The CX Files

The CX Files #25 - Martin Hobratschk

• Ben Foden • Season 1 • Episode 25

Share episode

Is your AI strategy failing because your Knowledge Management strategy doesn't exist?

In this episode, you will learn:

- The operational differences between Apple's siloed culture and Google's open information architecture.

- Real-world case studies: Reducing onboarding time from 16 weeks to a fraction of that time.

- The vital distinction between "Just in Case" training and "Just in Time" knowledge.

- How to structure your data (H2s, Q&A pairs) so both AI bots and humans can actually understand it.

- How to overcome internal resistance by answering "What's In It For Me?" for your frontline agents.

In this episode of The CX Files, we are joined by Martin Hobratschk, CEO of Cognita Knowledge Management. With 25 years of experience leading teams at giants like Apple, Google Nest, and IBM, Martin breaks down exactly why Knowledge Management (KM) is the critical foundation of modern customer experience results.

---
Save your team dozens of hours per month on the tagging, tweaking, and tuning of results: the tedious part of getting rock-solid search and chat. Your whole org and customer base can now spend way more time on core work. 550+ Helpfeel business customers saw a 50% improvement over their existing vendor and got an average 2.5X return on investment.

Learn more: https://www.helpfeel.com/en/helpfeel-ai

#CX #AI #CustomerService #leadership

one day I was sitting there and I was, I was thinking about my experience at Apple versus my experience at Google. And, you know, with Apple... my experience was very siloed. You didn't necessarily know what another team was doing. There wasn't, you had to have a good reason to be able to look at the information that they, they had access to and the knowledge they had Access to. Google was completely different. Google, pretty much everything was open. There was very little that was hidden. You could do a Google search and find. All sorts of, of information that other teams were using, right? Could be about products that were under development, that sort of thing. And you know, the upside was great, you could find, you know, find answers, you know, to, to related problems per perhaps. But there was also so much information that it was. was overwhelming. It was, it was like trying to find a needle in a haystack sometimes. And so I think, you know, where, where Apple was siloed and had a little bit more control, yeah, you could, you could find things a little bit easier. But at the same time, you know, you may not find what you're looking for because it was locked away someplace else. Hello. welcome to the CX files. Today's guest is Martin Hobratschk. He is the CEO of Cognita Knowledge Management. And as a 25 year veteran of knowledge management with a wealth of experience, he is, his work background covers a range of industries, including at leading companies like Google Nest. Apple, IBM, as well as the American Cancer Society. He's passionate about communication and sharing knowledge because it is the key to success across all organizations. Martin, thanks for joining. Glad to be here, Ben. So I always like to ask my guests about their past and understand sort of where, where they're coming from. So if you could share with us what is, what is one of your early experiences in customer experience, good or bad? My earliest experiences at customer experience, good or bad? You know I. Probably a, a bad experience early on that, that taught me to be patient. I was working for Apple I was I was a, a phone agent I was actually working from home. It was one of Apple's first forays into work from home. And I got a customer who is a celebrity who shall remain nameless. And I was excited. I saw the name pop up. I was like, oh, cool, a celebrity. And celebrity was very rude and was blaming me for his problems with his, his MacBook. And you know, I just had to, remain patient and you know, work through the issue. I, I don't know if we actually got it resolved or not. I think he pretty quickly demanded to speak to, you know, a supervisor. And so we went through that process. But, but yeah, you know, that was kind of a early, you know, early exposure into like, you, you, you know, you never know who people are and you never know who you're gonna get at the other end of that line. Absolutely. I, I think that that's, that's a little bit of a nervous moment when you're, you know, opening a new call or, or opening a new ticket and you're, you're sort of reacting to this, this person. It could be anybody that could have any kind of personality, and you have to be ready for that. I. Yeah. Yeah. I mean, that's one of those things that, you know, it, it all boils down to the soft skills, right? And those soft skills are, you know. Things you can train to an extent, but also a, a bit of just, you know, who you are as a person and, and, and can you deploy those soft skills, right? It's definitely not something that you can catalog in a knowledge base. You're not gonna, you know, create a knowledge base article that says When presented with angry celebrity, here's the steps you follow. Right. Right. Yeah. Well, I, I think that that is a, that is a kind of a fantasy or, or a dream state for a knowledge base, right? That it could, you know, react to, or respond or cover you know, emotion, right? Special circumstances beyond, you know, the standard case. Yeah. Yeah. I mean, and you can get a little bit of the way there. You can, you know, you can have. You