to get the information communicated quickly. I’m going to fire it PowerPoint. I’m going to use it as my, I’m going to do air quotes, “My throwaway content” because it’s something that is short, sweet, and needs to be communicated, absolutely. I’m not, and I don’t think you are either, saying that PowerPoint has to go away, it’s the when is it appropriate and when is it not?

SO: I mean, I am the queen of the one-off can never be reused content being developed in, now I refuse to use PowerPoint, but in slideware for a short presentation, so the next one of you that’s listening to this and walks up to me at a conference and says, “Oh, is your presentation structured content?” No, it is not. Thank you for asking. Why isn’t it structured? Because I don’t reuse it at scale. Because in fact, every presentation at every conference is a special snowflake and has been lovingly handcrafted by me to deliver the message that I need, the context that I need, potentially the language, but to your point, even if I’m not localizing the presentation itself, the cultural context matters. So if my audience is largely English-speaking or primarily English, or… I mean, we’re going to Atlanta for LavaCon, that is going to be mostly a US-based audience, and maybe we get some Canadians, eh. And other than that… But mostly US and a US context. Will I be using excessive amounts of images from the Georgia Aquarium? Yes, I will.

Now, when I go to conferences elsewhere, so let’s take tcworld in Germany in November, that audience is, we’re delivering content in English, and the audience ranges from perfect English speakers to sort of barely hanging on. And so my practice at a conference like that is to include more text on my slides because if I include some additional text, it gives the people that are not quite as comfortable in English, a little bit more scaffolding to hang onto as they’re trying to follow my ridiculous analogies and insane references to cultural things. I also do try to pay attention to the kinds of words that I’m using and the kinds of idioms that I’m using so that they’re just not completely lost in space or things are not coming from left field or whatever. So the context matters, and no, my presentations are not structured.

But pulling this back, let’s talk about the potential. So when we look at learning content and you think about saying, okay, we’re going to structure our learning content or we’re going to structure some of our learning content, what does that mean in terms of what gets enabled? What are the possibilities? What are the things that you can do with structured learning content that you cannot do in unstructured, by which I mean PowerPoint, but unstructured, locked-in content? If we break this stuff into components and we deliver on structured learning content, what are the ideas there? What are the possibilities?

MB: Well, as you’re explaining the PowerPoint point of view, a word that came up a few times was scale. I’m not having to do it at scale. Effectively, it is a one-off. Yes, I’m going to personalize it for the audience, and the degree of personalization and customization that you’re doing per conference, per audience, per default language that they’re speaking, you’re able to scale that to the degree that you need to. There’s no need for you to put your content in data and localize it and do all the things that you need to do. So it’s really that word at scale, that, I think, is the key word.

It’s when you hit that tipping point where the desktop tools that you’re using today, and we can say this with tech communications as well, I was using Word and Excel and copy and pasting and keeping things in sync, it works until you get to a tipping point where the scale no longer is sustainable. That same exact problem exists in training. So when you’re looking at things like, I have my training content that when I deliver it in California, I have to put my Prop 65 note in everything because Lord forbid, as soon as I step across the state line into California, everything that’s around me is going to give me cancer. Prop 65 is the default thing that you see plastered everywhere.

So do I need to customize my content for delivering in California? Perhaps. Maybe different states have different regional laws or policies that apply to only that audience. That’s where that mass customization and mass personalization are really hard to scale because now you don’t have just one course, you have potentially 50 courses, if I’m just talking about the US, 50 states, 50 courses, and I have to have 50 different variations, which means that not if something changes, but when something changes, now I have to open up and change 50 different courses, and it’s not, did I miss anything? It’s, “What did I miss?” That’s the thing that you wake up in the morning in a cold sweat of, “Oh my God, what did I miss?”

So why structured for learning? Largely when you get to that tipping point where you’re copy/pasting, and I call it the copy/paste published treadmill, when you are on that hamster wheel of copy/paste/publish, copy/paste/publish, and that is the majority of what you’re doing, and you’re looking at a pie chart of how much time is spent maintaining your courses or taking a base course and creating all the variations, that precious PowerPoint that is the handcrafted bespoke one-off, you can’t do that anymore. That’s the equivalent of, you look at a Lamborghini, how many do they make a year? They can afford to make a very small number per year because they’re really expensive to make. When you look at a Ford Mustang, which probably gives you 80% of the performance at a fraction of the cost and exponentially scales well beyond, it’s because they’ve taken that structured approach of, every frame’s the same, every hood’s the same, very few handcrafted things, and the things that are going to be handcrafted, that’s when I go order the special edition Shelby Cobra that has some handcrafted components put onto the basic structure. That’s that same metaphor applied.

So why structured content? Because I want to have modular content that can be reassembled really quickly, that I may have chunks that are reused so that when I need to slip in my Prop 65 disclaimers, I can do that at scale and have 50 variations of a course, but when it comes time to update it, I’m literally updating one or two things and it’s automatically updating all 50 courses and of course all the efficiencies of publishing things out in a structured format.

So that pixel-perfect placement, I’m going to give that up to stay sane so I can get home and have dinner with my family, because the amount of time that I’ve spent in my life doing pixel-perfect placement and updating things, God, I wish I could hit the way back machine and reclaim all that time in my life. How many… Guilty as charged. Show of hands of anybody who’s listening, how many times have you sat there and fiddled with the slide or a text box in InDesign then design to get it just right, that two days later, something changes and you’re back there spending 10, 15 minutes doing it to fiddle it in just right. So, as I affectionately like to say, I’m a recovered FrameMaker, InDesign, PowerPoint, and Word user because I want to author it in a structured format so that I am giving up the responsibility of layout and look and feel.

SO: I like to tell people, “I’m not lazy, I’m efficient.” The fact that I don’t want to do it is just a bonus; I can get out of doing all this work.

MB: That’s right, that’s right.

SO: Because we are not allowed to leave any podcast without covering this topic, what does it look like to have AI in this context?

MB: There are two sides of the AI coin from a content perspective, I think, and it’s the, “How can AI help me do my job better to create content?” Some things that when we’re looking at duplication of content, things that AI can do really well that, working smart, not hard, help me find things that already exist in my repository of structured content that look like this, that are really close. The human in the loop, so helping me deduplicate or help me not create new unnecessary variations of content. I think that’s one area of AI-based assistance for content creation that people may not be necessarily thinking about. Because right now, the easy one is like, “Hey, ChatGPT, help me write an introduction or an overview for the following,” it spits that out. That’s great, but that overview and that content may have already been written by somebody else, and so what ends up happening is you start generating content drift where it’s almost exactly the same but just slightly different. And in reality, yes, I could have used the one that was already there.

So I think that’s one of the areas where AI from a content authoring perspective is one that I’m really excited about. Because at the end of the day, and this leads us into the second part of AI, AI is only as good as what you feed it, and if you feed it junk food, you’re going to get junk results. So it’s that whole thing of do you eat healthy food or are you going to eat Cheetos? If you’re pointing your AI at a SharePoint repository and saying, “Hey, read all of this,” and all the content shifts and variations and content drift and out-of-date and perhaps out-of-context content that exists inside of that repository, your results are not going to be as accurate as they need to be. So, how do you ensure that AI is providing good results? Well, you feed good content.

And so within an organization, I think the two silos that we started our conversation with, technical communications and L&D, tend to have some of the most highly vetted, highly accurate, up-to-date content in an organization. And so this is my encouragement to everybody who’s in this space, you are the owners of what is good, highly nutritious food that you can feed your AI. So taking it back to the structured content perspective, if I’m authoring in the structured content, publishing it out in a format that is AI ready, all of your tags, all of your enrichments, all of your, here’s the California version of the content versus the Georgia or Florida’s version of the content, all of that context and enrichment and tagging that’s gone on, you’re now feeding AI all of that context so that AI can provide the proper answer. So that’s my short, it’s sweet for the AI side. We could talk for probably days on all sorts of other variations, but right now, that’s where I’m seeing the biggest impact that it’s going to have on techcomm and L&D.

SO: I think that’s a great place to wrap it up. And I want to say thank you for being here and for a great conversation around all of these issues, and we will reconvene at a future conference somewhere to cause some more trouble and talk some more about all of these things. So Mike, thank you.

MB: You are welcome. And yeah, I think the next conference we’re going to see each other is going to be LavaCon, so I’ll be talking in and around the convergence of L&D and techcomm and what life can look like with that. So certainly a deeper dive and continuation of what we started here, and super excited to sit on your session as well.

SO: Yep, super. I will see you there. I’m pretty sure I’m doing one on the same topic, but it will be more complaining and less positive, so that seems to be my role. Okay, with that, thank you everybody, and we’ll see you on the next one. 

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Questions about this episode? Ask Sarah!

The post From PowerPoint to possibilities: Scaling with structured learning content appeared first on Scriptorium.

Patrick Bosek: Nobody reads a page in your documentation site for no reason. Everybody that is there has a purpose, and that purpose always has an economic impact on your business. People who are on the documentation site are not using your support, which means they’re saving you a ton of money. It means that they’re learning about your product, either because they’ve just purchased it and they want to utilize it, so they’re onboarding, and we all know that utilization turns into retention and retention is good because people who retain pay us more money, or they’re trying to figure out how to use other aspects of the system and get more value out of it. There’s nobody who goes to a doc site who’s like, “I’m bored. I’m just going to go and see what’s on the doc site today.” Every person, every session on your documentation site is there with a purpose, and it’s a purpose that matters to your business.

Related links:

• Heretto
• Contact Heretto to walk through their support evaluation sheet with an expert!
• The business case for content operations (white paper)
• Curious about the value of structured content operations in your organization? Use our content ops ROI calculator.
• Get monthly insights on structured content, futureproof content operations, and more with our Illuminations newsletter

LinkedIn:

• Patrick Bosek
• Sarah O’Keefe

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Sarah O’Keefe: Hi, everyone, I’m Sarah O’Keefe and I’m here today with our guest, Patrick Bosek, who is one of the founders and the CEO of Heretto. Welcome.

Patrick Bosek: Thanks, Sarah. It’s lovely to be here. I think this is may be my third or fourth time getting to chat with you on the Scriptorium podcast.

SO:  Well, we talk all the time. This is talking and then we’re going to publi- no, let’s not go down that road. Of all the things that happen when we’re not being recorded. Okay. Well we’re glad to have you again and looking forward to productive discussion here. The theme that we had for today was actually traffic and I think web traffic and why you want traffic and where this is going to go with your business case for technical documentation. So, Patrick, for those of you that have not heard from you before, give us a little bit of background on who you are and what Heretto is and then just jump right in and tell us about web traffic.

PB: No small requests from you, Sarah.

SO: Nope.

PB: So I’m Patrick Bosek. I am the CEO and one of the co-founders of Heretto. Heretto is a CCMS based on DITA. It’s a full stack that goes from the management and authoring layer all the way up to actually producing help sites. So as you’re moving around the internet and working with technology companies, primarily help_your_product.com or help_your_company.com, it might be powered by Heretto. That’s what we set out to do. We set out to do it as efficiently as possible, and that gives me some insight into traffic, which is what we’re talking about today, and how that can become a really important and powerful point when teams are looking to make a case for better content operations, showing up more, producing more for their customers, and being able to get the funding that allows them to do all those great things that they set out to do every day.

SO: So here we are as content ops, CCMS people, and we’re basically saying you should put your content on the internet, which is a fairly unsurprising kind of priority to have. But why specifically are you saying that web traffic and putting that content out there and getting people to use the content helps you with your sort of overall business and your overall business case for tech docs?

PB: Yeah. So I want to answer that in a fairly roundabout way because I think it’s more fun to get there by beating around the bush. But I want to start with something that seems really obvious, but for some reason it isn’t in tech pubs. So first of all, if you went to an executive and you said, I can double the traffic to your website, and then you put a number in front of them, probably say a hundred thousand dollars, almost like any executive at any major organization is like a hundred thousand dollars, of course, I’ll double my web traffic. That’s a no-brainer. Right? And when they’re thinking of website, they’re thinking of the marketing site and how important traffic is to it. So intrinsically, everybody pays quite a bit of money and by transference puts a lot of value on the traffic that goes to the website and, as they should. It’s the primary way we interact with organizations asynchronously today.

Digital experience is really important. But if you went to an executive and you said, I can double your traffic to your doc site, they would probably be like, wait a second. But that makes no sense because nobody reads the docs for no reason. I want to repeat that because I think that’s a really important thing for us, as technical content creators to not only understand, I think we understand it, but to internalize it and start to represent it more in the marketplace and to our businesses and to the other stakeholders. People might show up at your marketing site, because they misclick an advertisement. They might show up in your marketing site because they Googled something and your market and a blog like caught them and they looked at it. So there’s probably a lot of traffic where people are just curious. They’re just window shopping. Maybe they’re there by mistake. But nobody shows up at your documentation site.

Nobody reads a page in your documentation site for no reason. Everybody that is there has a purpose and that purpose always has an economic impact on your business. People who are on the documentation site are either not utilizing your support, which means that they’re saving you a ton of money. It means that they’re learning about your product, either because they’ve just purchased it and they want to utilize it, so they’re onboarding, and we all know that utilization turns into retention and retention is good because people who retain pay us more money, or they’re trying to figure out how to use other aspects of the system and get more value out of it. There’s nobody who goes to a doc site who’s like, I’m bored. I’m just going to go and see what’s on the doc site today. So every person, every session on your documentation site is there with a purpose and it’s a purpose that matters to your business. So that’s why I want to start. That’s why it matters. That’s why I think traffic is important, but you look like you want to contribute here, so.

SO: We talk about enabling content. Right? Tech docs are enabling content. They enable people to do a thing, and this is what you’re saying. People don’t read tech docs for fun. I know of, actually, I do know one person. One person I have met in my life who thought it was fun to read tech docs. One.

PB: Okay. So to be fair, I also know somebody who loves reading release notes.

SO: Okay. So two in the world.

PB: But hang on, hang on. But this person, part of the thing is this person is an absolute, can I say fanboy, is that, they’re a huge fan of this product and they talk about this product in the context of the release notes. So even though this person loves the release notes, the release notes are a way that they go and generate word-of-mouth and they’re promoting your product because of the thing they saw in the release notes. The release notes are a marketing piece that goes through this person. All the people who are your biggest fans are going to tell people about that little thing they found in your release notes. Sorry. Anyways.

SO: So again, they’re trying to learn. Okay. But, so two people in the universe that we know of read docs for fun. Cool. Everybody else is reading them, as you said, for a purpose. They’re reading them because they are blocked on something or they need information, usually it’s they need information. And then you slid in that when they do this, this is producing, providing value to the organization or saving the organization money. So what’s that all about?

PB: Well, I mean there’s a number of ways to look at this. You want to start with the hard numbers, the accounting stuff, the stuff you can take the CFO. That stuff is actually, it’s pretty easy to do. You can do it in just a couple of lines. So every support ticket costs a certain amount of money. Somebody in your organization knows that number, if your organization is sufficiently large and sufficiently large is like 20 people probably. Maybe that’s not that small, but if you’re a couple hundred people, everybody knows what that number is. So it’s very easy to figure out how much it costs when somebody actually goes to the support.

SO: Somewhere between $20 and $50 is kind of the industry average per call. You may have better numbers internally in your organization, but if you don’t or you don’t know where to start there. Every call is $25.

PB: Yeah. $20, $25. A little more, if you’re in a complex industry. The reality is that when you start comparing it to how much you spend answering a question with content, it’s kind of like, oh, is it a thousand times cheaper or is it 2,000 times cheaper? So it’s not really that big of a difference. The cost of answering a question with content is also pretty straightforward. So all you really need to know is how much are you spending on your content, which is typically speaking just the combination of the people and tools, so people in content operations stack that you’re using to get that content out in front of people. And then the page views. I mean, fundamentally if you exclude search, so take search out of your page views, take home page out of your page views, if you can filter section pages, so just look at actual content pages and then you have to pick a resolution rate.

Obviously, if you want to say 100%, if you don’t have any better metrics, that’s probably too high. Maybe it’s unreasonable, but it’s very simple. It makes the equation easier. If you want to say that 50% percent of people who read what you’ve considered to be like a content page, resolve their issue, that’s probably too low. So pick a number between those two things and you run the multiplication on that and you’re going to find out that it’s going to cost you, in most situations, less than a penny to answer a question, typically way less than a penny to answer a question with content as opposed to the $25. That’s the pure economic math of it. There’s more though.

SO: Okay. So yeah, we did some math and we’re basically saying, looking at this in a tech support centric way, usually we talk about call deflection. Right? So the idea is that every time somebody does not call tech support, you save $25 and spend a penny, a fraction of a penny instead, which seems good. Now interestingly to me, I think, you can look at this as the first time somebody hits that site and hits a content page, costs really a lot of money. Right? Because the people and the tools and the setup and the publishing, but then the next one is zero.

So you’re replacing sort of an upfront planned cost with a recurring cost because every time somebody calls, it’s another 25 or 50 or whatever dollars. So there’s a huge scalability argument here, and I can make a decent case for if you are a startup, a day one startup, you have no content, you have nothing, you have no infrastructure, cool. Hire a tech support person. Let them do their thing for maybe a year, and then look at the top 10 queries that they had and write some docs and deflect off those top 10 queries and handle it that way. But most of our customers, speaking for both of us, are medium to large to incredibly large organizations that have content. We’re not talking about the you have nothing start from scratch scenario.

PB: A hundred percent. When you’re really thinking about where you get the value, both on the accounting side, like saving money, so bottom line stuff, and then also the customer experience, which I think is worth getting into in a minute, that’s really going to take place when you start scaling up. I agree with you that a startup style organization should write content. Even small organizations benefit from it. I think they, small organizations actually benefit in a slightly different way than the deflection, which is the word you’re using. And I’m going to come back to that because I have a pet peeve with that word, but I’ll use it right now for the purposes because we’ve been using it. I think that what, the value that a smaller organization gets is not in the deflection, but it’s actually in the presence. So if you’re trying to show up and you’re trying to compete with larger organizations and you’re doing something, which is technical or considered to be highly important, so you’re in a high technology industry, your buyer is going to go look at your documentation. They’re going to look at your competitor’s documentation as well.

And if your documentation appears to be not that great, it’s very thin, there’s not a lot there, that’s going to be a factor in a buying decision. And I know everybody kind of like, yeah, but it really is, and I can tell you because we’re not a huge organization, that we’ve won deals because our docs were better. We invest in it, as we should. We’re a documentation tool. You know? So it does matter at the smaller end, even if you can’t build a really scalable content operation stack that you probably don’t need.

SO: Now, personally, I’m okay with deflection, and I’ll also say that the key thing here is that if you’re doing additional research on this as a listener, call deflection is sort of the industry term that will help you in your Google/AI searches. But tell us about why call deflection is bad and evil.

PB: Okay. So that is true. If you are talking to executives, you should probably say deflection, but maybe forward-thinking executives would appreciate why I think deflection is a bad term. I think we should use, you’re shaking your head at me. Fine. I think we should be talking about call avoidance. And the reason that I think this is because when most people think about deflection, they’re thinking about it as being very reactive, and it’s that box that pops up when you’re trying to put a support ticket in that’s like, well, have you already looked at this? And by the time someone has arrived at your support site and they have decided that they want to interact with a human, they are annoyed. They don’t want to be there. Nobody visits the support site because they want to. They have made the emotional commitment that they’re going to go and deal with one of your human beings to solve their problem, which is not something they planned on doing today. Nobody wanted to do this when they got up in the morning. So you’ve already failed. And at that point in time, the best thing you can do is get them to a human efficiently without sticking things in front of them and trying to deflect them. So that’s why I don’t like deflection. Avoidance is that that never happened. They Googled it because Google is tier zero support for everybody, even if yours is bad. They got an answer or they ChatGPT-ed it, different topic, there’s problems there. But probably they Googled it. They got an answer very quickly. They solved their issue. You never heard about it. It cost you a fraction of a penny. They had a great experience. It’s how they prefer to get their information, and you avoided the support rather than trying to deflect them to save yourself a couple of bucks when they were annoyed and broke their customer experience.

SO: Yeah. I’m on board with that. It’s just that terminology-wise, we’ve got to work with what we’ve got. But I would agree that avoiding the call in the first place, and I talk about how when people call tech support, they’re mad. If you think about the emotional state of your customer, the tech support person is angry. There’s also the issue that they asked ChatGPT and it said something wrong, and then they call up tech support and yell at you because ChatGPT was wrong, which is, that’s a whole other podcast. So let’s just set that aside for a moment, but okay.

PB: Maybe you’ll invite me back. We can talk about that.

SO: Yeah. So the, it’d be a long podcast and we’ll have to lift our no profanity rule for that one just to get through the topic.

PB: Oh. Special edition.

SO: Special edition. Okay. So you were talking about the value though of a documentation site and we’ve sort of paired it with tech support and with this avoidance, deflection, get them the answers that they need before they get angry at the product. Right?

PB: Yeah. For sure.

SO: How does the customer experience tie into that? And what is the value of the customer experience?

PB: So the value of the customer experience is subjective, but every organization already has an opinion on it. Some organizations place a lot of value in customer experience, have done a lot of work to tie customer experience to the metrics and analytics and things like that they use to track financial performance. Other organizations less. So the first thing I would say is go and see where your organization is relative to their thinking on customer experience. But, as you’re talking about customer experience, other than the support, which I think we’ve covered that quite a bit, for someone who’s showing up your documentation site, really what it’s touching on is a couple of things, what they’re trying to get to. So there’s the discovery aspect of it. And this can be very, very simple or it can be very, very complex. The simple one I like is like let’s say you sell gym equipment and that gym equipment goes out to people who own gyms, as it would make sense, and they’re going to go and they’re thinking of buying a new treadmill or something from you.

They’re going to want to know, is this going to fit in my gym? Can the power I have set up work with it? What are the other details of this product? And then how much information is there to service it? So somebody, once they get past the whole like, okay, I kind of like this brand, maybe this is a good thing, it’s kind of cool, they’re going to go into the documentation because they’re making a purchase that matters to them. And having confidence and trust in the product based on the depth of information that they get prior to purchasing it is a major factor. And this only increases as the economic value and the end implementation, like how critical it is, how system critical it is, increases. So there’s a discovery, evaluation, and confidence, those are the three things I think of, aspect to your documentation or your help site that is there, even if you’re not thinking about it, even if it’s not coming up directly in sales conversations. I promise you, because I have the data that people are doing this during the process of deciding if they want to work with your organization. And that’s the kind of pre-customer experience that’s really, really critical that most organizations are just not thinking about and they’re probably leaving a lot on the table relative to their competitors that either could be advantage or they’re behind.

SO: There was a study. It was a while back, maybe five or 10 years ago that came out from, I always have trouble finding it. It was either PwC or IBM. The gist of it was that 80% of people that were buying consumer products were doing pre-buying research, the technical research. So they were looking at specs and they were looking at how do I install this thing and various other things that we consider to be not marketing information. They were looking at what is traditionally labeled post-sales documentation.

PB: Yeah. Because people care. And the other thing too is like as we move into an economic environment where people are more careful about what they’re spending on, they’re only going to do more research to make sure the things they’re buying are things that are going to last and be supported. I bought a pair of headphones a year ago, and I have an issue with one of them. They’re like the ones that go in your ears, one of them’s not working. I ended up going to the documentation to try to figure it out, and the documentation was so bad I could not make heads or tails of it. And I just gave up and I was like, okay, if I had spent hundreds of dollars on these, I’d go through the process, but they were like 30 bucks or whatever. But I’m never going to do business with that company again. Ever.

If I see another one of the products, I will never buy it. So they don’t know about that experience. But if you have, not even just bad content operations, because frankly their site was, it was kind of nice, it wasn’t bad. I think it could have been better, but you know, funny that I would have that opinion, but it was really the information architecture, so it was kind of the stuff that Scriptorium, Sarah, you guys would help them with. It wasn’t so much they had bad tools. They had terrible organization, and the content was, I’m not allowed to swear, which I wouldn’t anyways…

SO: Sorry.

PB: … but the content was, think of your word, it was bad. It was completely unhelpful. So you can have the best content operations in the world, but without the right information architecture, who cares?

SO: Yeah. This is the infamous if a tree falls in the forest. You know, and to your point, A, the company doesn’t know that your headphones are broken and you’re unhappy, but you just told me, and the next time I’m in the market to buy a pair of headphones, I’m going to remember this story and I’m going to call you, I won’t call you. I’ll send a text and say, hey, what brand was that? Right? And you’re going to tell me and then I’m going to not buy them. So the impact of this failure of documenting, well, actually it’s a product fail, right, but also of support. Because if they had come back with, oh, we’re so sorry, send them in or we’ll send you a new pair, whatever, they could have rescued this encounter, but they didn’t. So the next thing that’s going to happen is that you and every single one of your friends that hears the story will never buy that brand.

PB: Right.

SO: So as we talk about this, the really critical point here though is, I think, there are a bunch of really critical points, but the one that I really want to zoom in on is that the content has to be there. Right? You have to have helpful content that solves the problem that a person is on the website for. And, in your case, it might have been, oh, sometimes this happens and you have to repair them, or you have to this or you have to that, you know, press all these weird buttons in this weird sequence and sacrifice the chicken and stand on your head. Cool.

PB: Right. Which I would’ve done.

SO: Which you would’ve done. But the bigger problem is that you went to their website and we don’t actually know whether or not this problem is fixable because you didn’t find it. Right? You didn’t find the answer. And that means that it’s sort of like a last mile problem. I can write all these really good procedures, they can be super accurate, they can be amazing, blah, blah, blah, blah, blah. You come onto my website, you can’t find the answer your question, it exists, but you can’t find it, right, you, the customer, and so it fails, and now you either, A, tell all your friends that company XYZ is terrible, or, B, you call tech support and you’re mad. Right?

PB: Yeah.

SO: That’s actually the best outcome.

PB: It is. Yeah.

SO: Yeah. And interestingly, we’ve got some, I’ll be very non-specific, but we have a project right now where one of the top tech support topics, you know how you look at what are the top 10 things that people call and ask about, and it’s like, my headphones aren’t working, or how do I return this or whatever. One of the most common reasons that people call their tech support is to ask, where is the documentation? I can’t find it.

PB: Do you have any idea how common that is? I mean, you probably do, but it’s so common.

SO: Yeah.

PB: And we’ve started doing this thing in the process of helping people think through this where we have a very simple tool that we use. It’s a sheet, happy to share it with anybody, and a process where you effectively go through and you just do a very simple 15 to 30 minute interview with X number of support people. You know, we recommend three to five. Some people do more. And you just go through the last 10 support cases, the ones that they worked on, and there’s a few things you mark off, but the idea is to do lightning round, very, very quick. And could this be solved by documentation? And the amount of it that is just looking for documentation, I can’t find it, is so funny. And you’re like, I think that’s a problem. And people are like, wow. But you can’t blame them because people don’t think about these things and it doesn’t make sense that you would because it’s non-obvious, and I think that’s one of the really critical things I want to leave people with.

And I have one other thing that I, you know, we’ve been talking for a while that I want to let people go soon, but this one, I want to zoom in on this for a second. People shouldn’t feel bad that they haven’t thought about this. They shouldn’t feel bad that they haven’t thought about the value of the traffic, the impact of the traffic, the customer experience side of it, the cost ratio of the traffic relative to support people. It really isn’t that obvious. And there’s so much momentum around the way that we’ve done business in having people solve problems for other people in direct communications that even if that isn’t ideal, that’s just the way it’s done and that’s what feels obvious. So don’t feel bad about not having thought about this if you haven’t. Your colleagues shouldn’t either. But it is the way the world is moving, and I think it’s critical to start thinking about it now.

SO: Yeah. And you started this by talking about customer experience needing to be asynchronous. People can get the stuff, self-service when they want it and digital as opposed to call somebody on the phone. So let’s sort of wrap this up and say, what’s your advice to people that know that they’re struggling with this? They know that they have huge tech support volumes and nobody’s happy. And I mean, we know we have a problem. So where should they start? What’s the first step that they can take to begin attacking this thing in a way that will lead to forward progress within a large organization that has as their informal motto, oh, they can just call tech support.

PB: Yeah. So I would say buy-in is always step one, and that means that there’s going to be some selling that has to happen at the organization. You have to get people to recognize the value, the potential, and also the ability to achieve it. So it’s those things when they come together, there can be a ground swell where people are going to actually support these projects and fund them and get involved, and then you’ll have really successful projects. One of the big challenges with getting that buy-in historically has been that there’s no precedent. So when you’re looking for a better website, you already have a website. What if you increase traffic by 10%? You know, people can start to draw some lines between that and sales or the bottom line or value, those types of things. And oftentimes, even organizations that I would say are somewhat up to maturity curve in terms of tech pubs, they don’t have any metrics about their site, like how many people come to it? I don’t know.

They just don’t track it. So there’s not this historical precedent of metrics that can be back to results, and that can create some issues. So the advice that I give organizations that are in that situation is if you are in a technology field and you have a relatively complex product, so something where it breaks, it’s not always obvious how to use it, there’s a reason that people would need to learn about your product for some reason, what our data shows from having done this many times with organizations that fit that profile is that a well-implemented documentation help site, whatever you want to call it, gets about as much traffic as the dot com, the primary marketing site. It tends to be plus or minus 15%. We’ve actually seen as high as 65% of the total traffic between the two sites being on documentation.

That’s a bit of an outlier, but so is 30%. You know, we’ve seen that too. So if you’re want to be conservative, say you’ll get 40% of the total traffic. So four sessions for every six on a marketing site. If you want to be, what we tend to see on an average, just say it’s one for one. If it’s one for one and you don’t have metrics, that’s a target. And you have to ask the internal question, what’s the value of that? If we get a hundred thousand sessions per month or per year or whatever on the marketing site, what if we had a hundred thousand sessions on the help content? Well, those people are there for a reason. Remember? They’re there because they’re not calling support. They’re there because they’re onboarding and using our system better, or they’re there because they’re trying to figure out if our stuff’s going to work for them.

So like how valuable would that be? And once you get the organization to a place where they’re like, oh, that would actually be quite valuable, could we get that, I think 80% of the work is done and well, 80% of the work of getting started is done. And then you probably call somebody like Scriptorium or Scriptorium specifically, if you’re not familiar with this, and you start the process of actually thinking through of how to do it. But I do think the organizational buy-in and giving people in the right head space to think about the value of this is step one, and that’s the process I use for it.

SO: Yeah. I think I would agree with all of that, especially the part where they should call us.

PB: Go figure.

SO: But the key thing in here is, and you said this a different way, but changing the momentum, right, getting organizational buy-in, getting people on board with this concept. The other thing I’ll say is that ultimately one of the biggest problems we face in content ops is that so much of it is invisible in the sense that we’re going to refactor this and we’re going to do it better, and we’re going to produce it faster and we’re going to automate, okay, great, but you’re still producing the same thing. One of the most powerful things we can do early in the process is say to people, look at this portal that we can deliver. Look at this experience that we can deliver. It’s not the first thing or the only thing or even necessarily the most important thing we need to do, because the portal has to have content. Right?

PB: Yeah.

SO: I mean, it’s kind of a chicken and egg thing, but showing people the vision of what can be works typically much, much better than saying we should do structured content because it will help automate things and speed up time to market. That’s all behind the scenes, and it’s not visual and nobody cares. I mean, people care, but it’s hard to visualize. So, okay, I think we’ve promised people a whole bunch of resources. We will put those in the show notes. I’m quite certain that we could go on for a very long time about this topic, but I am going to wrap it up there ’cause I feel like we hit a good starting point for people.

PB: Yeah.

SO: So if there are other questions, I would say reach out to me or to Patrick, because I know we’ve only scratched the surface on this thing. Patrick, thank you for being here.

PB: Of course. Always a blast.

SO: Always good to see you. And we will wrap this thing up, and thanks for being here. Feel free to reach out if you have any other questions.

The post Every click counts: Uncovering the business value of your product content appeared first on Scriptorium.

Bill Swallow: I think it goes without saying that there’s going to be disruption again. Every single change, whether it’s in the localization industry or not, has resulted in some type of disruption. Something has changed. I’ll be blunt about it. In some cases, jobs were lost, jobs were replaced, new jobs were created. For LSPs, I think AI is going to, again, be another shift, the same that happened when machine translation came out. LSPs had to shift and pivot how they approach their bottom line with people. GenAI is going to take a lot of the heavy lifting off of the translators, for better or for worse, and it’s going to force a copy edit workflow. I think it’s really going to be a model where people are going to be training and cleaning up after AI.

Related links:

• Going global: Getting started with content localization
• Lessons Japan taught me about content localization strategy
• Conquering content localization: strategies for success (podcast)
• The Scriptorium approach to localization strategy
• Get monthly insights on structured content, futureproof content operations, and more with our Illuminations newsletter

LinkedIn:

• Sarah O’Keefe
• Bill Swallow

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Sarah O’Keefe: Hey, everyone. I’m Sarah O’Keefe, and I’m here today with Bill Swallow.

Bill Swallow: Hey there.

SO: They have let us out of the basement. Mistakes were made. And we have been asked to talk to you on this podcast about AI in translation and localization. I have subtitled this podcast, What Could Possibly Go Wrong? As always, what could possibly go wrong, both in this topic and also with this particular group of people who have been given microphones. So Bill.

BS: They’ll take them away eventually.

SO: They will eventually. Bill, what’s your generalized take right now on AI in translation and localization? And I apologize in advance. We will almost certainly use those two terms interchangeably, even though we fully understand that they are not. What’s your thesis?

BS: Let’s see. It’s still early. It is promising. It will likely go wrong for a little while, at least. Any new model that translation has taken has first gone wrong before it corrected and went right, but it might be good enough. I think that pretty much sums up where I’m at.

SO: Okay. So when we look at this … Let’s start at the end. So generative AI, instead of machine translation. Let’s walk a little bit through the traditional translation process and compare that to what it looks like to employ GenAI or AI in translation.

BS: All right. So regardless of how you’re going about traditional translation, there is usually a source language that is authored. It gets passed over to someone who, if they’re doing their job correctly, has tools available to parse that information, essentially stick it in a database, perhaps do some matching against what’s been translated before, fill in the gaps with the translation, and then output the translated product. On the GenAI side, it really does look like you have a bit of information that you’ve written. And it just goes out, and GenAI does its little thing and bingo, you got a translation. And I guess the real key is what’s in that magic little thing that it does.

SO: Right. And so when we look at best practices for translation management up until this point, it’s been, as you said, accumulate assets, accumulate language segment pairs, right? This English has been previously translated into German, French, Italian, Spanish, Japanese, Korean, Chinese. I have those pairs, so I can match it up. And keeping track of those assets, which are your intellectual property, you as the company put all this time and money into getting those translations, where are those assets in your GenAI workflow?

BS: They’re not there, and that’s the odd part about it.

SO: Awesome. So we just throw them away? What?

BS: I mean, they might be used to seed the AI at first, just to get an idea of how you’ve talked about things in the past. But generally, AI is going to consume its knowledge, it’s going to store that knowledge, and then it’s going to adapt it over time. When it’s asked for something, it’s going to produce it with the best way it knows how, based on what it was given. And it’s going to learn things along the way that will help it improve or not improve over time. And that part right there, the improve or not improve, is the real catch in why I say it might be good enough but it might go wrong as well, because GenAI tends to … I don’t want to say hallucinate because it’s not really doing that at this stage. It’s taking all the information it has, it’s learning things about that information, and it’s applying it going forward. And if it makes an assumption based on new information that it’s fed, it could go in the wrong direction.

SO: Yeah. I think two things here. One is that what we’re describing applies whether you have an AI-driven workflow inside your organization where you’re only allowing the AI to access your, for example, prior translation. So a very limited corpus of knowledge, or if you’re sending it out like all of us are doing, where you’re just shoving it into a public-facing translation engine of some sort and just saying, “Hey, give me a translation.” In the second case, you have no control over the IP, no control over what’s put in there and how it’s used going forward, and no control over what anyone else has put in there, which could cause it to evolve in a direction that you do or do not want it to. So the public-facing engines are very, very powerful because they have so much volume, and at the same time, you’re giving up that control. Whereas if you have an internal system that you’ve set up … And when I say internal, I mean private. It doesn’t have to be internal to your organization, but it might be that your localization vendor has set up something for you. But anyway, gated from the generalized internet and all the other people out there.

BS: We hope.

SO: Or the other content. You hope. Right. Also, if you don’t know exactly how these large learning models are being employed by your vendors, you should ask some questions, some very pointed questions. Okay, we’ll come back to that, but first I want to talk a little bit about pivot languages. So again, looking at traditional localization, you run into this thing of … Basically many, many, many organizations have a single-language authoring workflow and a multi-language translation workflow. So you write everything in English and then you translate. So all of the translations are target languages, they are downstream, they are derived from the English, et cetera. Now let’s talk a little bit about… First of all, what is a multilingual workflow? Let’s start there. What is that?

BS: Okay. So yeah, the traditional model usually is author one language, which maybe 90% of the time is English, whether it’s being authored in an English-speaking country or not, and then it’s being pushed out to multiple different languages. In a multilingual environment, you have people authoring in their own native language, and it should be coming in and being translated out as it needs to be to all the other target languages. Traditionally, that has been done using pivot languages because infrastructures were built. It is just the way it is. It was built on English. English has been used as a pivot language more than any other language out there. There are some outliers that use a different pivot language for a very specific reason, but for the sake of this conversation, English is the predominant pivot language out there.

SO: So I have a team of engineers in South Korea. They are writing in Korean. And in order to get from Korean to, let’s say, Italian, we translate from Korean to English and then from English to Italian, and English becomes the pivot language. And the generalized rationale for this is that there are more people collectively that speak Korean and English and then English and Italian than there are people that speak Korean and Italian.

BS: With nothing in between, yeah.

SO: With nothing in between. Right. Directly. So bilingual in those two languages is a pretty small set of people. And so instead of hiring the four people in the world that know how to do that, you pivot through English. And in a human-driven workflow, that makes an awful lot of sense because you’re looking at the question of where do I find English … Sorry, not English, but rather Italian and Korean speakers that can do translation work for my biotech firm. So I need a PhD in biochemistry that speaks these two languages. I think I’ve just identified a specific human in the universe. So that’s the old way. What is a multilingual workflow then?

BS: So yeah, as we were discussing, the multilingual workflow is something where you have two, three, four different language sources that you’re authoring in. So you’re authoring in English, you have people authoring in German, you have people authoring in Korean and, let’s say, Italian. And they’re all working strictly in their native language, and those would go out for translation into any other target language. It’s tricky because the current model still uses a pivot language, but I think when we talk about generative AI, it’s going to avoid that completely. It’s going to skip that pivot and just say, “Okay, I know the subject matter that you’re talking about and I know the language that you’ve presented it in. Let’s take this subject and meaning and just represent it in a different language and not even worry about trying to figure out what does this mean in English. It doesn’t matter at this point.”

SO: Right. And so I think the one caveat here as we’re looking at this issue is to remember that GenAI in general is going to do better when it has larger volumes of content. And a lot of the generative AI tools are tuned for English. That’s kind of where they started. But it’s also useful to remember that GenAI is math. GenAI doesn’t really have a concept of knowledge or learning or any of these other things. It’s just math. So math is a language of its own, and we should be able to express mathematical concepts in a human language of choice. So there’s some really interesting stuff happening there. Okay. So stepping back a little bit from this, let’s talk about where this is coming from and the history of machine translation in translation localization. Where did we start? And isn’t it true that localization really was one of the leaders in adopting AI early on?

BS: It really was. So way, way, way back, you had essentially transcription in a different language. So people were given a block of text and asked to reproduce it in a different language, and they went line by line and just rewrote it in a different language. Then you start getting into the old-school machine translation or statistical machine translation. What this did was it kept, essentially, a corpus of the translations that you’ve done in the past, and it also broke down the information that you were feeding it into small segments. And it would do a statistical query, taking one segment from what your source said and throwing it out into its memory and say, “Okay, is there anything out here? Was this translated before? And give me a ranking of these results of what was done before.” And essentially, the highest result floated to the top, and it used that. Translators could modify those results over time based on actual accuracy versus systematic or statistical accuracy. But that is forever old. Over the past 10, 15 years, we’ve seen neural machine translation come out, which is getting a lot closer to AI-based translation. So it takes away the text matching and replaces it with more pattern matching. So it’s better at gisting. It will find, let’s say, a 95% match and can fill in those gaps for the most part, or at least say, “Hey, this gets us 95% of the way there. I’m going to put this out over here, and then the translator will essentially verify that translation going forward.” It’s a bit more accurate, but it still relies on this corpus of translation memory that you build over time. And now we’ve got generative AI machine translation, which completely takes everything that was done before, and it doesn’t necessarily throw it away, but it says, “Thank you for all the hard work you did. I will absorb that information and move forward.”

SO: Does it actually say thank you?

BS: It could. It depends on the prompt you use. But I mean, really, you’re looking at a situation where the generative AI model, it uses a transfer learning model to do the translation work. So it takes everything that it knows, applies it to what you feed it for translation, produces an output, learns a lot of things along the way in getting that translation to a point where you say, “Okay, great, thank you. This was good,” and then applies what it learned to the next time you ask. And it keeps doing that and doing that and doing that. On the plus side is that, yes, you can train your generative AI to get really, really, really good if you train it the right way. If someone … And I am not saying it’s malicious or anything, but if you train your GenAI translation model to start augmenting how it translates, then you’ll start getting these mixed results over time because it’s going to learn a different way to apply your request to provide an output.

SO: So the question that I actually have, which I’m not going to ask you to answer because that would be mean, is whether AI is actually storing content in a language, like in English, or is language, in the case of GenAI, just an expression of the math that underlies the engines? You don’t want to tackle that, no. Moving on.

BS: Well, it’s worth poking at, at least, because … Does GenAI actually do anything with the language that we give it now, just for answers? If we’re asking it to write a stupid limerick about a news event, or are we asking, “Summarize this document,” does it care that it’s written in any language? I honestly don’t know.

SO: As meta as it is to ask the question, what is the math that underlies it, the other thing that’s helpful to me, and again, we’re grossly oversimplifying what’s going on, but what is very helpful to me is to think of AI as autocorrect, or autocomplete, actually, on steroids. It’s more than that, but not a lot more. It has just learned that every time I type certain words in my text app, certain other words are likely to follow and it helpfully suggests them. And sometimes it’s right and sometimes it’s wrong, but it’s just doing math, right? Autocorrect learns that there are certain words that, when misspelled or that I do not wish to have corrected, or perhaps it introduces the concept that that word needs to be corrected to the word that I use more commonly, which can be extremely embarrassing. We had some questions about this. We’ve done some prior localization AI conversation, and I wanted to bring in a question that came from one of our audience members. Their question was, “Will we get to the point where we can effectively ask an AI help system a question in a foreign language, the AI system will parse the source language content, and then return the answer in the user’s language? Will translating documentation eventually be no longer necessary?” And what’s your take on that?

BS: Well, I think the answer is yes, and my take is that we are nearly there already. We already have… even apps that you can run on your phone. We have apps that can translate on the fly from verbal language. And I have used them when I travel abroad and I don’t know the language very well, to be able to speak it into my phone and it essentially translates the text for the person I’m trying to communicate with. There are other apps that take a step further and use a synthetic AI voice to read it so that they don’t have to look at my screen. They can just hear what the phone has to say because obviously I’m unable to say it myself.

SO: There’s also a version that does that through the camera. So you point the camera at a sign or a menu, more importantly, and it magically translates the menu into your language while you’re looking at it through your phone, or through your camera.

BS: That has been so helpful.

SO: Yes. Now that is actually a really good example, though, of a place where this kind of translation is hard because there’s very little context, and there’s a tendency in food culture to have very specific terms for things that maybe are not part of the AI’s daily routine. We were talking not too long ago about … What was it? We came up with half a dozen different words in German for dumpling. And we got into a big argument about which one was what and which one is correct for this type of dumpling and all the rest of it. So yeah. The thing I would point out here is that the question was, if someone comes in and asks the AI help system a question in, let’s say, French, but the underlying system is in, let’s say, English, but it would then return French. It’s a very English-centric perspective, to say, “Well, the French people … Our AI is going to be in English, essentially. Our AI database.” And that is a really interesting question to me. Is the AI database actually going to be in English? And maybe not.

BS: Probably not.

SO: I tried this about a year ago with ChatGPT. And you might experiment with this if you speak another language, or combine it with machine translation, which should work as well. I asked ChatGPT a specific question, and I got an answer. Cool. And then I asked the same question again and added, “Respond in, in this case, German.” The answer that I got in German was, obviously, it was in German, step one, which I wasn’t actually sure it could do. But step two, the reply that I got in German, the content was different. It wasn’t just a translated version of the English content. It was functionally a different answer. So it’s like in English, I said to ChatGPT, “What color is the sky?” And it said, “The sky is blue.” And then I said the same thing, “What color is the sky? Respond in German,” and it came back with, “The sky is green.” Now, it was actually did a DITA-related question, which kind of explains what happened here. But what happened was that ChatGPT, even though the prompt was in English, it pretty clearly used German language sources to assemble the answer. And those of you who know that DITA is more popular in the US than it is in Germany would not be too surprised that the answer I got regarding something DITA-specific in German was very much culturally bound to what German language content about DITA looks like. So it was processing the German content to give me my answer, not the English content. Now, if you ask an AI help system, the next question is what’s sitting in that corpus? Because if you ask it a question in French and it has no French in the corpus, then it’s probably going to generate an answer in English and machine translate. But if it has four topics in French and you ask it something in French, it is probably going to try and assemble an answer out of that French content, which could be…

BS: Before it falls back, yeah.

SO: Fascinating, which brings me to my next meta question that we’re not going to answer, which is can we capture meaning and separate it from language? And a knowledge graph is an attempt to capture relationships and meaning. And that can be rendered into a language, but it is not itself specifically English. It’s a database entry of person, which has a relationship with address, and you can say, “Person X lives at address Y,” but that sentence is just an expression of the mathematical or the database relationship that’s sitting inside the knowledge graph. I want to talk about the outlook for LSPs, for localization services providers. What does it look like to be an LSP, to be a translation service provider, in this AI world? What do you think is going to happen?

BS: I think it goes without saying that there’s going to be disruption again. Every single change, whether it’s in the localization industry or not, has resulted in some type of disruption. Something has changed. I’ll be blunt about it. In some cases, jobs were lost, jobs were replaced, new jobs were created. And I think that for LSPs, I think AI is going to, again, be another shift, the same that happened when machine translation came out, when neural machine translation came out, all of this. They’ve had to shift and pivot of how they approach their bottom line with people. GenAI is going to take a lot of the heavy lifting off of the translators, for better or for worse, and it’s going to force a more copy edit workflow. And perhaps, I guess, a corpus editing role or basically an information keeper who basically will go in and make sure that the information that the AI model is being trained on is correct and accurate for very specific purposes, and start teaching it that when you talk about this particular subject matter, this is the type of corpus we want you to consume and respond with, versus someone who actually does the translation work and pushes all the buttons and writes all of the translations. It’s really going to be a model where I think people are going to be training AI and cleaning up after it, essentially. And I don’t know any further than that. I mean, it’s still pretty young. I think also you will see LSPs turning more into consultative agencies with companies, rather than just a language service provider. So they will help companies establish that corpus and train their AI and work with their corporate staff to make sure that they are writing better queries, that they are providing better information out of the gate, and so forth. So I think it’s going to be a complete shift in how these companies function, at least between now and what’s to come.

SO: Yeah. The cost of a really bad translation getting into your database when it was human-driven… this AI thing is going to scale. There’s going to be more and more of it, everything’s going to go faster and faster. And we already have these conversations about AI slop and the internet degrading into just garbage because there’s all this AI-created stuff. And so if you apply that vision to a multilingual world, it’s quite troubling, right? So I think you’re right. I mean, this idea of content hygiene. How do we keep our content databases good, such that they can do all this interesting math processing instead of becoming more and more and more and more error-riddled is really interesting. We started by saying clearly this is a disruptive innovation. Disruptive innovations start out bad, clearly of lower quality than the thing they’re disrupting, but they’re cheaper and/or faster and/or have some aspect that they can do that the original thing cannot. So mobile phones are a great example. They were worse than landlines in every possible way, but they were mobile, right? They were not tethered to a cord in the wall. And then over time, a mobile phone turned into something that really is a computer that is context and location-aware and can do all sorts of nifty things. It doesn’t look at what resemblance it bears to POTS, to plain old telephone service. And we hear people. Oh, I don’t use my phone to make phone calls. Why would I do that? That’s terrible, because we have all these other options.

So from a localization point of view, any organization that is using person-driven, manually-driven, inefficient, fragmented processes is going to be in trouble. And that stuff’s all going to get squeezed out. And I think it’s actually helpful to look at the structured authoring concept and how it eliminated desktop publishing, right? It just got squeezed right out because it all got automated. We do the same thing with localization. I think AI is going to have a similar impact, whether it’s on content creation in any language, that it’s going to remove that manual labor over time. And I think that maybe we’re going to reach a point where content creation is just content creation. It’s not creating content in English so that I can translate it into the target languages. I think that that distinction between source and target is really going to evaporate. It’ll just be somebody created content, and then we have ways of making that available in other languages, and that’s where this is going to go. I’ve talked to a lot of localization service providers recently, and certainly this is one of the things that they are thinking about and looking at, is the question of what it means, to your point, to be a localization service provider in a universe where language translation specifically is automatable, maybe. Okay. Bill, any closing thoughts before we let you go here?

BS: I think this is a good place to end this one.

SO: We’ll wrap it up, and they will come and take away our microphones and put us back in the corner. Good to see you, as always.

BS: Good to see you.

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post AI in localization: What could possibly go wrong? (podcast) appeared first on Scriptorium.

Sarah O’Keefe: But what’s actually being said is AI will generate your presentation for you. If your presentation is so not new, if the information in it is so basic that generative AI can successfully generate your presentation for you, that implies to me that you don’t have anything interesting to say. So then, we get to this question of how do we use AI in learning content to make good choices, to make better learning content? How do we advance the cause?

Related links:

• Synthetic audio example: Strategies for AI in technical documentation (podcast, English version)
• LearningDITA: DITA-based structured learning content in action (podcast)
• How CompTIA rebuilt its content ecosystem for greater agility and efficiency (webinar)
• Transform L&D experiences at scale with structured learning content (podcast)
• Overview of structured learning content
• Get monthly insights on structured content, futureproof content operations, and more with our Illuminations newsletter

LinkedIn:

• Sarah O’Keefe
• Alan Pringle

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Alan Pringle: Hey everybody, I am Alan Pringle, and today I’m talking to Sarah O’Keefe.

Sarah O’Keefe: Hey everybody, how’s it going?

AP: And today, Sarah and I want to discuss artificial intelligence and learning content. How can you apply artificial intelligence to learning content? We’ve talked a whole lot, Sarah, about AI and technical communication and product content, let’s talk more about learning and development and how AI can help or maybe not help putting together learning content. So how is it being used right now? Let’s start with that. Do you know of cases? I know of one or two, and I’m sure you do too.

SO: Yeah. So the big news, the big push, is AI in presentations. So how can I use AI to generate my presentation? How can it help me put together my slides? Now, the problem with that from our point of view, for those of you that have been listening to what we’re saying about AI, this will be no surprise whatsoever, I think this is all wrong. It’s the wrong strategy, it’s the wrong approach. If you want to take AI and generate an outline of your presentation and then fill in that outline with your knowledge, that’s great, I think that’s a great idea. Also, if you have existing really good content and you want to take that content and generate slides from it, I don’t have a problem with that. But what’s actually being said is AI will generate your presentation for you. If your presentation is so not new, if the information in it is so basic that generative AI can successfully generate your presentation for you, that implies to me that you don’t have anything interesting to say.

AP: And you’re going to say it with very pretty generated images and a level of authority that makes it sound like there’s something that’s actually there when it’s not.

SO: Oh, yeah. It’ll look very plausible and authoritative and it will be wrong, because that’s how this generative stuff-

AP: Or not even wrong, surface-skimmy, just nothing of any real value there.

SO: Yeah. So then, we go into this question of, how do we use AI in learning content to make good choices, to make better learning content, how do we advance the cause?

AP: Well, there’s that one case where we have done it, because we have our own learning site, LearningDITA.com, and we were trying to think about ways to apply AI to our efforts to create courses, to tell people how to use the DITA standard for content. And I think you and I both agree, one of the strengths of artificial intelligence is its ability to summarize and synthesize things, I don’t think that’s controversial. So if you think about writing assessments from existing content in a way that’s summarizing, so one of us suggested to our team, why don’t y’all try that and see what these AI engines can do to generate questions from our existing lesson content. And then, of course, we suggested that they—the people who were creating the courses—review them. So our folks reviewed them, and I think some of the questions were actually quite usable, decent.

SO: And some of them were not.

AP: True, this is true.

SO: But the net of it was they saved a bunch of time, because they said, “Generate a bunch of assessment questions,” they went through them, they fixed the ones that were wrong, they improved the ones that were maybe not the greatest, they got a couple that were actually pretty usable. And so, it took less time to write the assessments than it would’ve taken to do that process by hand, to slowly go through the entire corpus to say, “Okay, what are the key objectives and how do I map that to the assessments?” So that’s a pretty good example, I think, of using generative AI, as you said, to summarize down, to synthesize existing content. On the LMS side, so when we start looking at learning management systems and how the learning content goes into the LMS and then is given or delivered to the learner, there are some big opportunities there, because if you think about what it means for me as a learner, as a person taking the course, to work my way through course material, maybe the assumptions that the course developer made about my expertise were too optimistic. I’m really struggling with this content, it’s trying to teach me how to use Photoshop and I am just not good at Photoshop. There’s this idea of adaptive learning, this is not an AI concept, the idea behind adaptive learning is that if you’re doing really well, it goes faster. If you’re struggling, it goes deeper, or maybe you do better with videos than you do with text, or vice versa. It’s that adapt to the learner and to the learner’s needs in order to make the learning more effective. Now, if you think about that, that is a matter of uncovering patterns in how the learner learns and then delivering a better fit for those patterns. Well, that’s AI. AI and machine learning do a great job of saying, “Oh, you seem to be preferring video, so I’m going to feed you more video.” Now, we can do this by hand or we can build it in with personalization logic, but you can also do this at scale with AI and machine learning. So there are definitely some opportunities to improve adaptive learning with an AI backbone.

AP: I think it’s worth noting at this point, when you’re talking about gathering the data to make, I hate to, I’m going to personalize AI, so it can make these decisions or do the synthesis, there’s got to be intelligence that’s built into your content, and that goes all the way back to the content creation, going back from the presentation layer, back to how you’re creating your content. And again, this loops back, in my mind, to the idea of building in that intelligence with structured content, that is your baseline.

SO: Yeah. I know we’re just relentless on this drum of you need structured content for learning content, but it’s because of all these use cases, because as you try to scale this stuff, this is what you’re going to run into. I also see a huge opportunity for translation workflows specifically for learning content. So if you look at translation and multilingual delivery, there’s a lot of AI and machine learning going on in machine translation. So now, we think a little bit about what that means for learning content, and of course, all of the benefits that you get just in general from machine translation still apply, but the one that I’m looking at that I think would be really, really interesting to apply to learning is learning has a lot of audio in it, audio and video, but specifically audio, and audio typically is going to be bound to a language. You’re going to have a voiceover, you’re going to have a person saying, “Here’s what you need to know, and I’m going to show you this screenshot,” or, “I’m going to show you how to operate this machine.” And so, you’ve got audio and potentially captions that are giving you the text or the audio that goes with that video. Okay, well, we can translate the captions, that’s relatively easy, but what about the voiceover? And the answer could be that you do synthetic voiceovers. So you take your original, let’s say, English audio and you turn it into French, Italian, German, Spanish or whatever else you need, but you synthesize the voice instead of re-recording. Now, is it going to be as good as a human, an actual human person who has expression and emotion in their delivery? No. Is it better than the alternative where you don’t provide it in the target language at all? Probably, yes. And when we start talking about machines, “Here is how to safely operate this machine,” the pretty good synthetic voice in target language is probably better than, “Here it is in English, deal with it,” or, “Here it is in English with a translated caption in German, but no audio.” I think that’s what we’re looking at is, is the synthetic audio good enough that it will improve the learner experience, and I think the answer is yes.

AP: I’m turning this over in my mind, and there’s part of me that’s very resistant to the idea of these synthesized voices. For example, and this is bias on my part, when I am downloading audiobooks from the library, they now, in the app that I use that’s connected to the local library, a lot of the narration, it will say, “This is an AI-generated voice.” I tend to avoid those, I do, because sometimes the inflection’s a little odd, there’s no personality there. However, I can buy that having that slightly robotic-esque voice in another language is better than not having it at all, I can buy that.

SO: Right. And I think the audiobooks that we listen to for fun are different than I need to figure out how to use this machine without hurting myself, those are different, and I don’t need a… It wouldn’t hurt. I don’t need a personable obviously human voice to voiceover the video that helps me figure out how to use this thing on the factory floor. I wouldn’t object, but I would prefer to get something in my language. That’s really the key, because when we start asking the question, the question is less, would you prefer a really good artistic performance voiceover versus a robotic voice… That’s what you’re getting from the library, you’re saying, I am not going to consume entertainment content that is like this, and I think a lot of people are onboard with that. But what about technical product and learning content that you need? You’re not making a choice that this is something I want to do in my downtime, but rather, if I can’t figure out how to do this, bad things will happen.

AP: Yeah. There is a legitimate use case there, and they’re two different things, and I do think, based on some of the synthetic voices I’ve heard, they are getting better, quite better, and sounding a little more realistic as well.

SO: Right. We’ve already experimented with this. We have a podcast where we actually generated, it was a synthetic voice, but it was based on a person’s voice print. So it wasn’t fake AI, it was fake AI voice, but it was fake AI voice generated off of a specific person. The audio is quite good. Every once in a while between paragraphs, it shifts weirdly as you’re listening, as a new thought is introduced, and it shifts in ways that a human would not, but all in all, I thought it was pretty acceptable. So I think that what I’m trying to say in an extremely long-winded way is that when you have scalability issues in your content production, learning content or otherwise, AI has the potential to help you with productivity across multichannel workflows with repurposing content from it’s the learning content versus it’s the assessments, it’s in language A versus language B, it’s audio, it’s video. There are things that we can do there to use the AI tools for productivity to support these workflows and scale them, and to your point, and therefore, we need underlying structured content. We can’t do this with slapped-together one-off formatted mess.

AP: Yeah. The intelligence has to be built in at the very foundation, and that is when you are creating the content. That intelligence really can’t be a layer that’s put on when you transform things or you connect to an LMS, it’s not a presentation layer thing. The presentation layer needs to pull that intelligence from your source content. Again, this is why you need structured content, the metadata built in, to help drive the way you transform and distribute your learning content.

SO: Yeah. I’m, again, very skeptical of GenAI in the process of generating net-new content, new information, nobody’s ever written it before, it’s a new product, it needs to be explained, taught, whatever. Maybe an outline, this is what a typical intro course looks like, now go fill in the details, okay, maybe even a first draft, especially if product A is based on product B, or I guess the other way around. But our world is structured content, obviously, but also our world is content where it matters that the content is accurate, because when the content is wrong, bad, bad things happen, people get hurt, people die, companies get shut down for compliance reasons, that type of thing. So the content has to be accurate, and at the end of the day, it’s actually quite difficult to get GenAI to gen accurate content. That’s not what it does; that’s not its function. So I’m very interested in applying AI to various product and content roadmaps to enable productivity, to enable new deliverables, to enable new synthesis summaries, et cetera, but I’m very, very worried about what happens if you apply it on top of bad content or you apply it to the wrong use case in an effort to just get your stuff for free, essentially.

AP: So what I’m hearing in summary is that content creation for learning, AI is probably not a good fit now. To support you and help you possibly develop on the edges of that content or give you outlines and ideas, and also to augment and support delivery channels, it could be helpful. So it’s a support mechanism for the development of the content, distribution of the content, but not necessarily for the direct creation of that content.

SO: Yeah, I think that’s fair, and I think that’s where we land. I’d be quite curious to hear from our listeners, what they’re doing with this and where they’re going with it.

AP: And I’m sure people are having the same struggles right now over the best way to apply it. But I think right now, as of the moment that we’re recording this, AI is in no way ready for prime time to basically take the place of a learning content person. It should be there to support them, not to replace them.

SO: Yeah, for meaningful content.

AP: Exactly.

SO: And if it’s not meaningful, what are you even doing?

AP: Right.

SO: Well, that’s cheery, okay.

AP: And on that very cheerful note, we’re going to wrap up. So thank you, Sarah. And folks, do get in contact with us to let us know how you’re using AI, because that is of great interest to us. So thank you. Thanks, Sarah.

SO: Thank you. And maybe let us know how you’re being made to use AI.

AP: That too. Thanks, everyone.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Questions about this podcast? Let’s talk!

The post Help or hype? AI in learning content appeared first on Scriptorium.

Bill Swallow: On paper, it looked like a perfect solution. But everyone, including the people who greenlit the project, hated it. Absolutely hated it. Why? It was difficult to use, very slow, and very buggy. Sometimes it would crash and leave processes running, so you couldn’t relaunch it. There was no easy way to use it. So everyone bypassed using it at every opportunity.

Alan Pringle: It sounds to me like there was a bit of a fixation. This product checked all the boxes without actually doing any in-depth analysis of what was needed, much less actually thinking about what users needed and how that product could fill those needs.

Related links:

• How humans drive content operations (recorded webinar & transcript)
• Brewing a better content strategy through single sourcing (podcast)
• The Scriptorium approach to content strategy
• Get monthly insights on structured content, futureproof content operations, and more with our Illuminations newsletter

LinkedIn:

• Alan Pringle
• Bill Swallow

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Bill Swallow: Hi, I’m Bill Swallow

Alan Pringle: And I’m Alan Pringle.

BS: And in this episode we’re going to talk about the pitfalls of putting solutioning before doing proper analysis. And Alan, I’m going to kick this right off to you. Why should you not put solutioning before doing proper analysis?

AP: Well, it’s very shortsighted and oftentimes it means you’re not going to get the funding that you need to do the project to solve the problems that you have. And with that, we can wrap this podcast up because there’s not a whole lot more to talk about here, really. But no, seriously, we do need to dive into this. It is very easy to fall into the trap of taking a tool’s first point of view. You’ve got a problem, it’s really weighing on you. So it’s not unusual for a mind to go, this tool will fix this problem, but it’s really not the way to go. You need to go back many steps, shut that part of your brain off and start doing analysis. And Bill, you’ve got an example, I believe, of how taking a tool’s first point of view didn’t help back in a previous job you had.

BS: I do, and I’m not going to bury the lead here, but they didn’t do their homework upfront to see how people would use the system. So I worked for a company many, many, many years ago that decided to roll out and I will name the product. They rolled out Lotus Notes.

AP: You’re killing me. That’s also very old, but we won’t discuss that angle.

BS: But they did so because it checked every single box, every single box on the needs list, it did email, it had calendar entries, it did messaging, notes, documents, linking, sharing, robust permissions, and you even had the ability to create mini portals for different departments and projects. So on paper, it looked like a perfect solution. And everyone, including the people who greenlit the implementation of Lotus Notes, hated it. Absolutely hated it. Why did they hate it? It was difficult to use. It was very slow. It was very buggy. Sometimes it would crash and leave processes running, so you couldn’t relaunch it. There was no easy way to use it. Back at that point, we had PDAs, personal digital assistants, and very soon after that we had the birth of the smartphone. There was no easy way to use it in these mobile devices except for maybe hooking up to email. It didn’t fit how we were working at all. While it shouldn’t count, it really wasn’t very pretty to look at either. So everyone bypassed using it at every opportunity. They would set up a Wiki instead of using the Lotus Notes document or notes portal that they had. They would use other messaging services. This is back during Yahoo Messenger and ICQ. But yes, we had that going on and in the end it was discontinued after its initial three-year maintenance period ended because nobody liked it.

AP: Yeah, so sounds to me like there was a bit of a fixation. This product checks all the boxes without actually doing any in-depth analysis of what you needed, much less actually thinking about what users needed and how that product could fill those needs. And I think it’s worth noting too, think about this from an IT department point of view, because they’re often a partner on any kind of technology project, especially if new software is going to be involved because they’re going to be the ones a lot of times that say yay or nay, this tool is a duplicate of what we already have. Or no, you have some special requirements and we do need to buy a new system. So if I as an IT person, the person who vets tools hears from someone, and let’s get back into the content world, I need a way to do content management and I need to have a single source of truth and I need to be able to take the content that is my single source of truth and then publish to a bunch of different formats. This is a very common use case. I would be more interested as an IT person in hearing that than hearing I have to have a component content management system. There’s a subtle difference there. And I think, and this is possibly unfair and grouchy of me, but that is me, grouchy and unfair. If I hear someone come to me, I need this tool instead of I have these issues and I have these requirements. It sounds selfish and half-baked.

BS: It does.

AP: And again, I am thinking about this from the receiving end of these queries, of these requests, but I also want to step back into the shoes of the person making a request. You can be so frustrated by your inefficiency and your problems, you latch onto the tools. So I completely understand why you want to do that, but you are basically punching yourself in the face when you go and make a request that is, I need this tool instead of I have these issues, these requirements, and I need to address these things. It’s subtle, but it’s different.

BS: It’s very different. And also if you do take that approach of looking at your needs, you find that there’s more to uncover than just fixing the technological problem itself.

AP: Yes.

BS: There might be a workflow problem in your company that you may acknowledge, you may not know it’s quite there. Once you start looking at the requirements and looking at the flow of how you need to work, and how you need any type of new system to work, you start seeing where the holes are in your organization. Who does what? What does a handoff look like? Is it recorded? What does the review process look like? When does it go out for formal review? What does the translation workflow look like? And you start seeing that there may be a lot of ad hoc processes in place currently that could be fixed as well.

AP: True. And I also think when you’re talking about solving problems and developing your requirements from that problem solving, you are potentially opening up the solution to more than just your department, your group. It can possibly be a wider situation there, too. And also by presenting it as a set of problems and requirements to address those problems, there may be already a tool in-house at your company that you don’t know about or there may be part of a suite of tools, and if you add another component to it will address your problem instead of just buying something completely outright. And we’ve seen this before, where it turned out there was an incumbent vendor that had some related tools already at the company, and that company also had a tool that could solve the problems that our client had or our prospect had. We’ve had both prospects and clients have this issue, so it doesn’t make sense, therefore, to go and say, I need this tool, which is essentially a competitor of what’s already in place. You’re going to have a very uphill battle trying to get that in place. It is also very easy, as someone who has already done a content ops improvement project, to understand this tool is good. It saves me at this company, but you’ve got to be careful of thinking just because it helped you over at company A. Now you’re at company B, it may not be a fit for company B culturally, there may be already something in-house. So you’ve got to let go of those preconceived notions. I am not saying that the tool you used before was bad. It may be the greatest thing ever, but there may be cultural issues, political issues, and even IT tech issues that mean you cannot pick that tool. So why are you pushing on it when you have got all of these things against you? Again, it is easy to fall into these traps. Don’t do it.

BS: Yep. On the flip side of that, we had a situation where a customer of ours years ago was looking for a particular system, a CCMS, component content management system, and they had what they perceived to be a very hard requirement of being able to connect to another very specific system.

AP: Yes, I remember this. It was about 10 or 11 years ago.

BS: And it was such a hard requirement that it basically threw out all of their options except for one. And we got the system working the way they needed it to. It needed quite a bit of customization, especially over the years as their requirements grew. But in the end, they never connected to that requirement system. The one that everyone said this would be a showstopper. They never connected to it because they just decided it wasn’t a requirement after X many years. And that just kills me because there could have been three or four other candidate systems that would’ve easily have fit the bill for them as well and probably would’ve cost them a little bit less money. But there we are.

AP: In fairness, all parties involved, including us, we’re working on the information that we had at the time. And I think this is a case where a requirement that we thought was a hard requirement turned out not to be. However, just because this happened in this case, folks out there listening to us, that does not mean that if a particular requirement points at a particular system that it could be not a real requirement because you want another system really badly. So you want to ignore that really hard, not how that works. It’s not how that should work. So I think there is a balance here that needs to be struck, and I think this is probably a good closing message. Don’t follow your knee-jerk instinct in regard to, I need this tool. Really look at the requirements, do an analysis. And because we’re humans, sometimes that analysis is not going to catch other things that it should have. Or you may end up having, like you just mentioned, a requirement that that’s not necessarily as real as you thought that it was. But I think your chance at project success and getting a tool purchased can configure and up and running are much higher when you start with those requirements than you start off with, I need tool Y.

BS: Well said. Do the homework before the test.

AP: And don’t put the cart before the horse.

BS: Well, thank you, Alan.

AP: Thank you. This was shorter, but it’s an important thing, and I think, again, this points to any kind of operational change being a human problem and dealing with people’s emotions and their instincts as much or more than an actual technological issue.

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

Need to talk about content solutioning? Contact us!

The post Tool or trap? Find the problem, then the platform appeared first on Scriptorium.

When we deliver the content, whether it’s through the APIs or the portal that you’ve built that is served by the platform, we render the content in a way that we can dynamically remove or hide parts of the content that would not apply to the context, the profile of the user. That’s the magic of a CDP. It’s delivering that content dynamically.

— Fabrice Lacroix

Related links:

• Scriptorium: Personalized content: Steps to success (white paper)
• Scriptorium: AI in the content lifecycle (white paper)
• Fluid Topics, an AI-powered content delivery platform
• Fluid Topics: What is Content Operations and Why is it Important?
• Get monthly insights on structured content, futureproof content operations, and more with our Illuminations newsletter

LinkedIn:

• Sarah O’Keefe
• Fabrice Lacroix

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Sarah O’Keefe: Hi everyone, I’m Sarah O’Keefe and I’m here today with the CEO of Fluid Topics. Fabrice, Lacroix. Fabrice, welcome.

Fabrice Lacroix: Hey. Hi Sarah. Nice being with you today. Thanks for welcoming me.

SO: It’s nice to see you. So as many of you probably know, Fluid Topics is a content delivery portal or possibly a content delivery platform. And we’re going to talk about the difference between those two things as we get into this. So Fabrice, tell us a little bit about Fluid Topics and what that content delivery portal or maybe platform. Which one is it? What do you prefer?

FL: For us, it’s platform definitely. But you’re right, depends on where people are in this evolution process, on how they deliver content. And for many, many customers, the piece stands for a portal. You’re right, because that is the first need. That’s how they come to us, because they need a portal.

SO: Okay, so in your view, the portal is a front end, an access point for content, and then what makes it a platform rather than a portal?

FL: Probably because the goal that many companies have to achieve is delivering that content where it’s needed. It’s many places most of the time. So it’s not just the portal itself, and that’s where solving the problem of being able to disseminate this content to many touch points, you need a platform for that. The portal is one touch point only, but when you start having multiple touch points like doing in-product help or you want to feed your helpdesk tool or field service application or whatever sort of chatbot somewhere else, whatever use case you have that is not just the portal itself, then that becomes a platform thing.

SO: So looking at this from our point of view, so many of our projects start with component content management systems, CCMSs, which are the back end. This is where you’re authoring and managing and taking care of all your information, and then you have to deliver it. And one of the ways that you could solve your delivery front-end would be with a content delivery platform such as Fluid Topics. Okay. So then, what are the prerequisites, when you start thinking about this? So our hypothetical customer has content obviously, and they have, we’re going to say probably a back-end content management system of some sort, probably.

FL: Most of the time.

SO: Most of the time.

FL: Depends where you go, depends on the maturity and the industry. If you go to some manufacturing somewhere, they mostly still are maybe on the word and FrameMaker or something like that in design, and then they generate PDFs.

SO: So maybe we have a backend authoring, well, we have an authoring environment of some sort on the back-end. Maybe it’s a CCMS, maybe it’s something not like that. And now we’re going to say, all right, we’re going to take all this content that we’ve created and we’re going to put it into the CDP, the content delivery platform. Now, what does success look like? What do you need from that content or from the project to make sure that your CDP can succeed in doing what it needs to do?

FL: The first answer to that question that comes to my mind is no PDFs. I mean, if you look at it, don’t laugh at me. If you look at it from an evolutionary perspective, it’s like regardless how people were writing before, it was not CCMS, mostly unstructured. And at the end of the day, people were pressing a button and generating PDFs and putting the PDF somewhere, CRM, USB key, website for download. But managing the content unstructured was painful. That’s where you start working with the CCMS, because you have multiple versions, variants, you want to work in parallel, you want to avoid copy paste, translation, so the story around that. So then companies start and they start moving their content into CCMS. All of the content, part of the content, but they start investing in a modern way of managing, creating their content. But again, if you look at it once they have made that move, most of those companies 10, 15 years ago probably were still pressing a button and still generating PDFs. And then they realized that they had solved one problem for themselves, which is streamlining the production capability and managing the content in a better way. But from a conception perspective, regardless whether you work with word FrameMaker or in DITA with the most advanced CCMS of the market, if you still deliver PDF, you are not improving the life of your customers. And then people started realizing that, oh yeah, so we should do better. So let’s try to output that content in another way than PDFs. And then say, “What else than PDF, do we have? HTML.” And was like, okay, and let’s output HTML. But HTML that is pretty much the same as the PDF. You see what I mean? It’s like static document. Each document was a set of HTML pages. And then they started realizing that they need to reassemble the set of HTML pages into a website, which is even more painful than just putting PDFs on the website is reassembling zip files of HTML pages on the website, and then it’s like static HTML. And then you have to put a search on top and have to create consistency. And that’s why CDP have emerged. That’s solving this need, which is, how do we transition from PDF to static HTML to something that is easier, that ingest all this content, comes with search capabilities, comes with configuration capabilities, and as well at the same time as API, so that back to the platform thing, it’s not just a portal, but can serve other touch points. So that’s really because we are in the detail world, DITA is the Darwin Information Typing Architecture. So that’s a very Darwinian process that led to this creation of the CDP and the need of a CDP is the next step in the process. And many companies really follow that process of, I have to go from my old ways of writing, which are not working painful, move to a CCMS, but in fact realize that they don’t solve the real problem of the company, which is how can I help my customer, my support agent, my field technicians better find the content better use my content? And that’s where this T, oh, okay. That’s where we need a CDP.

SO: Yeah, and I think, I mean, we’ve talked for 20 years about PDFs and all the issues around them, but it’s probably worth remembering that PDF in the beginning was a replacement for a shelf of books, paper books that went out the door. And the improvement was that, instead of shipping 10 pounds, or I’m sorry, what four kilos of books you were shipping as you said, a CD-ROM or this was before USB, a zip drive. Remember those?

FL: Zip drive.

SO: A zip drive. But you were shipping electronic copies of your books and all you were really doing was shifting the process of printing from the creator, the software, hardware, the product company to the consumer. So the consumer gets a PDF, they print it, and then that’s what they use. Then we evolved into, oh, we can use the PDF online, we can do full-text search, that’s kind of cool, that was a big step forward. But now to your point, the way that we consume that information is not printed and it’s for the most part, and it’s not big PDFs, but rather small chunks of information like a website. So how do we evolve our content into those websites? So then what does it look like to have a, and I think here we’re talking about the portal specifically, but what does it look like to have a portal for the end user that allows them to get a really good experience in accessing and using and consuming the content that they need to use the product, whatever it may be. What are some of the key things that you need to do or that you can do?

FL: Yeah. I would say that the main thing that a CDP is achieving compared to static HTML, because now we have to compare not with PDFs that are probably still needed if you want to print as well, I’m not saying that PDF is dead and we should get rid of all PDFs. Just said that it’s just when you need to print, then you can get the PDF version of a document. But if we compare static HTML with what a CDP brings, we’re trying to make content personalized and contextual. If you pre-generate static HTML pages, it’s one size fits all. It’s the same HTML pages for everyone. And if you have two versions of your product and one variant, and then you translate the same zip file exists in 20 versions, so to say, and you have to assemble that and let people understand how to navigate that and that should become super complex. What a CDP solves is like, give me everything, and I will sort out this notion of I understand the fact that the same document can exist in 20 variants, whether it’s product version, document version, capabilities of the product version A, version, B, Asian market, European market, American market. And then you have subtilities and some paragraphs are here, some paragraphs are removed, added. And so we are adapting the content so that it fits the profile of the user. And if you ask me what’s needed to make a CDP work, it’s mostly metadata, metadata, metadata. And I can tell you a story, what was fun? It’s like, few years ago, some years ago, more than few, we had customers reaching out or expecting customers to reach out and say, “Oh, show me three topics.” And then we’re showing the capability and say, “Oh my God, it’s exactly what we need.” And then those guys disappeared for two years. And in fact, what they did during these two years is like adding metadata to the content. It was not about the product, but through this discussion we had with them and showing that you can put facets for the search and then varianting content and let people switch between variants and versions of the content through metadata and all that, and they realized that, oh my God, that’s exactly what we need. And then through their questions, they understood that they needed to have those metadata on the content and those metadata were not existing and still they were working with the CCMS. But if your output channel are PDFs, if you don’t put PDFs, you don’t care about putting this metadata on the content inside the CCMS. That’s a lot of work to do to maintain those metadata. But if at the end of the day you print a button and you generate a PDF, those metadata are lost, they are not used, they’re not leveraged by the PDF. So that becomes flat pages of content. So they had transitioned to a CCMS but never made this investment of tagging content. And when I mean tagging content, it’s not just the map, it’s like the section, the chapter, this is for installing, this is for removing, this is for configuring, this is for troubleshooting, this chapter is about this, this topic is about that for this version of the products. You know what I mean? Fine-grained tagging at different level of the documents. And because they were generating PDFs, they didn’t see the need of making that tagging at the right level, and they realized that suddenly the sheer value they could get from PDF is when the content is tagged because that’s using those tags and those metadata schemes that the CDP can adapt the content to the context profile of the user. So I would say, what’s needed to leverage the capabilities of a CDP? It’s mostly granularity of content and tags, metadata that let people, and you can design your metadata from a user perspective. As an end user, how would I like to filter the content? What are the tags I need for filtering the content? It’s like, if I run a search, I have these facets on the left side of the search result page, what would I like to click on to refine my search and spot the content that fits my needs?

SO: And I think, going back to our flat file PDF or static HTML, if we need to do this kind of thing, if you need context in a flat file, what you have to do is say something like, if you have product variant A, do this. And if you have product variant B, do this. Or if you are installing and the temperature, the ambient local temperature is greater than X, then do these extra steps. If you are baking and you are at high altitude, you have to adjust your recipe in these ways. So you end up with all these sort of if statements that are, hey, if this is you do these things, but it’s all in the text, because I have no way, maybe I can do two variants of the PDF like variant A for regular altitude and variant B for high altitude. But I can’t do one per country, right? I mean, I guess I could, but ultimately, what you’re describing is that instead of putting it into the text explicitly, “Hey Fabrice, if you meet these conditions, do these things or don’t do these things or do these extra things,” the delivery portal, platform is going to say, “Okay, what do I know about this end user? What do I know about Fabrice? I know he is in a certain location with a certain preferred language and a certain product. I know which products you bought.” So therefore you don’t get an if, if, if, if, you just get, here’s what you need to do in your context with your product.

FL: Exactly. When we deliver the content, whether it’s through the APIs or the portal that you’ve built and that is served by the platform, we render the content in a way that we can remove or hide dynamically parts of the content that would not apply to the context, the profile of the user. And that’s the magic of CDP. It’s making that content dynamically. It’s also called dynamic content delivery. You remember we had this concept, the dynamic part is, how can I dynamically leverage the metadata on the content side or the conditions that I adapted, read through metadata schemes and make that applicable to the situation and the user profile? So that’s the magic part of it, and that’s a huge improvement compared to a static document that lists all the conditions and then you put the burden on the reader to figure out, sort out inside the document what should be skipped and what to do depending on the product configuration.

SO: Which can of course get very complicated. Now you mentioned product help, in-app help, context sensitive help. So what does it look like to use a Fluid Topics or this class of tool to deliver context sensitive help or in-app help?

FL: We are back again to this granularity and the metadata. So imagine you are a software vendor, you design a web application that you have created and you want to do the inline help for your application, your web product. What would you do? You would say in that page, when people click on that question mark or help button, we should open a pane and display that information. That information needs to be a topic, it needs to be written, and the granularity should be a topic because that’s what you pull from the system. So that’s where we need the granularity that’s matching what you want to display inside your app, whether it’s a tool tip, maybe a small tool tip when you move something in the app and then that becomes some fragment of content you need to get from the CDP dynamically. That can be one page of explanation that you display in a pane that opens in your app, but you need to pull that content. So the same way that that’s how you would do it, you were embedding the content inside the application itself. You would write each part of the explanation, the help that you want to display as fragments of information. If you are doing it statically inside the application, but the problem is that if you want to fix something or enhance the content, you have to edit the application, change the… So it’s part of the development. Here, you want the app to pull the content dynamically because the same content can be not only used to be displayed live in the screen, real time. But can be the same content that is used on the doc portal or then you print a PDF on how to do this. That’s the same. You don’t want to maintain the same explanation, in the application, in the portal, in PDFs. So one source. So it’s exactly that. And then you’re pulling through metadata. The app will say, “Oh, give me what goes into that page.” So it’s metadata-driven as well.

SO: Right? So there’s an ID on the software or something like that, and it says, “Give me the content that belongs with this unique label.”

FL: Exactly. Behind each button you give an ID to that button, which is the question mark in that page. When people click pull content, inline content help, ID number 1, 2, 3, 4. And on your CCMS, you have a metadata, which is called content ID for inline help, whatever. And then you tag that piece of content, 1, 2, 3, 4, and then that’s it. Magic is done. So it’s that simple.

SO: So what I’m hearing, and this is in fairness, exactly what you started with is, you have to have metadata, right? On the content.

FL: You have to have metadata.

SO: And without the metadata there is, well, let’s talk about magic. So if you have a front end that is some sort of a large language model that bought something, what does that mean in terms of this content delivery platform? I mean, can’t you just use ChatGPT and call today?

FL: Yes, that’s a good one. I think most of the project AI project we’ve seen in large companies when they started to do, oh, let’s build a chatbot. That’s the magic dream of any company like building the chatbot that replies to any question. Okay, so how does the project start usually? You have the IT, some people in the IT team or the IT team is hiring external people specialized in AI and they realize that they need content. So the first thing they do is they come usually to the TechDoc team and say, “Give me all the content that you have.” And the TechDoc team says, “Okay, we have all these DITA contents.” You say, “No, I don’t want DITA, I want PDFs.” That’s huge to see that. Why? Because they use technology like something from Microsoft, you can build your chatbot in five minutes, but then the only content types you can fit this ready to use platform is with PDFs and Word. So all the magic you’ve put in your content and the tags are lost and you see people getting PDFs out of you wanting PDFs from your content, which is the exact opposite of the investment you’ve made. Putting PDFs somewhere on the storage place and say to Microsoft Chatbot, blah, blah, this is the content, this is the knowledge of the company. And then when you have 20 variants of the same product, then no metadata anymore. Then the chatbot is always mixing all the content. And when you start asking real questions about how to do this, how to do that with this version of the product, everything is lost. And then the chatbot start hallucinating, not because the LLM is hallucinating, because the LLM just the system, the chatbot does not know what PDF to use because it’s implicit to know that this PDF applies to that version of the product or that version. It’s even worse if you say, “If you have product A, do this, if you have product B, do that and start mixing conditions and then just the knowledge becomes barely readable by humans that make mistake reading it. So can you imagine how an LLM can make sure that it’s putting the right information from that complex text structure?