know what I like to call recommended responses. You know, I, I don't like the word script. I think that's too, too kind of confining. But, you know, you can, you can have, you know, recommended responses for situations and now with, with agent assist technologies, you know, and AI being able to listen in on a call and, and, you know, say, Hey, here's some, a recommended response. You can kind of get part of the way there, but it's not gonna be perfect. Right. And it's, and you really. Aren't going to be able to replace, you know, just human intuition and human you know, skill with, with recommendations from, from ai. I think. Right, right. Yeah. I mean, there's certainly, without a doubt, a value in human to human connection, which will not be replaced by AI and. I think a big part of that is beyond like a, a tactical or, or kind of a practical understanding. There's a, there's a feeling of understanding that you get when you speak to another human. And that has a value. Yeah. Well, it's, it's empathy, right? That's, that's that Right, and being able to kinda understand how somebody feels, understand while they're, why they're angry, understand why they're frustrated and, and yelling at you and demanding a supervisor, right? right. that, that, that empathetic response is is a really a human condition, right? And it's not something that you can, I don't think we're gonna ever be able to, to, you know. Train you know, a computer to be able to, to that. It might, might be able to mimic it, it might be able to say, here's what I think the correct response is, but it's not the same as, you know, having that, that empathetic, you know, ability. Right. Right. So you, you've worked across a range of big names famous. We, we called out a, a few of them in the beginning famous companies. And, and you, you started in frontline support, but obviously you've, you've transitioned and progressed in your career over the past 25 years, and I wanted to hear a little bit about some of those transitions. Between companies or between roles, if you could share any, any stories or lessons that were memorable there. You know, one of the things that that stood out to me in, I left. Apple and went I. shortly after Nest got acquired by Google. And this is a realization I didn't have until, I'd been kind of a few years in the, the Google plex as it, it's called you know, nest. When I joined Nest, it was still, it was still very much in startup mode, and it was only after a few years that it really got more fully observed, absorbed into the, the Google. Devices team. But when I was with the devices team and I, you know, there was one day I was sitting there and I was, I was thinking about my experience at Apple versus my experience at Google. And, you know, with Apple apple is, my experience was very siloed. You didn't necessarily know what another team was doing. There wasn't, you had to have a good reason to be able to look at the information that they, they had access to and the knowledge they had Access to. Google was completely different. Google, pretty much everything was open. There was very little that was hidden. You could do a Google search and find. All sorts of, of information that other teams were using, right? Could be about products that were under development, that sort of thing. And you know, the upside was great, you could find, you know, find answers, you know, to, to related problems per perhaps. But there was also so much information that it was. was overwhelming. It was, it was like trying to find a needle in a haystack sometimes. And so I think, you know, where, where Apple was siloed and had a little bit more control, yeah, you could, you could find things a little bit easier. But at the same time, you know, you may not find what you're looking for because it was locked away someplace else. Gotcha. Yeah, I mean, I, I think that lines up, you know, with, with my sense as an outsider, I mean, I've never worked at Google or Apple but you know, my understanding of Google is that their mission is to organize world's information. So I. Yep. It sort of makes sense internally to make that accessible as well. Yeah. I guess I'm curious if there was a moment for you when you went from, from frontline to, to knowledge base or you went from you know, that frontline role to, to maybe a management role. Can you talk to that point a little bit? Yeah, it was a, a little bit of a transition. I had. Apple moved from doing the CPU support to working on the developer support team. So Apple had, has had a developer support team since the very early days. And you know, the developer support team was really focused on the Mac Os. then with the introduction of the iPhone in 2008, the. Decision was made. Well, we need to have developer support for the developers of, of iPhone. And at the time they were, were. Essentially outsourcing it to a, to a vendor team to do the support. And it was just email support and it was a huge backlog and it was just a horrible experience for everybody. so they, they started up a, a developer support team, and I was one of the first folks hired onto that. And again, kind of during tier one developer support, basically helping with enrolling developers into the developer program. It wasn't technical support. And you know, from there I moved up. I went from tier one. To tier two to three. We were called content training support engineers. It, it, when I got that tier three level, that's when was involved in helping to document the processes for the team and the knowledge