SO: Okay, so make PDFs out of DITA, dumb it down, send it to the chatbot, that’s bad.

FL: And then it’s guaranteed failure.

SO: So what’s the good version of this?

FL: But that’s how it works. I guess, I write that you’ve seen this sort of projects where people were asking for the content, thinking that the more they have, the better it’s going to be. And suddenly they realize that, that chatbot is not working and doing many mistakes. And they call that hallucination, because if the LLM was hallucinating, but it’s not, it’s just able to feed the LLM dynamically with the right retrieval, augmented generation scheme to dynamically provide the information for replying to the question because it’s difficult to pull from the PDF the right information that applies to the context. And we are back to, what is the context? What is the machine? What is the profile of the user? What is the variant, the version, the whatever you have in front of you? So that’s the complex part. So what’s the relationship? What is the successful AI? What’s the relationship between CDP and AI? All AI projects I’ve seen start regardless of us, regardless of Fluid Topics, start with we need to gather content. We need to take the content that we have, put it in one place, create this sort of unified repository of content. The promise that usually, as I said, they do it using static document, PDFs, to analyze blah blah. If you look at what a CDP is, that’s exactly what it is. It’s already your repository of content. At least everything around the product, because we’ve been talking about CCMS published to CDP. What also makes a CDP very special is that, not only can we ingest this DITA content, but also this legacy PDF and markdown content, API documentation knowledge bases. So the CDP is here to ingest all the knowledge that you have around your product, not just necessarily the formal techdoc, the proper techdoc that has been well written and validated. So we have already, well, the CDP is exactly that. It’s building, that’s the purpose of it. It’s building that unified repository and that’s where you should start from. And it’s fine grained, and we have the metadata and we have everything, so we know how to feed the LLM. So there are two things in an AI project. One is the LLM, but now people use generic LLM, you don’t fine tune, train an LLM anymore for this sort of use case that is just a chatbot for replying to questions and solving cases automatically. You use a generic LLM and you feed the LLM dynamically with the fragments of content of knowledge that you have in your repository. And that’s where just as a human, when you run a search, you look for content, you know what part of content, what are the fragments, the topics, the chapters that contain the knowledge for replying to that question? The tough part is, extracting that from the repository. Am I extracting the 2, 3, 4 pages around the question that are matching the version, the situation that I’m in? So that I can then feed the LLM and say, “This is the 10 pages of knowledge that we have, or 20 or 50 pages of knowledge. This is the question replied to the question using that knowledge.” That’s exactly what a chatbot does. You’re giving the question of the user, you give 5, 10, 20, whatever number of pages of knowledge that you have in your repository and you ask the LLM say, “This is the question, this is the knowledge, please reply.” So the test part is extracting the 5, 10, 20 pages that are really adapted to the situation, to the context.

SO: And the metadata helps you do that.

FL: And the metadata. Nothing else than metadata for doing that.

SO: Right. Okay. So we’ve talked a lot about metadata as I guess a precondition, right? A prerequisite. Yeah, it is. If you don’t have metadata, none of these other things are going to work. And I wanted to ask you about other, maybe, challenges or prerequisites. So other than people coming in and saying, oh, right, we need metadata, and then they go away for two years and then they come back and they have some metadata, what are the other issues that you run into when you’re trying to build out a CDP like this? What are some of the other… What are the top challenges that you run into other than clearly metadata? So we’ll put that one at number one.

FL: Oh yeah, clearly number one. I would say the second one now is the UX UI people want to design. Because modern platform have unlimited capabilities in designing the front end, the UI that you want. It’s like what do you want? What makes sense for regarding, based on your product types, the user that you have, the content that you have, what is the UX you want to build? That’s interesting, because probably five, no, let’s say 10 years ago, we were providing default interfaces out of the box with the product, with three topics to build your portal. And you could just brand that, put your colors, logo, tweak it a bit, and everybody was happy with that. And then we’ve seen a big evolution because now for many companies, marketing everywhere to say on UX, you have now UX director of VP of user experience that were not existing five years ago, 10 years ago. See what I mean, everybody was working is on swim lane. The techdoc department was in charge of writing the content and probably generating the PDFs and then setting up a doc portal. But many companies have realized that this tech doc portal is instrumental to the performance of the company. And now it says, “Oh, we need to have a look at that.” So it becomes a shared place. See, you’ve seen that I guess in your project.

SO: Yeah. Yeah.

FL: Five years ago, 10 years ago, the only people you had to work with and educate and discuss with were probably the tech dog team. And now you’ve got marketing and you’ve got customer support, and you’ve got customer experience people. And because they’ve realized the value there is in this content, but as well as how important it is to design the writer’s experience that fits with the other touch points of the company to create a seamless journey when you go from the corporate website to the documentation website to the help desk tool to the LMS. And you need some consistency around that, not only in terms of just branding colors and logos, but you go beyond that. And we see this as a new place where people struggle a bit. Our customers struggle is what do we want? In fact, they know that marketing says we need something that is more modern, more like this, more like that. But we start opening the discussion, what is it really that you want? Some companies are very mature, they got the Figma mockups and they come to us, “This is what we need to implement. We’ve spent two years with UX designer crafting the UX of our portal.” And some come and say, “Oh my God, you’re right. We don’t know what you need. Give us a default, something to start with and we’ll see.”

SO: Well, you’ll appreciate this. I had a call not too long ago with a very, very, very, very large company, very large. And they said, “We need a front end for our content, this tech content that needs to go out into the world, we need a design for it.” And because it’s a very large company, I said, “Great, where’s your UX team? And do you have a design system?” Because, I mean presumably they do. And the person I was talking to said, “I don’t know. I don’t think so.” And so I consulted the almighty search engine and discovered that not only did this particular company have a design system, they had something that is publicly available, that is their design system that you can go get all the pieces and parts and all the logos and all the behaviors and everything. It is all out there in the world. And yet, the people that work at this organization and in their defense, there are many, many tens of thousands of them did not know that this thing existed. And so all of their requirements in terms of what they had to do for their portal design were right out there in the world accessible to me.

FL: They didn’t even know about it.

SO: And they had no idea that it existed. And so we had to be the ones to make that connection and say, okay, we have to talk to the people or at least download all these assets and then figure out what to do with them and then make sure that we’re following the rules and all the rest of it. So to your point, the enterprise issues, and we also run out into this with metadata and taxonomy, that that is typically an enterprise problem, not a departmental problem. And actually making those connections across the departments for the first time is a task that very often falls to us as the consultants on the outside who are asking, “Do you have a taxonomy project? Do you have design systems? Do you have these enterprise assets that we need to align with and be consistent with?” And they’re not ready for that question, because it was until recently, put a pile of PDFs somewhere.

FL: That’s just a known and you don’t know what you don’t know. And when they start moving up to more capable tools, they discover that it comes with more capabilities, but they have to make choices, they have to invest in metadata, UX design and all that. And it’s probably some of those companies are not ready yet. I mean, they didn’t foresee that coming. And that’s where the project lag a bit in terms of complexity as well, because they realize that it’s not just buying the tool as well, making the investment on their content, their UX strategy, their design system and all that. That may be missing in some cases.

SO: And I think that probably saying it’s not just about buying the tool is really a good summary of this whole situation. Because we started with you’re really going to need metadata, and if you don’t have metadata, that’s a huge problem. And we’ve landed on, and there are all these other connections and pieces and parts that you have to think about. So Fabrice, thank you very much. This was a great discussion and I appreciate all your information and we will wrap this up there. Are there any parting thoughts that you want to leave people with?

FL: It was an absolute pleasure having this discussion with you, Sarah. I think it could have last another hour easily, so we need to stop somewhere. Maybe we’ll have another opportunities to keep on chatting about some of the subjects.

SO: Yep. Sounds good. And thank you again, and we will see you soon. 

Christine Cuellar: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Deliver content dynamically with a content delivery platform appeared first on Scriptorium.

Because we used DITA XML for the content instead of the actual authoring in Moodle, we actually saved a lot of pain for ourselves. With Moodle, the name of the game is low-code/no-code. They want you to manually build out these courses, but we wanted to automate that for obvious reasons. SCORM allowed us to do that by having a transform that would take our DITA XML, put it in SCORM, and then we just upload the SCORM package to Moodle and don’t have to do all the painful things of, you know, “Let’s put a heading two here with this little piece of content.” And the key thing is that allowed us to reuse content.

— Allison Beatty

Related links:

• Self-paced, online DITA training with LearningDITA.com
• Structured authoring and XML (white paper), which is also included in our book, Content Transformation
• Confronting the horror of modernizing content
• The benefits of structured content for learning & development content
• Get monthly insights on structured learning content, content operations, and more with our Illuminations newsletter

LinkedIn:

• Sarah O’Keefe
• Allison Beatty

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Sarah O’Keefe: Hi everyone, I’m Sarah O’Keefe.

Allison Beatty: And I’m Allison Beatty.

SO: And in this episode, we’re focusing in on the LearningDITA architecture and how it might provide a pattern for other learning content initiatives, including maybe the one that you, the listener, are working on. We have a couple of major components in the learningDITA.com site architecture. We have learner records for the users. We have e-commerce, the way we actually sell the courses and monetize them. That is my personal favorite. And then we have the content itself and assorted relationships and connectors amongst all those pieces. So I’m here with Allison Beatty today, and her job is to explain all those things to us because Allison did all the actual work. So Allison, talk us through these things. Let’s start with Moodle. What is Moodle and what’s it doing in the site architecture?

AB: Okay. So Moodle is an open-source LMS that we-

SO: What’s an LMS?

AB: Learning management system, Sarah.

SO: Thank you.

AB: And we installed Moodle, our own instance of Moodle and customized it as we saw fit for our needs. And that is the component that acts as the layer between the content and the learning experience. So without the Moodle part, it’s just a big chunk of content that you can’t really interact with. And Moodle gives that a place to live.

SO: And then Moodle has the learner records, right?

AB: Yes.

SO: And what about groups? What does that look like?

AB: In Moodle, there’s a cohort functionality which allows us to use groups so that a manager can buy multiple seats and assign them to individuals and keep track of their course progress through group registration rather than individual self-service signups.

SO: So if I were a manager of a group that needs to learn DITA, instead of having to send five or 10 or 50 people individually to our site, I could just sign up once and buy five or 10 or 50 seats in a given course and then assign those via email addresses to all of my people, right?

AB: Exactly.

SO: Okay. So then speaking of buying things, we had to build out this e-commerce layer, which I was apparently traveling the entire time that this was going on, but I heard a lot of discussion about this in our Slack. So what does it look like? What does the commerce piece look like?

AB: Yeah. So it is a site outside of the actual learningDITA.com Moodle site that has a connector into Moodle so that you can buy a course or a group registration in the store, and then you get access to that content in Moodle.

SO: So we have this site, this actually separate site, and if you’re in there, you can do things like buy a course or buy a collection of courses or a number of seats. And then what were some of the fun complications that we ran into there?

AB: Oh yeah. So the fun complications there were figuring out how to set up an commerce site that A, connected to Moodle so that we could sell the courses, and B was able to process taxes and payments and all of that fun stuff. So Moodle has PayPal as a feature just out of the box and the base Moodle source code. But we wanted to accept credit cards directly and so that meant some additional layers, which is how we ended up with the store.scriptorium.com site, which is built on WordPress and uses a connector, the aforementioned connector, to make those two sites talk to each other. So they’re actually, the LMS and the e-commerce piece are totally separate websites, but exist within the same system environment.

SO: And most of you listening to this probably don’t care, but one of the things we learned was that digital training, downloadable training content is sometimes subject to sales tax and sometimes not, depending on the particular state or the particular jurisdiction. So it’s not just, what is sales tax in North Carolina versus what is sales tax in Washington state versus what is it in Oregon? But additionally, in each jurisdiction is this type of training subject to sales tax or not. So we spent a more than optimal amount of time on figuring out all of those things and making sure we get it right, because I’m extremely interested in making sure that those taxes are done correctly and keep us out of trouble.

AB: And the basic PayPal and Moodle wasn’t going to give us that level of granular control and specification.

SO: And typically our customers are looking to pay via credit card. So we’ve got the LMS piece with the learner experience, the actual learning platform. We’ve got the e-commerce piece with the Let’s Take Money piece. And then finally we have the content piece. So what does it look like to actually create these courses and create and manage the content that then eventually goes into Moodle?

AB: Yeah. So the content does have a single source of truth. It is all authored in DITA XML and stored in a central repository. You can see that content in GitHub. It’s open source. We took the DIT XML and we developed a SCORM transform that we could use to hook the content up into Moodle and be able to use all of the grading and progress and prerequisite type things that we needed to flush out the actual learning platform. We had learned a fun lesson along the way that Moodle does not support SCORM 2004. So that required a little bit of backtracking to make sure that we were getting the data into the correct SCORM to get into Moodle. And so because we used it XML for the content instead of the actual authoring in Moodle, we actually saved a lot of pain for ourselves with Moodle. The name of the game with Moodle is low-code/no-code, and they want you to manually build out these courses. But we wanted to automate that for obvious reasons, and SCORM allowed us to do that by having a transform that would take our DITA XML, put it in SCORM, and then we just upload the SCORM package to Moodle and don’t have to do all the painful things of let’s put a heading to here with this little piece of content. And the key thing is that allowed us to reuse content as well. And then if we need to update the content, all we have to do is replace the SCORM package in Moodle.

SO: So currently we have DITA 1.3 content out there. The DITA 2.0 content is under development, and I would say mostly done. We’re mainly waiting for the actual release of the those two chunks of content, although those courses are going to be in GitHub in the DITA training, or I think it’s called Learning DITA now, the Learning DITA project.

AB: Yep.

SO: Separately from that, we’re working on some new courses which are not going to be open sourced, but will be available on Moodle or… Sorry, on learningDITA.com. And so for those of you that are wondering, we’ve got a number of things on our roadmap. I’d love to hear more from people listening to this about what they need out of this. What more advanced courses are you looking for? One thing that we’ve heard a lot of requests for is a DITA open toolkit plugins 101.

How do I build a plugin? How do I use best practices? How do I make this all happen? So we have this, I don’t know, DITA inception thing happening because we’re training people on how to do DITA using DITA inside DITA, building out the stuff.

AB: It’s all very meta.

SO: It’s extremely meta. Hypothetically, what would it look like to localize this? So what we’ve delivered right now is in English, and in the past we have had people put together both, let’s see, German, Chinese, and I think French versions of the Learning DITA content. But what does it look like in this new architecture to localize?

AB: Yeah. So much like the tool chain for this new architecture, there are a couple of different components, and if you would like to localize the Learning DITA content, what you’ll want to look at is the content itself, translating and localizing the source content, but you’ll also need to localize Moodle some. So what you would do is make a, basically clone the Moodle site, and you’ll have to, not to go too into the Moodle weeds, but you’ll need to reconfigure the initializing PHP file a little bit. And then you would take your translated localized content and prep that up into your new Moodle for whichever language you’re localizing into.

SO: So it looks as though, you mentioned maintenance and this idea that Moodle by design wants you to make updates inside Moodle, and we pulled the content out of there. We’re basically saying Moodle is for learners and learning management and course records and sequencing and those kinds of things, and grading, I suppose, but the DITA back end is for content. So we’re putting all the content in DITA and then we push it over to SCORM, which then goes into learningDITA.com into the Moodle site. It sounds like more work, right? We had to build a SCORM transform. We had to put all this stuff in… We didn’t just go into Moodle and start authoring, which would be a lot faster on day one. So what’s the rationale for that? What does it look like in the long term to maintain something in Moodle versus to maintain something in the system that we’re describing?

AB: Yeah. It may seem easier on day one to manually put the content in, but when you need to make an update or change something, or particularly if you want to change something about a piece of content that is reused and repeated throughout the courses, you have to manually trawl through every single course page and make those updates, whereas with the SCORM package, once you have the SCORM transform set up and running to your liking, you can run your DITA content through there and then replace the SCORM package in Moodle instead of having to manually trawl through page by page. And maybe there is some content that is duplicated, but you mess it up because you were manually trawling through page by page. So it also, having DITA as the single source of truth helps you with maintenance, even if it seems scary at first.

SO: And I expect one of the things we’re looking at is CCMS courses, and the concept of what is a CCMS is going to be the same for all of them. The process of how do I check out files is going to be a little different for each of them. So if you think about that from a course material point of view, you would have that conceptual overview of, what is the component content management system and why do I care? And then there’s, how do I do the thing in specific component content management system? That would probably be unique, but the conceptual overview would be probably the same. So we might have two or five or 15 different courses, one for each CCMS, but you could see where the conceptual stuff would overlap.

AB: Exactly.

SO: Okay. Everyone, I hope this glimpse into content operations for structured learning content was useful. Of course, the learningDITA.com site is much smaller than what we typically do with our customers at scale, but we are getting more and more requests for learning content and structured content options for learning content. If you’re interested in learning more about learningDITA.com, would suggest you go there and check it out. Check out the DITA training, which has eight or nine courses on DITA stuff from what is structured authoring, all the way to tell me about the learning and training specialization. Allison, thank you so much for all your input.

AB: Thank you.

SO: And we’ll see you on the next one.

Christine Cuellar: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post LearningDITA: DITA-based structured learning content in action appeared first on Scriptorium.

Even if you are significantly reusing your learning content, you’re not just putting the same text everywhere. You can add personalization layers to the content and tailor certain parts of the content that are specific to your audience’s needs. If you were in a copy-and-paste scenario, you’d have to manually update it every single time you want to make a change. That scenario also makes it a lot more difficult to update content as you modify it for specific audiences over time, because you may not find everywhere a piece of information has been used and modified when you need to update it.

— Bill Swallow

Related links:

• Structured authoring and XML (white paper), which is also included in our book, Content Transformation
• Confronting the horror of modernizing content
• The challenges of structured learning content (podcast)
• Self-paced, online DITA training with LearningDITA.com
• Get monthly insights on structured learning content, content operations, and more with our Illuminations newsletter

LinkedIn:

• Alan Pringle
• Bill Swallow
• Christine Cuellar

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Christine Cuellar: Hey, everybody, and welcome to today’s show. I’m Christine Cuellar, and with me today I have Alan Pringle and Bill Swallow. Alan and Bill, thanks for being here.

Alan Pringle: Sure. Hello, everybody.

Bill Swallow: Hey, there.

CC: Today, Alan, Bill, and I are going to be talking about structured content for learning content. Before we get too far in the weeds, let’s kick it off with a intro question.

Alan, what is structured content?

AP: Structured content is a content workflow that lets you define and enforce consistent organization of your information. Let’s give a quick example in the learning space. For example, you could say that all learning overviews contain information about the audience for that content, the duration, prerequisites, and the learning objectives for that lesson or learning module. And by the way, that structure that I just mentioned … It actually comes from a structured content standard called the Darwin Information Typing Architecture, DITA for short. That is an open-source standard that has a set of elements that are expressly for learning content, including lessons and assessments. And I think it’s also worth noting, another big part of the whole idea of structured content is that you are creating content in a format agnostic way. You are not formatting your content specifically for, let’s say, a study guide, a lesson that’s in a learning management system, or even a slide deck. Instead, what a content creator instructional designer does … They are going to develop content that follows the predefined structure, and then an automated publishing process is going to apply the correct kind of formatting depending on how you’re delivering the content. That way, as a content creator and instructional designer, you’re not having to copy and paste your learning content into a bunch of different tools. And I know for a fact a lot of instructional designers are doing that right now. Instead of doing all that copying and pasting, you write it one time, and then you say, “I want to deliver it for these different delivery targets, whether it’s for online purposes, whether it’s for in-person training or maybe a combination of both.” You set up publishing processes to apply the formatting for whatever your delivery targets are so you, as a human being, don’t have to mess with that.

CC: Which is awesome. Part of the reason that we’re talking about this today is that structured content has been a part of the techcomm world for over 30 years, for a really long time, and now we’re starting to see it make inroads in the learning and development space. We’ve been doing a lot of work for structured content in the learning space, but how is it different from the techcomm space? And Bill, I’m going to kick this over to you for that.

BS: I think I’m going to take a higher-level view on this because there is a lot of overlap between techcomm and learning content. Where they really start to diverge is in delivery. Techcomm is pretty uniform in how it delivers content to people. There’s personalization involved and so forth, but essentially everyone’s getting the same thing. The experience is going to be the same. Everyone’s going to get a manual. Everyone’s going to get online help. Everyone’s going to get a web resource, what have you. It might be tailored to their specific needs, but it’s a pretty candid delivery experience. For training, the focus is on the learning experience itself, and it’s usually tailored to a very specific need, whether it’s a very specific type of audience that needs information, or it’s very specific information that needs to be delivered in a very specific way for those people. Beyond that, we start looking at the content itself under the hood, and the information starts to, I would say, broaden with learning content because it can consume all the different types of information you have with technical content. And generally in a structured world, we think of that as conceptual information, how-to information, and reference information, for the most part. With learning content, now you have a completely new set of content in addition to that where you have learning objectives. You have assessments. You have overviews, reviews, all sorts of different content that essentially expands on the wealth of information you have from your technical resources.

CC: That’s great. Typically, the arguments for structured content, and the reason it’s really valuable for organizations, is it introduces consistency in your content, consistency for your brand across wherever you’re delivering content. It also helps you build some scalable content processes, that kind of thing. What are some of the arguments for structured content for the learning environment specifically, if there are any other new ones?

AP: Some of the reasons that you want to do structured content for learning content are really similar to other types of content. We’ve already talked about one of them. I touched on this earlier in regard to automated formatting. You are not having to do all of the work as a human being, applying formatting to ever how many delivery formats that you have. That is a huge win that you’re not having to do that. And especially in the training space, I have seen so many organizations copying content from one platform to another because the platforms don’t play well together, so you’ve got multiple versions of what should be the same exact content to maintain. That is another huge reason to consider structure. You want a single source of truth for your content regardless of where that information is being delivered because if you’re looking at the overall learning experience and the excellence and quality of that learning experience, if you were telling learners slightly different things in different places in your content, you are not providing an optimal learning experience. Therefore, having that single source of truth for a particular bit of information gives your learners a consistent piece of information regardless of what channel they consume it for. That’s a really important win for a solid, dependable learning experience.

CC: Gotcha. No, that definitely makes sense. It sounds like it would take some of the effort off of the subject-matter experts who are creating these trainings so that they can … They, I’m assuming, would rather focus on the work of helping train people. Getting some of the manual formatting and copy and pasting off of their workload sounds pretty nice. What are the complications that it might introduce or the change management issues that might need to be tackled when you’re bringing structured content into a learning environment?

AP: It’s true anytime you bring in structure. When people are used to working in an environment where you are doing manual formatting, and you’re seeing what things look like as you kind of develop the content, the idea of developing content in a format agnostic way where you’re not thinking about what does this slide look like, or how is this assessment going to work in the learning management system, it’s very easy to get focused on the delivery angle because you want it to be good, and you want it to be done in a way that makes that learning experience useful for the people who are trying to learn whatever it is they’re trying to learn. You don’t want those impediments of bad formatting or a not great way that your assessments behave in your learning management system, but you kind of get to offload all of those concerns, which are very valid. I’m not saying they’re not valid. They are, but you want an automated process. Basically, you want computers to do that work for you. You want programming to apply that formatting so you can really focus on getting that information as solid as it can be, and you let technology handle the rest. You do set up the standards for how you deliver that content, whether it’s in print, online, in person, whatever. However you’re delivering your learning and training content, you set the standards. “This is how I need this to behave. This is how I need it to look. This is how I need it to interact.” Once you set those standards, then you turn around and have someone who has this programmatic skill set, like we do at Scriptorium, to come in and develop the transformations that take your content and deliver it in the ways you need it delivered so you, as, like you were saying, the subject-matter expert, the instruction designer, or whatever content creator we’re talking about here … You are not doing that for every single delivery type that you are putting out for your learners.

BS: And it’s not to say that the experience isn’t tailored because it still can be tailored. Even if you are significantly reusing your content, you’re not just taking the same text everywhere. You can add personalization layers to that content and tailor certain parts of the content specific to what that specific audience needs rather than having to retype it all every single time you want to make a change if you were in a copy-paste scenario. And that also would make it a lot more difficult to update all that content as you modify it for specific audiences over time because you may not find everywhere where a piece of information has been used and modified if you need to update it. It does take a little bit of … Well, it takes a lot of the work off of those developing the content because they don’t have to worry about exactly what it looks like for every single target that they’re producing. It does require a little bit of, I would say, faith in the system that it will work. It really comes down to how you’re architecting this in the first place to make sure you understand who your varied audiences are, what the look and feel needs to be, what the delivery points are, and making sure that you are authoring within the scope of those things. And once you get that down, as Alan mentioned, it becomes a push-button operation to produce all of your various outputs.

AP: I think, too, from a change management point of view, one thing that I have heard from lots of content creators in the learning space is the burden they have, for example, if a program or the company changes names, changes logos, changes branding, if you have that built in to the formatting in a way where you’re having to go into, say, a bunch of Microsoft Word or PowerPoint files and manually change those out, and I am sure I am talking to people out there in the ether who know exactly what I’m talking about, it is extremely painful. And when you have automated the application of formatting, what you can do is change those processes to update them to include the latest corporate colors, the latest taglines, the latest fonts, the latest logos, whatever has changed so you, as a human being, again, do not have to go in there and touch all of those files yourselves because that is a burden you don’t need when you were trying to quote do your real work, which is help people learn, not apply formatting to a zillion Microsoft Word documents. Nobody wants to do that, at least nobody I know anyway.

CC: No. That’s a very good example of how the structure can just take that part of the workload off of you so you can get to focus on what you want to do. But I like, Bill, how you put it that you have to trust the process because it is an adjustment to go from authoring your content in a specific PowerPoint or in a specific Word doc to authoring it in a way that it can be reused. But ultimately what I’m hearing both of you say is that, even though it’s a valid concern that you might worry about your ability to personalize and your ability to control the user experience, once structured content is implemented correctly, and everyone is adjusted to the system, it sounds to me like you’re saying that your opportunities for personalizing at scale are actually going to be bigger than when everyone’s doing it individually, and at least it introduces consistency across those personalized experiences. Do you think that’s fair to say, either of you? Do you think that’s a fair statement, or is that too optimistic-

AP: That is an incredibly loaded question the only answer to which is … No, you were correct. That is, structure does enable all the things that you just ask in that very leading, but good, question.

CC: It is very leading.

BS: It removes the visual context of where the content is going, but it doesn’t remove … In fact, it enhances the context of what the content is about.

AP: Right.

CC: That’s a good way to say it. I like that. Looking at structured content within the learning space itself, how does it … I know, Bill, you had mentioned that, within the techcomm space, it’s fairly uniform in how content is delivered and who it’s delivered to. Not that it’s always the same. How about in the learning space? How does that vary? And how does the structure approach vary?

BS: Well, this might contradict what I said before, but it’s a slightly different look on it in that, really, the learning clients that we’ve had … They kind of mirror a lot of the techcomm clients we had in that everyone is producing roughly … If you look at it from a high enough altitude, it all looks the same. They’re all producing manuals. They’re all producing e-learning. They’re all producing whatever. When you get down into the nuts and bolts, that’s when you start finding that every single implementation is going to look a little bit different. In techcomm, you might have completely different types of content that you need to be able to handle. The same thing is with the learning space. Every single group is going to have different needs, and they’re going to have very specialized needs based on the content that they’re producing and who they’re producing it for. The learning space, unlike techcomm where they’ve basically been going down the structured path for 20, 30 years … The learning space has really been a sea of black boxes where every single system has its own way of doing things. It does about 90%, 95% of the same stuff that every other system out there does, but there is something special, something canned, something within the system that allows it to do the one thing that no other system does. And all of these technologies historically have really been locked down tight where your content goes in, and it lives and thrives in that box that you’re developing it in. But if you need to take that content out and change systems and put it somewhere else, there’s a lot of rework that potentially needs to be done depending on how customized that system you were using was. And let’s face it. You can structure content. You can centralize it. You can componentize it all you want. It’s not going to change the fact that learning content is going to have these many varied endpoints for how it’s being delivered. Even though you are consolidating and structuring in a central repository to maximize your reuse, to not worry about the formatting, you may still have three or four different learning management systems that you are pushing that content into. Each one of those systems has different requirements. The type of content that gets consumed. What it does. How it reacts. What it expects. The order it needs that information in per lesson, per page. E-page. It gets a little more complicated in the delivery of the learning content because we need to be able to tailor to not only the needs of the particular client in the content that they’re producing but the needs of the systems that need to ingest it.

AP: One other thing I would mention here is the level of interactivity, I think, is higher with learning and training content than the techcomm world. Now, I realize there are documentation portals and things like that that do provide some levels of interactivity. However, I think you are going to see much more of that kind of thing on the learning and training side, especially in regard to assessments when you are trying to have people do little, basically, mini exercises to prove that they have learned what they need to learn and that they are graded, and then those scores are recorded. That is the kind of thing you don’t see in techcomm. That is a whole, very specific thing to the learning and training world. Therefore, the structure that you choose needs to accommodate that, and your delivery targets in particular need to accommodate that very high level of interactivity with, for example, like Bill was saying, a learning management system.

BS: You have quite a variety of needs out there from basic, true/false, multiple choice, or matching all the way down to simulations, doing interactive exercises, and so forth all within a learning management system. And you need to be able to account for that. And as I mentioned, not all of those systems function in the exact same way, so it needs to be tailored.

CC: For any listeners that are listening to this episode right now, and they are in the learning content space, and they’re interested in getting started with structured content, Alan, where would you recommend they start?

AP: Well, our website, scriptorium.com, has lots–very self-serving. Very self-serving. We have a lot of resources, and we will put them in the show notes so you can get to them. We also are the creator and maintainer of a site called learningdita.com that teaches people about one way to do structured content, which is DITA, which I mentioned earlier in the show. And there is a free Introduction to DITA course that you can take. Between some links that we’ll include in the show notes in regard to what is structured content, how it applies to the learning and training space, and learning DITA, those are all good starting points for people who are considering going on the structured content journey for their learning content.

CC: That’s great. And the only thing I’ll add to that is that, if you’re interested in learning more about learning content and structured content, this is something that we talk about a lot. I would recommend also subscribing to our Illuminations newsletter which, like Alan said, that’s also going to be linked in the show notes. But every month, we send out a recap of the topics we talked about, and learning content is very often in there because we talk about it a lot.

This final question is for both of you. Is there anything else that you want to leave our listeners with about structured content in the learning content space before we wrap up today?

BS: I’d say, if you’re looking at structured content, it’s not going to on its face be a savior solution. But if with enough thought, it can really make a difference in your content development workflow, and it can save you a lot of time in producing content that is targeted to very specific people and delivery points.

AP: For me, my final suggestion here is think about your pain points. What are the things that are keeping you up at night as you develop your learning and training content? What are the continual issues you are battling, especially your content creators? What are they battling? Is it they’re having to format for umpteen different platforms? Is it that they’re needing to personalize things for different locations? For different levels of service that you were training people about? What are the things that are causing you problems? Basically, compile a list of those. And then from there, figure out, could structured content, solve any of these problems? Don’t put the cart before the horse, is the best way to put it, really. Think about your pain points in your processes and then see if structure might be the thing to solve them.

CC: That’s great. And on that, Alan, Bill, thank you very much for being here and recording this with me today.

BS: Thank you.

AP: Absolutely. We like to talk about this stuff probably too much.

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

Get monthly insights on structured learning content, content operations, and more with our Illuminations newsletter.

The post The benefits of structured content for learning & development content appeared first on Scriptorium.

Gretyl Kinsey: Over time that user base grew and grew. And now it boggles my mind that it got all the way up to 16,000 users. I never expected it to grow to that size.

Alan Pringle: Well, we didn’t really either, nor did our infrastructure. Because as of late 2024, things started to go a little sideways, and it became clear our tech stack was not going to be able to sustain more students. It was very creaky. The site wasn’t performing well. So we made a decision that we needed to take the site offline, and we did, to basically redo it on a new platform.

Related links:

• Check out our self-paced online DITA 1.3 training.
• Open-source DITA training project GitHub files

LinkedIn:

• Alan Pringle
• Gretyl Kinsey
• Allison Beatty

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Alan Pringle: Hey, everyone, I am Alan Pringle, and today I am here with Gretyl Kinsey and Allison Beatty. Say hello, you two.

Gretyl Kinsey: Hello.

Allison Beatty: Hello.

AP: We are together here today because we want to talk about LearningDITA, our e-learning site for the DITA specification because we have just moved it to a new platform. So we want to give you a little background on what went on with that decision. So first of all, Gretyl, you and I were at Scriptorium when we kicked off this site, and I just went back and looked at blog posts. We announced it via blog post I wrote in July of 2015. So we have had this site up and running for 10 years, which absolutely blows my mind.

GK: It blows my mind too. It’s hard to believe that it’s been that long because it does seem like it got launched pretty recently in my memory, but it has been through a lot of changes and so has the entire landscape of content creation as well. So yeah, it’s really cool that now we can look back and say it has been 10 years of LearningDITA being on the web.

AP: For those who may not be familiar with the site, give us a little summary of what it is.

GK: Sure. So LearningDITA is a training resource on DITA XML and it’s developed by Scriptorium, and it covers a lot of the main fundamentals of DITA. So we have some courses on basic authoring and publishing. We also have a couple of courses on reuse and one course on the DITA learning and training specialization. So you get a good overview of a lot of different areas of DITA XML. And all of the courses are self-guided e-learning. So you can go through and take them at your own pace. You can go back and take the courses again if you want a memory refresher. And they all come with a lot of examples and exercises. So you get a download of sample files that you can work your way through. There’s some of that practice that’s guided, and then there’s others that you do on your own. And then there are also assessments throughout each course that help you test your knowledge. So you get a really nice hands-on approach to LearningDITA. So that’s why we called the site that in the first place. And it really helps to get those basics, those fundamentals in place if you are coming at it as a beginner who is unfamiliar with DITA or maybe you have some familiarity, but you want to just reinforce what you know.

AP: So we went along with this site and kept adding courses over the years. I think we got to nine, is that right? I think it’s nine.

GK: That’s right. So we really started this out, like I was mentioning earlier, that we needed something that was beginner-friendly, something for people who were unfamiliar with DITA because we saw a gap in the information that was available at the time 10 years ago. A lot of the DITA resources, documentation, guides and things like that out there were something that assumed some prior knowledge or prior expertise, and there wasn’t really anything that filled that gap. So we came up with these courses. And the nine courses that we have, the first one is just an introduction to DITA. So that was the first one that launched back in July of 2015. And then shortly after that, we added a few courses on topic authoring. So that covers the main topic types, concept, task reference and glossary entry. And then we just added more courses over time. So we’ve got one that covers the use of maps and book maps. We’ve got one that covers publishing basics. We have, like I mentioned, the two courses on reuse. So there’s a more introductory basic reuse course and then a more advanced reuse course, and then learning and training. So those are the nine courses that we have, and they’ve been up there pretty much the entire time. The earliest ones where that introduction, the authoring, and then we added the others as the demand increased over time.

AP: And that demand, I’m glad you mentioned that, really did increase because as of late 2024, we had over 16,000 students in the database for LearningDITA, which also completely blows my mind.

GK: Yeah, it does for me too, because I think in the early days we saw a lot more individuals using it, and then over time we would see more large groups of users sign up. So an entire class whose professor might’ve recommended taking the LearningDITA courses or sometimes an organization, whether it was one of our clients or just another organization, would have a lot of employees sign up all at once. And so yeah, over time that user base grew and grew. And now it does boggle my mind as well that it got all the way up to 16,000 users. I never expected it to grow to that size.

AP: Well, we didn’t really either, nor did our infrastructure. Because as of late last year, things started to go a little sideways and it became clear our tech stack was not going to be able to sustain more students. It was very creaky. The site wasn’t performing well. So we made a decision that we needed to take the site offline and we did to basically redo it on a new platform. And Allison, this is where I want you to come in because you are one of the, shall we say, victims on the Scriptorium side who got to dive into what our requirements were, what we needed to do. Essentially, I mean, we really became consultants for ourselves and turned our consultant eye at our problem to figure out what it was. And Allison, if you don’t mind, tell us a little bit about that process and where we landed.

AB: Yeah, so the platform was the first big choice that we knew we had to make, and things started out pretty fuzzy because we didn’t really know what we were doing and just had to figure out what was going to work to solve these pain points. And so as a starting place, we knew we needed a new LMS, learning management system. And so we did some research on what learning management systems were out there and thought about what we could use that would fit our needs. And we ended up choosing Moodle, which is an open source LMS that is very widely used within colleges and universities and higher education settings. And we knew it could be very powerful and probably suit our needs with some custom work. But the thing about Moodle is it’s known for having a high barrier to entry in terms of the installation, and that made us a little nervous. But the more we kept looking at LMS options, both open source and commercial, we realized that Moodle is so popular and industry standard almost for a reason and that it was worth taking on that challenge.

AP: And I even had someone in the learning space because I asked her advice, what LMS would you use? She pretty much said run away from Moodle because for a lot of the reasons that you just mentioned. But I think it’s worth noting, it does have… There are a lot of people using it, especially in educational settings, schools, universities. It’s also the open source angle was appealing because that way it didn’t look like we were picking “favorites” by picking a particular proprietary LMS.

AB: Yeah, definitely. And then the other piece of the puzzle there as far as how we’re going to display and host the learning content was the DITA transform for the content itself and how we were going to get the LearningDITA content into our LMS. And so we knew that Moodle is compatible with both SCORM and xAPI and we ended up deciding that we wanted to develop a DITA to SCORM transform because SCORM is something that we have discussed and worked on with other clients as we’ve been seeing this trend in learning and training content pickup.

I don’t know if Gretyl wants to talk a little bit about how she’s seen SCORM throughout various projects and why we decided it was something we wanted to pursue and learn more about ourselves.

AP: And what is it while you’re at it? That too.

AB: That’s a good question. I’ll just go ahead and talk a little about what it is without getting too deep technically. Basically it’s a standard for e-learning content and it provides communication that can do things like track grades within your LMS. In the LearningDITA, the previous site and the current site, you had to pass assessments to get to the next lesson. And so SCORM can handle things like tracking assessment completion and scores. It’s pretty flexible and widely used. It’s more or less just a standard, but it requires a pretty specific data structure for it to function because it’s expecting certain data structures that are defined in the standard for it to work in different environments. And Gretyl, would you like to talk a little bit about how we’ve seen the SCORM standard pop up through various client projects?

GK: Sure. So we have seen I think over especially these last 10 years since LearningDITA launched an increase or a bit of an uptick in clients who come to us with e-learning content specifically. Some of them, that’s the only content they have. For others, they are trying to get some sort of a process for developing both e-learning content and then other kinds like technical documentation, marketing content. But a lot of them end up going down this path where they realize DITA XML is going to be helpful for content creation, especially if they do have that cross-department collaboration or reuse that needs to happen. And SCORM has been something that we’ve seen crop up with a lot of these projects. Because like you mentioned, Allison, it offers all that flexibility around things like scoring the assessments, keeping that student data that’s needed. And we’ve also seen how it’s really good when you’ve got an organization that has to deliver e-learning content to multiple different LMSs. So let’s say they’ve got students in a lot of different geographical areas or different industries and they all use different LMSs. That SCORM package can be delivered into all of them and used. And so they get that flexibility. So we’ve seen this crop up in a lot of different client projects. And the more we saw it pop up in these different projects, the more we said this might be beneficial for us too. And we’ve seen all the different ways that these organizations have made use of SCORM packages and why not give it a try for our LearningDITA content. And which by the way, I just wanted to mention, I don’t think we explicitly said this, but all of the LearningDITA courses themselves are authored in DITA XML. So kind of meta layer there to think about. But because of that, we have to think about how are we going to publish this information, get these e-learning courses out onto the web. And so a DITA to SCORM transform, as Allison said, is the approach that we decided on.

AP: And those source files, by the way, are part of this open source project that’s out in GitHub. And we’ll put some links in the show notes about it. But you can look at the source files that we used and download them for free. They’re open source. You can look at them and even use them for your own purposes if you like.

GK: And one question I had there, so you mentioned that all of those files are free and LearningDITA itself, the website, the platform has always been free, but now we are introducing a new pricing model. And so Alan, I wanted to ask you about that, how that change came about, why we made that decision to go from an entirely free resource to something with a new pricing model?

AP: Yeah, that’s a hard one and it was not a fun discussion. It wasn’t. But basically considering we’ve got 10 years of work invested in this, we had both hundreds of hours invested in developing and maintaining the site and all the courses. We also have hosting costs involved. So it got to the point to where especially with those 16,000 students, things were just not sustainable. And the tech model, the tech stack was not working anymore. So we knew we had to do something and invest more time into the platform or frankly abandon it. And when you look at the choices, completely shut down the site and get rid of that resource or decide to charge very small amounts. The intro course will always be free. That was the decision that we made. And there will be coupon codes. There will be discounts for courses and other things. So we realize we are changing from the free model. Wish we didn’t have to do it. But looking at the reality of the time that we’ve invested in it and to keep it running in the future, that was a decision that we made to keep this running for the long haul.

GK: And I think, like we’ve said, we’ve seen so many changes in the content space, the industry itself over these years. And I think evolving and making sure that we are keeping track of the value that we add by having this resource makes sense to go to that pricing model.

AP: And I want to talk a little more about the Moodle part of this equation, because the way that it works is different than what we had before. And I think it’s worth noting the user experience is a little different. Because when you open up a course, it essentially opens up in a SCORM package viewer. Allison, could you talk just a little bit about how that experience is different?

AB: Yeah. So something that we noticed about Moodle is that it’s a very low-code, no-code type of platform. And so part of that SCORM decision was we wanted to be able to single source the content that lives in that repo or repository. We didn’t want to manually insert all that content. And so the way that SCORM ends up interacting with the Moodle site is that instead of having the content baked into webpages, it launches equivalent to an iframe, but it launches a second window where you take the course. And then when you close out that window, it ends your session. So don’t freak out if a second window pops up when you go to take your course. That’s the way that it is designed to work with the SCORM transform.

AP: And then Moodle records your activity, how well you’ve done with the quizzes, and all of that kind of information.

AB: And on the technical back end, all of that grade recording and assessment tracking is something that is handled because of the SCORM transform and how we built the Moodle site.

AP: And I think it is time for us to mention the people who really helped build that Moodle transform. Let’s call them out by name. Thank you to Jake Campbell, Simon Bate, and Melissa Kershes. Thanks to all of them for getting in there and helping us get that done.

GK: And I can just say after doing a lot of end user testing to make sure this works, I actually think it is easier to keep track of where you are than it was in our previous platform. I like that it pops things out into a new window. It really helps you, guide you along as you go through each part of the course. And it pops up with notifications about saving your progress if you need to stop and start a course at any point. And it does make it very clear where you are in the course and whether you have passed those assessments. And so the entire package does work really well. I think it’s really intuitive as an end user. And hopefully for all of you who go and take the courses on the new platform, you will see the same thing.

AP: I think it’s worth mentioning too, moving to this new platform, it’s going to give us opportunities to do more things in the future. We will be adding new content, especially as the DITA 2.0 standard comes out. So when that is released by the committee that controls the standard, we will do some updates to our courses. And I think we’re going to maybe do some micro learning perhaps, some live e-learning. We’ve got lots of choices here, so stay tuned for that.

And with that, Allison and Gretyl, I want to thank you very much for your work on the site and for talking with us today.

GK: Absolutely. Thank you.

AB: Thank you.

The post LearningDITA: What’s new and how it enhances your learning experience appeared first on Scriptorium.

Gretyl Kinsey: The ultimate end goal of a taxonomy is to make information easier to find, particularly for your user base because that’s who you’re creating this content for. With learning material, the learner is who you’re creating your courses for. Make sure to keep that end goal in mind when you’re building your taxonomy.

Related links:

• • Taxonomy: Simplify search, create consistency, and more (podcast, part 1)
  • The challenges of structured learning content (podcast)
  • DITA and learning content
  • Metadata and taxonomy in your spice rack
  • Transform L&D experiences at scale with structured learning content

LinkedIn:

• Gretyl Kinsey
• Allison Beatty

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Allison Beatty: I am Allison Beatty.

Gretyl Kinsey: I’m Gretyl Kinsey.

AB: And in this episode, Gretyl and I continue our discussion about taxonomy.

GK: This is part two of a two-part podcast.

AB: So if you don’t have a taxonomy for your learning content, but you know need one, what are some things to keep in mind about developing one?

GK: Yeah, so there are all kinds of interesting lessons we’ve learned along the way from working with organizations who don’t have a taxonomy and need one. And I want to talk about some of the high-level things to keep in mind, and then we can dive in and think about some examples there. One thing I also want to just say upfront is that it is very common for learning content in particular to be developed in unstructured environments and tools like Microsoft Word or Excel. It’s also really common that if you are working within a learning management system or LMS for there to be a lack of overall consistency because the trade-off there is you want flexibility, right? You want to be able to design your courses in whatever way is best suited for that specific subject or that set of material. But that’s where you do have that trade-off between how consistent is the information and the way it’s organized versus how flexible is it to give your instructional designers that maximum creativity. And so when you’ve got those kinds of considerations, then that can make the information harder for your students to find or to use and even for your content creators. So we’ve seen organizations where they’ve said, “We’ve got all of our learning materials stuck in hundreds of different Word files or spreadsheets or in sometimes different LMS’ or sometimes different areas in the same LMS.” And when they have all of those contributors, like we talked about with multiple authors contributing, or sometimes lots and lots of subject matter experts part-time contributing, that really creates these siloed environments where you’ve got different little pieces of learning material all over the place and no one overarching organizational system. And so that’s typically the driving point that see where that organization will say, “We don’t have a taxonomy. We know that we need one.” But I think that is the first consideration is if you don’t have one and you know you need one, the first question to ask is why? Because so often it is those pain points that I mentioned, that lack of one cohesive system, one cohesive organization for your content, and sometimes also one cohesive repository or storage mechanism. So that’s typically where you’ll have an organization saying, “We don’t have a good way to kind of connect all of our content and have that interoperability that you were talking about earlier, and we need some kind of a taxonomy so that even if we do still have it created in a whole bunch of different ways by a bunch of different people, that when it gets served to the students who are going to be taking these courses, it’s consistent, it’s well-organized, it’s easy for people to find what they need.” So I think that’s the first consideration is that if you’ve got that demand for taxonomy developing, think about where that’s coming from and then use that as the starting point to actually create your taxonomy. And then I think one other thing that can help is to think about how your content is created. So if you do have those disparate environments or you’ve got a lot of unstructured material, then take that into account and think about building a taxonomy in a way that’s going to benefit rather than hinder your creation process. And that is especially important the more people that you have contributing to your learning material. It’s really helpful to try to gather information and metrics from all of your authors and contributors, as well as from your learners. So any kind of a feedback form that, if you’ve got some kind of an e-learning or training website where you can assess information that your learners tell you about, what was good or bad about the experience, what was difficult or what would make their lives easier, that’s really great information for you to have. But also from your contributors, your authors, your subject matter experts, your instructional designers, if they have a way to collect feedback or information on a regular basis that will help enhance the next round of course design, then all of that can contribute to taxonomy creation as well. When you start building a taxonomy from the ground up, you can look at all the metrics that you’ve been collecting and say, “Here’s what people are searching for. We should make sure that we have some categories that reflect that. Here are difficulties that our authors are encountering with being able to find certain information and keep it up to date or with being able to associate things with learning objectives. So let’s build out categories for that.” So really making sure that you use those metrics. And if you’re not collecting them already, it’s never too late to start. I think the biggest thing to keep in mind also is to plan ahead very carefully and to make sure that you’re thinking about the future, that you’re doing futureproofing before you actually build and implement your taxonomy. And I know we both can probably speak to examples of how that’s been done well versus not so well.

AB: Yeah, maintenance is so important.

GK: Yeah, and I think the more that you think about it upfront before you ever build or put a taxonomy in place, the easier that maintenance is going to be, right? Because we’ve seen a lot of situations where an organization will just start with a taxonomy, but maybe it’s not broad enough. So maybe it only starts in one department. Like they have it for just the technical docs, but they don’t have it for the learning material. And then down the road it’s a lot more difficult to go in and have to rework that taxonomy for new information that came out of the learning department. That if they had had that upfront, it could have served both training and technical docs at the same time. So thinking about that and doing that planning is one of the best ways to avoid having to do rework on a taxonomy.

AB: And I’m glad you brought up the gathering of feedback and insight from users before diving into building out a taxonomy. Because at the end of the day, you want it to be usable to the people who need that classification system. That is the most important part.

GK: Yeah, that’s absolutely the end goal.

AB: Usability.

GK: Yeah, and I think a big part of that, like I’ve mentioned, planning ahead carefully and futureproofing, is looking at metrics that you’ve gathered over time because that can help you to see whether something in those metrics or in that feedback is a one-off fluke or whether it’s an ongoing persistent trend or something that you need to always take into consideration from your end users. If you’ve got a lot of people saying the same things, a lot of people using the same search terms over time, that can really help you with your planning. And yeah, like you said, I think the ultimate end goal of a taxonomy is to make information easier to find, and in particular for your user base because that’s who you’re creating this content for. And with learning material, that’s who you’re creating your courses for. So you want to make sure that when you’re building that taxonomy, that that end goal is something you always keep in mind. How can we make this content easier for people to find and to use?

AB: Definitely. Something else that I am curious to get your take on is in this planning stage. So in my experience, I feel like there’s never nothing to start with. Even if there’s not any formalized standards or anything around classification of content, there’s like a colloquial system, right?

GK: Yes, very much so.

AB: Of how content creators or users think about an organized content, even if they’re not necessarily using a taxonomy.

GK: Yeah. A lot of times it’s very similar to when we just talked about content structure itself. That if you’re in something like Microsoft Word or Unstructured FrameMaker, even if there’s not an underlying structure, a set of tags under that content, there is still an implied structure. You can still look at something like a Word document and say, “Okay, it’s got headings at these various levels. It’s got paragraphs. It’s got notes,” and you can glean a structure from that even though that structure does not exist in a designated form, right? So taxonomy is the same way. You’ve got people using information and categorizing information, even if they don’t have formal categories or a written down or tagged taxonomy structure. There’s always still some a way that people are organizing that material so that they can find it as authors or so that their end users can find it as the audience. And so that’s also a really good place to draw from. If you don’t have that formal taxonomy in place, you do still have an implied taxonomy somewhere. And so that’s where, going back to what you said about gathering the metrics, that’s a lot of times how you can find it and start to root it out if you are looking for that starting point of here’s how we need to build this formal taxonomy. So I think that’s step one is after you’ve figured out why you need to have that formal taxonomy in place, what’s the driving factor behind it? Then start going and hunting down that information about your existing implied taxonomy and how people are currently finding and categorizing information, because that will help you to at least start drafting something. And then you can further plan and refine it as you take into account the various metrics from your user base, and then gather information across all the different content producing departments in your organization until you finally settle on what that taxonomy structure should look like.

AB: I know that the word taxonomy can sound complicated and scary and all that, but you’re never really starting with the fear of a blank page. Taxonomies are everywhere and in everything, even if they’re not formalized. Think about when you go to the grocery store and you know you need ketchup and you’re going to go to the condiment aisle to find that. There’s so much organization and hierarchy just in our day-to-day lives that exist already. That’s never a fear of a blank page with taxonomies. There’s just thinking of the future and being mindful that things may change and maintenance will happen.

GK: Exactly. I think that point that you made about even when you go to the grocery store, humans think in taxonomy, right? Humans naturally categorize things.

AB: And group things. Yeah.

GK: And so I think the main goal of having a taxonomy formalized is to take that out of people’s heads and actually get it into a real form that multiple people can all use together, and then that serves that ultimate end goal we talked about of making things easier for your users to find.

AB: Access. Definitely. I want to talk about some lessons learned based on taxonomies that you and I have worked with clients, and I’m thinking of how you’re never starting with a blank page. I’m thinking about one project in particular where we developed a learning content model and used Bloom’s Taxonomy as a jumping-off point for this learning model. That’s another option or another way to go about it is use the implied structure in combination with a structure that already exists and integrating that into your content model. And then on the other hand, I know we’ve also done taxonomies for learning where we’ve specialized a lot.

GK: And specialization is always interesting because we see that develop out of… If you are putting out information that is very specific, so for example, if you are putting out learning material or courses around… I’ll go back to the example from earlier. Here’s how to use this specific kind of software. Here’s a class that you can take to get certified for doing this kind of an activity and this kind of software. Then that’s when it makes sense to think about any kind of specialized structures that you might want to have that are specific to that software. And it can be the same in whatever kind of material that you’re presenting. If you’re saying, “Oh, we’re in the healthcare industry. We are in the finance industry. We’re in the technology industry,” whatever your industry is, there’s going to be specific information to that industry that you probably want to capture as part of your taxonomy. Those categories are going to be specific to that industry and to the product or material that you are producing or to the learning material, the courses that you’re creating. So that’s a really good thing to think about when it comes to that taxonomy development is if we are in any very specific industry where we need that industry-specific information in the taxonomy, then it’s going to be really important to specialize. And so if you’re working in DITA XML, specialization is creating custom elements from out of the box or existing ones or standard ones. And so whenever you think about a taxonomy that is driven by metadata in DITA XML, then that’s where you might start creating some custom metadata elements and attributes that can drive your taxonomy. And those custom names for those elements and attributes would be something that you do specialize in and that matches the requirements or the demands of your industry.

AB: Yeah, that’s spot on with the example I was talking about a while ago about how the Library of Congress uses Library of Congress subject headings, but the National Library of Medicine has their own classification system for cataloging. But under the hood, they’re both Dublin Core. They’re both specialized Dublin Core. You know what I mean?

GK: Yes.

AB: There’s different context and then… Yeah, totally. Oh, this was the question I was going to ask you. Is there a trade-off with heavy specialization in your taxonomy?

GK: I think the biggest trade-off is maintenance. So we were talking earlier about how when you’re doing that initial planning that you want to think about futureproofing and you want to think about how you can make it as easy to maintain as possible within reason, of course, because nothing is ever easy when it comes to content development.

AB: That’s true.

GK: But yeah, when it comes to heavy specialization, that’s the biggest thing to consider is that for any kind of specialized tagging, you have to have specialized knowledge, so people who understand the categories, who know how to build that specialization and how to maintain it. So you have to have those resources available, and you also have to think about when you need to inevitably add or change the material, how much more difficult is that going to be if you specialize tags. Maybe it’s going to actually enhance things. And so instead of making things more difficult, it might be a little bit easier if you are specializing because then you already have created custom categories before. And if you need to add one down the road, you’ve got a roadmap for that. But it really depends on your organization and the resources that you have available. And thinking specifically about learning content as well, I think one of the biggest areas where heavy specialization can be challenging is that it is typical to have so many part-time contributors and subject matter experts who are not going to be experts in the tagging system. They’re just going to be experts in the actual material that they’re contributing. And so if they have to learn how to use those tags to a certain extent, then sometimes the more customization or specialization that you do, the more difficult that can be for those contributors, and it can make it sometimes difficult to get them on board with having that taxonomy in the first place.

AB: Yeah, change management.

GK: So I think that’s the big trade-off. Yes, change management, maintenance, and thinking about the best balance for making sure that things are useful for your organization. That you’ve got the taxonomy in place that you need, but it’s also not going to be so difficult to maintain that it essentially fails and that your authors and contributors don’t want to keep it going.

AB: This is a big question, but who’s responsible for maintaining a taxonomy within an organization that develops learning content site.

GK: So I think there’s a difference here between who is responsible and who should be responsible.

AB: Oh, that’s so true.

GK: If we think about best practice, it really should just be I would say generally a small team who is designated for that role, who has an administrative role so that they can be in charge of governance over that taxonomy. Because if you don’t have that, if you don’t have the best practice or the optimal situation, then instead, what can happen is that either no one’s managing the taxonomy, which is obviously bad, because then it can just continue to spiral out of control, or it’s almost like a too many cooks in the kitchen a situation, where if you don’t have that designated leadership or governance role over taxonomy, and anyone can update it or make changes to it, then it loses all of its meaning, all of its consistency. I do think it’s important that it’s a small team and not one single person. Because if that person is sick or something, then you’re left high and dry. So you want to make sure you’ve got it’s a small enough team that it’s not going to have the too many cooks in the kitchen problem, but it’s also not just one person.

AB: Another reason that it’s not ideal to have just one person is diversity prevents bias in your taxonomy, right?

GK: Absolutely.

AB: If one person has a confirmation bias about a specific facet and they document it or build something that way, but no one in the organization… You know what I mean?

GK: Yeah. So that’s where that small team can provide checks and balances too.

AB: Totally.

GK: You can have things set up where maybe every person on that team has to approve changes that are made to the taxonomy, or when they’re initially designing it, they all are giving the final review and final approval on it, so that way you’re not having it just through one person and whatever biases that person might carry.

AB: And biases isn’t necessarily a negative connotation, but just that people see the world differently from person to person. And by world, I do mean learning content sometimes. Is there anything else that you wanted to cover?

GK: I think I just want to wrap things up by saying the big things to keep in mind, the main points that we talked about when you’re developing a taxonomy, whether it is for learning content or just more broadly, are to plan ahead, think ahead, do all of the planning upfront that you can, rather than just building things, so that that way you can avoid rework. Use the metrics of the information that you’ve gathered from both inside your organization and from your user base. And finally, keep that end goal in mind that this is all about making things easier for people to use, for people to find content and develop your taxonomy with that end goal in mind.

AB: Yeah, I agree with all of that. Well, thanks so much for talking with me, Gretyl.

GK: Of course. Thank you, Allison, for talking with me.

Outro with ambient background music

Christine Cuellar: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

Behind every successful taxonomy stands an enterprise content strategy

Building an effective content strategy is no small task. The latest edition of our book, Content Transformation is your guidebook for getting started.

The post Building your futureproof taxonomy for learning content (podcast, part 2) appeared first on Scriptorium.

Allison Beatty: I know we’ve made taxonomies through all sorts of different frames, whether it’s structuring learning content, or we’ve made product taxonomies. It’s really a very flexible and useful thing to be able to implement in your organization.

Gretyl Kinsey: And it not only helps with that user experience for things like learning objectives, but it can also help your learners find the right courses to take. If you have some information in your taxonomy that’s designed to narrow it down to a learner saying, “I need to learn about this specific subject.” And that could have several layers of hierarchy to it. It could also help your learners understand what to go back and review based on the learning objectives. It can help them make some decisions around how they need to take a course.

Related links:

• The challenges of structured learning content (podcast)
• DITA and learning content
• Metadata and taxonomy in your spice rack
• Transform L&D experiences at scale with structured learning content
• Rise of the learning content ecosystem with Phylise Banner (podcast)

LinkedIn:

• Gretyl Kinsey
• Allison Beatty

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Gretyl Kinsey: Hello and welcome. I’m Gretyl Kinsey.

Allison Beatty: And I’m Allison Beatty.

GK: And in this episode, we’re going to be talking about taxonomy, particularly for learning content. This is part one of a two-part podcast.

AB: So first things first, Gretyl, what is a taxonomy?

GK: Sure. A taxonomy is essentially just a system for putting things into categories. Whether that is something concrete like physical objects or whether it’s just information. A taxonomy is going to help you collect all of that into specific categories that help people find what they’re looking for. And if you’ve ever been shopping before, you have encountered a taxonomy. So I like to think about online shopping, in particular, to explain this because you’ve got categories for the type of item that you’re buying at a broad level that might look something like you’ve got clothing, household goods, electronics, maybe food. And then within that you also have more specific categories. So if we start with clothing, you typically will have categories for things like the type of garment. So whether you are looking for shirts, pants, skirts, coats, shoes, whatever. And then you also might have categories for the size, for the color, for the material. They’re typically categories for the intended audience. So whether it’s for adults or kids. And then within that may be for gender. So all these different ways that you can sort and filter through the massive number of clothing results that you would get if you just go to a store and look at clothing. You’ve got all of these different pieces of information, these categories that come from a taxonomy where you can narrow it down. And that typically looks like things on a website, like search boxes, checkboxes, drop-down menus, and those contain the assets or the pieces of information from that taxonomy that are used to categorize that clothing. So then you can go in and check off exactly what you’re looking for and narrow down those results to the specific garment that you were trying to find. So the ability to go on a website and do all of that is supported by an underlying taxonomy.

AB: So that’s an example of online shopping. I’m sure a lot of people are familiar with taxonomies in the sense of biology, but how can taxonomies be applied to content?

GK: Sure. So we talk about taxonomy in terms of content for how it can be used to find the information that you need. So when you think about that online shopping example, instead of looking for a physical product like clothing. When it comes to content, you’re just looking for specific information. So it’s kind of like the content itself is the product. So if you are an organization that produces any kind of content, you can put a taxonomy in place so that your users can search through that content. They can sort and filter the results that they get according to those categories and your taxonomy. And that way they can narrow it down to the exact piece of information that they’re looking for instead of having to skim through a long website with a lot of pages, or especially if you’re dealing with any kind of manuals or books or more publications that you’re delivering. Not forcing them to read through all of that instead of being able to search and find exactly what they’re looking for. So some of the ways that taxonomies can help you categorize your content would be things like what type of information it is. So whether it is more of a piece of technical documentation, something like a user manual or a quick start guide or a data sheet, or whether it is marketing material, training material. You could put that as one of the categories in your taxonomy. You could also put a lot of information about your intended audience. So that could be things like their experience level. It could be things like the regions they live in or the languages they speak. Anything about that audience that’s going to help you serve up the content that those particular people need. It can also be things like what platform your audience uses or what platform is relevant for the material that you’re producing. It can be things like the product or product line that your content is documenting. There are all kinds of different ways that you can categorize that information. And I know that both of us have a lot of experience with putting these kinds of things together. So I don’t know if you’ve got any examples that you can think of for how you’ve seen information get categorized.

AB: So a lot of the way I think about taxonomies is a library classification system or MARC records so in the same way that if you wanted to find a particular information resource and you went to your library’s online catalog and could filter down to something that fits your needs. You can think of treating your organization’s body of content like a corpus of information that you can further refine and assign metadata values to. Or in the case of a taxonomy hierarchy in the clothing example, choosing that you want a shirt would be a step above choosing that you want a tank top or a long sleeve shirt or a blouse. So a lot of my mindset around taxonomies for content is framed like libraries. The Library of Congress subject headings are generally a good starting off point for a library. But sometimes if your library has specific information needs, like the National Health Library has its own subject scheme that is further specialized than the broader categories that you get in Library of Congress subject headings, because they know that everything in that corpus is going to be health or medicine related information. And in the same way you and I have developed taxonomies for clients that are particular to their needs, you’re never going to start off knowing nothing when you build a taxonomy, right?

GK: Exactly. And with the example that you were talking about of kind of looking at information in a library catalog, we see that with a lot of documentation. So if you’re thinking about technical content and things like product documentation, user guides, user manuals, we see that similar kind of functionality. If you have that content available through a website or an app or some other kind of digital online experience, back to the online shopping example. Your user base can in all of those different cases, go to those facets and filters, those check boxes, drop down menus, search boxes, and start narrowing down the information to what exactly they’re looking for. So that really helps to enhance the user experience to have that taxonomy in place underlying the information and making it easier to narrow down. I’ve also seen it really helpful on the authoring side. So if you have a large body of content, maybe you have it in something like a content management system. And more content that you have, the harder it becomes to find the specific information that you’re looking for. In particular, we deal with a lot of DITA XML. And so there will be a component content management system that that’s typically housed in. And when you’ve got it in there, those systems typically have some kind of underlying taxonomy in place as well that can capture all kinds of information about how and when the content was created. So that can help you find it. And then of course, you could have your own taxonomy for the kinds of things I named earlier, what type of information it is, what the intended audience is in case that can help you as the author find and narrow down something in your system. And it can also help you as an author to put together collections of content for personalized delivery. So maybe you have a general version of your user guide, but then you’ve also got audience specific versions that you can kind of filter and narrow it down to based on the metadata in your content. And that’s all going to be informed by those categories in your taxonomy. So really leveraging any of the information that you have about your audience, about how they use your content or how they need to use your content is really going to help you deliver it in a more flexible way and in a more efficient way as well.

AB: I know for me personally, sometimes the amount of information out in the world can get very overwhelming.

GK: Absolutely.

AB: So I’m thinking about our LearningDITA e-learning project, and how much content we’ve collected between different versions of it and over the amount of time it’s been up, and it makes it so much easier to navigate knowing where pieces of content are when I’m looking for something as an author on that project.

March 2025 update: We have moved LearningDITA to a new platform. The Introduction to DITA course is still free, and you can sign up for courses at store.scriptorium.com.

GK: And that actually brings up a really good point because we were talking about the taxonomies used in content. We were primarily talking about technical content, so things like product documentation, user guides, legal, regulatory, but it can also be used for other types of content. And learning content is a really big one, and we are seeing that more and more.

AB: Absolutely.

GK: There’s a lot of overlap at organizations between technical documentation and learning or training material, especially if you make a product where there are certifications. So we see a lot of times, for example, with people who make software. That organization will usually have the product documentation, here’s how you use this software. But then there’s also training material so that if there are certifications around the use of that software, then there’s that material where their user base can go take a class and essentially be students or learners in that context rather than just consumers of the product. And so there’s a lot of need to share information across the technical documentation and the learning material.

And we see more and more organizations where the learning material is kind of their main product, looking for ways to better categorize that information and have a taxonomy underneath it. And so when you mentioned LearningDITA, that kind of got me thinking about how not only that useful for us as the creators of LearningDITA, but for all the other organizations that also produce learning material. How much a taxonomy helps that experience, not only for them as the authors, but also for their end users.

AB: It’s a win-win for users and creators. Something I would like to discuss is self-guided e-learning, and how a taxonomy can make it easier to tie assessments to learning objectives in that sort of asynchronous setting as opposed to a more traditional classroom.

GK: And e-learning is really interesting because there’s a lot of flexibility out there in terms of how you can present that information and how you can gather information from the students or the learners taking your e-learning courses. And we’ve seen different categories or taxonomies around gathering information or putting information on your learning material about things like the intended reading level or grade level if you’re dealing with students who are still in school. You could also put information about things like the industry. If your learner base is professionals, you can put information about the subject that you’re covering, the type of the certification associated with that material. And then like you mentioned, learning objectives. So typically with any kind of a course that’s put out there for students to take, whether it’s e-learning or whether it’s just in a classroom, there are specific learning objectives that that material is intended to cover. So whenever you as a student get to the end, it’s basically you should be able to understand this concept or perform this activity as a result of taking this course. And we have seen a lot of demand in various different industries for tying those learning objectives to the assessment questions. So if you’re in an e-learning course, you’ve got your kind of self-guided material where you’re walking through, you’re reading, maybe you’re doing some exercises, maybe you’re watching some videos or looking at some examples. And then at the end there’s some kind of a quiz or an assessment to test your knowledge. And with e-learning, that’s typically something where you’re entering answers, maybe you’re checking boxes for multiple choice questions, or you’re typing a response in, or you’re picking true faults, things like that. So you take that quiz and the questions in that quiz are tied back to those learning objectives from the beginning of the lesson. So that way if you get a question wrong, it can tell you this is the specific learning objective that you missed this question four, and that you should go back and review more material that’s associated with that learning objective. And having all of that tied together so that your e-learning environment can actually serve up that information is where it can really help to have a taxonomy underneath. When you think about it, learning objectives themselves kind of naturally fall into categories. And there are even standards when you think about things like Bloom’s taxonomy, that’s a typical standard that’s applied to learning material. And of course you could also come up with whatever categories that you want for your learning information, but those objectives are often tied directly to the categories. And then being able to have the structure in place to tie those objectives and the taxonomy categories that are associated with to your assessment questions to the rest of your material just makes the whole experience a lot more seamless and streamlined for your learners.

AB: It’s so valuable, particularly learning objectives. I’m glad you brought up Bloom’s taxonomy because I think that’s a pretty familiar entry point to taxonomies for a lot of people who work in the learning space. And I’m kind of also thinking about whether it’s learning content or technical documentation, any implementation of a taxonomy for a body of digital content. It sort of turtles all the way down, whether it’s a learning objective that is the value or significance being assigned to a piece of content. If you think about information theory and how sort of the basis of what is a node and a taxonomy is it’s a discrete thing. And I know it drives people crazy. That thing is more or less the technical term in that situation. It sounds so vague, but the thing is, it’s a discrete object that has a purpose for why it exists, whether it’s a learning objective that’s tied as an attribute in your DITA or piece of metadata somewhere or elsewhere, or whether it’s technical documentation that’s telling you which product, a piece of content assigns to. I know we’ve made taxonomies through all sorts of different frames, whether it’s structuring learning content, or we’ve made product taxonomies. It’s really a very flexible and useful thing to be able to implement in your organization.

GK: And it not only helps with that user experience for things like learning objectives, but it can also help your learners just find the right courses to take. So if you have some information in your taxonomy that’s designed to narrow it down to a learner saying, “I need to learn about this specific subject.” And that could have several, of course, layers of hierarchy to it. It could also help your learners to understand what to go back and review based on the learning objectives. It can help them to maybe make some decisions around how they want to take a course. So when you think about e-learning, you can have it be self-guided and asynchronous, or sometimes it could be instructor-led. And so if you’ve got something like that baked into your taxonomy, something about the method of delivery that could help your learners decide which mechanism is going to be better for them. So all of that can be really helpful. And I also want to talk about it again from going back to the creator side, just like we did with technical content. Because if you are designing learning material, you’re an instructional designer, you’re putting together a course, then you might want some information about things like the learner’s progress, their understanding of the material. You’re going to want to obviously capture all the information around the scoring and grading from the assessments that they take. And having that tied back to a taxonomy, whether it’s to learning objectives or to any other information, can help you to understand how you might need to adjust the material. So if you notice, for example, that you’ve got one learning objective that everyone seems to struggle to understand, you’ve got a large percentage of your students missing the assessment questions associated with that learning objective, then maybe that tells you we need to go back and rewrite this or rework how it’s presented. So the taxonomy can not only help your learners find the information, navigate the courses, and take the courses that they need, but it can also help you to adjust the design of those courses in a way that further enhances their learning experience.

AB: Absolutely. Something else that you just made me think of is say you have an environment of creating learning content with multiple authors. Another advantage of the taxonomy is that it can standardize metadata values. So say you and I, Gretyl are working within the same learning organization, and then when content that’s written by either one of us goes to publish, the metadata values will be standard if we use the same taxonomy.

GK: And that’s also a really important point because that standardization is good not only across just a subset of your content, like your learning material, but we’ve seen some organizations go more broad and say, “Our learning content and our technical docs and our marketing material.” And whatever other content they have, all needs to have a consistent set of terminology. It needs to have a consistent set of categories that people use to search it. And so you can think about taxonomy at a broader level too, for all the information across the entire company or the entire organization, and make sure that it’s all going to fit into those categories consistently because it is, like you said, very typical to have lots of different people contributing to content creation. And then in particular, with learning content, we see a lot of subject matter experts and part-time contributors who do something else, but then they might write some assessment questions or they might write a lesson here and there. And having the ability to have that consistent categorization of information, consistent terminology, consistent application of metadata is really, really helpful when you’ve got so many different people contributing to the content because that helps to make sure that they’re not going to be introducing inconsistencies that confuse your end users.

AB: That’s really a strength of most classification systems, whether it’s a controlled vocabulary or something more sophisticated like a taxonomy. And I’m thinking about something that you and I see a lot working with clients with DITA XML in particular is sort of blending technical and marketing content once DITA is implemented and having interoperability with your taxonomy definitely is a boon to that.

GK: Absolutely. I think that’s a good place to wrap up for now. We’ll be continuing this discussion in the next podcast episode. So Allison, thank you.

AB: Thank you.

Outro with ambient background music

Christine Cuellar: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

Behind every successful taxonomy stands an enterprise content strategy

Building an effective content strategy is no small task. The latest edition of our book, Content Transformation is your guidebook for getting started.

The post Taxonomy: Simplify search, create consistency, and more (podcast, part 1) appeared first on Scriptorium.

There are other people in the content creation world who have had problems with content duplication, having to copy from one platform or tool to another. But I will tell you, from what I have seen, the people in the learning development space have it the worst in that regard—the worst.

— Alan Pringle

Related links:

• The challenges of structured learning content (podcast)
• DITA and learning content
• Rise of the learning content ecosystem with Phylise Banner (podcast)
• Flexible learning content with the DITA Learning and Training specialization
• Building an effective content strategy is no small task. The latest edition of our book, Content Transformation is your guidebook for getting started.

LinkedIn:

• Alan Pringle
• Bill Swallow

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

AP: Hey, everybody, I’m Alan Pringle.

BS: I’m Bill Swallow.

AP: And today, Bill and I want to talk about structured content in the learning and development space. I would say, the past two years or so, we have seen a significantly increased demand of organizations who want to apply structured content to their learning and development processes, and we want to share some of the things those organizations have been through and what we’ve learned over the past few months, because I suspect there are other people out there who could benefit from this information.

BS: Oh, absolutely.

AP: So let’s talk about, really, the drivers, what are the things that people, content creators in the learning development space, what’s driving them to it? One of them off the bat is so much content, so, so very much content, on so many different delivery platforms. That’s one that I know of immediately, what are some of the other ones?

BS: Oh, yeah, you have just the core amount of content, the number of deliverables, and the duplication of content across all of them.

AP: That is really the huge one, and I know there are other people in the content creation world who have had problems with content duplication, having to copy from one platform or tool to another. But I will tell you, from what I have seen, the people in the learning development space have it the worst in that regard—the worst.

BS: Didn’t they applaud you when you showed up at a conference with a banner that said end copy, paste?

AP: Pretty much, it’s true. That very succinct message raised a lot of eyebrows, because they are in the position, unfortunately, in learning and development, having to do a lot of copying and pasting, and part of the reason for that copying and pasting is, a lot of times, the different platforms that we’ve mentioned, also, different audiences. I need to create this version for this region, or this particular type of student at this location, so they’re copying and pasting over and over again to create all these variants for different audiences, which becomes unmanageable very quickly.

BS: Yeah, copy, pasting, and then, reworking. And then, of course, when they update it, they have to copy, paste, and rework again to all the other places it belongs, and then, they have to handle it in however many languages they’re delivering the training in.

AP: So now, everything is just blown up. I mean, how many layers of crap, and I’m just going to say it, do these people have to put up with? And there are many, many, many.

BS: Worst parfait ever.

AP: Yeah, no, that is not a parfait I want to share, I agree with you on that. So let’s talk about the differences between, say, the techcomm world and the learning and development world and their expectations for content. Let’s talk about that, too, because it is a different focus, and we have to address that.

BS: So techcomm really is about efficiency and production, so being able to amass quite a wide mass of content and put it out there as quickly as possible, or put it out there as efficiently as possible. Learning content kind of flips that on its head, and it wants to take quality content and build a quality experience around it, because it’s focused on enabling people to learn something directly.

AP: And techcomm people, we’re not saying you’re putting out stuff that is wrong or half ass. That is not what we mean, I want to be real clear here. What we mean is, there is a tendency to focus on efficiency gains, and getting that help set, getting that PDF, getting that wiki, whatever thing that it is that you’re producing, getting that stood up as quickly as possible, whereas on the learning side, speed is not usually the thing that you’re trying to use to sell the idea of structured content. I don’t think that’s going to win a lot of converts in the learning space. I do think, however, you can make the argument, if you create this single source of truth so you can reuse content for different audiences, different locations, different delivery platforms, and you’re using the same consistent information across all of that, you are going to provide better learning outcomes, because everybody’s getting the same information. Regardless of what audience they are or what platform that they’re learning, whether it’s live instructor-led training, something online, whatever else, you’re still getting the correct same information, whereas if you were copying and pasting all that, you might’ve forgot to update it in one place as a content creator, and then, someone ends up getting the wrong information, a student, a learner, and that’s when you’re not in the optimal learning experience situation.

BS: Right, and it’s not to say that every single deliverable gets the exact same content, but they get a slice from the same shared centralized repository of content so that they’re not rewriting things over and over and over again. And they’re still able to do a lot of high-quality animations, build their interactives, put together their slide presentations, everything like that, but use the content that’s stored centrally rather than having to copy and paste it again and again and again.

AP: Yeah, and let’s talk about, really, the primary goals for moving to structure content for learning and development folks. We’ve already talked about reuse quite a bit, that’s a big one. Write it one time, use it everywhere, and that also leads to creating profiling, different audiences, content for different audiences.

BS: Right, I mean, these goals really are no different than what you see in techcomm, and what techcomm has been using for the past 15, 20, 25 years. It is that reuse, that smart reuse, so write it once, use it everywhere, no copy paste, having those profiling attributes and capabilities built in so that you can produce those variants for beginner learners versus expert learners versus people in different regional areas where the procedure might be a little bit different, producing instructor guides as well as learner guides. All of these different ways of mixing and matching, but using the same content set to do that.

AP: Yeah, it’s like one of our clients said, and I have to thank them forever for bringing this up, they were bogged down in a world of continuous copying and pasting over and over and over again, and maintaining multiple versions of what should’ve been the same content, and they said, quote, “We want to get off the hamster wheel.” And that is so true and so fitting, and we probably owe them royalties for saying this over and over again, because such a good phrase. But it really did capture, I think, a big frustration that a lot of people in the learning and development space have creating content, because they do have to maintain so many versions of content.

BS: And those versions likely are stored in a decentralized manner, so they could be on multiple different servers, they could be on multiple different laptops or PCs, they could be on thumb drives in some random drawer that are updated maybe once every two, three years. So being able to pull everything together into a central repository and structure it so that it can be intelligently reused and remixed, there’s so many benefits to that.

AP: Yeah, and in regard to the remixing, the bottom line is, you want the ability to publish to all your different platforms. I believe the term people like to use is omnichannel publishing, so you basically can do push-button publishing to basically any delivery need that you have, whether it’s an instructor versus student guide for training you’re having live, e-learning, even scripts for video. Even when you’re dealing with a lot of multimedia content, there is still text involved, underpinnings of that content, audio and video, there’s still probably bits and pieces of that, that can come from your single source of content, because at the core of it, it’s text-based, even though if the delivery of it is a video or audio.

BS: Now, we’ve had structured content for a good couple decades, at least-

AP: At least, yeah.

BS: … but there really is a reason why the learning world really hasn’t latched onto it completely, and it really comes down to the different types of content that they need to produce versus what traditionally a techcomm group would do. So right off the bat, there are all the different tests, quizzes, and so forth, all the assessments that are built into a learning curriculum. There was never really anything built to handle those in traditional structured authoring platforms in schemas.

AP: And there are solutions now that will let you handle assessments and different types of questions, and things like that.

BS: But the whole approach to producing learning content, it’s quite similar to techcomm and to other classic content development, but it’s also quite unique in its own right, and we do have to make sure that all of those different needs, whether it be the assessments, any interactives that need to be developed, making sure that you tie in a complete learning plan, and perhaps even business logic to your content, making sure all that can be baked in intelligently so that we’re able to produce the things that we need to produce for trainers.

AP: Yeah, and now, especially, you have to be able to create content that integrates easily with the learning management system, which has its own workflows, it’s got tracking, it tracks progress, it scores quizzes, it keeps track of what classes you’ve taken, prerequisites, all of that stuff, that is a whole delivery ecosystem, and structured content can help you communicate with an LMS and create content that is LMS friendly by baking in a lot of the things that you just talked about.

BS: And the content really does boil down to a more granular and targeted presentation to the audience rather than techcomm, which is more of a soup to nuts, kind of everything in the kitchen sink approach to offer.

AP: Yeah, and then, there’s also the whole live delivery aspect, that is not something that’s really part of techcomm at all.

BS: I wouldn’t want someone there reading a manual to me.

AP: No, nor would I. Well, it might be a good way to treat insomnia, but that’s not what we’re here for. But you do have to consider, the assessments are a big difference from a lot of other content that is a good fit for the structure world, and then, the possibility of live instruction, that’s also another big difference, which, still, there are structured content solutions that can help you with both of those very distinct learning and development content situations. So I think it’s fair to say, based on talking to a lot of people at conferences focused on learning, and a lot of our clients, that the traditional way of creating learning and development content, it is not scalable. The copy and paste angle in particular is just not sustainable in any way, shape, or form.

BS: No, you have so many hours in a day, so if you need to start producing more, you really need to start adding more people. And you add more people, then you have the likelihood that more things could go wrong with the content, or the content could get-

AP: Will go wrong.

BS: … could get out of sync with itself.

AP: Yeah. Well, let’s talk also a little more about some of the challenges. We’ve talked about the interactivity, how that and the assessments, that’s something that’s kind of particular that you have to solve for in the learning space. Let’s talk about the P word, PowerPoint.

BS: PowerPoint. Yeah, being able to pull focus slides together, which really would likely have a very small subset of a course’s content built within them, unless you’re producing a wall of text per PowerPoint. Those are quite unique to the space, so you don’t see much in techcomm where things are delivered via PowerPoint, or you hopefully don’t.

AP: No, PowerPoint is great because it’s wide open and you can do a lot of things with it, PowerPoint is bad because it’s wide open and you could do a lot of things with it. That’s the problem with PowerPoint.

BS: And a template’s only as useful as those who follow it.

AP: Exactly. And now, you mentioned templates, structure content is a way to templatize and standardize your content, and I’m sure that can rub people the wrong way. My slides need to be special, this, that, and the other. There’s a continuum here of, I want to do whatever I want to the point of sloppy, or I can do things within this particular set of confines so there is consistency. And again, I think it’s fair to say, providing consistency for different learners with slide decks, that is going to make some better outcomes instead of a free-for-all, I can do whatever I want scenario. And I’m sure there are people out there who are going to kick and scream and disagree with me, but that’s a fight we’re just going to have to have folks.

BS: Well, no, it provides us a consistent experience throughout, rather than having some jarring differences from lesson to lesson or course to course.

AP: Yeah, yeah, and I think there’s one thing, too, that, in addition to the PowerPoint angle, with the learning and development space, there is this focus on, we need to create, this thing went off, that thing went off, and this other thing went off. There’s still standardization you can do among your different delivery targets that will streamline things, create consistency, and therefore, a better learning experience. I do believe that’s true, even though some people at first in particular can find it very confining.

BS: Oh, right, I mean, it just takes the development of the end user experience, I don’t want to say completely out of the learning content developer’s hands, but it kind of frees them up to better frame the content for the lesson rather than worrying about the fit and finish of the product.

AP: Yeah, and let’s focus now on some of the options out there in the structure content world for learning and development content. There’s several out there, let’s talk about what’s on the table.

BS: It comes down to two different types of systems, one would be a learning component management system, so it’s a system that’s more built for learning content specifically.

AP: Yeah, I would say it’s purpose built, I agree, yeah.

BS: Yeah, and it functions the same way as a lot of, I guess what we would call the traditional techcomm component content management systems do, where you’re able to develop in fragmented pieces, in a structured way, in a centralized manner, and intelligently reuse and remix all of these different components to produce some type of deliverable.

AP: Right, so you can therefore, within this system, set up things for different locations, different audiences, whatever else. And if you were moving into an LCMS or one of the other solutions we’re talking about, you are also going to make localization and translation much more efficient, and you’ll get stuff turned around in other languages for other locales much more quickly. So we’ve got the LCMS’s which are more proprietary, and then, on the flip side of that, let’s talk about DITA.

BS: So DITA does provide you with a decent starting point for developing your content, and we’ve helped several clients do this already, but a lot of the tools that are out there on the flip side, where the LCMS is targeted at developing learning content, a lot of the tools for DITA aren’t, so it requires a lot of customization on the tool chain, as well as in the content model, to get things up and running. However, DITA does give you an easier point of integration with any work that is being produced by your techcomm peers.

AP: Yeah, I do think it’s fair to say it’s a little more extensible, but the mere fact it is an open standard as an extensible means that it may take some configuring to make it exactly what you need it to be. And like Bill was saying, DITA has some custom structure that is a very good fit, it is specifically for learning and training, and you can further customize those customizations to match what you need. I will say, I think some of the assessment structures are not as robust as they should be, and we’ve had to customize those for some clients. So that’s another thing that you would have to kind of think about when you’re trying to make this decision, do I need to go with an LCMS, or do I want to go with DITA and a component content management system, and understand that I’m going to have to make some adjustments to make it more learning and development friendly?

BS: No matter which way you slice it, though, moving to any kind of a structured repository in a structured system really starts to open things up from a back end production point of view, while not necessarily forgoing a lot of the experience-driven design that goes into producing those different learning deliverables. It is a way to kind of become more efficient, and as Alan mentioned, avoid the copy and paste, which can be a nightmare to maintain over time.

AP: And at the same time, you do not have to throw out your standards for the quality of the content and the quality of the learning experience. You want to have structure, support, and bolster, and maintain those things, and don’t look at it as something that is going to degrade those things, because when used correctly, it can really help you maintain that level of quality and consistency that you really need for an outstanding learning experience. And with that, Bill, I think we can wrap up. Thank you very much.

BS: Thank you.

Outro with ambient background music

Christine Cuellar: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

Questions about this podcast? Let’s talk!

The post Transform L&D experiences at scale with structured learning content appeared first on Scriptorium.

When it comes time to write the RFP, rely on your procurement team, your legal team, and so on. They have that expertise. They know that process. It’s a matter of pairing what you know about your requirements and what you need with their processes to get the better result.

— Alan Pringle

Related links:

• Survive the descent: planning your content ops exit strategy (podcast)
• The business case for content operations (white paper)
• Content accounting: Calculating value of content in the enterprise (white paper)
• Building the business case for content operations (webinar)

LinkedIn:

• Sarah O’Keefe
• Alan Pringle

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Alan Pringle: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about writing effective RFPs. A request for a proposal, RFP, approach is common for enterprise software purchases, such as a component content management system, which can be expensive and perhaps risky. Hey everybody, I am Alan Pringle.

Sarah O’Keefe: And I’m Sarah O’Keefe, hi.

AP: So Sarah, we don’t sell software at Scriptorium, so why are we talking about buying software?

SO: Well, we’re talking about you, the client buying software, which is not always, but in many cases, the prerequisite before we get involved on the services side to configure and integrate and stand up the system that you have just purchased to get you up and running. And so, because many of our customers, many most, nearly all of our customers are very, very large, many of those organizations do have processes in place for enterprise software purchases that typically either strongly recommend or require an RFP, a request for proposal.

AP: Which let’s be very candid here. Nobody likes them. Nobody. 

SO: No, they’re horrible.

AP: Vendors don’t like them. People who have to put them together don’t like them, but they’re a necessary evil. But there things you can do to make that necessary evil work for you. And that’s what we want to talk about today.

AP: So the first thing you need to do is do some homework. And part of that homework, I think, is talking with a bunch of stakeholders for this project or this purchase and teasing out requirements. So let’s start with that. And this is even before you get to the RFP itself. There’s some stuff you need to do in the background. And let’s talk about that a little bit right now.

SO: Right, so I think, you know, what you’re looking to get to before you go to RFP is a short list of viable candidates, probably in the two to three range. I would prefer two, your procurement people probably prefer three to four. So, okay, two to three. And in order to get to that list of these look like viable candidates, as Alan’s saying, you have to do some homework. Step one, what are your hard, requirements that IT or your sort of IT structure is going to impose. Does the software have to be on premises or does it have to be software as a service? Nearly always these days organizations are hell bent on one or the other and it is not negotiable. Maybe you have a particular type of single sign-on and you have some requirements around that. Maybe you have a particular regulatory environment that requires a particular kind of software support. You can use those kinds of constraints to easily, relatively easily, rule out some of the systems that simply are not a fit for what your operating environment needs to look like.

AP: And by doing that, you are going to reduce the amount of work in the RFP itself by doing this now. So you’re going to streamline things because you’ve already figured out, this candidate is not a good fit. So why bother them and why make work for ourselves having to work and correspond with the vendor that ends up not being a good fit.

SO: Right, and if we’re involved in a process like this, which we typically do on the client side, so we engage with our customers to help them figure out how to organize an RFP process, right, we’re going to be strongly encouraging you to narrow down the candidate list to something manageable because the process of evaluating the candidates is actually quite time consuming on the client side. And additionally, it’s quite time consuming for the candidates, the candidate software companies to write RFP responses. So if you know for a fact that they’re not a viable candidate, you know, just do everybody a favor and leave them out. It’s not fair to make them do the work.

AP: No, it’s not. And we’ve seen this happen before where a organization will keep a vendor in the process kind of as a straw man to strike down fairly quickly. It would be kinder and maybe more efficient to do that before you even get to the RFP response process, perhaps.

SO: Yeah, and of course, again, the level of control that you have over this process may vary depending on where you work and what the procurement RFP process looks like. There are also some differences between public and private sector and some other things like that. But broadly, before you go to RFP, you want to get down to a couple of viable candidates, and that’s who should get your request for proposal.

AP: Yeah, and when it does come time to write that RFP, do rely on your procurement team, your legal team. They have that expertise. They know that process. It’s a matter of pairing what you know about your requirements and what you need with that process to get the better result. And I think one of the key parts of this communication between you and your procurement team is about use case scenarios. So let’s talk about those a little bit because they’re fundamental here.

SO: Yeah, so your legal team, your procurement team is going to write a document that gives you all the guardrails around what the requirements are and you have to be this kind of company and our contract needs to look a certain way and various things like that. We’re going to set all of that aside because A, we don’t have that expertise and B, you almost certainly as a content person don’t have any control over that. You’re just going to go along with what they are going to give you as the rules of the road in doing RFPs. However, somewhere inside that RFP it says, these are the criteria upon which we will evaluate the software that we are talking about here. And I think a lot of our examples here are focused on component content management systems, but this could apply to other systems whether it’s translation management, terminology, metadata, you know, all these things, all these content-related systems that we’re focused on. So, somewhere inside the RFP, it says, we need this translation management system to manage all of these languages, or we need this component content management system to work in these certain ways. And your goal as the content professional is to write scenarios that reflect your real world requirements that are unique to your organization. So if you are in heavy industry, then almost certainly you have some concerns around parts, about referencing parts and part IDs and maybe there’s a parts database somewhere and maybe there are 3D images and you have some concerns around how to put all of that into your content. That is a use case that is unique to you versus a software vendor who is going to have some sort of, we have 80 different variants of this one piece of software depending on which pieces and parts you license, and then that’s gonna change the screenshots and all sorts of things. So what you wanna do is write a small number of use cases. We’re talking about maybe a dozen. And those dozen use cases should explain, you know, as a user inside the system, I need to do these kinds of things. You might give them some sample content and say, here is a typical procedure and we have some weird requirements in our procedures and this is what they are. Show us how that will work in your system. Show us how authoring works. Show us how I would inject a part number and link it over to the parts database. Show us, you know, those kinds of things. So, the use case scenarios typically should not be, “I need the ability to author in XML,” right?

AP: Or, “I need the ability to have file versioning,” things that every CCMS on the planet does, basically.

SO: Right, somewhere there’s a really annoying and really long spreadsheet that has all those things in it, fine. But ultimately, that’s table stakes, right? They should not get to the short list unless you’ve already had this conversation about file versioning and the right class of system. The question now becomes, how do you provide a template for authors and what does it look like for authors to start from a template and do the authoring that they need to do? Is that a good match for how your authors need to or want to or like to work. So the key here from my point of view is don’t worry too much about the legalese and the process around the RFP, but worry a whole bunch about these use case scenarios and how you are going to evaluate all the different tools that you’re assessing against the use case scenarios.

AP: Be sure you communicate those use case scenarios to your procurement team in a way they understand so they have a better handle on what you need because if everybody is kind of on the same page as far as those use cases go the clearer it’s going to be to communicate those things to the candidate vendors when they do get their hands on the RFP.

SO: And I think as we’re going in or talking about going into a piece of software, there probably should already be some consideration around exit strategy, which Alan, you’ve talked about that a whole bunch. What does it mean to have an exit strategy and to evaluate that in the inbound RFP process?

AP: It is profoundly disturbing to have to think about leaving a before you’ve even bought it, but it does, does behoove you to do that because you need a clear understanding of how you are going to transition outside of a tool before you buy it. So when that happens, when you come to a point where you have to do it, you have an understanding about how you can technically exit that tool. For example, how can you export your source files for your content? What happens when you do that? In what formats? These are part of the use cases that you’re talking about perhaps here too. So it really is so weird to have to think about something that’s probably years down the road, but it is to your advantage to do that at this point in the game.

SO: Yeah, I mean, what’s the risk if something goes sideways or if your requirements change? This doesn’t have to be sideways. So you are in company A and you buy tool A, which is a perfect fit for what you’re doing. Company A merges with company B. Company B has a different tool and B is bigger than A. So B wins and you exit tool A as company A and you need to move all your content into tool B. Well, that’s a case where you made all the right decisions in terms of buying the software. You just didn’t account for a change in circumstances, as in B swooped in and bought you. So what does it look like to exit out of tool A?

AP: Yeah, it doesn’t necessarily have to be the tool no longer works for us. It could be what you describe. There can be external factors that drive the need to exit, have nothing to do with bad fit or failure on anybody’s part.

SO: So we have these use case scenarios and we’ve thought about exit, though this is entrance. 

AP: Or even before entrance, you haven’t even entered yet.

SO: And so now you’re going to have a demo, right? The software vendor is going to come in and they’re going to show you all your use case scenarios. Well, we hope they’re going to show you your use case scenarios. Sometimes they wander in and they show you a canned demo and they don’t address your use cases. That tells you that they are not paying attention. And that is something you should probably take into account as you do your evaluation.

AP: Yeah, and don’t get sucked in on a similar note. Don’t get sucked in by flashy things because that flash may blind you and very nicely disguise the fact that they can’t quite match one of your use cases. So look at this sparkly thing over here. Don’t fall for that. Don’t do it. Yeah.

SO: Sparkles. So, okay, so we have our use cases and they are going to bring a, they, the software vendor is going to bring some sort of a demo person and they are going to demo your use cases and hopefully they’re going to do it well. So you sort of check those boxes and you say, okay, great, it works. I think the next step after that is not to buy the tool. The next step after that is to ask for a sandbox so that your users can trial it themselves. There is a big, big difference between a sales engineer or a sales support person who has done hundreds, if not thousands of demos going click, click, click, click, click, at how awesome this is. And your brand new user who has never used a system like this, maybe, trying to do it themselves. So user acceptance testing, get them into a not for production sandbox, let them try out some stuff, let them try out all of your use cases that you’ve specified, right? 

AP: It’s try before you buy is what we’re talking about here. Yep.

SO: Mm-hmm. Yeah, I’ve just made a whole bunch of not friends among the software vendors because of course setting up sandboxes is kind of a pain. 

AP: It’s not trivial. 

SO: Yeah, but you’re talking to just one of two candidates, right? So it is not unreasonable. It is completely unreasonable if you just did a, know, a spray this thing far and wide and ask a dozen software vendors for input. That is not okay from my perspective. And when we’re involved in these things, we try very, very hard to get the candidate list down to, again, two or three at most because almost certainly you have requirements in there somewhere that will make one or another of the software tools a better fit for you. So we should be able to get it down to the reasonable prospect list.

AP: And I think too, this goes back to efficiency. Having fewer people or fewer companies in this means you’re gonna have to spend less time per candidate system because you’ve already narrowed it down to organizations that are gonna be a better fit for you. So it’s gonna be more efficient for them because they’re not having to probably do as much show and tell because you’ve narrowed things down very specifically here in my use cases. Also for you as the tool buyer and your procurement team, you’re going to have less to do because you’re not having to talk to four, six candidates, which you should not be doing for an RFP, in my opinion. I know some people in procurement will probably disagree with that though.

SO: Well, we’re just going to make everybody mad today. And while I’m on the topic of not making friends and not influencing people, I wanted to mention something that probably many of you as listeners are familiar with, which is something called the Enterprise Architecture Board. If you work in a company of a certain size, you probably have an EAB. And the EAB is kind of like the homeowners association of your company, right? They are responsible for standards and making sure that you occasionally mow the lawn and whatever else, whether there are other ridiculous rules the homeowners association set. But EABs, Enterprise Architecture Boards in a company context, are responsible for software purchases, software architecture, and looking at what kinds of systems are we bringing into this organization and usually how can we minimize that? How can we maintain a reasonable level of consistency instead of bringing in specialty solutions all over the place? Now, a CCMS, a component content management system is pretty much the definition of a specialty system. 

AP: It’s niche. Yeah.

SO: Yep, and EABs in general willl take one look at it and say something very much like, “CCMS, no, we have a CMS. We have a content management system. We have SharePoint, just use that. We have Sitecore, just use that. We have fill in the blank, just use that.” And your job, if you have the misfortune to have to address an EAB, is that you need to explain why it is that the approved existing solutions within the company architecture do not meet the requirements of the thing that you are trying to do and because that one’s not hard. The and part is the hard part and it is worth the and they’re going to talk about TCO total cost of ownership. It is worth the effort and the risk and the complexity of bringing in another solution beyond the baseline CMS that they’ve already approved to solve the issues that you’ve identified for your content. This is difficult. I’ve spent a lot of quality time with the AABs and they’re literally their job is to say no. I mean, that is just flat out their job. Their job is to streamline and minimize and have as few solutions as possible. So if you have to deal with this kind of situation, you’re going to have some real challenges internally getting this thing sold.

AP: Yeah, and while we’re making friends and influencing people with our various comments on this process today, one final thing I want to say before we wrap up is, that common courtesy goes a really long way in this process. When you have wrapped things up, you have made your selection. Be sure you also communicate that to the vendors you did not choose.

SO: Yeah.

AP: Too many times in RFP processes, there’s not the level of communication with the people who did not win. And it’s just common courtesy, let them know, no, we chose someone else. And if you’re feeling super polite, you might even tell them why this use case you didn’t quite hit. This is why we went with this organization if you choose to. So be nice and be courteous because I realize this is more of a professional business situation, but it still doesn’t hurt to tell someone exactly why you did what you did.

SO: Yeah, and I know those of you in more on the government side of things, nonprofit, typically do have a requirement to notify on RFPs and even give reasons and all the rest of it. But on the corporate side, there’s typically not any sort of requirement to let people know, as Alan said. you know, people put a lot of work into these RFPs and a lot of pain. 

AP: Yeah.

SO: And one last, last thing beyond you should notify people. I want to talk about RFP timing. So we’re rolling into the end of 2024 here. I fully expect that there will be RFPs that will come out on roughly December 15th, which will be due on something like January 1st. So in other words, “Hi vendors, please feel free to spend your holiday time filling out our RFP so that we can, you know, go into the new year with shiny RFP submissions.”

AP: RUDE!

SO: That is not polite. Don’t do that. It is extremely rude. And it signals a level of disrespect that from the vendor side of the process makes them perhaps less inclined to bend on some other things. So reasonable amount of time for the scope of work that you’re asking for. And holidays don’t count.

AP: Yeah, exactly. to go back, I think we can kind of wrap this up and go back to what we were talking about. All of that legwork that you do upfront for this RFP process, your vendors, believe it or not, would generally appreciate it because it shows you’ve done the homework, you have thought about this, and you’re just not wildly flinging out asks with no money, no stakes behind those asks. And they will probably be much more willing to work with you and go that extra mile when you have done that homework. Is there anybody else that we need to tick off before we wrap up?

SO: I think we covered our list. So I’ll be interested to see what people think of this one. So let us know, maybe politely, but let us know.

AP: And I’ll wrap up before there’s violence that occurs. So thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Creating content ops RFPs: Strategies for success appeared first on Scriptorium.

The truth that we’re finding our way towards appears to be that you can use AI as a tool and it is very, very good at patterns and synthesis and condensing content. And it is very, very bad at creating useful, accurate, net new content. That appears to be the bottom line as we exit 2024.

— Sarah O’Keefe

Related links:

• Pulse check on AI: May, 2024 (podcast)
• AI in the content lifecycle (white paper)
• The future of AI: structured content is key (webinar)
• Savor the season with Scriptorium: Our favorite holiday recipes

LinkedIn:

• Sarah O’Keefe
• Christine Cuellar

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Christine Cuellar: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, it’s time for another pulse check on AI. So our last check-in was in May, which in AI terms is ancient history, so today, Sarah O’Keefe and I are gonna be talking about what’s changed and how it can affect your content operations. Sarah, welcome to the show.

Sarah O’Keefe: Hey Christine, thanks.

CC: Yeah. So 2024, as we’re currently recording this 2024 is winding down. People are preparing for 2025. Throughout this year, we went to a lot of different conferences and events. Of course, everybody’s talking about AI. So Sarah, based on the events that you like just recently got back from, you finally get to be in your own house. What are your thoughts about what’s going on with AI in the industry right now?

SO: There’s, still a huge topic of conversation. Lots of people are talking about AI, a huge percentage of presentations, you know, had AI in the title or referenced it or talked about it. With that said, it seems like we’re seeing a little more sort of real world, hey, here’s some things we tried, here’s what’s working, here’s what’s not working. 

CC: Mm-hmm.

SO: And I’ll also say that we’re starting to see a really big split between the AI in regulatory environments, which would include the entire EU plus certain kinds of industries and the sort of wild, wild west of we can do anything.

CC: Yeah. So do you feel like it sounds like, know, when AI first came onto the scene, there was mostly, you know, let’s just all adopt this right now. Let’s go for it full steam ahead, especially marketers as a marketer. can I can say that because we’re definitely gung-ho about stuff like that. It sounds like, the perspective has shifted to being more balanced overall. Is that what you would say?

SO: Yeah, I mean, that’s the typical technology adoption curve, right? You know, have your your peak of inflated expectations, and then you have the I think it’s the valley. It’s not the valley of despair, but it’s something like that. But you know, you sort of go from this can do anything. This thing is so cool. Go, go, go, go, go to a more realistic. Okay, what can it actually do? And what you know, does the and this is true for AI or anything else? What can it do? What can’t it do? What does it do well?

CC: Mm.

SO: Where do we need to put some guardrails around it? What are some surprises in terms of things that are and are not working?

CC: Yeah. And at some of the conferences we were at this year, our team had some things to say about AI as well. So we will link some of the recap blog posts we have in the show notes. Sarah, what are some of the things AI can’t do right now? are the still, what are, Sarah, what are some of the big concerns about AI that are still unanswered, unresolved?

SO: So in the big picture, as we’re starting to see people roll out AI-based things in the real world, whether it’s tool sets or content ops or anything else, we’re starting to see some really interesting developments and some really interesting assessments. Number one is that when you look at those little AI snippets that you get now when you do a search and it returns a bunch of search, well, actually it returns a page of ads.

CC: Yes.

SO: And then some real results under the ads. And then above that, it returns an AI overview snippet. So those are surprisingly bad. You do a search on something that you know a little bit of something about and see what you get. And you will see content in there that is just flat wrong. I’m not saying it’s not the best summary. I’m saying it is factually incorrect, right?

CC: Yeah, I hate them right now.

SO: So those are surprisingly bad. And talking about search for a minute, which ties into your question about marketing, there’s some real problems now with SEO, with search engine optimization, because if I’m optimizing my content to be included in an AI overview that is A, wrong, and B, doesn’t actually give me credit, Pre-AI, those snippets that showed up would say, I sourced it from over here.

CC: Mm-hmm.

SO: And in many cases now, the AI overview is just like the sort of summary paragraph with no particular, there’s no citation. It doesn’t say where it came from. So what’s in it for me as a content creator? Why am I creating content that’s going to get taken over by the AI overview and then not lead to people going to my webpage, right? How’s that helped me? 

CC: Yeah. Yeah.

SO: So there’s some real issues there, there’s a move in the direction of thinking about levels of information. So thinking about very superficial information. How much does a cup of flour weigh? That type of thing. That’s just a fact and you can get it pretty much anywhere, we hope. And then there’s deeper information. Why is it better to weigh flour than to measure it? By volume, if you’re a baker.

CC: Yeah.

SO: And what does it look like to use weights? And are there differences among different kinds of flours? And what are some of the things I should consider when I’m going in that direction? So one of those, know, flours, a cup of flour weighs 120, sorry, a cup of all-purpose flour weighs 120 grams is a useful fact. And I don’t know if I really care if people peruse that further or come to my website for more about flour. The deeper information, the more detailed discussion of, you know, whole wheat versus all-purpose versus European flours versus American flours and all these other kinds of things, that requires more in-depth information and that is not so subject to being condensed into an AI summary. So that distinction between, you know, quick and dirty information versus deeper information, information that goes into a topic,

CC: Mm-hmm.

SO: We have a huge problem with disinformation and misinformation with information that is just flat out not either not correct or because of the way AI tools work, is trivially easy to generate content at scale. Tons and tons and tons and tons and tons of content. And because it’s trivially easy,

CC: Mm-hmm.

SO: That means it’s also trivially easy for me to generate, for example, a couple thousand fake reviews for my new product or a couple thousand websites for my fake products. It we can fractionalize down the generation of content. 

CC: Yeah.

SO: And the you know, the interesting part of this is that it implies that you could potentially, you know, we talk about doing A/B testing and marketing. You could do A/B/C/D/E/F/G testing pretty easily because you can generate lots and lots of variants and kind of throw a bunch of stuff against the wall and see what works. But the bad side of this is that you can generate fake news, fake information, fake content that is going to be highly, highly problematic from a content consumer trust point of view. And so that I think is the third piece that we’re looking at now that is going to be critical going forward. And that is information trust, content reputation or the reputation of content creators and credibility. 

CC: Mm-hmm.

SO: So for those of you listening to this podcast, how do you know it’s really us? Do you know these are live humans actually recording this podcast versus you know there’s now the ability to generate synthetic audio and you can create a perfectly plausible podcast which is really hard to say unless probably your AI and then it can probably do it perfectly but our perfectly plausible podcasts are you know how do you know that what that what you’re receiving in terms of content, digital content in particular, is actually trustworthy. And so I think ultimately there’s going to be some, need to be some tooling around verification, around authenticity, around, you know, this was not edited. You know, in the same way that you want to be able to verify that a photo, for example, is an accurate record of what happened when that photo was taken.

CC: Yeah.

SO: And if I went in and photoshopped it and cleaned it up, then that’s something that should be acknowledged. By the way, for the record, we do record these things and we do edit them. We try to stay on the right side of just editing out dumb mistakes and not editing it in a misleading way. 

CC: Yeah, ums and ahs and yeah.

SO: So it’s not like we record the whole thing from soup to nuts and never, you know, never break in and never edit things out because believe me, I’ve said some stuff that needed to be taken away. If you ever get the raw files, they are full of, I didn’t mean to say that. you might want to take that out. 

CC: Me too, so many times. Let me start over, that’s me a lot all the time.

SO: Yeah, sorry. Starting over. OK, but the point is that when we put out a podcast, we are saying this is our opinion, this is our content, and we’re gonna stand behind it. Whereas if it’s synthetic or AI generated or AI generated by these non-humans, you can do these weird, let’s make a podcast out of a blog post, well, okay, but what’s the value of that and why would I trust that content?

CC: Yeah.

SO: So that I think is going to be the big question for the next couple of years is what does it look like to be a content creator in an AI universe and to have the ability or sorry to as the content consumer to have the ability to validate what you’re listening to or reading or seeing.

CC: Yeah. And a point that you had brought up in, I believe it was the white paper that you authored back in 2023. One of the points in there was that, people are going to, because of this trust and credibility issue, people are going to have to start relying on companies and brands that they’re already familiar with for the information that they’re looking for rather than a search from scratch because, you know, search is so messed up right now. And that is something I’ve seen personally, like myself, I do it a lot more. I’ve seen that with friends and other contacts and stuff like that. That’s really what people are doing is they’re going to, you know, the source even for recipes. Recently, as I was looking for a recipe and instead of just Googling it like I used to because I’m so sick of the summarized AI search, I went to all recipes, you know, a place that I knew that I liked the recipes or I think Sally’s baking addictions or something like that. There’s a lot of different places like that that now I’ll just go there instead of, you know, a search from scratch. That’s… I don’t know how we’re gonna fix that problem, yeah, trust and credibility, that’s gonna be a huge one.

SO: It’s a really good example though because if you search for a particular recipe, even say two years ago, you would get a certain set of results and then you would say, I’ve heard of that website and I’ll go there. Now you search on a recipe, I’m getting 20, 30, or 40 websites that I’ve never heard of that all seem to have posted exactly the same recipe.

CC: Mm-hmm.

SO: I, you know, do I trust them? Do I trust them not to be AI-generated? Do I trust them to remember to not, you know, recommend that I put gravel in my recipes? You know, maybe not. And so I’m doing the same thing you are, which is, you know, reverting to trusted sources, trusted brands that I know that have a reputation for producing good recipes. Now, the flip side of this is that content is disappearing. 

CC: Hmm.

SO: So, I have an infamous triple chocolate cookie recipe, is really if you’re looking for a chocolate bar in the form factor of a cookie, that is what it is. It’s just stupid amounts of chocolate. 

CC: Mm-hmm. yes, that sounds amazing.

SO: It’s they’re delicious. And I think we’re putting them in our our holiday post, which may or may not have gone live already. So keep an eye out for that. But here’s the thing. I have the recipe because I got it out of Food & Wine about 20 years ago and I have a paper cut out of it that I wrote, hand wrote Food & Wine 12/01 on. So it was December of 2001 and so I went to Food & Wine. I went searching for this recipe knowing that it was originally published by them. I can’t find it. It is not there.

CC: Hmm. wow.

SO: It is not in their database, or at least it didn’t come up in their database when I searched on the exact name of the recipe. I then searched that exact recipe name, you know, just generally on the Internet, and I found three or four or five different places that had it, but none of them credited where I got it from 20 years ago, which I’m pretty sure is the original, right? Because these are all much more recent sites. So there are digital copies out there floating around, but they are not the original recipe and they didn’t credit the original publisher. Now, I don’t know exactly where Food & Wine got it because all I did was cut out the recipe. didn’t cut out the article. It was probably the context around it. But what I’m now reduced to is that I have a paper copy stashed in my paper recipe book, right? And I took a photo of the paper copy and put it on my phone. So I have a sort of digital version, but it is literally a photograph of a printout, which is, it is 2024 and we are doing photographs of printouts, but I can’t find it or I can’t find the original online.

CC: Yes. Yeah. That’s interesting. Why do you think that content has disappeared? Do you think it’s because of the breakdown of the content model where the AI engine is just eating what it’s already regurgitated a bunch of times? Do you think it’s that? Does an org pulled it for some reason or what do you think is the cause?

SO: Well, I mean, my best guess is that their recipe database only goes back so far and they just said anything more than X years old doesn’t need to be in here. They had some similar recipes. So maybe, well, this one’s been updated. It’s a little more modern, whatever. But it was just, it was really troubling that I, even knowing what the source was, I couldn’t find it.

CC: Yeah, that is troubling. So how can companies prepare knowing that this is our context, this is our landscape? What should we do to prepare for 2025 and beyond? Because it’s not just like next year.

SO: Beyond yeah, okay. So first of all you have to understand your regulatory environment Because that is very different by country or by region the issues that the people in the EU are looking at or American companies that sell in the EU, right. 

CC: Mm-hmm. Yeah.

SO: There’s an EU AI act, and there’s a whole bunch of guidance that goes along with that. So there’s some concerns there. Whereas here in the US specifically, we don’t have a lot of regulation around AI, if any. Mostly we lean on, well, if you put out something that’s incorrect, there’s potentially product liability. If you put out instructions that are wrong and people follow them and they get hurt or worse, then the product owner is probably liable for putting out wrong instructions. That’s kind of where our stuff lands. But as a content consumer, I think you have to do what you’re describing, Christine, and become very, very skeptical about your sources methods, right? Where’d you get this stuff? And do you trust the source that it came from? 

CC: Yes.

SO: If you are a content creator, then looking at questions around AI, the questions become, how can I employ AI inside my content workflows in a responsible way that achieves the goals that I have and doesn’t get me in big trouble in whatever way? And there’s also the question of, if I’m a content creator and I know that my consumers, my customers, are going to be using AI to consume my content, then how do I optimize that for that? How do I prepare for that? So it looks very different if you’re a person writing, creating new content, versus you’re the person deploying a chat bot on your corporate website that’s going to go read through your content corpus versus the person actually using the chat bot versus you name it. So.

CC: Yeah.

SO: And then, you know, we’re talking about AI generally, but of course we have AI tooling and we also have generative AI and we have all sorts of different things going on. So it’s a very, very broad topic, but overall, you know, what’s the problem I’m trying to solve? Can I apply this tool in a useful way? And what are some of the guardrails that I need to employ to keep myself out of trouble?

CC: Yeah, in one of our webinars from this year, from 2024, depending on when you’re listening to this podcast, Carrie Hane mentioned something along the lines of like, you know, when you’re dealing with AI, it’s such a huge topic. You need to break it down by what’s the purpose of what you’re trying to do and then tackle the problem that way. Okay. So to wrap up, Sarah, what are your final thoughts, wishes and or recommendations for the world as we enter this new era? Or I guess we’re in it, but as we try to recover.

SO: So the very short, we’ll try and keep it short. I think when all this AI stuff hit us a year or two ago, business leaders generally were hoping that they could just use AI as a general-purpose solution. Fire all the people, use AI for all the things, cool. 

CC: Mm-hmm.

SO: The truth that we’re grasping towards or finding our way towards appears to be that you can use AI as a tool and it is very, very good at patterns and synthesis and condensing content. And it is very, very bad at creating useful, accurate, net new content. That appears to be the bottom line as we exit 2024.

CC: Yeah. Well, thank you very much for unpacking this with us because I know that, you know, things are changing so fast. It’s helpful to have people like you that have been in the industry, the content industry specifically for a really long time that can help, you know, figure out a way through all this and give some practical ideas.

SO: Well, you know, in six months, we’ll just feed this podcast into the AI and tell it to fix it so that it remains accurate. And off we go.

CC: Yeah, there we go. And then we’re done. 

SO: And we’re done.

CC: Yeah. Thanks so much for being here today and for talking about this.

SO: Yeah, anytime.

CC: And thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Pulse check on AI: December, 2024 (podcast) appeared first on Scriptorium.

Sarah: You’ve got to get your terminology and your taxonomy in alignment. Most of the industry I am confident in saying have gone with option D, which is give up. “We have silos. Our silos are great. We’re going to be in our silos, and I don’t like those people over in learning content anyway. I don’t like those people in techcomm anyway. They’re weird. They’re focused on the wrong things,” says everybody, and so they’re just not doing it. I think that does a great disservice to the end users, but that’s the reality of where most people are right now.

Bill: Right, because the end user is left holding the bag trying to find information using terminology from one set of content and not finding it in another and just having a completely different experience.

Related links:

• The business case for content operations (white paper)
• Replatforming an early DITA implementation (case study)
• Hear Sarah speak about The reality of enterprise customer content at tcworld 2024!
• Hear Bill speak about the The challenges of replatforming, also at tcworld 2024.

LinkedIn:

• Sarah O’Keefe
• Bill Swallow

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Bill Swallow: Welcome to The Content Strategy Experts podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about enterprise content operations. Does it actually exist? And if so, what does it look like? And if not, how can we get there? Hi, everyone. I’m Bill Swallow.

Sarah O’Keefe: And I’m Sarah O’Keefe.

BS: And Sarah, they let us do another podcast together.

SO: Mistakes were made.

BS: So today we’re talking a little bit about enterprise content operations. If it exists, what it looks like. If it doesn’t, why doesn’t it exist? What can people do to get there?

SO: So enterprise content ops, I guess first we have to define our terms a little bit. Content operations, content ops is the system that you use to manage your content. And manage not the software, but how do you develop it, how do you author it, how do you control it, how do you deliver it, how do you retire it, all that stuff. So content ops is the overarching system that manages your content lifecycle. And when we look at content ops from that perspective, and of course we’re generally focused on technical content, but when we talk enterprise content ops, it’s customer-facing content, which includes techcomm, but also learning content, support content, product data potentially, and some other things like that. And ultimately, when I look at this, again bringing the lens back or going back to the 10,000-foot view, we have some enterprise solutions but only on the delivery side. The authoring side of this is basically a wasteland. So I have the capability of creating technical content, learning content, support content, and putting them all into what appears to be some sort of a unified delivery system. But what I don’t really have is the ability to manage them on the back end in a unified way, and that’s what I want to talk about today.

BS: So those who are delivering in that fashion, so being able to provide customer-facing information in a unified way, as far as their system for content ops goes, it’s more, I would say, human-based. So it’s a lot of workflow. It’s a lot of actual management of content and management of content processes outside of a unified system.

SO: So almost certainly they don’t have a unified system for all the content, and we’ll talk about why that is I think in a minute. It’s not necessarily human-based, it’s more that it’s fragmented. So the techcomm group has their system, and the learning group has their system, and the support team has their system, et cetera. And then what we’re doing is we’re saying, okay, well once you’ve authored all this stuff in your Snowflake system, then we’ll bring it over to the delivery side where we have some sort of a portal, website portal, content delivery CDP that puts it all together and makes it appear to the end user that those things are all in some sort of a, it puts it in a unified presentation. But they’re not coming from the same place, and that causes some problems on the backend.

BS: Right, and ultimately the user of that content doesn’t really care if it’s a unified presentation. They just want their stuff. They don’t want to have a disjointed experience, and they want to be able to find what they’re looking for regardless of what type of content it is.

SO: Right, and the cliche is “don’t ship your org chart,” which is 100% what we’re doing. And so let’s talk a little bit about what does that mean, what are the pre-reqs? So in order to have something that appears to me as the content consumer to be unified, well for starters, you mentioned search. I have to have search that performs across all the different content types and returns the relevant information. And what that usually means is that I have to have unified terminology. I’m using the same words for the same things in all the different systems. And I need unified taxonomy, classification system metadata so that when I do a search, everything, and maybe I’m categorizing or I’m classifying things down and filtering, that when I do that filtering, that the filtering works the same way across all the content that I’ve put into the magic portal. So taxonomy and terminology are the things that’ll make your search, relatively speaking, perform better. So we have this on the delivery side and that’s okay-ish, or it can be, but then let’s look at what we’re doing on the authoring side of things because that’s where these problems start.

BS: So what do they start looking like?

SO: Well, maybe let’s focus in on techcomm and learning content specifically. We’ll just take those two because if I try and talk about all of them, we’re going to be here for days and nobody wants that. All right, so I have technical content, user guides, online help, quick snippets, how-tos. And I have learning, training content, e-learning, which is enabling content, I’m going to try and teach you how to do the thing in the system so that you can get your job done. Now, let’s go all the way back to the world where we have an instructional designer or a learning content developer and a technical content developer. So for starters, almost always those are two different people, just right off the bat. And instructional designers tend to be more concerned with the learning experience, how am I going to deliver learning and performance support to the learner? And the technical writers, technical content people tend to be more interested in how do I cover the universe of what’s in this tool set, or this product, and cover all the possible reasonable tasks that you might need to perform, the reference information you need, the concepts that you need? It’s a lot of the same information. It’s there’s a slightly different lens on it. And in the big picture, we should be able to take a procedure out of the technical content, step one, step two, step three, step four, and pretty much use that in a learning context. In a learning context, it’s going to be, hey, when you arrive for your job at the bank every morning you need to do things with cash that I don’t understand. And here’s a procedure, and this is what you’re going to do, steps 1, 2, 3, 4, 5, and you need to do them this way and you need to write them down, and it tends to be a little more policy and governance focused, but broadly it’s the same procedure. So there should be the opportunity to reuse that content. And big picture, high-level estimate is probably something like 50% content overlap. So 50% of the learning content can or should be sourced from the technical content. The technical content is probably a superset in the sense that the technical content covers, or should cover, all the things you can do, and training covers the most common things or the most important things that you need to do. It probably doesn’t cover a hundred percent of your use cases. Okay, so now let’s talk about tools.

BS: Right because I was going to say these two people, the technical writer and the training developer, they are using, at least historically, two very different sets of tools to get their job done.

SO: Right. So unified content solutions, without getting into too many of the specifics, which will get me in big trouble, basically the vendors are working on it, but they’re not there yet. There’s a lot of point solutions. There’s a lot of, oh yes, we have a solution for techcomm and we have a solution for learning and we have a delivery solution, but there’s not a unified back end where you can do all this work.

And some of the vendors have some of these tools in their stable, some of them don’t. But from my point of view, it doesn’t really make a whole lot of difference whether you buy two-point solutions from separate vendors or from the same vendor because right now they’re disconnected.

BS: They’re two-point solutions.

SO: Yeah, they’re all point solutions. So it’s not good. And then that brings us to how can we unify this today? What can we do and what kind of solutions are our customers building or are we building with our customers? So a couple of things here. Option A is you take your structured content solution and you say, “Okay, learning content people, we’re going to put you in structured content. We’re going to move you into the component content management system. We’re going to topicify all your content, and we’re basically going to align you with the techcomm toolset and make that work.” We have a few customers doing that. It works well for learning content developers that are willing to prioritize the document structure and process over the flexibility in the downstream learning experience.

BS: Right.

SO: That’s a small set of people. Most learning content developers are not willing to prioritize efficiency and structure over delivery, which I think is actually the root cause.

BS: Right. Now, those who are doing this, they are seeing some benefit in being able to produce a wide variety of their training deliverables from that unified source. But again, it comes back to how willing people are to give up the flexibility that they have in developing course content.

SO: We can talk about big picture and we can talk about all the things, but this decision, this approach 100% of the time comes down to how badly do you want to be able to flail around in PowerPoint. And if having the ability to put random things in random places on random slides is critical, then this solution will not work.

BS: So on the flip side, you would then look to maybe somehow connect your technical communication system to your learning repository.

SO: Right. So you take your techcomm content and you treat it as a data source essentially for your learning content, and you just flow it into the learning authoring environment. It turns out that’s hard.

BS: It’s very hard.

SO: Super difficult. It’s difficult to get your structured content out into a format that the learning content system can accept in a reasonable manner.

BS: And if your content is highly structured, you’re likely losing a lot of semantic data along the way to get it there.

SO: Yeah, you lose a lot, but it’s just bad. And ultimately, this almost always lands, I mean we talk about flow it in there, but ultimately this almost always means that you’re going to be copying and pasting and reformatting and re-reformatting, and it’s just terrible.

BS: So more often than not, we’re not seeing this level of unification then.

SO: Yeah, I mean, are you connecting your techcomm and you’re learning in a structured environment? A few people, yes. And for the right use case, it’s great. Or flow the techcomm content down into the learning environment, but ultimately not worth it, we’ll just copy and paste. So in terms of unification, basically none of the above, right?

BS: Mm-hmm. So how would people get there?

SO: So there’s a couple of options. The probably most common one is some sort of a DIY solution. We’re going to find a way to glue these systems together. We’re going to find a workflow that involves converting the techcomm content, which usually is created first and move it into the learning content. Again, for the right group, for the right environment, unifying everything in a structured authoring environment makes a lot of sense. I think ultimately that’s where it’s going to land, but the structured content systems need to do some work to make themselves into what amounts to a reasonable viable authoring solution for the learning content people. Basically the learning content people are not willing to put up with the shenanigans that ensue in order to use a structured content system. And I’m not even sure they’re wrong, right?

BS: Yeah.

SO: They’re just saying, “No, this is terrible and we’re not doing it.” Okay, well, that’s fair. So either you tinker and put it all together in some way. Option B is wait for the vendors, wait for the vendors to fix this problem, fix this requirement, and deliver some systems that have a solution here. And it’ll be a year or two or five or 20, and eventually they’ll get to it. You can go with a delivery-only solution, so we’re only going to solve this on the delivery side. If you do that, you really, really, really, really need an enterprise-level taxonomy and terminology project group.

BS: Absolutely.

SO: You’ve got to get that aligned. You cannot go around having half your text say entryway, and half your text say hallway, half your text says study, and half your text says den. And I’m halfway down a clue reference, was it the wrench or the outlet? No, no, no, okay. You have to get your terminology in alignment. You must because otherwise people search on oven and it doesn’t return range because those are in fact… Well, okay, they’re not exactly the same thing, but close enough, so those types of things. So you’ve got to get your terminology and your taxonomy in alignment. Most of the industry, like most of the people out there that are doing techcomm and learning content, I am confident in saying have gone with option D, which is give up. Just don’t do it. Just don’t bother. We have silos. Our silos are great. We’re going to be in our silos, and I don’t like those people over in learning content anyway. I don’t like those people in techcomm anyway. They’re weird. They’re focused on the wrong things, says everybody, and so they’re just not doing it. I think that does a great disservice to the end users, but that’s the reality of where most people are right now.

BS: Right, because the end user is left holding the bag there trying to be able to find information using terminology from one set of content and not finding it in another and just having a completely different experience.

SO: They make it a you problem.

BS: Yeah. So if you’re seeing opportunities to unify content operations in your organization, what are some key ways of communicating that up so that you can begin to get some funding, some support, some executive level buy-in to do these things?

SO: The technology problem is hard. Putting everybody in an actual unified authoring environment is a really hard problem. So I think what you want to do is go for the easier solutions where you can get some wins. And the easier solutions where you can get some wins are consistent terminology across the enterprise. So we’re going to have some conversations about terminology and what we need to do in terms of terminology, and everybody’s going to agree on the words we’re going to use. Taxonomy, what does our classification system look like? What are the names for our products and how do we label things so that when we deliver all these different content chunks, they’re coming from all these different systems, we can bring them into alignment? I mean, you can do the work on the back end to align taxonomy or you can do it on the delivery side to say these things are synonyms. So there are some ways of addressing this even when you get down into the delivery end of things. But I think what you want to do is start thinking about the things… Oh, and translation management, which ties into both terminology and taxonomy. I think you want to start maybe with those things and then slowly work your way upstream, like a salmon, avoiding the bears on the… Okay, you’re going to try and work your way upstream towards the authoring. Because ultimately if you look at this from an efficiency point of view, it would be much, much more efficient to have unified authoring and put it all together. It’s just that right now today, that’s a heavy lift and it only makes sense in certain environments. So what can we do to prepare for that so that when we do get to that point and those tools do start to unify a little bit better, we’ve done the legwork that’ll make it easier to make that transition as we go?

BS: Right. So it’s spending the effort to unify as much as you can the content and the language and the organization, as well as trying to keep pace with where I guess all of these different industry tools are going and making sure that you are making improvements in the right direction. So if you’re thinking about structured content, that you are keeping an open mind as to where and how I guess these other groups can start leveraging what you’re using and vice versa. And I guess talking with the other groups in your organization. So if you’re in techcomm, then talk to the training group, see what they’re doing, see what their plan is, what’s their five-year roadmap? Are they looking at certain technologies? How might that play into your development, and vice versa, being able to share that information.

SO: And I know, Bill, you’re doing a session on re-platforming at tcworld this November 2024. And when you’re thinking about re-platforming, what are some of the factors that you should be looking at there that tie into this?

BS: Well, it directly plays into that next step of we have a platform on the techcomm side, we bought it 12 years ago, it served our needs. But the training group, let’s say, has been talking and they have this other system that they’re not too happy with, and they want to see if they can start sharing our content.

Well, then you have an open conversation to say, “Okay, how can we get to a shared solution, what do these requirements look like,” and go ahead and pick a system that kind of meets both requirements. But then you have that heavy lift of just saying, “Okay, so now we have these two different old systems and we need to dump our content, and I use that very generally, into the new system, so that everyone from those two groups can now author in the same place.

SO: And I’m thinking as you’re evaluating these systems, all other things being equal, which they are not, but all other things being equal, you would look for the one that’s more open, that is more flexible knowing that things are going to change because they always do. What’s available to us that’ll give us maximum flexibility in a year or two or five when these new requirements come in that we have not anticipated at this point?

BS: Right, because you’re exiting your old systems because they are potentially inflexible. We cannot accommodate anything new. We can sustain what we’re doing indefinitely, but we can’t accommodate this new thing that we need to do.

SO: Yeah, it’s interesting because looking at the the techcomm landscape, we have a lot of customers and a lot of just generalized ecosystem that has moved into structured content, and starting as early as the late nineties or maybe even the early nineties in Germany, people were moving into structured content at scale. And now we’re looking at it and saying, “Okay, well there’s all this other content out there and we need to look at that and we need to look at whether we can bring that into the structured content offerings.” But not unreasonably, those other groups are looking at it and pushing back and saying, “This isn’t optimized for the kind of work that I do. It’s optimized for the kind of work that you people do. So how can we improve this and bring it into alignment with what the new and additional stakeholders need?” And it’s a hard problem, I really feel for the software vendors. It’s easy for us sitting here on the services side to say, “Hey, do better,” because we’re not doing the work.

BS: Very, very true. And at that point, you have a winner and a loser, and I hate to say it that way, but you have a winner and a loser on the system side at that point. Where you’re pulling one other group in because you have an established structural approach and they could benefit from it, but basically they have to absorb the brunt of the change that’s going to happen, and it’s not necessarily fair.

SO: Well, yeah. I mean, life isn’t fair. But also I’ll say that that pain that you’re talking about, the people that are now in structured content, they had that pain. It was just 10 years ago-

BS: Very true.

SO: …and they’ve forgotten. For those of you that were around and in this industry 10 years ago, or 20 years ago, or 25, I mean, remember what it was like trying to get people to move from you will pry unstructured FrameMaker from my cold, dead hands. You’ll pry Microsoft Word from my cold, dead hands. You will pry PageMaker, Interleaf, Ventura Publisher from my cold, dead hands.

BS: WordStar.

SO: Okay. So tools come and go, and the tool that is the state-of-the-art, BookMaster, for today is not necessarily the tool that’s going to be state-of-the-art for tomorrow or yesterday. I mean, basically this stuff evolves and we have to evolve with it, and we have to understand what are the best and most reasonable solutions that we can offer to a customer or to a content operations group in order to deliver on the things that they need to deliver on.

BS: Very true. So there are no unicorns.

SO: No unicorns, or maybe more accurately you can construct your own unicorn and it might be awesome, but it’s going to be a lot of work.

BS: So I think we could probably talk about this for hours because there are so many different facets that we can touch upon, but I think we’ll call it done for now, and maybe we’ll see you soon in a new episode?

SO: Yeah, if this speaks to you, call us because we’ve barely scratched the surface.

BS: All right. Thanks, Sarah.

SO: Thanks.

BS: And thank you for listening to The Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

The post Do enterprise content operations exist? appeared first on Scriptorium.

Alan Pringle: When you’re choosing tools, if you end up something that is super proprietary, has its own file formats, and so on, that means it’s probably gonna be harder to extract your content from that system. A good example of this is those of you with Samsung Android phones. You have got this proprietary layer where it may even insert things into your source code that is very particular to that product line. So look at how proprietary your tool or toolchain is and how hard it’s going to be to export. That should be an early question you ask during even the RFP process. How do people get out of your system? I realize that sounds absolutely bat-you-know-what to be telling people to be thinking about something like that when you’re just getting rolling–

Christine Cuellar: Appropriate for a cave analogy, right?

Alan Pringle: Yes, true. But you should be, you absolutely should be.

Related links:

• Nightmare on ContentOps Street (podcast)
• Enterprise content operations in action at NetApp (podcast)
• Content creature feature

LinkedIn:

• Alan Pringle
• Christine Cuellar

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Christine Cuellar: Welcome to the content strategy experts podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize and distribute content in an efficient way. this episode, we’re talking about setting your ContentOps project up for success by starting with the end in mind, or in other words, planning your exit strategy at the beginning of your project. So I’m Christine Cuellar, with me today is Alan Pringle. Hey, Alan. 

Alan Pringle: Hey there.

CC: And I know it can probably sound a bit defeatist to start a project by thinking about the end of the project and getting out of a new process that maybe you’re building from the beginning. So let’s talk a little bit more about that. Why are we talking about exit strategy today?

AP: Because everything comes to an end. Every technology, every tool, and we as human beings, we all come to an end. And at some point, you are going to have tools, you’re gonna have technology and process that no longer supports your needs. So if you think about that ahead of time, and you’re ready for that inevitable thing, which will happen, you’re gonna be much better off.

CC: Yeah. So this conversation started around the news of the DocBook Technical Committee closing, and that’s kind of a big deal for a lot of people, and it kind of sparked this internal conversation about like, you know, what if that happened to you? How can people avoid getting caught by surprise? And of course, as Alan just mentioned, the answer to that is really to begin with the end in mind, to have an exit strategy because everything does end at some point. So this got me thinking about, you know, I don’t know, Alan, you’ve seen the horror movie The Descent, right? You’ve seen that movie? Yes, because it’s amazing and it’s a horror movie and it’s awesome. So it me kind of think of that because, you know, this group, and I’m not going to spoil it, no spoilers for people who haven’t seen it yet, but, if you haven’t, go watch it. The first one’s my favorite. I haven’t seen the second one, so I’m biased. Anyways, that’s not the point. This group plans to go along one path, you know, down these caves which are definitely in North Carolina, right Alan? That’s definitely where they take place.

AP: Well, they say it is in North Carolina, but it is quite clearly not filmed in North Carolina. As someone who is familiar with Western North Carolina, I had to laugh at this movie trying to pass off somewhere in the UK as like the Appalachian Mountains, but that’s just a quibble. So go ahead with your story.

CC: Anyways, yeah, they got a mountain in there, right? And then there’s a path into the mountain. Of course, they’re going to explore this deep, dark cave. So they’re descending as the name implies. And so they’re planning to go along one path. think someone maybe tricked someone else along the way. I can’t remember. But they’re planning on going down one path. And there’s a lot of things that begin to happen that they didn’t plan on. And one scene in particular, there’s a cave that collapses and of course that means they have to pivot, right.

AP: Yeah.

CC: So when you’re thinking about building an exit strategy and trying to plan for things that you can’t anticipate, how do you anticipate things you can’t anticipate?

AP: Well, first of all, let’s be clear. All the things that happened in that movie happened in a period of like two hours or an hour and a half. And part of the issue with any kind of process and operations is things can slowly start to go badly and you just kind of keep on trucking and really don’t pay attention to it. But…

CC: Yes.

AP: It’s not just about fine tuning your operations. That’s a whole other conversation. You your process is going to require updating every once in a while. There going to be new requirements and you need to address them in your content ops by changing your process, updating your tools, maybe adding something new. What we’re talking about here is when those tools and that process, they’re coming to an end, for example, because a particular piece of software is being defecated. It is end of life. What are you going to do?

CC: Mm-hmm.

AP:  What if there is a merger? You have a merger and there are two systems doing the same thing. One of those systems is going to lose and go away. Why are you going to maintain two of the same systems? So you’re going to have to figure out how to pivot to get to that.

CC: Mm-hmm.

AP: So there are all of these things that can happen that mean you have got to exit whatever you were doing and move into something new, something different. And the reasons are many, like I just mentioned, but the end result is, are you ready for when that happens? In a lot of cases, frankly, people aren’t.

CC: Yeah. So if you could give listeners three pieces of advice on how to be less dependent on a particular system, if you had to narrow it down to three, what would you suggest to help them not be just dependent on one particular system or maybe a set of systems?

AP: One thing is when you’re choosing tools, if you end up something that is super proprietary, has its own file formats, et cetera, that means it’s probably gonna be harder to extract your content from that system because it is proprietary. Even if your content is in a standard, and in a lot of cases, of course, I’m talking about DITA, the Darwin Information Typing Architecture and XML standard. Even with DITA, even though it’s open source and a standard, some of the systems that can manage DITA content put their own proprietary layer on top. A good example of this is, for example, those of you with Samsung Android phones. I’ve had one in the past.

CC: Yeah, that’s me.

AP: Samsung puts their own proprietary layer on top of the Android operating system and a lot of that stuff frankly I hate, but that’s not the point of this conversation, but it’s the same issue. You have got this proprietary layer where it may even insert things into your source code that is very particular to that product line. So look at how proprietary your tool is or your toolchain is and how hard is it going to be to export? That should be an early question you ask during even the RFP process. How do people get out of your system? And I realize that sounds absolutely bat, you know what, to be telling people to be thinking about something like that when you’re just getting rolling–

CC: Appropriate for a cave analogy, right?

AP: Yes, true. But you should be, you absolutely should be.

CC: And how do you know you are going to get onto the other two things to think about in just a second, but question there, how do, what are some maybe green flags for how that question should be received or how you want that question to be received if it’s going to maybe be the right fit?

AP: I would hope some variation of the answer would be you can export to this standard, although that often is probably not the answer that you’re going to get.

CC: Okay, as standard. What are some other things people need to keep in mind in order to not be system-dependent?

AP: I don’t know if it’s so much system-dependent, but you need to think culturally about what this means. People become very attached to their tools because they become very adept. They become experts in how to manipulate and do whatever with a certain tool set. And they feel like, you know, I am in total control here. I know what I’m doing. Things are running well. 

CC: Yeah.

AP: And when it turns out that tool is going to have to go away, their entire process and their focus on being an expert, it’s blown. It’s just blown away. And that can be very hard to deal with from a person level, a people level, having to tell people, yeah, this is a shock to your system. You’ve been using this tool forever. You’re really good at it. Unfortunately, that tool is being discontinued. We’re gonna have to move to something else. That can be very hard for people to swallow and it’s understandable.

CC: Mm-hmm.

AP: It’s completely understandable. One other thing that I will mention is if you can get your source content, not the actual delivery points I’m talking about here, but wherever you’re storing your source in some kind of format neutral, file format and again, talking mostly about XML content, extensible markup language, because when you create that content, you are not building in the formatting. You were creating it as a markup language. And the minute your content is in a markup language, it becomes easy to easier. I shouldn’t say easy because nothing here is easier. There is a better path to moving that content, possibly to another standard, for example, because you can set up a transformation process that’s very programmatic.

CC: Mm. Yeah.

AP: This particular element in this model becomes this. And when you hit this particular element in this model, you start a new file. If you see this particular attribute, it needs to be moved over here to this attribute.

CC: Hmm.

AP: So it’s a matching process that you have to do so it can be programmatic. So anytime you get into something that’s XML and what does that X stands for? And what does that X stand for? It stands for extensible. That gives you a little more control because it gives you more flexibility. And that’s weird to think more flexibility gives you more control. That almost seems kind of diametrically opposed, but that’s true.

CC: Yeah.

AP: Because you can move something out more easily because it is something that can be sliced, diced, transformed. So there’s that angle.

CC: Yeah. Yeah. So, okay. So as a non-technical person myself, I’m gonna see if I can summarize this and you tell me whether or not this is accurate. So from a very high level view of this, it’s almost like, you know, rather than keeping all of your content in one particular content management system or something like that, you’re keeping it in a, it’s all stored in a separate box or a separate repository. And then whatever system you’re going to use is your delivery output. It’s almost like a, is that accurate to say? Okay.

AP: Because when you are in a format that is not, doesn’t have the, if you’re in a file format that does not have the formatting of your content built in, that means you can deliver to a bunch of different presentation layers. You can automatically apply it. 

CC: Okay.

AP: And that’s really, I was kind of headed that way. You can even see your new system as almost a delivery target, I need to figure out how to transform my source content in a way that a new tool, a new system can understand. And so basically you’re saying, okay, let’s export it, let’s clean it up, maybe do some automated transformations and programming on it to make it more ingestible by the other system.

CC: Mm-hmm.

AP: So you could even look at this process of moving from one system to another as being really your final destination, another horror movie, your final delivery target, moving that source content into another system that you’re about to use.

CC: Yeah. Thank you also for unpacking that because that was much more clear than my example, but that was really helpful. So since people are planning with the end in mind, how far out are we thinking this exit strategy would typically be implemented? How far down the road is this?

AP: And that’s the thing, I can’t answer that question because you never know what is going to happen. you, right, mean, it’s like the cave collapse analogy like you mentioned, sometimes you have to take a detour, not of your own choice or of your own making. And again, mergers, tools being discontinued, companies that go under, all of these things can happen. And you need to have a contingency.

CC: Mm. Never know. So it’s a contingency plan, really. Yeah.

AP: And you need to have a contingency plan in place to get ready to exit. It’s just like during natural disaster season, you hear people say, do you have your emergency preparedness kit ready? It’s a very similar thing, but it’s in the corporate world. This is as much about risk reduction as it is about smooth content operations, at least from my point of view.

CC: Yeah. Yeah. And you mentioned several like big things that happen that can trigger the need to, you know, it’s time to exit and move on. Are there any scenarios where there isn’t a big thing that happens like a merger or a business closing or different things like that? Are there more quiet ways where you realize you may not realize that it’s time to exit? But it’s more the need to exit is more subtle.

AP: If your content process, your content operations cannot support new business requirements, for example, you need to connect to a new system, you need to deliver your content in another format. If your current system and tools can’t do that, that is a sign you’re probably going to have to find the exit door and find something that will support whatever it is that you cannot do.

CC: Mm-hmm.

AP: It’s usually you just hit this wall where you realize we have taken this tool and this process as far as it can go. It is time to move on. And here I am going to toot the consultant horn again. But that is when you start getting that uneasy feeling, that’s when you can talk to a consultant who can help you unpack it to see if it’s really a sign that the tool is no longer going to fit you or if there’s something you can do within your current system to make things work. That’s when a third-party point of view can be very valuable.

CC: Question for you on that third party perspective, since you’ve seen companies make these transitions many times and exit something and go into a new one, what’s one thing or pitfall that companies need to be aware of that maybe isn’t included in their exit strategy that should be? 

AP: Something that’s very common is to frame everything you want from your new system from the perspective of what your current system is doing. Even though your current system is not going to do something that you need it to do, you still are so fixated on how it is doing things and you can’t get beyond that. That can be a huge problem. Being able to step back and objectively look. This system can’t do this.

CC: Mmm.

AP: We need it to do that. And this is how we need to get there. People can get so mired in the, this is how we’re doing things. And we’re going to move over to this new system and do the same exact thing, just in new tools. That’s not a reason to move. There’s some compelling thing that’s forcing you out of that other tool. So now is the time to change things, update things, make some nips and tucks. Maybe undo some things. Don’t just wholesale move over into a new system and keep things status quo. Otherwise, why bother?

CC: Yeah, yeah. Is there anything else you can think of when you get to when it’s time to start the exiting process? Anything else that you can think of that companies need to have at the forefront of their mind?

AP: It’s the communication. And that includes the vendors and it includes with the people inside the company who are using the tools. And I would also mention it includes procurement. They need to understand the wins, the whys, why you’re having problems, all that, because there can be contractual obligations about when a license ends and another one begins. So you’ve got to keep that information flowing to all kinds of parties to make this exit, this transition work well.

CC: Yeah, you want it to end like the American version of The Descent where the hero actually gets out and drives away in the car, not like the UK version where the person is still stuck in the cave, which is the better ending for a horror movie, I will say, but not for your content ops project. Definitely.

AP: Yeah, but at least in a content ops project, you’re not going to get eaten by some humanoid blind thing living at a cave. 

CC: Hopefully, right? That’s ideal. That’s the best case scenario. 

AP: Hopefully not. Yeah.

CC: Well, Alan, is there any other parting advice you can think of before we wrap up today’s topic?

AP: Don’t go into a cave unprepared. Okay? Just don’t. How’s that?

CC: Yeah, don’t yeah that that is actually good advice. Yeah, don’t go unprepared. That’s really helpful. And like Alan mentioned earlier a third party perspective. I know it’s very biased to be saying it but a third party perspective when it’s time to either make the exit transition or plan for the exit transition. Content strategists can really help with that because we’ve seen we’ve seen a lot of things a lot of caves. Yes. Yeah.

AP: A lot. Maybe not cave dwellers, but a lot.

CC: Hopefully, hopefully no one has actually seen those. Yeah, well, thank you so much for being here, Alan. I really appreciate you talking about this with me today. And thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Survive the descent: planning your content ops exit strategy appeared first on Scriptorium.

We have writers in our authoring environment who are not writers by nature or bias. They’re subject matter experts. And they’re in our system and generating content. That was about joining us in our environment, reap the benefits of multi-language output, reap the benefits of fast updates, reap the benefits of being able to deliver a web-like experience as opposed to a PDF. But what I think we’ve found now is that this is a data project. This generative AI assistant has changed my thinking about what my team does. Yes, on one level, we have a team of writers devoted to producing the docs. But in another way, you can look at it and say, well, we’re a data engine.

— Adam Newton

Related links:

• NetApp Product Documentation featuring Doc, NetApp’s GenAI-powered assistant
• AI in the content lifecycle
• Technical debt in content operations
• The business case for content operations

LinkedIn:

• Adam Newton
• Sarah O’Keefe

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Welcome to the content strategy experts podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage structure, organize and distribute content in an efficient way. In this episode, we talk about content operations with Adam Newton. Adam is the senior director of global content experience services at NetApp. Hi everyone, I’m Sarah O ‘Keefe. Adam, welcome.

Adam Newton: Hey there, how are you doing, Sarah?

SO: It’s good to see and/or hear you. 

AN: Good to hear your voice.

SO: Yeah, Adam and I go way back, which you may discover as we go through this podcast. And as those of you that listen to the podcast know, we talk a lot about content ops. So what I wanted to do was bring somebody in that is doing content ops in the real world, as opposed to as a consultant.and ask you, Adam, about your perspective as the director of a pretty good-sized group that’s doing content and content operations and content strategy and all the rest of us. So tell us a little bit about NetApp and your role there.

AN: Sure. So NetApp is a Fortune 500 company. We have probably close to 11,000 or more global employees. Our business is primarily data infrastructure, storage management, both on-prem. We sell storage operating system called ONTAP. We sell hardware storage devices, and we are most importantly, think, at this day and age, integrating with Azure, Google Cloud Platform, and AWS on first -party hyperscaler partnerships. My team at DENAP is… I actually have three teams under me. The largest of those three teams is the technical publications team. The other two teams globalization responsible for localization translation of both collateral and product. And then finally, and most new to my team is our digital content science team, which is our data science wing. Have about 50 to 53, think, employees at this point in my organization and all told probably about a hundred with our vendor partners.

SO: And so I think we all have a decent idea of what the technical publications team and the globalization teams do. Can you talk a little bit about the data science side? What does that team up to?

AN: Yeah, that’s a thank you for asking that question. So about two years ago, I was faced with an opportunity to hire. And maybe some of your listeners who are managers are familiar with that situation, right? I hope they are, rather than not being able to hire. I took a moment and thought a little bit more about what I needed in the future. And I thought a little bit differently about roles and responsibilities, opportunities inside NetApp and the broader content world and decided to bring in a data scientist. And then I thought a little bit more about, well, there are other data scientists at NetApp. Why would I need one? And I thought a little bit about the typical profile of the data scientists at that time at NetApp, mostly in IT and other product teams. Those data scientists were primarily quantitative data scientists coming from computer science backgrounds. And I thought, well, you know, we’re in the content business. I want to find a data scientist who is a content specialist and who has a background in the humanities and who also has skills in core data science skills, emphasizing, for example, NLP. And so that was my quest. And I was very, very fortunate to find a PhD candidate in English who wanted to get out of the academy and who had these skills. And it’s been an incredible boon to our organization. We’ve even hired a second PhD in English recently. And Sarah, since you and I are friends, I’ll say one was from UNC and one was from Duke. Okay. So we don’t have to have that discussion here. I’m an equal opportunity person. Although I did hire the UNC one first, Sarah.

SO: I see, I see. So for those of you that don’t live in North Carolina, this is… I’m not sure there is a comparison, but it is important to have both on your team. And I appreciate your inclusion of everybody. It is kind of like… I’ve got nothing.

AN: Yes.

SO: Okay, so you hired some data scientists from a couple of good universities. Or do they get along? Do they talk to each other? 

AN: Fabulously, yes. No petty grievances.

SO: Okay, just checking. All right. So how do you, in this context then, what does your environment look like? What kinds of things are you doing with the docs team? And what’s the news from NetApp docs?

AN: So maybe a little bit of background actually, and you and I have talked about this previously, but we used to be a data shop. And then as things sped up inside our business with the adoption and development of cloud services at NetApp, we found that some of the apparatus of our data infrastructure, our past practices weren’t able to keep up to speed of the cloud services that were being developed. I think this is actually, I’ve talked to other people in our business, this is a very common situation. We handled it in one way. There are many ways to handle it, but the way we chose to handle it was to exit data and to move in our source format anyway to a format called ASCII doc, which I always frequently describe as a dialect of markdown. And we went from being a closed system of technical writers working inside a closed CMS to adopting open source. We now work in GitHub. Our pipeline is all open source and we have now contributors to our content that are not technical writers. In some cases, they’re technical marketing engineers, solution architects, and so forth as well as a pipeline of docs that we build through automations where we, for example, transform API specifications or reference docs that are maintained by developers and output those into our own website docs.netapp.com. In addition to just the docs part, my globalization team has been using for many years, machine translation. So speaking to one particular opportunity of being in one organization, when we output our docs and whenever we update our docs in English, they’re automagically updated in eight other languages and published to docs.netapp.com. So we roughly maintain 150,000 English files and you can times those by eight. Is that right? Did I do the math right? Yeah.

SO: Or nine, depending. 

AN: Nine. Yeah. Is English the language? Yeah, sure. Let’s count it.

SO: Depends on how we use it. Okay, so you have an ASCII doc, you know, Markdown-ish. Is it fair to call it Docs as Code environment?

AN: So we often describe it as a content ops, environment. I’m not sure if that is, different from Docs as Code, but I think maybe I will accept that as a reasonable description in the sense that, we have asked our team members to think about the content that they’re writing as highly structured, semantically meaningful units of information. I think in the same way I think a developer can be asked to think of their code being that way and the systems in which we write in VS code, many engineers are writing in that.

SO: Mm-hmm.

AN: And of course our source files, as I mentioned, all in our automation and our pipelines are all based on being in GitHub.

SO: And so then you’ve got docs.netapp.com as a portal or a platform where a lot of this content goes. And what’s happening over there? Do you have any news on new things you’ve done there?

AN: Yeah. I mean, very recently, you know, the timing of this is really interesting. We, have been working on a generative AI solution, for a year, Sarah. you’ll recall the, the hype, right? When, when chat GPT exploded onto the, the, into the public consciousness, right? Through the media and, shortly thereafter, we began imagining what it might look like to leverage that technology, those types of technologies to deliver a different customer experience. And we identified a chatbot as being something we thought could add to the browse and search experiences on docs .netapp .com. And we just released that on the 20th of August announced it here internally inside of NetApp on the 27th. So we are literally like 48, 72 hours into a public adventure here.

SO: I take full credit for planning it, even though I knew nothing about any of this.

AN: Yeah. And that was a long time. I think it’s worth noting too. It was a long time. And I think it’s beyond the full dimensions of this, this discussion to talk about why it took so long. But I will say maybe to, you know, the, were early adopters and we felt, we felt the pain and the benefit of being that, you know, it was like, you know, changing the tires on a, on a race car, right? That was speeding around the track. So we had to learn and be responsive and also humble in the sense that there were some missteps that we had to recover from and some magical thinking, I think, at the beginning of the project that was qualified more over the course of the project.

SO: And so what does that GenAI solution sitting in or over the top of the docs content set, what does that do in terms of your authoring process? Do you have any, are there any changes on the backend as you’re creating this content that is then consumed by the AI?

AN: I would say we’re in the process of understanding the full implications of having this new output surface, this generative AI assistant, and fully grappling with what the implications are for the writers. We find ourselves frequently in discussions about audience. And audience is all those humans that we have been writing for and a whole bunch of machines that we now need to think more consciously about, you know, and it’s, we find ourselves often talking about standards and style, but not just from the perspective of, you know, writing the docs in a consistently patterned way for humans to be able to consume well, but also because patterns and machines are a marriage made in heaven. And we see actually opportunities to begin to think of the content we’re writing as a data set that needs to be more highly patterned and predictable so that a machine can consume it and algorithmically and probabilistically decide how to generate content from the content we’re creating.

SO: And where is this going in terms of what’s next as you’re looking at this? I think you mentioned that there’s other opportunities potentially to add more data slash content.

AN: Yeah, actually, if I back up to a detail and I shared, but maybe quickly, you know, we do have writers in our authoring environment who are not writers. They are by nature and by bias sort of, they’re, people who have their subject matter experts, right? And they’re in our system and they’re generating content. But I think that some of the opportunities that, so that was about join us in our environment, right? Join us in our environment, reap the benefits of multi-language output, reap the benefits of fast updates, reap the benefits of being able to deliver a web-like experience as opposed to a PDF. But what I think we’ve found now is that this is a data project. This generative AI assistant has changed my thinking about what my team does. And I think, yes, on one level, true. Yes, we have a team of writers and there’s a big factory devoted to producing the docs. But in another way, you can look at it and say, well, we’re a data engine. We own a large, own, maintain a large data set and the GenAI is one consumer of that data set. But we’re also thinking about our data set as being joinable to other data sets inside of NetApp. And in particular, I work inside the chief design office at NetApp, along with UX researchers and designers. And we’re also more broadly part of our platform team at NetApp, shared platform team. So we’re thinking about how might we join our data with other teams’ data to create in-product experiences that are data-led or data-driven in combination with curated experience. So if your viewers were to be able to see me, I am waving my hand a little bit, not because I’m dissembling, but more because I’m aspiring. And I think there’s a really, really cool future ahead for, a way, Sarah, that I think is super energizing for the writers, right? To see that their work is being reframed, not replaced or changed, right? The fear of writers with GenAI, right, of being replaced. Well, I would offer this as an example of, you know, maybe it’s not such a dismal view and maybe in fact there’s a very interesting future if you reframe your thinking about what you do and the opportunities to join what you do to create different experiences.

SO: And I think it’s an interesting perspective to look at GenAI as being a consumer of the content slash data that you’re putting out. A lot of the initial stuff was, this is great. GenAI will just replace all the tech writers. You’re talking about something entirely different.

AN: I guess I wanted to expand on that because I think we’re actually now hovering on a really important point. You know, what is your mindset? You know, what what how are you thinking about this moment in time? The broad we write you or the broader you us generally write who are in this industry. And, you know, I think we don’t see a great indication that GenAI can create net new content and do it well, honestly. I think you can write it summarizing, it can make your day-to-day, your meeting notes and so forth, Microsoft Co-pilot, right? There are some great uses, but I have not seen convincing, compelling indicators that docs can be written by, at least at the enterprise level, right? Our products are complex. We often talk about our writers as sense makers, right? And I think that we can take advantage of GenAI in the right ways. And I think this is one of the ways that we’re taking advantage of it, which is to give customers another experience. And frankly, also for us to learn a lot about what people are asking and assuming and we can learn a lot and continuously improve.

SO: So what’s happening on the delivery side? Somebody asks for some sort of information and it gives either, it says it doesn’t exist or it gives an incorrect response. Are you seeing any patterns there? What are you doing with that?

AN: Yeah, many of your listeners might have produced products themselves, right, or delivered products themselves and remembered what happens in the first day or two of releasing a product, right? So the timing of this chat is really good. Yeah, in the last couple days we’ve seen I was just talking to a data scientist on my team and I was saying, you know, what I think I see here emerging as a possible pattern is that people don’t actually know how to use these things effectively. That, you know, they ask of it questions that it really could never answer, or they don’t fully understand the constraints of the system, meaning that, well, it’s only based on a certain data set. you know, they don’t know that the data set doesn’t include the data they’re looking for, right? Because it sits somewhere else. You know, we’re modifying our processes to intake feedback. I think there’s a real interesting nexus is, is it the AI or is it the content? That’s the really interesting one, right? You know, was the content ambiguous, deficient, duplicitous, whatever, you know, is that a word?

SO: It is now.

AN: At UNC we use that word, not at Duke. But it is an interesting discussion inside our organization when we receive a piece of feedback, what’s causing it? Is it the interpretive engine or is it our source? And so we’re seeing a lot of gaps in our content, it’s exposing a lot of gaps or other suboptimal implementations.

SO: I mean, we’ve said that in a sort of glib manner, because of course you’re living this day to day and hour by hour, but we’ve said that, know, GenAI sitting over the top of a content set is going to uncover all your inconsistencies, all your missing pieces, all your, you know, over here you said update and over here you said upgrade. That was an example I heard from someone else. And so it basically uncovers your technical debt.

AN: Yeah, beautiful. Yeah, bingo. Yeah. Yeah. Yeah. You’re so right there. Terminology, right? my God. Can you believe how many things, how many ways we’ve talked to, talked about X, right?

SO: Right, and the GenAI thinks they’re different because, or it doesn’t think anything right, but the pattern isn’t there and so it doesn’t associate those things necessarily.

AN: Yeah, your listeners may commiserate with this, or the use of words as verbs and nouns, like cable. We often in our documentation talk about cabling devices. How would a GenAI know that the writer of the question is using cable as a verb or noun?

SO: Mm-hmm. So as you’re working through this and with your, you know, it sounds like two days of go live plus a year or two or three of suffering and a year and two days. 

AN: Well, a year and two days, a year and two days.

SO: You know, I think you’re further along than lot of other organizations. Do you have any advice for those that are just beginning this journey and just looking at these kinds of issues? What are the things you did best or maybe worst or would do the same way or not? What’s out there that you can tell people that’ll maybe keep them from, you know, get them, get them or help them as they move forward?

AN: Yeah, but maybe think of it in the old people process systems dimensions. Actually, taking that latter one, systems, I would say beware the fascination of the system without thinking more about the processes and people that are going to be involved in the creation of some kind of generative AI solution. I think, you know, this is as much of an adaptive people process as it is a problem as it is a technical problem. Probably more frankly on the adaptive. And from a process perspective, I’d say, be curious about what you learn. Be attentive to the specifics, but look for the broad patterns in the feedback or what you’re seeing as you develop these solutions, you know, for me, I think I hinted at this before and I think it for me has been frankly, the epiphany of the project. There have been many, but I’d say I I would really highlight this one, which is what does my team do? What is the value of what they generate? And for me, yes, we are, you know, primarily a team that creates documentation, but you know, holy smokes, you know, the, the idea that we are data owners, and we govern a massive, semantically rich, non-determinant, fast-changing data set, that is super, super interesting. Even here inside NetApp, Sarah, we have teams reaching out to us who frankly before probably never thought about the docs. And all of a sudden, because we have this huge data set, they’re like, wow, we can, you know stress test our system or our new technologies using what they have. That’s a super cool moment for our team. 

SO: Yeah, I think you’re the first person that I’ve heard describe this sort of context shift from this is content to this is data or this content is also data or however you want to phrase that. But I think that’s a really interesting point and opens up a lot of fascinating possibilities, not least for the English PhDs of the world. That’s super helpful.

AN: Is this where I confessed at one time trying to think I was going to be one of those and I got out because I realized I was terrible at it?

SO: No, no, no, that goes in the non-recorded part of the podcast. Yeah, I’m going to wrap it up there before Adam spills all of the dirt. 

AN: Yeah, what am I compensating for, right?

SO: But thank you, because this is really, really interesting. And I think it will be helpful to the people listening to this podcast, because it’s so rare to get that inside view of what it really looks like and what’s really going on inside some of these bigger organizations as you move towards AI, GenAI strategies and figure out how best to leverage that. So thank you, Adam. And it’s great to see you.

AN: No, Sarah, thank you. And actually, I would like to thank my team. I mean, it has been an incredible adventure, and I think the team is really amazing.

SO: Yeah, and I know a few of them and they are great. So with that, thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Enterprise content operations in action at NetApp (podcast) appeared first on Scriptorium.

If you’re in a desktop tool and everything’s working and you’re happy and you’re delivering what you’re supposed to deliver and basically it ain’t broken, then don’t fix it. You are done. What we’re talking about here is, okay, for those of you that are not in a good place, you need to level up. You need to move into structured content. You need to have a content ops organization that’s going to support that. What’s your next step to deliver at the enterprise level?

— Sarah O’Keefe

Related links:

• The business case for content operations
• Do you have efficient content ops?
• Technical debt in content operations
• Content Ops Forecast: Mostly Sunny With A Chance Of Chaos (webinar)

LinkedIn:

• Sarah O’Keefe
• Alan Pringle

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Alan Pringle: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about setting up your content operations for success. Hey everyone, I am Alan Pringle and I am back here with Sarah O ‘Keefe in yet another podcast episode today. Hello, Sarah.

Sarah O’Keefe: Hey there.

AP: Sarah and I have been chatting about this issue. It’s kind of been this nebulous thing floating around and we’re gonna try to nail it down a little bit more in this conversation today. This idea of setting up your organization for success and their content operations. And to start the conversation, let’s just put it out there. Let’s define content ops. What are content operations, Sarah?

SO: Content strategy is the plan. What are we going to do, how do we want to approach it? Content ops is the system that puts all of that in place. And the reason that content ops these days is a big topic of conversation is because content ops in sort of a desktop world is, well, we’re going to buy this tool, and then we’re going to build some templates, and then we’re going to use them consistently. And the end, right? That’s pretty straightforward. But content operations in a modern content production environment means that we’re talking about lot of different kinds of automation and integration. So the tools are getting bigger, they’re scarier, they’re more enterprise level as opposed to a little desktop thing. And configuring a component content management system, connecting it to your web CMS and feeding the content that you’re generating in your CCMS, your component content management system, into other systems via some sort of an API is a whole different kettle of fish than dealing with, you know, your basic old school unstructured authoring tool. So yeah.

AP: Right. But in their defense, for the people who are using desktop publishing, that is still content operations.

SO: Sure, it is.

AP: It’s just a different flavor of content operations. And frankly, a lot of people, a lot of companies and organizations outgrow it, which is why they’re going to this next level that you’re talking about.

SO: Right. So if you’re in a desktop tool and everything’s working and you’re happy and you’re delivering what you’re supposed to deliver and basically it ain’t broken, then don’t fix it. You are done. You should shut off this podcast and go do something more fun with your time. Right? What we’re talking about here is, okay, for those of you that are not in a good place, you need to level up. You need to move into structured content. You need to have a content ops organization that’s going to support that. What do you do? What’s your, you know, what’s your next step and what does it look like to organize this project in such a way that you move into, you know, that next level up and you can deliver all the things that you’re required to deliver in the bigger enterprise, whatever you want to call that level of things. So desktop people, I’m slightly jealous of you because it’s all working and you’re in great shape and good for you. I’m happy for you.

AP: So making this shift from content operations and desktop publishing to something more enterprise level like you’re talking about, that is a huge mind shift. is also technically something that can be quite the shock to the system. How do you go about making that leap?

SO: Well, I’m reminded of a safety announcement I heard on a plane one time where they were talking about how, you know, when you open the overhead bins after landing, you want to be careful. And the flight attendant said, shift happens. And we all just looked at her like, did you actually just say that? And she sort of smirked. So making this shift can be, it’s can be, it’s difficult, right? And what we’re usually looking at is, okay, you’ve been using, you know, Word for the past 10, 15, 20, 57 years. And now we need to move out of that into, you know, something structured XML, maybe it’s DITA, and then get that all up and running. And so what’s going to happen is that you have to think pretty carefully about what does it look like to build the system and what does it look like to sustain it? Now here I’m talking particularly to large companies because what we find is the outcome in the end, right, when this is all said and done and everything’s up and running and working, what you’re probably going to have is some sort of an organization that’s responsible for sustainment of your content ops. So you’re to have a content ops group of some sort, and they’re going to do things like run the CCMS and build new publishing pipelines and keep the integrations moving and help train the authors. And in some cases, they’re kind of a services organization in the sense that you have an extended group of maybe hundreds of authors who are never going to move into structured content. So you’re taking on the, again, word content that they are producing, but you’re moving it into the structured content system as a service, like an ingestion or migration service to your larger staff or employee population. Okay, so in the future world, you have this group that knows all the things and knows how to keep everything running and knows how to kind of manage that and maintain it and do that work. And probably in there, you have an information architect who’s thinking about how to organize content, how to classify and label things, how to make sure the semantics, you know, the actual element tags are good and all that stuff. But right now, you’re sitting in desktop authoring land with a bunch of people that are really good at using whatever your desktop authoring tool may be. And you have to sort of cross that chasm over to, now we’re this content ops organization with structured content, probably a component content management system. So what I would probably look at here is, you know, what is the outcome? You know, thinking about the system has stood up, we’ve made our tool selection, everything’s working, everything’s configured, everything’s great. What does it look like to have an organization that’s responsible for sustaining that? And that could be, you know, two or three or 10 people, depending on the size, again, the size and scope of your organization and the content that you’re supporting. But in order to get there, you first have to get it all set up. You have to do the work to get it all up and running. Our job typically is that we get brought in to make that transition. Right? So we’re not going to be for a large organization, we’re not going to be your permanent content ops organization. We might provide some support on the side, but you’re going to have people in-house that are going to do that. They’re going to be presumably full-time permanent kind of staff members. They know your content and your domain and they have expertise in, you know, whatever your industry may be.

AP: Right.

SO: Our job is to get you there as fast as possible. So we get brought in to do that setting up piece, right? What are the best systems? What are the things you need to be evaluating? What are the weird requirements that you have that other organizations don’t have that are going to affect your decisions around systems and for that matter, people, right? Are you regulated? What is the risk level of this content? How many languages are you translating into? What kind of deliverables do you have? What kind of integration requirements do you have? And when I say integration, to be more specific, maybe you’re an industrial company and so you have tasks, service, maintenance kinds of things, and you need those tasks like how to replace a battery or how to swap out breaks to be in your service management system so that a field service tech can look at their assignments for the day, which are, you know, go here and do this repair and go here and do this maintenance. And then it gets connected to, and here’s the task you need and here’s the list of tools you need. And here are all the pieces and parts you need in order to do that job correctly. Diagnostic troubleshooting systems. You might have a chat bot and you want to feed all your content into the chat bot so that it can interact with customers. You may have a tech support organization that needs all this content and they want it in their system and not in whatever system you’re delivering. So we get into all these questions around where does this content go? You know, where does it have tentacles into your organization and what other things do we need to connect it to and how are we going to do that? So I think it’s very helpful to look at the upfront effort of configure or, you know, making decisions, deciding on designing your system and setting up your system versus sustaining, enabling, and supporting the system.

AP: There are lots of layers that you just talked about and lots of steps. It is very unusual, at least in my experience, to find someone, some kind of personnel resource, either within or hiring, who is going to have all of the things that you just mentioned because it is a lot to expect one person to have all of that knowledge, especially if you are moving to a new system, and you’ve got a situation where the current people are well versed in what is happening right now in that infrastructure, that ecosystem. To expect them to magically shift their brain and figure out new things, that’s a lot to ask for. And I think that’s where having this third-party consultant person, voice, is very helpful because we can help you narrow in on the things that are better fits for what you’ve got going on now and what you anticipate coming in the future.