base. But I also was, was training the team. And, and helping ramp up some new sites in, in Europe, and that's where I, I really, you know, kind of. Started down the path of just doing knowledge management as my main type of job.'cause to me training is, is very closely related to, to knowledge management. I, I tend to group it as a function of knowledge management. A lot of folks in the learning and development industry may not agree with me on that. But but you know, they're, they're kind of two sides of the same coin training. Is, you know, you, you train somebody just in case they might need the knowledge. Knowledge management is about, about just in time. You know, you, you need that answer, right. Then you need to find it. Right. And so they, they have to work hand in hand, right? And so, you know, that was, I think that's given me a really interesting perspective on, knowledge management because I see it as, as. One sort of holistic thing, you know, the learning and development part and the knowledge management part, again, are two sides of the same coin. And I've always worked very closely with the the training team because it's crucial to expose folks to the knowledge. you have in your knowledge base as a part of the training, you need to basically train them where to look for the, those answers, right?'cause they're never gonna be able to remember it, right? And so you have to, you know, develop those knowledge assets alongside the training so that they are, they're complimentary to each other. And so that's sort of a, know if it's a unique point of view, but, but it's not something that I come across a whole lot when I'm talking to, to other knowledge management practitioners. Definitely, I, I think of it as sort of, you know, teaching people to teach themselves, right? Yeah. And, you know, as you, as you moved from tier one to, to three and, and into more of a sort of a process creation role, sort of a documentation building role was there, was there a moment or, or maybe at a period of time where you felt like, okay, knowledge management is, is really underrated. Like this is really the thing that we need to be focusing on. Be honest with you, I that. Insight. Years before, Hmm. was, was at A IBM, I was a customer service manager. So my very, very deep background is you know, when I went to college and I graduated from college, I was a, newspaper reporter, you know, I was gonna be a journalist and you know, so from, you know, that's, you know, in hindsight that's a, a very much a knowledge management type of job. Right. I left that for various reasons. then when I was at IBM. You know, I was, I was really looking to, to move back into, you know, how do I, do I, you know, leverage these as a tech writer or as a writer? know, in, in this technical organization. And that's when I started becoming aware of knowledge management and I was like, okay, this is maybe a direction I want to go in. Right? but it was only a few years later when I was with Apple that I was actually able to make that change and say, okay, yeah, this, this knowledge management function is, is really crucial for the organizational success because, you know, the team that I was on. That developer support team, they had some, processes, but they didn't a lot of processes, so we had to do a documentation of those. And so I would interview various folks about, you know, what do you do? You know, it was, again, it was just like being a, a newspaper reporter, just slightly different focus and you know, interviewing. Lots of different people, you know, not just the people who were, were doing the job and were doing the process, but you know, the management and, and getting their input and saying, well, is this the way you want the process to work? Do you see any, do you see any potential problems with the way this process is outlined? Right? And so that's when I really was like, okay, the light bulb went off. It's like, this is, this is something I need to, to really, I guess. Invest in more for myself and, and learn more about and and is the path that I want to pursue. And from that point, that, that's when I was really like, okay, knowledge management is now my career. It's not tech support, it's knowledge management within that technical or customer support area. Got it. Got it. Yeah. That's interesting. I, I feel like, you know, knowledge management, it sounds kind of intimidating on the surface. It sounds so broad in scope. Can you. Maybe for people out there who are aware of it, but maybe haven't sunk their teeth in yet. Like, could you give some, some concrete, like either examples of, of things people can do to kind of, to open that door or, or maybe some concrete kind of results that you've seen as well. Yeah, I think. know, you hit the nail on the head that that knowledge management can seem kind of broad. I think too, that an awful lot of people don't even know what knowledge management Right. And, and so, you know, I think for me, and, and I think the definition is different for everybody, but for me, knowledge management is. Empowering people to create and share the knowledge that, that they need to solve problems. that's a pretty generic sort of definition, and that can, that can apply to a lot of different functions. You know, a knowledge base is, is one of those functions. A knowledge base is a, is a library essentially. Of, of different types of knowledge, assets, you know, usually articles of, you know, to solve a problem, right. Or maybe a policy or something like that. but, you