SO: Yeah, I mean, the thing is that what you want from your internal organization is the sustainability. But in order to get there, you have to actually build the system, right? And nearly always when people reach out to us and say, we’re making this transition, we’re interested, we’re thinking about it, et cetera, they’re doing it because they have a serious problem of some sort. We are going into Europe and we have no localization capabilities or we have them, but we’ve been doing, you know, a little bit of French for Canada and a tiny bit of Spanish for Mexico. And now we’re being told about all these languages that we have to support for the European Union. And we can’t possibly scale our, you know, 2 .5 languages up to 28. It just, it just can’t be done. We’ll, we’ll drown. Or people say, We have all these new requirements and we can’t get there. We’ve been told to take our content that’s locked into, you know, page based PDF, whatever, and we’re being required to deliver it, not just onto the website and not just into HTML, as you know, content as a service, as an API deliverable, as micro content, all this stuff. And they just, they just can’t, you can’t get there from here. And so you have people on the inside who understand, as you said, the current system really well, and understand the needs of the organization in the sense of these things that they’re being asked to do and they understand the domain. They understand their particular product set internally. But it’s just completely unreasonable to ask them to stand up, support and sustain a new system with new technology while still delivering the existing content because, you know, that doesn’t go away. You can’t just push the pause button for five months.

AP: No, the real world does not stop when you are going on some kind of huge digital transformation project like one of these content ops projects. So basically what we’re talking about here, especially on the front end, the planning discovery side, is we can help augment, help you focus. And then once you kind of picked your tools and you start setting things up, there’s some choices there that sometimes have to do with like the size of an organization about how to proceed with implementation and then maintenance beyond that. Let’s focus on that a little bit.

SO: Most of the organizations we deal with are quite large. Actually, all of the organizations we deal with are quite large compared to us, right? It’s just a matter of are they a lot bigger or are they a lot, a lot, a lot, lot bigger?

AP: Correct.

SO: Within that, the question becomes how much help do you want from us and how much help do your people need in order to level up and get to the point where they can be self-sufficient? We have a lot of projects we do where we come in and we help with that sort of big hump of work, that big implementation push, and help get it done. And then once you go into sustainment or maintenance mode, it’s 10% of the effort or something like that. And so either you staff that internally as you’re building out your organization internally, or we stick around in sort of a fractional, smaller role to help with that. The pendulum kind of shifted on this for a while, or way back, way back when it was get in, do the work and get out. We rarely had ongoing maintenance support. Then for a bit, we were doing a lot of maintenance relative to the prior efforts. And now it feels as though we’re seeing a shift in a little bit of a shift back to doing this internally. Organizations that are big enough to have staff like a content ops group or a content ops person are bringing it back in-house instead of offloading it onto somebody like us. We’re happy to do whatever makes the most sense for the organization. At a certain size, my advice is always to bring this in-house because ultimately, your long-term staff member who has domain expertise on your products and your world and your corporate culture and has social capital within your organization will be more effective than offloading it onto an external organization, no matter how great we are.

AP: To wrap up, think I want to touch on one last thing here, and that’s change management. And yes, we beat that drum all the time in these conversations on this podcast, but I don’t think we can overstate how important it is to keep those communication channels open and be sure everyone understands what’s going on and why you’re doing what you’re doing. What we’ve talked about so far is very much, okay, we’ve come up with a technical plan, we’ve done a technical implementation, and now we’re going to set it up for success and maintain it for the long haul and adjust it as we need to as things change. But there are still a group of people who have to use those tools, your content creators, your reviewers, all of those people, your subject matter experts, I mean, I can go on and on here, they are still part of this equation here and we can’t forget about them while we’re so focused on the technical aspects of things.

SO: I would say this and directly to the people that are doing the work, know, the authors, the subject matter experts, the people operating within the system. I would look at this as an opportunity. It is an opportunity for you to pick up a whole bunch of new skills, new tools, new technologies, new ways of working. And while I know it’s going to be uncomfortable and difficult and occasionally very annoying as you discover that the new tools do some things really well, but the things that were easy in the old tools are now difficult, right? There’s just going to be that thing where the expertise you had in old tool A is no longer relevant and you have to sort of learn everything all over again, which is super, super annoying. But it’s fodder for your resume, right? I mean, if it comes to it, you’re going to have better skills and you’re going to have another set of tools and you’re going to be able to say, yes, I do know how to do that. So I think that just from a self-preservation point of view, it makes a whole lot of sense to get involved in some of these projects and move them forward because it’s going to help you in the long run, whether you stay at that organization or whether you move on to somewhere else, you know, at some point in the future. That’s one of the ways I would look at this. It is certainly true that the change falls on the authors, right?

AP: Correct.

SO: They all have to change how they work and learn new ways of working and there’s a lot there and I don’t want to you know sort of sweep that aside because it can be very painful. We try to advocate for making sure that authors have time to learn the new thing that people acknowledge that they’re not going to be as productive day one in the new system as they were in the old system that they know inside out and upside down that they get training and knowledge transfer and just, you a little bit of space to take on this new thing and understand it and get to a point where they use it well. So I think there’s a, you know, there’s a combination of things there. For those of you that are leading these projects, it is not reasonable, again, to stand the thing up and say, go live is Monday. So, you know, I expect deliverables on Tuesday. That is not okay.

AP: Yeah. And you’ve just wasted a ton of money and effort because you’ve thrown a tool at people who don’t know how to use it. So all of your beautiful setup kind of goes to waste. So there are lot of options here as far as making sure that your content ops do succeed. And I don’t think it’s like pretty much everything else in consulting land. It is not one size fits all.

SO: It depends, as always. We should just generate one podcast and put different titles on it and just say it depends over and over again.

AP: Pretty much, we’d probably just get an MP3 of us saying that phrase over and over again and just loop it and that will be a podcast episode. And on that not-great suggestion for our next episode, I’m gonna wrap this up. So thank you, Sarah.

SO: Thank you.

AP: I think she just choked on her tea, everyone.

SO: I did.

AP: Thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Position enterprise content operations for success (podcast) appeared first on Scriptorium.

Mike McDermott: It gets very cumbersome to continually do these manual steps to get to a translation update. Once the authoring is done, ideally you just send it right through translation and the process starts.

Bill Swallow: So from an agile point of view, I am assuming that you’re talking about not necessarily translating an entire publication from page one to page 300, but you’re saying as soon as a particular chunk of content is done and “blessed,” let’s say, by reviewers in the native language, then it can immediately go off to translation even if other portions are still in progress.

Mike McDermott: Exactly. That’s what working in this semantic content and these types of environments will do for a content creator. You don’t need to wait for the final piece of content to be finalized to get things into translation.

Related links:

• MadCap Software
• MadTranslations
• Accelerate global growth with a content localization strategy (podcast)
• Lost in translation? Create scalable content localization processes

LinkedIn:

• Bill Swallow
• Mike McDermott

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Bill Swallow: Welcome to the Content Strategy Experts podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we explore strategies for conquering localization challenges, and unlocking new market opportunities. Hi everybody. I’m Bill Swallow, and with me today is Mike McDermott from MadCap Software. Hey Mike.

Mike McDermott: Hi Bill.

BS: So before we jump in, Mike, would you like to provide a little background information about you, who you are, what you do at MadCap?

MM: Sure. My name is Mike McDermott. I am the director of language services at MadCap Software working with our MadTranslation Group. And we support companies that work in single source authoring in multichannel publishing tools like those offered from MadCap Software for IXIA and MadCap Flare and Xyleme and other tools.

BS: So Mike, what are some of the challenges you’ve seen and what works for overcoming some of these localization challenges?

MM: One of the main challenges I see with companies that come to us, and they typically come to us because they’re looking at working in an XML-based authoring tool and they’re curious about the advantages it has for translation. And one of the biggest challenges I see initially with these companies is just figuring out what content needs to go into translation when you’re working in different types of tools. And one of the ways I see to solve that problem is working in a tool where you have the ability to tag certain content and identify content for different audiences or different purposes. It just makes it simpler to identify that content and get it straight into translation and removes a lot of the human error around packaging up content and trying to figure out yourself what files, house texts that might be translatable for whatever the output is that you’re looking to build. So just working in those tools I see inherently helps with translation because it helps you identify exactly what needs to be translated and it gets it into translation much quicker.

BS: So I think we’re talking about semantic content there and making sure that you have all the right metadata in place so that you can identify the correct audience, the correct, let’s say versions of the product, whether to translate or not, and any other relevant information about the content. So you’re able to isolate the very specific bits of content that need to be translated and omit a lot of the content that necessarily isn’t needed for that deliverable.

MM: Exactly, Bill. It lets the technology tell you what needs to be translated in what houses text versus you trying to go through a file list and determine what do I need to send out to a translator to translate. The flip side of that is to just send everything for translation, but it’s very rare that anything in any given project for any type of system is going to need to be translated. So by tagging it in that way, you can quickly get into the translation and get things moving. And what I see happening at the end of these projects, oftentimes when you’re not working in those types of systems is you end up finding bits and pieces of content or different files that ended up needing to be translated that missed that initial pass. Now they have to go back through translation and you’re delayed. So just getting everything right the first time and relying on the tools to tell you exactly what needs to be translated by looking up metadata or different tags just simplifies the process and speeds everything up, helps translation get done quicker and just improves time to market for the end user to get their content out.

BS: So it sounds like it reduces a good amount of friction, especially with regard to finding missing bits and pieces that should have been translated and weren’t, and then needing to go back and make sure that’s done in time. What are some other ways that people can reduce friction in their translation workflow?

MM: Well, a big emphasis for us over the past few years around removing friction is working with connectors and different technologies that can orchestrate the translation process. So we can automate a lot of this and remove the bottlenecks around someone having to, like I said before, manually go into a set of files and package things up for a translator, zip up files, upload them to different locations, and they just get passed around and things can happen when working that way, even outside of just missing files. So working with connectors and these technologies that can connect directly into these systems and get the text right into translation, removing all those friction points just eliminates a lot of room for error in project delays, bottlenecks for tasks that can be easily handled by modern technology.

BS: And I assume that there’s probably some technology there as well that kind of govern other things, other parts of the workflow, like review, content validation, that type of thing?

MM: Exactly, exactly. So we’re trying to automate the flow of data into the different points in translation and then get the content ready. For example, for reviewers, you mentioned reviewers. So once content gets into translation, we can get it right into the translation system from the authoring environment that the customer’s working in, get it into translation. And as soon as the translation is done, a human reviewer on the client side or on our side or whoever can be notified that this content is ready for translation and it just helps keep things moving. So now it’s on them to complete their translation. And once that’s done, the process can continue on and the automated QA checks, the human QA checks can be done at that point, and then the project can be pushed back to wherever it needs to go and put into publication. But by automating the steps and plugging in the humans where they provide the most value, it just removes the time costs in error-prone steps that don’t need to be there.

BS: So it sounds like a lot of it does come down to saving a good deal of time. I would also imagine that these types of workflows, they also help streamline a lot of the publishing needs that come after the translation as well.

MM: Correct. And that’s kind of why we started MadTranslation when we did, was to provide our customers a place to go to work with the translation agency that understood these tools and understand how these bits and pieces come together to build an output. We put it together to provide our customers a turnkey solution where they can get a working project back where they can quickly get into publication. By removing the friction points and using modern technology to automate a lot of these processes, we’re able to get things into translation and add a translation into the final deliverable much faster. So once that happens, we can build the outputs and we can check if it requires a human check on it, things can get to that point much quicker, and we’re not waiting for somebody to manually pull down files and putting them into another location so the next actually take place. We want to automate that part of it so we can get to that final output into a project file where a customer can plug it into their publishing environment and get it out as quickly as possible. A lot of the wasted time is around those manual steps, and when it comes to validation and review, it’s just the reviewers and validators maybe not being ready for the validation or not being educated on how it will work. So it’s important to make sure that everyone in that process knows how it’s going to be done, when things are going to be ready for the review or the QA checks. And then the idea from there is to just feed the content in via connectors, removing the friction point and just send it through. And this is necessary, especially when you’re doing very frequent updates and kind of a more of an agile translation workflow. It gets very cumbersome to continually do these manual steps to get to a translation update. Once the authoring is done, ideally you just send it right through translation and the process starts.

BS: So from an agile point of view, I am assuming then that you’re talking about not necessarily translating an entire publication from page one to page 300, but you’re talking about as soon as a particular chunk of content is done and it’s “blessed,” let’s say, by reviewers in the native language, then it can immediately go off to translation even if other portions are still in progress.

MM: Exactly. Exactly. And that’s what working in this semantic content and these types of environments will do for a content creator is you don’t need to wait for the final piece of content to be finalized to get things into translation. So as you said, it becomes even more important when you’re doing updates because you don’t want to have to send over the entire file set every time you’re doing an update. Whereas when you’re working in a more linear format like Word, you end up having to send that full file every time, and the translation agency is likely reprocessing it using translation memory. But all that stuff still takes time and working in these types of tools, you can very quickly identify those new parts or those bits that you know are ready for translation, tag them or mark them in some way and send them through the translation process.

BS: Very cool. So a lot of the work that we’re seeing now on the Scriptorium side of things is in re-platforming. So people have content in an old system or they have, say a directory full of decaying word files, and they want to bring it into some other new system. They want to modernize, they want to centralize everything, basically have a situation where they’re working in data or some other structured content, bring it into semantic content. What are some of, I guess, the benefits of doing that give you as far as translation goes when you’re looking at content portability? So being able to jump ship from one system to another.

MM: I think working in those systems where the text or the content is stored away from the output that you’re building has a lot of benefits to not only translation being able to just get the text that needs to be translated, exported out of the system and then put back where it needs to go. But it really future-proofs you and gives you the portability that you talk about to make changes because the text is stored in a standard format that can be ported versus you see some organizations getting locked into a closed environment to where when it goes to make a change, it requires certain types of exports to other type of file types that other tools can then import. But by storing them in a standard way in XML, for example, it gives you that flexibility in a future proves you from being locked into any one scenario.

BS: Excellent. So I have to ask, since I’ve come from a localization background as well, what’s one of the hairier projects that you’ve seen or one of the hairier problems that people can run into and in a localization workflow?

MM: One of the challenges we run into sometimes around client review, when you start incorporating validators into the translation system and include them as part of the process, when you get multiple reviewers. Sometimes that will happen where a company will assign a reviewer for every language, but you might have different people reviewing the same set of content. I mean, that’s the biggest delay that we see with projects is translations delivered and then the translation is dumped on a native speaker within the company’s desk and they’re asked to review it and they’re not ready to do the review, it’s not scheduled and it can delay the project. That’s one of the biggest delays we see. So that’s why we try at the front end of a project to figure out on the client side, what’s going to happen after we deliver this project, after we send the files, is the content going to be reviewed or validated? If so, let’s figure out a way to incorporate them into our translation system where they can review the translations before we build the outputs and do all the QA checks. So that’s one of the hairier situations in terms of time delays. Expectations around just time in general have always been a thing in localization. As you know, people can be surprised as to how long it can take for a translator to get through content. I mean, the technology is there certainly to speed it up. Since we’ve started MadTranslations a little over 10 years ago, we’ve seen the translation speed increase quite a bit, but it still takes time for a good translator to get through that content and know when to stop and do the research that’s needed to get a technical term right. So that’s one of the surprise moments I think for new buyers of localization is the time that it can take and there’s solutions in place, like I said, to make it go faster. But if you want that human review and that expertise and the cognitive ability to know when to stop and figure out what this term is or what the client wants or doesn’t want around certain terminology, and then to database it and then include that as part of the translation asset so it stays consistent every time. That takes time versus just sending something through a machine translation, doing a quick spot check and sending it back to the customer.

BS: So it sounds like having that workflow defined and setting those expectations that certain things need to happen at each point of that workflow. Some of it might be automated, some of it does require a person, and that person I guess should probably be identified ahead of time and given a heads-up that, “Hey, something’s going to be coming at you in three weeks. Be ready for it.”

MM: Be ready for it. And also, what are you ready for? So it’s kind of training a reviewer, what are you looking for here? Are we looking for key terms? Are we looking for style preferences? Everyone kind of understanding what it is that a reviewer is going to be looking for, and they might be looking for different things when it comes to technical documentation versus a website, for example. So just having everyone communicate and understand what the intended purpose of the final output is and where everyone fits in the process and defining a schedule around that process definitely helps.

BS: Definitely. I know myself, I’ve seen cases where working for a translation agency, having a client come to me and basically say, “I need this done as soon as possible. What can you do?” And it was a highly technical manual, and we said, “Well, we have an expert in these different languages. This person is available now. This one won’t be available until next month. And this person really only works nights and weekends because they are a professional engineer in their day job.” So turnaround is going to be a little slow, and the client persisted that we just need it as soon as possible. We need to get it out the door in a couple of weeks, and I’m thinking to myself in the back of my head, why are you coming to us now when you need this in a couple of weeks? You shouldn’t just be throwing it over the fence at the last possible minute and expecting it to come back tomorrow. So there was that education. Unfortunately, they decided that they didn’t care. They wanted us to use as many translators as possible and get it done as quick as possible. And we had them sign documents that basically said that we are not liable for the quality of the translation since the client is basically looking to get this done as quickly and cheaply and dirty as possible. It was a nightmare, and I think it took one round of review on the client side for them to basically circle back and say, “Okay, I get what you were saying now.” None of these translations work at all together, because we were literally sending out a chapter to a different translator and there was no style guide because the client hadn’t provided anything. There was no terminology set because the client didn’t provide anything and everything came back different. And they said, “Okay, we get it. We get it. We’ll revise our schedules, get it done the right way. I don’t care how long it takes.”

MM: I’ve run into something very, very similar to what you described, and it was put disclaimers in the documents to where this is going to be poor quality. We’re admitting it right now. This is the only way we’re going to get it back within a week, and we do not recommend publishing. And as soon as the files come back and so on, looks at it and says, “Okay, let’s back up and do it the right way.”

BS: Yes. I guess the biggest takeaway there is plan ahead and plan for quality and not just try to get it done as fast as possible.

MM: And that’s one of the benefits to where we sit at MadTranslations with MadCap Software companies, companies coming into these types of environments. They’re typically at the front end, the planning stages on trying to figure out how all this is going to work. So we have an ability to help them understand what the process looks like and then define it in combination with our tooling and their needs and come up with a workflow that’s going to keep things moving fast, but gives you that human level quality that everyone needs at the end.

BS: Being able to size up exactly what the process needs to look like before you’re in the thick of it definitely helps. And having that opportunity to coach someone through setting up the process for the first time, I’d say that’s definitely priceless because so many mistakes can happen out of the gate between how people are authoring content, what their workflow looks like.

MM: And it’s even more important for companies to have to maintain the content. So it’s one thing to just take a PDF and say, “Hey, I need to translate this file and I’m never going to have to update it again. I just need a quick translation.” It’s another to have a team of authors dispersed around the globe working on the same set of content that then needs to be translated continuously.

So different needs, but like you said, planning, defining the steps and knowing what the requirements of the content are from authoring to time to publication in each language, and how to fit the steps and to meet that as best as possible is best done, like you said, upfront versus when it needs to be published in a week.

BS: Planning, planning, planning. I think that sounds like a good place to leave it. Mike, thank you very much.

MM: Thank you, Bill. Thanks for having me on.

BS: Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Conquering content localization: strategies for success (podcast) appeared first on Scriptorium.

Here’s the real question I think you have to ask before replatforming—is the platform actually the problem? Is it legitimately broken? As Bill said, has it evolved away from the business requirements to a point where it no longer meet your needs? Or there are some other questions to ask, such as, what are your processes around that platform? Do you have weird, annoying, and inefficient processes?

— Sarah O’Keefe

Related links:

• The true cost of quick fixes (podcast, part 1), where Gretyl Kinsey discusses, “spaghetti reuse”
• Technical debt in content operations
• Renovation revelations: Managing technical debt (podcast)
• Replatforming an early DITA implementation (case study)

LinkedIn:

• Sarah O’Keefe
• Bill Swallow

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about replatforming and its relationship to technical debt. Hi, everyone. I’m Sarah O ‘Keefe. And the two of us rarely do podcasts together for reasons that will become apparent as we get into this.

Bill Swallow: And I’m Bill Swallow. 

SO: What we wanted to talk about today was some more discussion of technical debt, but this time with a focus on a question of whether you can use replatforming and new software systems to get rid of technical debt. I think we start there with the understanding that no platform is actually perfect. 

BS: Mm-hmm.

SO: Sorry, vendors. It’s about finding the best fit for your organization’s requirements and then those requirements change over time. Now Bill, a lot of times when we talk about replatforming, you hear people referring to the burning platform problem. So what’s that?

BS: Yeah, it’s well, it may actually be on fire, but likely not. What we’re really talking about is, you know, a platform that was chosen many years ago. Perhaps it’s approaching end-of-life. Perhaps your business needs have taken a, you know, a left or sharp left or right turn and it no longer, you know, the platform no longer supports those business needs or, you know, it really could be just a matter of cost. You know, the, platform you bought 10 years ago was, was built upon a very specific cost structure and model. And you know, the world is different now, and there are different pricing schemes and whatnot. And you may just want to, you know, replatform to recoup some of that cost.

SO: So does that, I mean, does that work? mean, if you exit platform A and move on to platform B, are you necessarily gonna save money? So no.

BS: In a perfect world, yes, but we don’t live in a perfect world. Yeah. I mean, I hate to be the bearer of bad news, you know, if you’re looking to switch from one, you know, from one platform to another to save costs, there is a cost in making that switch. And, you know, at that point, you need to look at, weighing the benefits and drawbacks, you know, is the cost to move to a new system going to be worth the cheaper solution in the long run. I mean, it’s a very, very basic model to look at. And there’s a lot of other costs and benefits and drawbacks to making a replatforming platform switch. But it’s one thing to consider there.

SO: Yeah, I think additionally, it’s really common to have people come to us and say, you know, our platform is burning. We’re unhappy with platform X and we want to replatform into platform Y. Now, what’s funnier is that usually we have some other customer that’s saying, I’m unhappy with platform Y and I need to go to platform X, right? So it’s just like a conveyor belt of sorts.

BS: You can’t please everybody.

SO: But the real question I think you have to ask before replatforming is, is the platform actually the problem here? Is it legitimately broken? And as you said, it’s evolved away from the business requirements to a point where they no longer meet your needs. And or there are some other questions to ask, like, what are your processes around that platform look like? Do you have weird, annoying, and inefficient processes?

BS: Mm-hmm.

SO: Do you have constraints that are going to force you in a direction that isn’t maybe from a technology point of view the best one? Have you made some old decisions that are now non -negotiable? So you’ll see people saying, well, we have this particular kind of construct in our content and we’re not giving it up ever.

BS: Mh-hmm.

SO: And you look at it and you think, well, it’s very unusual and is it really adding value, but it’s hard to get rid of it because it’s so established within that particular organization. So the worst scenario here is to move from A to B and repeat all the same mistakes that were made in the previous platform.

BS: Yeah, you don’t necessarily want to carry, well, you don’t want to carry that debt over, certainly. You know, so anything that you have established that worked well, but doesn’t meet your current or future needs. mean, absolutely. You do not want to move that forward. That being said, you have a wealth of content, a wealth of technology that you have built over the years and you want to make sure that you can use as much of that as possible to at least give yourself a leg up in the new system. So that you don’t have to rewrite everything from scratch, that you don’t have to completely rebuild your publishing pipelines. You might be able to move them over and change them and you might be able to move and refactor your content so that it better meets your needs. But I guess it’s a long way of saying that not only are you looking at a burning platform problem, but you’re also looking at a futureproofing opportunity. And you want to make sure that if you are going to do that lift and shift to another platform, that you, you take a few steps back and you look at what your current and future requirements are or will be and you make the necessary changes during the replatforming effort before you get into the new system and then start having to essentially deal with the same problems all over again.

SO: Yeah, I mean, to give a slightly more concrete example of what we’re talking about, relative to 10 years ago, PDF output is relatively less important. 10 years ago, we were getting a lot of, need PDF, we have to output it, and it has to meet these very, very high standards. People are still doing PDF, and clients are still doing PDF, but relatively, it is less of a like showstopper, primary requirement. It’s more, yes, we still have to do PDF, but we’re willing to negotiate on what that PDF is going to look like. Instead of saying it has to be this pristine and very complex output, they’re willing to drop that down a few notches. Conversely, the importance of HTML website alignment has gotten much, much higher. And we have a lot of requirements around Content as a Service and API connectors and those kinds of things. So if you just look at all your different publishing output connection pipelines 10 years ago PDF was really still unquestionably the most important thing and that’s not necessarily the case anymore.

BS: And on the HTML side, there’s also, could be HTML, could be JSON, but you do have a wealth of apps, whether it be a phone app or an app in your car or an app on your fridge that needs to be supported as well where your PDF certainly isn’t going to cut it. And a PDF approach to content design in general is not going to fly.

SO: So when we talk about replatforming, we tend to, in many cases, I look at this through the lens of, okay, we have, you know, DITA content in a CCMS and we’re gonna move it to another DITA CCMS. But in fact, it goes way, way beyond that, right? What are some of the, I guess, input or I’ll say legacy, but what are some of the formats that we’re seeing that are on the inbound side of a replatforming?

BS: Let’s see, on the inbound side, we certainly have maybe old models of DITA. So maybe something that was developed in DITA 1.1, 1.2, pre 1.0, something that’s heavily specialized. We have things like unstructured content, like Word files, InDesign, unstructured FrameMaker, and what have you. We’re also seeing that there’s an opportunity there as well to move a lot of developer content into something that is more centrally managed. In that case, we’ve got Markdown and other lightweight formats that need to be considered and migrated appropriately. And then, of course, all of your structured content. So we mentioned DITA. There’s DocBook out there. There are other XML formats and whatnot. And potentially, you have other things that you’re you’ve been maintaining over the years that now is a good opportunity to migrate that over into a system, centralize it, and get it aligned with all your other content.

SO: Yeah, and looking at this, I think it’s safe to say that we see people entering and exiting Markdown, like people saying we’re going to go from DITA to Markdown, but also Markdown to DITA. We’re seeing a lot of going into structured content in various flavors. Unstructured content, we largely are seeing as an exit format, right? We don’t see a lot of people saying, “Put us in Word, please.”

BS: No, no one’s going from something like DITA into Word.

SO: So they might go from DITA to Markdown, which is an interesting one. Okay, so I guess then that’s the entry format. That’s where you’re starting. What’s the outcome format? Where are people going for the most part?

BS: For the most part, there are essentially two winners. There are the XML-based formats, and then there is the Markdown-based formats. And I’m lumping DITA, DocBook, and other proprietary XML models all into XML. But generally, people are migrating more toward that direction than to Markdown. And there’s really a division there. It’s whether you want the semantics ingrained in an XML format and the ability to apply or heavily apply metadata. Or if you want something lightweight, that’s easy to author and is relatively, I don’t want to say single purpose, but it’s not as easily multi-channel as you can get with XML.

SO: Yeah, I mean the big advantage to Markdown is that it aligns you with the developer workflows, right? You get into Git, you’re aligned with all the source control and everything else that’s being done for the actual software code. And if that is a need that you have, then that is, you know, that’s the direction to go in. There are some, as Bill said, some really big scalability issues with that. And that can be a problem down the line, but Markdown generally, you know, okay, so we pick a fundamental content model of some sort, and then we have to think about software. So what does that look like? What are the buckets that we’re looking at there?

BS: For software, we’ve got a lot of things. First and foremost, there’s the platform that you’re moving to. What does that look like? What does it support? You have certainly authoring tools that are there. You also have all of your publishing pipelines. All of that’s going to require software to some degree. Some of it’s third party. Some of it’s embedded in the platform itself. And then you have all of your extended platforms that you are connecting to. Those might change. Those might stay the same. You might not change your knowledge base, for example, but you still need to publish content from the new system. The new system doesn’t quite work the way the old system did. So your connector needs to change. Things like that. I would also say that, you know, with regard to software, there’s also a hit. It’ll be a temporary blip, but it will be a costly blip in the localization space because when you are replatforming, especially if you are migrating formats to a new format, you’re going to take a hit on your 100% matches in your translation memory. So anything that you’ve translated previously, you’ll still have those translations, but how they are segmented will look very different in your localization software.

SO: Yeah, and there are some weird technical things you can do under the covers to potentially mitigate that, but it’s definitely an issue. 

BS: And it’s still costly.

SO: OK, so we’ve decided that we need to replatform and we’ve done the business requirements and we picked a tool and we’re ready to go from A to B, which we are carefully not identifying because some of you are going from A to B and some of you are going from B to A. And it’s not wrong, right? There’s not a single, you know, one CCMS to rule them all. 

BS: Mh-hmm.

SO: They’re all different and they all have different pros and cons. So depending on your organization and your requirements, what looks good for you could be bad for this other company. But within that context, what are some of the things to consider as you’re going through this? So you need to exit platform A and migrate to platform B.

BS: Mm-hmm. I think the number one thing you should not do is expect to be able to pick up your content from platform A and just drop it in platform B. Yeah, it’s never going to be that easy and it shouldn’t be something that you really are considering because not only are you replatforming, but you’re aligning with a new way of working with your content. So just picking it up and dropping it in a new system is not going to help you at all with in that regard. And given that you need to get the content out of the system, that’s the best time to look at your content and say, how do we clean this up? What mistakes do we try to erase with a migration project on this content before we put it in the new system?

SO: Yeah, I think the decisions that were made that tend to take on a life of their own, like this is how we do things. And much, much, much later you find out that it was done that way because of a limitation on the old software. This is like that dumb old story about, you know, cutting the end off the pot roast. And it turned out that Grandma did that because the roasting pan wasn’t big enough to hold the entire pot roast. It’s exactly that, but software, right? So bad decisions or constraints, you need to test your constraints to see whether your new CCMS, in fact, is a bigger roasting pan that does not require you to cut the end off the pot roast. What about customization?

BS:  Customization is a good one. And what we’re finding is that a lot of the old systems or people who are exiting an older system for a newer system, they have a lot of heavy customization because there wasn’t a, in many regards, there wasn’t a robust content model available at the time. So they had to heavily specialize their content model and make it tailored to the type of content that they were developing. And now, you know, something that was built 10, 15 years ago that is using highly structured, specialized structured content. If you look at what’s available now, a lot of those specializations have been built into the standard in some way. So you can unwind a lot of that. It’s a great opportunity to unwind a lot of it and use the standard rather than your customization. That helps you move forward as the specifications for the content model change, you will be aligned with that change a lot better than if you had used a customization along the way. Specialization or any kind of customizations for that matter, you know, they’re expensive. They’re expensive to build. They’re expensive to maintain. They’re expensive to train people on. You know, they affect every aspect of your content production from authoring to publishing. There’s, something that needs to be specifically tailored, whether it’s training for the writers, whether it’s a training, you know, designing your publishing pipelines to understand and be able to render those customers, customized models, the translators that are involved, making sure that, you know, their systems can understand your tags if they’re custom so that they know whether, you know, that they can show and hide them from the translators and you don’t get translations back that contain translated tags, which we’ve seen. There’s a lot going on there. So the more that you can unwind, if you have heavily customized in the past, the better off you will be.

SO: Yeah, I think, mean, and here we’re talking, I think specifically about some of the DITA stuff. So if you’re in DITA 1.0 or 1.1 with your older legacy content, they added a lot of tags and did a 1.3 and they’re adding more and did a 2.0 that might address some of the things like you added a specialization because there was a gap or a deficiency in the DITA standard. So you could probably take that away and just use the standard tag that got added later. Now, I want to be clear that, I mean, we’re not anti-specialization. I think specialization is great and it’s a powerful tool to align the content that you have and your content model with your business requirements. And you have to make sure that when you specialize, all the things that Bill’s talking about, all those costs that you incur are matched by the value that you get out of having the specialization.

BS: Mm-hmm.

SO: So, you’re going to specialize because it makes your content better and you have to make sure that it makes it enough better to make it worthwhile to do all these things. Very, very broadly, metadata customization nearly always makes sense because that is a straight-up, we have these kinds of business divisions or variants that we need because of the way our products operate. And those nearly always make sense. And element specialization tends to be a bigger lift because now you’re looking at getting better semantics into your content. And you have to ask the question, do I really need custom things, or is this out of the box, did a doc book, custom XML content model good enough for my purposes? That’s kind of where you land on that. And then reuse, I did want to touch on reuse briefly because, you know, we can do a lot of things with reuse from reusing entire, you know, chunks, topics, paragraph sequences, list of steps, that kind of thing, all the way down to individual words or phrases. And the more creative you get with your reuse and the more complex it is, the more difficult it’s going to be to move it from system A to system B.

BS: Absolutely. It’ll be a lot more difficult to train people on as well. And we’ve seen it more times than not that even with the best reuse plan in mind, we still see, you know, what we call spaghetti reuse in the wild, where, know, someone has a topic or a phrase or something in one publication and they just reference it into another publication rather, you know, from one to the other. And it doesn’t necessarily, some systems will allow that. I’ll just put that out there. Other systems will absolutely say, absolutely not. You cannot do this. And you have to, you know, make sure that whatever you’re referencing exists in the same publication that, you know, that, that you’re publishing. so we’ve had to do a lot of unwinding there, you know, with regard to this spaghetti reuse and we’ve, we’ve had a podcast in the past with Gretel Kinsey on our side who I believe she talked extensively about spaghetti reuse. What it is what it isn’t and why you should avoid it. But yes as you’re replatforming if you know you have cases like this It’s best to get your arms around it before you put your content in the new system.

SO: Yeah, and we’ll see if we can dig it out and get it into the show notes. What about connectors?

BS: Connectors are interesting. And by that, we’re talking about either webhooks or API calls from one system to another to enable automation of publishing or sharing of content and what have you. For the most part, if you’re not changing one of the two systems, managing that connector can be a little bit easier, especially if it’s your target or the receiving end of the content is reaching out and looking for something else in like a shared folder using the webhook or using an FTP server, what have you. But generally, know, those webhooks can or sorry, those connectors can get a little sketchy. You know, it might be that your new platform doesn’t have canned connectors for the other systems that you have always connected to and need to connect to. So then you need to start looking at, well, do we need to build something new? we find a way of, find some kind of creative midpoint for this? They can get a little dicey. So I think it’s important to, before you re -platform, before you even choose your new content management system, that you look at where your content needs to go. And if you have support from that system to get you there.

SO: So a simple example of this is localization. If you have a component content management system of some sort, you’ve stashed all your content in, and then you have a translation management system. And the old legacy system, the platform you’re trying to get off of, has or maybe doesn’t have, but you need a connector from the component content management system over to the TMS, the translation management system, and back so that you can feed it your content and have the content returned to you. 

BS: Mm-hmm.

SO: Well, if that connector exists in the legacy platform, but not in the new platform, you’re gonna have to either lean on the vendors to produce a new connector or go back to the old zip and ship model, which nobody wants, or conversely, you were doing a zip and ship in the old version, but the new version has a connector, which is gonna give you a huge amount of efficiency. 

BS: Mm-hmm.

SO: The connectors tend to be expensive and also they add a lot of value, right? Because if you can automate those systems, those transfer systems, then that’s going to eliminate a lot of manual overhead, which is of course why we’re here. 

BS: Mm hmm. Human error as well.

SO: So they’re worth looking at, you know, pretty carefully to see what that connector, as you said, Bill, you know, what’s out there, what already exists. Does the new platform have the connectors I need? And if not, who do I lean on to make that happen so that I don’t go backwards, essentially, in my processes? Okay, anything else or should we leave it there?

BS: I think this might be a good place to leave it. We could talk for hours on this.

SO: Be good place to leave it. Let’s not and say we did. OK, so with that, thank you for listening to the Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Cutting technical debt with replatforming (podcast) appeared first on Scriptorium.

In many cases, you can get away with the easy button, the quick-and-dirty approach when you have a relatively smaller volume of content. Then as you expand, bad, bad things happen, right? It just balloons to a point where you can’t keep up.

— Sarah O’Keefe

Related links:

• Technical debt in content operations
• AI in the content lifecycle (white paper)
• Collaborate with a content strategist to transform content operations
• Accelerate global growth with a content localization strategy

LinkedIn:

• Sarah O’Keefe
• Alan Pringle

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Alan Pringle: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about technical debt and content operations. What is technical debt and can you avoid it? Hey everybody, I am Alan Pringle and I’ve got Sarah O’Keefe here today.

Sarah O’Keefe: Hey everybody.

AP: And we want to talk about technical debt, especially in the context of content operations. And to start off, we should probably have you define what technical debt is, Sarah. I think this is something most people run into during their careers, but they may not have had a label to apply to what they were dealing with. So what is technical debt?

SO: We usually hear about technical debt in the context of software projects. And it is something along the lines of taking the quick-and-dirty solution, which then causes long-term effects, causes long-term costs. So Wikipedia says it’s the implied cost of future reworking because a solution prioritizes expedience over long-term design. And that’s really it. You know, I have this thing, I need to deliver it this week. I’m going to get it done as fast as possible. But then later, I’m going to run into all these problems because I took the easy road instead of the sustainable

AP: So it’s basically when the easy button bites you in the backside weeks, months, years later.

SO: Yeah, and with any luck you are aware that you’re incurring technical debt. The one that’s really painful is when you don’t realize you’re doing it.

AP: Right, or you didn’t know you weren’t part of the process when it happened. And I think this is kind of moving into where I want to go next. Let’s talk about some examples, especially in the context of content of where you can incur or stumble upon technical debt.

SO: So right now, the example that we hear actually most often is that any inconsistencies and problems in the quality of your content, the organization of your content, and the structure of your content lead to a large learning model or AI misinterpreting information and therefore your generative AI strategy fails. So essentially, because the content isn’t good enough, genAI you know, tries to see patterns where there are none and then produces some stuff that’s just complete and utter junk. Now, the interesting thing about this is that probably you are aware, at least at a high level, that your content wasn’t perfect. But the LLM highlights that it’s like, it’s like a technical debt detector. It will show that, look at you, you took a shortcut and it didn’t work or you didn’t fix this and it didn’t. And so here we are. Another good example of this is any sort of manual formatting that you’re doing. So you’re producing a bunch of content, a bunch of docs, a bunch of HTML pages, PDF, whatever. And in the context of that, you’ve got some step in there that involves cleaning it up by hand. So I get it sort of 90—95% is I just apply the template and it all just works. But then I’ve got this last step where I’m doing a couple of little finicky cleanup things and that’s okay because it’s just an hour or two and all I’m delivering is English. Okay, well along comes localization and suddenly you’re delivering in not just one language but two or three or a dozen or 27 and what looked like one hour in English is now 28 hours, you know, once time for English and 27 times again where you’re having to do this cleanup. And so all of a sudden your technical debt balloons into something that’s basically unsustainable because that choice that you made to not automate that last 5% suddenly becomes a problem.

AP: It’s a scalability issue, really, at the core.

SO: Yeah, in many cases, you can get away with the sort of, as you said, the easy button, the quick-and-dirty approach when you have a relatively smaller volume of content. And then as you expand, bad, bad things happen, right? It just balloons to a point where you can’t keep up.

AP: Yeah, and I have recently run into some technical debt, not in the content world, but in the homeownership world. And I’m sure this painful story will resonate with many people and not in a good way. But how many times have you gone to update a kitchen, update a bathroom, only to discover that there was some weird stuff done with the wiring? The plumbing is not like it really should have been. And basically you want to jump into a time machine, go back to when your house was built to have either a gently corrective conversation with the people who are building your house or just murder them outright because you are now having to pay to untangle the mess that was made 30, 40, 50 years ago. I am there right now and it is not a happy place.

SO: And it would have been, whatever it was they did was presumably cheaper than doing it right. But what they actually paid to do it the cheap way, plus what it would have cost to do it right, you know, would have been an extra 5 % or whatever at the time. But now it’s compounded because you’re having to, you know, in the case of plumbing, you know, tear out walls and go back and replace all these pipes instead. So you have to essentially start over instead of just do it. Another great example of this is accessibility. So when you start thinking about a house that has grab bars or wide doorways that wheelchairs will fit through, right? If the house was built with it, it costs a little bit more, not a lot, but a little. But when you go back to retrofit a house with that stuff, it is stupidly expensive.

AP: Exactly. And really, these things that we’re talking about in the physical world very much apply when you’re talking about software infrastructure, tool infrastructure as it can be bad.

SO: Yeah, I mean, there’s a perception of it’s just software, right? We’re not doing a physical build. We’re not using two by fours. So how bad could it be? It can be real bad. But that is the perception, right? That we’re not building a physical object so we can always go back and fix it. And I mean, you can always go back and fix everything. It’s just how much is it going to cost?

AP: Right, how much time and money and effort is it going to suck up to get you to where you need to be so you can then do the next thing that you intended to actually do in the first place? So yeah, I think this is something where this technical debt, sometimes there is no way around it. You inherit a project, you’ve got some older processes in place and you’re gonna have to deal with it. Are there some strategies that people can rely on to kind of mitigate and make it less painful? 

SO: Well, first I’ll say that not all technical debt is bad or destructive in a way. And the canonical example of this is if you’re trying to figure out is this thing gonna work, I wanna do a proof of concept, I don’t wanna see if the strategy that I’m considering is even feasible. So you go in and you take a small amount of content and you build out a proof of concept or a prototype, proof of concept like, look, we were able to generate this PDF over here and this HTML over here, and we fed it into the chat bot and everything kind of worked. And you look at it and you say, okay, so that was good enough. And because it was a proof of concept, you maybe didn’t sort of harden it from a design point of view. You just did what was expedient and you got it done. That’s fine, provided that you go into this with your eyes open, knowing where you cut the corners, recognizing that later we’re going to have to do this really well and we probably can’t use the proof of concept as a starting point, or it’s good enough and we can use it as a starting point, but here’s where we cut all the corners. You have this list of like, we didn’t put in translational localization support, we didn’t put all the different output formats we’re going to need, we just put in two to prove that it would more or less work. But I think you made a really good point earlier. So often you inherit these things. So you walk into an organization and you’re brand new to that organization and you get handed a content ops environment. This is how we do things. Great. And then the next thing that happens is that genAI comes along or a new output format comes along or, we’ve decided we want to connect it to this other software system over here that we’ve never thought about before, or, hey, we’re bringing in a new enterprise resource planning system and we need to connect to it, which was never on the requirements day one. And now you realize, looking at your environment, that what’s there won’t, you can’t get from what you have to where you need to be because the requirements shifted underneath you. Or you came in and you just didn’t have a good understanding of how and when these decisions were made because it was five or 10 years ago with your predecessor kind of thing. So. So how do we deal with this? It’s I mean, it just sounds awful, but it’s like you have to manage your debt just like actual debt. 

AP: All right, sure.

SO: Right, so understand what you have and haven’t done. We have not accounted for localization. We’re pretty concerned about that if and when we get to a point where we’re doing localization. Scalability. We are only going to be able to scale to maybe 10 authors and if we end up with 20, we’re going to have a big problem. So let’s just be aware of that when we get to eight or nine. But the thing is you always have technical debt that you identify that you know about this is hopefully unlike personal finance, you always have more debt than you think you have, right? Because in the content world, things change. Or in your housing example, like the building code changes. So they built the thing, umpteen years ago, and it was okay in the sense that it conformed with the requirements of the building code at the time, I assume. 

AP: Of course.

SO: And now you’re going in and you’re making updates and suddenly the new building code is in play and you’re faced with the technical debt that accrued as the building code changed, but your house, your physical infrastructure did not change. And so there’s a gap between where you need to end up and where you are, part of which is just time has elapsed and things have changed.

AP: Right, and that is very true of some of the requirements you mentioned in regard to content operations. Generative AI, that’s what, the past two years, if that, that wasn’t on the horizon five years ago when some decisions were made. it absolutely is very much parallels. And when it comes to personal finance, sometimes things get so bad, you have to declare bankruptcy. And I think that can also apply to technical debt as well.

SO: Yeah, it’s a, you know, it’s an unhappy day when you look at, you know, a two-story house and you’ve been told to build a 50-story skyscraper. It just can’t be done, right? You cannot take a, you know, a sort of a stick-boiled house made of wood and put 50 stories on top of it. At least I don’t think so. We’ve now hit the edges of what I know about construction. So sorry to all the construction people, you build differently if you know that it’s going to be required to be 50 stories. Even if you only build the initial two, so either you build two knowing that eventually you’ll scrape it and start over with a new foundation or you build what amounts to a two-story skyscraper, right, that you can then expand on as you go up. So you overbuild, mean, completely overbuild for two stories knowing you’re going forward.

AP: Scalability.

SO: But yeah, we have a lot, a lot of clients who come in and say, you know, we’re in unstructured content, know, word unstructured frame maker, InDesign, basically a PDF-only workflow. And now we need a website or we need all of our content in like a content as a service API kind of scenario. And they just can’t get there from a document page-based, print-based, PDF-targeted workflow, you can’t get to, and also I wanna load it into an app in nifty ways. I mean, you could load the PDF in, but let’s not. So you end up having to say, this isn’t gonna work. This is the, I have a two-story suburban house and I’ve been told to build a 50-story skyscraper. Languages, localization are really, really common causes of this. So separately from the, “I need website, in addition to PDF,” the, “We’re only going to one or two languages, but now we’re going to 30 because we’re going into the European Union,” is a really, really common scenario where suddenly your technical debt is just daunting.

AP: So basically you’re in a burn it all down situation. Just stop and start all over again.

SO: Yeah, I mean, your requirements, it’s not that you did it wrong. It’s that your requirements changed and evolved and your current tools can’t do it. So it’s a burning platform problem, right? The platform I’m on isn’t isn’t going to work anymore. And so I have to get to that other place. It’s really unpleasant. Nobody likes landing there because now you have to make big changes. And so I think ideally, what you want to do is evolve over time, evolve slowly, keep adding, keep improving, keep refactoring as you go so that you’re not faced with this just crushing task one day. But with that said, most of the time, at least the people we hear from have gotten to the crushing horror part of the world because it’s good enough. It’s good enough. It’s not great. We have some workarounds. We do our thing until one day it’s not good enough.

AP: And it’s very easy to get used to those workarounds. That is just part of my job. I will deal with it. You kind of get a thick skin and just kind of accept that’s the way that it is. While you’re doing that, however, that technical debt in the background, it’s accruing interest, it’s creeping up on you, but you may not really be that aware of. 

SO: Right. Yeah, I’ve heard this called the missing stair problem. So it’s a metaphor for the scenario where, again, in your house or in your life, there’s a staircase and there’s a stair missing and you just get used to it, right? You just climb the steps and you hop over the missing stair and you keep going. But you bring a guest to your house and they keep tripping on the stairs because they’re not used to it, at which point they say, what is the deal with the step? And you’re like, yeah, well, you just have to jump over stair three because it’s not there or it’s got a, you know, missing whatever. So missing stair is this idea that you can get, you can get used to nearly anything and the workaround just becomes, “Get used to jumping.”

AP: And it ties into again, there’s technical debt there, but you have kind of almost put a bandaid on it. You’re ignoring it. You’ve just gotten used to it. Yeah, you do. So really, there’s no way to prevent this? Is it preventable?

SO: I mean, if you staffed up your content ops organization to something like 130% of what you need for day-to-day ops and dedicated the extra 30 or maybe 10%, but you know the extra percentage to keeping things up to date and constantly cleaning up and updating and refactoring and looking at new and yeah so no there’s no way to do it and everybody is running so lean.

AP: I’m gonna translate that to a no. That is a long no. So yeah.

SO: And as a result, you make decisions and you make trade-offs and that’s just kind of how it is. I think that it’s important to understand the debt that you’re incurring, to understand what you’re getting yourself into. And, you know, I don’t want to, you know, beat this financial metaphor to death, but like, did you take out like a reasonable loan or are you with the loan sharks? Like how bad is this and how bad is the interest going to be?

AP: Yeah, so there’s a lot to ponder here and I’m sure a lot of people are listening to this and thinking, I have technical debt and I’ve never even thought about it that way. it is a topic that is unpleasant, but it is something that needs to be discussed, especially if you’re a person coming into an organization and inheriting something you may not have had any say in the decisions that were made 10 years ago, five years ago, and things have changed so much that might be why they’ve brought you in. So it is something that you’re gonna have to untangle.

SO: Yeah, sounds about right. So good luck with that. Call us if you need help, but sorry.

AP: Yeah, so if you do need help digging out of the pit of technical debt, you know where to find us. And with that, I’m going to wrap up. Thank you, Sarah. And thank you for listening to the Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

SO: Thank you.

The post Renovation revelations: Managing technical debt (podcast) appeared first on Scriptorium.

Localization is generally a key business driver. Are you positioning your products, services, what have you for one market, one language, and that’s all? Are you looking at diversifying that? Are you looking to expand into foreign markets? Are you looking to hit multilingual people in the same market? All of those factors. Ideally as a company, you’re looking at this from the beginning as part of your business strategy.

— Bill Swallow

Related links:

• Strategien für KI in der technischen Dokumentation, (original German version)
• Strategies for AI in technical documentation (English version with synthetic audio)
• Lost in translation? Create scalable content localization processes
• What does it all mean?! Foundations of an enterprise content strategy
• AI in the content lifecycle (white paper)

LinkedIn:

• Bill Swallow
• Christine Cuellar

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Christine Cuellar: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we are talking about content localization strategy. So maybe you’re starting to think about introducing a localization strategy. Maybe you’re hitting some pain points in your localization processes, all that good stuff we’re going to be talking about today. Hi, I’m Christine Cuellar.

Bill Swallow: And I’m Bill Swallow.

CC: Bill, thanks for being here today to talk about localization. Bill is our go-to localization expert, and localization has been coming up a lot. So I noticed for me, on the marketing side of things, there’s been a lot of, you know, SEO stuff coming up for localization. People seem to be searching about it, asking questions at a more beginning to thinking about the whole localization process level. So that’s what we wanted to talk about today. Give you the chance to have some upfront knowledge about what you could be getting into with introducing localization in your content strategy. And yeah, let’s talk about it with an expert. So thanks, Bill.

BS: Thank you.

CC: First things first, the most basic question, what is content localization strategy? So what do we mean by that?

BS: Okay, so I can kind of frame this in, I guess the same point of view as a content strategy, but basically you’re taking a look at your entire localization process from start to finish. Plus you’re looking at what are the systems that are involved? How are authors prepping the content for localization? Are they writing well upfront? What does the publishing preparation look like? How are you choosing your translators? Are you going to pure machine translation? Are you using live people to do the translation? Are you using people who are content experts? Are you using people who are market experts? So there are a lot of different factors there that all kind of get balled up into this grander strategy of how are you going to approach getting your content authored and translated appropriately in other regional markets.

CC: Yeah, okay. That makes sense. And taking a step back even further, can you walk me through the difference between localization and localization strategy?

BS: Sure. Localization itself is kind of more of an action, and whereas strategy is more planning around that action, I think that’s the best way to put it. So localization involves a bunch of different things. It involves the act of internationalization. So that’s prepping your content, your code, your product, whatever it is to be delivered for multiple regional and language markets. And then you have the translation component of localization, which is actually getting things written, spoken however, in other languages. And the strategy piece is more bridging both of those and adding additional components so that you have a solid plan for every step in that process.

CC: Okay, yeah, that makes sense. And where do we step in? We here at Scriptorium, where do we sit?

BS: Generally we at Scriptorium, we sit on the source content authoring side. And we look at the overall content strategy, and we do look at a localization strategy as a component of that. They’re not separate. They’re very intertwined and we need to take a look at really both of them. So a lot of our clients do come to us because they have localization requirements.

And we have to account for those in the content strategy that we build for them. So we’re looking not only at the source content authoring process and what needs to happen in that to get the job done, but we also have to look at where are they going with their content, how are they going to localize it, what do they need to localize, what processes do they have in place now? Are they working? Are they not looking at systems? Are they adequate? Are they not? And look at the markets. Are they already reaching those markets? Do they need to do something different? How do we need to position the content as it moves through that funnel of production so that when it comes out the other side, it is ready for those markets. So they’re kind of intertwined there.

CC: Okay. Yeah. So when are organizations typically thinking about a content localization strategy?

BS: Well, localization generally it’s a key business driver. Are you positioning your content for one market, one language, and that’s all? Or are you positioning… I shouldn’t say just product because product services, what have you. Are you looking at diversifying that? Are you looking to expand into foreign markets? Are you looking to hit multilingual people in the same market? All of those factors. So ideally as a company, you’re looking at this from the beginning as part of your business strategy. And what are you doing to… What are you producing? Who are you producing it for? How do they need to consume it? So as soon as you catch a whiff of those multilingual requirements, bells should be going off saying, “Hey, we need a plan for this.” More commonly, an organization might be producing for one market or producing for several markets. They’re kind of doing things ad hoc, producing content, then sending it out to a translator. They’re getting something back, they may be polishing it up or it’s a finished product and then they send it out. It’s a very time-consuming process. It’s a very costly process, and it’s very difficult to kind of juggle when things will be done. Because if you don’t have a set process around things and you don’t have an idea of how long things will take, what efficiencies you’re able to build up front and so forth, you’re throwing caution to the wind and just putting stuff out there and hoping that it comes back in time so that you can go to market with it. We’ve worked with clients who have said that generally it takes about nine months or so to get their localized product out the door and into the market after the English is done. And for a lot of those, we’ve brought that number into three months, one month, depending on exactly what they’re producing and how they need to produce it, so-

CC: Yeah, it’s a huge difference.

BS: Looking at that… Oh, huge difference. And looking at that time to market, that’s perhaps more valuable than the cost that you’re dumping into putting a localization strategy or a content strategy together because you’re able to sell quicker into those markets. You’re not waiting for the opportunity to start seeing revenue come back from the initiatives that you’re taking to get stuff out there.

CC: Yeah. Yeah, that makes sense. And I feel like… So correct me if I’m wrong here, but in the global world that we live in, it feels like localizing products and getting them ready for new regions is a very… I think that would be something that executives think about from the get-go like, yes, of course we want our product ready for new regions and locations. But why is the… It sounds like maybe the content piece of that is not thought about or maybe left behind until it’s an absolute emergency. Would you say that that’s… First of all, is that accurate?

BS: Sadly, I’d say yes.

CC: Okay.

BS: Content is often an afterthought in general, whether we’re talking about producing stuff just in your native language for a native market. Localization is usually even more of an afterthought because it’s like, oh, well, we wrote it in English, we’ll just have someone translate it. And by then you’re waiting until that product is done and then sending it to somebody else who’s looking at it going, “I can’t make sense of this. It’s not written well. And I’m going to take my best guess at how to translate this.” It could take months to get that back.

CC: So maybe organizations see the value in having their products and services available in other markets, but they don’t necessarily think of all of the content localization pieces that are involved in getting that out the door.

BS: No, and it’s similar for pretty much anyone trying to get anything done that you want to do something. But for example, I really want to put a new patio in the back of my house. I know exactly… I even have an idea of exactly how that should go in. I don’t have the time. I don’t have the materials needed to do it. And I’d much rely on somebody else who knows what they’re doing to put it in the correct way so it’s not graded improperly, so that there aren’t uneven portions that people will trip over and so forth. So looking at it that way, the same thing with localization. People who are running a company or starting a company, they may have an idea that yes, they need to get from point A to point B to point C to point D. They don’t know those steps along that path, and they need some help figuring out, okay, it’s not that you just write your English content, you throw it over to somebody else and they send it back. It’s a more intricate process. You have some systems in place that we’ll manage that handoff that will allow people to gate the content and proof it and make sure it’s correct before it goes anywhere. And you may have some other efficiencies built in that allow you to automatically format things when the time comes to actually produce. So there are a lot of bits and pieces that people just generally don’t think about because it’s not in their wheelhouse.

CC: Yeah, they can’t know what they don’t know.

BS: Exactly.

CC: Okay. So it sounds like most organizations realize that this is a problem once they’re actually trying to get their product out the door and into a new market, into a new region. What are some obstacles to getting a content localization strategy set up? I’m sure that one issue is probably like, oh, you’re in emergency mode and we just need to get this product out the door. That might present a challenge in and of itself.

BS: Absolutely.

CC: Yeah. Are there other obstacles as well to getting a more future-focused strategy in place?

BS: Oh, that one is a good one. That is the first hurdle to get over.

CC: Is the emergency mode.

BS: So being able to recognize or realize that you’re in emergency mode and getting out of that mindset and saying, okay, it’s not just that this will be a forever problem of just waiting and hoping for good quality coming out in the end. Once you’re able to realize that you need to break that mindset and start looking forward, then we start hitting other obstacles. One of them is going to be funding because there will be systems involved, there will be personnel required, there will be processes that need to change and so forth. And that will certainly cost a lot upfront. You’re going to basically see that return on investment in a pretty quick amount of time. We’ve seen one company make their investment back within a year, but they were producing an insane amount of languages already, and they just needed to tidy up their process. And again, by bringing that window in from nine months to about a month and a half or so, to be able to get their localized stuff out, they were able to quickly realize that return on investment there. But another one is buy-in, because you have a lot of people who are busy doing their job and you’re suddenly telling them that they need to change how they do their job, and it might be abandoning the tools that they like to use. Writing in a different way, looking at publishing in a different way and interacting with people who they normally don’t interact with on a day-to-day basis. So your source author’s interacting with a localization manager internally who needs to send stuff out to translators or your writer’s interacting with translators to explain what they had written so that the translator has a definitive idea of what it is and how to translate it for the market that they’re translating for. And then of course, you have the obstacle of governance and change management comes along with that. You need to be able to make sure that any of the changes that you introduce, that people are following the new way of doing things and aren’t falling back to old bad habits or even old good habits at the time. And you need to make sure that you have these gating processes so that once something is written in English, you have a formal review on that to make sure it’s correct, to make sure it’s written appropriately. That goes out to translation. They have their own gating process of making sure they receive all the files, that they understand the content that they have, all the supporting information that they need to help them translate and localize this information for that market. Then of course, they do their own quality checks. It comes back, you make sure that there’s a final review on the company side to make sure the translation seems good. And then you’re able to publish and deliver. So it still sounds like a lot of gating factors, but once you kind of get things going and figuring out where you can expedite and make things a lot easier, you start to bring in that entire timeline.

CC: Yeah, that makes sense. You mentioned buy-in, and so I could see how if people feel like their workload’s being increased by suddenly needing to talk to more people, coordinate between more departments or even just have more things on their radar, I could see how that could create a lot of, oh, I don’t know if I want to go in this direction. What are some ways… And that’s probably one of the… As you mentioned, that’s just one of a few buy-in challenges. What are some of the ways that you maybe win people over or show people how this can benefit their work life versus just make it harder?

BS: That’s a good question. I think that authors in general to understand where their content is going and who is consuming it. And even though it’s… We’re talking about corporate content, we’re talking about everything from website content to product manuals to troubleshooting tips and all that stuff and training materials. So it’s not really… Even though it belongs to the company, a lot of authors tend to have a kind of, I guess, personal pride built around what they write.

CC: Yeah, okay. Yeah, that makes sense.

BS: So knowing who is consuming it down the road and the reason why you have these additional checkpoints and processes in place will kind of help, I think get a lot of them around the idea of, yeah, this is a good thing and I’m looking forward to helping any way I can. Because the last thing they want is to have something written completely correctly in English and have it go out to, I guess let’s say a market in Denmark. And the content was translated incorrectly because the translator maybe didn’t understand what something meant, and they gave it a different term, which had a different meaning in that market.

CC: Yeah. And I could also see from a safety standpoint, that could be really dangerous too, if you’re not properly translating instructions for high stakes content, medical devices, stuff like that. Just like you do in English, you want that content to be accurate and understandable. Because if it’s not accurate, of course it’s wrong and people could get hurt also if people don’t understand it, even if it’s totally accurate. But it’s just hard to understand. That presents, I’m sure, a lot of dangerous situations where your people could get hurt and your company is liable. So yeah, it makes sense that you would really want to have a good process in place.

BS: Oh, absolutely. And even more along those lines, the regulations that we have to adhere to here in the US are somewhat different to… Very different to anywhere else in the world. There are different directives in place depending on where you are regionally, things that have to be included that have to be said a very specific way. So I guess the easiest way to look at it is that there are more legal ramifications in the US. So you could get sued if something is wrong, whereas opposed to if you go over to the UK, it’s generally more that there’s a directive you have to follow and you simply cannot release in that market if your, for example, machinery content does not meet that specific directive’s requirements. So there’s a slightly different approach. So it might be… There’s still a legal ramification if things go wrong, but there’s also another set of requirements that need to be met before you even start worrying about the legal stuff.

CC: And are most organizations aware of those kind of requirements when they start trying to get into a new market?

BS: Some of them might be, but again, if you’re in one particular region, chances are that’s the region you’ve grown up with and that’s the region you understand. And there’s been very little attention paid to what are their requirements in other geographic regions, other countries and so forth. So I can’t say is it common, is it not common? But in general, you know what? And when you’re looking to move to a foreign market, there’s the foreign context. You’re going to have very little insight into what that foreign market demands by its very nature. As a company moves into a new language market, new geographic market, they’re going to learn things as they go, and they’re going to bring that knowledge back and refine how things are being done currently so that it also satisfies that new requirement. And it’s going to be an iterative process until they really get their arms around it. And again, going back to a localization strategy for your content, you can kind of start putting those feelers out. Because if one market has one set of requirements, it’s like, wait a minute, now we want to go to three. What are the requirements for the other two before we even start thinking in that direction? So you’re able to start building upon that strategy that you’re developing. I mean, we’re not experts in all the requirements for every single market on the face of the earth. I can say that outright, but we can help companies start to identify what they need to start looking into before they start running.

CC: So since we mentioned one of the reasons this topic came about was seeing some SEO search trends, people trying to get more information on localization. What other trends are you seeing in localization right now?

BS: I think the big one is still going to be machine translation. It’s continually evolving and it’s getting smarter, still not, I would say, better than a human. It’s certainly quicker, but we’re getting there. And a lot of that… We talk about AI a lot. And obligatory nod to AI for this podcast, but when we talk about AI, and I think I mentioned this on another podcast already, that when you look at machine translation, that was really like AI Alpha or AI Beta where it was already using an algorithm to start putting together translations for written text. So with AI in the mix now, we’re getting a lot more, I guess, interesting results, a lot more targeted results with machine translation. I still don’t think it’s a perfect solution, and we’ll certainly need some proofreading, but it’s come a long way. And I think that that trend is certainly not going to fall off the radar anytime soon. In fact, recently Sarah O’Keefe had a podcast with Sebastian Göttel about strategies for AI and technical documentation, and they actually recorded that podcast in German. And they used AI to translate and voice augment into English. So not only were things machine translated from German into English, but the German speaking was then synthetically reproduced in English, which just is really cool.

CC: Yeah, it’s super cool to listen to, and we’ll link those in the show notes as well. There’s two versions, the German version and the English version. But yeah, you’re right. It was a super cool process, but you had mentioned earlier there was a human piece to it that was still needed because when it was originally recorded in German, then we got the German transcript, translated that into English. And when we translated that, at first it was Google Translate just to get it all done, but then Sarah needed to go and check it because she speaks both English and German. And we needed that human element to make sure that the translation was correct. Because like you were saying, you can’t just necessarily put it into a machine and cool, yay, it’s done. We need the human to make sure that it was actually translated properly and the things make sense. And we did notice once Sebastian’s synthetic audio was created in English, a lot of the prompts or the questions just were different lengths. The English version sometimes was shorter or sometimes longer of just the exact same question. It’s just the languages are different. So it’s really cool. It was a really cool experiment and does open up some interesting possibilities, would you say, for localization. And we’ve never been able to have a German and English podcast before, so that’s kind of cool.

BS: Yeah, no, it was very cool. I sat in the back of the room just watching the entire process, but it was definitely something I was quite interested in seeing. Yeah, there was a lot of editing of the English translation because again, it was pure machine translation and it needed some help. But once that was done, the synthetic audio really came right together, and I was impressed in how that happened.

CC: Yeah. And it’s so interesting because it’s definitely… It sounds like Sebastian, but then also it sounds not quite human, but it’s really close. It’s really interesting. But it did-

BS: Very uncanny valley.

CC: Yeah, it was, and I only speak English. I don’t speak German, so it made that podcast accessible to me. I was able to listen to it, and it does present some interesting opportunities, but as always with AI, the human element was definitely needed. It was very important to make sure that the humans at the other end of the screen could eventually consume it.

BS: Oh, yeah.

CC: Awesome. Well, bill, thank you so much. We covered a lot of ground today, and we really appreciate it. This was really helpful, and yeah, thanks for being on the show.

BS: Yeah, thanks.

CC: And thank you for listening to the Content Strategy Experts podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Accelerate global growth with a content localization strategy appeared first on Scriptorium.

Sarah O’Keefe: So what does AI have to do with poems?

Sebastian Göttel: You often have the impression that AI creates knowledge; that is, creates information out of nothing. And the question is, is that really the case? I think it is quite normal for German scholars to not only look at the text at hand, but also to read between the lines and allow the cultural subtext to flow. From the perspective of scholars of German literature, generative AI actually only interprets or reconstructs information that already exists. Maybe it’s hidden, only implicitly hinted at. But this then becomes visible through the AI.

How this podcast was produced:

This podcast was originally recorded in German by Sarah and Sebastian, then Sarah edited the audio. Sebastian used Whisper, Open AI’s speech-to-text tool to transcribe the German recording, followed by necessary revisions. The revised German transcript was machine translated into English via Google Translate and then we cleaned up the English transcription.

Sebastian used ElevenLabs to generate a synthetic audio track from the English transcript. Sarah re-recorded her responses in English and then we combined the two recordings to produce the composite English podcast.

Related links:

• Strategien für KI in der technischen Dokumentation, (original German version)
• Scriptorium: AI in the content lifecycle (white paper)
• Quanos
• Quanos: AI-based meta data assignment in ST4 
• Quanos: An example of a real English talk of Sebastian

LinkedIn:

• Sebastian Göttel
• Sarah O’Keefe

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Today’s episode is available in English and German. Since our guest works with AI in German-speaking countries, we had the idea to create this podcast in German. The English version was then put together with AI support, particularly synthetic audio. So welcome to the Content Strategy Experts Podcast, today offered for the first time in German and English. Our topic today is Information compression instead of knowledge creation: Strategies for AI in technical documentation. In the German version, we tried to put it all together in one nice long word, but it didn’t quite work. Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about best practices for AI and tech comm with our guest Sebastian Göttel of Quanos. Hello everyone, my name is Sarah O’Keefe. I am the CEO here at Scriptorium. My guest is Sebastian Göttel. Sebastian Göttel has been working in the area of ​​XML and editorial CCMS systems in technical documentation for over 25 years. He originally studied computer science with a focus on AI. Currently, he is Product Manager for Schema ST4 at Quanos, one of the most used editorial systems in machinery and industrial engineering in the German-speaking regions. He is also active in Tekom and, among other things, contributed to version 1 of the iiRDS standard. Sebastian lives with his wife and daughter, three cats, and two mice just outside Nuremberg. Sebastian, welcome. I look forward to our discussion. In English, we say create once, publish everywhere. This is about recording once and outputting multiple times. So, off we go. Sebastian, our topic today is, as I said, information consolidation instead of knowledge creation and how this strategy could be used for AI in technical documentation. So please, explain.

Sebastian Göttel: Yes, first of all thank you for inviting me to the podcast. It’s not that easy to impress a 14-year-old daughter. And I thought, with this podcast I have a chance. So I told her that I would be talking about AI on an American podcast soon. And the reaction was a little different than I expected. Youuuuu will you speak English? You can put quite a lot of meaning into a single “uuuu” like that. And that’s why I’m glad that I can speak German here. But, and this is now the transition to the topic, what will the AI ​​make of the “You will speak English”? How does it want to pronounce that correctly in text-to-speech or translate it into another language? And that’s what I think our conversation will be about today. If we want to understand how AI understands us, but also how we can use it in technical documentation, then we have to talk about information compression, but also invisible information. “You will speak English?” Can the AI conceptualize that my daughter doesn’t trust me to do this or simply finds my German accent in English gross? Well, if the AI ​​can understand that, then it is new information or actually information that was already there and that both father and daughter were actually aware of during the conversation. I find it quite exciting that German scholars have often dealt with this. Namely, what is in such a text, and what is meant in the text? What’s between the lines? And when you think back to your school days, these interpretations of poems immediately come to mind.

SO: So poems. And what does AI have to do with poems?

SG: Yes, well, you often have the impression that AI creates knowledge; that is, creates information out of nothing. And the question is, is that really the case? I think it is quite normal for German scholars to not only look at the text at hand, but also to read between the lines and allow the cultural subtext to flow. And from the perspective of scholars of German literature, generative AI actually only interprets or reconstructs information that already exists. Maybe it’s hidden, only implicitly hinted at. But this then becomes visible through the AI. Wow, I never thought I would refer to German literature scholarship in a technical podcast.

SO: Yes, and me neither. But the question remains, how does AI work and why does it work? And then why do these problems exist? What is our understanding of the situation today?

SG: Well, I think we’re still pretty impressed by generative AI, and we’re still trying to understand what we’re actually perceiving and what’s happening there. There are things that just make our jaws drop. And then there are those epic fails again, like this recent representation of World War II German soldiers by Gemini, Google’s generative AI. According to our current understanding, the soldiers were politically correct. And there were, among other things, Asian-looking women with steel helmets. I always like to compare this with the beginnings of navigation systems. There were always these anecdotes in the newspaper about someone driving into the river because their navigation system mistook the ferry line for a bridge. It was relatively easy to fix such an error in the navigation system. It was clear why the navigation system made the mistake. Unfortunately, with generative AI it’s not that easy. We don’t know, actually, we haven’t even really understood how these partially intelligent achievements come about. But the epic fails make us aware that it’s not an algorithm, but a phenomenon that seems to emerge if you pack many billions of text fragments into a matrix.

SO: And what do you mean here by “emerge”?

SG: That is a term from natural science. I once compared it to water molecules. A single water molecule isn’t particularly spectacular, but if, for example, you’re sailing in a storm on the Atlantic or hitting an iceberg, you get a different perspective. Because if you put many water molecules together, completely new behavior emerges. And it took physics and chemistry many centuries to partially unravel this. And I think we will, maybe not for quite as long, but we will have to do a lot more research into generative AI in order to understand a little more about what exactly is happening. And I think the epic fails should make us aware that we would currently do well not to blindly place our fate in the hands of a Large Language Model. I think the human-in-the-loop approach, where the AI ​​makes a suggestion and then a human looks at it again, remains the best mode for the time being. The translation industry, which feels like it is a few years ahead of the world when it comes to generative AI or neural networks, has recognized this quite cleverly and implemented it profitably.

SO: And if translation is the model, what does this mean for generative AI and technical documentation?

SG: That’s a good question. Let’s take a step back. So at the beginning of my working life, there was a revolution in technical documentation, these were structured documents; SGML and XML. This has been known for several decades now, and it is still not used in every editorial team. And that means we now have these structured documents and the other thing, which are the nasty unstructured documents. I always thought that was a bit of a misnomer because unstructured documents are actually structured. Well, at least most of the time. There’s a macro level where I have a table of contents, a title page, and an index. There are chapters. Then there are paragraphs, lists, and tables and that goes down to the sentence level. I have lists, prompts, and so on. It’s not for nothing that some linguists call this text structure. And if I now approach XML, the beauty of XML is that I can now suddenly make this implicit structure explicit. And the computer can then calculate with our texts. Because if we’re being honest, in the end, XML is not for us, but for the machine.

SO: Is it possible then that AI ​​can discover structures that, for us humans, have so far only been expressed through XML?

SG: Yes. Well, I recently looked into Invisible XML. There you can overlay patterns onto unstructured text and they become visible as XML. Very clever. I think generative AI is a kind of Invisible XML on steroids. The rules aren’t as strict as in Invisible XML, but genAI also understands linguistic nuances. I found it very exciting, a customer of ours fed unstructured PDF content into ChatGPT; that is unstructured content from the PDF, in order to then convert it to XML. The AI ​​was surprisingly good at discovering the invisible structure that was hidden in the content and converted XML really well. So that was impressive. When AI now appears to create information out of nothing, I think it is more likely that it makes existing but hidden information visible.

SO: Yes, I think the problem is that this hidden structure, in some documents, it’s there, but in others, there’s what we call “crap on a page” in English. So that’s, there’s no structure. And from one document to another, there is no consistency, so they are completely different. Writer 1 and Writer 2, they write and they never talk. And so if the AI ​​now creates an entire chapter and an outline from a few keywords, how does it work? How does that fit together?

SG: Yes, you’re right. So far we’ve been talking about we take PDF and then XML is added to it. But if I’m put on the spot, I’ll throw in a few keywords and ChatGPT suddenly writes something. But also, I think this idea also applies that this is actually hidden information. It might sound a bit daring at first, but there’s nothing new, nothing completely surprising. Now if I just ask, let’s say ChatGPT, give me an outline for documentation for a piece of machinery. And then something comes out. I think most of our listeners would say the same thing. This is nothing new. This is hidden information contained in the training data, which is easily made visible through the query. Because ultimately, generative AI creates this information from my query and this huge amount of training data. And the answer is chosen so that it fits my query and the training data well. It creates a synthetic layer over the top. And in the end, the result is not net new information, but hopefully, the necessary information delivered in a way that’s easier to process further. Either like the example with PDF, enriched with XML or I maybe now have an outline. And I imagine it’s a bit like a juicer. The juicer doesn’t invent juice, it just extracts it from the oranges.

SO: Making information easier to process sounds almost like a job description for technical writers. And what about other methods? So if we now have metadata or knowledge graphs, what does that look like?

SG: That’s right, in addition to XML, these are also really important. So metadata, knowledge graphs. I find that metadata condenses information into a few data points and the knowledge graphs then create the relationships among these data points. And this is precisely why knowledge graphs, but also metadata, make invisible information visible. Because the connections that were previously implicit can now be understood through the knowledge graphs. And that can be easily combined with generative AI. At the beginning, the knowledge graph experts were a bit nervous, as you could tell at conferences, but now they’re actually pretty happy that they’ve discovered that generative AI plus knowledge graphs is much better than generative AI without knowledge graphs. And of course, that’s great. By the way, this isn’t the only trick where we have something in the technical documentation that helps generative AI get going. If you want to make large knowledge bases searchable with Large Language Models, you can do that today with RAG, or Retrieval Augmented Generation. And this means you can combine your own documents with a pre-trained model like ChatGPT very cost-effectively. If you now combine RAG with a faceted search, as we usually have in the content delivery portals in technical documentation, then the results are much better than with the usual vector search, because in the end it is just a better full-text search. That’s another possibility where structured information that we have can help jump-start AI.

SO: Is it your opinion that structured information will not become obsolete through AI, but will actually become more important?

SG: My impression is that the belief has taken hold that structured information is better for AI. I think we’re all a bit biased, naturally. We have to believe that. These are the fruits of our labor. It’s a bit like apples. The apple from an organic farmer is obviously healthier than the conventional apple from the supermarket. I think this is scientific fact. But in the end, any apple is better than a pack of gummy bears. And that’s what can be so disruptive about AI for us. Because at the end of the day, we are providing information. And if users gets information that is sufficient, that is good enough, why should they go the extra mile to get even better information? I don’t know.

SO: Okay, so I’m really interested in this gummy bear career and I want to hear a little bit more about that. But why is your view on the tech comm team’s role so, let’s say, pessimistic?

SG: I think my focus has gotten a little wider recently. I think I’m not really just looking at technical documentation. When it comes to technical documentation, we are lost without structured data. It will not work. But if we take the bigger picture, at Quanos we not only have an CCMS, but we also create a digital twin for information. I’m in all these working groups as the guy from the tech doc area. And I always have to accept that our particularly well-structured information from tech doc, the one with extra vitamins and secondary nutrients, is actually the exception out there when we look at the data silos that we want to combine in the info twin. When I was young, I believed that we had to convince others to work the way we do in tech docs. That would have been really fantastic. But if we’re honest with ourselves, it just doesn’t work. The advantages that XML provides for technical documentation are too small in the other areas and for individuals to justify a switch. The exceptions prove the rule. As a result, tons of information is out there locked up in these unstructured formats. And it can only be made accessible with AI. That will be the key.

SO: And how do we do that? If XML isn’t the right strategy, what does that look like?

SG: Well, so let’s take an example. So many of our customers build machinery and let’s take a look at the documentation that they supply. There are several dozen PDFs for each order. And of course the editor has a checklist and knows what to look for in this pile of PDFs. The test certificate, the maintenance table, parts lists, and so on. And even though the PDFs are completely “unstructured” as compared to XML files, we humans are able to extract the necessary information. And the exciting thing about it is that anyone can actually do it. So you don’t have to be a specialist in bottling systems or industrial pumps or sorting machines. If you have an idea of ​​what a test certificate, a maintenance table, a parts list is, then you can find it. And here’s the kicker: the AI ​​can do that too.

SO: Ahh. And so in this case are you more concerned with metadata…or something else?

SG: No, you’re right. So this is in fact about metadata and links. I find it fascinating what this does to our language usage. Because we have gotten used to saying that we enrich the content with metadata. But in many cases we have simply made the invisible structure explicit. No information was added. Nothing has become richer, just clearer. But now imagine that your supplier didn’t provide a maintenance table. Then you need to start reading, understand the maintenance instructions, and extract the necessary information. And that’s tedious. Even here, AI ​​can still provide support. But how well depends on the clarity of maintenance procedures. The more specific background knowledge is necessary, the more difficult it becomes for the AI to provide assistance.

SO: What does that look like? Do you have an example or use case where AI doesn’t help at all?

SG: It depends on contextual knowledge. I once received parts of a risk analysis from a customer. And her question was, “Can you use AI to create safety messages?” And I said, “Sure, look at the risk analysis and then look at what the technical writers made of it.” And they were exemplary safety messages. But there was so little content in the risk analysis that with the best intentions in the world you couldn’t do anything with artificial intelligence; that end result was only possible because the technical writers had an incredibly good understanding of the product and also had the industry standards. The information was not hidden in this input, but in the contextual knowledge. And that’s so specialized that it’s of course not available in the Large Language Model.

SO: In this use case, you don’t see any possibility for AI at all?

SG: Well, at least not for a generic Large Language Model. So something like ChatGPT or Claude, they have no chance. There is an opportunity in AI to specialize these models again. You can fine-tune this with context-specific content. But we don’t yet know at the moment whether we normally have enough content. There are some initial experiments. But let’s think back to the water molecules. We need quite a few of them to make an iceberg or even a snowman. Ultimately, you have to ask which supporting materials are needed from which point of view, and fine-tuning is really expensive. So there are costs. It takes a long time. Performance is also an issue. And how practical is this approach? Do we have training data? So, given all these aspects, it is still unclear what the gold standard is for making a generic large language model usable for content work in very specific contexts. We just don’t know today.

SO: Can you already see or predict how generative AI will change or must change technical documentation?

SG: I really think it’s more like looking into my crystal ball. So it’s not that easy to estimate which use cases are promising for the use of AI in technical documentation. As a rule, you have a task where a textual input needs to be transformed into a textual output according to a certain standard. And it used to be garbage in, garbage out. In my opinion, the Large Language Models change this equation permanently. Input that we were previously unable to process automatically due to a lack of information density, we can now enrich it with universal contextual knowledge in such a way that it becomes processable. Missing information cannot be added. We’ve discussed that now. But these unspoken assumptions, in fact, we can pack them in. And that helps us in many places in technical documentation, because one of the ways good technical documentation differs from bad documentation is that fewer assumptions are necessary in order to understand the text or if you want to process it automatically. And that’s why I find condensing information instead of creating knowledge to be a kind of Occam’s Razor. I look at the assignment. If it’s simply a matter of making hidden information visible or putting it into a different form, then this is a good candidate for generative AI. What if it’s more about refining the information by using other sources of information? Then it becomes more difficult. If I now have this information, this other information in a knowledge graph, if it is already broken down there, then I can explicitly enrich the information before handing it over to the Large Language Model. And then it works again. But if the information, for example, the inherent product knowledge, is in the editor’s head, as was the case with my client’s risk analysis, then the Large Language Model simply has no chance. It won’t generate any added value. Then you may have to rethink your approach. Can you divide the task somehow? Maybe there is a part where this knowledge is not necessary, and I have an upstream or downstream process where I can optimize something with AI. And I think that’s the mother lode of opportunities lies. This art of distinguishing what is possible from what is impossible, and this will be more of a kind of engineering art, will be the factor in the coming years that will decide whether generative AI is of use to me or not.

SO: And what do you think? Of use, or not of use?

SG: I think we’ll figure it out. But it will take much longer than we think.

SO: Yes, I think that’s true. And so thank you very much, Sebastian. These are really very interesting perspectives and I’m looking forward to our next discussion, when in two weeks or three months there will be something completely new in AI and we’ll have to talk about it again, yes, what can we do today or what new things are available? So thank you very much and see you soon! 

SG: … soon somewhere on this planet.

SO: Somewhere.

SG: Thank you for the invitation. Take care, Sarah.

SO: Yes, thank you, and many thanks to those listening, especially for the first time in the German-speaking areas. Further information about how we produced this podcast is available at scriptorium.com. Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links. 

The post Strategies for AI in technical documentation (podcast, English version) appeared first on Scriptorium.

Sarah O’Keefe: Was hat die generative KI mit Gedichtinterpretationen zu tun?

Sebastian Göttel: Ja, nun, also oft hat man da ja den Eindruck, dass KI das Wissen schöpft, also Informationen aus dem Nichts erschafft. Und da ist die Frage, ist das denn wirklich so? Denn für die Germanisten ist es, glaube ich, schon eher normal, nicht nur den vorliegenden Text anzuschauen, sondern auch zwischen den Zeilen zu lesen, den kulturellen Subtext einfließen zu lassen. Und aus dem Blickwinkel der Germanisten, interpretiert oder rekonstruiert generative KI eigentlich nur Informationen, die schon vorhanden ist. Möglicherweise ist die verborgen, nur implizit angedeutet. Aber die wird durch die KI dann sichtbar.

Related links:

• Strategies for AI in technical documentation (Englische KI-Version)
• Scriptorium: AI in the content lifecycle (white paper)
• Quanos
• Quanos: „Die Doku-Lounge“ (podcast)
• Quanos: “ChatGPT – Evolution für die Technische Doku?“ (talk)
• Quanos: „Zwischen Verstand und Verschlusssache – KI im Spannungsfeld von MI5 und ST4“ (talk)
• Quanos: KI-basierte Metadatenvergabe in ST4

LinkedIn:

• Sebastian Göttel
• Sarah O’Keefe

Transcript:

Sarah O’Keefe: Die heutige Episode ist auf Englisch und Deutsch verfügbar. Da unser Gast sich im deutschsprachigen Raum mit KI beschäftigt, kam die Idee, diesen Podcast auf Deutsch zu erstellen. Die englische Version wurde dann mit KI-Unterstützung zusammengebastelt. Also herzlich willkommen zum Content Strategy Experts Podcast, heute zum ersten Mal auf Deutsch. Unser Thema ist heute Informationsverdichtung statt Wissensschöpfung. Strategien für KI in der technischen Dokumentation. Wir haben versucht, das alles in ein Wort zusammenzubringen, das hat aber nicht ganz geklappt. Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize and distribute content in an efficient way. In this episode, we talk about best practices for AI and TechCom with our guest Sebastian Göttel of Quanos. Hallo, ich heiße Sarah O’Keefe. Ich bin hier bei Scriptorium die Geschäftsführerin. Mein Gast ist Sebastian Göttel. Sebastian Göttel arbeitet seit über 25 Jahren im Bereich XML und Redaktionssysteme in der technischen Dokumentation. Ursprünglich hat er mal Informatik mit Schwerpunkt KI studiert. Aktuell ist er bei Quanos Product Manager für Schema ST4, einem der meistgenutzten Redaktionssysteme im Maschinen- und Anlagenbau in DACH. Er ist auch in der Tekom aktiv und hat unter anderem an der Version 1 des iiRDS-Standards mitgewirkt. Sebastian lebt mit Frau und Tochter, drei Katzen und zwei Mäusen vor den Toren von Nürnberg. Sebastian, herzlich willkommen. Ich freue mich auf diesen Austausch. Auf Englisch sagen wir ja create once, publish everywhere. Hier geht es um einmal aufnehmen und mehrfach ausgeben. Also, los geht’s. Sebastian, unser Thema ist heute, wie gesagt, die Informationsverdichtung anstatt von Wissensschöpfung. Und wie diese Strategie für KI in der technischen Dokumentation eingesetzt werden könnte. Also, bitte, erklär doch mal.

Sebastian Göttel: Ja, erstmal vielen Dank für die Einladung in den Podcast. Es ist ja gar nicht so einfach, eine 14-jährige Tochter zu beeindrucken. Und ich dachte mir, mit diesem Podcast habe ich eine Chance. Also habe ich ihr erzählt, dass ich demnächst in einem amerikanischen Podcast über KI sprechen werde. Und die Reaktion war ein bisschen anders, als ich mir das erwartet habe. Duuu wirst da Englisch sprechen? Man kann schon ziemlich viel Bedeutung in so ein einzelnes Duuu legen. Und von daher bin ich zum einen froh, dass ich hier Deutsch sprechen darf. Aber, und das ist jetzt die Überleitung zum Thema, was wird die KI aus dem “Duuu wirst da Englisch sprechen” machen? Wie will sie das beim Text-to-Speech korrekt aussprechen oder in eine andere Sprache übertragen? Und darum, glaube ich, wird es in unserem Gespräch heute gehen. Wenn wir verstehen wollen, wie KI uns versteht, aber auch wie wir sie in der technischen Dokumentation einsetzen können, dann müssen wir über Informationsverdichtung, aber auch unsichtbare Informationen sprechen. Duuu wirst da Englisch sprechen. Kann die KI rekonstruieren, dass meine Tochter mir das nicht zutraut beziehungsweise meinen deutschen Akzent im Englischen einfach grottig findet? Naja, also wenn die KI das rekonstruieren kann, ist es dann neue Information oder eigentlich eher Information, die schon da, war und die eigentlich im Gespräch sowohl Vater als auch Tochter bewusst war. Ich finde das ziemlich spannend, dass die Germanisten sich damit schon ganz häufig beschäftigt haben. Nämlich, was steht in so einem Text drin und was ist in dem Text gemeint? Was steht zwischen den Zeilen? Und wenn man so an seine Schulzeit zurückdenkt, dann fallen einem ja sofort diese Gedichtinterpretationen ein.

SO: Also Gedichte und was hat die generative KI mit Gedichtinterpretationen zu tun?

SG: Ja, nun, also oft hat man da ja den Eindruck, dass KI das Wissen schöpft, also Informationen aus dem Nichts erschafft. Und da ist die Frage, ist das denn wirklich so?

Denn für die Germanisten ist es, glaube ich, schon eher normal, nicht nur den vorliegenden Text anzuschauen, sondern auch zwischen den Zeilen zu lesen, den kulturellen Subtext einfließen zu lassen. Und aus dem Blickwinkel der Germanisten, interpretiert oder rekonstruiert generative KI eigentlich nur Informationen, die schon vorhanden ist. Möglicherweise ist die verborgen, nur implizit angedeutet. Aber die wird durch die KI dann sichtbar. Ui, hätte nie gedacht, dass ich mal in einem technischen Podcast mich auf Germanisten berufe.

SO: Ja, und ich auch nicht. Da bleibt aber doch die Frage, wie funktioniert das? Also wie funktioniert die KI und warum funktioniert das? Und wieso gibt es dann diese Probleme? Was ist denn heute unser Verständnis von der Lage?

SG: Also ich glaube, wir sind immer noch ziemlich beeindruckt von der generativen KI und wir versuchen noch zu begreifen, was wir da überhaupt wahrnehmen, was da passiert. Da gibt es Dinge, die lassen uns einfach den Kiefer runterklappen. Und dann gibt es wieder diese Epic Fails, wie vor kurzem diese Darstellung von Wehrmachtsoldaten von Gemini, der generativen KI von Google. Die Soldaten waren nämlich nach unserer heutigen Vorstellung politisch korrekt. Und da gab es dann unter anderem asiatisch aussehende Frauen mit Stahlhelm. Ich vergleiche das immer so ganz gern mit den Anfängen der Navigationssysteme. Da gab es ja auch immer diese Anekdoten in der Zeitung, dass wieder jemand in den Fluss gefahren ist, weil sein Navi die Fährlinie für eine Brücke gehalten hat. So einen Fehler konnte man im Navigationssystem relativ einfach fixen. Da war klar, warum das Navi den Fehler gemacht hat. Bei der generativen KI ist das leider nicht ganz so einfach. Wir wissen nicht, eigentlich, wir haben es noch nicht mal wirklich verstanden, wie diese teilweise intelligenten Leistungen zustande kommen.Die Epic Fails, die machen uns aber bewusst, dass es sich nicht um einen Algorithmus handelt, sondern um ein Phänomen, das scheinbar emergiert, wenn man viele Milliarden Texte in eine Matrix packt.

SO: Und was meinst du da mit emergiert? Was ist das denn?

SG: Das ist ein Begriff aus der Naturwissenschaft. Ich habe das mal mit Wassermolekülen verglichen. Ein einzelnes Wassermolekül ist nicht sonderlich spektakulär, aber wenn du zum Beispiel im Segelboot in einem Sturm auf dem Atlantik unterwegs bist oder auf einen Eisberg aufläufst, dann kriegst du eine andere Perspektive. Denn viele Wassermoleküle zusammengenommen zeigen ganz neues Verhalten. Und das nennt man Emersion. Und Physik und Chemie haben viele Jahrhunderte gebraucht, um das halbwegs zu enträtseln. Und ich denke, wir werden, vielleicht nicht ganz so lange, aber wir werden noch ein gutes Stück weiterforschen müssen bei der generativen KI, um auch da ein bisschen mehr zu verstehen, was da jetzt genau passiert. Und ich finde, die Epic Fails, die sollten uns bewusst machen, dass wir aktuell gut daran tun, unser Schicksal nicht blind in die Hände eines Large Language Models zu legen. Ich finde, der Ansatz Human in the Loop, wo die KI einen Vorschlag macht und dann ein Mensch nochmal drüber schaut, das bleibt bis auf weiteres der beste Modus. Und die Übersetzerbranche, die gefühlt der ganzen Welt ein paar Jahre voraus ist, wenn es um generative KI geht oder um neuronale Netze, die hat das ziemlich klug erkannt und gewinnbringend umgesetzt.

SO: Und wenn also jetzt die Übersetzung das Muster ist, was heißt das dann für generative KI und die technische Doku?

SG: Das ist eine gute Frage. Lass uns mal einen Schritt zurück machen. Also am Anfang meines Arbeitslebens, da war die Revolution in der technischen Dokumentation, das waren diese strukturierten Dokumente. SGML und XML. Und das kennt man jetzt also mittlerweile schon seit mehreren Jahrzehnten und es ist ja immer noch nicht in jeder Redaktion gebräuchlich. Und das heißt, wir haben jetzt diese strukturierten Dokumente und das andere, das sind die bösen unstrukturierten Dokumente. Und ich fand das schon immer so ein kleines bisschen einen Etikettenschwindel, denn unstrukturierte Dokumente sind ja in Wirklichkeit auch strukturiert. Also meistens zumindest. Da gibt es so eine Makro-Ebene, da habe ich ein Inhaltsverzeichnis, ein Titelblatt, ein Stichwortverzeichnis. Es gibt Kapitel. Dann gibt es Absätze, Listen und Tabellen und das geht dann runter bis auf die Satzebene. Da habe ich Aufzählungen, Aufforderungen und so weiter. Und nicht umsonst nennen das manche Linguisten ja Textstruktur. Und wenn ich jetzt mit XML rangehe, das Schöne daran an XML ist, dass ich diese implizite Struktur nun plötzlich explizit mache. Und damit kann dann der Computer mit unseren Texten rechnen. Denn wenn man ehrlich ist, am Ende ist XML nicht für uns, sondern für die Maschine.

SO: Kann es dann sein, dass die KI Strukturen entdecken kann, die für uns Menschen bis jetzt zwangsweise nur durch XML ausgedrückt wurden?

SG: Ja. Also ich habe mich da mal vor kurzem mit Invisible XML beschäftigt und da kann man über unstrukturierten Text Muster legen und die werden dann als XML sichtbar gemacht. Ganz clever. Und ich finde generative KI ist so eine Art Hochleistungs-Invisible XML. Also weil es zwar nicht so ganz strikt wie Invisible XML Regeln enthält, aber dafür auch sprachliche Nuancen versteht. Und ich fand es ganz spannend, ein Kunde von uns, der hat unstrukturierte PDF-Inhalte in Chat-GPT gefüttert, also unstrukturierte Inhalte aus dem PDF, um sie nach XML dann zu konvertieren. Und die KI hat erstaunlich gut die unsichtbare Struktur entdeckt, die in den Texten verborgen war und echt prima XML konvertiert. Also das war beeindruckend. Also wenn KI jetzt scheinbar Informationen aus dem Nichts schafft, dann ist es eben eher so, dass es existierende, aber verborgene Informationen sichtbar macht.

SO: Ja, ich glaube das Problem ist ja so, dass diese verborgene Struktur, also in manchen Dokumenten ist das da, aber in anderen da ist das, was wir auf Englisch, bei uns heißt das Crap on a Page. Das ist also, da gibt es keine Struktur. Und von einem Dokument zum anderen, da gibt es keine, also keine, die sind ganz anders. Also Redakteur 1 und Redakteur 2, die schreiben und die unterhalten sich niemals. Und also wenn die KI jetzt aus ein paar Stichworten ein ganzes Kapitel und eine Gliederung erstellt, wie geht das? Wie passt das zusammen?

SG: Ja, du hast recht. Jetzt haben wir die ganze Zeit drüber geredet: Wir nehmen PDF und dann wird da XML noch dazu gepackt. Aber wenn ich jetzt hier an der Stelle bin und sage, ich haue mal ein paar Stichworte rein und ChatGPT schreibt dann plötzlich etwas. Aber auch, ich finde auch da gilt dieser Gedanke, dass das eigentlich verborgene Information ist. Klingt vielleicht zuerst mal ein bisschen gewagt, aber da entsteht nichts Neues, nichts völlig Überraschendes. Wenn ich jetzt, sagen wir mal ChatGPT, einfach frage, gib mir mal eine Gliederung für eine Maschinen-Dokumentation. Und dann kommt da was raus. Ich denke, das würden die meisten von unseren Zuhörern genauso hinschreiben. Das ist nichts Neues. Das ist versteckte Information, die in den Trainingsdaten steckt, die durch die Anfrage einfach sichtbar gemacht werden. Denn letztendlich erstellt die generative KI diese Information aus meiner Anfrage und dieser riesigen Menge an Trainingsdaten. Und die Antwort, die ist so gewählt, dass sie gut zu meiner Anfrage und den Trainingsdaten passt. Die, ja, legt sich so ein bisschen wie so ein Layer da drüber, sodass das einfach gut das simuliert. Und am Ende habe ich damit dann keine neue Information, sondern hoffentlich die benötigte Information in einer besser verarbeitbaren Form. Entweder wie vorhin beim Beispiel mit dem PDF, mit XML angereichert oder ich habe jetzt eine Gliederung. Und ein bisschen stelle ich mir das vor wie so bei einer Saftpresse. Ja, die erfindet den Saft ja auch nicht, sondern die holt das aus den Orangen einfach raus.

SO: Informationen besser verarbeitbar zu machen, also das klingt doch fast schon wie eine Tätigkeitsbeschreibung für technische Redakteure. Und was ist mit anderen Methoden? Also wenn wir jetzt Metadaten oder Knowledge Graphs haben, wie sieht das denn da aus?

SG: Stimmt, das ist neben XML natürlich auch total wichtig. Also Metadaten, Knowledge Graphen. Ich finde Metadaten, die verdichten Informationen auf wenige Datenpunkte und die Knowledge Graphen, die machen dann die Beziehungen zwischen diesen Datenpunkten. Und gerade dadurch machen Knowledge Graphen, aber auch Metadaten ja unsichtbare Informationen sichtbar. Denn die Zusammenhänge, die vorher implizit wahr waren, die können jetzt durch die Knowledge Graphen nachvollzogen werden. Und das lässt sich prima mit generativer KI kombinieren. Am Anfang waren die Knowledge Graph Experten ein bisschen nervös, das konnte man merken auf Konferenzen, aber jetzt sind sie eigentlich ziemlich froh, dass sie festgestellt haben, generative KI plus Knowledge Graphen, das ist viel besser als generative KI ohne Knowledge Graphen. Und das ist natürlich prima. Das ist übrigens nicht der einzige Trick, wo wir in der technischen Dokumentation etwas haben, was der generativen KI auf die Sprünge hilft. Wenn man mit Large Language Models große Wissensbasen durchsuchbar machen will, dann macht man das ja heutzutage mit RAG, also Retrieval Augmented Generation. Und damit kann man sehr kostengünstig eigene Dokumente mit einem vortrainierten Modell wie ChatGPT kombinieren. Und kombiniert man jetzt RAG mit einer Facettensuche, so wie wir das in den Content Delivery Portalen in der TechDoc normalerweise haben, dann sind die Ergebnisse viel besser als mit der üblichen Vektorsuche, denn die ist am Ende ja nur eine bessere Volltextsuche. Und das ist dann auch wieder eine Möglichkeit, wo strukturierte Informationen, die wir eben haben, der KI auf die Sprünge hilft.

SO: Also bist du dann auch der Meinung, dass die strukturierte Information, durch KI nicht obsolet wird, sondern sogar noch wichtiger wird?

SG: Ich habe schon den Eindruck, dass sich so ein bisschen der Glaube durchgesetzt hat, strukturierte Informationen sind besser für KI. Ein bisschen sind wir dann natürlich, glaube ich, alle biased. Also wir müssen das glauben. Das sind ja die Früchte unserer Arbeit. Ein bisschen ist es auch so, also genauso wie der Apfel vom Biobauern natürlich gesünder ist, als der konventionelle Apfel aus dem Supermarkt. Ich denke, das ist wissenschaftlich klar erwiesen. Aber am Ende ist ein Apfel immer besser als eine Packung Gummibärchen. Und das ist es, was bei KI so disruptiv sein kann für uns. Denn am Ende machen wir Informationsvermittlung. Und wenn der Anwender Informationen bekommt, die ausreicht, die gut genug ist, warum sollte er dann noch die Extra-Meile gehen, um noch bessere Informationen zu bekommen? Ich weiß nicht.

SO: Ja, also ich interessiere mich wirklich an dieser, also Gummibärchen-Karriere. Da will ich mal ein bisschen mehr hören. Aber warum ist das denn so, sagen wir mal, pessimistisch für die Redaktion von dir?

SG: Ich glaube, mein Bild ist ein bisschen größer geworden in der letzten Zeit. Ich glaube, da geht es mir gar nicht so sehr um die technische Dokumentation. In der technischen Dokumentation sind wir ohne strukturierte Daten aufgeschmissen. Das wird nicht funktionieren. 

Aber wenn wir das größere Bild machen, bei Quanos haben wir ja nicht nur ein Redaktionssystem, sondern wir machen auch so einen digitalen Informationszwilling. Und dann sitze ich immer in diesen Arbeitskreisen drin als der Typ aus dem Tech-Doc-Bereich. Und da muss ich immer hinnehmen, dass unsere besonders gut strukturierten Informationen aus der Tech-Doc, also die mit den besonders viel Vitaminen und sekundären Pflanzenstoffen, das ist halt doch in der Realität da draußen eher die Ausnahme, wenn wir uns die Datensilos angucken, die wir im Info-Twin zusammenfahren wollen. Und als ich jung war, da habe ich noch dran geglaubt, dass wir die anderen davon überzeugen müssen, auch so zu arbeiten wie in der technischen Dokumentation. Das wäre doch echt prima gewesen. Aber wenn wir ehrlich sind, es klappt halt nicht. Die Vorteile, die wir in der technischen Dokumentation dank XML haben, die sind in den anderen Bereichen für die einzelnen Kollegen zu klein, als dass sie umsteigen wollen. Also Ausnahmen bestätigen die Regel. Das bedeutet, da draußen gibt es Tonnen von Informationen, die in diesen unstrukturierten Formaten eingesperrt sind. Und die können nur mit KI zugänglich gemacht werden. Das wird der Schlüssel sein.

SO: Und wie machen wir das? Also wenn jetzt XML da nicht der richtige Pfad ist, dann wie sieht das aus?

SG: Naja, also nehmen wir ein Beispiel. Also viele unserer Kunden sind ja Maschinenanlagenbauer und gucken wir mal auf die Zulieferdokumentation. Da kommen für einen Auftrag, mehrere Dutzende PDF. Und natürlich hat die Redakteurin dann so eine Checkliste und sie weiß, was sie in diesem Haufen PDF suchen muss. Das Prüfzertifikat, die Wartungstabelle, Ersatzteillisten und so weiter. Und obwohl die PDFs ja komplett unstrukturiert sind, also dieses unstrukturiert, wie wir halt als XML-Leute das dann so nennen, sind wir Menschen in der Lage, diese Informationen zu extrahieren. Und das Spannende daran, eigentlich kann das jeder. Also dafür muss man kein Spezialist für Abfüllanlagen oder Industriepumpen oder Sortiermaschinen sein. Wenn du eine Vorstellung davon hast, was ein Prüfzertifikat, eine Wartungstabelle, eine Ersatzteilliste ist, dann findest du die. Und jetzt kommt’s. Dann kann die KI das nämlich auch.

SO: Aha. Und also geht es dir in diesem Fall eher um Metadaten oder um was anderes?

SG: Nee, du hast schon recht. Also es geht hier in der Tat um Metadaten und Verlinkungen.

Ich finde das spannend, was das mit unserem Sprachgebrauch macht. Denn wir haben uns ja so angewöhnt zu sagen, wir reichern die Inhalte mit Metadaten an. Aber in vielen Fällen haben wir einfach nur die unsichtbare Struktur explizit gemacht. Da ist gar keine Information dazugekommen. Da ist nichts reicher geworden, sondern einfach nur klarer. Aber jetzt stell dir mal vor, dein Zulieferer hat keine Wartungstabelle geliefert. Dann musst du anfangen, die Wartungsarbeiten zu lesen, zu verstehen und die notwendigen Informationen zu extrahieren. Und das ist ziemlich mühsam. Selbst hier kann dann die KI noch unterstützen. Aber wie gut, hängt dann schon davon ab, wie verständlich die Wartungstätigkeiten beschrieben sind. Und umso mehr spezifisches Hintergrundwissen notwendig ist, umso schwieriger wird es, für die KI hilfreich zuzuarbeiten.

SO: Und wie sieht das denn aus? Also hast du ein Beispiel oder ein Use Case, wo die KI gar nicht weiterhilft? 

SG: Wie schon gesagt, das hängt natürlich dann vom Kontextwissen ab. Ich hatte von einer Kundin mal Teile der Risikoanalyse bekommen. Und da ging es darum, kann man daraus mit KI Sicherheitshinweise erstellen? Und ich habe dann gesagt, ja klar, guck mal die Risikoanalyse an und dann guck mal an, was die Redakteure daraus gemacht haben. Und es waren mustergültige Sicherheitshinweise. Aber es stand so wenig in der Risikoanalyse drin, dass beim besten Willen konnte man da nichts mit Künstlicher Intelligenz machen, sondern das ging nur, weil die Redakteure ein wahnsinnig gutes Produktverständnis hatten und auch noch die Normen im Hinterkopf hatten, die dafür notwendig waren. Da war eben die Information nicht in diesem Input versteckt, sondern im Kontextwissen. Und das ist so speziell, das ist natürlich auch nicht im Large Language Model vorhanden.

SO: In so einer Anwendung oder in so einem Anwendungsfall siehst du dann überhaupt keine Möglichkeit für KI?

SG: Also zumindest nicht für ein generisches Large Language Model. Also sowas wie ChatGPT oder Claude, die sind da chancenlos. Es gibt die Möglichkeit in der KI, diese Modelle nochmal zu spezialisieren. Man kann die ja mit kontextspezifischen Texten feintunen. Aber ob wir da im Normalfall ausreichend Texte haben, weiß man im Moment noch nicht so. Da gibt es die ersten Experimente. Aber denken wir nochmal zurück an die Wassermoleküle. Für einen Eisberg oder schon für einen Schneemann brauchen wir ziemlich viele davon. Also heute ist letztendlich so, welche Hilfsmittel unter den Gesichtspunkten dann auch, also Feintuning ist echt teuer. Also Kosten. Dauert lange. Also auch Performance ist ein Thema. Und wie praktikabel ist das? Haben wir Trainingsdaten? Also unter diesen ganzen Aspekten, was da jetzt wirklich der goldene Weg ist, um so ein generisches Large Language Model für die Textarbeit für sehr spezifische Kontexte brauchbar zu machen, ist einfach noch unklar. Weiß man heute einfach nicht.

SO: Kannst du denn heute schon sehen oder voraussehen, wie die generative KI die technische Dokumentation verändern wird oder muss?

SG: Ich finde das noch echt mehr so einen Blick in die Kristallkugel. Also das ist noch gar nicht so einfach einzuschätzen, welche Use Cases jetzt für den Einsatz von KI in der technischen Dokumentation vielversprechend sind. In der Regel hast du eine Aufgabenstellung, wo ein textueller Input nach einer bestimmten Maßgabe in einen textuellen Output transformiert werden soll. Und früher galt da Garbage in, Garbage out. Die Large Language Models nach meiner Meinung verändern diese Gleichung nachhaltig. Input, den wir mangels Informationsdichte früher nicht automatisch verarbeiten konnten, den können wir jetzt durch universelles Kontextwissen anreichern, so anreichern, dass er verarbeitbar wird. Fehlende Informationen können nicht ergänzt werden. Das haben wir ja jetzt besprochen. Aber diese unausgesprochenen Annahmen, in der Tat, die können wir mit reinpacken. 6Und das hilft uns in der technischen Dokumentation an vielen Stellen, weil sich eine gute technische Dokumentation ja unter anderem dadurch von einer schlechten unterscheidet, dass weniger Annahmen notwendig sind, um den Text zu verstehen, beziehungsweise auch, wenn man ihn maschinell verarbeiten will. Und deshalb finde ich Informationsverdichtung statt Wissenschöpfung für mich so eine Art Ockhamsches Messer. Ich betrachte mir die Ausgabenstellung. Geht es jetzt einfach nur darum, verborgene Informationen sichtbar zu machen oder sie in eine andere Form zu bringen, dann ist das einfach ein guter Kandidat für den Einsatz von generativer KI. Oder geht es jetzt eher darum, durch den Rückgriff auf andere Informationsquellen die Informationen zu veredeln? Dann wird es schon schwieriger. Wenn ich jetzt diese Informationen, diese anderen Informationen in einem Knowledge Graphen habe, wenn die dort schon aufgeschlüsselt sind, dann kann ich ja die Informationen explizit vor der Übergabe an das Large Language Model anreichern. Und dann geht das auch wieder. Wenn aber die Informationen, zum Beispiel das inhärente Produktwissen im Kopf des Redakteurs ist, wie bei der Risikoanalyse meiner Kundin, dann hat das Large Language Model einfach keine Chance. Das wird da keinen Mehrwert generieren. Dann muss man eventuell nochmal überlegen, kann man die Aufgabenstellung noch irgendwie aufteilen? Vielleicht gibt es einen Teil, wo dieses Wissen nicht notwendig ist und ich habe einen vor- oder nachgelagerten Prozessschritt, wo ich mit der KI was optimieren kann. Und ich finde, da wird in der Zukunft die Musik spielen. Diese Kunst, das Machbare vom Unmachbaren zu unterscheiden, und das wird eher so eine Art Ingenieurskunst sein, das wird in den kommenden Jahren der Faktor sein, der entscheidet, ob die generative KI mir einen Nutzen stiftet oder nicht.

SO: Und was glaubst du, mehr oder nicht?

SG: Ich glaube, wir werden das raustüfteln. Aber es wird viel länger dauern, als wir das glauben.

SO: Ja, also ich glaube, das stimmt.

Und also vielen Dank, Sebastian. Das sind wirklich ganz interessante Perspektiven und ich freue mich auf unsere nächste Diskussion, wenn in so zwei Wochen oder drei Monaten was ganz Neues da in der KI ist und wir uns noch mal darüber unterhalten müssen, ja, was können wir denn heute machen oder jetzt machen? Also vielen Dank und wir sehen uns …

SG: … demnächst irgendwo auf diesem Planeten.

SO: Irgendwo.

SG: Vielen Dank für die Einladung. Mach’s gut, Sarah.

SO: Ja, und vielen Dank an die Zuhörenden, besonders zum ersten Mal im deutschen Raum. Weitere Informationen sind bei scriptorium.com verfügbar. Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links. Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Strategien für KI in der technischen Dokumentation (podcast, Deutsche version) appeared first on Scriptorium.

Why do we still have these silos of content? Back to what you said, Sarah, if we’re thinking about the learner experience, the learner doesn’t distinguish between classroom, e-learning, looking something up, or going to technical documentation. They just know, “I gotta get my job done. I need to perform. I need to know what I’m doing.”

— Leslie Farinella

Related links:

• Xyleme LCMS
• MadCap CCMS-LCMS Guide (white paper)
• So much waste, so little strategy: The reality of enterprise customer content
• Rise of the learning content ecosystem with Phylise Banner (podcast)
• Wrangling the Meg of learning content

LinkedIn:

• Leslie Farinella
• Sarah O’Keefe

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about the challenges that organizations face with content operations for learning. Hey, everyone. I’m Sarah O ‘Keefe, and today I’m delighted to welcome Leslie Farinella of Xyleme to the podcast. Xyleme, as you may know, has recently been acquired by MadCap Software, which also owns Flare and IXIASOFT. So Leslie, welcome. Tell us about yourself and your role at Xyleme/MadCap.

Leslie Farinella: Hi, Sarah. I’m super excited to be here today. So I’ve been at Xyleme for over the last eight years. Actually, prior to that, I was in the learning content space, but on the business side, helping organizations to drive performance within their workforce. And I realized that, you know what, if we wanted to scale, we were going to have to bring technology to help solve this problem. So I got really excited. So I jumped over to the product side. And since I’ve been at Xyleme, I’ve pretty much covered almost all of the roles, ending up with my last role being the chief strategy officer.

SO: And so here we are. And I think you’re probably the perfect person to talk to about this topic where we’re getting a lot of interest all of a sudden. Well, from my point of view, maybe not from your point of view, but from my point of view, we’re getting a lot of interest in content operations for learning content. 

LF: Yeah.

SO: So people are asking questions like, if I have overlapping content between my tech comm content and my learning content, why, you know, why can’t I combine those in some efficient way as opposed to what I’m doing now, which is this terrible copy and paste or worse rewrite without, you know, people ever talking to each other. But also we’re hearing from learning organizations that don’t actually have what I would consider to be tech comm content who need a more mature content workflow. So they’re asking questions like, “How can I develop learning better, faster, cheaper?” So what does that look like on your side of the fence?

LF: We absolutely hear the exact same thing, and I think it’s only gonna get worse because if we think about the root cause and think about what’s really driving this conversation and what’s making this conversation escalate is the speed of change and the need to drive agility within the organizations so organizations have to adapt faster than they have before which means people have to learn new skills new mindsets and new behaviors faster than before and which means inevitably they have to learn on the go, which means that performance support and tech comms is part of that learning. And as you and I know, cause I know you and I’ve had past conversations breaking down that silo between tech comm and learning is gonna be essential to driving that agility that organizations need to change. And that’s why they’re feeling the pressure.

SO: And so what does that look like? You know, Xyleme in particular is an enterprise learning content management system, which perhaps I should have said in the intro. What does it look like when people start considering something, you know, a solution like that? What’s the executive-level argument for that?

LF: Speed, agility, cohesiveness, learner experience. And I think that what we all have to remember is when you’re buying something like a CCMS or an LCMS, you know, component content management system or learning content management system, they’re kind of flip sides of the same coin, but they also need to work together. And I think that is the change in mindset we need in the industry is that if you think about learning, you have formal learning. I take a course. Usually, I’m a novice. I need some scaffolding. But the majority of the learning, once I kind of get my initial scaffolding happens by experience. It happens by solving problems. And inevitably that means looking stuff up. So it means going back to the documentation because no one’s going to go to the LMS to go flip to halfway through the e-learning course to look something up that’s just very painful. So what I hear from the top executive level is how do we make that whole system work together? How do we consider it from a job performance perspective and moving people from a novice to proficiency across that entire spectrum, which is learning and tech comm. And that’s where this idea that we have these separate systems and these separate processes really start to get in our way. And I think that’s where the opportunity is, is to see how do we break down that silo and how do we think about how these technologies can work better together or maybe even collapse into a single tech stack.

SO: Yeah, and I think that, you know, a big part of this is if you if you go back 20, 25, 30 years, we had classroom training, basically, and we had paper like books or maybe a cheat sheet or a job aid, but, you know, some sort of a printout. And so the distinction between I’m going to go to a class and learn the things and they’re going to give me a like a student guide or a textbook or, you know, but something, some sort of supporting material. And then there’s my reference library of books. And today, we still have that. I mean, we still have that distinction between class, e-learning, blended learning, and online, and all the rest of it. But there’s that bucket. And then there’s that bucket of, OK, there’s this other book adjacent or book-derived stuff. However, today, it’s all sitting on the same website. And so now as an end user, as a software user or learner, I show up on your website, your product website, and like, hey, I’m blocked on this task that I need to do. I’ve got a job I need to get done. I don’t know how to do it. And I just frankly don’t care. I just want you to give me the answer. Now, I don’t care where it lives. Not my problem. But give me the answer and give it to me better, faster, cheaper. And then, you know, infamously, we always say, “Don’t ship your org chart,” except we always do. So what does it look like to start to foster these connections and improve the integration or the interaction or the, I’m struggling for words, which is probably a symptom of this problem. What does it look like to start fostering those connections to improve the end-user experience?

LF: I think what you just said, end user experience. You know, we have to map that user experience. And I think that’s one thing that the learning side has done well is they’ve invested in the LMS, the learning experience platforms. Everybody still complains about them, but at least they were, you know, investing and trying and those experiences are getting better and better because there’s more competition in the market. People are coming up with other tools. They’re bringing, you know, more algorithms into play and then, you know, AI will play into that as well. But what they haven’t done well is content management and structured authoring. So Xyleme is an LCMS. So actually, you know, there obviously are people on the learning space that have bought into, we need to bring structured authoring into learning. But it’s not the majority. A lot of organizations still haven’t done that. And I think that once you start to bring what tech docs already knew is, you know, you’ve got to standardize to personalize. You’ve got to bring in, you know, you got to think modular. You’ve got to be able to standardize against your terminology. And then you can start to scale. That’s something that the learning side, you know, needs to learn and that’s something that the LCMS, which is the counterpart to component content management brings in and we’ve tailored it to the audience of instructional designers and learners to help with that transition. But the base ideas underneath the technology are the same. One of the interesting things in the acquisition with MadCap and the IXIA team when we started comparing products, we’re like, we do that, we do that too. yeah, we’ve always wanted to do that. You guys already have it, but we all, we realized very quickly we were solving the same problem and getting to the same result. We made them make different design decisions along the way, but we were solving the same problem and the fundamental premise underneath both technologies were the same, which then starts to beg the question, why aren’t they combined? Like, why are we still have these silos of content? If we’re thinking about back to what you said, Sarah, the learner experience, the learner doesn’t distinguish between classroom e-learning, looking something up, going to technical documentation. They just know, I gotta get my job done. I need to perform. I need to know what I’m doing. And I wanna, you know, ready myself for my next role in promotion within the organization. And they have expectations on their performance. And so how do we look at that and understand it needs to be more cohesive and how can we as both the tech docs and the learning industry break down that silo with the content but also the experience itself to make that more cohesive. 

SO: Yeah, I think one thing that’s sometimes overlooked in this is that the default emotional state of a person who is looking for information is something like frustration and anger, right? Because they’re not reading for fun. They’re not going to class for fun. I mean, probably. They are doing it because this class or this learning piece or this piece of information that I don’t have, is standing between me and getting the job done. I need to generate a pivot table and I don’t know how, so show me how to do it. I need to do a thing and until I do the thing, I can’t progress in my tasks of the day and so I’m annoyed. And we’ve set aside knowledge base for the purpose of this conversation, but knowledge base usually is even worse because usually that’s something like my system crashed, why? So they’re not just annoyed, they’re like incandescently angry because something is not working. Okay, so, and I think you said something really interesting in there about how the learning experience, you know, the downstream user experience for learning, there’s been a lot of work put into that and comparatively less on the tech comm side. I’m not saying all tech comm is bad or anything like that, but when you look at some of the work that’s been done in producing really sophisticated e-learning and really interesting learning experiences on a platform of some sort, and then conversely on the back end, tech comm has done a huge amount of work around reuse and efficiency and automated formatting and automated delivery and multi-channel and all these things, which I think there’s some advantages there and there’s some things there that I think the learning world can can probably leverage and you know vice versa so, you know, while you and I are ruling the world and we’re fixing all of this, you know, we can’t fix the integration next week and I mean I’ve been complaining about that for a while, but you know that is a legitimately difficult hard problem. But what are some of the steps that we can take as content creators, whether learning or tech comm, to start thinking about this sort of more unified approach to enabling content? What can we do there? And what are some of those first steps?

LF: I think the first step is we have to collaborate. I think the first step is, do you even know the people in your tech comm team or your learning team? Like, do you even know who they are? So, you know, I think there’s a conversation. I think the second one is to have a shared goal of we want to create a better user experience. Like, you know, an agreement that that is a goal that’s worth, you know, pursuing. And I think your managers, your VPs, definitely your leadership would agree that is. and then I think mapping that out. Like what would that learning experience look like? What’s your utopia? And then break it down, right? You can’t boil the ocean. You have to kind of have a plan. You know, what does the vision look like? And then what’s the first step? Start small. Like what’s the first step in the vision? And I think you and I talked earlier, a procedure is a procedure. Like there’s no magic. There’s some obvious low hanging fruit here as far as, you know, where you can share content that drives efficiency and makes sense. And then to the learner, you’re not coming up with different terminology. We all know the brain loves consistency because it helps with retrieval within the brain. So when I see the same picture, when I see the same example, when I see the same terms, it unlocks memory within the brain. It helps with retrieval. So, you know, we can make it easier for people. But then also looking at, you know, can we put some of that technical documentation and embed it in the learning content in the LXP so it’s easy to find where are people going? Maybe it is to the tech doc portal. Maybe we put it in both places and we figure out single source, right? We can update it in both places. We can keep that in sync, but really understanding and mapping that learner, the end user experience for performance and working together and understanding that we both have something to contribute to the conversation. I think, you know, to your point, tech comms can learn a little bit about experience and how people, you know, retrieve information, but the learning team can definitely learn a lot about structured authoring content management from the tech comm team. So bring those expertise together, which is 80% business and 20% technology. I mean, the first part is, you know, you just got to agree and set your goals and then figure out what’s the best technical solution that will drive those goals. And I would even argue, take it small. Like, you know, do experiment, see what works, what doesn’t work, trial and error. Cause I wish I had the whole answer. I don’t. I think it definitely is a problem that we need to invest in solve. And the only way we’re going to solve is through experimentation. But I also don’t think there’s a one size fit all answer either. I think each organization has legacy tech stacks. We all know we can’t just throw out the tech stack we have, you know, we have different competing business priorities. We have different skills and capacity within our teams. So do what you can. And I think that sometimes people throw up their hands and they do nothing because they think it’s too big. But you got to start small and you got to start somewhere. And step one is go have lunch with the people, maybe a virtual lunch these days, but on the other side, like talk to them, share you guys. At the end of the day, you have a common goal of driving performance within your organization. You have a shared mission. That’s where I would start.

SO:  Yeah, I like figure out who your counterpart is. That seems like a reasonable achievable goal. And then, yeah, and then back, you know, work from there. What can you, you know, can you reach consensus on shared terminology? Because, you know, I mean, never mind unified content authoring, that would be lovely but can we agree to call a car seat a car seat and not sometimes a safety seat and sometimes a baby seat and sometimes a something else? Because that would be like a really good start.

LF: Yeah. And the more things you can agree on, the more things you’ll find to agree on. So start with that. How do I share, you know, the procedures? How do I keep stuff in sync? You know, how do I even reduce the time between, you know, product release, the technical documentation and any formal training that needs to have? How do I make sure, you know, how can I generate FAQs? There’s a lot of things that you could brainstorm that you could do together, which then it fosters that collaboration.

SO: Mm-hmm.

LF: And then figure out what are the technical barriers I’m hitting. And I’ll say this as a vendor and then talk to the vendor and say, hey, here’s the business problem we need to solve. We think it’s a market problem. We think there’s value with you. We need you to fix this. Like we need you to be able to integrate these systems. And again, from the vendor side, if you make a good business case and you can show that the market in general, it’s good for the market, you can probably push their roadmap. But if you don’t speak up, if you haven’t tried, how do you know what those barriers are? So how do you know what to push? So just because it doesn’t do it today doesn’t mean you can’t get a solution.

SO: And the bigger you are, the more we would like you to kindly contact the vendors because…

LF: Yeah, the more money you have, the more clout you have. But I’ll be honest with you. As far as our roadmap on the vendor side, many times anyone who’s willing to experiment and to put some skin in the game as far as a real use case and to work together, I would rather build features and integrations based on real-world examples and real-world data than a theoretical PowerPoint we may put together from a nice product feature. And I know most product vendors are the same.

SO: I’ll have leverage.

LF: So partnering with your tech vendors and coming to them with, this is the business problem we want to solve. This is why we think it’s worth solving. And partnering with them to solve it is going to help to break down some of those technical silos. And the good news is on the MadCap side, because we do have the IXIA, we have the Flare, we have the Xyleme, that’s our vision is to how do we bring it together? It’s not gonna happen overnight because we all have. Like I said earlier, we all kind of made different design decisions which aren’t necessarily all compatible right this second, but we’re figuring out how do we make them more compatible? Like who’s got to kind of give up what and how can we make these work together? And because they’re all in our product stack, we have a vested interest in doing that. And honestly, we’re looking for customers, if there’s any MadCap customers out there listening, we’re looking for customers who want to partner with us on that journey and help us to figure out the answer because we know the problem pretty clear. We know some of the answer, but the only way you truly find the answer is by partnering with customers to figure it out.

SO: So I have to ask you about AI because we’re not allowed to do podcasts without asking about AI anymore. Tell me a little bit about your take on AI in the content universe that you live in.

LF: Yeah, I can, you know, there’s so much buzz about AI generation and the large language models and chat GPT. And I think because it kind of like wowed us all and it made the news and not that there’s not some efficiencies to be found there around summarization and descriptions. Cause one thing we know is that. The quality of the descriptions that go in the LMS and the LXP really drive retrieval or people being able to find something. And humans actually write really bad descriptions. AI does a better job of writing descriptions that search can find. So I think there’s something there there. But what really excites me is AI retrieval. Being able to match content to a person, like to me specifically based on my role context, where am I searching from? Am I searching from within Salesforce? Am I searching within my technical app? You know, what gives some idea of what I might be my problem that I’m having? Maybe even send error messages in what’s my region? What are my current skills? What are my skill gaps that would get me the information that I need faster and just the information that I need, not, you know, the 20 page document and now I’ve got to go find page five of 20. The great thing about AI retrieval is it can just bring me topic seven out of 70 and just bring that back to me. So I think that really solving that retrieval problem is huge, that time to an answer. The second one is AI data. AI’s been doing a lot with data. It’s not new news as far as data classification, looking at patterns. But if we think about if our common mission is performance and people being able to do their job, understanding holistically somebody’s journey from novice to proficiency and expert and what really drove those. And we might find out it’s all on the managers. And I argue a lot of it is their manager, you know, their manager and their coaching and had nothing to do, nothing against the audiences we’re talking to, but had very little to do with the learning team and the comp team. It had a lot to do with the managers, but understanding that and how we contribute into that journey will help us to understand what’s really important. And the nice thing about AI is it can bring in a lot more data and look at patterns that are much more sophisticated than us as humans can. We can’t hold that many variables in our head at one time. So I’m excited about AI to bring personalization of content, matching people to content, helping us better understand the value of the content we write and what drives that value of the content so that we can drive those best practices because I think we guess a lot and we have our ideas, we might be surprised at the answer. And then yeah, I mean, AI generation does definitely have a role. I don’t want to say it doesn’t have any, but honestly, it doesn’t excite me quite as much as the other two.

SO: Well, I, you know, I sort of lost interest early on when I asked chat GPT to generate a bio for me and it informed me that I had a PhD, which I mean, cool, but no. So, you know, it, it just, there were a couple of other things like that. It, and, and you said this earlier, you know, it is, it is important in our context to get the information right. And the thing that ChatGPT and the other generators don’t necessarily do is accuracy. They generate plausible content. But if we care about getting it right, cut the blue wire, then the red wire. no, wait, wrong. So it’s important to have this stuff be correct. And that’s the thing that GenAI really struggles with because it doesn’t really have a concept of correct.

LF: Yep. I think that’s where we are sitting on a gold mine with our content, because if you think of RAD, which is Retrieval Augmented Generation, which is the current, you know, leading answer as far as proprietary information that must be correct, it really is about retrieval. And what it does is it points to your vetted database of content. Well, where are those? By LCMS? CCMS? Gold mines of content, because, well, AI can do unstructured content. So not saying that you can’t give it a PDF or PowerPoint, whatever unstructured content. If you give it structured content, it’s like rocket fuel. It’s just easier, it’s better. And if you tagged that content, even if you use AI to help tag it, but if you’ve tagged that content, now that retrieval accuracy goes up exponentially, so we are sitting on rocket fuel. If you’ve already invested in an LCMS or a CCMS, you’re doing structured authoring, you have rocket fuel to drive your AI solution. And you don’t need AI to do it. It’s not that it has AI inherently in our databases. It’s just that we have the content that’s going to generate those AI agents and help to generate those answers and drive those right answers. And one of the key things when you think about proprietary content in these rag systems is the attribution. So it will provide a response. It’s not totally, it may summarize it, but it’s not rewriting it to the, it’s not just making it up like Jack GPT would, where it’s writing it from scratch. It is retrieving it. It may summarize it, but it gives an attribution. It tells me where it got that content from so as the person looking at it, I can decide whether I trust that source and I can verify it. So if it’s red wire versus blue wire and the wrong blue wire, something’s gonna blow up, I can go check the source and say, okay, yes, I trust that source and I’m gonna cut the blue wire.

SO: And on that cheery and I think hopefully explosive note, that seems like that sounds like a good place to wrap it up. Leslie, thank you so much for coming on. I hope we’ll continue this conversation and drive some positive change and some new cool integration and cooperation possibilities. And with that, thank you for listening to the content strategy experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Overcoming operational challenges for learning content, feat. Leslie Farinella (podcast) appeared first on Scriptorium.

AP: Technical content, your tech content or product content, wants to convey knowledge so the user or reader can do whatever thing that they need to do. Learning content is about improving performance. And with your knowledge base content, it’s when, “I need to solve this very specific problem.” So those are the distinctions that I see among those three types.

SO: Okay, and from a customer point of view, what does this mean?

AP: Well, in reality, I don’t think the customers care. They want the information available, and they want it in the formats they want it in. And also, they want the right information so they can either get that thing done, improve their performance, or solve a specific problem.

Related links:

• So much waste, so little strategy: The reality of enterprise customer content
• Pulse check on AI: May, 2024
• New to tech comm? Expect the unexpected
• Wrangling the Meg of learning content

LinkedIn:

• Sarah O’Keefe
• Alan Pringle
• Bill Swallow

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about the challenges of content operations across the enterprise. Hi, everyone. I’m Sarah O ‘Keefe. I’m here today with two partners in crime, Alan Pringle and Bill Swallow.

Alan Pringle: Hello.

Bill Swallow: Howdy.

SO: That first one was Alan, and the second one was Bill. Good luck with that everybody. So I have a big topic today. I want to focus on the intersection of technical content, learning content, and knowledge base content. And Alan, what’s the difference between the three?

AP: Okay, let me see if I can break this down, because I’m sure people have very strong opinions about this, and we may hear about them, but this is how I’m gonna break them down. Technical content, your tech content or product content, wants to convey knowledge so the user or reader can do whatever thing that they need to do. Learning content is about improving performance. And with your knowledge base content, it’s when, “I need to solve this very specific problem.” So those are the distinctions that I see among those three types.

SO: Okay, and from a customer point of view, what does this mean?

AP: Well, in reality, I don’t think the customers care. They want the information available, and they want it in the formats they want it in. And also, they want the right information so they can either get that thing done, improve their performance, or solve a specific problem.

At the end of the day, they don’t care what department or what group wrote it. They just want it, and they want it then and there.

SO: So this enabling content is like, here’s how you can get your job done. Here’s how you can do the thing you need to do and move on with your day so that you can generate the report or write the thing or do the code or whatever it is. They need this content so that they can do the thing. So then, we have all these silos, right? We have technical content in its silo, and we have learning content, and we have knowledge base content, and then we have tools optimized for each of those use cases or for each of those sets of authors. So, now, is this a bad thing from a content perspective?

AP: That is possibly the worst leading question I’ve ever heard on this podcast. The worst. 

SO: Okay, I’ll rephrase.

AP: You don’t need to, but of course it’s bad. It is very, very bad. And the reason that it’s bad is because there is so much overlap in this content. Roughly half of technical content, there’s overlap because you’re both dealing with tasks. You’re dealing with tasks. 

SO: Procedures, yeah.

AP: Yeah, step-by-step instructions. So you don’t need two sets, one for each group. Why are we doing this? And when I say we, I mean the entire content world because folks, we are. You’ve also got overlap between your technical/product content and your support content. Troubleshooting instructions, Q&A’s on avoiding very specific problems. Same exact stuff, yet again, we’re often maintaining two different versions of that information. So there you go.

SO: So what we want is shared content, right? But we can’t do it because the tools aren’t there. Is that right? It is right. I know it’s right.

AP: Well, yeah, I mean, but it’s not just the tools. It’s the people that write this content because they often have, shall we say, fairly strong opinions that they need a special flavor or they need a special twist on the content. So it’s tools, but they’re also these opinions that the content creators have that inform these problems as well, I think.

SO: Okay, and then Bill turning to infrastructure, what does this look like from an infrastructure point of view as opposed to a, I mean, shared content is kind of an infrastructure problem, but I think there’s additional ones. What does that look like?

BS: Goodie, it’s my turn. Yeah, so shared infrastructure is a big one, you know, getting everyone to kind of play in that, you know, that same sandbox. But there are other things that really need to be shared across the enterprise. 

AP: Hmm.

BS: So things like taxonomy, you know, making sure everyone is aligning, you know, with the same terms, the same way of categorizing things, the same way of organizing information, their localization workflow, and even the vendors that they’re using, you know, that they’re all going under the same process so that they get a uniform result back. And then, you know, design systems, making sure that there’s a federated search in place, and making sure that anything that’s being produced for customer or reader consumption has the same unified experience might be a little bit different from content type to content type from delivery platform to platform, but in the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

SO: So from an infrastructure point of view, what does it look like today to set up shared infrastructure? Can you tell us a little bit about the software tools that are available that allow you to do all of this in a unified way?

BS: You know, it’s too big of a list. And that list is basically consumed with things like duct tape, string, Bondo, you name it. There is nothing out there that will give you a unified experience across the enterprise for every content type out there. Right now, it does not exist.

SO: So on the authoring side, I think there’s some unified delivery kinds of integrations. But I think we’re talking about the back end. 

BS: We’re starting to see a lot with portals that are starting to collect a lot of information and present them all in one unified space, or at least provide one universal point of access for that content. And we are seeing some tools start to reach out and kind of embrace other traditional content silos. So things like, for example, being able to do develop all of your content in one single place and be able to push to a same branded let’s say knowledge base and documentation portal But I don’t think that there’s anything out there that really grabs everything and says okay. We’re going to do you know manuals We’re going to do other tech content. We’re gonna do web-based references we’re going to do knowledge base articles and tech support guides and training materials, you name it, and produce it all from one source to all these different things. So we have a lot of duct tape and string in place at the moment.

SO: And point solutions like, hey, we’re optimized for learning. Hey, we’re optimized for KB. We’re optimized for tech com. And I mean, it does seem to me that there’s a really big disconnect between what our clients are asking for and what the market has available because our clients are asking for slash demanding unified authoring solutions. And like you said, we have duct tape and string to offer them.

BS: Mm-hmm.

SO: So, okay, so if let’s step back a little bit and say you don’t do this. So you take the departmental approach and you push your tech com content through your tech com solution to the web and you push your KB to a KB article database thing and you have learning content which goes to a learning management system and therefore some sort of a learning platform. What happens when those are not unified? And I’ll, Alan, I’ll start with you. What happens with that if they’re not unified from a content point of view?

AP: Well, the terminology you’re using is not gonna be consistent or often is not consistent across your content types. For example, you go to your knowledge base, and you find a support article that uses a certain term for some widget. And then later on, when you try to search for the name of that widget and some other content, like on the product side of the content, and that product side uses a slightly different term, you’re not gonna get a search result because they’re using different terminology for what is really the same exact thing. So you have that lack of alignment. And the same thing is true, for example, with your product content and your training content. You may have slightly different how-tos or tasks to accomplish the same exact thing. So you’ve got those contradictions there in how to do things, in terminology, and you’re not getting a consistent voice at all in what you are presenting to your customers because of these departmental silos that we were talking about.

SO: And then Bill, on the infrastructure side, what do you see there in terms of problems that surface?

BS: A lot of it comes around or comes back to user experience, you know, because all these tools have very, I guess, a targeted focus. They have a lot of custom feature sets that are built just for that type of content. And a lot of the more generalized features are built out in slightly different ways. And you don’t have a lot of, or you may have a lot of ability to customize, but generally they’re not customized for whatever reason. Either it’s too difficult, no time, one group likes it one way, one group likes it another way. So you have these disjointed user experiences, just going from one area of the website to another. So being able to navigate manuals online to going over to a knowledge base and seeing a completely different interface and not knowing how to navigate it out of the box. So you’re now asking your customers to learn how to use your content in addition to having to use your content to find information in the first place.

SO: So we’re, I mean, we’re doing a lot of complaining, right?

BS: It’s fun to complain.

SO:  It is fun to complain. But I guess as consultants, our job is, in fact, to take on the complaints and then come up with a solution. So in the absence of the magic system that does all the things, you know, one thing we’ve seen a lot of customers do is make that compromise where they say, okay, we’re gonna take the thing that’s optimized for A, but we’re gonna use it for A and B even though it’s suboptimal for B. And of course, then the B people feel like B-class citizens, which isn’t great, but enterprise-wide, it’s very, very helpful. On the taxonomy side of things and some of these others, it does feel as though you can build that over the top and then just integrate it into all the other tools and push it down onto those. So I guess that part’s okay-ish. But I mean, what does this look like? And I guess my question to both of you is what’s the solution here? I mean, what’s the path forward and where do we want this to land? I mean, for our personal gratification, but mostly for our customers. What do our customers need the solution to look like so that this is, infamously, the line is you don’t want to ship your org chart, right? You don’t want your website to be a reflection of your org chart at a level that is recognizable to the end customer because, again, they don’t care. So what are some of the solutions here? What are some of the options that people have?

AP: Well, I think one thing you’ve got to do and step back and realize this is not just a tech problem. Now, the tech problem is very real in regard to the silos because you’re using different sets of tools, especially on the authoring side and the content creation side to get things done. But I think all of those content creators need to step back and think a little more globally across the company and not just about this is just for my people, this is just for me. Need to take a bigger step back and think, how can other departments potentially use this information? And then you start getting into tech, how can they actually reuse it? And that’s where you slip away from more culture to tech and how it can enable that sharing and that reuse.

BS: Mm-hmm.

SO: And some of the things like terminology is a good example. If you standardize terminology, you can ask people to follow that across all their systems, right? Like use this term and not that term does not require a unified, you know, content management solution. It’s just a writing practice. And you could layer the terminology management over the top of multiple systems. I mean, it’s more expensive, but you could. Bill, do you have any hope?

BS: Mm-hmm. There’s always hope. You know, we’re starting to get there and especially as, you know, at least systems are starting to be able to somewhat talk to each other via API. So there is a way to share information across. It’s not a, it’s not what I would call anything remotely close to, you know, intelligent reuse, because you’re still duplicating content from one system to another. But at least if you’re consistent about writing in one place, and pushing it out where it needs to go via those hooks, then it’s better than authoring everything separately.

AP: You still have a single source of truth in what you’re talking about and that’s the end goal or it should be the end goal for this problem.

BS: Exactly.

SO: And it might be helpful to look at single source of truth less as the process of doing a task, like how do I change my password in a database, right? There’s a four-step or a two-step or one-step procedure, but there’s a procedure and there’s only one way of doing it. And I think a lot of times the ultimate solution to this is to do some, essentially, forensics on where does that information originate. And if it originates here and I am a downstream user of that information, that’s fine. Just don’t ever modify it. Always go back to the source of the information and modify it at the beginning and then flow it back through. The problem that arises is that in a scenario where flow it back through involves manual processes or copy and pasting, it’s always going to fail because people fail, right? People don’t do the thing. And so you get those inconsistencies and now there’s four different ways of changing your password. One in the tech docs, one in the learning and like two in the knowledge base. And now what do you do with it?

AP: And you’ve got frustration among your users because they’re getting inconsistent information. And then you’ve got frustration with your content creators because they constantly feel like they’re having to go hunt for something or it is not worth my time to go find it. 

BS: Mm-hmm.

AP: I’m just gonna copy and paste and then they forget to update one of the umpteen versions they have. And then they’re stuck in this constant go go go process so it’s bad on both sides of the content equation for your content creators and the people who were consuming that content as well.

SO: Okay, well, this is super encouraging. And with those helpful words from Bill and Alan and maybe me, but mostly them, I will leave you to it. And so with that, thank you for listening to the Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post The challenges of content operations across the enterprise (podcast) appeared first on Scriptorium.

We’ve seen this before, right? It’s the gold rush. There’s a new opportunity. There’s a new possibility. There’s a new frontier of business. And typically, the people who make money in the gold rush are the ones selling the picks and shovels and other ancillary services to the “gold rushees.”

— Sarah O’Keefe

Related links:

• “Put an AI on it” meme
• AI business viability (gift link)
• AI and GDPR
• AI and mushrooms (gift link)
• AI in the content lifecycle (white paper)

LinkedIn:

• Sarah O’Keefe
• Alan Pringle

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Alan Pringle: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re checking in on the state of artificial intelligence. Things are moving really fast in the AI space, so we want to let you know we recorded this podcast in May of 2024. Hey everyone, I’m Alan Pringle.

Sarah O’Keefe: And I’m Sarah O’Keefe, hi.

AP: And we’re going to talk about AI yet again, but we need to circle back to it because it’s been a while and kind of assess the space right now. Last week I saw a really great meme. It was a still of Carrie Brownstein and Fred Armisen from the Put a Bird On It sketch from Portlandia. And it said, “Put an AI on it!” And that’s kind of where we are now.

SO: Yay.

AP: So many companies, so many services, so many products look at this AI thing that we’ve got now. And a lot of these AI birds, if you will, have landed on content creation, kind of our wheelhouse. So let’s pick that apart for a minute.

SO: So I guess we can start with generative AI, GenAI, which is a ChatGPT and all of its general ilk, right? The chat interfaces. And generally speaking, at least for technical content. There does seem to be an emerging consensus that this is not where you go for content creation. You’re not going to start from scratch. Now, maybe you get it to throw out some ideas. Maybe you can do a first draft, but overall, the idea that, you know, ChatGPT or generative AI is just going to generate your docs for you is not the case. So there’s a big nope on content creation, but there’s also a big yes for productivity enhancement. I wrote a draft, but did I write it at the appropriate seventh or eighth grade level? Can I run it through the AI and let it clean it up? I need a summary. I need this cleaned up. I need my XML tag set corrected. I need a proposal for keywords that metadata that I haven’t put in yet, those kinds of things. So there does seem to be a rising level of capabilities in that space, in that productivity enhancement, how can I take this thing that I wrote or that I created and refine it further to get to where I need to be.

AP: Yeah, I was at a conference a few weeks ago, and in the expo hall, so many of the vendors were selling an AI service or some kind of AI add-on. And my thought was, how can the market possibly sustain all of these new products and new services? And I know there was an article in the New York Times last week that was talking about the business viability of AI. And it really doesn’t matter how cool or neat what your AI tool does. If there’s not business viability behind it, you’re going to have a really hard time in the marketplace, because you’ve got so many established players like the likes of Google and Microsoft who are really starting to dig into AI, and does it leave room for anyone else? So part of me wonders, is this going to help some vendors, hurt some vendors, or some vendors just going to go away at some point because of this tussle with AI features?

SO: Well, I mean, we’ve seen this before, right? And it’s the gold rush. There’s a new opportunity. There’s a new possibility. There’s a new frontier of business. And typically, the people who make money in the gold rush are the ones selling the picks and shovels and other ancillary services to the “gold rushees.”

AP: Exactly.

SO: And so to me, I’m starting to think about this as it’s going to fade into the background eventually in the sense that it would not occur to me at least to write a document without a spell checker and/or, you know, some sort of built-in grammar checker. They’re super useful, but I don’t necessarily do exactly what they tell me at all times. I look at what they tell me and then I use my own judgment. So I think that’s where we’re going to land where AI is going to be this useful tool that sort of a little bit fades into the background and that has human review. And we’re starting to see people refer to human in the loop, just as we did with machine translation, which is another place where you can look for patterns. What is AI adoption gonna look like? Go look at machine translation. Sometimes it’s good enough, sometimes it needs a human in the loop. Sometimes if you’re translating, let’s say, literary fiction, it’s maybe not that well suited, because it’s just not going to pick up on the kinds of things you need to pick up as a literary translator.

AP: Yeah, yeah, I agree. Is this going to be a feature that you accept as part of whatever suite of tools that you’re using? It’s just built in and there it is. So let’s talk now about something a little more complicated and I think maybe a little more dangerous with AI and that’s intellectual property. It has always been a problem, and there are all kinds of lawsuits flying about with different content creators claiming that different AI engines are stealing their copyrighted content, that sort of thing. And I don’t think that haze, that cloud has really been removed at this point. It’s still a problem that we need to address.

SO: Yeah, it’s a huge question mark. And, you know, it’s terrifying from the point of view of if I use AI and the AI injects something into my content or into my code that is that belongs to somebody else that’s copyrighted by somebody else. What’s that going to look like? What’s going to happen? And I have seen, you know, differing opinions on this from all sorts of people in our industry, in adjacent industries, from attorneys, non-attorneys, everybody has an opinion on this. And the thing is that the responses are, they just run the gamut from, do not use under any circumstances because we could get ourselves in trouble to eh, whatever, YOLO, it’ll be fine. I saw a comment just the other day along the lines of, well, I can’t believe that people would get sued for this because everybody’s doing it essentially. And I mean, they might be right. I’m not saying they’re wrong, but remember Napster? I mean, they got taken down. 

AP: Yes, they did.

SO: We now have streaming and those kinds of things, but the original one that was kind of the unlicensed in a pirate version, really, did get taken out. And I haven’t the slightest idea whether the regime that we’re under right now is going to end up like, you know, a Napster or like a Spotify. Not a clue.

AP: Yeah, yeah. And this conversation on IP intellectual property kind of ties into something else I’m going to talk about too. And that’s the regulatory angle. Different governments are taking a look at this. And I think that’s absolutely worth discussing as well.

SO: Yeah, again, I think more questions than answers, but just in the last, say, two months, the European Union has passed an AI act, which divides AI into risk categories based on what kinds of things it is doing. And so they’re banning certain kinds of AI, they are regulating certain kinds of AI, and then they’re allowing certain other kinds, you know, but they’ve basically said, if it’s in the highest risk category, then you have to follow these kinds of rules, or maybe it’s not allowed at all. China has taken a different approach. The US has so far done nothing in terms of regulations. 

AP: Nothing.

SO: We’ve talked about it, but we haven’t done anything. So it’s quite likely that at least in the short term, the regulatory schemes will be different in different locations, in different countries. And then just in the past week or so, I bumped into a pretty interesting article that was talking about GDPR, the European Privacy Regulation. And basically, under GDPR, you have certain kinds of rights. You have the right to be forgotten. You have the right to be taken out of a database, and somebody has anonymously sued OpenAI because when they go into OpenAI and they say more or less, “What is my birthday?” It gives them the wrong answer. So this is apparently a, again, anonymous but public figure, and we’ll put the article in the show notes. So this anonymous public figure is suing AI on the grounds that it reports an incorrect birthdate for that person and you have the right to have your data be correct under GDPR. Well, OpenAI’s response to this lawsuit is along the lines of it is impossible for us to correct that, right? Because there’s not an underlying database that says John Smith date of birth X. It’s just generative, which is sort of the crux of the whole issue here. But the legal footing, the legal argument appears to be that under GDPR you can’t say, oh, I’m sorry, it’s impossible for me to correct that fact. So you’re just gonna have to deal with it. And so we’re gonna have a really interesting collision between the content that generative AI creates, which may or may not be factual. That’s not a thing, right? And GDPR, which is an established law. And I have the slightest idea where that’s going.

AP: Yeah. And I think too, in this vacuum or with this absence of regulations in some countries, you’re going to see companies then make their own rules. And a lot of them have telling employees when they, what they can and cannot do with AI, which really, like I said, in the absence of there being any kind of rules to help kind of create a baseline, it makes sense, especially if you’re trying to be very careful about liability, putting out incorrect information or using copyrighted information that you shouldn’t be, it would make sense for you to protect your bottom line by basically instituting your own guidelines for how you can and cannot use AI.

SO: And if you look at social media where the platform is basically not responsible for the content that people are putting on it, right? So if I’m on LinkedIn, let’s say, and I put something on LinkedIn and then somebody else reads it, if what I’ve said is problematic, they’re gonna sue me, not LinkedIn, right? LinkedIn is not responsible. And with AI right now and generative AI, who’s responsible? If I go and I generate something using generative AI, and then I publish it in some way, and then I guess I assert copyright on it, which is a whole other can of worms because I can’t right now under current law. But if I do that, then if what I post is wrong and legally problematic, so it’s, I don’t know, defamatory or something, then like who gets sued? Do you sue OpenAI for being incorrect? Do you sue me? Do you sue the platform I put it on? Like who is responsible when the AI gets the content wrong? Is it me because I didn’t validate it or correct it or clean it up? If we build out a chatbot that’s AI-driven, that’s generating information and you know, we’ve already seen this use case legally. You know, the company is going to be responsible for the information that the chatbot is putting out if the chatbot is sitting on the company website. But if it’s impossible to be sure that the chatbot’s gonna be right, what do you do with that?

AP:  Yeah. And it’s been established as of last night before we recorded this, the big Met Gala happened. And apparently there were two quite realistic photos or images of Katy Perry in two different dresses. How she pulled that off, I don’t know, at on the steps at the Met Gala. So and the problem is a lot of the social media platforms absolutely could not, they just didn’t do anything. These photos just exploded. 

SO: Right. Because they were fake, right?

AP: They were fake. 100% generative AI fake. And even her mother was fooled by it, apparently. And Katy Perry’s response was, “I was working, so no, I was not there.” But it just goes to show you that you’re right. Once these images got out there, they exploded on social media, and those platforms really are not equipped to handle flagging of that or even removing it at this point.

SO: “I didn’t know you were going to the Met Gala.”

AP: Exactly.

SO: Yeah, I’ve seen a decent number of it largely in AI news coverage where, you know, a New York Times or Washington Post will put up an image and they’ll put a slug on it or a caption that says this is AI-generated. And usually, they watermark it. So it’ll be actually in the image, not on a caption below, but in coverage of AI itself. And for example, talking about this deep fake or, you know, the one where the Photoshop UK princes, princesses, that one. They carefully labeled the photo itself as altered on the photo so that people would know when they were reading the news story what they were dealing with. But of course, you know, that’s not going to happen on social media, where it’s just going to fly around the world faster than anything. And so, yeah, I think I don’t know. I mean, I’m saying I don’t know a lot. That’s where we are. We don’t know.

AP: We don’t. Yeah.

SO: We don’t know what’s going to happen. Things are changing very quickly. The legal and regulatory and risk scenarios are completely unclear. I did want to touch on one other sort of more practical matter. We’ve seen a lot of complaints recently, and I think I’ve experienced this personally, and I think you have as well, that search, like Google search, Bing search, all the traditional search is actually getting worse. 

AP: Oh, 100%. Yeah.

SO: You search and you get bad, you know, just junky results, and you can’t find the thing you’re actually looking for. And the basic reason that that’s happening is that the internet, the worldwide web has been flooded with AI-generated content at a scale that has completely overwhelmed the search algorithms, such that they are unable to sort through all this stuff and actually give you good information. I mean, we did at one point, a year ago, have a scenario where if you had a pretty good idea of what you were looking for and you typed in the right search phrase, you would get some pretty decent results and you could find what you were looking for. And now it’s just junk, which has to do with AI-generated content that is micro-targeting SEO phrases. And ultimately, I think this means, well, it’s going to be a war between the search engine algorithms and the AI-generated content. But I suspect that search and SEO as we know it today is done because it won’t win this. And then people are like, “Oh, I like it a lot better when I go to ChatGPT, and it gives me this nice conversational paragraph of response,” notwithstanding the fact that that paragraph of response probably isn’t super accurate.

AP: But it’s so chatty and friendly.

SO: Uh-huh. So I’m not terribly optimistic about that one either. And so what does this mean if you are a company that produces important and high-stakes content, like all of our clients, basically? What does that mean to you? And I think it means that you’re going to be looking hard at a walled garden approach, right? To say, if you are on our site, and you are behind a login on our site, we have curated that information, we have vetted it, we have approved it, and you can rely on it. If you go out there, you know, in the big wide world, there’s no telling what you’re gonna find out there. And that implies that I have to know who I’m buying from so that I can go to the right place and get the right information. And I’ve already found myself doing this. Instead of going to a big general purpose, e-commerce buy things site, such as the one I’m carefully not mentioning, I find myself saying, oh, I need a new stand mixer. I like KitchenAids. I’ll go to their site and buy it there. And so I’m buying direct from brands that I’m familiar with and that I know because that feels safer than going to the great big site that has a little bit of everything, including a stunning array of what seems to be problematic counterfeit and or knockoff kinds of things. So instead, yeah, but so if I don’t know the brand, if I don’t know the brand, then what? Like, how do I find the right thing if I don’t know where to start already?

AP: The same as true of information. Right. Yeah, I don’t think that’s going to be fixed anytime soon and it’s probably going to get worse after this podcast, in fact.

SO: So I’m concerned. Yeah, and you know, as a parting gift of, I guess, fear, we will put it in the show notes using a gift link. But there was an article that appeared in the Washington Post about a month ago, maybe two, having to do with apps for identifying wild mushrooms when you’re foraging. So this already seems kind of like a high-risk activity to me, just generally going out in the forest and looking for mushrooms that you’re going to forage and hope you get it right and you pick the really delicious one and not the one that’s gonna kill you. And Alan’s making faces at me because he hates mushrooms.

AP: I have the solution for this problem. Don’t eat them. But that’s not helpful. Yeah.

SO: Yes, you have a really simple solution. But for those of us who do like mushrooms and don’t want to die, there are a whole bunch of apps out there. And so there was some research done in apparently Australia on mushroom identification apps, which are apparently AI-driven, which seems like kind of not a good idea. However, what they found was that the best of the AI-driven apps was 44% accurate. And I wish for my mushroom identification app to be a whole lot more than 44% accurate, especially in Australia where everything kills you!

AP: So a 56% chance of poisoning yourself. That’s excellent. Great.

SO: Yeah, or at least of getting it wrong. But again, it’s Australia. And so if it’s wrong, it’s probably going to kill you because that’s Australia. So yeah, that’s not good. And that feels like a not acceptable outcome here. So I don’t know where this is going, but I am pretty concerned.

AP: Yeah. So as we wrap up, there are some good things to talk about, especially, there are a few. Sarah was whispering, “Are there? Are there?” Or made a face. There are, I mean, on the content-creation side, I think there have been some tools that have added some useful features, much like the spell-checker analogy that you talked about. But there are still so many unanswered questions in regard to intellectual property and legal risk. All of those things are still way up in the air. A lot of countries are trying to adjust by taking a look at regulations, but you know, those aren’t in place yet. So we’re in, we’re at a crossroads, I think, and we’ve still got to pay a lot of attention to what’s going on with AI right now.

SO: Yeah, you know, there’s some really, there’s some really nifty tools out there. It’s also worth pointing out that there have been tools that use machine learning and AI that are already out there. They just weren’t, it wasn’t AI front and center. Now everything, as you said, put an AI on it because you can get sales that way, and you can get attention. But there are a lot of companies that are doing some really interesting and really difficult work with this. And I want to, you know, I’m not against any of this stuff. I just want to make sure that we use these tools in a way that, you know, maximizes the good outcomes and minimizes the, “Oops, I ate the wrong mushroom.”

AP: Yeah. Fatal mistakes. Not a fan. Not a fan at all. Well, I think we’ll wrap it up on that cheery note about eating poisonous mushrooms on the Content Strategy Experts podcast. We go places, folks. We will talk about almost anything on this, not just content. So thank you for listening to the Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Pulse check on AI: May, 2024 appeared first on Scriptorium.

I think that this comes back to the same thing that it came back to at every technological shift, which is more about being ready with your content than it is about having your content in the perfect format, system, set of technologies, or whatever it may be. The first thing that I think either of us will say, and a lot of people in the industry will tell you, is that you need to structure your content.

— Patrick Bosek

Related links:

• Heretto
• Content Components podcast by Heretto
• AI in the content lifecycle (white paper)
• Content paradox: Standardization = personalization

LinkedIn:

• Patrick Bosek, Heretto
• Sarah O’Keefe, Scriptorium

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk with Patrick Bosek about the changing role of content in self service and whatever the opposite of self service is, maybe just service. Hi, everyone. I’m Sarah O ‘Keefe, and I’ve got Patrick Bosek, the CEO of Heretto with me today. Hey, Patrick!

Patrick Bosek: Hey Sarah, it’s good to be here. I guess to be back, technically.

SO: Yeah, you’ve been here one or two times before, so I’m going to cut to the chase here. And our topic today is self-service content and how things are changing in self-service content. So talk a little bit about that. What’s going on?

PB: Well, I think to talk about self-service content, we have to talk about what’s changing in, I think, self service more generally, which you kind of alluded to in the idea of, you what is the opposite of self service, right? So the landscape is, as I see it, is very interesting today, because historically we had what was very obviously self service, and then what we had was very obviously not self service. So I guess just people or service or something—people service maybe. And for the most part, self service was content, right? So if you went someplace and you read something and you figured it out on your own, over the last decade or so, self services started to involve a little more action. You can go to a McDonald’s and self-service order a coffee today. We can talk about it in a minute whether or not we think that’s a good idea or a bad idea. But now as we’re getting into the age of true…intelligent, if you want to call them, virtual assistants, AI, those types of things. Now we’re in a place where the things that were very traditionally handled by humans. So helping you figure out what you really mean, helping you dig through something when you’re not exactly sure where you’re finding, finding it, or if it is possible, those types of questions are actually performing actions. Some of those are going to continue to bleed over into systems. So now self service isn’t just content anymore that you go and look up and then you yourself go and figure it out and do something. There’s going to be this mixing between these two things where the service that’s provided by automated systems is going to perform some of the things that humans were performing. They’re going to need a bunch of content in order to be able to do this properly. And probably also as instructions, you’ve got to teach these things what to do somehow. And as we all see with the way that we interact with them, you use words, you don’t use programming languages as much. So content plays a role in its traditional form. It continues to play a role in training people. It also plays a role in establishing what this new generation of systems that are going to help us perform actions and learn things and answer questions, what those things are going to do.

SO: So it feels like we’re adding another dimension to this, because when mobile apps first came out, the big development there was that they were contextually aware. So you can get your app to tell you what the weather is at your location because it knows where you are or it can know where you are. And it feels like this is a similar kind of thing that some of this is more a matter of not just, “Hey, here’s a page with some instructions,” but rather, you know, let me, let the system do some work around what your context is and what some of your knowledge is and adapt accordingly.

PB: I think there’s absolutely an aspect. So I would actually put that in the category of just like maybe even traditional personalization. You know, feed metadata in those are things about yourself and then you perform some type of a matching or a computation. And then you feed content back. So that’s, that’s effectively personalization out of its core. Like here’s some things about me. Okay. Then those match to some things about the content. Give me just the content that matters to me. I think where this starts to become new and really interesting is where you start to have systems, so probably, you know, AI-based systems that are actually not just like filtering or personalizing content, they’re actually manipulated in content or they’re manipulating your journey with the content. And one of the places that, you know, we are seeing more of that I think is an interesting place for this is in learning. So you start to think about how learning systems and self service have worked for a long time. And as much as there’s been like micro learning content, and then there’s been more organic things like that kind of stuff, by and large learning has been linear when it comes to self service. Here’s a guide, here’s a course, whatever it may be. And it didn’t matter if you didn’t need to know a good chunk of it or if you already knew a good chunk of it or whatever it may be. Like you went through that, right? That’s how that works. So that, I mean, it’s how colleges, college courses work. It’s how, it’s how learning works in general. Like unless you’re sitting across from a tutor, like learning is linear by and large, when it’s being taught. Well, with AI, all of a sudden we can deploy systems at scale potentially where you can always be sitting across from a tutor. The entire paradigm around how it is that we, you know, air quotes here, “self service,” if we still want to call it that, the things that we need to learn can fundamentally change.

SO: So what does it look like for us sitting in the content universe when customer experience is moving in this direction towards this, I guess, more sophisticated self service? Not just here’s what we have, deal with it, but rather here is information or learning or a chunk of content or whatever that is adapting to that person’s requirements. I think it is, right?

PB: In certain circumstances, it certainly has the ability to be adapting to people’s requirements. I think that’s the thing that we will absolutely be seeing. But more generally, what does content need to look like to give you the range of things you might want to do as an organization in this new paradigm? And I think that this comes back to the same thing that it came back to at every technological shift, which is more about being ready with your content than it is about having your content in the perfect format or the perfect system or the perfect set of technologies or whatever it may be. So the first thing that I think either of us will say, a lot of people in the industry will tell you is like, you need to structure your content. And I do think that the story for this on the learning side, on the traditional self service side, on the AI-agent side, and I think even on the people service side of things still does start there. But I don’t think it’s because self service is intrinsically something which is powered by structured content. What I think is that structured content really just gives you, the organization, you, the content creator, a lot more control over what goes into these systems no matter the range of intelligence that they have. And that means that you have input control on the experiences. And as we all know, LLMs, even when they’re backed by like RAG, retrieval augmented generation, or other systems that are meant to kind of keep these things fenced in, they’re black boxes. And the bigger the box, the blacker the box. So, the strategy, if you look out over the industry, there’s a lot of very sophisticated stuff, but some of the stuff that works the best is input control. And that’s where I think that structured content is really gonna be a key element of this, no matter how far in the future you look.

SO: Yeah, and I mean, my explanation of this to people, which I’m sure makes the actual AI experts cry, is AI likes patterns. And so if you feed it content that follows consistently the same pattern, you greatly improve your odds of getting good output from what you’re putting into the system. When you have stuff that’s not well organized or structured or anything else, you know, garbage in, garbage out—you’re gonna get a mess.

PB: So I think there’s that is true. There are caveats, but the thing that remains true at the center of that is that if you don’t have very precise control over what goes in, you lose an enormous amount of control over what comes out. So even there’s, there’s such things like overtraining, right? Where you can actually get AI that will produce, less high-quality results with certain quantities or certain types of training. And what you end up with in those circumstances is that like, okay, well, if your stuff is just a bunch of stuff and you stuff it all into an AI system. 

SO: That was excellent.

PB: It’s good, right? I gotta have some fun. So you don’t have any ability to say, okay, well, these pieces really, these are the ones that are impacting our outputs. Let’s pull this out, or even just iterate in an intelligent way. So, which part of the corpus, which part of the things that we put into this system are the ones that are having the negative impact? Retraining becomes a much more complicated process. And at the same time, when we’re looking out over deploying across multiple experiences, right? So, you know, let’s take the learning and reference. So, you know, probably speaking documentation portals, whatever they may be. Some people call them knowledge bases in certain circumstances. Those are the two obvious things, because in the past they’ve been highly bifurcated, even though they use a lot of the similar information underneath the hood. Well, if you’re trying to build AI-backed much more like personalized learning systems. Well, you can’t have the content in those systems being different than the reference content, because when you go and you look at the stretch of things that go into that stuff, well, if you have the AI system telling your, user something which is wholly inaccurate. And you can’t pull it back to the rest of the stuff that’s published on the internet, you can get highly divergent results, and you could end up in a circumstance where you have no ability to actually deploy these things properly. So you can’t have one set, which is very cottage based, like, you know, we will go in and we craft these things and one set, which is highly structured. And then you power all of the learning, the intelligent learning systems of the structured stuff, because it’s going to be easier. So you have to find a way to pull these things together, and then use the mechanisms underneath the content to put the right inputs into the right places.

SO: And we’ve been talking for years and years and years about problems with silos and how they’re an outgrowth of the organization itself, right? You’ve got a learning organization and a documentation organization and a tech support organization. They’re all producing content into their respective silos. And the question becomes, if organizationally that’s what the company looks like, then it is almost impossible to rip those silos apart or put them together, destroy them to collaborate across them because the org chart doesn’t encourage it or even makes it impossible potentially. And so then you’ve got different terminology being used by the same company but in different departments, which is really common. And then what? So we’re back to, you know, the fundamental truth that when you have a website as a company, even if you segment that website into like, oh, learning.xyz.com and docs.xyz.com and KB or support.xyz.com, your customers don’t care, right? I mean, they’re not interested in the fact that you have three separate organizations that all hate each other. That’s just not on their list of things they care about.

PB: So I mean, this goes back to the classic, like don’t ship your org chart, which is, yeah, obviously, right. So obviously we’ve been doing this in content for ever, basically. I do think that it’s gonna be, we’re gonna be forced to change because, you know, again, you go back to the idea of like, if you contradict yourself in your learning content and your docs content and it’s being read as written or as built and presented to a human being. Human beings are incredibly flexible creatures. We can go in and be like, oh, well, okay, fine. So like they didn’t update that piece, those dummies, they should have done this, but I understand what’s going on. But when you put an abstraction layer over that, now you have a system that just basically does what it’s told, you know, by and large, or understands what it’s, what it’s educated in, and what it’s told, it’s not going to have that same intuition. That’s a very human thing, even at this point in time. I don’t, I don’t really see the current generation of LLMs getting to a point of having that style of intuition. I mean, the thing that just happened with the ASCII art is a great example, right? And it’s a little bit divergent here, but bear with me. So people figured out how to hack these AI systems by going and asking them questions with ASCII art, which in one sense shows their brilliance because they’re able to understand it. But in the other sense, it shows their lack of intuition because they were like, oh, well, this doesn’t apply to my rules. Who cares? Right? And whereas a human being would have been like, oh, I’m still not allowed to talk about bombs. Right? It doesn’t matter if you’re in a theater, if you write, don’t yell bomb in ASCII or in Sans Serif, people understand that it’s still talking about the same general concept. So this is the same thing that you run into where you can’t have these discrepancies and stretch a single system over the top of these. And you can’t have a really strong customer experience that properly educates people, properly answers questions, and all those types of things, unless they’re joined together.

SO: Yeah, apparently in addition to ASCII art, if you use Morse code, that will also work around all the guardrails, which sounds fun. So, okay, so in our couple of minutes that are left here, how does Heretto and CCMSs in general, but Heretto specifically, how do they play into this?

PB: Yeah, sure. So that’s a great question and one I appreciate you asking it for obvious reasons. I’m going to answer the CCMS part first, then I’m going to answer the Heretto part. So CCMSs as platforms, and I think this is probably true for pretty much every major CCMS in the industry or in the space. They’re going to give you the ability to manage more structured content at a higher velocity and a higher level of governance. Now they’re all going to be able to do this, you know, to different efficacies, right? So some are going to do it better or worse for your particular circumstance. But broadly speaking, that’s why you buy a CCMS. A bunch of content, you want to be able to have your per author or per information developer content be higher than it is, and you wanna make sure that you have the proper amount of governance so that what you deploy is what should be deployed, right? It has to be good enough, it has to meet the criteria, especially today. So those are the things that you build into the process in the CCMS. And then, obviously, they help you track things like localizations as well, but I would broadly put that in the same bucket. So as we’re looking at, how does this relate to the future of the customer experience, you know, be it directly with the content or be it derived from the content through some intermediary system like AI. It’s the governance piece, and it’s also the quantity piece. You have to have enough to be able to answer all the cases to be able to touch all the learning points to be able to educate and guide these systems in all the proper ways. And now, because you don’t have that human intuition as your last fail save, the level of governance has gone up a bar. You have to be able to have much better governance on your content to be able to control inputs. So I think that this is a new age of CCMS. And it’s funny because we have seen an acceleration in interest from people and an acceleration in interest that’s educated where people are coming. And they’re like, we have to get this in order, because we realize that if we don’t have our hands around this, we’re gonna have a huge mess at the end of the toolchain. So I do think that people are more aware today, you know, it’s probably still relatively niche in the grand scheme of things, but there’s a growing awareness that the having the right systems in your content operations ecosystem to produce the right outcomes down the chain is gonna be critical. And CCMS for this style of content is 90% of the time gonna be the best place to start. Not to say there’s not other ways to get there. On the Heretto question, Heretto does all that stuff like the other CCMSs. Obviously there’s some aspects of collaboration and things like that that we think we do better. But I think the key thing as it relates to the future of these technologies that Heretto provides that you don’t really get in other CCMS technologies is our ability to efficiently and agilely deploy content into specific pods. So we have static publishing, we have the ability to generate HTML, PDF, all that kind of stuff, like all the other CCMSs. But we also have the ability to dynamically deploy content into an API layer where the content is in its own little pod. So you can kind of deploy as many little content APIs as you want. Most organizations have one big API that they deploy that powers an entire doc site. It can be tens of thousands or more, you know, topics. But you also have the ability to say, all right, I want to just deploy this here, and this API is only going to have this content in it. And that comes back to the critical aspect of the bigger the block box, the blacker the box as it relates to AI systems. So you don’t go hook your AI system up to the totality of, you know, your large API that serves your web experience or general web experience. You hook your AI up to this specific pod that only has these specific things in it. And therefore, you know exactly what’s going into that AI system, you know, be it for something that’s more like RAG-based, which is really just like search and summarize, I think it’s a much better name for it. Or BSL which is more training-based. So I think that’s kind of the critical piece that Heretto offers right now that is not present in other systems that, you know, relates to what we’re talking to today anyways.