know, other types of knowledge management are things like communities of practice, you know, bringing people together to talk about what they're doing. Knowledge retention programs. How do you, how do you capture. that people have about how a, a company works or, or their job before they leave, whether they're, you know, retiring or they're laid off or they pursue other opportunities. How do you, how do you capture that? Right. Those are kind of the, the three big ones, but there's, there's so much more. You know, learning management systems are, are akin to knowledge bases and you know, there's some library connotations to that as well. Really any kind of activity that is right at that nexus of. Getting tacit knowledge from inside people's heads or capturing tacit knowledge, know, that that arises from interactions and, and documenting that so that other people can access it and making that knowledge explicit, that really where, you know, knowledge management happens, right. In any kind of activity like that. Right. And so, you know, my main focus has always been. Customer service, contact center, technical support, contact center, and knowledge management is especially powerful and especially useful there for, for those teams to be able to access that knowledge and not just, you know, in the sense that. A customer has a problem and I have to give them the solution. You know, that's the, the, the big, you know, win. You know, and that could be maybe tied back to customer satisfaction, right? But if you think about it, those knowledge management systems, or the existence thereof, has implications for a whole host of other things, such as employee retention. Because if you don't have a good solid knowledge base that an employee can refer to, they're gonna get very frustrated with the job because they don't feel like they're effective and so they're gonna leave or. Or onboarding time. If, if you don't have a good, solid knowledge base, it can take a lot longer for somebody to become proficient at their jobs. One of the clients I worked with, one of my very early clients as a consultant to me and they said, we don't have a knowledge base, and it takes us 16 weeks to onboard a new contact center agent and. We wanna put a knowledge base in place 'cause we know that that's gonna help us reduce that. And so we were able to put that in place and that that did, you know, significantly reduce the amount of time with onboarding because. What they were seeing was, you know, the new agents would come on all the knowledge was, you know, held by these very tenured employees. And so those new agents would have to know who the employee was if they, they couldn't find the answer and go find that employee and bug them and, and get the solution from them. And that just added time to the resolution. It was very frustrating for everybody involved. Right. And so by implementing a knowledge base, they were able to. To reduce that frustration for all the employees, they were able to speed up the time it took for somebody to become proficient. They were able to improve the speed of time it took for a customer to get an answer. So there was so many knock on effects by just implementing a very simple knowledge base. Yeah. Interesting. Yeah, I mean, those are some great examples too. And as, as you're talking, I'm thinking about all of these these points of friction without the knowledge base, right? The, the, the co, the employee that leaves and brings the knowledge in their head, you know, with them, right? The new employee that doesn't have the knowledge in their head. You know, the, the, the tenured experienced employee who has to stop what they're doing to answer a question to, you know, to transmit what's in their head to the, to the junior. These are all points of friction that are solved by having a good, effective knowledge base. I think of it as like, you know bridges with toll booths on them, right? And every time the knowledge has to, to cross a bridge, you know, there's a cost, right? It is time. And. So I think that hopefully this is, you know, listening to your response and into this podcast, people can start to, to visualize and, and, and make more concrete these, the cost of these points of friction. Yeah. I. a hundred percent, that's, that's key, right? Companies, organizations, teams, even individuals who are are, are starting to look at this problem is to, you know, obviously start off with an assessment and kind of figure out where you're at. You know, what, what does your technology look like? What are your people, you know, what are the processes you have? But, but use that assessment to help craft a, strategy. You know, are you going to do? You know, in the next six months, what are you gonna do in the next year? What are you gonna do in the next two years? Whatcha gonna do in the next three? Have a roadmap for how you're going to, you know, improve all this, right? Because it's not gonna be something you can do overnight. And it's, it's, it, it can be very overwhelming to start off, say, okay, we're gonna do knowledge management, know, and we're gonna. We're not sure exactly what we're gonna do about knowledge management. We're gonna do something about it. You know? And it's, and it's always more than just, you know, okay, we're gonna put a knowledge base in place. We're gonna, we're gonna go and invest in this tool and have, you know, we're gonna put all our knowledge in there and we're gonna be good. Well, that knowledge needs to be managed. It needs to be curated. And so you