SO: Alright, I mean, that seems like a good place to leave it, because basically you’re saying, hey, this stuff is coming. All these things are changing, and here’s a helpful roadmap for how to get there. Any closing words before I wrap this up?

PB: No, other than this is a really exciting time to be part of content. You know, we’ve both been here for a little while, and we’ve seen a lot of changes in this industry. But this is certainly unique. There is no doubt that the acceleration understanding and the change in the landscape over the last, you know, year, 18 months, I would say has been unprecedented. You know, I think you see that all the way from, you know, the types of experiences that we want to start deploying that we believe are possible, but we’re not totally sure based on new technologies. And then also the change in approach to things like learning content, seeing organizations suddenly starting to say, okay, so like PowerPoint is not our primary method of training people. Like our primary method of training people is going to be dynamic digital experiences. And we need to be prepared for that. And then whatever comes after that, you know, I think that this is a shift that, I’ve been waiting for, you’ve been waiting for, for a long time. I mean, like, for gosh sake, like we implemented the experience for DITA learning and training. What is it? One dot one or something like that, like 10 years ago. And we’ve had a couple of customers that have used it across that time, but it’s just been recently that we’ve had more and more people coming in and starting to use it. And there has, there seemed to be a bit of a Renaissance in the understanding around these things. So, I don’t know, this is just, it feels very new. It feels very fresh again, which I think is part of the structured content cycle. And this is the fun part of the cycle. So I’m enjoying it.

SO: Yeah, I would I would agree with that. So I’ll leave it there. Patrick, thanks for being here. Always good to see you. And with that, thank you for listening to the content strategy experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes.

The post Self-service content in the age of AI with Patrick Bosek appeared first on Scriptorium.

You really start to run into trouble when you need to make version two, and you discover a problem with version one. If I’m making some marketing materials, maybe I need to use some information from the engineering team or from the manuals for whatever product I’m marketing. I might just copy that information over and put it into my marketing materials. Then, when we go to produce our training for that particular product, we might say, “Okay, I need that stuff. I’m gonna copy that from wherever I can find it,” which might be from marketing or engineering depending on where I look and who I know better or which repository is easier for me to get to. The problem here is that if anybody has made any edits along the way, they have to ensure that those edits are propagated through all these departments. And that doesn’t always happen. 

— Chris Hill

Related links:

• Data Conversion Laboratory (DCL)
• Harmonizer by DCL
• Confronting the horror of modernizing content (case study)
• Training content paradox: Standardization = personalization

LinkedIn:

• Chris Hill, DCL
• Alan Pringle, Scriptorium

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Alan Pringle: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk with guest Chris Hill of DCL about learning content and where you can find redundant duplicated content, what causes it, and how a reuse strategy can eliminate that duplication. Hey everyone, I am Alan Pringle and we have a guest here today, Chris Hill of DCL. Hey Chris, how are you doing?

Chris Hill: Doing well, thank you, Alan. It’s nice talking to you.

AP: Great, yes as always. Chris, tell folks out there a little bit about yourself, DCL, and your role there if you would.

CH: Sure. DCL stands for Data Conversion Laboratory. And so we got our start doing data conversion, which is moving content between formats. And over the last, let’s see, that started in the 80s, if you can imagine a tech company starting in the 80s. 

AP: Yes, I can. I am of an age, yes.

CH: So since then, we’ve expanded out into lots of areas, but basically any kind of content transformation, workflows, content enrichment, all sorts of activities around content. So that’s our key theme. I joined DCL about four years ago, and I’ve actually been in the content management space for a good more than 20 years now, and have a lot of experience with both migrating from, you know, using tools like Word and such, and then moving into a content management system. I actually managed, product managed a content management system and then got into conversion. And as part of my job here, I oversee a product called Harmonizer, which is our tool for doing content analysis and specifically reuse analysis to find places where content is redundant, duplicated, and help users figure out what they need to do to improve that situation.

AP: Well, in this conversation today, I think we’re going to tap into all the wisdom that you bring to the table with your background and content and your experience at DCL identifying reuse. And let’s start with just the concept of redundant content. And there are lots of ways to describe this. And I’ve heard it referred to several different ways. Redundant content, duplicated content, overlapping content. If you would kind of give people a bird’s eye view of what we’re talking about here.

CH: So we’re really talking about any place where you’ve got similar or exactly the same content reproduced. And you usually know you’re doing this because anytime you hit that Control C and Control V or choose the copy paste menu, if you’re a menu person, anytime you’re doing that, you’re creating redundant content. And, you know, it’s usually the easiest way to get it done if you’re working in a tool like Microsoft Word or a word processor or a desktop publishing environment or something like that. Generally, you copy stuff from one document to another. And that can be fine for version one of those documents. Where you start to really run into trouble is when you need to make version two, and you discover a problem with version one. So if I’m making some marketing materials, maybe I need to use some information from the actual engineering team or from the manuals for whatever product I’m marketing. I might just copy that engineering data or whatever information over and put it into my marketing materials. And then when we go to produce our training for that particular product, we might say, okay, I need that stuff. I’m gonna copy that from wherever I can find it, which might be their marketing or it might be engineering depending on where I look and who I know better or which repository is easier for me to get to. And the problem with that is that if anybody’s made any edits along the way, they have to ensure that those edits are propagated through all these departments. And that doesn’t always happen. 

AP: It usually does not happen. You’re being kind.

CH: Yes, I am. So when the engineers find out, oops, we made an error here in the technical manual, we better fix that or somebody is gonna do the wrong procedure or come out with a bad result, they might fix their manual, but. Are they aware that there’s all this marketing material with that stuff in it? Are they aware that the education team actually copied the stuff from marketing? They may not have even talked to the engineers to tell them they were using that content. And so what happens is you pretty soon have a sort of information entropy where things start to go fall apart and the information gets out of sync and you may have inaccurate information through various departments that no one can really trace. So that’s kind of where I see this grow and it’s pretty much a natural feature of using computers and the more traditional desktop application approach to creating content.

AP: Absolutely, and you’ve really kind of covered the big picture here really well. And what I want to do is kind of move just a little bit away from that and talk now about, especially for people in the learning and training space, where they might see some of that content overlap. And you’ve kind of touched on one. Anytime that you have a new version of the product or service that you are creating content for, it’s very common to just copy and paste the previous version, create a new file set, and then make your edits and updates in there. There’s one scenario right there where you have used copy and paste, and there’s a very good chance there’s a lot of overlapping information between those two versions that probably really should be maybe one set of files instead of duplicated content. So that’s one example I can think of immediately off the top of my head. Where are some other places where learning and training people might see this duplication of content?

CH: Yeah, so, well, the copy and paste happens for a lot of different reasons. Sometimes you’ll have product diagrams that somebody has or engineering schematics or something like that that need to be part of multiple divisions. And you’ll see that stuff sort of get copied around, if you will. I think you make a very good point about new versions of the product or because even, even in the case where you wrote perfect content the first time, if you ever could do that. And I wrote it perfectly well for the current release of the product. When the product is upgraded or changed in some way or a new revision is released. When you make those changes, that doesn’t mean all the old product disappears. People are still accessing that older content.

And if you start to find issues in the older content that get addressed maybe through your user support, is that getting pushed up to the newer stuff? Because if the newer stuff did what you described, which is I copied it, I may not even know that that’s now inaccurate in the new release of the manual. Or vice versa, it could be someone using the new product who identifies a problem with our documentation, and we go back and we neglect to fix the old ones, well then all the users of the older product are going to run into that issue sooner or later.

AP: Yeah, and then you’ve got this whole layer too. What if you were delivering to all of these different delivery targets, different delivery formats, you’re using Microsoft Word over here to create perhaps more study guides or scripts or something like that. Then you’re also using PowerPoint over here to create slides. You are copying and pasting perhaps into some kind of software. That will help you with simulations or more audio video kinds of things. So in addition to what you and I’ve just talked about with the different versions, how those are out of sync, if you were copying and pasting content into all of these different tools that create these different delivery types, then this problem is multiplying rapidly because you’re gonna have to go in and touch all of that source for all of those different delivery targets; your Word files, your PowerPoint files, your Articulate content, whatever else. So it kind of can explode pretty quickly in your face.

CH: It sure does. And we haven’t even touched on if you’re in different countries translating to different languages, what do you do about all the translated content? And that can quickly overwhelm you as well.

AP: Exactly. Yeah, so basically this problem becomes exponential, both from say, the versions of your product to service, across the different delivery targets that you’re dealing with. And then if you have to localize that content, all of the, shall we say, bad behaviors that are in your, or let’s call them inefficient behaviors, that’s less judgmental. 

CH: There you are.

AP: Yeah, less judgy. These inefficient, behaviors are then duplicated in every single language that you crank out. So yeah, it’s very ripe for inefficiency. It’s very ripe for errors because it is unfair to expect a human being to go through and keep track of all of this. So things go sideways and you even touched on something else a little earlier.

CH: For sure, yes.

AP: And then in some cases, you are pulling content from other departments, other content creating groups. And then that’s another layer of this exponential explosion where if you’ve changed something and someone quote, borrowed that from your group, are you sure they’re gonna know that you changed that? Or you fixed it when they copied and pasted it into their version? And then think about the poor end users, the content consumers who were getting this information they’re probably not getting a consistent picture at all about what you’re talking about because of all this copy and paste all over the place. It’s a mess. Yeah. So let’s go on and try and put a more positive spin on this mess and start talking about the process for identifying this duplicated content. 

CH: That’s good.

AP: So what can people do to start kind of taking the pulse of this problem?

CH: I think a lot of it depends on your resources and your organization’s commitment, but there’s always things you can do, whether they’re smaller efforts or larger efforts. So, you know, at the very BMW view or let’s say Cadillac view, if you’re from the 80s like me. You would probably have a huge budget to be able to implement a whole new set of tools and workflows that allowed you to use all sorts of technologies to do what’s called single-source publishing. And that’s where you author in a format neutral format. And then you take those pieces and really you’re creating sort of Legos of content, you could imagine.

AP: I call them puzzle pieces, so yeah. Yep.

CH: There you go, puzzle pieces, Legos. And they fit together in lots of different ways. You can put them together for training. You can put the little pieces together for your user manuals. You can put some of the pieces together for your marketing materials. But the key is that you’re using the same piece in all of those places. And what these sort of advanced tools allow you to do is keep track of all those pieces. Use those pieces in all those multiple places and then still create your deliverables out of those pieces. So instead of authoring directly in PowerPoint when you’re writing a course or writing in Word when you’re writing a manual or maybe working on HTML when you’re creating your website instead of creating content in those sort of single-use formats you create your content in a neutral format and then you have it output to those formats. 

AP: Exactly.

CH: And so you still can deliver those end formats that you need to actually put out in the world, but you’re doing it from a single source of truth. And that’s that single content repository. Now that’s the ideal, that’s the perfect one.

AP: Yeah, and you’re not, and you are not going to get to what you just described overnight. You are not going to snap your fingers and that’s going to happen. So yeah, I think you’re headed kind of where my brain was. And that is you can start small with this and you don’t even have to think about tools. You can start very small and start thinking about, you know, where is this duplicated information? Just trying to ferret it out. And one way you can do that, you as a content creator have a very good idea of what is in your set of training content. You’re the people who are creating it. You know where the bodies are buried, where things are going wrong, where you’ve noticed that there’s this duplication. You could also work with a consultant like me who has been doing this kind of stuff for years and can help you by asking the right questions and maybe trigger some things in your brain. Oh yeah, I didn’t think about that. But there is also technology out there like your Harmonizer tool that can help people start to identify that reuse. And I think it’s worth noting it doesn’t have to be things that are exactly the same. Your tool can help find things that are fuzzy matches that are sort of the same because that’s equally valuable as well. And I want you to talk a little bit about how that process works because I think that’s important.

CH: Sure. So the tool we developed, which was actually kind of a companion to our conversion work, is we had the same problems. People come to us and bring those content reuse problems, and they would ask us if we could help them in some way, because when they’re converting content, even if they’re going to move to some neutral format or they’re just moving from, say, Word to FrameMaker or FrameMaker to something else. That was a lot of the work we were doing, but they would bring us lots of duplicated content. And sometimes at that conversion stage is a good time to nip that a little bit or make some headway against those duplications. So we developed Harmonizer as a tool that was very format neutral. It just basically extracts all the text from whatever content you have and puts those into blocks and then it compares every single text block to every other text block and it’ll tell you which ones are all the same, which ones are close and that close can be pretty far apart actually. So I could do things like if I had a sentence and I told you when you go to the store pick up some milk and then somewhere else I tell you to pick up some milk when you are at the store. Those aren’t exactly the same. And in fact, if you do a word-by-word analysis, they’re completely different. But if you do a harmonizer style analysis, we use some linguistic algorithms to be able to tell that linguistically, those are essentially the same thing, or at least very close in what they’re describing, even though the words and the letters are all in a different order.

AP: It’s the intent of that sentence, basically. Yeah. Yeah.

CH: Very much, yeah. So we detect that as well and put that into groups. So then you can look and you can say, okay, I’ve got this block of text. It says this. Here’s all the places Harmonizer will highlight where they’re different, sort of like a diff tool so that you can see, oh, I use the word or here and I use the word and in this other place. Or maybe I used one version of our product name, in some of the content and I am using a different version of the product name in another part of the content. Or maybe I’m comparing two products and their manuals are 75 % the same content just every now and then the product name is mentioned and that has to be different. All of those things can really illuminate why you have duplication. It can also help you find those places where maybe you’ve made corrections in one place and haven’t got to those other places because you might see, oh, this paragraph is the same except we added a warning at the bottom, do not do something. We better tell everyone else that warning in all the other formats that we’ve created. So that’s kind of what Harmonizer does. It’s not a magic bullet. It gives you a very large, well, if you have a lot of content, it’ll give you a large report if you’ve got a modest amount, you’ll get a modestly sized report. It’ll scale to whatever amount of content you want to feed it. What we do is we use it very strategically. And for instance, we can use it to identify just why you have maybe close but not matching content. So maybe you’re using inconsistent wording in different places. We can identify maybe if you have already some standard content, we can identify if there are places where maybe it varies in ways you didn’t expect. So you can check your standard content libraries if you need to. There’s all kinds of ways it can be used, but at its core, it’s again, just giving you those matches and helping you see, really shining a light on where your content is as far as redundancy.

AP: And one thing point I want to make here is it really doesn’t matter what tools you’re using to create content. This work you can do is not dependent necessarily on those tools. Like I said, you yourself can kind of do a self-service thing where you start to think more deliberately about where you think content is. You can work with a consultant who can help you figure this out. You can use a tool like Harmonizer to help dive deeper and really find this content. So there are all these layers that you can do. And the first layer is you can start thinking about that yourself. So there’s a lot of options there. So once you have started to identify this duplicated content through whatever those methods are that we just talked about, it’s time to get into a reuse strategy. And you’ve already touched on this really well. The core of that reuse strategy is you have a single source of truth for every piece of content, every piece of information, there is one version, one format-neutral version that you can then pull into all your different delivery targets and all your different types of content. So that’s kind of the core of that. Once you know where that duplication is, you can start coming up with this more formal reuse strategy. And I think you also pointed out to the copy and paste that is like the morning light going off, you’ve got duplicated content. There’s copying and pasting going on. That’s what you want to try to eliminate with the single source of truth. Give people a little idea of the benefit of the single source of truth. And I’m talking about both for content creators and for the content consumers because it falls on both sides, the benefit of that single source of truth.

CH: For sure it does. Content creators know this. We’ve already touched on when there’s a problem found or a change needed in the documentation. Maybe the product’s changing or was updated. If it’s software, who knows? Maybe we’ve added a new menu item. So we need to add that to the documentation. Well, if we’ve got a single source for everything and everyone draws from that source, we update that source and it will flow out into all the other channels without any real effort. Now, you can simulate this with your copy-paste activities, but you have to really formalize how you do copy-paste. So you’ve got to only copy from say the source of truth, not from each other or something like that as a starting point. If you can’t actually implement true, single source tool chain. Another area though where this really impacts is on the quality of the content you’re delivering to your readers and your consumers. We all know and I deal with this all of the time and this should be make everyone feel a little bit better that even a giant company like Microsoft has this problem. I work in SharePoint quite a lot. And SharePoint has a lot of different versions. It’s been around forever. One of the biggest challenges I have is when I go look for answers, and this isn’t to pick on Microsoft, by the way. Every software company, you could probably find some of this. 

AP: Absolutely.

CH: But I go looking in the content for something, I’ll read it one way in one place. I’ll read something a little bit different about the same feature in another place and Sometimes they’re just describing them in two different ways Because maybe one was written by the engineering team and one was written by the marketing department Maybe another version was written by the training department. So that’s going to happen. But then I also run into a lot of places where it’s not easy to tell when this stuff was even created. So it might be very old stuff that I’m looking at that no longer is even applicable. All these issues become simplified if you’re doing that single source of truth because you can start tying together a strategy to deal with that. When you just publish stuff out there and it all gets sort of thrown out in a fire hose to your consumers, that can become a very big challenge for them when there are all these inconsistencies in different language styles or different ways of writing the information.

AP: And if people are using all the different content that’s available out on your website to make a purchasing decision, and it doesn’t just have to be the marketing content, they can be looking at the product content. They can be looking at the publicly available training content. If they are getting mixed messages, different information that should be talking basically about the same thing, that can be a huge turnoff and it can hurt you financially because people will be like, I’m not comfortable buying this product or service because I’m getting mixed messages in the content that’s available out here. The bottom line is people don’t care what department or what your organization is like, what your hierarchy is, what your tree is, whatever you want to call it for your different departments and your management. They don’t care about that. They just want a consistent message, consistent information and they want to get it from wherever they find it and they want to be sure that it’s the same message they get regardless of what quote, department’s content that they’re touching.

CH: Yeah, when I’m working with your product, your product is really what I, how I see you. I see you through the product. I don’t see you through your departments and your channels and whatever organizational structure you’ve created to manage your company. So I think that’s a really important point you make to really make sure that that product experience is consistent and clean. And doing this, you know, even if all you’re doing is just trying to make things more consistent than addressing the redundancy issue can help just in ensuring that we’re presenting that unified view of our product to the world.

AP: This conversation really has probably given people a lot of food for thought. There’s a lot to think about when we’re talking about this duplicated content, redundant content. If we want to kind of back up a little bit and give people maybe one or two pieces of advice on where to get started, even if it’s starting small, what are some things that people can start to do now to start thinking about this bigger picture of duplication, reuse, single source of truth? Any recommendations there?

CH: For sure. So the first thing is you’ve got to tame a little bit of your Wild West if you’ve got that of content. So if I can just go on the corporate network and start willy-nilly looking around and copying and pasting stuff out of anywhere I can find it, which is sometimes the case, that’s probably a big area where you’re creating a lot of content entropy. So you need to think about that. And it may just be even a training issue. It may be a network organization issue. But you should start considering how you can make the authoritative repository accessible to everyone and then limit where they’re getting stuff to that authoritative repository. You don’t have to implement a whole new content management system and tool chain to do that. You can do that using permissions, using training, and having regular contact between the groups that create the content that’s getting copied around. So making sure there’s some interface between them so that they can coordinate and know that they need to coordinate these content activities. A lot of times that simple piece just gets overlooked because a lot of companies really treat content as kind of the afterthought. I’ve built the product, okay, hurry up, make a manual, do some training, do whatever, because we’re product-focused. And so it’s kind of natural, but you really need to see your content as an integral part of that product that you’re delivering so you can get started with just using the tools that you have and working on the processes and the consistency with which you apply those tools. You can also start strategizing for the future. So you can look at, okay, maybe we need to figure out, first of all, how much money is it costing us to copy and paste a lot? Again, knowing how much duplication you have, and then you can put estimates on, okay, if I’ve got all this amount of duplication, how much does it cost to make a change to this manual if we are to ensure that it gets to all the delivery channels, including marketing, training, all the languages, all the manuals? How much does a change cost? Once you start quantifying that, you might find out there’s a better budget than you think for working on this problem. 

Again, you’re going to have to look at your content itself and figure out how much redundancy there is. So planning that strategy, figuring out how much it’s costing you, all of that can be very helpful, I think. And then ongoing maintenance. How are we going to maintain it? I’ve been to a lot of organizations where they’ll do a big push to clean things up and they’ll say, okay, we’re going to hire someone, we’re gonna get some new tools going and man, we’ve fixed it, right? And so they fix it. And then three years later, they’re in the same boat they were in because they didn’t really follow up on that. They didn’t plan to maintain the content. Nobody was charged with the duty to ensure that we were adhering to the strategies that the tools were providing and nobody really had the responsibility to look at that stuff. So if you’re going to make the investment, you have to also have the follow-through. And a lot of times that involves consultants, because let’s be honest, if this is the first time I ever do this, I’m not going to do it very well. And I usually don’t get a chance to do this 100 times. I’m not going to do this over and over in my organization.

AP: Yeah.

CH: But if you find a consultant, you can find someone that’s done this 100 times for a lot of different organizations. And they already know where all the pitfalls are and where all the trouble is. And they’ll help steer you in the right direction the first time. Because you don’t get a lot of bites at this apple. Like, your company’s not going to say, oh, just keep working on content reuse for the rest of time. They’re going to want to see some progress.

AP: Exactly. Yeah, and it comes down to return on investment. You do not do these kinds of things for fun. You’re doing them for business reasons, and business reasons include making money and getting a return on investment on any kind of investment in technology, and that includes content technology.

CH: Absolutely.

AP: Chris, this has been very helpful. I think this is a good place to wrap up. Thank you so much for your insights. I think you’ve given people a whole lot to think about.

CH: Well, I appreciate the conversation.

AP: Thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post How reuse eliminates redundant learning content with Chris Hill (podcast) appeared first on Scriptorium.

“Showing up with cookies never hurts, but what is your executive’s motivation from a business point of view? What are they trying to accomplish in their goals for this next quarter or month or year, and so on? You need to show them, assuming that you can, that moving to structured content, moving to DITA, and changing tools is going to help achieve those business goals.”

— Sarah O’Keefe

Related links:

• Content operations ROI calculator
• The business case for content operations
• Content operations from start to scale
• LearningDITA

LinkedIn:

• Bill Swallow
• Sarah O’Keefe

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Bill Swallow: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk to you about next steps after LearningDITA, how to get your boss to sign off on a DITA project. Hey everybody, I’m Bill Swallow.

March 2025 update: We have moved LearningDITA to a new platform. The Introduction to DITA course is still free, and you can sign up for courses at store.scriptorium.com.

Sarah O’Keefe: And I’m Sarah O ‘Keefe, hi.

BS: So yeah, we’re going to talk a little bit about what to do after you’ve completed your learningDITA.com courses and you have some DITA knowledge under your belt. So I guess we’ll start off with completing the courses. You pretty much have a working DITA environment then after you complete all of the courses on learningDITA .com, you have a batch of topics, a batch of tasks, a batch of other types of files, a map, you have a publishing scenario, you have some reuse going on. So it kind of makes for a neat little proof of concept package. But now that you’ve got that, how do you bring it to management? How do you sell it as we want to move forward in this direction?

SO: We’re assuming, of course, that I think a lot of the people that do LearningDITA, they come for different reasons. And a big chunk of it is just, I need to learn this because I want to be more marketable. I want to get a new job. I want to have a chance at the jobs that require DITA information or DITA knowledge.

BS: Right.

SO: But I guess what we’re focused on here today is this question of, all right, so you’ve run through the courses and you’ve decided that this is potentially a good idea for your company, for your employer. You really want to advocate for “we need to move our content into DITA because it feels like this is a good idea for this particular organization.” So what do you do next? And at that point, you’re right, you’ve got a proof of concept and that may be enough to show to your peers and maybe your immediate manager just to let them look at that. Almost certainly the next thing they’re gonna ask you for though is to take some of your content because the learning ditto ducklings are only gonna get you so far. They’re gonna say, well, how does this apply to our content? So probably you’re gonna have to go off and do some…

BS: Haha.

SO: …test topics or some test content using your actual live content. I think that’s probably step one. The key thing though, I think to recognize is that DITA and structured content is not just a tool. You’re not going to your manager and saying, hey, I need $500 for a piece of software or even a thousand.

BS: Mm-hmm.

SO: You can of course do this potentially with source control, which is at least free in theory, free but not cheap, right?

BS: Haha.

SO: And, but the effort of, for example, taking five or 10 or 50,000 pages of word content and moving it into DITA is really significant. And so you’re talking about a big, you know, departmental or even enterprise effort to make this happen. And so the bottom line is that somebody needs to agree that this is a good use of your time and or resources, which means you need an executive sponsor.

BS: Right. So how would you start moving up the chain to have those discussions in order to, I guess, get to an executive sponsor or how would you frame a pitch to an executive sponsor then? If you are convinced this is the right direction to move in, you have your proof of concept, you are hopefully moving some of your actual real-world content into DITA to beef up that proof of concept to pitch. What are the things we need to start thinking about?

SO: I think that many of us that live in this technical writing, technical communication world tend to be really interested in new technology. Something new comes along, we’re like, oh, this is so cool and I can’t wait to use it and I can’t wait to apply it and it is delightful and fun and new and different and nerdy. That pitch, you know, look at this, this is so cool. That doesn’t work unless you’re selling AI, then it pretty much works. But the question you have to ask is who is the person that’s going to fund this project? And the more money you need, the higher up the chain you’re going to have to go. And what motivates that person from a business point of view?

BS: Haha.

SO: Right? I mean, showing up with cookies and things never hurts, but what is their motivation from a business point of view? What are they trying to accomplish in their goals for this next quarter or month or year or whatever? And you need to show them, assuming that you can, that moving to structured content, moving to DITA, changing tools is going to help achieve those business goals.

BS: Mm-hmm.

SO: So the number one most obvious way to do this is to show cost avoidance, right? There’s a decent amount of research that says that if you’re using desktop publishing tools, you’re probably spending something like 50% of your time doing formatting work as opposed to content work. And the formatting automation that you have with structured content, gets you out of that formatting work. So you can basically say, hey, we were spending 50% of our time on formatting. Instead, we’re going to write some transforms, and then we’ll be done. We’ll have push-button processing, which is a pretty clear cost avoidance and a pretty clear gain. And we have a calculator for this that addresses looking at those issues, which we’ll make sure to put in the show notes.

BS: Mm-hmm.

SO: But there are other levers that may matter more to your executives and to your leaders than cost avoidance. Time to market is a big one.

BS: Mm-hmm.

SO: Can we get this stuff done faster? Not necessarily cheaper, but can we get it out the door faster? Or do you have these delays of, oh, I still have to reformat it, and oh, now all my numbering is wrong, and I have to go back through and fix everything, and it’s just a nightmare. Can we get a competitive advantage? Can we do a better job of supporting the brand? Can we do a better job of translation localization and expanding what we’re doing? You need to really understand where’s the business going and why? What direction is it going in? It is really, really common after a merger to have a situation where you have two or three or 15 mutually incompatible content development systems. And what you really need to do is bring them all together in the same way that the products are being brought together and the company is being brought together into one unified thing so that you can sell, you know, products A, B, and C, which used to belong to different companies as a unified set. Well, you need the content to also be a unified set, which pushes you towards a unified approach. And if that’s, you know, if DIDA can solve that for you, then that’s a story that’s gonna be compelling to a leader who’s dealing with merger headaches.

BS: Mm-hmm.

BS: So finding a way to kind of translate what you need to do to expedite and streamline your work to align with the company goals, or at least the goals of essentially the person with the money who’s going to make this effort happen.

SO: Yeah, and know, expedite and streamline is really useful and in and of itself doing your job more efficiently as opposed to less efficiently is generally a good idea. I think it goes beyond that into additional factors. When we talk about, so did a reuse is a great example, right? You walk into this presentation and you’re like, Conrefs are the coolest thing ever and look at these keys and look at what I can do with scope, right? And you’re…

BS: Haha.

SO: …you’re the people you’re presenting to are like what what what they have no context they don’t care if they’re software engineers you can maybe talk to them about like object-oriented things and how you can you know whatever but no you walk in there and you say okay um you know how we have this problem where your content over in this bucket contradicts the content over in this other bucket. And the reason is that we copy and paste from A to B, and then we update A, but we don’t update B. And they’re like, oh, yes. And then if right now you’re going to bring up that Air Canada issue with their chatbot that had incorrect information, which is a great example of this, where almost certainly what happened was that the chatbot was fed a bunch of information that wasn’t kept up to date.

BS: Mm-hmm. Yeah, they have no context for what you’re talking about.

SO: Or they were fed the incorrect information to begin with, well, that shouldn’t happen. You should have a single place where you stash all of that information and then you just push it to all of your endpoints, such as a chat bot. And, you know, solving those kinds of problems so that the company doesn’t get embarrassed slash sued slash held liable for making mistakes with their content is valuable. And that is you know, different and arguably more important than we can do it better, faster, cheaper.

BS: Mm-hmm. So yeah, it’s really avoiding those risks that you have in producing content where you can have inconsistencies. If you’re doing things right, you will write once, use everywhere by reference so that the same copy goes out in every place it needs to go. Are there any other things that we should really start looking at with regard to risk management there?

SO: One of the biggest challenges with making a change in tools, whether DITA or anything else at all, is that people, people who are not consultants really hate change. Actually, we hate change too. We’re just in the business of inflicting it on other people, but when the shoe is on the other foot and somebody’s advising us, we’re just as bad as all of you. Hi, everyone. Yeah. It’s pretty bad.

BS: Mm-hmm.

BS: That is true. That is entirely true.

SO: So, okay, so we all hate change, right? Change is bad. And change is perceived as being risky, right? Because there’s the thing I’m doing right now, which I know how to do, and I know where the problems are, and I know it’s inefficient, but I know how to get around it. It’s all known. 

BS: Mm-hmm.

SO: And when you walk up to me and say, hey, I found this cool new way of doing content and it’s gonna be awesome and we’re gonna solve all these problems and it’s gonna be so great. My reaction as a human is A, I don’t believe you and B, this sounds like change and change is bad. So what you have to do is you have to convince me that making the change is less risky than not making the change. 

BS: Mm-hmm. Yep.

SO: And, there’s a lot of things you can do to mitigate that, but probably the biggest one is to start small and do like a proof of concept and show some stuff and say, look, you know, we have this ongoing problem and I’ve solved it over here and look at how this just works. And I made this little update and look, it percolated into five different locations automagically and isn’t this cool. So to start to build that confidence and that trust and that knowledge, that understanding of the techniques or the technology or you know the thing that you’re trying to convince people to use to switch to. But the unknown, whatever that unknown is, is always going to be perceived as being riskier than the known, even when the known is bad. Like known bad is actually easier than unknown good.

BS: Mm-hmm.

BS: Mm-hmm, right, because you’re asking people to take a step forward in the dark.

SO: Right. And, you know, the dark is bad and I don’t like it. So now there you get into other issues. We’re talking here mostly about how do you deal with leadership and leadership is looking at it and saying, you know, is the risk worth it? Is the funding worth it? They have X amount of funding, some number. They have one hundred dollars and you’re asking for 50. But there’s eight other people also asking for fifty dollars and they have to pick.

BS: Mm-hmm.

SO: You know, two that are going to get $50 a piece out of their eight projects. So your pitch has to be, you know, you’re competing almost certainly for limited resources within your organization. So it has to be a good pitch. I mean, you have to make a compelling argument and, you know, con -KeyRefs are really cool is not actually a compelling argument.

BS: Yeah, how does it impact the bottom line of the company?

SO: Yeah, how can I fix these issues that we are wrestling with as an organization? We have localization problems, stuff we don’t, you know, we’re not managing our content properly and we get all these problems in localization. We’ve got writing issues, our warnings are not standardized and that’s gotten us into trouble because, you know, we got sued and these two documents didn’t agree with each other and they pointed out the discrepancy and that had real-world implications. We’re having trouble delivering content that complies with the EU directives, the machiner directive or the product documentation directives, because we don’t have enough control over the content that we’re delivering. Those are conversations that need to happen, and underlying that is, and so if we use DITA and we redo reuse and we do this and this and this and we automate our formatting,

BS: Mm-hmm.

SO: We can address these issues, but you have to start with the business problem and not with the feature.

BS: Mm-hmm. Right. Yeah, Conrefs are cool is definitely not a selling point out of the gate.

SO: I mean, it works for me, but you know.

BS: Well, but if you frame it the right way and get the executives on board with the business reasons for moving, you might actually get the executives saying, hey, con refs are cool.

SO: Right, now the big challenge here is that, you know, we’re talking about leadership as this amorphous thing, but it turns out that what’s gonna happen almost certainly is that the priorities change as you go up the line. So your tech com manager has one set of priorities and a vision or a, you know, amount of stuff that they’re looking at. 

BS: Mm-hmm.

SO: And the director above that is looking at something different because tech com is just a part of their responsibilities. And the VP above that, again, so you have to understand what messaging is going to work at every level in the organization. And accordingly, provide the proper message or a message that is going to work. 

BS: Mm-hmm.

SO: So ultimately, this comes down to know your audience, know who you’re talking to and what their priorities are and figure out how, whether and how. I mean, we should start with, does this actually fit into the game plan? I mean, is this the right solution for your organization? If you’re convinced it is, then how do you communicate that in a way that is understandable to your non-interested in content leadership?

BS: And then magic happens.

SO: And then magic happens.

BS: So that’s a big leap from doing a LearningDITA proof of concept course, more or less, to doing an executive pitch. And I know we covered a lot of ground here, and there are a lot of things that we still have not even discussed. But I guess in the interest of time, we do have a lot of resources available to you to start thinking in this direction, being able to put that pitch together, get the data that backs up your position that you do need to move if you are looking for a move into DITA. So we will put a bunch of these resources in the show notes. Sarah, do you have any particular ones in mind you’d want to share?

SO: So I mentioned the Content Ops ROI Calculator, and we’ll get that in there. There’s also a chapter that I wrote called the Business Case for Content Ops, which sort of goes through all of these different factors and the risk management issues. We haven’t really touched on compliance, but that’s another key factor that tends to play into this. That is available both on our site and then, you know, the larger Content Ops book is out there now and available for free. So there’s a whole bunch of interesting stuff in there that might be of use. So we’ll post all of that and links to some of the white papers that are floating around that may be of use to our listeners. And beyond that, if you’re, you know, working on building this case out, I would say feel free to reach out to us and we’ll do the best we can to help.

BS: And that sounds like a good place to close. Thank you, Sarah. And thank you for listening to the content strategy experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post What’s next after LearningDITA? (podcast) appeared first on Scriptorium.

“We know companies that have moved away from a do-it-yourself approach because they had maybe two or three different people putting in half to almost full-time work on the publishing system and not on other facets of the company’s core business or the writing. They were simply there to keep everything working. It just blows my mind that on a scale where you have hundreds of writers contributing content, you are saying, Okay, you three people are going to be solely responsible for keeping this thing up and running so that they can produce their content, rather than having a system that’s designed to keep itself up and running.”

— Bill Swallow

Related links:

• The truth is out there
• Content as a service (white paper)
• Prerequisites for efficient content operations (podcast)

LinkedIn:

• Bill Swallow
• Christine Cuellar

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Christine Cuellar: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re talking about how you can brew a better content strategy through single sourcing. Hi, I’m Christine Cuellar.

Bill Swallow: and I’m Bill Swallow.

CC: Hey, Bill, thanks for being here today. 

BS: Hey, thanks.

CC: So what I mean by brewing a better content strategy is that both Bill and I really love coffee. Right now for both of us, we’re recording it fairly early times in the morning. So actually we’re heavily reliant on coffee and other caffeinated sources to enable this conversation. Also, Bill, I know you like homebrewing beer. I like drinking beer. I have no idea how to homebrew, but I do enjoy beer as well. So we just thought that beer, coffee, drinks in general actually have some good analogies for single sourcing, which can be part of your content strategy. And it’s something that’s been coming up more and more in a lot of conversations with clients and people that are interested in content strategy so we thought this would be a good topic for today. So Bill I’m gonna kick it over to you for our first really big-picture question. First of all what is single sourcing? What do we mean when we say that? Let’s kick it off there.

BS: All right, so in a nutshell, single sourcing is writing content once for multiple purposes. It’s about as simple as you can get. It could be authoring centrally, it could be authoring collectively in a group or centrally as a single person for a wide variety of publishing needs, whether it be for different audiences, different output types, or what have you.

CC: Okay, yeah, that’s great. So how does, what are some ways that single sourcing can start to mimic drinks? Coffee, beer, any of that?

BS: We could take the example of multiple output formats. So traditionally with single sourcing, we’ve been doing that since I think the mid-90s. I remember working in. Oh, that’s based in the name. I remember working in Doc to help back in, I think it was 1996, to produce online help and written manuals from the same source using a very high-tech convention called RTF, which is basically the backbone of Microsoft Word at the time.

CC: Ooh.

BS: So that was fun. I had many nightmares about RTF coding. I solved problems in my dreams using RTF. It was a scary time. Yeah, I was essentially fully immersed, let’s say that. But in many ways, to take the same analogy, you’re producing a wide variety of, or you’re producing a core set.

CC: That’s when you know it’s really stressful. Yeah, that’s not good.

BS: of stuff that needs to go to many different places. And it’s a lot like, let’s say a coffee roaster since it’s early in the morning and we want to talk about coffee. A coffee roaster is going not going to sit there and roast a pound of beans, put it in a bag, and then send it off, and then roast a pound of beans, put it in a bag, send it off. You know, they’re going to roast, you know, a ton of beans, 10 tons of beans, however, you know, many that they can fit into their roaster.

CC: Yep.

BS: and do it all at once. A couple of things that allow them to do, one, it streamlines the process and speeds things up because now they have a wealth of products that they can then put in large bags for distribution to restaurants or cafes or what have you. They can put it in smaller bags and send it out to the grocery stores. They can do their online mail orders for coffee that way. Five-pound bags, one-pound bags what have you or they can even grind it up themselves put it in k-pods and people can destroy the planet with those I’m not a big fan of those the k-cups and pods but It also helps them create a more homogenous product because they’re working at a very large scale So and they’re they’re producing things in very large batches So with all their beans together in one roaster, they are able to produce a very consistent product that way.

CC: Yeah, that’s great. That’s a great analogy and that definitely makes a lot of sense. So when it comes to both coffee and beer, there’s a, you know, the commercial option that you just outlined, which is really helpful. And there’s also usually a DIY component. I mean, you can home brew beer, you can home brew coffee, of course, and do that in a bunch of different ways. Like it can just be your coffee pot or you can get all fancy and do, you know, all the little like other fancy things you can do with it, all of which I’ve done and they’re all leaving my brain at this moment. French roast, okay, that’s one. Anyways, it should have been more top of mind. But is that also an option for content?

BS: It can be. Looking at a commercial solution versus a DIY or DIY approach, it’s not so much a question of which approach do you prefer to take. Because I mean, yes, I’m a hobbyist when it comes to brewing beer. But I still, and really for the past 10 years, I stopped brewing because there were just so many high-quality

CC: Okay.

BS: Options on the market at that point. I’m like, why am I spending my time doing this when I can just go to the store and pick up? one of a thousand different types of beer but you really need to look at it from the standpoint of how much money do you have to spend on a commercial product versus how much time and commitment do you have to doing it yourself if you do it yourself. 

CC: Yeah.

BS: The results can vary, but if you put the time and energy into it, you can produce some amazing results, but there is always a hidden cost of time and labor. When I used to actively brew, I brewed with a buddy of mine and we would do it every Monday night. So he would either come to my place with his equipment or I would go to his place with my equipment. And from like six o ‘clock until about midnight, we would be either brewing beer, cleaning equipment, bottling beer, doing whatever. It was a commitment. I mean, it was six hours a week, and literally it was every week. Unless we had something going on and we took a bye week, we were doing that every single week because there is always something that needs to be done in the process.

CC: Hmm. Yeah. Yeah, that’s a big time commitment. And I like that you mentioned that not only was there a big time commitment in actually brewing the beer, but also the cleanup, also the prep work. Yeah, I like that there’s this there’s other factors that you don’t think about that also are involved in doing it yourself? Is that also something that applies to, you know, single sourcing and content strategy? Are there a lot of factors that can come into play?

BS: Oh, absolutely. I mean, if you’re a homebrewer, you have to enjoy the monotony of cleaning. And it’s the same thing if you’re doing it yourself with putting together a publishing system and an authoring system that relies on, let’s say, open source tools and a lot of human care and feeding. You have to really enjoy the monotonous. 

CC: Hmm.

BS: Droning kind of day-to-day maintenance work. You know, when you’re brewing, it’s, it literally is 90% cleaning, 10% brewing. Because I mean, you start, you know, you have to have everything completely sanitized. And once you get the pot boiling, you know, it’s, it’s doing its thing for about an hour. You know, you might be adding, you know, some hops here and there, or some other flavoring agents, depending on the type of beer you’re producing. 

CC: Wow.

BS: But, largely, you’re just waiting for an hour. So while you’re waiting, you’re cleaning other stuff that you’re gonna need later in the process. And then you take five minutes to move to that next step, and then you have to wait for the beer to cool down. So then there’s another round of cleaning. Okay, all the stuff that I used to make this batch of beer now needs to get cleaned. And then you go to put it into the fermenter, and now you have to clean everything else. And the cycle just continues.

CC: Yeah, oh wow.

BS: It’s the same thing with these with, you know, with a do-it-yourself approach. And it’s not to say that it’s wrong or that it’s not ideal, because you can learn quite a lot in a do-it-yourself environment. But it does come at a cost. You know, you’re going to spend I actually we know companies that have, you know, moved away from a do-it-yourself response, because they had, you know, maybe two or three different people putting in half to almost full-time work on the publishing system and not on other facets of the company’s core business or the writing or what have you. They were simply there to kind of keep everything working. And it just blows my mind that on a scale where you have hundreds of writers contributing content that you are saying, okay, you three people are going to be solely responsible for keeping this thing up and running so that they can produce their content rather than having a system that’s designed to keep itself up and running.

CC: Yeah. Would you say that because it sounds like with a DIY approach, it can work, but it has to be very intentional and you have to be very realistic, like you said, about the cost and the time that’s involved. And I can see from like a coffee analogy. Do companies, I guess, default or kind of slide into a DIY approach without really thinking about it. Because I could see with like coffee, I do love enjoy, okay, with coffee, I do enjoy attempting to make lattes and, you fun stuff with my espresso machine, which I have like a really crappy one right now, but it’s really fun to play with. And I’ve practiced a lot with it. But still, the best cup that I make does not compare to like, basically every one of our local coffee shops here, I would 100 %… enjoy their stuff more than what I make. It’s just fun to play with. But it’s not realistic for me to go and buy, you know, the best coffee from one of the local places every single day. So instead, I have a coffee machine and instead I brew stuff here at home, you know, every day for my regular coffee addiction. And then when I want to be fancy, I go to a coffee shop. But just, you know, I don’t have the capacity to go somewhere else every single day. So that’s kind of why I’ve just

BS: Yeah.

CC: Not really thinking about it, slid into a DIY approach. Is that also something that happens with companies that they kind of DIY until they realize there is a different way to do it? Is it kind of a default method if that makes sense?

BS: Yes and no. And the decision as to why a company might choose to do it themselves rather than purchase a more packaged or commercial solution. It really varies. You know, you have some companies that, yes, they started out small. They hired someone perhaps who had some serious technical chops and was able to put together something very, very, very slick.

CC: Okay.

BS: But you know, they were the only ones who really knew how it worked. And as they hired more writers, you have varying degrees of varying degrees of, I guess, capability and willingness to learn how this thing works.

CC: Mmm.

BS: You know, so if, you know, for example, let’s say that they’re doing Markdown and they have all of these, you know, different scripts that run and fire off and they produce, you know, all these different outputs. It’s very, very slick. I’ve seen lots of implementations like that and that, you know, they’re actually pretty cool. But, you know, as you hire more people,

CC: Hmm. Oh yeah, that’s true.

BS: You start getting into, why do I have to write and mark down? I always keep forgetting to use this character instead of this character when starting a bulleted list. Or I always forget to, you know, close off the end of my, you know, my title or what have you, anything like that. You know, why can’t I use Microsoft Word? Why can’t we move to just using HTML? Why can’t we move to XML? Like, you know, you start getting a lot of that pushback and the pushback may not be direct.

CC: Mm.

BS: So you have cases at that point where you have quality slips starting to make their way into the core content set. And that’s where things get a little hairy. But to go back to your analogy, making coffee at home, you can have, there are plenty of really, really good espresso machines out there that you can buy for home, but it will never compete with that $8,000 Italian espresso maker that your cafe, you know, your choice, you know, the cafe has in town. You know that they, you know, they paid a ton of money for and they’ve spent hours and hours and dollars and dollars to train their staff on how to appropriately use it and clean it to produce that same, you know, questionably but perfect cup of coffee every single time.

CC: Yeah.

BS: You know, same thing with buying coffee, you know, buying beans or buying grounds. You know, these companies you buy and you know, people will laugh. I make the same comments about, you know, certain beer manufacturers. But, you know, you buy something like Folgers. It’s not, you know, in my opinion, it’s not the world’s best coffee. You know, I just don’t like, you know, what it tastes like.

CC: Yes.

BS: But every single time you buy a, they’re not tins anymore, are they? I think they’re more like plastic jugs of coffee. But you buy a jug of coffee and it’s always gonna be the same every single time. And you can say the same thing about Budweiser. People may say, oh, Budweiser, why would you ever drink that? It’s horrible. It’s like, yes, but it is absolutely consistent. You can buy a Budweiser anywhere in the United States, in the world.

CC: They’ve evolved. Yeah, yeah, yeah.

BS: Open it up and it will taste exactly the same.

CC: That’s true. Yeah, that’s true.

BS: You know, there are really no differences there. And they spend quite a lot of time and energy into ensuring that that product is consistent from every single batch that’s made in every single location across the world because they have breweries all across the world that produce this stuff because shipping it from one location around the world is just not gonna work. So all of these different locations have their equipment set up just the right way. Their chemists work, yes chemists, their chemists are working to make sure that the pH balance is perfect every step along the way as that beer is being produced. So otherwise, if you’re brewing yourself at home, your equipment may vary. I’ve put stuff together literally with duct tape and string.

CC: Hmm.

BS: I made it, I made a shower head out of a nine-inch tin foil pie pan 

CC: Hahaha! Wow. Yeah, that’s a DIY way.

BS: Because, it was available, you know, to sparge or to clean my grain as it was, being run off as the beer was being run through. Or, you know, even if you roast your own beans at home, you know, the level of quality is going to vary, you know, because you are likely using your, your oven to do that roasting. And if you step away for a minute too long, or if you didn’t get the temperature setting quite right, so if you don’t have a digital temperature setting, or maybe your heating element is a little futsy, so sometimes it might be 310 degrees, sometimes it might be 332, who knows? There are lots of elements that can go wrong in a do-it-yourself environment.

CC: Yeah, that’s true. And like you mentioned earlier that a lot of that comes down to the people, not only the equipment that you’re using, but also the people. Like, do they know what they’re doing? Do they know why they’re doing it? And especially as you introduce more people, like you mentioned, if it’s you and your buddy that are brewing beer together, that’s another person that’s been added. And, you know, in a scenario where one person’s not as interested or, you know, just doesn’t know as much about the process that can really change things and vice versa. Like if you have two people that both really know what they’re doing and both really enjoy it, that can lead to a really good output. 

BS: It can vary because yes, we both knew exactly what we were doing and But you know you start biting heads. I want to do it this way No, I want to do it this way if we do it this way. You’re gonna get this result I don’t believe you I think if we do it this way, we’ll get this result and yeah, we’ve had You know, we actually tried it and tried two different techniques of brewing the same beer and they came out very very different so

CC: That’s true, yeah.

BS: You know, it is what it is. But yeah, it all comes down to that quality control element, you know, and, you know, generally when you have a bigger commercial system, you can kind of get there a lot quicker. Now, it’s not going to do everything for you, but it’s got the pieces already laid out and it’s got some recommended workflows and processes for using that system to produce consistent results. Whereas with a do-it-yourself, you’re kind of left at your own devices and how well you document your stuff and how well you regulate it.

CC: Absolutely. Yeah, which can is it in and of itself is another time commitment. Yeah. So we’ve talked a lot about consistency, which is a really important element of this, but also personalization is another important value that you can get out of single sourcing. How does that? So let’s say if we put it in our coffee or beer analogy, let’s say you’re personalizing your packaging for, you know, different restaurants and different cafes or whatever. How does single sourcing make that more effective or what does that look like?

BS: Well, at the core of it, like for example, if you’re putting stuff out to cafes and restaurants, you’re typically not going to use the same level of pomp and flash on your branding packaging that you would if it was going to a grocery store. Because you want that product to pop off the shelf in the grocery store and catch people’s eyes, whereas at the restaurants and so forth, as long as the logo’s on the bag so they know they got the right thing.

CC: Yeah.

BS: It’s usually just a pretty nondescript bag with a description of what’s inside it. But in the end of the day, you’re not producing different product for these different groups. You’re producing the same product that’s going out to many different people, depending on who it needs to go to. So you may have one conveyor belt that takes the beans down to where they dump them into 25-pound bags or 50-pound bags. And then you have this other conveyor belt that goes off and does the one-pounders.

CC: Mm-hmm.

BS: And so it’s really streamlining from that. You’ve spent the time to build this, I guess, storage heap of beans that you then are distributing to many different people. So at that point, you’re taking from that same source and you’re partitioning it off as you need to for multiple different consumers.

CC: Mm. That’s true.

BS: Same thing with single sourcing. I mean, you have a core collective of content that ideally is all written in the same tone and voice. Aside from all the mechanics of how content gets produced, it needs to be written in the same tone and voice for…

to be able to blend and remix and be able to send it out to different audiences so that it doesn’t sound like, you know, eight different people, even though eight different people may have written the content, it doesn’t sound like eight different people wrote different parts of whatever it is you’re delivering. It’s a little jarring to go from…

CC: Hmm. Yeah.

BS: You know, one style of writing to another within the same paragraph or within the same, you know, chapter of a book or, you know, series of topics in an online help system. It can get very distracting. So, you know, in that case, you do need some attention toward how all these people are developing the content and what tone and voice they’re using. But aside from that, with regard to packing your…

CC: Yeah.

BS: You know, packaging your output from a content standpoint, you have things like, you know, templates that drive the look and feel of what the various outputs are going to look like. So templates or, you know, style sheets or what have you to produce these things. But also behind the scenes, you have other conventions such as variables, conditions. Perhaps you’re leveraging some form of reuse. So that you can kind of mix and match your content, turn things on and off depending on, oh, this is going out to, you know, an advanced user or this is going out for our, this is going out for our premium product. And this one’s going out for our base-level product. And base level product has features A, B, and C, but our premium has features D and E also tacked on. That type of thing. So you’re not rewriting content for these.

CC: Mm.

BS: You know, very many different outputs, but rather you are pulling from a single, you know, managed source of content and, you know, mixing and remixing and turning things on and off to produce that desired result.

CC: Yeah, absolutely. And then so taking that a step further, when you when it’s time to start selling your coffee or selling your beer in a location in a different country or different region, what happens then in that localization process? I mean, I’m assuming all of that is involved plus more. Yeah.

BS: Oh, plus more, because then you have language on the packaging and so forth that needs to change. But more importantly, with any kind of food-based product, and particularly with alcohol, there are different rules that govern how things can be sold, what you can say, what you can’t say on the packaging. We’re pretty loosey-goosey here in the United States where you can say anything. You can put out a package that is the same size product and say now 20% more. And you look, it was a 16-ounce box before, it’s a 16-ounce box now, but now it says 20% more.

CC: What? Maybe they meant air, 20% more air in the package.

BS: I guess, I guess, but you start going overseas and the nutrition labels need to change. You have to take very different stances when you’re listing ingredients. There are certain claims you can and cannot make on the packaging and in the advertising. And when it comes to alcohol, particularly, there are different rules that govern what can go into it that can be then passed off to a consumer and what you have to disclose and what you can’t disclose. And I go back to one of these things, and it’s not so much a governing rule anymore as far as you know how strict it is but there’s the Reinheitsgebot I hope I am pronouncing that right but it’s basically the German purity rule for beer and it basically governs and says that beer can only be made of three components water barley and hops and they omitted yeast even though yeast is what does the fermenting process because at the time they created the law, they didn’t really know about it. But yeah, essentially those four ingredients are the only things that can go into beer for Germany Not so much a rule anymore, but it’s it’s it’s an example of you know, if you were to produce something And call it something. Yes, if you were to produce beer and call it beer, but you’re making beer with Barley and corn and rice, you know, so something that let’s say Budweiser does. Would that technically be beer? Maybe not in Germany. So what do you call it? How do you package it? Can you sell it? Again, it’s not so much a thing anymore. It’s more of a historic note, but it kind of shows the differences in what you can do and what you can say in different countries. 

CC: Oh, okay, interesting.

BS: Likewise, when you go to different, when you publish for different locales, you have not only different languages, but you have different fonts that you have to consider. You have different complete character sets, you know, so, you know, there’s, you know, the more the Latin character set that we use throughout the United States and throughout Western Europe. We start going more into Eastern Europe and you start getting into needing to use a Cyrillic alphabet. 

CC: Mm-hmm.

BS: Certainly you move into Asia and now you’re starting to look into, oh, I’m going to need you know a completely different character set a double bite character set to put these things together and You know in some places you’re gonna have to change the complete layout of your content as it as it gets published because you know certain languages they go from right to left, not left to right, so that’s a completely different change and you know a lot of that you bake you hopefully are baking into the infrastructure that you are driving your content production with and not doing this by hand every time you need to send something out.

CC: Yeah, I can’t even imagine. Yeah, that would be a lot. Well, so for organizations that may not have adopted this single-sourcing approach yet, what are some factors? I mean, we’ve talked about a lot of them, but what are some either factors or like pain points or experiences they may be having that signal, hey, maybe it’s time to start thinking about this? How would you sum up those indicators?

BS: I think the biggest indicator is that you have a very overworked team of people who are spending their time on everything but their core job. So their core job should be producing content, developing content. It should not be formatting and reformatting content to produce it.

CC: Hmm. Yeah.

BS: You know, it certainly should not be copying and pasting content from one place to another and then making sure that any change to that copy and pasted content is reflected in the two or eight or 16 or 150 different places they pasted it into last time. You know, that’s a lot of busy work and you know, a lot of things that I hear, especially from small teams, is that they reach a point where they are so busy.

CC: Yeah.

BS: And making so little progress on new content development because they are spending all their time, you know, prepping for publishing, prepping for publishing, you know, prepping for publishing literally should be content is done. And that should be your prep for publishing. It shouldn’t be, okay, now let’s apply this template and let’s reformat everything. And now let’s send it off to the translator and oh, we got it back. Okay, now we have to reformat it so that it fits in this language because German is now, you know, eight pages instead of five. You know, it shouldn’t be fixing these things. Those are things that really should be handled automatically and, you know, allow the content developers to do what they were hired to do, which is develop the content.

CC: Yeah, exactly. Yeah, allow them to be able to do what not only you hire them to do, but I’m thinking that they’re more passionate about. That’s where their passion is. That’s why they’re here. I could see that being very discouraging if you’re passionate about the content and you spend almost all your time on formatting and other stuff. That sounds awful. And it would be discouraging. And I’m assuming leads to burnout, lead to, you know, high turnover.

BS: Yeah.

CC: Because you’re not getting to do what you want. You want to write content.

BS: True, although some people do thrive in that environment and they love that they love the fiddly bits, you know, and, you know, you’re not going to make them happy by taking that away. But then again, it’s like, you know, as you know, your company is growing, you’re producing more stuff, you need to produce more content, you need to do it quicker, you need to do it at a higher quality. You know, you’re you’re publishing at a higher volume, you’re adding more languages. You know, at that point, it’s like, do I keep that person happy?

CC: Oh, yeah.

BS: Or do I focus on what we need to get done?

CC: Yeah, fair. And maybe they can have some say or you can include them in what’s what the big vision is. But yeah, like you said, that you can’t always just make one person happy with the system. There’s all these other people that may also not be happy because of, you know, not having an efficient process and a way to pump out a lot of content at scale in a way that’s still quality.

BS: Mm-hmm.

CC: Still consistent. Yeah.

BS: Yeah, and there is a risk there as well because those who put together the DIY approach, they may love that. You know, I mean, that that’s something that they built from the ground up. That’s their baby, you know, and you’re taking their baby away. That can lead to some big problems. 

CC: Yeah, makes sense.

BS: You know, either you lose that person who has all the publishing knowledge, even though you may be transitioning away from that system, they kind of know how it was set up and they know they know where the I hate to use the analogy, but they know where the bodies are buried in their infrastructure, and what made it tick. And you don’t want to lose that knowledge. Instead, you want to try to hopefully work with them to stand up the new one and give them some governance over how that runs. That might be an approach. But it does get tricky.

CC: Yeah, it makes sense because at the end of the day, it’s still about people. The people that you’re working with, you wanna make sure that they’re, the people on the team that are creating the content, it’s still about them, it’s still about the people at the other end of the screen or book or whatever, whatever kind of content you’re writing. Yeah, it’s still about people and people are complicated. We are.

BS: That’s putting it lightly.

CC: Yeah, that’s my deep wisdom for the day. That’s what comes from five cups of coffee in the morning. And on that note, I think we have exhausted every part of this beverage analogy for single sourcing and content strategy, but it was really helpful even for me to hear. I mean, I knew some of this, but there was a lot of this that I hadn’t thought of in terms of something very tangible like drinking coffee or drinking beer. So thanks Bill for exploring this with me. I also just love talking about coffee anytime it’s possible. So yeah, it’s great.

BS: It was fun.

CC: Well, yeah, thank you so much for being here and thank you for listening to the content strategy experts podcast brought to you by Scriptorium. For more information, visit scriptorium .com or check the show notes for relevant links.

The post Brewing a better content strategy through single sourcing (podcast) appeared first on Scriptorium.

SO: “When I envision this in the ideal universe, it seems that the most efficient way to solve this from a technical point of view would be to take the DITA standard, extend it out so that it is underlying these various systems, and then build up on top of that. I don’t really care. What I do care about is that I need, and our clients need, the ability to move technical content into learning content in an efficient way. And right now that is harder than it should be.”

AP: “Oh, entirely. And I would even argue it should go the other way, because there is stuff possibly on the training side that the people in the product content side need. So both sides need that ability.”

SO: Right, so give us seamless content sharing, please. Pretty please.”

Related links:

• The business case for content operations (white paper)
• Ask Alan Anything: Resolving pain in content operations (podcast, part 1)
• Developing a strategy for learning content
• Prerequisites for efficient content operations (podcast)

LinkedIn:

• Sarah O’Keefe
• Alan Pringle

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. You may have heard that Madcap has added a learning content management system called Xyleme to their portfolio. In this episode, we are providing an entirely unsolicited roadmap to the vendors in this space, including but not limited to MadCap, for enterprise content ops software as we move forward. Vendors, welcome to the show and think of this as your roadmap to success and call us if you need help. You totally do. Hi there. I’m Sarah O’Keefe and I’m here with Alan Pringle.

Alan Pringle: Hey there, I’m not sure this is the best idea, but we’re about to find out.

SO: Yes, it’s going to be great. We will totally not get in trouble. Alan, let’s dive in and maybe get in trouble as fast as possible. What is the number one item on our list of demands for content ops enterprise software?

AP: Going to vote for seamless content sharing and with a little asterisk here this is not just about us as consultants I think this is as much about our clients and what we have seen over the past few years in the content operation space. We need some kind of way where you can author in a component content management system and then turn around and use that information, for example, in a learning content management system. And there’s, well, exactly, and I was just getting to that. There’s some logistics here. It would be maybe nice to have the same content model underlying all of this, but considering the different authoring audiences, I don’t know if that necessarily has to be the case.

SO: And does that have to be DITA?

AP: I really I’m not even sure if it’s possible. We can discuss that right now. It’s really not possible. I don’t think.

SO: Yeah, as far as I know, nobody can do this right now. You cannot take DITA content and efficiently ingest it into a learning content management system. If I’m wrong, call me.

AP: Yeah. That said, I do know some people, including our clients, who are on the learning training side, and they have chosen to use DITA as their model. But that is not true for every learning organization on this planet, not by a long shot.

SO: And they’re in CCMSs. They’re not in “L” learning CMSs. So they’ve, you know.

AP: Exactly.

AP: The LMS is a target. It is not the place where they are actually building the content.

SO: Yeah. And so, I mean, when I envision this in the ideal universe, it seems that the most, you know, efficient way to solve this from a technical point of view would be to take the DITA standard, extend it out so that it is underlying these various systems, and then build up on top of that. I don’t really care. What I do care about is that I need, and our clients need, the ability to move technical content into learning content in an efficient way. And right now that is harder than it should be.

AP: Oh, entirely. And I would even argue it should go the other way, because there is stuff possibly on the training side that the people in the product content side need. So it’s both sides need that ability.

SO: Right, so give us seamless content sharing, please. Pretty please.

AP: Yes, and I’m going to throw the ball to you this time. What’s number two on our list of demands?

SO: Number two on our list of demands is a unified portal for content delivery. So setting aside the authoring issue for a minute, you know, maybe it’s unified, maybe it isn’t. Give the end user a seamless user experience where they’re going in and they can get all the content they need across all the different, you know, technical content types. Now, there are a couple of specialized portal vendors that do have this and have solutions in this area. But if you’re going to position yourself as we are the solution for all things content, then this needs to be in your portfolio in some way, not just, oh, you know, go talk to this other vendor. So I think a unified content portal, again, I don’t really have a strong opinion on how this needs to be done from a technical point of view, other than words like seamless and good customer experience.

AP: I do have some opinions on how technically it should happen and that is copy and paste from one tool to another better not be part of this picture at all because today it is and it kills me. Especially on the product content side, we got over this hump of automated formatting or manual formatting. We’ve pretty much handled that. I think on the learning side, they’re starting to understand they should not be futzing and manually touching things. And right now, especially on the training content side, to get things to go to different delivery targets, there’s entirely too much copying and pasting between and among tools. It’s like every delivery portal requires you to do that. This is the 21st century people and it should not be happening, no.

SO: So okay, I would like to revise my opinion too. I do have some demands and they are those. I am co-signing Alan’s demands. Okay, what’s next?

AP: Hahaha! Okay, let’s talk about classification, taxonomy, because you gotta be able to label your things to sell different versions. If you’re selling software, you’ve got a light version, you’ve got a professional version and maybe an enterprise level solution. You gotta build in that taxonomy, that intelligence. How are you gonna do that? And how are you gonna do it across multiple content types? That’s tricky, that last bit in particular.

SO: Yeah, and so, you know, the terrible keyword here is enterprise taxonomy, right? You have to build out a classification system for your content, both for the authors and for the end users. Like, the end users need the ability to say, oh, I bought the lite version, only show me that. Not, all these enterprise level features that you don’t have. And how many of us have seen the infamous like car manual that says, oh, if you have the XYZ CXE extended edition, you have this feature in your car. Well, I didn’t buy that version and I don’t have that feature and.

AP: That just happened to me with a printer. I will not name the manufacturer because I’ve been happy with it overall, but the user guide, it actually came with a printed user guide, which was shocking for 2023, which is when I bought it. It was like, and then it will do this, and this. And then it’s like a little parenthesis later. And this model only. Well, that’s not the model I have, man. You’re killing me. So yeah, that’s not where you need to be with that kind. New.

SO: Oh man.

SO: Yeah. And you’re not going to run out and buy the upgraded printer or car. That is not happening. Yeah, it’s too late. So OK, so we need labels so that we can do versioning. But additionally, in this sort of enterprise content ops demand, we need those labels to be consistent across shared content. So for example, in the.

AP: Too late.

SO: And I’ve seen this happen. In the technical content, we have free, pro, and enterprise. And then the learning content, we have light, intermediate, and enterprise. And they’re referring to the same thing, but the labels are different. And hey, guess what? That’s not going to work. So fix it and give us a classification system, a taxonomy that we can use across all these different content dimensions. Now again, there are some tools that’ll do this. I mean, there are enterprise taxonomy tools, barely, some people are using them. Many, many, many people need to be using them and are not, so.

AP: There are.

AP: Right, I was about to say many people are using them and even more should be using them right now. And I will almost give people a pass on this one, almost, almost because it’s like get your ops to a certain point and then this can be let’s improve them even further. But having that built in from the get go, that would not be a bad thing either at all.

SO: Yeah, and related to this terminology, the words that you use for different things. If my learning content talks about a door and my technical content talks about a doorway or an entry point or an I don’t even know, then that’s not going to work. So you need to call the thing what it is and do that consistently across all of your content.

AP: Including your marketing content because if you’re talking about brand and consistency and voice this is a huge part of that and I’m sure your marketing department would be delighted for there to be some controls, some kind of corralling of this to be sure people are consistent and give a consistent brand image but the way we refer to things.

SO: All of it. Yeah. Yeah, and it also ties into some, you know, typically some protection for trademarks and those kind of branding and those kinds of things. And this isn’t, you know, the focus of this, but if you are translating or localizing your content, you have to do this work in all your languages, not just your source language.

AP: 100% and if your source language is crap, the translation is going to be crap too as far as consistency and anything else. Yeah, right, degrade.

SO: It’ll be crappier. It’ll always degrade slightly. So yeah, okay. And then what else have we got in our unified hallucinations slash vision?

AP: There’s one more. Yeah.

Yeah, it’s like we want everything. The last one, that’s yours. I’m gonna give that to you.

SO: Oh, so, you know, we’ve talked about unifying technical content, marketing content, help content, maybe UX content, those kinds of things. But there are two other missing pieces, which you touched on marketing, that’s one, and that’s a big one. And the other one is knowledge base, support content. So you know, where are those in this unified vision? All of these things are…

AP: Yep.

SO: …from an end user’s point of view, they look at all of this content, and yet all of it is being done in point solutions, in dedicated, this is only for the knowledge base, this is only for marketing, this is only for tech comm, this is only for whatever. And so we need to unify all this stuff so that there is in fact a unified customer experience. I don’t see a whole lot going on here with knowledge bases. If you look at marketing content, there are a couple of vendors that have ways to take the technical content and push it over or integrate it into the web CMS. But in general, this is much more challenging than it should be. And depending on your web CMS, you may or may not have a path for this at all, other than put it side by side or something like that. So I would…

AP: And news, yeah, and news flash, guess what? The people reading your content do not give one about how you classify this as sales or marketing or KB or whatever. They just want the information and they want it right then and now. And in a way they can get to it very quickly. They don’t care if you think this is quote marketing content. Just give it to them and make, be sure it’s correct, please. P.S. That’s also very important.

SO: Yeah, and I mean the reality is that people’s websites reflect their org charts and there are all these points solutions and different people own different chunks of the website or subdomains or whatever. But okay fine you know if you’re going to have these acquisitions and tell me how great it’s going to be then show me the results, and this is what this is what we want.

AP: Well, we are asking for the world’s, we might as well get all of our demands out here and that is certainly one of them. All these tools really kind of support these increasingly false kind of classifications based on org charts and whatever else, but the end result, the end content result, shouldn’t necessarily reflect those things, there should be unification there, not these weird distinctions that are based on the way people report to each other within the company, because your customers don’t care.

SO: So while we’re making friends and influencing people, we did also come up, as always, we did also come up with a list of things that we do not care about. So what you got?

AP: As always, as always.

AP: Yeah. I do not care that you have four or five different solutions that do different things under your brand, especially if they don’t talk to each other. If they’re just these multiple tools speaking to different audiences, how is that really any different than, you know, different people owning different things? I don’t, there’s a disconnect there for me, a huge one.

SO: Yeah, and, you know, single, we have, you know, single vendors with lots of tools, which may or may not integrate. We have multiple vendors with individual tools, which again, do or do not integrate like the level of or the degree of difficulty in integrating these various tools does not appear to be particularly tied to whether they live under the same roof or not. You know, fix the integration. I don’t really care about the ownership. I understand that from a business point of view, you do, that’s fine, but fix the integration. And so to my vendor friends who are currently apoplectic, you know, have a drink, whatever, of choice. But your mission, should you choose to accept it, is to address our pain points and our customers’ pain points and actually deliver on the challenge of unified content. And I am so looking forward to seeing progress in this area. Alan, any closing words?

AP: I think I am going to throw back to the Willy Wonka and the Chocolate Factory movie character Veruca Salt and say, “I don’t care how, I want it now.”

SO: Thank you for listening to the Content Strategy Experts Podcast. I have nothing to add to that. Brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

What do you want to add to this wish list? Leave your thoughts in the comments below, or let us know on LinkedIn!

The post Our demands for enterprise content operations software (podcast) appeared first on Scriptorium.

“I think about enterprise-wide applications. Consider the tools that are used to generate help solutions. Let’s just use Jira as an example. You have a knowledge base, enterprise-wide, and everyone at the organization has access to ask a question or search the knowledge base, or something like that. That’s where I want to go, that’s what I want to see. I want my learning experience platform to be like that. I want a knowledge base that I can tap into any place, anytime, anywhere. And then, have my mastery checked in the ways that I want to have it checked. ”

— Phylise Banner

Related links:

• Wrangling the Meg of learning content
• Content operations for elearning content (podcast)
• Developing a strategy for learning content
• Flexible learning content with the DITA Learning and Training specialization (white paper)
  

LinkedIn:

• Phylise Banner
• Alan Pringle

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Alan Pringle: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize and distribute content in an efficient way. In this episode, we’re talking about how people in the learning space are addressing challenges in their content operations. What do those changes mean for learning management systems? Is this the end of the monolithic LMS?

Hey, everybody, I’m Alan Pringle. Today, we have a special guest, Phylise Banner. Phylise, welcome. Please tell us a little bit about yourself and your background. 

Phylise Banner: Sure. Thanks for having me, Alan. My name is Phylise Banner. I’m a learning experience designer. I have, I want to say, over 25 years. I did the math the other day, actually. It’s about 27 years in higher education, and corporate and non-profit government learning design. Before that, I worked in data visualization and information design. I came into this field in a little bit of a different way, although there’s other folks who came in it the same way that I did, considering this from an information perspective rather than from a teaching perspective. 

The minute I started working in the field, I was fascinated by educational theory, and pedagogy, and philosophies, and andragogy, and hudagogy. And techno-hudagogy, thanks to my friend Bill Pelz, there. But throughout the years, I have watched technology evolve alongside learning theory, and I’m fascinated by that. I had been in the content strategy space this whole time, both from the information design, data visualization side, also going over into learning design. I’ve had a focus on content strategy all along. I’ve known folks at Scriptorium for probably 25 years. 

AP: Well, probably so because we’ve been around since ’97. And we have crossed paths in conferences probably more times than we can tell people. Indeed.

Well, with your background, you’re the perfect person to talk to about this, in the learning management system, LMSs, and what’s going on with them because we’re certainly seeing a shift. And you’ve got your feet even more firmly planted in the learning space than we do. I’m very interested in your perspective. I think a good place to start, especially for people who may not necessarily be in the learning space, maybe even a little more content focused, let’s start with a quick definition of what a learning management system is and what it does for an organization. 

PB:  Oh, I didn’t know that was going to be on the test, Alan. 

AP: Curveball.

PB: Curveball. I’m not going to have the ultimate, perfect definition of what a learning management system is. If we want to talk about a content repository and what different content repositories look like, overlay a content repository, content management system with registration. The ability to create courses, to offer courses and show progress through those courses. Whether it’s simply content, or content interaction and assessment. I would say those are the features that would differentiate a learning management system from a content management system. 

Early on, when learning management systems started to become more widely available, the joke was all it is is a content management system with the ability to register thrown on top of it. But there are so many pieces that are built into learning management systems these days, which is why the behemoths got to become behemoths. With student privacy, the data that’s being collected, learner privacy, the interactions between student information systems. Setting up the databases behind the scenes, so that it would be possible, back in the day, for a student information system, akin to Banner, Banner is one of the systems, to be able to talk to the data in the learning management system. 

AP: Sure. The people that use these LMSs, and I’m talking more about the trainers, the learning people, what’s the general process for creating content and getting it into one of these LMS systems? What’s their process? Or, does it vary from system to system? 

PB: It varies from system to system. It also varies from practice to practice. If we want to talk in any learning space, imagine a training session … We’ll talk about a physical learning experience, where you’re all designated to meet in the same place. You all show up in the same place. Someone walks in the room, drops a bunch of material or folders on the desk, and walks out of the room. That’s how most learning management systems are used. Unfortunately, it’s the way they were designed. It was upload your file-

AP: A dumping ground, essentially. 

PB: Exactly. A dumping ground with no context. That’s the same as someone just dropping … I used to do that when I did training. I’d come in, I’d drop it on the table, I’d walk out and say, “That’s what you’re doing to your learners.” If you don’t provide context for your information, that’s exactly what you’re doing to your learners. 

The process depends on the tool that’s being used. So we’ll say, am I using one of the big tools. Let’s say it’s Canvas, or Moodle, or Brightspace, or even if it’s Teachable, or Kajabi. It depends on how the LMS itself, or this learning platform, is enabling you to structure a learning experience and upload content, create assessments, enable interactions. The instructional design process or practice needs to happen first. 

AP: Right. 

PB: We need to design this learning experience. We need to consider how we want the learners to progress through that, how we want them to communicate with each other, with an instructor, with themselves. It’s sort of there’s no right answer to your question. 

AP: Sure. That’s true, even on the content side too. It leads into what I want to talk about next. It sounds like dumping ground, or maybe better than dumping ground, there’s still going to be some challenge and obstacles, especially to assign any intelligence to all of this content that you’re putting into these systems. What kinds of things, in general, do you see these people who are creating this learning content, what kind of hoops are they jumping through? What kind of workarounds, what things are they doing to get things to work better in these systems? 

PB: I’m going to roll it back a little bit, and talk about when learning content has typically developed, and shared, and reused.

AP: Yeah. 

PB: Because that reuse is something that we didn’t think about very much. Not everyone. 

AP: You’re not the only industry, either.

PB: Right. 

AP: Learning folks, we’re not slamming you at all because, trust us, it is a problem everywhere. 

PB: But coming from an information design space, reuse was always in the back of my mind, and classification’s always in the back of my mind. 

AP: Sure. 

PB: Having always known what a library system could do, what a database could do, how classification could help organize any type of information. Taking a look at learning management systems, and the ability to tag content and content types has been missing. 

AP: Yeah. 

PB: All along. I remember when I could first build a course in WordPress, and was able to program the heck out of that backend, and classify learning content, classify activities as activities. I also remember Angel, the learning management system, where we could do that within a learning object repository. And then, Blackboard acquired Angel so that went away. 

But, I think the struggles we’re up against now to make things talk to one another, our learning content repositories, our learning management systems. If we’re using these old, big solutions, there’s Lectora. I don’t want to go through and just bring out all these names. 

AP: Brand name salad, yeah. 

PB: Brand name, yeah, salad. But the newer tools are really taking into consideration how we might reuse content. How we might want to, how we might need to. 

Some of the things you and I have talked about in the past, and other folks at Scriptorium, are the possibilities of even going as far as using micro-content. Or the DITA learning terms, to really tap into those frameworks to become a little bit more consistent with tagging our content so that we can reuse it. 

One of the things that I see, one of the biggest challenges I see right now is you’ve got the training department, and the marketing department, and the documentation department not able to share content, using different systems. You see this all the time, Alan. 

AP: We do. We do.

PB: That’s your job. How do we make that go away? 

AP: You’re speaking my language. Yes, you are. 

PB: Yeah. 

AP: We have noticed, we have more clients from the training space now. They are really up against what you just talked about. Reuse and the single source of truth, those are two things that really, a lot of them, their hair is on fire because they are being forced to do copy-and-pasting for different versions. Copying and pasting from one system to another. 

PB: Right. 

AP: It’s my observation, and you can tell me if this is unfair, that a lot of tools marketed to the learning groups seem very closed and do not play well with others, at all.

PB: Completely. Completely. 

AP: Yeah. 

PB: We see that changing a little bit.

AP: Good.

PB: Once we started becoming comfortable using APIs and getting things to talk to one another. But the thing that’s still missing is that centralized database of information. 

You’ll hear the term learning experience platform being thrown around a lot these days. The way I have seen them used, I have never seen one used to its full potential. If we want to talk about how are we including or taking into consideration informal learning, what I learn in my kitchen about my job just because I happened to learn something that has something to do with something else I’m …

AP: Sure. 

PB: Just these tangents and things like that. And, how we capture them.

I am going to call out a product. I want to call out Docebo. The folks at Docebo know I love them. I’ve seen the best approach to learning experience platform, With the standards that exist in the learning space. You’ll need to find someone whose more versed in SCORM than I am, which is the standard for exporting and importing across different platforms. But that’s just taking a package, and downloading it, and putting that package somewhere else. It’s not letting one assessment, or seven questions from one assessment, talk to a different learning experience. 

AP: Yeah. I compare a SCORM package almost to an ebook, like an ePUB file, which is basically a container, a ZIP file really, a container file, full of HTML files. A SCORM package is very similar. It is just a container for a lot of files. 

I will tell you, one of our clients has been concerned about SCORM packages from an intellectual property, IP point of view, because the second you let that go and it’s just manually uploaded or imported into a system, it can be hard to get controls. But you’ve already mentioned APIs, there are ways to make virtual SCORMs, almost like an API, where you can hold onto it. But the traditional SCORM package, if you just hand it over, I’ve just given you my stuff.

PB: Yeah. 

AP: What if there’s an update, what if something’s outdated, whatever-

PB: Exactly. 

AP: It’s a big mess. I have also noticed that we will create automated transformation processes to basically create SCORM packages so people can put content into an LMS. The problem is LMS A likes a slightly different version of SCORM than B. Yeah, it is a standard, but there are flavors within that standard, we have observed.

PB: Exactly. 

AP: Yeah. 

PB: Oh, exactly. Yeah. 

AP: That’s another big pain point. But what I’m hearing from you is it sounds like two things are going on. Some of the vendors, the companies are getting wiser with letting people create smarter content, number one. Number two, people are starting to move to those platforms and realize maybe the older ways of having just that LMS sitting in the middle, that pretty much it, maybe is not the way our things need to be. It needs to be connectivity, there needs to be a wider ecosystem of tools that’s not just in your department. It needs to be cross-departments, in a lot of cases, in organizations. 

PB: Absolutely. I think about enterprise-wide applications. Consider the tools that are used to generate help solutions. Let’s just use Jira as an example. You have a knowledge base, enterprise-wide, everyone at the organization has access to ask a question or search the knowledge base, or something like that. That’s where I want to go, that’s what I want to see. I want my learning experience platform to be like that. I want a knowledge base that I can tap into any place, anytime, anywhere. And then, have my mastery checked in the ways that I want to have it checked. 

AP: Sure. 

PB: A lot of times, the learning management systems are talking about being really focused on the learner, and more adaptive. I’ve seen adaptive systems, and especially with generative AI being so widely available. 

AP: I wondered if that was going to come up. There we go, the requisite AI mention. 

PB: We’ll get there again. The adaptive pieces, what I’m seeing are in content and serving up content. 

AP: Yeah. 

PB: Adaptive learning means you’re giving me different content because maybe something I’ve searched for. But are you giving me a different assessment? Are you giving me an different option to interact? This is where I see the future of learning experience platforms going. 

AP: Sure. 

PB: That it’s the experiences that I have will be different, will change. I haven’t seen it well done yet. I want someone to show me. 

AP: Well, even on the content side of the world, because we’re focused, Scriptorium, on the product content side of the world. You talk about, “We need to deliver omnichannel content, we need to deliver content, what people want at the time they need it, and the format that they want.” Yes, that sounds great but not everybody is doing it. So again, this is not just about learning folks. This is a problem that’s universal. Yeah, I think there is a lot of room for improvement. 

Wherever content is, you have got to have, your source has to have that intelligence built in that lets you do that adaptive content on the fly. A quiz based on your location, and you’re at this particular branch, or at this particular hospital, or this location so you’re going to get this training. If you don’t have that intelligence, metadata, yeah I said, built into that source content, and then it needs to be processed by the various systems, you’re sunk. That goes right back to you’ve got to start during the creation process and get that intelligence built into that content so you can do the adaptive things that you are discussing. 

PB: Yeah. You talk about being in that place, or that space, and being served what’s appropriate in that moment of learning need. I’m fascinated by location-based tools. Lidar, iBeacons, like when I walk past this, I might need to learn something different in order to do something past this point. I think all of that is really important.

Let’s go into AI.

AP: Yeah.

PB: We touched on it. We don’t know what might come next.

AP: Yeah.

PB: I’ve embraced it. I love playing in this space. Anything that can help with the … I talk about dreaming drudgery design in development, and anything that can help with the drudgery piece is always welcome in my book. 

AP: It’s hilarious you said that because I was about to say we see it as another tool. If it can handle the drudgery of content creation, there’s several things I can think of. It could help you sort. It could help you … Yes, people still index things. Why not let AI take a whack at it? It may not be perfect, but then you can go clean it up. Any kind of pattern matching, that sort of thing, I think it does very well.

Now, we can quibble about should you be going out on open sites and dumping your corporate information in there. 

PB: Right. 

AP: But if you’re in a closed, large language model that is specific to your company, your organization, why not let it look at your stuff and find relationships that you probably don’t have the time to go dig around and find, and it can. It’s just another tool. Do I think it’s going to replace content creators in any space right now? The only space where I think it might is if you are someone who is cranking out low-quality content, of people who do, shall we say, not entirely truthful reviews on various sites, things like that. Things that can be put together fairly quickly, I think there might be problems for those kind of people, low quality content. But when you’re talking about the spaces you and I are in, I see it more as a tool and not the replacement. 

PB: Absolutely. A lot of what I love about this community, we talk about documentation and training on new products, well nothing exists. 

AP: Yeah. 

PB: We can’t tap into existing content to generate this content. In the learning space, I see so much potential for different types of tutors based on information that we have, existing knowledge. 

You talked about intellectual property earlier, and that’s a big deal. 

AP: Very. 

PB: On the higher ed side, there’s the open education movement, open education resources, and just open education about enabling more access. I’d love to hear your thoughts on what open access looks like in this content space, the struggles we have and maybe what advice do you have for protecting intellectual property, but sharing content? Creative Commons licensing is a beautiful thing, and being able to share learning content would be so helpful but we don’t go there. Companies spend so much money creating from scratch, the same trainings that other companies are creating.

AP: Right. 

PB: I just think about all the compliance training I’ve written in my lifetime. 

AP: What you’re talking about is a tightrope, and it’s a very difficult tightrope because we are a profit-based society, unfortunately. This is business. It can be very hard to give things away. 

I’m going to toot Scriptorium’s horn here for two seconds, in this regard, because what we did is we created a WordPress-based site called learningdita.com, to teach people about an XML specification, the Darwin Information Typing Architecture. Which, by the way, can be a very good fit for learning content. We basically created that where it is out on GitHub, you can download the source files, do whatever, and then you can take the classes for free. This was our thought on that. We are proving our own bonafides in this space, the DITA space, by putting these courses together, but then they benefit people too. And I’ll be blunt, they also benefit our clients because instead of paying someone to pay for an introduction to DITA course, people can take it at their own pace, through this self-paced learning that’s online, and do it that way to get a baseline and it also saves the client some money. It doesn’t even have to be our clients, anybody can go out there and take advantage of this free training and not pay for it.