need to have a plan for how you're gonna do that. Right. And you know. discoverability questions. Yeah, there's search, but, but how is that knowledge gonna integrate with your, your AI tools, you know what teams are actually gonna be able to leverage this knowledge? Because organizations will have many, many knowledge bases, they've got lots of different silos. and again, it, it needs to be. Strategic in how you, how you address that. Because having of silos is, is like having a giant digital landfill, just a bunch of stuff in there that nobody can find anything because it's just so spread out. They don't know where to look. Right, right. But also trying to. Condense everything into one single point of truth can be a bit overwhelming too. So understand, you know what, maybe it's not a single point of truth, but maybe it's, you know, three or four points of truth, you know, but they're well managed, right? And, and there's some sort of system to, to where they're talking to each other and they're integrated, right? So, but again, you can't do any of this without having a really thoughtful strategy about how you're gonna get there. Right. Understand the reality, make a practical plan and then go forward. So one of the things that is a recurring theme on this podcast is this idea of internal salesmanship and, and how do you win support for the initiative that you see, the value, you know? From your experience that it, it's absolutely worthwhile to do, but you have to convince others. And, and I know you're the CEO of, of Kognito knowledge management, and so you've got some perspective as a business owner, but also you know, just for people out there, like how would you recommend, or how would you advise people go about, you know, selling these kinds of initiatives internally? You know, it's very simple. I think it boils down to a concept that a lot of folks are gonna. Be familiar with you know, just under, you know, tell people what's in it for them. You know, what, how is this going to help them? How is this going to help them? Save money. How is this going to help them help customers faster? How is this going to help them find the answers that they're, that they need? How's it gonna make their job easier? Right. That's, that's, that's the place to start is, is just, you know, very simple what's in it for me. And, and being able to communicate that. With knowledge management, especially in a contact center space, I think it's really crucial to involve. The front line as much as possible, and not just kind of helping to chart the path that you're going to be following and the tools that they're going to use. But, but in actually creating and, and sharing and curating that knowledge so it becomes a function of their job.'cause if, if you just treat your knowledge base as kind of a set it and forget it thing where you've got, you know. Maybe some SMEs who work with tech writers to, put content in even just have SMEs tell 'em, go ahead and put the content in there. It, it's over the long term, it's gonna get, get left behind. It's gonna, it's gonna stagnate because people aren't taking an active role in, in kind of curating that knowledge. Right. And so I think it's really key to, to involve everybody because. the end of the day, knowledge management isn't something you do for people or do to people. Sorry. You don't do it to people, you do it for them. Right. And, and, and, but they need to be involved in doing that for themselves. Right. And, and I think with, by getting that involvement and, and, and showing, you know, what's in it for them, I think that's really the key to having a successful knowledge management initiative. Absolutely. You know that's like a story I heard from my dad who, who has a marketing background, but he said, you know, everybody's tuned into WIFM radio, which is what's in it for me. That's it. That's it. That's a hundred percent. It's just pure, you know, human nature that. Right, If you can show somebody what's in it for them, they'll be like, okay, yeah. right. I'm, I'm definitely interested. If, if they don't, then they're just gonna be like, yeah, I really care about that. You Yeah, I understand. Here's this thing that you want and here's how this new project is gonna help you get it. Right. Exactly. Okay, great. So, I mean, I think that's, that's something practical that people can take away and, you know, whatever, whether it's knowledge management or, or AI or whatever initiatives they've got going on, that's something that they can use. When you when you look at, you know, your past experience with, you know, deploying, knowledge management, whether it's tools or a new initiative or process you know, there's this transition that goes from, you know that people go through, right? So they, they start in frontline support and they're responding to tickets, they're taking calls, doing emails, and then they transition into being writers, or at least partially part of their responsibilities, become writing and, and curating, creating the knowledge base. Can you tell us some stories about that transition and, and sort of maybe some some challenges and opportunities there? For me, it was pretty simple, you know, because I had that writing background. Right. but. not everybody has that writing background. Right. you know, how do you, how do you empower somebody to kind of be a writer when maybe that's not the experience they have and maybe, maybe it's not even a desire that they have. They or they don't know they have that desire. So, you know, in the