March 2025 update: We have moved LearningDITA to a new platform. The Introduction to DITA course is still free, and you can sign up for courses at store.scriptorium.com.

You really have to think very carefully, bigger picture, how this could pay off. If getting content out there, if providing some open training, open source training to people, it can help you indirectly. It can prove your competence in topics. That’s the angle that I’m coming it. I don’t know if that exactly answers your question, but that’s where my brain has gone. 

PB: No, I like that. I wonder, can people reuse and reshape it? If it’s on GitHub, it’s there and someone could take it-

AP: They could take it, and adapt it, and they can take that source.

PB: Yeah. 

AP: Basically, the site that we have, a learning management system that sits on top of WordPress, that is ours. That is just one instance, one instance of how you could use this content. If people wanted to take that content and then do something more print or PDF based, or some other format, they can. We’ve even had some other people in our line of work, in different parts of the world, take that GitHub content, translate it, and then create their own instances. In German, in French. That same content is out there and it’s been localized. If you want to, you can go to their learning DITA sites and do it through that language, if you’re more comfortable in say German or French. 

PB: There’s nothing to stop someone from taking it and charging for it, either. 

AP: If they wanted to, they could.

PB: Yeah. 

AP: Again, everything that you said, these are the kind of considerations you have to think about when you put things out there for free.

PB: Yeah. 

AP: It’s like you’ve got to let your child go out into the world and do their own thing. I’m comfortable with that, because at the end of the day, a more informed world about DITA, in our case, that is a possible customer for Scriptorium down the road. That is very business-y and maybe even a little repellent to put it so bluntly, but there you have it. There is a case for providing free, open source information, even from a for-profit corporation. 

PB: Absolutely. Absolutely. For those of you that are listening that are not familiar with Creative Commons licensing, I highly encourage you to go out and take a look, to see what the different types of licenses are. Because there’s that non-commercial use that I would recommend, in many cases. But, I like to think about learning content and the levels at which we would share it. 

AP: Yeah. 

PB: I would love to see more collaboration. Not just across departments, but across organizations. 

AP: Yeah. 

PB: I don’t know how we do that. 

AP: And again, there’s goodness to be had, but sometimes in a profit-driven situation, longterm thinking is not the motivator. Short term profits are the motivator, so it gets very sticky in there. 

PB: Yeah. 

AP: Unfortunately. Because at the end of the day, if you’re a for-profit corporation, you’re not there for the sake of giving things away. You’re just not. With education, I think it’s even a little stickier perhaps, because you are talking about trying to improve people, their knowledge, to give them more information. Where do you draw that line? 

PB: I’m going to stop you there and say okay, if we separate this out into knowledge, skills, behavior, attitude-

AP: See, this is the learning person talking right here, and I’m going to sit back and let you do it. 

PB: Knowledge, skills, behaviors, attitudes. Let’s think of, what if for skills, because yes there are some skills that are unique, but what if we shared that learning content? I can’t tell you how many times I have reinvented the wheel.

AP: Oh, sure. 

PB: Every other learning designer has done the same exact thing.

AP: Yeah. 

PB: That’s our job, to continuously reinvent the wheel.

AP: Yeah. 

PB: Maybe, we need one giant learning experience platform, where we can have skills. I would say, knowledge, skills … Think about how we’ve learned, and how you want to learn, and how you will learn in the future. I’ve heard people come out and say, “I don’t want to learn from a robot.” You already have been for years and you may not have known that, but you have. The expertise that we’re relying on in any learning experience when we introduce an instructor, we need to factor that in. What does it mean if instructor A has this content that they’re delivering as part of a learning experience, or instructor B has that content and they’re delivering this learning experience? Are they going to be two different experiences? In my mind, yes. They’ll be different, depending on the individual’s expertise that they’re bringing. But is that going to get minimized, will that go away? 

I’m rambling on here, Alan. I’m so sorry. But now I’m thinking of influencers, and influencers online, and product influencers. They’re educators, too. 

AP: They are. 

PB: Where does that content lead us when we’re learning from TikTok, or we’re learning from Instagram?

AP: Sure. 

PB: Gosh, I’m all over the place, here.

AP: No, it’s a valid point. I know a lot of people who, they run to YouTube for a video to learn how to do things. This drives me back to the question I would like to wrap, is okay, with all of these changes that you’re talking about, all this sharing that needs to be going on, all this reuse that should be going on, what does that mean for the LMS, from your point of view? 

PB: Well, this is a dinosaur I would like to see hit by a meteor tomorrow. I have never been a fan of the learning management system. I think that the information repository with the ability to customize the interactions you want is what an LMS needs to be. Too many times, I have been forced into designing, developing and delivering a learning experience around the limitations of the learning management system.

AP: I have seen clients do exactly what you just said, and they hit a breaking point and they say, “No more.” 

PB: Yeah. They’ll sit there and say, “No more,” until someone offers them a solution. What is that solution going to look like? What I see that solution looking like is a lot of pieces that fit together. That it’s app salad, strung together with a central content repository, that can be classified or searched.

There is a learning experience platform out there that you can just create these adaptive learning experiences, and there is no tagging, there is no metadata. I know that they’ve used large language models to generate results, but I still don’t love it. 

So for me, the future for me, the meteor may not hit. It may be a slow death. I’d like to be there when they bury Blackboard. Just throw a handful of dirt on that LMS. But I’d love to see someone come up with a solution that helps us stop reinventing the wheel, helps us invent a new form of transportation that we don’t even know about, to push that metaphor a little too far. 

AP: No, but I think that’s a very good place to end it. Future thinking, some positivity, but there’s some real work that needs to be done before that.

PB: Absolutely. 

AP: Phylise, thank you so much. This conversation went to some really interesting places that I didn’t expect and that is always a plus on a podcast like this. So thank you so much for your expertise, we deeply appreciate it. 

PB: Oh, thanks for having me. I love you folks at Scriptorium, I love the work that you do. I love the way that you educate folks. And maybe, someday, we can partner and solve this problem together.

AP: A lot of people would be very happy if we did, indeed. 

Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Rise of the learning content ecosystem with Phylise Banner (podcast) appeared first on Scriptorium.

“I mentioned it before: invest in training. It’s very important that your team knows first of all not just the tool, but also the concepts behind the tool. The concept of structured content creation, leaving ownership behind, and all of those things that we’ve referred to earlier on. You’ve got to invest in that kind of training. It’s not just a one-off, you want to keep it going. Let them attend conferences or webinars, and things like that, because those are all instructive, and those are all things that will give good practice.”

— Dipo Ajose-Coker

Related links:

• Challenges of moving from unstructured to structured content with Dipo Ajose-Coker (podcast, part 1)
  
• MadCap IXIA CCMS
• Webinar: Everything is Awesome! A DITA Story: A webinar on Dipo’s experience migrating from unstructured FrameMaker to DITA XML
• Structured content: the foundation for digital transformation (podcast)

LinkedIn:

• Dipo Ajose-Coker
• Bill Swallow

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Bill Swallow: Welcome to The Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way.

This is part two of a two-part podcast. I’m Bill Swallow. In this episode, Dipo Ajose-Coker and I continue our discussion about the top challenges of moving from unstructured to structured content. 

So we talked about a lot of different challenges, and I don’t want this to be some kind of a scary episode for people. Let’s talk about some tips you might have for people, as they do approach this move from unstructured content to structured content. 

Dipo Ajose-Coker: Yeah. Now, I would always say the first thing is start small and then scale up. You need to take one example of each type of manual. I used to work with we had user manual, pre-installation manual, service manuals, maintenance manuals, and so on. Some of them are similar in that they’ve got similar type of content, we’re just removing parts of it. But some of them are really radically different. So we took one user manual, and one service manual, and one pre-installation manual, three major types of content. And then you convert that, test it to breaking point. And then, by the back-and-forth that you’re doing in making that the conversion matrix, so fine-tuning that conversion matrix, you’re more confident that, when you then throw the rest of the manuals in there, you’ll have a lot less cleanup. I’m never going to say that you’re going to have zero cleanup, you will always have cleanup. But you will have a lot less to do in cleanup, in manually going to look for those areas where the conversion didn’t work. 

I mentioned it before, invest in training. It’s very important that your team knows, first of all not just the tool, but also the concepts behind the tool. The concept of structured content creation, leaving ownership, and all of those things that we’ve referred to earlier on. You’ve got to invest in that kind of training. It’s not just a one-off, you want to keep it going. Let them attend conferences or webinars, and things like that, because those are all instructive, and those are all things that will give good practice. And share that in between. Maybe have a train-the-trainer type of program, where there’s one person who’s your champion within the company, and who does all the conferences, and does all that. And then comes back, and resumes, and trains the rest of the staff. 

Your migration must be detailed in the planning. You’re basically, “Step one, we’re going to do this. Step two, we’re going to do this.” I create phases of those because you might have to repeat a whole phase again at a different point in time. The phases, for example, verification of the content. Was what I put in what came out? When I compare my Word document and I compare the XML of it, does it match? And then, you’ll do a few things, and then you’ll publish. But you’ve got to verify again because some of those mechanisms, like I said, pushing content at publication, picking the wrong key, using the wrong DITA val would create different content. So again, you’ve got to do that verification again. You’ve got two verification phases, in that case. 

BS: Yeah, I think that’s actually a really good point. Because we also see that, even when you have a smooth migration of one particular content set, once you move on to a different manual, there might be something unique about that one that suddenly, everything goes sideways when you try migrating. And you don’t have a home, or you don’t have a structure planned for a certain piece of content that you probably didn’t realize existed. 

DA-C: I’d say also, you’ve got to be flexible. No matter how much planning you put into place, the plan is always 100% correct until you start executing it. And it’s at that point that you’ve got to be flexible and be able to say, “Okay, well things did not turn out right. Let’s adapt to that.” And by the end of that phase, we’ll be able to take a look back and say that, “Okay, well this went wrong at this point. Can we fine-tune it? Or is it something that we should just anticipate that it will always go wrong?” If you know that it’s always going to go wrong, you’d better able to plan for that. You know that you just need to add that step to the phase, to the next phase, in that check that this was as expected. 

Look at the long-term benefits. That translation example, in that first boom, bang, “We already paid for the translation six years ago. Why do we have to pay for it again?” The long-term benefit is that, six years ago, you paid 100 grand for your translation, say. And then, every year, you were paying 20 grand because of every update. So that’s six years of 20 grand, 120, plus your 100 initial cost. Then, you switched over to DITA, where they’ve promised you your translations are only going to cost you 10 grand a year from now on. Yeah. Well, that first hit is going to still be maybe not 100 grand, but let’s say 80. People balk at that and say, “Well, you said it’s going to be 10.” No. Because for the next six years, you’re only going to be paying 10. So in the long term, it is eventually costing you less. Apply that to whatever part of it, of the scenario you want. You find long-term, it’s best. 

If you look at what’s happening today, and I will only mention this once, ChatGPT and training large language models, and that. Well, training large language models on structured content has proved for efficient than just hoovering up content that does not have a semantic meaning to it, attached through the metadata. You know, attributes that you add onto that saying, “This is author information. Or this is for product X, version Y. But there’s a version X as well available.” All of that, if you look at it in the long term, those companies that have already moved to DITA are going to be better able to start quickly switching their content, repurposing it, feeding it to their large language models. Using it to train their chatbots. Their chatbots are better able to pick up micro-content. 

If you look at Google today, you search for something and you get this little panel. You know, that YouTube video that tells you which section of the video answers your question. That’s micro-content. And having structured content, because you’ve got smaller, granular pieces of information, enables you to provide that sort of granularity of answers. Your users are going to be happier in the long term.

You need to, let’s say, plan for compliance. We’ve already mentioned that. Look at how you’re going to manage your terminology because that’s another aspect. How are you going to, first of all, tag it? Making that decision is your information architect. Which element are you going to use? UI control, or are people still going to be using bold italics around that? And how are you going to enforce that people don’t use that non-standard use of the correct elements? 

Localization is another area that you need to … First of all, warn all your stakeholders. If there’s people that are going to be people for … Explain. Give this example that I just gave, that in the longterm your translations will end up costing less, the turnaround time will be faster, and so on. And, those issues that we used to have in that world, there was an update while it was out for translation, and then we had to pick up the PDF and highlight all those points that changed in between those two translations. That used to be such a headache for us. 

BS: Those were the worst. 

DA-C: Totally. And your CCMS is able to do that for you, in that it’ll send only the changed content. It can lock out content, I can lock out things that you don’t want translated. 

There’s nothing worse than sending your translations out, and you know that all your UI variables have been pre-translated as string files, and what you’re doing is just importing those and that then puts the correct term inside of those tags. Well, if you send it off and then your translators then decide, “Well, no, I think that’s a better translation for that UI label that is inside,” you’re just causing a whole load of trouble that’s going to come up and catch you later. I’m speaking from experience, again. Things that will get changed during a translation, your system can lock those things out. 

Another top tip is to invest in a quality translation service provider. Having a translation service provider that understands structured content is better than one who is just used to doing words translations all the time. They’re better able to understand the concept of, “Well, this topic is reused, so when I’m creating my translation, I must also translate with reuse in mind.” Looking at not breaking tags in content, not moving things around in the content, all of that training needs to be present as well on your translation service side. 

And, you’ve got to leverage your technology for efficiency. Major tip there is create workflows, create templates. Templates will help your authors know that, “Well, for this topic type, these are the sorts of information types that I need to put into it. This particular topic needs a short description, and this one doesn’t.” So by picking the right template, they’re guided. They can concentrate, they can focus on creating their content. 

Workflows. Oh God, workflows. That’s another big one in that review and approval workflows. What has been reviewed, what has been approved? If you’ve got content that’s already been approved, and then somebody goes and makes a change to that already approved content where it was not due for a change, that will cause problems during your audit. Because remember, you said you could prove to them that this topic was at version X, and we didn’t touch any other topics. Well, if you sent everything off, and then an SME made a change to one of the topics because they saw a mistake in there. 

Well, that’s not a good enough reason, when it comes to audit. That, “I saw a mistake, so I made that.” No, you need to follow engineering change management processes, which say that for every single change … I’m talking in regulated industries. For every single change, I must have a reason for change. I saw a type in the text and I just decided to change it is not a good enough reason. If you saw that, then you must create a defect and add that to the change log that you’re submitting to say that, “We changed these. Oh, and by the way, we were trying to fix this error. But as we were going through, we saw that somebody did not put any full stops in all the sentences in this topic, so we decided to raise that as an improvement opportunity, and we added to the docket.” So we have a reason why those other topics, which were initially analyzed as those are the ones we need to change, what are these other topics that got changed? Well, we also created a ticket for that and put it in there. 

So leveraging workflows will allow you to force things to go also to the right person. How many times have you forgotten to send it through to legal?

BS: Yeah. 

DA-C: Using the final approval workflow, make sure that okay, well the initial engineers are excluded from that because they’ve already done their workflow, but we’re sending it for that final boss-level approval, and legal can finally sign off on it. Those are the things that are parts of what your tool can do.

Your tools can also help you find out what went on where. By being able to roll back, “Well, we made this change. We thought it was an improvement, but eventually it was just a stop-gap, we’ve made a better one. Let’s roll back to before, and then create that new one that documents this.” Well, your toolset, your CCMS is able to do that for you. We used to have to do this, again talking from experience, going into the archive database, looking for one that was roundabout the date of the change that we made, picking that one out, unzipping it. And then, the whole load of trouble. 

BS: I remember doing that. 

DA-C: Use and leverage technology. Yeah. 

BS: I remember doing that quite a bit, especially when we’d have someone from legal running down to the engineering floor and saying, “Hey, we need to find X version from X date, and see if it contains this particular sentence.” 

DA-C: Yeah. Yeah. 

BS: That was always fun. 

DA-C: Oh, yeah. Totally. 

BS: And then, needing to roll back and then reissue all the other following versions with the correct change. 

DA-C: That was always a nightmare. I can remember, there was one particular incident where someone, again, had gone off on holiday. Again, ownership of documents and so on. This change had to be made. There was a stop shipment, which means there was a defect found and the regulatory body said, “You’re not allowed to sell any more until you fix this, and you make sure that it’s all done.” So connect stations, everyone. This person’s on holiday, so we go into the archives, look through, find what we thought was the right one. Only, that person that person had not checked in the real last version. So the corrections were made to the last but one version. And then, when you published it, some of the information that was supposed to be in there was not in there. But we were looking for that specific phrase, we found it. We thought, “Yeah, everything’s good.” Only by the time it goes out and gets off to the regulatory body. Then they say, “Well, what happened to all these other changes then?” 

So investigation goes on, and then you’ve got to find out why. Those are all parts of the reason that pushed this organization to say, “Look, we need something that handles this a little bit better.” We had a stop-gap interim period where introduced an SVN system, but that was on a local computer, and we were able to recreate repositories on everyone’s. But that relied a lot on discipline as well. People checking in stuff. And you could always break locks. I spent so much time fiddling with the SVN system on every update. It was just a lot, too much. The CCMS was able to resolve, let’s say, 80% of all those kinds of issues. I’ll never say that a tool is of 100%, but it does help quite a lot. 

BS: Yeah. Having had some SVN or GIT collisions in the past that we’ve had to unwind. Branches, upon branches, upon … Yeah. Having a system that can at least manage some level of that automatically is a godsend.

DA-C: Totally. 

BS: Well, Dipo, thank you very much. I think this will pretty much wrap the episode. But thank you very much for joining us. 

DA-C: Oh, thanks for having me. 

BS: Thank you for listening to The Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links. 

The post Tips for moving from unstructured to structured content with Dipo Ajose-Coker appeared first on Scriptorium.

“I think we could make broad categories of challenges as tools, technology, people, and methodologies, and I think we’ll just dive into these because they’re not necessarily independent—some of them flow one into the other. One of the most complex and challenging parts is implementation. Changing over to a new tool also involves changing processes and training the staff. Basically, some documentation teams struggle with that initial learning curve.”

— Dipo Ajose-Coker

Related links:

• MadCap IXIA CCMS
• Webinar: Everything is Awesome! A DITA Story: A webinar on Dipo’s experience migrating from unstructured FrameMaker to DITA XML
• Structured content: the foundation for digital transformation (podcast)
• Misconceptions about structured content (podcast)
• Unpacking structured content, DITA, and UX content with Keith Anderson

LinkedIn:

• Dipo Ajose-Coker
• Bill Swallow

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Bill Swallow: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997 Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about the top challenges of moving from unstructured to structured content. This is part one of a two-part podcast. Hi everyone. I’m Bill Swallow, and today I have a special guest. I have Dipo Ajose-Coker from MadCap IXIA. Dipo, hi.

Dipo Ajose-Coker: Hi there, Bill. Thanks for having me on.

BS: Can you let our listeners know a little bit about yourself?

DA-C: Yeah, I’ve got a background in languages and IT. I did a bachelor’s in that and then, well, almost 20 years ago, I made the move to come over to France, and as teaching doesn’t pay that much, I thought I’d retrain and to do something that still combines languages and informing people, and I found a master’s program for technical writing and that’s how I got into that. I did my master’s and I’ve been working in medical devices, financial technology companies as a technical writer, as a technical editor. Then a couple of years ago I got that itch to change professions again. I wanted a little bit more creativity in my writing, and so I went to content marketing, and so now I’m a product marketing manager for Madcap software representing MadCap Flare, Madcap Central, and Madcap IXIA CCMS.

BS: Excellent. Today we’re going to be talking about how you might be moving from unstructured to structured content and what some of the, I guess, challenges are in that move. I guess we’ll jump right in. I’ll just ask you what is one of the key challenges that people face?

DA-C: Yeah, I think we could make broad categories of challenges as tools, technology, people and methodologies, and I think we’ll just dive into these because they’re not necessarily independent, some of them flow one into the other. One of the most complex parts, the most challenging parts is the complexity of implementation. Changing over to a new tool also involves changing processes, training the staff. Basically, some documentation teams struggle with that initial learning curve. You’ve got to learn a new markup language, you’ve got to learn a new way of writing. Then you also need additional help mostly from IT. You’re getting teams that never used to be involved in helping you put in your Framemaker or whatever it is that you’re using. You didn’t need your IT department in setting up Microsoft Word, for example, where that used to be the writing tool, setting up CCMS involves a little bit more of a lift that documentation teams might not be experienced with or be comfortable with.

BS: The implementation really checks all of the complication boxes, doesn’t it?

DA-C: Totally. You’ve got so many more people involved and you’ve got time scales and everything as well to consider.

BS: I guess let’s dig a little bit into that. You mentioned conversion, learning a new markup system. What goes into that type of an effort?

DA-C: Okay, let’s look at the first thing. Everyone goes to school learns to write English, French, whatever language it is, but then when you want to start moving to structured content, it’s usually an XML-based language, XML markup, we say. It’s not real coding, but it is still learning a new vocabulary if you want a new syntax, a new way of expressing yourself. The fact that it’s structured then means that as you do in your own language, you have a certain way of creating a sentence. You have subject, verb, object, and so on in a particular order, it gives you a particular meaning. That also applies to markup languages. Writers have to learn, in effect, a new language, a new way of expressing themselves that is valid and that the machine at the end of the day… Because we are writing for machinery, when you start writing in XML that the machine can understand, so you’re learning a new syntax, a new vocabulary as well.

BS: I guess coming from that angle in learning to essentially write in a different language, there would be some cultural and probably some workflow changes that would need to happen there.

DA-C: Absolutely. Learning that language for some people might be easy and there’s lots of courseware that’s out there that can get you into that way of writing, but it does involve classes, training entire teams, and not everyone might be open to retraining in a new way of writing. Once you have trained those writers and they’ve got up to a certain level, you can only do so much training. Afterwards, the rest comes as experience. Then another big change that your writing teams will have to make is that ownership, that question of “I own this content, this is my…” Owning the source content is something for the past, it’s cultural change that has to happen within the team in that we’re writing for a team, we’re just contributors now. We contribute to a pool of information and you have to learn a way of writing that makes it that the content that you put into the pot can be used by other people.

My style of writing things might differ from somebody else’s style of writing things. All of those have to start disappearing in the way that the writers actually create that content, and that’s a big change for a lot of people. I’ve worked in teams where during the summer holidays someone says, “Well, okay, look, if there’s any changes, I’ll make them when I come back,” and even if there’s an emergency, they’ve locked down their files, you don’t have the latest versions and so on. You’re having to wait for that person to come back. If your teams, I suppose, one of the ways that you can make the medicine go down better is to let them know that they can own the output.

You own what you put together and in structured in DITA, you have the concept of maps and book maps, so well they own that because they’re the ones that have decided which topic goes before which, and so on so forth. Then when they press that button, the PDF or the HTML output that comes out of it, they can sign their name to that. However, in the creating of the content, you must start thinking “I’m writing for a pool,” as they used to have in newspaper, poolrooms. Everyone would contribute, and then in the end you have a whole newspaper.

BS: I think that would probably go doubly for any content that certainly is going to be written for reuse so that you are absolutely writing for your team and not for just your particular need.

DA-C: Exactly.

BS: All right, so going from old to new, let’s talk a little bit about data migration.

DA-C: Now, this part of it is, I think, one of the most complex and the longest parts of that migration from unstructured to structured. You’ve got to make decisions as to how you’re going to convert that content. Are you going to bring in an outside consultancy or are you going to do it one at a time? You’ve got to make decisions as to whether you’re going to continue updating content that is being migrated, whether to use a production and staging server, whether to wait for that pause. If you are lucky to work in a company that does not do Agile, for example, and you have big breaks in between product releases, you could say, “Okay, well we’re going to take that time to then create all the new content.” Do you also want to convert all of your content? If there’s stuff that you’re not going to be updating, this is your chance to get rid of all that stuff.

Just don’t convert it and know that whatever you find inside of your CCMS is what has a life and is able to continue living. Then you also have to consider that no matter how much help you get, whether you’re writing it yourself or getting a conversion done by a consultancy, there’s going to be some cleanup to be done because if your content was written so well in the first place in Word that you could create a matrix, mapping it directly to DITA, there was no real point moving over to DITA.

Basically, that content was good enough as is, so you are going to have to come back and go over the stuff and change strategies as you go along and think, “Okay, well, we thought we’d be able to reuse this, but actually maybe it’s best to have a branch of this or create a duplicate of that topic.” You’ve also got to think a little bit further forward as to how that content is going to be localized, it’s going to be translated, and some of your reuse decisions must also consider that part of it, as well. In that, is it something that is translatable or should we have separate topics, and so we’re able to translate them differently depending on the context and so on. I think that that shows just some of the aspects of that complexity of that data migration.

BS: Yeah, the localization angle is a big one because even if you had a perfect migration, the way that the content is now essentially tagged is going to be different than how it was tagged before. Even if the text doesn’t change, there’s still going to be some segmentation problems, so you’re not going to get that 100% match that you were looking for the first time out. It’s something that we actually caution a lot of our clients with, as well. It’s like, “Expect to take a hit on the first localization pass. You’ll get a lot of leverage, but it won’t be a hundred percent, and then from then on you’ll see a huge improvement.”

DA-C: Yeah, totally. Real-world experience, this is what we went through when I was working with a medical device manufacturer, and we planned pretty much what we thought for everything, and we had that in mind, all the advantages. Oh yeah, drop in translation costs and so on, and that was what was communicated to the engineering teams who were the ones that eventually paid for the technical publications and so on, you know the way companies work, different departments, different budgets and so on. Then we converted everything and it came to that first release and we sent them what we sent out for translation. We got that translation quote back, and it was just a little under what the initial translation was, whereas what we were doing was just an update of some of the content, and we had some explaining to do in that.

“Oh, yes, well look…” Because of the way, and as you said, segments are different, and if you look at the code for a paragraph in Word, you’d put a bold on there, and then that segment goes off into the translation memory, and it doesn’t matter whether it’s bold or not, the words, that paragraph is there as one segment. However, in XML, your bold is actually elements, B elements, before and after, and when the translation management system starts looking through it basically cuts off at that point where it encounters a new element.

It used to encounter P and then end with P/P, whatever. With this new translated migrated content, it’s going to start off with possibly a P, and then it’s going to come up in bold and then possibly another italics, and end italics and then UI control if you were doing things properly and things like that. Each of those becomes a segment, and so the translator then ends up with, “Well, it matches, but this changes,” those fuzzy matches do cost you a bit more. Think of when we had to go back to engineering and explain all of that in that further translations will cost a lot less, but this first one, you’ve got to be prepared to take that hit.

BS: Absolutely. Actually, speaking of costs, I’m sure there are others that we could mention here.

DA-C: Oh, yeah. Well, apart from training costs, which we’ve already brought in, while there’s free training, it’s never 100% free, because you are paying your staff while they’re doing that training, and so they’re not producing content, so it’s not free. You’re paying someone to do that, but you really should invest in formal training for your staff. There’s the initial setup costs, so there’s the cost of the software, there’s the cost to your IT department in putting in place all of these things. You might need to pay for someone to create the publication outputs that you need to have if you don’t have that expertise in-house.

You might need to also invest in a content delivery system because you were delivering PDFs before, but part of the whole content strategy is to have everything on a portal, on a website, and so well, there’s maybe cost that’s going to be added on to that. There’s the cost of the conversion. It’s either you’re paying a consultancy to do it or somebody in your team is going to be doing that and not working on the project that they’re normally working for, but these are all costs that will be in there. Some of them can be quite high and some of them would be just normal, one-off costs and so on. We’ve already talked about the translation.

BS: I guess let’s talk a little bit about the challenges of maintaining your consistency, because once you move to structured content, yes, structure has a series of rules. You can’t have this element before this element, and a lot of the systems enforce that for you, but what are some of the other things that you need to be careful about when it comes to consistency?

DA-C: Many teams think, many organizations think that once we’ve got this thing in there itself policing, if you want in inverted commas, you don’t need an editor, you don’t need someone to go over that because you’re overly reliant on the tools. However, you need to know that even if you have these rules in the order of elements that are allowed to be used, you might not want a particular element to appear in a particular type of content. For example, you have short descriptions of a particular type of content that you can add to your editor content, but it’s not always appropriate. Well, between user manual for product X, who is being written by Tech Writer One, and the same thing for another product within the same company, but it’s being written by a different person, one or the other might decide to include a short description, and they’re both valid.

They’re both valid topics. However, why does one have a shorter description than the other? You need that editor, you need someone who’s there to be able to take a look at that sort of thing and to help harmonize content across the different content types that you have. You would have maybe an information architect who’s there not just to help set up that order of elements and help your writers learn how to use and put them, but also who’s there to show good practice, who maybe has a session every month to just say, “Okay, well this is the best way to do this,” or “We found these examples. Could we make sure that we’re all following the guide for this type of manual, and this is the way we do it?”

Terminology is another big one in that, and you can either enforce it using a third-party tools that can plug in, or you’d have someone in there making sure that you’ve used this term. When you’re creating terminology lists, it’s not just a list of approved terms. You also should be looking at terms that are not approved.

BS: Absolutely.

DA-C: That must not be used.

BS: Absolutely. I would probably also mention the classic need for style, tone, and voice as well, especially now that you don’t have writers who own their manuals, “This is my manual. I wrote it from cover to cover, it has my voice, or it has my interpretation of the corporate voice in there.” But now you have a situation where you do have that reuse of individual topics in a myriad of different places, and if that style of that tone or whatever changes from one topic to the next, it’s going to be pretty jarring to someone who’s reading the whole piece.

DA-C: Yeah, a simple example is you have a writer who likes to use, “Please do this before you do that,” another writer who just goes, “Do this, do that.” If you are reading from one to the other, that can be really jarring and you might even take offense because you’re so used to the pleases and thank yous from one author, and then you get into this topic, which is actually a troubleshooting one, and you find you get this tone that they’re telling you off, whereas it was just a difference in style that should have been enforced globally.

BS: Yeah, equally jarring going from one topic to the next, active voice, passive voice, active voice, passive voice.

DA-C: Oh, yeah.

BS: Let’s see. We’ve got translation challenges, consistency challenges, some cost implications there, migration, overall cultural issues, and just the overall complexity of doing all of that work. Is there anything else we should mention here?

DA-C: Regulatory compliance.

BS: Ah, yes.

DA-C: I’ve worked in regulatory for pretty much all of my technical writing career, so that’s maybe about 14, 15 years of the 18 that I used to be a tech writer. Adhering to industry specific regulations can get very complex, and while the promise of having a CCMS with version control and being able to prove that this output was created using this version of this topic, I could get that whole list out and prove it to you. If it’s not integrated within the quality management systems of the entire enterprise, then you’ll find that certain departments will not accept that as proof. Also, the mechanisms between your source files and what you can produce with DITA, you’ve got different ways of compiling your final output, and there’s stuff that you use variables for and the stuff that you’re referencing by keys, and so it’s going to use this version as opposed to that version.

You can also push content at the point of publication, so you don’t see it in that source. However, when you do publish it, then you see this new word in there, how do you prove to the regulatory department that all that content is sane it is sound, it meets with the requirements and so on? That was another really complex thing that we had to deal with that. But by integrating the tools between each other, linking topics to requirements, for example, so you always have a requirements database, even if you’re using Jira, that’s your requirements database if you want, but if you can link those two things as a starting point, then wherever a requirement changes, for example, you know which topics are impacted. When you have to do a regression analysis, a topic impact, a change impact analysis, you’re better able to prove that to the relevant departments that, “Well, you changed this requirement. One, we’re sure that all the topics that did refer to that requirement were analyzed and we made the necessary changes, but we’re also sure that we didn’t create any fallback impacts on other topics in the entire manual.”

There’s a lot of complexity in that makes it that you really need to strategize from the start on how you’re going to respond if you’re a regulated industry, but then there’s also the part where it can help you. It’s a very interesting use case that I saw where we’re mapping DITA XML to machinery standards, and so a company that is an OEM manufacturer is able to supply the exact information required by each of the different subcontractors that we have by mapping that to the IIRDS machinery standard. That is a very interesting use case where regulatory and compliance is enhanced by being able to map those two standards and being able to push the right information based on the metadata attributes and things like that, that are tying both together. You’re easing some of the workload, the heavy lift that used to go on there.

BS: Very cool. I think this is a good place to wrap up, but we’ll be continuing this discussion in the next podcast episode. Dipo, thank you.

DA-C: Thank you very much for having me, Bill.

BS: Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Challenges of moving from unstructured to structured content with Dipo Ajose-Coker appeared first on Scriptorium.

“Design thinking is not a model first. It is a mindset that incorporates a strong inquisitiveness. What’s happening here? Who are the people that are being affected by whatever problems that are happening here? And what don’t I know that I need to learn before proposing any solutions? That’s design thinking in a larger understanding.”

— Dee Lanier

Related links:

Dee’s top 4 design models:

1. IDEO, 1978
2. Stanford d.school, 2005
3. Liberatory Design, 2016 (updated 2021)
4. Solve in Time!, 2019 (solveintime.com)

Books:

• Demarginalizing Design: Elevating Equity for Real World Problem Solving by Dee Lanier
• The Inner Work of Racial Justice by Rhonda V. Magee

Contact Dee:

• Website: https://www.lanierlearning.com/
• Email: dee@lanierlearning.com
• Twitter/X: https://twitter.com/deelanier

LinkedIn:

• Dee Lanier
• Sarah O’Keefe

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Welcome to the Content Strategy Experts podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way.

In this episode, we’re talking about design thinking with a special guest, Dee Lanier. Hi, everyone. I’m Sarah O’Keefe, and welcome, Dee.

Dee Lanier: Hi. Thank you so much for having me.

SO: It is great to have you. For those in our audience who don’t know, we literally met on a plane. So we were both headed to San Diego for different reasons, and had a really great discussion. And then I decided that that discussion really needed to be recorded, so, here we are. And thank you for being here.

DL: It was a fantastic conversation, and so I’m happy to continue it now.

SO: So, we complained a lot about AI and the state of the universe and a bunch of other things. But Dee, you’re a published author and a consultant, running around doing cool workshops. Tell us a little bit about what you do and how and where.

DL: The where part will probably be the most difficult because it’s literally all across the country, and sometimes internationally. But I am oftentimes brought in to do human-centered design, also known as design thinking work, helping organizations tackle challenges that they are experiencing, and then come up with some form of contract or goals. And then coaching them longer term in executing on their stated goals, and really being one who can infuse some form of instruction and help and supports in some cases. But also just being responsive to the roadblocks that they’re experiencing, some of their communication challenges, things of that nature, and helping them see their goals through. And then celebrating what they have accomplished as well as setting up some of their longer term goals that need to be evaluated over the course of three to five years.

SO: And so, this really sounds a lot like what we do here at Scriptorium, except where you’re talking about design thinking and human-centered kind of approaches, I’m deeply afraid that we are more about the systems and the tools and the software and the, I guess, automation centered approaches. But how do you define, for this audience that sits more on the techie software side of the world, how do you define design thinking for them, for us?

DL: Sure. Well, I feel like I have to always start off with helping people understand what I don’t mean by design thinking. And that is if your brain lights up, and I’m sure some listeners say, “Oh, I know exactly what design thinking is,” and what immediately comes to mind is a model or a process. That is what first comes to mind. And I would venture to say it’s either coming from IDEO’s Model established in 1978, or it’s Stanford D School’s model established 2002 or five, something of that nature. So by and large, what they’re thinking of is a model and they’re thinking of a fairly recent phenomenon. And I like to say first and foremost, design thinking is exactly what it sounds like. It is thinking like a designer.

So if you’ve ever been in contact with any form of designer, someone who does graphic design, industrial design, interior design, you start to notice that these people think differently. And I would say it’s not just different in they just think in a manner that is different than other people. But they literally, they slow down and they ask questions and they seek to understand. And that really is the goal, is the seeking to understand before proposing any solutions.

So with that, I say, “Well, design thinking is not a model first. It is a mindset. And that mindset incorporates a strong inquisitiveness about what’s happening here. Who are the people that are being affected by whatever said problems that are happening here? And what don’t I know that I need to learn before proposing any solutions?” So, that is design thinking in a larger sort of understanding. And then if you’re curious about models, I could share a couple, because you can Google search at least 10. Which again becomes something that sometimes blows some people’s minds when they’ve been introduced to design thinking through a particular model.

SO: Well, we’ll take your top three or four and stick them in the show notes. And I wanted to touch… I mean, it’s interesting, right? Because we go in and we will look at things, and a lot of times we’ll say, “That’s not actually the problem. That’s the symptom.” Right? You see these issues, but you have to figure out what’s the root cause. And so I think really at the end of the day, there’s a lot of overlap there.

And I know that one of your focuses in addition to this design thinking lens and this really understanding the stakeholders and the organization and how they need to change to address the issue that you’re dealing with, is that you have a strong focus on design equity or equity in design. And I wanted to touch on that. I mean, I think most of us are familiar with the really obvious problems like you ask a search engine for images of a CEO and you get a collection of white men with good hair. But your practice goes way beyond this. And so what I wanted to ask you was, how do you look at equity and design? And what are some of the issues that leak into that work in ways that are not as obvious as my really dumb CEO example?

DL: That’s not a dumb example, that’s an excellent example. Or even just doing a Google image search on good hair or professional hairstyles versus unprofessional hairstyles, and then we’ll see what you discover. But that is part of it, even doing that, starting with an investigative practice or a prompt to get the conversation going. But equity and design or elevating, as I like to say, elevating equity in the problem solving process is twofold. The first being making sure that you’re actually gathering the people that are most proximate to whatever pain that is being experienced as part of the process. And so it is not just an expert or consultant who’s coming in, who’s taking inventory of whatever’s happening. And then going off to the side and developing whatever their solutions are. And then coming back to the team and say, “This is what I got. This is what you hired me as a professional or as an expert to do.”

I think that there’s a need for that in certain instances, but when you think about problems or challenges that affect a community, it requires that the community is engaged in identifying what is the root problem, what is the core of the problem. And being a part of the process for describing not just what the problem is, but also gathering the research so that they can see for themselves that they can also share the antidotes of their experience and their exposure to whatever the challenge is. And then them also ideating and being a part of, “Well, we could do this, we could do this, we could do this, we could do this.” And bringing in their thoughts, their brilliance, but really it’s because they’re bringing their pain to the table, and they want to be a part of the solutions.

Because then lastly, whenever their solution is then proposed, and then there are goals set and there’s some action planning and some execution of those things. And if they’re a part of that process all the way through, then that sort of eliminates the blame game of, “Well, this outsider told us we should do this. We never understood or agreed with that. We attempted it didn’t work. And I could have told you from the very beginning, it never would’ve worked.” It kind of separates that us versus them mentality, and instead invites everyone who’s really deeply vested in seeing that problem overcome as a part of the solution. So, that is long-winded answer to part one of, that is what it means to elevate equity and problem solving.

Secondarily, it is literally taking on particular topics that are related to equity in whatever the setting. And so whether that be anti-bias work, which is what I’m oftentimes brought in to do. Or sometimes it is, and giving a distinction between, what are the differences between individual and collective bias versus different forms of discrimination? Anti-racism work. And then also there’s an opportunity, and I see this last category primarily in schools, and that being civic engagement. And so it’s identifying a problem, understanding what the big problem is, and then spending the time with the collective group to problem solve.

But part of the work that I do in the pre-work is really listening well to leadership. And then having them help me identify who are other people I should be talking to learn what is the core issue. So then we just propose, “Okay, this is where we’re going to go with this next.” And it may be starting with bias or it may be going into anti-discrimination. Or it may go into, “Okay, it seems like this is an issue that is particularly related to racism and we need to do some, not just anti-racism training in the sense of me giving you a bunch of terminology. And building up your lexicon and helping you have a better understanding of what these things are. But really being a part of problem solving, identifying the particular challenges that are being experienced typically by people of color within your organization. And then how can we rectify those issues?”

SO: It’s interesting because in many cases, I think the projects that we come into, nine times out of 10, the people on the ground, the line employees that are in the trenches doing the work have a really, really good understanding of what the problem is and how to solve it. They know. I mean, they know what’s wrong and they know how to fix it, and they’ve already figured it out. But because as somebody or others said, infamously, “You get more credibility when you commute on an airplane.” So because we’re outsiders coming in, we get additional credibility, even though we’re potentially saying the same things that your staff, your long-term employees are saying.

And I’ve had, I mean many conversations where I would say to somebody, “Okay, you’re absolutely right about the problem here, and this is exactly the solution. You’re absolutely right about the solution, and this is what we’re going to propose. Now, would you like us to give you credit for it?” And 100%, I’ve never had anybody say anything other than, “No, you have to take credit for this because if I propose it will not get done.”

DL: Very, very interesting.

SO: It is an uncomfortable place to be. Right? But basically what they’re saying is, “Look, Sarah, we are going to leverage your credibility as an outsider to get the thing that we all agree we need.”

DL: Makes sense. Makes sense.

SO: Okay.

DL: Right. Makes sense.

SO: I mean, I can accommodate that, assuming… I mean in the scenario where we all agree that that is the right answer. But it is very upsetting to have person after person after person say, “I know the answer, I just can’t get them to listen to me.”

DL: You’re right. Well, and we may differ in approaches as well as how we differ in particular work that we do, in me more doing design thinking, you doing systems design. But what I like to do is help equip the community with the skills and the actual data that they need to move forward. Which is to say, “If you’re going to argue with this, know that you’re arguing against what the data says. And we are looking at the data.”

So if we can, attempting to be careful with my words, not to be taken in a different sense, but if we can objectify the scenario a bit… Which sidebar, when I do anti-racism work, part of the reason why I work more as a facilitator and guide the process is because it’s also extremely harmful for me to experience microaggressions, even in someone’s question. If I am being looked at as the expert who has the knowledge base, who has to respond to you, when you raise your hand and you have a critical question that also comes across like a confrontation. That can be incredibly challenging.

So instead, if it can be set up where there are small groups and small groups are where in collaboration with one another, they’re also utilizing the same level setting of background knowledge that was not only given, but really facilitated. Because what I do is I try and propose questions and give the tools for people to discover on their own. And then we come to agreements, “Is this what we all saw? Is this what we all heard? Is this what we all understand? Any objections to that?” So I’m objectifying the scenario a little bit to say, “If you are having an argument still, it’s not with me.”

Because that can, for me as a facilitator, as a person of color, trying to lead a workshop that is oftentimes for the sake of helping the people of color within that community to not feel abused, I don’t want to experience the same abuse that they’ve been experiencing. I know why I am there. It’s typically due to a scenario, something that happened. And so, let’s have a conversation about what happened, and then let’s have some conversation about what else is happening. And then, what is your community most interested in tackling primarily? And then let’s discover how to do that. If I can stand more on the side and help lead in that regard, then I also protect myself. And that is honest and real.

SO: Yes. And thank you for doing this work because the whole thing just makes me twitch. Just listening to this, it sounds painful.

DL: Yes. Yes, it can be very painful, ’cause I’ve been saying it. Part of what I do is anti-racism work, part of what I do is anti-racism work. Well, I’ve had to learn a lot even in doing that. Now, my background is totally in this field. My undergrad and graduate work is primarily focused on race relations from a sociological perspective. But knowing about something does not make it easier in a situation where you find yourself being tokenized in the moment, experiencing a microaggression in the moment, noticing someone centering on themselves and their experience. And then confronting you to have to try and counter what they are saying because they see you as the enemy in this setup.

All of that is hard, so I’ve had to learn some things. Had to learn some things such as being mindful in the moment. I will give a shout-out to Rhonda V. Magee and her book, I want to quote it or name the title properly. It’s, The Inner Work of Racial Justice, which is to take a deep breath and pause when experiencing something offensive in the moment. How do we stay professional when we notice that something that is being said or done causes harm, whether it’s to me directly or to others around? And how do we address that situation? So, doing the inner work.

Secondly, making a huge point to level set, to say, “What we’re going to do is attempt to make sure that everyone has the same baseline understanding.” So therefore, if I am brought in to do anti-racism work, I first have a large conversation about the concept of race. Because we’re not going to talk about an ism if we don’t understand the structure in which it’s being built upon.

And I ask three questions and give time and space and also some resources, so that a group can investigate on their own and say, “When was race created? Why was race created and how was race created?” So again, once those things are being investigated and discovered, they’re not doing battle with me, they’re doing battle with research, they’re doing battle with history. They’re doing battle with what is real and not what’s imagined. There are people in that room who could say, “I can tell you this right now,” but there are others in the room that need to discover that for the first time. So, that is part of what I do.

And then the next thing I do is ensure that we don’t move on with doing design thinking through these particular challenges, until we have set some expectations and some commitments from the people that are in that space individually. Because we’re going to work corporately, but we are going to need to individually agree on some things. And so, those things become things that I can always call back on and say, “Remember you said that you would commit to the following.” And so if there’s any need to address any issues, it’s based on their commitments, not the thing that I’ve imposed upon them.

And then of course, I’ve already brought up bringing in definitions of terms so that people aren’t just going off of their understanding of a concept. But at least we’re all utilizing the same definitions, as we talk and discuss them. But then what everyone is able to bring to the table is their experience with those particular concepts.

Those are things I attempt to do to create safety, in a sense, for the participants as well as for myself. But safety cannot be demanded or controlled in a sense of saying to the group, “This is a safe space.” Who says it’s a safe space? Safe for who? And how do we know? But we can do certain things to attempt to create safety. And then we can always stop and pause and call back to, are we actually doing what we committed to do or are we doing something different now?

SO: And so, some of the conversations that we had when we first met were actually revolving around some of these concepts you’re talking about, in terms of safety and bias. But what actually led us off was AI, right? We started in on this question of, “Oh, well, what does it look like to start to bring AI into some of these settings?” Whether it’s to support design work or it’s to support corporate training, K through 12 education, or anything else. The AI is out there, the tools are happening. What do you see? I mean, what’s your sort of capsule view of what’s going to happen, as we go forward with these tools in a variety of settings?

DL: Part of our conversation was acknowledging that AI and the various tools that exist, they’re not going away. We know that that is the case. I wanted it to kind of feel like, “Oh, let’s see if this is a trend that will fizzle away, like Wordle and Bitcoin.”

SO: Wait, one of those has actual value, and it’s not Bitcoin.

DL: I see what you did there. Exactly. But there are billions of dollars being invested in by big corporations. So part of what I do is try and say, “Well, let’s effectively utilize AI or let’s attempt to effectively utilize AI in a research process.” And so that is skill development, much of what it requires to not only participate in design thinking, but then to slow down, stop after what would oftentimes be like a rapid prototype. We quickly, within a very condensed timeframe, came up with what our proposed solutions to whatever said problem is based on this very limited amount of time.

But now that we have more time, extended time, we need to fill in the gaps with what is missing. Some of those may be interviews, and some empathy mapping. But it also requires deeper research. And part of that research requires understanding the tools that exist and how to use them effectively, and being mindful of things such as the bias that exists within them. And so, that becomes a whole workshop in and of itself.

We are going to deep dive into AI because people come to the table. Similarly, as we were talking about race and racism, people come to the table with varying degrees of understanding. And what ends up happening is some people presume that others know exactly what they’re talking about when they say whatever they say. Or there are others that have very, very strong opinions on certain things that it’s clear in certain cases, that they actually haven’t done much research, nor have they actually participated in or evaluated something critically from using. But they’re just like, they heard on NPR, they watched on CNN, they listened on Fox News, and now they have opinions. And I always say opinions matter, but they’re not more important than research.

And so, having people actually deep dive into research, and that includes just starting off with, I got three companies to name to you, Google, Microsoft, and Amazon. What all do they have in common? They are big data corporations. So, let’s start there. And if I say, “One is invested $10 billion here, another has invested $4 billion there, another has invested $2 billion externally here. And who knows how many dollars they’ve invested, invested internally for the development of their tools. And they own the space of data. It’s not going away. What kind of data do they have? How is that data being utilized? How can you be mindful of those things? And then how can you utilize these tools effectively, while also being mindful of the ways in which, if you’re not careful… You are the contributor to the data, and so you can be bringing your bias to the table as well.”

And so yeah, it’s a big, big, big, big discussion that’s still results similar to how all I think design thinking activities should result. And that is concluding with some commitments. And so whether it is revolving around the particular challenge that people are experiencing or with AI and the challenges that it presents, I always bring up a fourfold framework for goal setting. And that is what is it that we are trying to prevent, correct, improve, and excel in? And if we can set our feet on those four foundational pillars, then they become our guide as we continue to move forward. And AI is now just another part of that.

SO: So Dee, thank you. We could probably keep talking for a couple of hours, and I would appreciate that, and I suspect our audience would as well. But if people want to reach out, what’s the best way to find you? And we’ll, of course, also embed information in the show notes.

DL: Sure, sure. Thank you. Well, my website is Lanier Learning, my name, L-A-N-I-E-R, lanierlearning.com. Can also be emailed at dee@lanierlearning.com. I’m still on the Twitter or X or whatever that thing is called @DeeLanier. You can also find me at LinkedIn @DeeLanier. So my name is easy to find, and I would love to hear from some folks.

SO: So, Dee has a book out there in the world called Demarginalizing Design, which I would strongly recommend. And we didn’t have time to get into this, but some really interesting workshop techniques around how to get people engaged doing different kinds of things. Not just talk in a small group, but do some more creative things, which I believe is called, Solve in Time.

DL: That’s correct.

SO: So, that’s out on your website. We will get all of that into the show notes. And I hope that we’ll have an opportunity to have some further conversations about where this mess is going.

DL: We’re all learning, right? Absolutely. Well, hopefully we will have more opportunities such as this. Maybe we’ll even find ourselves on another plane together, having a conversation.

SO: Seems likely. So Dee, thank you so much for being here. And with that, thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Design thinking & equity in design with guest Dee Lanier (podcast) appeared first on Scriptorium.

“Here’s the thing. Skepticism is healthy. If people are trying to poke holes in this new process, sometimes they can actually uncover things that are not being addressed. That is real, that is useful. So don’t confuse that with people who were being a-holes and just being contrary for the sake of being contrary. Those are two different things, and you’ve got to be sure you understand those two things.”

— Alan Pringle

Related links:

• Ask Alan Anything: Resolving pain in content operations (podcast, part 1)
• Content strategy pitfalls podcast: change management
• “Why do I have to work differently?” (podcast, part 1)
• Training by Scriptorium

LinkedIn:

• Alan Pringle
• Christine Cuellar

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Christine Cuellar: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. This is part two of a two-part podcast.

I’m Christine Cuellar. And in this episode, Alan and I are continuing our discussion about pain points, pain points that Scriptorium has resolved over the years. And we have a lot more to talk about. So Alan, let’s get right into it if you’re ready. Are you ready for round two?

Alan Pringle: Well, I took the first bit okay, I think. So let’s go ahead and knock it out.

CC: All right, let’s do this. Okay, so let’s talk about some more interpersonal pain points. So let’s talk about office politics. How does office politics impact content operations problems that might already exist?

AP: Oh, office politics affects every operation. Not just content, every operation at every level. And you have to be savvy and know how to play the game. If you have had experience with that at the company where you are, or at another company, it can be a very valuable thing to understand that how to read people, how some things are left kind of unsaid, inferring things.

Understanding that when you have a C-level executive who has a priority on, they want content to be like X, that all of a sudden probably becomes a priority for you, even though it may not have been one in your mind. Because the person who has the money sees it as the priority.

So there are lots of things that you have to bridge and address, and it can be a minefield, absolutely. But if you’ve had experience with it before, or again, if you’ve worked with a consultant who has seen these things before and we have seen politics at Scriptorium, lots, it’s inevitable because humans are political beings. It’s just how it is.

CC: Yeah. What are some common office politics or sticking points for content operations? Is there anything unique to content struggles?

AP: This goes back to a little bit about what we talked about in the previous episode, in regard to finding the common communication method, a common language of speaking. Be sure you’re not talking at each other, that you’re talking with each other when you were talking about these things.

And again, this is not just about content. But what is about content is, content does often not quite get the attention that it should. So you may have to spend a little more time explaining its value as we discussed earlier. And that can be a sticking point here.

CC: Yeah. And if you didn’t have a chance to check out the earlier podcast, it is in the show notes, and I do recommend it. Because Alan also shared some specific metrics that you can have on hand to help communicate the value that content brings to your organization. So definitely recommend checking that out.

How about a pain point where people, whether that’s the technical writers or other people involved in this whole process, don’t really want to be helped? They’re kind of happy with what they’re doing. Maybe the reversal is true, they don’t see the need for the change, and maybe managers or executives are the ones pushing that change. How do you navigate that?

AP: Well, you have to find advocates at every level. Even though you’re saying some people may not see the value or are not feeling the pain, I bet there are other people who are sitting back looking at this. Content creators are saying, “This is crap. We need to fix this.”

If they can get other people on board, that’s how you do it. It’s more of a lateral thing. You’ve got coworkers explaining to you, this is why we need to do this. That is much more effective than from top down, you will do this. Although sometimes you may have to play the, you will do this, card. And if those things aren’t done, it may be time for some personnel changes perhaps.

Yeah, that’s not pleasant, but it can get there sometimes.

CC: Yeah, no, that makes sense. Do you feel like once they see the value of what’s trying to be done, or once they see a coworker that’s really motivated by this and sees the benefits, even if this one individual doesn’t, do you mostly see people being won over to the cause, quote-unquote the cause?

AP: Not always, but here’s the thing. Skepticism is healthy. Because if people are trying to poke holes in this new process, sometimes they can actually uncover things that are not being addressed. That is real, that is useful. So don’t confuse that with people who were being a-holes, and who were just being contrary for the sake of being contrary. So those are two different things, and you got to be sure you understand those two things.

But I can tell you I have seen, even on two projects within this past year, where I sense skepticism from certain people and I saw them change over weeks and months. It happens. It absolutely happens. And that’s when you know you’re headed towards success. Because people who were like, “I don’t think so,” are like, “Okay, I see this.”

People who now champion what you’re doing, that’s really rewarding and it will really guide you to success.

CC: And I’m sure that that really helps them, that they were able to question and bring honest questions, and feedback, and concerns about, I don’t know how this is going to work, that kind of stuff. They were able to bring that to the table and have that addressed to the point where they’re now fans. Like you said, they’re champions of … That sounds like a safe environment for them as well. Hopefully that resolves their concerns.

AP: That’s what you want. I mean, that is ideal. And it does happen. Absolutely, it does happen.

CC: Yeah. All right, so how about a pain point where you realize that your team wants to or needs to move to structure, but your team isn’t technical. Do you have any thoughts or examples about how that is navigated? Because that sounds painful.

AP: It is. And it doesn’t happen overnight. Again, we are talking about a situation where you need to win people over, help them understand the bigger picture. And this is where, for example, a proof of concept can speak volumes. Where you take a slice of content and use it, set it up in the new process or quasi-new process, close enough where you can demonstrate the change. Where you can demonstrate the value. That’s one tool that can be very effective in communicating things and bringing people on board.

Also, you got to remember, you cannot throw a completely different way of doing things on anybody, in any circumstance, at any job, not just content creators and say, “Here’s some new tools. Go do it this way.” No, you’ve got to have some knowledge transfer. You’ve got to have training that’s tailored to all the different levels, all the different users of the system and how they’re going to use it. So all of that is vital.

And again, I’ve repeated this probably ’til I’m blue in the face in past events and podcasts. When you are budgeting for a project, never, ever, ever leave out training, always have budget for training, or you’re going to end up with a system that nobody can use. What’s the point?

CC: Absolutely. And like you mentioned earlier, if the worst-case scenario happens and there is some turnover, I mean, we try to avoid that at all costs and try to win people over. But if that…

AP: That can be healthy. I will argue sometimes turnover can be healthy. If someone realizes that they are not going to be a good fit for this new process, maybe it is a good time to bring someone in who can.

Yes, the loss of that institutional knowledge, the product knowledge, the service knowledge, the process knowledge, I am going to fully acknowledge that is a big loss. It is painful. But big-picture wise, sometimes changes like that are exactly what you need to get things moving.

CC: Yeah, yeah, that makes sense. And if you have training, if you’ve budgeted for training like you mentioned earlier, it sounds like that could be something that not only helps navigate the transition, but it can also help new team members that come maybe six months, a year, or even more so after the changes already happened. It’s an asset that, it’s good to have in place from here on out.

AP: Yeah, I’m glad you mentioned that. Because there are multiple ways to navigate what you just mentioned. You can set up a “train the trainer” scenario, where a consultant or an expert comes in and basically gives people within the organization the knowledge they need to then spread the good news to other people. And people who were maybe hired even six, eight months, a year down the road. So you have got those resources internally.

You can also record training and use that as a resource as well. So there are ways to address that. But it is important. You’re right. It’s not just about the transition, it’s about helping people when they’re introduced to the process as new hires.

CC: Yeah. So shifting to some technical pain point questions, tell us about some scenarios or maybe some ideas you have when technical obstacles come up that weren’t discussed in the discovery stage. So this is probably particularly when a consultant is brought in. But during that initial assessment, there was a lot more hiding under the surface than was realized. How do you navigate that?

AP: I would hope there are not a lot of that going on, because that means discovery probably wasn’t as deep as it should have been. It does happen. But I’m going to hope and cross my fingers that we’re talking about some things around the edges, edge cases, things like that.

When you have edge cases, you have to say, okay, do we need to spend time and money for the system to address it, or is this edge case a one-off, and things need to be reconfigured with this edge case, so it’s not an edge case? That’s one way of looking at it.

But if you find enormous gaps where you have completely glossed over something, there’s part of me that feels like discovery went a little awry. That’s where my brain is right now. And that’s like, did the consultant, did we do our jobs here? What happened here? I would take a hard look at that and there would need to be some soul-searching there for sure.

CC: So that’s a good point. That for the most part, the way that a consultant guides that initial assessment should flesh out the major problems. That’s what I’m hearing.

AP: I really hope, I really hope. Because a lot of times, if you’ve done this as long as we have, that sounds boastful, but it’s just a matter of fact.

CC: 1997, so yeah.

AP: Yeah.

CC: It’s been a long time.

AP: Yeah. Your antenna goes up and you’re like, I hear that, but I know that also means X, Y, and Z. So that’s where a consultant can be helpful. Because they can pick up on things that, on the surface, may not mean anything to someone who is mired in the pain. But it really means something to someone who’s seen this stuff before and can pinpoint, oh, if I’m hearing that, that means these things are also probably true. Let’s go digging around on those things.

CC: Okay. Okay. So how about a situation where you need a specific output, but the current authoring and publishing systems don’t support it? And there’s really no way around that.

AP: This is a signal that is not just about that output. It probably means your ops are not where they should be. Because good content operations, they are going to allow you, enable you to deliver to a yet-to-be-specified delivery format. That is the crux, the joy of good content ops. They are going to be basically future-proof.

If you’ve got things set up in a way where your content source is, let’s call it format neutral, and then you apply different transformation processes to it to create all the end results, delivery formats you need, one more delivery format shouldn’t be a huge burden if things are set up well.

Now, you may have to add another layer of intelligence, some new information into your source content to deliver that. But beyond that, you should be more or less ready for the unknown. That’s where my brain is anyways. I mean, to me, good content ops are not just about the here and now. It’s also about what’s coming down the road in 18 months.

CC: And speaking of that, what happens when your content processes, you just outgrow them? Okay, two questions in there. One, that’s a pain point that was brought up a lot is, what happens when you outgrow your processes? So there’s that. But then also, number two, can you create a solution where you don’t outgrow your processes? Is that even possible?

AP: In theory, I think baseline, you can create something that is somewhat future-proof. I do believe that, and I’ve seen that happen. Especially if your content is structured, and it’s got a lot of intelligence, I’m going to use the M word, metadata, built into it. So you can slice, dice, and present that content in many, many different ways to many different audiences, versions, levels, whatever it is that you need at the end.

And then it also gets into content as a service, where other systems can pull in that content and use that intelligence to create what the end user, the reader, or whoever, what they need. And gives them exactly what they need, and often in real-time.

So yes, theoretically, you can do that. But like I said around the edges, you may have to add a little bit more intelligence here or there to your source to be sure that you can address that new delivery format. So yeah, you can do it. But nothing on this planet is foolproof, as much as I would like it to be.

But having structured, intelligent content that is filled with metadata, if you have that as a core, you can take that a really, really long way. A really long way.

CC: So Alan, are there any other pain points that we haven’t covered in our list that I’ve grilled you on? Is there any other kind of pain point that you’d want us to address right now?

AP: The only thing that I want to say to kind of close this up is that change is a people problem. Don’t consider it a tech problem. That’s kind of my overarching advice, based on all these questions that I’ve heard at this point. And looking at it simply through the lens of tools and technology, I think you’re basically guaranteeing you’re going to have your backside handed to yourself. That’s what I think.

CC: Yeah, that’s a really good way to phrase that. I like how you phrase that. Because that also applies to other aspects of the organization, not just content. But it has a big impact here.

AP: Basically, basic change management applies here. Good project leadership applies here. Yes, a hundred percent.

CC: Absolutely. Well, Alen, thank you so much for letting us grill you on this. Especially because you didn’t have the list in advance. You didn’t know what we were going to bring up today, so thank you for being here.

AP: Sure. It was interesting.

CC: Sure. It brought up a lot of really happy memories of resolving all these things very easily.

AP: And some unhappy memories as well. Yes, it did.

CC: All of the above. Yeah.

AP: Yeah.

CC: Well, yeah. Thank you so much. And thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Ask Alan Anything: Resolving pain in content operations (podcast, part 2) appeared first on Scriptorium.

“The amount of time content creators spend on formatting and for little payoff, it’s just… the numbers don’t add up. Especially in the 21st century now that we have so many automated ways to publish things to multiple channels, if you are futzing and tinkering with formatting trying to deliver to multiple channels, I can say with a great degree of certainty, you are absolutely doing it wrong.”

— Alan Pringle

Related links:

• Personalization in marcom and techcomm
• Is Content as a Service right for you?
• Content experts will soar when you remove these burdens
• “Why do I have to work differently?” (podcast, part 2)

LinkedIn:

• Alan Pringle
• Christine Cuellar

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Christine Cuellar: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re sharing stories about pain, specifically pain points that Scriptorium has resolved over the years. This is part one of a two-part podcast. I’m Christine Cuellar, and with me, I have Alan Pringle. Alan, thanks so much for being here.

Alan Pringle: I think you’re welcome, but I may regret it based on the format of this particular podcast.

Christine Cuellar: Yes, you may. So Alan has no idea about what we’re going to talk about today other than we’re talking about pain points. He has not seen the notes. I’ve instead collected data from our team about lots of pain points that Alan and the team have resolved over the years. So there’s going to be a lot of pain in here, Alan, but hopefully there’s going to be a lot of resolution as well. There’s hope.

Alan Pringle: We can only hope so, and I thought of a little subtitle for this. We can call it AAA, Ask Alan Anything, with very deep apologies to Reddit AMA, and to the American Automobile Association. So yes, this is-

Christine Cuellar: I love it.

Alan Pringle: … the AAA talk, and I’m frightened.

Christine Cuellar: Let’s do it. I’m so excited. I’ve been looking forward to today. Not looking forward to your pain, Alan, just these pain points. Anyway, it’s going to be great. It’s going to be so great. Okay.

Alan Pringle: We’ll see about that. Yeah.

Christine Cuellar: So generally we have some main reasons for why people come. They come because they’ve experienced a lot of mergers or acquisitions, and they’re trying to consolidate different ways of approaching content operations, or they have a lot of localization requirements. There’s a lot of big-picture challenges for why people come to us.

But yeah, we’re going to go ahead and pick Alan’s brain on some specifics. So let’s kick it off with this one, Alan. Can you tell us about a time or about some pain that was involved when you and the team moved a customer or a client from disconnected document systems to a unified system? Tell us how that went.

Alan Pringle: The thing is, this could be many, many people. Here’s the thing. I think you always need to rewind before you talk about the systems because you need to lay the groundwork before that, and that goes back to the pain points you were talking about. Okay. You ask the client, “What pains are you having?” And then, from there, you go, “Why are you having those pains? What can we do to stop those pain points, make things better,” and then you pick your system?

So that’s not a super fun answer, but there’s always this temptation to dive directly into tools, and I’ve said this a zillion times in presentations here, panels, and wherever else, don’t do it. Think about your requirements first. And pain points are a great way to dig out and tease out those requirements. But get those in place first, and then pick the tools that are going to help you address them the best.

Christine Cuellar: Yeah, absolutely. Yeah, start with what you need before trying to make a tool decision. That totally makes sense.

Alan Pringle: Yeah.

Christine Cuellar: How about this pain point? Dealing with manual formatting when authors have to manually format things all the time. Has that ever come up before?

Alan Pringle: All the time. The amount of time content creators spend on formatting and for little payoff, it’s just… the numbers don’t add up. And especially in the 21st century now that we have so many automated ways to publish things to multiple channels if you are futzing and formatting and tinkering with formatting, trying to deliver to multiple channels, I can say with a great degree of certainty, you are absolutely doing it wrong.

Why are you inflicting that upon yourself? Stop it. So yeah, don’t do that. Please don’t do that because it’s not a good use of your time, mostly because your reason for creating this content is to educate, help the people who are reading it. You need to spend the time on that, not on the formatting. It’s just not a good use of your time. It’s just not.

Christine Cuellar: Yeah. Do you have any examples of a company that was held back by the time that their team was spending on manual formatting? So maybe they were trying to translate into new languages or rebrand. Any examples of-

Alan Pringle: Oh, yeah.

Christine Cuellar: … how that went wrong?

Alan Pringle: I mean, again, it’s not so much that it goes wrong. It is that what they are doing is just not sustainable, and it is costing them so much more money. I mean, you think about it, if you have your source content, and because my primary language is English, really my only language is English. I’m going to say your source content is English. So all the time that you’ve spent formatting and getting that ready, you have to apply that to every single language. That effort becomes exponential. It’s multiplied again and again and again.

Please, why are you doing this to yourself? Don’t do that. You need to have a system where your formatting and your source language is as automated as it can be, and then that automation will then apply to the localized content as well. It really is just kind of stupefying to me to see people continue to spend so much time on formatting on source content, much less when they have to localize for, you know, how many different locations.

It is just, again, the money and the time, and then there’s the delay because, say, you ship out to your primary language. Again, I’m going to say English. It’s not always that way, but that’s just because I speak English. And then three or four or six months later, you’re shipping out the other languages. Why? You need to get that window down to almost simultaneous shipment so you won’t have this huge delay because if you have that huge delay, that is an income stream that your company is not getting from those markets that need the translated content. There you go.

Christine Cuellar: Yeah. Yeah. So in a nutshell, for organizations that have had this as their primary pain point, you know, the writing team is spending way too much time, manually, formatting things, and they don’t actually get to do their job, which is write the content. What’s the big-picture fix to that? I know it’s probably different for each person and each organization, but what is… where’s square one?

Alan Pringle: There’s lots of square ones here, so I got to be careful. There’s not a one-

Christine Cuellar: Yes.

Alan Pringle: … size fits all. If you are working in more traditional content development ways, when I mean by that desktop publishing, templatize. Your formatting should be coming from a template, creating a repeatable process, and that template can be applied to your localized content as well.

If you have outgrown desktop publishing, and that does happen, you need to look at structured content, and that means there is no formatting in your source content. It is applied automatically later on. When you do that, it basically takes it out of the author’s hands completely, and automated transformation processes apply it. So those are two go-to’s right there on how to possibly address that problem.

Christine Cuellar: Gotcha. How about this pain point? An organization is being asked to personalize content, or they’re being required to personalize content, but they have to rely on manual work to make that happen.

Alan Pringle: No. Just like I was talking about formatting, it causes me pain to hear about people who are basically copying and pasting content over and over and over again to make slight variations of content for different audiences. It happens all the time. Again, please don’t do that to yourself if you can help it. This can be basically the thing to help push you into improving your content operations.

It’s, again, a question of efficiency, a question of reuse. There may be a core of content that pretty much stays nearly the same or static. It’s just there’s bells and whistles on the edges that need to change based on location, on audience, or whatever else. What you’re going to have to do is build on that intelligence. So you have got some content that’s being reused, and then you have flagged the stuff that is specific to a particular audience or whatever else. When you start getting into building in that kind of intelligence, you’re talking about structured content, usually XML, not always XML, but usually XML.

So you can build in that intelligence that says, “Okay, this is my common core of content. Then here are things that are a little bit different for all of these different things.” And you can have this huge matrix of things that are different, audience location, product version level, whatever else. And then, based on those things, you can put in that intelligence and then turn off… turn certain content on and off when you create whatever delivery points that you have, whether it’s print online or whatever else these days. Lots of choices there too.

Christine Cuellar: Yeah, that’s great. Is that something… Okay, just because this is kind of top of mind because we’ve been talking about this a lot recently. Is that something… If people are interested in pursuing that, should they look more at content as a service? Where would you recommend they dig for more information on creating that kind of a system?

Alan Pringle: Again, I would say go backwards and think about your requirements, what those things are. Personalization as a requirement. Yes, content as a service, and let’s explain what that is. When you have built intelligence into your content about audience, product variant, whatever else, version, you can connect systems together in a way where the system that is going to present the information to the end users, to the content consumers can pull the information that it needs from the repository where you have stored your content with that intelligence built in. Yes, content as a service is great.

It sounds great, but you don’t start there. People don’t just say, “I need content as a service.” They may, but I don’t think it’s something that comes to top of mind immediately. What they’re thinking is, “I need a way to personalize this content for my different users so they get exactly what matches the version of the product that they’re using, for example.” Or, “I need the people who were taking this course and this learning management system to get things zeroed in on the way that they have their software configured and they’re trying to learn about it.”

Christine Cuellar: Yeah.

Alan Pringle: To me, there, there’s a distinction there. Yes, content as a service is a way to solve those problems, but I don’t think people generally go there top of mind. “That is what I need.” They think more about, “I need personalization.” Content as a service is a way to get it. That’s how I would like to frame it anyways.

Christine Cuellar: Yeah. No, that totally makes sense. They need that personalization, but they need to not be relying on some person or a group of people going in and manually making all those changes because that’s just not… that’s not feasible to keep up with.

Alan Pringle: Oh, people do it all the time, and then they end up all having breakdowns because it’s just not sustainable. Yeah.

Christine Cuellar: Oh, yeah. Oh, yeah.

Alan Pringle: It’s awful.

Christine Cuellar: Especially as you grow. And yeah, I can see that’s a major scalability issue in so many different ways.

Alan Pringle: Yeah, yeah.

Christine Cuellar: So do you have any examples of that inaction about companies that need to personalize content that have been set up for success now? Even if it’s an unnamed example or stories you can share there?

Alan Pringle: Yes, and I’ve got to be careful here because I don’t want to get too much into it-

Christine Cuellar: Yeah.

Alan Pringle: … to identify customer. But yes, we have done things where the end user is getting information, whether it be from a web-based portal, for example, that matches exactly their customer profile. So yes, we have done this, and I know you probably want more details than that, but-

Christine Cuellar: No, that’s fine.

Alan Pringle: … I don’t want to go too deep into it, but yes.

Christine Cuellar: Yeah.

Alan Pringle: We have done it. We are doing it as we speak. As we record this, we are working on projects trying to do that very thing. So that’s very much in our wheelhouse, indeed.

Christine Cuellar: Okay. No, yeah, absolutely. That’s great. That’s a great example. Okay, so let’s switch gears to another pain point. What has it been like for… or what do you recommend for people who are struggling with the pain point of inconsistent content? Either inconsistent content or maybe inconsistent ways of creating the content.

Alan Pringle: Well, inconsistency can be many levels here. It can be the tools that you are using. Not everybody’s using the same thing, maybe because of a merger. It can be the way that the content is organized. It’s not the same from one product to another or one service to another. It could also be as getting more down at the content itself. The way that people describe things. You are not consistent in what you call this widget in this document versus how you describe that widget in what it does in this online document over here. So there are multiple layers of inconsistency here, and it can even be as using certain terms and terminology.

You’re not consistent in how you do that. And again, there are technologies that can help with all of those things. For look and feel, templatization can help make things more consistent, or you can move to structured content and have your formatting applied automatically to take care of that consistency. There are ways to basically enforce word choice, control vocabulary tools to be sure that you’re using the terminology in your company consistently or different authors and content creators and content contributors are using a term consistently.

Alan Pringle: So again, there are lots of layers here, but there’s a way to solve all of them that basically you can use tech to take that burden off of you, so you’re not having to always think about those things all the time. Having tech provide you a helping hand. And I dare say there’s a point we’re reaching now where even artificial intelligence, AI tools, can help with some of these things too.

Christine Cuellar: Yeah.

Alan Pringle: So as much as I get so tired of hearing about AI and all the irresponsible talk about it, you can also look at and frame AI as a tool to help you make things more consistent. It can help. For example, maybe look across a vast body of content and find where there are things that are not consistent, so you, as a human, don’t have to go and do all that horrible, crappy work.

Christine Cuellar: Yeah, yeah. And going back to something you said earlier about this. You mentioned, okay, so using a merger as an example, people using all these, trying to consolidate these different systems or trying to just work in these different systems after mergers.

Is it common for people to be, for lack of a better word, putting up with dealing with a bunch of different systems until the pain is just absolutely unbearable and they have to reach out, like putting up with this for years or something like that? Is that pretty common, or do you feel like this is a pain point that is painful enough that people reach out pretty quickly when it crops up?

Alan Pringle: I hate to keep saying it’s not one size fits all, but it’s not. Some people recognize the problem earlier than others. Some people just kind of put their heads down to the grindstone and deal with it and grit their teeth. Other people, especially if you’ve got somebody new coming in who’s maybe done things a little differently before, and they see these things, and they’re like, “Oh my God, what are you people doing to yourself? Stop.”

Christine Cuellar: Yeah.

Alan Pringle: It can be-

Christine Cuellar: Fresh eyes.

Alan Pringle: … a catalyst like that.

Christine Cuellar: Yeah.

Alan Pringle: So…

Christine Cuellar: Okay.

Alan Pringle: Yeah, fresh eyes. That is really a dull answer, but that’s often what happens.

Christine Cuellar: No, that makes sense. Yeah, no, that makes sense. And does it make the problem worse if people put it off, put off consolidating systems, or does that not really matter?

Alan Pringle: Oh, I think it does. I mean, think about it. What happens if you ignore a plumbing problem in your house? Is it just going to go away by itself? No, it most certainly is not.

Christine Cuellar: It’d be nice, but yeah.

Alan Pringle: Yeah. I mean, just think about it. “Oh yeah, I’m going to ignore the fact that I have got a dripping hole in my ceiling or there’s water pouring down my wall. I’m just going to ignore it and hope it goes away.” I don’t think that’s the best way to handle that. And that’s true of content operations as well.

Christine Cuellar: It’s the ostrich approach, right. “If I can’t see, it’s not real. It’s not… We’re fine.” Yeah, that doesn’t ever work out. That kind of leads me into another pain point that actually came up quite a lot. Yeah. Doesn’t work. A lot of people mentioned executives or managers not valuing content, which kind of seems like that would be related to this. That was a pain point that we have often seen. Can you talk a little bit more about that?

Alan Pringle: There is an issue where people who create content and their contributions sometimes are not quite understood, or they’re overlooked by executives. A lot of executives are focused on numbers. That is their language.

Christine Cuellar: Mm-hmm.

Alan Pringle: They don’t care about the tools that you’re using. They don’t care about anything but, for example, that people are getting the content they need and not calling a help center, and costing money. That’s when they care about content. They’re looking at it from a different lens.

Christine Cuellar: Yeah.

Alan Pringle: So if you’re going to communicate to them about content, you’ve got to talk metrics, you’ve got to talk numbers, you’ve got to talk money, and that’s where sometimes content creators fail. They don’t look at things that way. So that’s sometimes where a consultant can come in handy and start to help you speak “C-level-ese”—

Christine Cuellar: Yeah, yeah.

Alan Pringle: … basically to kind of bridge that gap between, “This is what’s broken versus this is how we can fix things, and it will increase productivity and better metrics.” Less money spent, better results, that sort of thing.

Christine Cuellar: Yeah, that makes sense. And it sounds like bridging that gap of communication both ways, you’re both helping executives understand the value and helping content people communicate their value. Is that accurate to say?

Alan Pringle: That is fair, and again, not one size fits all. There are some executives, especially that have come up through the ranks of content. They get it.

Christine Cuellar: Yeah.

Alan Pringle: They totally get it. So there are some people, and those people are great to work with. Sometimes, people need a little education, and I’ll just leave it at that.

Christine Cuellar: Yeah, yeah. No, that makes sense. And so you mentioned metrics. What are some metrics that content individuals can have just on hand to start communicating their value to their team, to their company?

Alan Pringle: One thing you can do is kind of get what’s the dollar value you can place per hour on what it costs for a content creator to develop and distribute content. Find a way to find out what that amount is, what that dollar value is. Then, take a look at, for example, what if you automate publishing and cut out 80, 90% of that work by automating publishing? What’s that worth? What’s the dollar value on that? What’s the dollar value on getting closer to simultaneous shipment on localized content?

When you get your product, your service, whatever out there to other markets in this very, very global world environment now, everything’s so interconnected if you get things out to all the different markets, almost at the same time, how much more money are you going to pull in than if you had to wait three, four months for the localized version to get out there to those customers? So think about things like that.

Christine Cuellar: Yeah, those are great. Those are really helpful examples. And do you have any specific recommendations on how those should be communicated? Is that something that should be in a big kind of company team meeting? I know that’s probably a case-by-case basis, but-

Alan Pringle: Well, again, I mean, what is the executive team’s preferred way of communicating? There’s your answer right there.

Christine Cuellar: Yeah. Yeah.

Alan Pringle: If they don’t like email, why are you going to send that … email? Don’t do that.

Christine Cuellar: Don’t send an email that doesn’t communicate your value. 

Alan Pringle: No. If they like spreadsheets, put that mess in the spreadsheet. It depends on the audience. You need to find a common ground with the people that you’re creating these stats for and share it in a way that they can absorb and appreciate whatever that is. And me telling you what to do here is not as helpful. You need to do some digging or have your consultant work with you to figure out the best way to communicate that and do it that way.

Christine Cuellar: Yeah, absolutely. That makes sense because ultimately, I think if you can communicate… Because content really does have real business impact and real business value, and so it’s just about communicating that.

Alan Pringle: Yeah. And this is… And it’s not even just in regulatory situations. Yeah, content in regulatory situations matters a whole lot because if it’s non-existent or wrong, somebody’s going to die or get injured.

Christine Cuellar: Mm-hmm.

Alan Pringle: Even beyond that, even if you’re not in a regulated environment, there are contributions content can make to keep customers happier, to keep down support costs, and many other things. Not everything is tangible. A happy customer, that can be hard to quantify. But a happy customer not calling your support line, you can quantify that. So that’s-

Christine Cuellar: Yes.

Alan Pringle: … one way to look at it.

Christine Cuellar: Absolutely. I know just personally, for me, I’m much more likely to continue or stick with a company where I can do… I can be pretty self-sufficient. If I have problems, I can look it up and deal with the problem myself. And if I do have to contact support, it’s a quick call that gets resolved easily.

That’s just… I think that is how people make their purchases nowadays. And I know that’s kind of more of a consumer kind of mindset rather than business-to-business. But that’s a big part of the consumer experience is can I get what I need just with the content that you already have out there in the world?

Alan Pringle: Yeah. And I think it’s worth mentioning here that when people go to your site and look at the content that’s available out there that’s associated with whatever product or service they’re considering, it could be support content, it could be a help portal, it could maybe even be training content. They are not just looking at your marketing to make a decision here.

Christine Cuellar: Yep.

Alan Pringle: There are other content types that come out to play. And anything that’s out there that the public can get to and see, believe it or not, that’s marketing content, and you need to treat it as such and understand its value as that as well.

Christine Cuellar: Yeah, absolutely. Well, Alan, I think that’s a really good place to wrap up. Clearly, we could talk about pain all day because we have a lot more to…

Alan Pringle: It’s my job, what can I tell you?

Christine Cuellar: Yeah. Yeah. So we are going to continue this discussion in the next podcast episode. Alan, thanks so much for being here with us today.

Alan Pringle: I haven’t run away, so let’s-

Christine Cuellar: Yeah.

Alan Pringle: … get to the next episode.

Christine Cuellar: Thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Ask Alan Anything: Resolving pain in content operations (podcast, part 1) appeared first on Scriptorium.

“Regardless of whether you’re talking about machine translation or AI, don’t just run with whatever it provides without giving it a thorough check. The other thing that we’re seeing with AI that wasn’t so much an issue with machine translation is more of a concern around copyright and ownership.”

— Bill Swallow

Related links:

• AI in the content lifecycle (white paper)
• Adapt to evolving content careers with guest Jack Molisani (podcast)
• Lessons from LavaCon 2023: How AI will impact the future of content
• 2017 content strategy trend: the rise of the machine (translation)

LinkedIn:

• Bill Swallow
• Christine Cuellar

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Christine Cuellar: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re talking about the parallels between AI and machine translation. Hi, I’m Christine Cuellar, and with me on the show today I have Bill Swallow. Bill, thanks for coming.

Bill Swallow: Hey, thanks for having.

CC: Absolutely. So for non-technical people like myself, what are we talking about when we say machine translation, is that like Google Translate? What are we talking about there?

BS: Google translates a form of it.

CC: Okay.

BS: But essentially, yeah, it’s a programmatic way of translating from one language to another.

CC: Okay.

BS: It’s been around for quite a while and we see it commonly in Google Translate and other online uses, but it’s actually been around for quite some time.

CC: Okay. So I know that as AI has become the biggest topic in 2023, we’ve often compared it to machine translation. I know we’re going to talk about that throughout the episode, but can you give just a little intro to why they’re compared so often?

BS: Yeah, I think it boils down to really where machine translation started.

CC: Okay.

BS: So I’m not going to give you years because it’s not at the top of my head, but it basically started out as a rules-based program. So people sat down, wrote these if then else statements essentially, to basically say, if you come across this phrase, then it’s translated in this way for this language.

So they started out with that rules-based approach, and they’ve beefed up the rules and they’ve beefed up the processing. And of course, they improved the examples on the backend of the finished translation and modified that so that the translations kind of became a little bit better over time.

CC: Okay.

BS: Then they switched over in many cases from the rules-based to more of a machine learning model, which then, basically it’s like early AI. So it started to learn patterns and it started to learn about context a bit based on the words and phrases that were being used and could draw additional inference from that.

CC: Interesting.

BS: And essentially that started to develop more and more until we got to an AI use case. So it’s something where you actually get this robust use of machine translation. So it’s actually using a lot more learning models in that translation process. And the machine translation process is a little odd because you can do it out of the box, so something like using Google Translate where it basically uses its own Google index as a resource for translating a lot of that content. But a lot of translation companies and a lot of companies that employ machine translation, whether they are translators or not, some companies do it in-house on their own. They will basically train their machine translation against their own content and their own translated store of content so that it brings back their approved wording, their approved language models.

CC: Gotcha. I can totally see how that is a big parallel to AI right now as we’re talking about having an internal AI versus just throwing content in ChatGPT. That makes sense. You mentioned there was a transition into machine learning. When that happened, how did people react? Was it really similar to how people are reacting with AI? Was it split? What was that acceptance like?