days, you know, it was a matter of. You know, finding folks who, who had the interest, you know, maybe they had some background in in doing some sort of documentation and you, you know, we would, you know, create writing tests and say, okay, here's, kind of a situation. Write a, write a process about it and see kind of how they handled it. Mm-hmm. Now, today that's less. Of a, a chore because there are so many ways to leverage AI to help somebody do that writing. You know, so they don't have to necessarily be a writer. They can just put some notes into a widget and, you know, an AI agent can, can look at that and format that and say, okay, hey, is this. The knowledge article you want, and then have somebody who has the expertise to, to look at that and review it and sign off on it. Right? And so it really can speed up the process and, and enable folks who maybe in the past really wouldn't have even considered doing something like that to be able to do it and be able to do it pretty effectively. Absolutely. And, and that the, the episode hasn't been published yet. I think it'll be out by the time this one is published, but previous guest was talking about exactly this point, and they, you know, they, they agree with you completely, and I agree as well, which is, you know, you take the subject matter expert, the Smee, you take them and you have. They have the passion. Maybe they don't have the writing skill. They've got the experience, they've got the passion. And through using these generative AI tools, they can, they can kickstart, they can get that first draft out. You know, they can give it a once over, it can get reviewed and approved before it goes live. But, but taking them from what's in their head to what's on the page, you know, that that gap is smaller than ever, or, or, or even non-existent at this point. And so that's, that's like a real concrete thing that, you know it's not like a rare capability in the world today. There's a lot of tools that can do this for you, I think. Yep. But I feel like this is one sign of a, a transition. I'm using this word a lot today, but I think of like. There's a changing landscape, of course, in CX with ai and, and there's a changing landscape as far as careers, and a lot of people are rightly concerned about their jobs. But I think that there's, as, as any technology over in history has come out, you know, people have transitioned. They've, they've shifted their focus into using the new tool in a new direction. And this is a big opportunity because now you can. Even if you're not a writer by background or by by interest perhaps you can do writing and that that knowledge base becomes your work. I mean, it's a big part of your work, basically. Yeah. And, and that, that powers up the AI as well. So how do you think about like this, that changing direction and sort of where things are going? This relationship between, you know, the traditional support role, the knowledge base, and ai. You know, I think it's constantly evolving. I don't think anybody has a real clear vision of, of where it's all gonna end up, you know? I think it, know, it definitely holds, I. Promise for making it easier for people to do their jobs. And again, to, to be able to share that knowledge. I think that the, the is that there's a lot of fear is, maybe that's the right word, that you know well AI's here to replace. me. Right? And that's not helped by all these executives saying, we're gonna, we're gonna replace all of our customer service people with AI agents. But, you know, I think they're also kind of finding the reality that not a hundred percent. And, and plus customers, they don't wanna work with AI bots. You know, they, if they, if they're gonna talk to somebody, they wanna talk to a human being, right? They want that human empathy, right? They want somebody they could communicate with and not just get sent into an endless loop. Right? but so I, so I think that, you know, there, there's a lot of promise for, for the, if, if implemented in the right way and, and you get people involved and, and them the tools that are really helpful to them, that can help them. Do their jobs better and faster they'll, they'll be more inclined to say, yeah, this is something that's good and this is something that's gonna help me. Right. you know, one of the things a lot of folks talk about is, you know, ai not necessarily replacing everybody's job, but being able to handle kind of, you know, in terms of like customer. Experience being able to handle those very simple issues, you know? Yeah. A AI bot can handle a password reset request or something very simple. Up to be able to apply their, their reasoning and cognition to solving the really complex problems that often a lot of empathy because you have a very frustrated customer on the other end of the line. Right. Had, I had this experience just yesterday. I, you know, we had ordered some, some meds for our pets and got a message that, oh, it's delayed. You need to talk to your, your vet. So I called the vet and I was like, well, we didn't get the notification. Can you, can you call them And, and tell Luis sent us a notification. So. I called, it was a, a voice bot. what is your problem? All this kind of IVR sort of stuff, not getting me anywhere. You know, finally figured out, you know, I kept asking for a human. He didn't understand if I just hit zero. I was like, oh, we'll put you in touch with somebody. I was pretty frustrated at this point, you know, just knowing that, okay, this is not going to end the way I want