BS: Yeah, I think there were some parallels there. Just as with what we’re seeing with AI now, there’s a lot of concern from people saying, oh, the machine is going to essentially rule, make my job obsolete because it can now write these blog posts, it can write these screenplays, it can develop these characters, it can produce these images. But with machine translation, there was that similar kind of fear where translators were like, oh, it’s going to reduce my margin. It’s going to put me out of a job. But we haven’t really, we saw that to some extent in the very beginning, but what we’ve found over time is that no, the people are still required to go in, proofread that machine-translated content, clean it up, make it more appropriate, and essentially improve what’s on the backend that the machine translation is pulling from so that things are improved over time.

CC: Yeah, process updates and that kind of thing. Improving the bank of-

BS: Right, improving the phrases, getting rid of things that are no longer said in certain areas because language is ever-evolving.

CC: Yeah, that’s true.

BS: You need to be able to keep up with those changes.

CC: That’s true. And how far ahead would you say that machine translation is compared to AI? Is it five years in the future so we can maybe see what might be coming? I know that’s probably really hard to quantify.

BS: Let me get my crystal ball.

CC: Yeah, yeah, there we go. Give us an exact answer.

BS: I’d almost say that they’re on two parallel, but different paths.

CC: Okay.

BS: And that I think we’re going to see a lot more blurring of the lines. Those paths are going to start to come together a little bit more. I mentioned that machine translation is leveraging AI to a good degree these days because it’s the next step in that form of machine learning. It’s no longer a core programmatic learning model, but it’s more of an adaptive one. So it basically will influence its own way of learning about stuff going forward. AI is employing machine translation to many degrees. We saw there was a video floating around LinkedIn of this new utility where, and I think Sarah spoke about it on a previous podcast with Stephan Gentz. But yeah, you basically record yourself saying something and it will turn around, machine translate that content, use your tonal voice and basically re-speak, and then re-sync the video so that it looks like you’re speaking a completely different language.

CC: That’s crazy.

BS: It’s nuts. I watched the video a few times. I don’t know either languages. I think they used French and German. I know enough German to be dangerous, and I know enough French to order a meal.

CC: It’s the priority.

BS: But the German I found was actually pretty spot on from what I could understand of it. And I know Sarah speaks pretty much fluent German, certainly more than I do, and she only found really one mistake, I think.

CC: That’s crazy.

BS: It’s crazy. So there are cases where things are being employed, and I think we’re going to see a lot more of that.

CC: Okay.

BS: On the machine translation side, we’re certainly going to see it adopting more robust AI models so that it can continue to build and improve how machine translation is being done. On the flip side, I do think that AI will be leveraging more of the linguistics modeling that is baked into machine translation so that it can do a better job of representing essentially the human construct of language.

CC: Wow. That video example that you gave and that Sarah shared before, that’s just, I feel like that’s one of those examples that I don’t know, 50 years from now, we’ll look back and the kids will be like, that’s so used to, I don’t know, stuff like that is what they’re totally used to, or I remember back in my day that was a big deal, anyways, it’s just mind-blowing that this kind of stuff is happening. So speaking of those kind of innovations and industry disruptions and that kind of thing, we’ve talked a little bit about how with machine translation and then with AI kind of on parallel paths merging together, what are some of the ways that the disruptions have been really different or have created different things for the content industry?

BS: I don’t know if there’s any real difference in how they might be disrupting the industry or how they might be employed. There are differences from a practical matter, when would you deploy a translation management system versus when could you use… Well, AI is kind of a really nebulous term. It could mean anything. It could mean ChatGPT, it could mean image rendering software. It could mean really anything. With machine translation, we’ve seen it become more of a daily utility. So you come across a news article in another language, if you’re using Google Chrome, you might have the option to translate this page. If you’re not using Google Chrome, you can go to, for example, translate.google.com and just provide it the URL or copy and paste a paragraph, and you can basically get an idea of what that website’s talking about. But we’ve seen it become more baked into applications as well. Certainly, there’s a whole industry around providing translation services. So we’ve seen that kind of pick up the pace on round-tripping translation work.

So before you would have someone sit down and actually translate a block of text and they would use translation memory, which is essentially a store of what was translated last time, to kind of pull from and pre-fill the translation, and then that way they can fill in the gaps. That’s a very, very high-level view of translation memory, but essentially it takes that to the next level where it will pre-process the translation for you and provide you with something that’s maybe 95% there. And then you would get someone who is an expert in the language and the subject matter and the target locale, because we know that Spanish is different depending on where you are in the world, for example. And they would proofread it, clean it up, and probably commit that back to whatever the machine translation is using so that it uses that reference next time rather than having to go through that again.

We see it baked into applications as well. So there are some gaming applications that will auto-translate a chat on the fly so that depending on, no matter where you are in the world, you can actually still understand what these players are saying. So if you’re on a team and someone’s saying, go now, and you don’t speak their language, you have no idea what they’re saying.

CC: Yeah.

BS: But the chat translation can kind of help. It’s not perfect, but it’ll help. With AI, I kind of see that moving into a similar role. It’s going to be, now we’re looking at it as, oh, look what this thing can do. It can write me a limerick. It can essentially create me a photorealistic image of whatever I choose to think up. I give it a description and it creates something, and it might be what I’m looking for, and it might not, and there are flaws to those as well. But I kind of see AI being baked more into the backend of a lot of the tools that we use on a daily basis to help with more robust search and query activities, to be used as an editor or a checker for things on the backend, to be a starting point for developing something new.

So whether it’s a piece of code or in our world where we do structured authoring work, it could be something as easy as give me a framework for a new task that I need to produce, and it will lay everything out. That kind of harkens back to more of a template, but you can kind of say, give me a task based on what I’m writing about here in this section, and it can pull some pieces in and fill things out. So I also see it as being more of an aid for finding resources that already exist so you’re not reinventing the wheel and things like that. So things that essentially it’s going to be baked into a lot of different utilities that some of which we use now, some of which we haven’t thought of yet that will make our lives easier.

CC: Okay. So what are some of the pitfalls that we fell into during machine translation that we can avoid with AI? Do you have any red flags or things to watch out for based on how things went the last time, essentially?

BS: Yeah, I think the biggest one is to not take what it provides for granted.

CC: Okay.

BS: So regardless of whether you’re talking about machine translation or you’re talking about AI produced whatever, is to not run with whatever it provides without giving it a thorough check. I think the other thing that we’re seeing though, and it wasn’t so much an issue with machine translation, is more of a concern around copyright and ownership.

CC: Okay.

BS: So who essentially owns the rights to these things?

CC: Yeah.

BS: And it kind of goes back to, well, what was the model used to kind of create them in the first place? Was it using a public domain model or was it something that was trained only on a private store of information?

CC: Yeah. So looking into the future, do you see private AI being maybe the best way to move forward with AI? Not that people will necessarily, or there’s maybe some use cases for public domain AI too, but do you see that though as more of where we’re going to head?

BS: I think it’s inevitable. I think that we’re going to have cases where, we’ve seen cases already where companies have kind of uploaded examples of their own code to see if they could get a public AI model to write more code based on that model. And unwittingly, they basically let their own IP out into the wild, so now everyone can use what these people created that they uploaded in the first place. So that’s an oopsie. So I think that based on cases like that, I think people are going to start employing a private model, basically a walled garden where they can train and develop their own corpus of information, whether it’s images, code, text, what have you, and use that to produce things using AI.

But I still think that, yeah, there’s going to be a public model for, I don’t see that need ever going away. Just as we have public models for everything else that we use on the internet, I think we’re going to see AI have its own footprint there as well. We might need to be careful while using it. There might need to be more guardrails attached, but I don’t see that going away.

CC: Yeah, that makes sense. And you mentioned that with concern for people’s jobs, I know that of course is a concern right now with AI as well. And you mentioned that at the beginning of machine translation, that was, you did see a little bit of job loss, but overall, those experts were still needed to manage the content, make sure that everything that is being created is accurate. So what would you say to people that are really concerned about that right now? Do you think that’s going to be really similar for AI? Are there any differences you can think of?

BS: I think this is actually a good learning point from machine translation because yes, some people lost their jobs initially when machine translation came out. I think in hindsight, that was an error or that was a bad decision to either let people go saying, oh, a machine can just do it. Because it was very clear out of the gate once machine translation really started being used that people are still needed. They’re still needed to clean up what the machine translation is producing. They’re still needed to do new translations into new markets in new contexts with new terms. A machine just can’t invent things and have it be correct for a very specific target audience.

To do any kind of translation correctly, you need to know the subject matter. You need to know the language that’s being spoken in, the flavor of language for the locale in which you are targeting that content, and anything else about that locale that might influence jargon or anything else that might need to be employed. So yeah, I see a similar warning, I guess, for people who are looking at AI and saying, oh, we can reduce our staff by employing AI. It’s like, no, you’re going to augment your staff and they are going to need to learn new skills because they are going to need to learn how to leverage AI to produce basically more and better work. It’s a utility, it’s not a replacement.

CC: Yeah, I liked how you phrased that. I think that that’s a good perspective for employers, for writers, for anyone who is worried about the job climate right now, I think that’s a good way of looking at AI.

BS: And as of right now, we know that AI is being used to generate articles on the web. There are a lot of websites that are using AI to just basically pump out post after post after post, article after article after article. And you can tell immediately once you start reading it that it was not written by a human.

CC: And at the end of the day, it’s still humans connecting with humans. So whatever content we’re putting out there, it needs to be valuable to people that are reading it. It needs to have a purpose, it needs to be doing something. It needs to just be humans communicating with humans. So those big content pumping blog posts, all that kind of stuff, that does bother me because it’s just content for the sake of getting content out there. And there’s humans at the other side that actually need information. So I think this is a really good perspective to have for how to leverage AI in the same way that we’ve leveraged machine translation, how to automate processes, how to have a starting place for people when you’re writing, but not to just make it all about machines and not people. So Bill, is there anything else that you can think of when you’re thinking about machine translation? Any other comparisons between that and the rise of AI? Anything else that you wanted to share before we wrap up today?

BS: I’d say approach it both optimistically and cautiously.

CC: Yeah, that’s really good, especially with the concerns that you mentioned about copyright. We do have an article that Sarah O’Keefe wrote and recently updated as well about AI and the content lifecycle. So we’ll post that in the show notes. Also, some other interviews and information that we’ve provided about AI. So all of that will be linked in our show notes. And Bill, thank you so much for joining the show and talking about this today. I wasn’t in this space while machine translation was happening. It’s really interesting to hear about the parallels because they really are very similar in a lot of ways, and it’s cool that we have some takeaways from both.

BS: Thank you.

CC: Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post How machine translation compares to AI appeared first on Scriptorium.

“This is going to be a free book. We are not going to become rich and famous with this book because we decided that we wanted to make the content in the book accessible for everybody who is interested in learning about content operations. It’s going to be published as an open-access book by Virginia Tech Publishing.”

— Dr. Carlos Evia

Related links:

• Access your copy of ContentOps Edited Collection: Content operations from start to scale from Virginia Tech publishing.
• Adapt to evolving content careers with guest Jack Molisani (podcast)
• The Scriptorium Content Ops Manifesto
• Prerequisites for efficient content operations (podcast)

LinkedIn:

• Dr. Carlos Evia
• Sarah O’Keefe

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Welcome to The Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about the ContentOps Edited Collection: Content operations from Start to Scale. 

Hi, everyone. I’m Sarah O’Keefe. I’m delighted to welcome Dr. Carlos Evia to our podcast today. Based at Virginia Tech, Dr. Evia is a Professor of Communication, Associate Dean for Transdisciplinary Initiatives, and Chief Technology Officer in the College of Liberal Arts and Human Sciences. He’s also Director of the Academy of Transdisciplinary Studies and affiliated with the Virginia Tech Centers for Human Computer Interaction and Communicating Science, and also a member of the Stakeholder Committee for the Virginia Tech Center for Humanities. In his copious free time, aside from these things, he has been involved with work on DITA standards and especially the Lightweight DITA initiative. So Carlos, welcome aboard. I’m glad you found 20 minutes or so to join us here.

Dr. Carlos Evia: Hello, Sarah O’Keefe. It’s been a while, so good to catch up with you.

SO: It is good to catch up with you. So tell us about this new content ops book. You spearheaded it and I guess I should mention that I about a million years ago, contributed to it. I don’t actually remember what I wrote, so this could be a problem. So tell us about the book.

Dr. CE: Well, it’s new. It’s new to the world because it’s coming out next month and by next month, I mean October of 2023. But it’s a book that has been about 10 years in the making. And some sections of the book really read like creative nonfiction because there are characters that are people in real life and surprise, you are one of those characters. Because the idea for the book started some 10 years ago when we will meet at conferences. And I don’t even remember what happened first, if I invited you to come visit my class here at Virginia Tech or if I saw you at the STC summit, and I was like, “Oh, wow. She’s very smart. I have to invite her to come to my class.” But I don’t know, I guess we were already chatting and talking to each other. I cannot claim that we were friends. I would dare to say that now we’re friends. We’ve had many meals together, family involved, so I guess that counts as friends.

SO: I certainly hope so.

Dr. CE: So you and Alan Pringle in Scriptorium published a very handy book that I used for many, many years in my classes, Technical Writing 101. And you had three editions?

SO: Yeah.

Dr. CE: Yeah. So after the third edition, I started chatting with you on Twitter, when it was called Twitter and not X or whatever it’s called now. And I said, “Oh, wouldn’t it be nice if we write a new version of that book because I have been using it in my college level classes for many years and I have ideas on how to expand it, how to improve it.” And we have been talking about it for many years. And then finally before the pandemic in 2019, we were together at a conference in your neighborhood. It was in Durham. And we sat down and we said, “Okay, let’s finally start thinking about it.” And we made an outline and then we both realized that we could not call ourselves technical writers and that we could not write another edition of a book called Technical Writing 101, because what we were doing was way more than just technical writing.

Yes, of course, what paid the bills was doing technical writing, but you were doing more sophisticated things. I was teaching more sophisticated things that were not just writing about technical subjects. So we brainstorm about many ideas on what do we call it? And we ended up with how about content operations? That’s a thing, and people are talking about content ops. And then the pandemic hit. And when the pandemic hit, everything stopped. And I remember that we had nothing better to do. We will get into endless Zoom conversations, and we started inviting people and we invited Patrick Bosek to chat with us about it. And he said, “Wait a minute, if you’re talking about content operations, we have to bring Rahel Bailie.” And we brought Rahel.

And I guess at the time the idea was that we were going to have a book with four authors and you were going to write some chapters and I was going to write some chapters and Rahel was going to write the introduction and Patrick was going to write something. And then we were like, “What if we invite more people?” And we started making a list of topics that we wanted to cover and we ended up inviting more people. And this is where we are. The book became an edited collection with several chapters written by experts in industry who had something to say about how content operations is impacting the work that they do, not just in our home neighborhood of technical communication, but also in marketing and other forms of more persuasive content.

And finally, the book after those delays, and there were a couple other delays that we can talk about later and we will talk about those later, finally, it’s coming out next month. And I was able to see a draft of the cover. I think I shared with you the draft of the cover and yeah, it’s coming out. Oh yeah, important thing to mention. This is going to be a free book. We are not going to become rich and famous with this book because we decided that we wanted to make the content in the book accessible for everybody who is interested in learning about content operations. So it’s going to be published as an open access book by Virginia Tech Publishing.

SO: So I think this means that if you want an electronic copy of it, it will be freely available. And if you insist on print, then presumably people will have to pay to get the actual physical print edition.

Dr. CE: That is correct. And I don’t think the print version will be an on-demand print service, and it’s not going to be very expensive. But there will be, I think, EPUB and PDF versions that would be downloadable from the Virginia Tech Publishing website.

SO: And I appreciate that Virginia Tech Publishing did this because of course, academic publishing is notorious for these $500 science textbooks and they’re apparently doing it all wrong, and I appreciate that. So this is great.

Dr. CE: We didn’t want to go in that direction on purpose because we know based on the kind of books that you have published with Scriptorium, the kind of work that I have published about DITA and Lightweight DITA, that we have readers in parts of the world that they just cannot buy a book, but they’re very interested in these topics and that’s why we, and I appreciate that you and all the other people who made contributions to the book accepted and signed the agreements to have this be released as open access with awareness that there won’t be any sweet money coming to you in royalties for the chapters that you contributed to this book.

SO: Well, I’ve done a number of commercial books that had royalty agreements associated with them, and I can assure you that the delta between that and what we’re doing with this book is far smaller than you might hope. I mean, it’s never been a big moneymaker. So in addition to Rahel and Patrick, I don’t want to leave anybody out, but I did want to mention that we brought in Kevin Nichols to talk about customer experience in content ops. Jeffrey MacIntyre is dealing with personalization. We’ve got Loy Searle on localization and content ops. Kate Kenyon did a really good chapter on governance, and then we’ve got some really interesting forwards and epilogues and afterwards from some other luminaries in the industry. So it was a really fun project to work through.

Dr. CE: Yeah, I’m very grateful that it started during the pandemic, and I will just email people that some of them we knew from conferences, some of them we didn’t know, and somebody will make a recommendation and I will knock on their virtual doors and be like, “Hi, I have this project that is going to be free and you won’t be making any money out of it, but people will know about content operations. Do you want to write something?” And they said yes. So that was very generous.

SO: So the intent here is to put a stake in the ground and sort of say, “Okay, this is what we think.” This is where we think content operations is and what it is and how it connects to all these other aspects of content, of I want to say communication, but what it looks like to have a content lifecycle that has all these tentacles into all these other pieces and parts. Customer experience is a great example because once you know what your customer journey needs to look like, you can connect that to, and thus I need this kind of content and therefore I need this kind of a content lifecycle. Who’s the target audience for this? Who do you think should be reading this book?

Dr. CE: Well, the way that we started conceiving the idea and what eventually became the book, and it goes back to when I first met you and I invited you to come and visit my class. And again, you were very generous to drive all the way from Durham to Blacksburg to talk to a class of 20 students who were learning about DITA. And I didn’t pay you, I just bought you dinner, and I really thank you for that. That was like, gosh, how many years ago, 13 years ago or something like that.

When I was learning and putting in practice the things that I learned when I was in graduate school and also my experience being a technical writer in industry, I always applied the things that I knew to my classes and I was reading and doing the traditional approach of exposing myself to new ideas, going to conferences. But I realized early on in my career as a professor, which I’ve been doing this gig for like 23 years now, don’t tell anybody, that one of the best ways to bring fresh ideas into the classroom was to invite guest lecturers.

And in particular, in the case of technical communication and the type of technical content enabling content that we do, I realized that bringing guest lecturers from industry and particularly consultants was the best way, in my opinion, to expose my students to practices and knowledge that were not in written textbooks, that were not even in academic journal articles because that was not the work of people who were in academia. So I think the book is structured like that, is the equivalent of a guest lecture. Somebody who comes to your classroom, in the case of people in academia, and is going to be presenting their ideas and give you some pointers on how to implement this into your content work.

And on the other side of the spectrum, we have people in industry, and this will also be the equivalent of having somebody who is a guest and comes to give a presentation about a new topic that people might be interested in. And from the work that Rahel and I were doing for a couple of years when we were working on our chapters for the book, we realized that there’s a lot of interest from many corners of the content universe on the topic of content ops or content operations, be it because people think that is related to dev ops or design ops or many other ops that are out there, or because people want to get an operational model on how to tackle enterprise level content.

So if you’re in academia, what I hope is that this book helps you expose your students and yourself to perspectives from experts in industry when it comes to technical content and marketing content and many other aspects of persuasive and enabling content. And if you’re in industry, I hope that this also helps you continue your learning or start expanding your learning on topics related to the content lifecycle that go beyond just planning how to do things in a content strategy, but really developing a good governance model for content operations that really keeps everything, we hope, under control, but we know that things are never going to be under control, and that’s when we are probably going to have to write a new book in a few years.

SO: Well, yeah, I mean, it’s funny that you talk about the intersection of academia and industry or practice. I mean, first of all, I live in Durham, North Carolina, so Virginia Tech is actually not that far, and it’s this really pretty drive through the mountains. So no particular trouble there. But I think the really important thing about this is that the work that you’re doing at Virginia Tech paying attention to this question of how do we apply, how do we look at what people are doing out there in the world and then intersect that with the rigor of the academic inquiry and practice and all the rest of it, I think is really important and unusual.

There’s not actually very many professors. There’s a few, but there’s not very many academics out there that are looking at this kind of information through a practical lens in addition to the study of rhetoric and all these other underpinnings that I think are important to the practice of whether it’s technical communication or any kind of communication. So I’m always happy to come and talk to students. They have a habit of asking questions that I can’t answer because they are much better grounded, really, than I am in the theory. I know an awful lot about how to make things happen, but anything I’ve learned about the theory that’s underlying it is kind of incidental to what I’ve done.

So it’s always interesting to hear those voices and hear people talk about the research that they’re doing, especially the grad students, but everybody, and the questions that they’re asking as they’re getting all this foundational learning. And you talk about being a professor for a while, it is very, very unusual for somebody in our age cohort to, we’ve had a longstanding argument about who’s older, but we won’t get into that just now. But we fall into the same generation certainly, and I think our birthdays are like a year apart or something dumb. And I think we decided I’m older, although for a while I thought you were older and that was awesome. Anyway.

Dr. CE: That might be correct.

SO: But the thing is that for us, a generation ago when we were in school, in college, there wasn’t a whole lot of any of this. There wasn’t really the study of TechCom or, I mean, there was certainly rhetoric but not rhetoric as applied to TechCom and enabling communications. And so people like me tend to be very poorly grounded in the academics and the preceding research that has gone into this. So I appreciate being able to do that. So how do you define, what’s your best definition of content operations and how that fits into the world?

Dr. CE: Well, the book actually borrows Rahel’s definition, that I think I have a coffee mug here with her definition that she mailed me. And she talks about you have your content strategy, and I guess at this point, people kind of know what a content strategy is. I think the listeners of this podcast need to know about content strategy or maybe they’re interested in content strategy. And that’s the plan of how do you develop, maintain, publish, sunset or revitalize content. So Rahel’s definition says that content operations is the implementation of that strategy.

So it’s like a good example that she has been using for years is that think about if you’re an architect and you make the blueprints for a house, that’s the strategy, that’s the plan. But ain’t nobody telling you in those plans how to live in the house, that you have to change the air filters of the air conditioning, that you have to clean the toilets. Nobody’s telling you that. So that’s the operational part of it, and that’s the content operations component. Other people, sometimes I’m in that camp, see content operations as bigger than that and including the process of developing, implementing and revising the content strategy.

So I think it’s a combination of knowing who is available, what is available in resources and what is missing or what’s needed to really keep a healthy lifecycle of content. That includes the planning, that includes the actual writing, creating, I was going to say filming, but nobody uses film anymore. The actual recording of videos and audio and the publishing and the evaluation assessment and then making new versions or just putting to sleep content that nobody cares about. So it’s really about how to live in that house that you created with all the daily and monthly and yearly transactions that need to happen that when they sold you the house, when they sold you the idea of the house, those were not considered. But based on the work from experts like you and the people who wrote chapters for the book, we are offering these lessons that say, “Hi, we have lived in houses and we know how to take a look at those operational components that you might not even consider now that you’re starting your strategy.”

So I think that’s a complicated way to tell you what I see as part of operations, but it’s heavily influenced by the work of Rahel Bailie, who was very generous to write the introduction to the book. And then last year when the book was almost ready, this close to being ready last year, Rahel and I sat down and said, “This is missing something. It’s missing a chapter that talks directly to content developers, not their managers, not people who are at the high level of strategy or the high level of governance, but people who are actually going to create the content. How does content operations can help you or create challenges for you?”

So Rahel and I went into a months’ long adventure of writing this long chapter that at one point we decided this might be a separate book altogether, but we created this new chapter that is included now in the final version of the book that is speaking directly to people who are going to be creating content. And how thinking about the work that you’re doing as part of a system and not just, “I’m here in my lonely cubicle or working from home because hashtag remote work forever and I don’t talk to anybody else.” So I think that’s the whole process of thinking about operations in a systems approach.

SO: Yeah, that’s interesting. And I think that looking back at some of this stuff, back in the olden days, there was really this concept that as a content creator, technical writer, whatever, I had ownership of a particular book or document or set of documents, but it was like, I’m the writer of the admin guide and you are the writer of the user guide, and I’m going to go learn admin things and write them down, and you’re going to go learn user things and write them down, and then we’re going to have this big complicated print production process. And I know an awful lot of things about press checks and blue lines that I haven’t used in 25 years. I used to know things about blue lines and press checks. But I think one of the reasons that we really need content ops is because the concept of authorship has fragmented, right?

I’m not writing a 500-page admin guide. In fact, it’s pretty unlikely that the organization is writing a 500-page admin guide. We might be writing 500 topics worth of admin stuff, but I’m writing a hundred of them and you’re writing a hundred of them and a couple of other people are contributing bits and pieces. And then we put it all together as the sort of, here’s the help for the admin person, and we put it online.

So the print production process is gone, the press check process is gone, the physical production is gone. And we are fragmented in the sense that nobody has the overarching view of what is this set of content. And because that doesn’t exist, because there’s not me as the owner of this book, which, by the way, from a psychological point of view, introduces a whole set of other complications. But because that owner doesn’t really exist anymore, our systems have to be better so that the five of us, or the 27 of us that are all writing three topics can contribute in a consistent and useful manner. Your systems don’t have to be as good when you’re relying on individuals, single individuals.

Dr. CE: And it might be that the system has people who are in charge of ensuring that the user experience of those who need the content is going to be good and satisfy the information needs. And that’s not the job of the developers. I mean, as the writer, as the creator of videos or audio, it might not be your job to ensure that whatever website, app, product that comes out of that machine that generates the content is going to satisfy the needs of a human being. And it might be that it’s not your job as the creator to be in charge of managing that whole process.

So that’s why the systems approach of thinking and being aware, it doesn’t have to be that happens at the big enterprise level, as you know, because that’s the job that you do every day at Scriptorium. Even small organizations, I don’t want to say corporations, have adopted these models of creating reusable chunks of content that you create. And based on the metadata and the connections that they have behind the scenes are going to be reassembled in different deliverables for the needs of different audiences and in different contexts and in different models.

So it’s not just the work of a lonely writer. It’s a combination of approaches. And I think that content operations really takes a look at that lifecycle. And like you have said before, not every implementation of content operations is going to be super high-tech and mega efficient. You might have your content operations approach that is based on the budget that you have and the scale that you have. And it might not be the prettiest, but at least you have an idea and you want to have, not that you can always achieve that, but you want to have some sort of control over your content publishing structure instead of letting whatever, I’ll just write a piece of paper and see how far it goes if I send it like a paper airplane. So yeah.

SO: So you mentioned the machine and the systems, and I don’t think we’re allowed to have podcasts this year without talking about AI. So do you think that the, I’m trying to avoid using the word fad. Do you think that the rise of AI, and especially this sort of 2023, all of a sudden AI is everywhere and everything is AI-enabled and everybody’s talking about AI, do you think that’s going to change content ops? How is it going to change content ops? What do you think?

Dr. CE: I think it has already changed it. Remember I told you that there was a couple of moments in which we had stopped the publication of the book and revised it. Well, the first one was, I told you, Rahel and I decided that we wanted to write a chapter that talked directly to content developers. And the second one was that Patrick Bosek and I and you were in one of those meetings, we sat down and we said, “We cannot publish a book on content operations without talking about AI and particularly ChatGPT,” because it was the boom of everybody’s talking about ChatGPT and all the conference presentations were about ChatGPT. So the book was already going to print when we said, “Wait a minute. We need to open it and revise Patrick’s chapter, which is about the technology that supports content operations and include a statement about ChatGPT.”

So I honestly think that artificial intelligence has already impacted and changed the work of content operations. It might not have affected, like you said, all the content operations implementations of the world because some might be with limited budget and limited scale. But I think that there are many use cases that are happening right now.

The main consideration is this. It’s not about learning to use the tools. It’s not about seeing how much money you can invest into having AI create your content. It’s about, as the person who supervises and is in charge of the whole operations or the persons, if it’s a large team, consider the ethical implications of using artificial intelligence and decide, “I’m going to use AI for this, to summarize this, to create this. What are the possibilities that by doing this, I put some of my users at a disadvantage? What are the implications of by doing this, I’m going to completely run my bulldozer over the diversity of my readers, of my users, and I’m going to have damaged their perception of their interactions with whatever information products I’m creating.”

So I think the big conversation has to be not is AI going to impact content operations or content because it’s already impacting it, but how do we supervise and bring this into the cycle of content operations in an approach that doesn’t leave people at a disadvantage? And it might be that doesn’t leave content creators or content managers at a disadvantage, and it’s concentrated on the ethical perspectives, on the use, implementation and feeding of artificial intelligence tools. So I think that’s where the conversation is really going to go in the near future.

SO: That’s interesting. And I think additionally to that, the question of trust and reputation. If you develop a reputation for generating junk because I asked ChatGPT to write my bio and it made up a bunch of stuff, and then I just used it because why not? But it seems to me that this is going to, and we’re already seeing search degrading because of all the AI generated stuff. So I think in addition to the ethical issues, there’s some really, really interesting questions around whether the efficiency that you get out of generated content, is the plus of gaining that efficiency greater than the minus of the trust and reputation problems that you’re going to have if you’re not very, very careful? I mean, you could generate it and then you can review it and clean it up and fix it, but you just gave back your efficiency gains. So then is it really a net positive?

I do think that gisting and summarizing can be very useful, but I have some real concerns about when you go in and you tell it to tell me how to operate this medical device, first of all, people don’t use Chat to ask it how to operate a medical device. But if and when you do, be careful because it might make some stuff up. And I can’t remember where this was, but yesterday I heard somebody say that, on a podcast I was listening to, and when I figure out who it was, I’ll dig it out and I’ll put it in the show notes, but essentially that when we create enabling content for new products, we are in the business of creating new content and ChatGPT does not do a very good job of creating new content. It only reissues what it has. And so if you’re creating something brand new, somebody has to do that work. And I don’t think the person or thing doing that work is going to be an AI-enabled large language model.

Dr. CE: There are many tests and forms of evaluating the content created by human beings or created, I mean, it’s not really created, it’s assembled by artificial intelligence. But I am old school when it comes to some of my metrics. And I know that some people have challenged this, and I know that some people have come up with better approaches for evaluating the content, the quality of technical content. But I go back to IBM’s Developing Quality Technical Information, and I want to be sure that the content either created or written or produced by human beings or by artificial intelligence is easy to use, easy to understand, and easy to find. And I send people back to reading the second edition of IBM’s DQTI.

And that is pretty valid today because you can have a machine generate paragraphs and paragraphs of content, and you can have very nicely machine-generated DITA tags that give it some structure. And you can have ChatGPT help you do the XLT to do a beautiful HTML5 transformation. And your content might look like it’s good, but it has to be measured by is this really helping human beings? Because otherwise it’s just garbage regardless of how pretty the code behind the scenes is, which is not necessarily that pretty because ChatGPT doesn’t know much about DITA and it doesn’t know how to establish the difference between a task and a general topic. But that’s a conversation for another day.

SO: And I mean, that’s probably a good place to leave it. I think we’ve raised more questions than we’ve answered.

Dr. CE: That’s what I do.

SO: But the book is going to be out shortly, we hope. So October 2023. And we’ll include a link in the show notes that will point you over to wherever it is that you’ll be able to order or pre-order it from. So we’ll set all of that up. I remembered who it was that talked about new content. It was Jack Molisani in our podcast from a couple of weeks ago, so I’ll add that link. And Carlos, thank you. This has been really interesting as always. Glad to see you. And sounds like we need to talk some more about what’s going on here.

Dr. CE: Yes, indeed. Thank you very much, Sarah.

SO: Thank you. And thank you for listening to The Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post ContentOps edited collection: Content operations from start to scale (podcast) appeared first on Scriptorium.

“As a company and as a content producer who’s publishing content, you are responsible for that content and you cannot rely on an agent to produce completely accurate information or information that is always correct.”

— Stefan Gentz

Related links:

• DITAWORLD 2023 recordings (YouTube)
• Adobe – Beyond Paragraphs
• Sarah O’Keefe – Is AI the meteor? Are we the dinosaurs?
• AI in the content lifecycle (white paper)

LinkedIn:

• Stefan Gentz
• Sarah O’Keefe

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. 

In this episode, we welcome Stefan Gentz from Adobe. Stefan is the principal worldwide evangelist for technical communication. He’s also a longtime expert in the space with knowledge of not just technical communication, but also localization and globalization issues. He’s here today to talk about the opportunities and applications of AI in the context of knowledge content.

Hi, everyone. I’m Sarah O’Keefe. And Stefan, welcome.

Stefan Gentz: Hello, Sarah. Nice to be here and thanks for inviting me.

SO: Always great to hear from you and look forward to talking with you about this issue. So I guess we have to lead with the question of knowledge content. What do you mean when you say knowledge content?

SG: It depends a little bit on the industry, but generally, there’s enterprise content and there are multiple areas in enterprise content and we all know marketing content and that beautiful content on marketing websites and advertising and so on, but there’s also a huge amount of other content in an enterprise and what kind of content that is is a little bit depending on the industry and which sector we’re looking at. But they also share a lot of content, which is produced across multiple industry verticals.

If you look at software, hardware, high-tech like semiconductors and robotics and so on, we have content like getting started guides, user guides, administrator guides, tutorials, online helps, FAQs and so on. But we also have things like knowledge bases, support portals, maybe API documentation, and you will find similar content in the automobile and industrial heavy machinery industry where you also have user manuals, maintenance guides, things like that, but also standard operating procedures, troubleshooting guides, safety instructions, parts catalogs and so on.

And when we look into industries like BFSI, banking, financial services and insurances, we have content like regulatory compliance guidelines. Of course, also policies and procedures, but also things like accounting standards documentation or terms and conditions, and again, knowledge bases and support portals, training portals for employees, et cetera, or partners.

And in healthcare, medical pharma, we have a lot of similar content, but we also have things like citation management, clinical guidelines, the core data sheets, CDS, dosage information, product brochures, regulatory compliance guidelines again, SOPs, maintenance guides and so on. And we have in other industries, things like installation guides, user guides, flight safety manuals in aerospace and defense, technical specifications of products, kinds of products and so on.

So there’s a huge amount of enterprise content that is produced in companies and marketing content is probably just a fraction of the content that is produced in other departments, like classic technical documentation, training departments, and generally, also as I just said, knowledge content producers or I think you originally mentioned product content which also fits, but I like to call it knowledge content because it’s a very broad term that covers not only knowledge basis as many people think, but all the content that carries and transports knowledge from the company to the user of that content.

SO: Yeah, I’ve also heard this called, I think we’re all searching for a term that encompasses the world of… It’s almost like not-marketing, not persuasive, the other stuff, other.

SG: Non-marketing content.

SO: I’ve heard it called enabling content in that it enables people to do their jobs, but of course, enabling has some pretty not so great connotations.

Okay, so we take your knowledge content and we wanted to talk about what it looks like to apply some of these recent AI innovations into the context of knowledge content. So what are some of the opportunities that you see there?

SG: There’s a huge amount of opportunities for companies using AI. Maybe we can break it a little bit down into two areas and let’s not talk about creative gen AI, like Adobe Firefly or Midjourney or so that are engines that are used to produce visuals, images, and graphics, but let’s talk about the written content here.

So I see two areas there and one is the area of authoring where content is created, and then there’s the area where content is used and consumed, whatever the consumer might be, maybe chatbot or chatbot interacting with an end user, or maybe even other services that use the content. And we can, of course, when we think from the content consumer perspective, a chatbot is definitely an area where AI can help to find content better and give better answers and maybe also rephrase content in a way that is appropriate to the content consumer. If I’m talking to, let’s say, 10-year-old children, or if I’m talking to a grownup with a university degree, they might have different expectations in how they want to get the content presented to them in terms of language, in terms of voicing, voice and sound.

SO: Right. The 10-year-old understands the technology and you don’t have to explain it to them.

SG: That might be, of course, true. Yeah, maybe they don’t even need the chatbot. So that’s the content consumer perspective, which AI can help to find better results, more fitting results, and produce nicer answers.

But there’s the other field where content is created with authoring content, and I see a lot of opportunities there. And at Adobe, especially in Adobe Experience Manager Guides, our DITA CCMS for AEM, there, we are implementing a lot of AI functionalities. I’m not sure how much I am allowed to talk about that, but we showed a couple of things at the last DITAWORLD, Adobe DITAWORLD in June where we presented some of the features that we’re implementing into AEM guides, into the authoring environment.

And one is, for example, the engine checks the content that an author is creating and compares it with the repository of content that is already there. And then makes suggestions like, “Oh, I understand that you’re trying to write that safety note, but there’s also a small snippet of content with a standard safety note in your company that maybe you want to turn that what you’re currently writing into a content reference, con reference, or maybe that single term that you’re writing there, you could turn that into a key ref because there’s already a key definition in your DITA map,” things like that.

So to assist the author to leverage the possibilities that their technology writes in a more intuitive way, instead of thinking for maybe minutes, “I remember I had written a note for that already, or I had already written that safety note,” the system will assist you with that and give you the suggestion, “Hey, this is already there. You can reuse that content.” That is authoring assistance.

We also showed, I think, some sort of auto-complete. So you’re starting to write the sentence and then a small popup comes up giving you a couple of suggestions how you could continue the sentence. And we all know this predictive typing thing for quite a few years, but usually, they are more created on classic statistical engines that try to predict what you want to write. But our solution there will take the repository of content that is already there in the database as a base for making suggestions that will fit much better than just a statistically calculated probability, how you probably want to continue the sentence.

So this kind of authoring assistance with auto-complete and predictive typing, that gets much better when you have an AI engine that understands your existing content and can build these suggestions on top of that. That is definitely one area.

SO: We’ll make sure to include a link to that presentation, which I actually remember seeing, in the show notes. So for those of you that are listening, it was at DITAWORLD 2024 and-

SG: 2023. You’re quite ahead to the future.

SO: I’m sure there will be an AI presentation at DITAWORLD 2024, however-

SG: Oh, I’m very sure. Yeah.

SO: Yeah. So this year, the 2023 presentations had this demo of some of the AI enablement that’s under development, and we’ll get that in there for you.

SG: Yeah. So these two areas are definitely areas where AI will help authors in the future, but there are many more things. For example, when you think in terms of DITA, you have that short description element at the top and an AI engine is pretty good in summarizing the content off of that topic into one or two sentences. And if you try to do that as a human being and you have your topic in front of you with maybe 10 paragraphs, a couple of bulleted lists and a table, and then trying to find two sentences that are basically the essence of the topic and making two nice sentences, “This topic is about dah, dah, dah, dah, dah,” that is quite hard for a human being, and an AI engine can do that in two seconds.

This is another area where AI will help people to get that job faster. And of course, they can then take that suggestion or not or rephrase it and rewrite it if they want, but they can take it as a starting point, at least. Short description summarizing the content.

It’s also rewriting content, maybe for multiple audiences. Originally, a couple of months back, I bought a tumble dryer from a German company for household appliances, and they have that classic technical documentation that comes with a tumble dryer explaining in long written sentences how to use it. And there are better concepts sometimes to do that. For example, a step list. And I copied and pasted three, four paragraphs there and said, “This is classic documentation. Can we write that a more simple way, maybe as a step list in DITA?” And then I got a step list with the paragraphs broken down, the steps that are ascribed in these paragraphs broken down into step list, step one, step two, step three, and so on. And that made the content much more consumable and accessible.

And so one could use AI here and say, “Okay, here’s my section in my DITA topic, for example, with the legally approved official technical documentation content,” and then I just duplicate that and let it rewrite as a step list maybe for the website. And then I could even duplicate it again and say, “Now let’s rephrase that for multiple audiences,” and say, “Okay, I have that TikTok generation person in front of me and they want to be addressed in a more personal, more loose language, more fun language, and please rewrite that content for this audience.” And then the engine will rewrite that content and say, “Yeah, hey, yo, man, you can put your dirty cloths into the dishwasher or into the tumble dryer, not the dishwasher. And you will have a lot of fun watching how it’s rotating when you hit the start button.”

And then you can change. That’s, of course, an extreme example, but you can create multiple variants of your content for different audiences very easily then. And I see that, and a lot of people are talking about doing that on the front end, on the website for example. I see that more from a responsibility perspective, on the authoring side when an author is doing that and approving it, so to say, maybe checking it if the information is really correct, the steps are really in the right order, whatever, and then it goes checked for different audiences into the publishing process in the end because that responsibility is, I see that not on the AI engine, I see that on the author who needs to make sure that the content is still accurate and correct.

SO: And I think that’s a really important point because at the end of the day, the organization that is putting out the product and/or the content that goes with the product, they can’t say, “Oh, I’m sorry. The AI made the content wrong. Too bad. So sad.” I mean, they are still responsible and accountable for it, which actually brings us very elegantly into the next topic that I wanted to touch on, which is what are some of the riSOs, some of the potential challenges and red flags that you see as we start exploring the possibilities of using AI in our content ops?

SG: That’s a very important topic I think to talk about because even very advanced engines like ChatGPT come with certain challenges and problems. There is, of course, we just talked a lot about, is the information correct or is it inaccurate or is it maybe even just invented by the engine? Usually, people call that hallucinating by just generating content and it would continue to generate content as long as you want and it will invent things.

And I was throwing some content to ChatGPT and said, “I want to write a nice blog post or a LinkedIn article. Can you give me some quotes that fit to the content that I have provided you?” And it provided me five, 10 quotes that sounded like some CEO would have said that, and it was even giving some names. And then I was aSOing, “Is that person, John something, really existing? And is that a real quote?” “No, I invented that, but it might fit. It could have been said by someone.”

SO: It could be real.

SG: Yeah, it could be real. That was basically the answer that ChatGPT was giving. That comes with a huge problem because as a company and as a content producer who’s publishing content, you are in responsibility for that content and you cannot rely on an agent to produce completely accurate information or information that is always correct because it will always generate content and will not let you know that it generated that content.

It’s extremely difficult for a human being to even check that content and say, “This is probably correct, and this might be just made up, and this might be an invention from ChatGPT because it just generated on a statistical probability that this content will probably fit.” And that is a big problem. You don’t have that when you let ChatGPT write code like JavaScript or maybe even DITA XML. There, it’s pretty accurate because it’s based on a certain framework, like a DTD or a JavaScript standard document that explicitly declares or defines how something needs to be structured and which element can follow on which other element and so on. But for more loose content, it’s extremely difficult and good for an author to distinguish that.

And this is why I also say there’s no danger that human writers or content producers will get jobless because of such an engine. No, the role will change. Maybe we use these engines more to generate content, but we as authors become more the reviewer and the editor of that content. It’s a little bit like machine translation where you had a machine translation engine translate your content, but then you need to do post-editing to make sure that this content and the translation is really correct and that the correct terms are used and so on. And we will see a similar development with gen AI for text-based content for sure in the future when it comes to all kinds of content production, maybe technical documentation, maybe knowledge bases, et cetera.

SO: So then can you talk a little bit about the issues around bias and the ethics of using AI and where that leads you?

SG: An AI engine like ChatGPT, for example, is of course trying to create unbiased content, but we were talking about that. I don’t have an example for that, for written content now, but we were talking about that example from the lady who was giving a photo of herself and then aSOed then the generative AI engine, “Please make me a professional headshot photo for an interview letter.” And it created a nice photo with nicely made-up hair and some nice dress and so on with a nice background and looked very professional, like a professional headshot from a professional photographer. The only problem was that this photo was showing a person with blue eyes and blonde hair while the person who provided the original photo to be beautified was an Asian person with a different look.

And that brings that discussion of the bias of an engine. Maybe it was feeded and trained with 5 million photos of professional business people photos from a Caucasian background and maybe just 1 million photos from an Asian background and maybe even less from an Indian background or whatever. And then this engine is making statistical calculations and says, “You want to turn that into professional business photo? Based on my training set, my training data set, I will make you a Caucasian-looking person.” And that is a huge problem.

And this is where this governance of AI generated content will maybe even become a full job one day where we say we need to make sure that the content that an AI engine is generating is really appropriate and culturally sensitive and is not biased and taking all kinds of other factors into consideration, and maybe an AI engine is not yet able to do that.

SO: Yeah. So the question of what goes into the training set is really interesting because of course, it is a little unfair to blame the AI, right? The AI is, in its training sets, reflecting the bias that exists out in the world because that’s what got fed into it.

And I don’t want to go down the rabbit hole that is deep fake videos and synthetic audio, but I will point out that just earlier this week, I saw a really, really interesting example of an engine where somebody took a video of themselves speaking in English and talking about something. Actually, they were sort of saying, “Hey, I’m testing this out. Let’s see what happens.” And then the AI processed what they said, translated it and regenerated the video with them speaking first French and then German.

And so it was, I don’t want to say live video, it was synthetic video of a person who spoke in one language and who was then transformed into that same person speaking fluently in their voice in a different language that they do not in fact speak because the content was machine-translated, and then they used the synthetic audio and video on top of that to generate it.

I mean, my French isn’t very good. It sounded plausible. The German sounded fine. I heard one mistake, but he sounded like a fluent German speaker, and there wasn’t any obvious weird rearrangement. They somehow matched it onto there. It was quite impressive and it was fun to watch. And then you think about it for a split second, and you realize that this could be used in many different ways, some of which are good and some of which are not.

SG: Yeah. I mean, we had some really ugly examples here in Germany where some political party was using gen AI photos to transport a certain political message, and then it came out that these photos were not from actual events that they were claiming it would be, but were AI-generated.

So there’s a lot of danger in there, and we will also need to adapt as societies and human beings to get a better find feeling what is generated content and what’s not? That will become increasingly difficult, but at least developing the awareness that what we get presented as content, especially when it comes to images, that we’ll need to develop stronger than ever before. Photoshop is there for a long time. We all know that photos can be Photoshopped, but with this new approach of generative AI that this awareness becomes even more important.

But when we talk about ethics, I know we are running a little bit over time probably, but there’s another aspect in ethics that I see as something we need to discuss in more detail in the future. We feed the engines with content, existing content, and maybe it’s content that is even intellectual property of someone. And then this engine produces new content that is leveraging the knowledge of that, that is in that content, to produce new content. And then something, especially in the context of university content, research content and so on, who’s the owner of that content that is newly created? And whose intellectual property is it? And what is, if content is generated that is very clearly rephrased of existing content from some content that is maybe protected by licenses or so?

So there’s also this ethical discussion that we need to have and that will for sure maybe even need some regulation on the government level in the future.

SO: Right. And the answer right now, at least in the US is that if the content was generated by a machine, you cannot copyright it. That implies that if I feed a bunch of copyrighted content into the machine and produce something new out of the machine, that I have essentially just stripped the copyright off of the new thing, even if it’s a summary of the old thing or a down-sampling or a gisting of the old thing, the new thing is not subject to copyright unless there is significant human intervention.

So yeah, I think that’s a really good point because there’s a big riSO there. And there’s also the issue of credit. I mean, if I just take your content and say it’s mine, that’s plagiarism, but if I run it through an AI engine and plagiarize from millions of people, then it’s suddenly okay. That seems not quite right. Okay, so yes, tell us-

SG: A plagiarism engine that checks the content is probably very useful in the future, yeah.

SO: Yep. So lots of things to look out for. And I think it sounds as though, from what you’re saying, you see a lot of potential benefits in terms of using AI as a tool for efficiency and recombination of content.

So if you join me in, I’ve already moved on apparently to DITAWORLD 2024, so if you look ahead a year or so, what do you see as the opportunity here? How are companies going to benefit from doing this, and what kinds of things do you think will be adopted the fastest?

SG: I think coming back to the beginning basically, these two areas of authoring and authoring content, content creation and content consumption, and these are the two fields where companies can benefit and will benefit from the near future as soon as enough of these new features will have found their way into the tools themselves.

Faster content production is definitely one part, but that also means that authors need to learn how to create content with AI engines, the art of prompting as a keyword here, and to detect the voice and tone of generated content. It’s relatively easy after a while to identify, oh, this content was written by ChatGPT, for example, because the standard way ChatGPT is generating content is sort of always the same, and you can easily identify it after a while. This will give some job changes and means that companies will need to adapt to that before they can really benefit from it.

People, authors, and content creators need to learn how to get the right content out of an engine, out of prompting, prompt engineering, how to write proper prompts, and that will take some time and trainings and so on, but then it’ll really speed up the content production process a lot. And the second benefit is then with the content consumption, providing just better customer experiences by having more intelligent chatbots that provide better answers, right-fitting answers, maybe assisting users of a long blog post on a website with giving a small summary of that and things like that.

So there will be many benefits for companies using AI, just only when it comes to this specific area of content, knowledge content, but there will be other areas of course as well, financials, detecting patterns in financial data, and so on, for research and so on. There will be a lot of benefits, but when we talk about content, the content we are talking about here today, there will be mostly the biggest benefits will be probably content production, which also includes, for example, translation.

SO: Yeah, I think I agree with that, and that sounds like a relatively optimistic note to wrap things up on. Stefan, thank you so much for all of your perspectives on this. You’ve obviously thought about this carefully and you’re sitting inside an organization at Adobe that is actually building out some tools that are related to this, and I’ll be interested to see what comes out.

Tying back to that, the DITAWORLD 2023 recordings are available, and we’ll put those in the show notes. There were a couple of presentations in there, this was back in May, June, that addressed the state of AI and some of these similar kinds of considerations along with that. I’m not sure if it was exactly a demo, but there was a discussion of what the AEM Guides team is thinking about in terms of product support. So we’ll make sure to get that into the show notes.

Scriptorium has a white paper on AI and we’ll drop that in there, and then I think there will be more discussion about this going forward. So thank you again for being here, and we’ll look forward to hearing more from you.

SG: Thank you.

SO: And with that, thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Applications of AI for knowledge content with guest Stefan Gentz (podcast) appeared first on Scriptorium.

“Rather than applying for a job […] you want companies to come to you and say, ‘Hey, will you come work for us?’ The only way they’re going to do that is if you write articles, if you’re speaking at conferences, and if you position yourself as an expert in your field.”

— Jack Molisani

Related links:

• ProSpring Technical Staffing
• Beating the dreaded applicant tracking system – PDF
• Molisani – Intercom – Beating the Dreaded ATS – PDF
• Register for LavaCon on the conference website. Use the code Scriptorium to get $300 off.
• Contact Scriptorium to schedule a private meeting with us during LavaCon

LinkedIn:

• Jack Molisani
• Bill Swallow

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Bill Swallow: Welcome to The Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re talking with the president of ProSpring Technical Staffing, and executive director of the LavaCon Conference, Jack Molisani, about how content roles have changed over the last year and what you should do now to advance your career in content. Hi everyone. I’m Bill Swallow.

Jack Molisani: And I’m Jack Molisani.

BS: Jack, lovely to have you here again.

JM: Always a pleasure.

BS: So I guess let’s just get right into it. You’ve seen things from both angles, from a conference organizer doing content conferences and also with running a staffing agency for content people. How have roles changed over the past year or so?

JM: What’s really been amazing over this past year, we’ve seen mass resignations, tech layoffs, quiet quitting, all at the same time. Never seen that before.

BS: That’s crazy. So do we know what’s contributing to that?

JM: Let’s take each one in turn. I do believe that a lot of companies did layoffs in the first quarter because they over-hired during the pandemic. Right. So everyone said, oh my God, Oracle’s laying off 10,000 people. Well, they hired 40,000 during the pandemic, so there’s still a net gain of 30,000 jobs. I also believe that a lot of tech companies or companies in general were worried about a recession and they started trimming the fat off their payrolls in advance. But here’s the deal. I believe that if enough companies start laying off out of fear of recession, they’re going to cause the very recession they were afraid was coming.

BS: It’s funny how that works.

JM: Yeah. And then with the great resignation, I think companies did so much with so little for so long that people just got tired of it. And once companies started hiring again, even with the tech layoffs, companies are still hiring that they said, the heck with this, I’m jumping ship. I’m finding something a little more work-life balance in addition to compensation. But really it’s the work-life balance that I’ve been seeing people changing because of.

BS: So does that mean it’s also a factor as far as the quiet quitting is concerned?

JM: That’s a little different. Yes, and because the fear of recession applied to candidates just as much as it did to companies. So maybe people are tired of where they’re working, tired of being abused, but instead of just quitting and finding a new job, they just say, the heck with it, I’m going to do the absolute minimum possible without getting fired. And that’s where the quiet quitting came through. And I did some research on this and there’s actually top five reasons why people did quiet quitting. Would you like to hear them?

BS: Sure.

JM: One, toxic work culture. Right. And now I have the pleasure of having a really great team on my company, as do you.

BS: Absolutely.

JM: And I personally have never experienced a toxic work culture, but I’ve heard many, many stories from people who have. Two is job insecurity and reorganization. With every acquisition and reorg comes the possibility that you’re going to lose your job. So people are being proactive and resigning. High levels of innovation, I thought was an interesting reason why people changed jobs, not just quite quitting, but also great resignation. Because if you’re constantly doing something new and companies are, what’s the word I’m searching for? Demanding shorter development types. Produce, produce, release, release, release. Do you remember the good old days when we released software once a year?

BS: I do remember those.

JM: Right. I know we both have a little gray in our temples or in our beards in our case. But yeah, now they’re innovating, release, release, release. And that gets tiresome. Four was failure to recognize performance. How many times have we heard technical communicators complain because they’re not recognized for all the work they do. And part of my response to that is, are you letting people know how good of work you’re doing? Are you doing a corporate newsletter for your department? Are you letting people know how much you just saved the company? That’s another whole podcast. And this was fifth, was poor response to COVID-19. I still know companies who, managers who are insecure managing a younger workforce want to see people in their chairs and personally,

BS: Yeah. Butts in seats.

JM: Yep. Butts in seats. And I tell my people, I don’t care where you work, when you work, how you work, as long as you get your work done. Right. If you can do that at home in your pajamas at two o’clock in the morning, you go.

BS: Just be on that call later this afternoon.

JM: Exactly.

BS: Yeah. No, I hear that. So I guess we’ve talked a little bit about the negative trend that we’ve saw with resignations, quiet quittings and general layoffs. As far as the roles that we’re seeing out there now, how are they starting to differ from what we’ve seen let’s say, let’s even go back a few more years. So pre-pandemic versus post pandemic. What are we kind of seeing here as far as the roles, as far as content development, content ops, anything new and exciting going on there?

JM: I’ll start with a happy news that we did not see the mass migration of jobs to India and other countries that people were fearing or they left and came back, right? So yes, you might be able to get a cheaper writer strategist, UI designer elsewhere, but if it takes them five times as long and it’s half as good, you’re really not saving money. So I did see a return of jobs since this, we’re both based in the United States. I’ve got a US-centric viewpoint on this, is that I did see jobs come back to the US. I’ve seen both more and less specialization at the same time. Used to be you’d see a job opening and say technical write needed, must have FrameMaker and RoboHelp. Where now it’s like, all right, yes, we want someone who does structured offering. We don’t care which tool. Because really once you’ve got the concept of structured authoring down, it doesn’t matter what content management system or structured authoring development tool you’re using. Because if you know one, you can pick up the others.

BS: Right.

JM: Now that said, a majority of the world is still not doing structured authoring, but I see that as you asked what trends are happening, that is definitely a trend where people who are hiring are looking forward, and even if they’re not doing structure authoring now, they’re looking ahead. So if they’re going to hire someone and they get that few precious headcounts, they’re going to make sure that person that they do hire is prepared to move forward and know what’s on the horizon coming down the pipe.

BS: Gotcha. So as far as things on the horizon or coming down the pipe are actually being forced through the pipe as we speak. Let’s talk a little bit about AI and,

JM: Oh, let’s not.

BS: Its impact.

JM: Okay, so I’ve got two,

BS: I have my own thoughts on this as well, but let’s go. Let’s hear from you.

JM: I have two completely divergent views on AI, maybe three on a good day. One, I think there’s very, very valid uses of AI. For example, 23andMe, we now have millions of people who’ve mapped their genomes. Take 20,000 people who have male pattern baldness and 20,000 who don’t. Give it to an AI and say, find the difference in the genomes. Brilliant use of AI. All right. Now, how do we apply that as technical communicators or content strategists? Right. I saw a chapter, did a presentation on AI for technical writers, and the first thing the speaker said is, I’m not a technical writer and I’m using AI to come up with ideas for blogs on LinkedIn. What?

Now that said, I can see a valid use for AI in content development. For example, you’re doing structured all three. You just wrote 100 topics. Ask the AI to populate your meta tags for you, or here’s a CMS with 400 topics. Read them all, find out which ones are sufficiently similar that we could combine them and reuse, cut down our translation costs, cut down our maintenance costs. Brilliant use of AI. None of the tools are there yet though.

BS: No.

JM: Right.

BS: No.

JM: So I see value, but here’s another thing. I just saw another blog on LinkedIn the other day going, AI is going to increase your efficiency. That is the main thing we’re going to save money is by increasing efficiency. And my thought is I’m documenting a new printer from Canon or Epson or Kodak, how is that going to help me talk to a subject matter expert about how do I maintain this thing? Right. And I distinctly remember doing maintenance documentation on an LCD projector and discovered that if you didn’t put your finger down on the screw as you unscrewed it, the spring would go spring and the screw would go flying across the room. And the only way you know that is by doing it.

BS: Yep.

JM: And I believe that we as technical profession document things that don’t exist yet. That is our reason for existence and how are you going to get that to an AI?

BS: Yeah, I think we’re on the same wavelength here because I take a similar approach where I don’t consider AI as being a valid content generation tool for technical content, but I see it as being useful. One, behind the scenes. So facilitating, like you said, facilitating search, coming up with keywords. So if you need to do any kind of SEO prep for content, being able to spider that, look against your other content, find a good keyword or a key phrase that’s going to work to make this stand out. Yeah, certainly aid in populating search for content that’s going out to the web, but I don’t really see it in a, it’s going to write these procedures for you because exactly, you need that level of preciseness on things that maybe aren’t yet documented. So it doesn’t have anything to rely on to explain it. So that’s interesting.

JM: Your audience has not been able to see me nodding my head during your entire answer. Another thing I want to comment on, I think people are grossly overusing the term AI. I was just speaking with a vendor yesterday about their system that’s supposed to be AI-enabled and a structured authoring system. And I said, well give me an example of the AI that you’ve added. And she goes, well, it will create a table for you. I go, that’s not AI, that’s a wizard. And we’ve had them for decades and she was the marketing person. So when I really pressed her on what part of that was artificial intelligence, she couldn’t answer me. She goes, I’ll let you talk to the engineer.

So I think there’s a lot of buzzwords going on and a lot of people talking about something they don’t deeply understand and they’re just using AI because it’s popular now. Now one more thing I want to add, if you remember, okay, we mentioned LavaCon, which is a conference on content strategy. Was it four years ago? Everybody was talking about chatbots. Oh my gosh, chatbots are going to be the next delivery platform. Everyone’s got to structure their content for chatbots. Next year, crickets. I have to say, from my little perch looking, my little crystal ball on where the industry is going, I said, oh no, this is going to be a flash in the pan. And I kind of feel the same way about AI at the moment.

BS: Yeah, I think it has a little bit more staying power because it’s more than just a delivery format. But I think that what we’re talking about with regard to AI now is probably not what we’re going to be talking about with regard to AI next year, five years later. It’s going to be a very different beast and it’s going to have some very different applications that I think what we’re seeing now, most people now are looking at it and saying, oh yeah, this is something that will generate a few paragraphs for me. And we’re talking about ChatGPT here. But there are other things where we’ve got cases where you can create artwork and such with AI as well. But again, it’s just pulling a bunch of different representations together and smoothing the edges and saying, ta-da. Whether it’s good or not is of course in the eye of the beholder because the AI doesn’t know what’s good or bad, it’s just going to do what you told it to.

JM: Agreed. The other thing that concerns me about AI is hallucinations.

BS: Yes.

JM: I ran ChatGPT and asked it to create tweets for all my speakers, and one of the tweets was about someone who’s not even speaking at the conference. A friend of mine had an AI write her bio and it said that she had a PhD in mathematics when she didn’t.

BS: Oh, I have a PhD as well, in case you didn’t know.

JM: So yeah, so,

BS: And I don’t. I don’t.

JM: But however, that’s creating a whole new job is fact-checking and editing the content that an AI… Now let me add one more thing. We’ll go on to the next question. Is that another valid use of AI that I thought was really clever was one of the banks would write an article and then run it through an AI and said, rephrase this as a CFO would want to read it in the terminology that CFO understands. Rewrite this in terms of how a financial analyst would want to read it. Rewrite this as how a consumer would want to read it. I thought that was brilliant use, again, not generating it from scratch, but taking an existing dataset and transforming it for a target audience.

BS: That’s an interesting perspective. Okay, so we talked a lot about AI. We talked a bit about people starting to look for less on tools experience and more on structured authoring and more, I’d say non tool specific skills. So what other trends are you seeing with companies looking to hire content professionals? Are there any other things that they’re looking for? And what can people do, I guess, to start sprucing up their resume and their experience to look for that next big gig?

JM: So my answer to this is going to be completely non sequitur and you’re not going to see it coming. Are you ready?

BS: Alrighty, let’s hear it.

JM: Take a class at improv.

BS: Improv.

JM: Improv comedy. I’ve studied improv, I’ve taught a workshop on it at the ESTC summit. Interesting thing about improv. I’ve heard people tell me, oh, I could never think fast enough to do improv, which is interesting because the first thing they teach you in improv is to stop thinking and start listening. Right. So one of the things that I discovered after taking a class at improv, I’ve never been thrown off by a question I wasn’t anticipating because part of the whole concept of improv is yes and. You take whatever your partner, boss, whoever gives you and go, yes and, and add to it. Right. And that’s also a great way, if there’s someone on your team that you don’t like their idea, you go, oh, yes and we can also do this. Right. And without just saying, oh, that’s the stupidest thing I’ve ever heard. That and take a class on public speaking, like at Toastmasters.

Even though a lot of the work we’re doing is remote, I see that 100% remote is probably going to start whittling down. And we’re going to have to either one, come back to the office occasionally or to be visible, right? Speak at conferences, speak at meetups, speak at your local STC chapter, right? Because rather than you applying for a job, and we’ll come back to applicant tracking systems in a second, write that down, that you want companies to come to you, say hey, will you come work for us? And the only way they’re going to do that is if you write articles, if you’re speaking at conferences, if you position yourself as a expert in your field.

BS: So raise your own profile, I guess, out there, LinkedIn, whatever, and build those skills to start putting yourself out there a little bit more.

JM: Oh my gosh, I cannot go on LinkedIn a week without seeing a blog post from Bill Swallow unless that’s AI generated and I should not be impressed.

BS: Oh, I don’t know.

JM: Okay. So I mentioned applicant tracking systems.

BS: Yes.

JM: Real briefly, and I actually have an article and a whole presentation on this that if you want to send that out in aligner notes at the end, we can do that. Real quick. When you apply for a job through a website, it goes through an applicant tracking system. And originally that was just a way to actually track where you are in the system. Well, with the advent of things like Indeed for mobile where you can create a profile and every time you see a tech writer job or a content job, you go apply, apply, apply, apply, apply, apply. So suddenly companies are getting hundreds of resumes that are not even remotely qualified. So again, added artificial intelligence into their applicant tracking systems to weed you out. So 99% of the applications that you submit will never be seen by a person. Right. Because not only are they comparing your resume to see if it matches the job requirements, they’re taking your resume to see if it matches the job description. Right.

So the first thing I tell people, stop applying for jobs through websites. Go to LinkedIn, find somebody who works there, even if it’s a recruiter, because every single recruiter has a LinkedIn profile and say, Hey, I see you have an opening for X, Y, Z. May I send you my resume? They’ll do one of two things. They’ll go, sure, send it over. Or they’ll go, no, go ahead, apply online and I’ll keep an eye open for the application. But now you have a human that can fish your resume out of the spam folder because you are qualified for that job. So that’s another thing I’ve seen change over the past few years, is just an explosion of AI applicant tracking systems weeding people out. In fact, I personally know five people that got jobs from personal referrals last year, and they did not get a single interview applying through jobs, through websites. So again, work your professional network.

BS: Sound advice. I will actually echo on that resume spambot approach to responding to job postings. A few years ago, I actually posted a job for a content, well, not a content developer, but a developer of content systems. So basically I did a plugin developer and I made the mistake of including Java as a desired skill, and I actually got several resumes for baristas come in.

JM: Oh, yes, yes. Absolutely. Yes. Yeah.

BS: And I was looking to see if there was anything, I mean, it piqued my interest because I had to look and see if there was anything in there that indicated that these people were interested in moving into some kind of a development role. And it’s like, no, no, they’re just interested in making really good coffee, which is fine, but it’s not what I’m looking for. Although I’d love the coffee.

JM: And I don’t even think that. I think they now have AIs where you could go, anytime a job opens that matches my resume, submit me. So you’re not even saying apply, apply, apply anymore. It’s the AI automatically submitting to a job that you’re not qualified and AI automatically rejecting you. Madness.

BS: So the computers are taking over.

JM: Yeah, Skynet.

BS: Excellent. Well, I think this is a good place to leave things, Jack. Thank you very much for talking, and actually, I’ll give you a moment to kind of plug LavaCon since that’s coming up as well.

JM: Oh, thank you. So this is our 21st year. We’ve survived two recessions and a .com crash. It’s the LavaCon Conference on Content Strategy. We do have a track on integrating AI into your content strategy, more specifically the benefits and liabilities of integrating AI into your content strategy. But it still covers content strategy and user experience. We’re going to be in San Diego in October. We have a discount code for your listeners. Anybody who registers using Scriptorium as a referral code gets $300 off registration, and it’s at lavacon.org.

BS: Excellent. Jack, always a pleasure.

JM: Thank you for having me.

BS: Thank you for listening to The Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Adapt to evolving content careers with guest Jack Molisani (podcast) appeared first on Scriptorium.

“There’s a valid use case for almost every approach that’s out there. There’s no way around that. I think what it really starts to come down to is making sure that you’re matching the 18+ months [ahead] to the decision you’re making now.”

— Patrick Bosek

Related links:

• Heretto.com
• Demystifying content modeling
• Is Content as a Service right for you?
• LearningDITA—self-paced, online DITA training

LinkedIn:

• Patrick Bosek
• Alan Pringle

Transcript:

Alan Pringle: Welcome to The Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about choosing a content model and the pros and cons of customizing it with Patrick Bosek of Heretto. Hey everybody, I am Alan Pringle, and today we have a special guest. It’s Patrick Bosek of Heretto. How are you, Patrick?

Patrick Bosek: I’m good. How are you, Alan?

AP: Good. Let’s talk a little bit about content models today, and let’s start really at the beginning, choosing one, do you pick a standard? Do you create your own? What do you do?

PB: I guess if you’re looking for my advice, which I suppose you are since I’m on this podcast.

AP: Correct.

PB: It’s obviously use-case specific, everybody goes into the process of creating a content model and the first step they look at is like, “What do we need this thing to do?” Well, not everybody, let me back up. People who make good decisions when choosing a content model start with deciding what they need it to do in the long run. And I think the thing that I’ve seen here over the what? 15 plus years that I’ve been working in this industry, is really that there are organizations which somebody chooses a content model, because they think it’s cool and it works for what they’re doing right now. And then there are organizations that look at the total scope of what they’re going to need to do both in their group and then probably beyond their group for the organization long run. And then they embark on a much more formalized process for choosing a content model.

Very often you’ll see that where you start, how you start is pretty impactful on what you choose. It’s not real common that the very iterative approach, it’s almost an Agile approach in a lot of ways, like, “Oh, this works for this, let’s move it forward and we’ll do it this way, this way, this way.” And it’s very iterative. Does that lead people or land people on structured content? Typically, that lands people on either proprietary tool sets that are built on whatever’s in their proprietary tool set. There’s a lot of wikis out there that have their own set of structure in the background, it could be either text-based or it could be HTML based. MadCap’s got their own proprietary standard. There’s a few other tools that are built on standards which are standards but proprietary.

But I think those are even probably more on the side of things that are intentionally selected. Very rarely do you see an organization that takes this iterative path go into it and then choose something which is structured, because that stuff is typically less available to just put your hands on and just start creating something that you can then spit out a PDF or spit out a website. I think that knowing how it is that you’re going to start and knowing what set of problems and what the time horizon you’re trying to cover are, that’s like getting ready to get ready to choose your standard if choosing your standard is your first step. And I think that knowing where you are there is really critical, how is it that we’re making this choice?

AP: No. And I think you’re right. This is like any kind of business decision, you’ve got to think about what your requirements are and it is not a situation where you were looking at or I would prefer that people not look at the next three to six months. Yes, you may be on fire and have something to do, but you’ve got to be careful and balance things out and think, “Are we going to go with something that’s much narrow and very focused on one use case? Are we going to go a little wider and accommodate things that might be say 18 months, two years down the road?” For example.

PB: Yeah. I think that’s fair. I think the thing I would add to that is that, there’s a valid use case for almost every approach that’s out there. There’s no way around that. I think what it really starts to come down to is making sure that you’re matching the 18 plus months to the decision you’re making. And so I’ll give you a really good example, I think it’s a really good example anyways, so if you’re just writing a README file for a microservice that you’re setting up and it’s going to be maintained with a code and nobody’s really going to be referencing it, who doesn’t actually have their hands on the code, using true structured content for that makes no sense.

AP: It’s overkill. 100%, yes.

PB: Yeah. And it doesn’t really integrate well with the delivery or with the end user. It would be a bad experience all around. That makes a ton of sense to just use what is supported by the repository that you’re putting that into, which is by and large, it’s either GitHub or Bitbucket or the other one, GitLab, so it’s one of those three, but they all support some Markdown. README files, by and large, if you’re choosing something other than Markdown, you should have a really special case. On the other end of the spectrum though, if you’re thinking about, “Okay, this is going to result in a large set of content, which is intertwined and pieces of it and move at different speeds throughout time and different audiences access it in different ways and potentially get different pieces of content based on who they are,” at that point in time, you can’t do that with Markdown without doing a lot of custom stuff.

AP: I was going to, say there’s some people who might tell you that you can do that, but I’m pretty sure you should not. How’s that?

PB: Okay, fair. That’s an important distinction. You shouldn’t do that with Markdown. This is a tangent, but I love tangents. I was looking through the software documentation, I can’t remember which company it was, it might’ve actually been one of the Git providers, and they’re still in Markdown with a lot of their content. But they’ve gone so far with pieces of this to customize it for this platform or this audience or that, they don’t have tags in there, but they have things that are tags in there. I think they’re square brackets with a percent sign or something, and then a name after it, and then an end one too. And I’m like, “These are just tags.”

The thing is, once you get to a certain level of sophistication with effectively having to put metadata in your content to tell your content how to behave in different circumstances or to just expose information to other systems like search systems or AI systems or whatever it may be that isn’t the same information you’re exposing to the end user, you have to do it with tags. There’s no other way to do it, because all tags are as a way of putting information into a document that isn’t rendered directly to the user.

AP: Yes. You’re adding intelligence into your content.

PB: You may not like angle brackets, but if you have this case, you’re going to use some kind of tag at some point. And this actually relates in a funny way, I’ll stop my tangent in a second, to another conversation I had, I promise, to another conversation I had with one of DITA’s founding fathers, or one of the longest standing people on the TC, Eliot Kimber, which you know and I’m sure everybody who’s listening to this are going to know. And I love challenging him with stuff, because he has such good answers to everything.

And so I thought I would play devil’s advocate and be like, “Well, why not use a text based format? Why not use Markdown?” And we started going through some stuff and he was like, “Well, why not use DITA if you have all those cases, if you’re going to do all this stuff, if you can do all this stuff, why wouldn’t you just get that out of the box? At what point does it make any sense to ask the question, why not use Markdown plus this, plus this, plus this, plus this, plus this?” And all you’re doing is rebuilding DITA, which frankly is probably my position, not probably, it is my position anyways. But it was interesting to watch how Eliot got there and the way that he positioned it was so very Eliot and it was… I don’t know. I loved it.

AP: At some point, if you start with something maybe a little more boxed in, that’s not a technical term and you keep having to add things to it to do what you need to do, and that happens a lot, that may tell you you’re possibly a little too constrained, perhaps.

PB: Well, I don’t know if I would use the term boxed in, because I think boxed in, implies a structured starting point that has limits around you. Whereas I think the reality is that, especially a lot of the text-based formats, they’re so open, there’s no standard. There’s general accepted practices if you want to call them that, you can put anything you want in there and you can build a processor that processes it, literally anything. And I’ve seen so many bespoke things put into these formats over the years, that you realize that there is no box and you can do whatever you want with them, which in some ways is the beauty of them. But as you scale, more people have more ideas and there’s no box, so they can add whatever they want and they can add onto the processor. And then some of those people go to other places and some people didn’t document what they did and they forget why they did it and blah, blah, blah, blah, blah. And you have system creep. And the problem is, the system creep is built into your fundamental content structure.

AP: Your choice is enabling what you just said. Exactly.

PB: Right. That aspect, the fact that there’s no separation of concerns there, when you’re building this stuff directly into custom stuff, directly into your core content in a way which isn’t patterned and isn’t based on a larger set of standards and rules, means that you’re evolving something which is innately going to become brittle eventually.

AP: Sure. And as you add business requirements, that brittleness that you’re talking about can become basically magnified from my point of view, say for example, you have a merger and you’ve got two companies doing similar things, yet they’ve got two entirely different content models, two entirely different tool chains, at the end of the day, are you going to keep both of those things? I’m going to guess not. At that point, you’re going to have to go through a process of figuring out what you’re going to do. Is it going to be survival of the fittest? Are you going to do some bake off? Are you going to have someone come in maybe and take a look and say, “What should we pick?” There’s some options there.

PB: And so the merger is a great example, and it’s a clear vision of when two different content infrastructures are going to collide and something’s going to have to win. But I almost think that the merger, people tend to feel like it’s really distant. Nobody goes into work every day and thinks about mergers except bankers.

AP: The people who make the money from them.

PB: Right. But people in tech pubs, they don’t think about the merger until it hits them. But the thing that isn’t distant is product evolution. And a lot of products will… You’ll start a new project, and this will be its own product maybe, and it’ll build up, build up, build up, build up, and then you’ll realize it needs to be merged into this other thing. Or it can go the other way, where you’ll start this module in the product and it will build up, build up, build up, and you’ll realize, “Oh, it needs to be separated out.” And these are mini mergers.

AP: Yeah. Absolutely. Internal mergers.

PB: Totally. And the thing that you’ll see here is that, when you’re keeping content isolated into the product and it doesn’t have this box, so there’s no standard rules that go across all the different products, that when you have to bring them back together, maybe somebody in this product team decided, “Oh, we’re going to add this MDX component or this thing or this thing,” and then it doesn’t work now. Or it could conflict with this other version of that to somebody that was very similar, because they’re not talking to each other, because they’re not on the same product team. And that can become a fundamental problem. And then even beyond that, the thing is, while those are two separate things, you’re still one company.

AP:

Yes. Siloed tech stacks, essentially, more or less content tech stacks.

PB: And siloed user experiences. You go to the documentation for this product or module or whatever it may be, and it’s got this structure and this interactivity and it looks like this. And you go to this other one and it’s like, “Oh, okay, well this is same colors but functions very differently, navigation, all this stuff is just separate.” I think this element of consistency, when you don’t have accepted standards across the organization, it shows up. It shows up in efficiency, it shows up in user experience, and both in the customer and the employee side.

AP: The customers do not get a consistent experience, they don’t get consistent messaging. And I’m sure the marketing folks will be really happy about that when you are basically giving two different flavors, yet you’re the same company.

PB: Totally. Well, two is probably a best case scenario.

AP: Indeed.

PB: I think it might be more like 40 in some cases.

AP: If what I’m hearing from you should thinking bigger, always be in your mind when you’re talking about modeling then? Or is that unfair?

PB: Okay. I guess we’re returning to the question, choosing a content standard or a content content model. I think being aware is what’s important. I think most organizations have a general concept of trajectory, what things look like, what the culture of the organization is going to look like. And not everybody needs scale, not everybody needs consistency across many parties because they’re just never going to be there. There’s plenty of hardware companies, software companies, any kind of company out there that’s just never going to have more than three writers. That is a situation. And in those cases, do you really have to think bigger? No, probably not. Should you? I guess that’s a different question.

AP: It’s a balancing act. I think that’s the best way I would put it. You’re right, with three writers, if you’ve got three content creators that presents a different set of challenges, problems that you need to solve versus having a team of three digits. It’s a completely different beast. It is.

PB: Totally. The reality is that you can get to know two other people very, very well and you can read all their stuff and just by the nature of that, you can stay in the same page.

AP: And then of course, the consultant in me says that group of three, what if your company takes off and you have all this growth that three could become nine or it could become 12 or it could become 15. You never know.

PB: Yeah, for sure. That’s the big question that I think that organizations have to wrestle with. If you know that growth is coming, in my view, it’s irresponsible not to choose something that will facilitate that growth. But if you don’t think that growth is coming or it’s not on the horizon, it might be the responsible thing to choose whatever is going to work with relatively low implementation friction and a good customer experience for your small group at that time. And then once you start to see that growth coming, be proactive in terms of transitioning to something which is going to support that growth.

AP: And that comes to a point I want to make here. If you do decide that a, let’s say smaller, and I don’t mean that in a pejorative way, a smaller solution, smaller scale solution, if you do go that route because it’s a good fit, I would suggest you have your eye on an exit strategy then and there when you make that choice, think about your exit strategy, where you might need to go next and think about how you could map where you are now to the new thing. Does it have to happen immediately? No. But I would recommend that you have that in the back of your head filed away because you may need it sooner than you think.

PB: Totally. I think that’s absolutely fair. The reality is that, when you’re trying to do complex content at scale and choose your axes that you want to put complex on, so it could be personalization, it could be multi versions, it could be multilingual, I could continue going, there’s all these different ways that content can become more of a complex, regional is a great example, this content applies to this region versus this region, which again, it’s personalization, but it’s a special form. When you’re in that circumstance, you really have to choose something that’s going to support that. And that doesn’t really matter if you’re one or 100 authors. You need to recognize that that’s your circumstance, where it’s like, “Okay, we’re going to have a personalization requirement.” Or, “We’re going to have a complex versioning requirement.” Or, “We’re just going to have so much content that isn’t highly isolated, especially content writer ratio or highly collaborative, that we need structure to support that.”

Think in the physical world, why do skyscrapers have more structure underneath them than houses? It’s because they need to be bigger. And so when you know that you have these situations, you have to match your content model selection to those things. And so when you’re starting to think about like, “Okay, what content model is going to do that?” Unless you’ve got a really specialized case or you’re in an industry that’s had a content model specifically built for them, aerospace is the one people throw around a lot.

AP: JATS for technical journals, things like that.

PB: JATS for journals. That’s a great one. The reality is that DITA is the gold standard for that stuff. DITA teams three to 300, they’re highly performant when they’re well-trained and they can build anything to any size you need in terms of content. There isn’t an upper limit for good DITA implementations. And part of that is, one of the words we said we weren’t going to say today, but it’s the ability to specialize DITA. That’s DITA’s secret sauce that I think a lot of people don’t realize how important it is. And this ability to extend the DITA without breaking what you’re currently doing is enormous. The business value there is beyond.

AP: Just to give people some context, before we got started, we were talking about not trying to go too deep down the whole DITA specialization path and what it is. And just for a quick, quick like 10,000 foot summary of it, specialization is a way that you take existing elements that are in the DITA standard and you basically build new structures based on things that are already in the standard. And that’s how you customize. And that is probably an oversimplification, but I want to throw that out there for people who were not familiar with the term. It is just a fancy way in DITA speak of saying customize the DITA model.

PB: There’s one key thing there, and this is the only thing I think you really need to know about specialization. One key thing you didn’t mention, which is that when you take an element in DITA and you specialize it, all of the DITA processors, understand your new element to be a version of your old element. It’s like, “Why does that matter?” Well, that matters because if we have a Scriptorium content model and in our thousand person Scriptorium company, someone named Tony goes and decides that they’re going to add this new functionality and it needs this new structure, they specialize off of the base content model. Even if that content comes back into reuse in other parts of the organization that haven’t implemented specific functionality for Tony’s new element, because those elements are derivatives of the underlying elements, they just get treated that way. You can have structured planned, asynchronous evolution of the model across a large enterprise that doesn’t break all the different delivery mechanisms that are based on the fundamental cross enterprise understanding of the model. That thing there, that’s what makes DITA enterprise grade and everything else not.

AP: Absolutely. To say that it puts the extensible and XML, even though I know I’m mixing DITA and XML here. It is super, super extensible. And it really to me, people talk about should, “I pick an open standard like DITA or should I do a custom model?” Well, from my point of view, you can have both based on the discussion that we’re having. That’s where my brain is going right now. I will say X years ago, actually X decades ago, I remember creating custom models mostly in SGML. There was no standard out there to support what we were trying to do. 20, 25 years later, we have DITA, which if that were available when I was creating those models nearly 30 years ago, you better believe we probably would’ve picked it, because it probably did 85, 90% of what we needed the custom model we created to do, so it takes care of that problem. And as you said, you can customize it without breaking the bigger picture. And that’s a big deal. That’s a really big deal.

PB: Yeah. It’s enormous. It is the business case for why you go through the upfront implementation to do DITA, because you look at content operations implementations that have been around and are still modern and are still delivering an ROI year-over-year, and they’ve been around for a decade or more, they’re all DITA, every single one of them. There’s no such thing as the 15-year-old Markdown implementation. It’s the same thing as with the wikis, they go through cycles. If you want something that’s going to serve you today and then in the long run and you have the ability to do the upfront, it’s going to work. Going back to your SGML comment, I think one of the best ways that DITA was ever positioned to me, this goes back a long ways, this is a friend of mine, he basically said, “The reason they invented DITA was so they didn’t have to do the first million of customization on every project for SGML.”

AP: I agree 110% with that, having lived through what you just said. Yes, a 100%.

PB: It was just reinventing the wheel every company, and it was a really expensive wheel and people were like, “Let’s stop doing this.”

AP: Right. It is cost savings off the bat, because like I said, if it gives you the majority of what you need, you can customize it and flex it to make it do what you want to do. I want to quickly investigate the flip side of that coin, are there times when you should not be customizing/specializing your DITA model?

PB: When you don’t need to. In a lot of ways, I think specialization, especially day one, less is more.

AP: Right.

PB: Yeah. You should have a really, really good reason for specializing. And I think the thing that’s really challenging about specialization is that, if you think about it in terms of other technologies, it’s one of the four features that should convince you to go with DITA. But very few organizations use it day one and very few organizations should use it day one. But the reality is that over time, you’re going to find cases that you just can’t efficiently support in other ways. And the alternative to having specialization is something like HTML classes or some other XML attribute that you throw onto something or some tag thing you invent in Markdown. But it’s super difficult to validate that and to make sure that it’s used consistently. And none of that stuff really effectively translates back to the rest of the publishing pipeline in a way that is consistent. There’s not a strong process for it. You have to invent the process and the pattern and then actually do the thing you want it to do. Should you specialize day one? Sometimes. I would ask your friendly neighborhood consultant. about that one.

AP: I’ll tell you right now, sometimes when it comes to metadata, starting early with that is a requirement, that is based on some past project experience. Yes.

PB: That’s fair. And I think the way that you end up managing the metadata, because metadata is a really… We might have to decide what you mean by metadata, because I can make anything metadata.

AP: Things you shouldn’t, by the way. Yes, you can.

PB: There’s definitely a conversation around, where does your organizational intelligence and taxonomy and terminology weave into your content model?

AP: Yep.