it to end. you know, then it was like, yeah, I'm on hold for 40 minutes. at least it gave me the estimated time. So, so I bailed and I canceled the order, and I went with another provider. Mm-hmm. But, you know, it was just that frustration of dealing with that automated system and not being able to talk to a human quickly that lost this company in my business. Right. Right and Concrete. and that's, it's, it's not, and it's not an uncommon experience. Right. Right. And so I think that, you know, companies are gonna have to figure out how to, how to make these, these AI systems work in a human way and, and, and, and b, very human And being able to, you know, a understand, you know, what you want to do initially.'cause I was telling it exactly what I wanted to do. I was like, I need to have a re notification sent to my vet and didn't understand it. didn't understand it. Right. And, and so that's so frustrating. And so I think that, I think there's a long way to go for, for many, many companies in terms of able to have those kind of AI capabilities that, that are gonna really work for people. Right. I think I think we're, I think we're still very early on despite all the promises from these companies. I think we're very, very early on in terms of, of, of. The capability of these systems. Absolutely. And I, I, you know, I work on the, the discoverability side and so exactly this kind of challenge that you're talking about, but I'm not gonna talk about what I do today. But as far as, you know, the knowledge base. Goes and the knowledge management practice goes that is very much the root of reliable self-service. The root of reliable ai. If you do not have that foundation in place, your chat bot's gonna be a disaster if it's voice or text or whatever. If it's an AI system, it's only as good as the data that it can pull from. And, you know, the, the structure of that data, the clarity of that data, the, how up to date is it? And so on. And so all of this points back to having a, you know, a good observation of the reality and, and a clear strategic plan for knowledge management. Have you, have you talked or heard about, you know, this, you know, knowledge management for ai or sort of preparing the knowledge base to be ready for ai, and what do you think about this generally? Yeah, it's, it's, it's a hot topic right now with knowledge management within the knowledge management community you know, because. Of exactly what you said, right? That knowledge base is, is the foundation the success of, of these different tools. And you know, the, the conversations that I've been having around this are we, how do we structure our, our knowledge base articles so that, you know. AI chat bots can, can easily find the right information and accurately find the right information, but also so that it's consumable by humans, right? Because you're gonna have both types of agents looking at this knowledge, and they need to both be able to easily and quickly understand what it's saying, right? And so, you know, there's some very basic things that apply to both. You know, you need to. You know, have, you know, headers, you know, H two and H three, use those you know, have the, the language be very clear and, and simple and not too dense. You know creating question, answer pairs you know, kind of FAQs. There's some debate as to whether those need to be standalone documents or as part of the, the general document. But you know. These are all things that, that AI uses to, you know, find the right information, but it's also stuff that, that humans need to, to be able to, to really quickly understand these knowledge A assets, right. Right. So to close out the episode here I wonder if you could make a recommendation or, or a thought on the future if you want to give advice to anybody out there. CX leaders knowledge managers. You know, what would you say are, are the the places to dig the the, the places to, to focus on for the future? I think the biggest one is. And we've talked I. already is, is that knowledge governance. You know, what, how, how are you, how are you ensuring that your knowledge is, is curated? And it's not just stale and static. is the, the single most important thing to look at. But in looking at that knowledge governance, you also need to look at the people, right, who are, who are managing the knowledge and using the knowledge. And also the systems that you're using, right? Not every system is created equally, and there's a lot of legacy knowledge based systems out there that just aren't really prepared for the future and, and to get them to a point that they are, are gonna be ready for the future. Is, is gonna take a whole lot of effort on your part, right? And so you have to make the decision, do we stick with what we know and, and spend a lot of time and effort trying to develop it into something that, that will work for the future? Or do we, we find a new solution that has everything we need that can, can easily work, you know, integrate with the content we already got, and ingest that content to an extent. But starting with, you know, the governance, you know. what, when, where, why of, of how that knowledge is curated is, is key. Absolutely. Thank you Martin. Martin again is the CEO of Kognito knowledge management, and he helps companies and teams. To prepare for this future in the right way and, and deploy a solid knowledge management practice. So Martin, thanks for joining us today on the CX files. Thanks for having me, Ben. Alright everybody, we'll see you on the next episode.