CELab - Ep 183 - Your Product Isn’t Too Complex for AI: Georg Gottschalk on ERP, Partners, and Learning at Scale

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Dave Darrington: changes that you might need to make,

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Dave Darrington: Hello again everybody. Welcome to another episode of C Lab, the Customer Education Laboratory.

Narrator: We explore how to build customer education

Dave Darrington: programs, experiment with new approaches and really work to exterminate the myths and the bad advice that stop growth dead in its tracks. And I'm Dave Darrington. Today I am very pleased to um, welcome our guest, Jorg Gottschalk. Look at that, right? Can you say hi and just tell us a little about yourself and we'll jump into the show?

Georg Gottschalk: Yes, hi, um, thank you for um having me on your show and my name is Georg Gottschalk, I'm uh, VP of Global Education at Acumetric. Uh we are an um ERP company for the small mid sized businesses. We are building gross businesses together and we are very focused on ah, native cloud, native AI forward erp um solution that brings technology to what I would call the heart of um, what drives growth uh, in any developed country.

Dave Darrington: Yeah, I've wanted to learn about your company for quite a while. And I've had some background in ERP too. I know how complex it is and, you know, challenging. You've got a really interesting background. But before we break into it, let's do a little bit of fun stuff here. It's. It's the International Day of segment. That's our. Always our warm up. And we queue up the page. I won't show it on the screen here. Um, I think you know what's most important to you right now, and that

Georg Gottschalk: is World Cup Go Germany International Day. We are here talking to a German who lives in the United States.

Dave Darrington: Indeed international sport and passion. I'm in Seattle, so we're going to be hosting, uh, events at extremely high cost. But it's exciting to see the whole city is on fire right now. Not in a bad way.

Georg Gottschalk: And Seattle have a really good soccer team, too.

Dave Darrington: Yeah, we have fun up here. The, uh, Seattle Sounders are. I've been to some of the games. It's an experience. I actually, at one point, one of my friends who's in the advertising industry here, he's like, Dave, you got to go with us. Like, we sit in the pep squad area. What? Just come and then. It was amazing. It was. We were doing the chants and songs and all that kind of stuff, and it took me back to my marching man days. It's amazing.

Georg Gottschalk: Very cool. I think our CEO has season tickets and one of our partners in Germany offer. They're, um, sponsors. Big sponsors of FC Freiburg. So shout out to Freiburg.

Dave Darrington: Amazing. And you know, it is National German Chocolate Day today, too. So let's shout out to Germany for. It's one of my favorites. Okay, Jorg, let's get into this today. Uh, I always like to do either a hypothesis or what I call my frame up, which can help us articulate where we're going, what directions we're speaking of today. And for this one, um, you know, I want you to push on some of the things here, some of the statements that I've made in scripting is erp, let's talk about it. Enterprise Resource Planning. If you aren't aware of this, in our field, it's very complicated. It's probably one of the hardest possible stress tests. And now we're doing AI assisted education in this. Right. This is genuinely complex. And we were talking previously, unlike a lot of times, we've been focused on software As a service, SaaS where we're releasing all the time. Now we're looking at something where we have a massive product with so many belt and only components to it ship a couple of major releases a year. So now we have that, uh, I would call content drift or decaying of education as things come on. Now we've got a new release, we've got to time it right. You know, you, you deal with customers and partners. There's a lot of content decisions that you need to make. And you have a vast ecosystem of, you know, both partners, customers, resellers. There's a lot to be done. So here's the assertion. Today we're going to be talking about a couple different things. Uh, if AI assisted learning, how does it actually work here in partner led twice a year? The excuse most of us have been hiding behind a lot of the times is that our product is too complex. My situation is too special. AI can't handle that content. I think that's dead. I think that ship has sailed. And what I'd really like to get you talking about is your experiences. You've got a deep experience that you've been at companies like IBM, Salesforce, et cetera. Now you're at Akumenica. Uh, you've had uh, time working. And this is one thing, this is a, um, somewhat. I don't really want to call this a partnered episode, but I've been working with Sarah Sedgman and at Learn Experts. Their uh, product. Leah, uh, Leah, um, really amazing stuff and I know you're leveraging that, so we'd like to go talk about that in and that today. So you ready to start?

Georg Gottschalk: Yeah, let's go ahead.

Dave Darrington: Wonderful. Okay, so let's start off by you, your career and frame up how you got to here. What are the things you've been working at? Again, I said you've done a lot of stuff. And one of the things that tipped me off, it was interesting. You were at Mulesoft too, right? Training and cert. That's a heck of a complicated project or program platform. I was in, um, you know what we call it, iPass, integration platforms. And met uh, people at that organization, Salesforce, uh, IBM, Web Sphere. Tell me about your career and your background and how you got to here.

Georg Gottschalk: Yeah, thank you. What always interested me was the interaction between um, business and technology. Um, that leads back to my university days where I worked at an integrated manufacturing company, Technology Transfer Center. We, we built a really cool shop floor. We integrated Mac systems with iOS and others. And um, we had um, early work with uh, SAP where we built one of their first data models, process models. And it was always, how do I, how do I mirror image? The Physical world into the data digital representation. Uh, if I have a shop floor, I want to know, um, how long does it take me to get something in my warehouse through the production line and out the door into the truck so we can get it to the customer. Right? Um, I want to know where it is at every point in time. I want to optimize it. One of the projects we did was, you know, truck logistics optimization at um, Anheuser Busch um Brewery in St. Louis, the U.S. i'm German. I come from Columbus beyond the world. And we had some disagreements about brewing techniques. But we went past that

Narrator: real quick

Dave Darrington: here because I'm a St. Louis boy. I grew up in St. Louis, Missouri, the home of Anheuser Busch in the U.S. so you know, I have a lot of love for uh, German brewing techniques

Georg Gottschalk: ingredients is Reinhardt board the purity law. We don't use rise fii anheuser but anyway, you know, um, we always mirrored digitally what the business was doing. Whether that's in financials, uh, um, in workflows, in organizational structures and processes. And um, that's kind of what interested me throughout. Uh, in order to do that you have specialized systems and you have platforms where these specialized systems run on and you have to integrate them and really orchestrate um, your technology to support your real life, uh, your business. And even today, um, is fast forward, um into AI. For instance. For me AI is not a, um means in and of itself. It's an end in and of itself. It's in the end technology that makes business um, work better, humans work smarter. Um, it's cutting edge technology with human ingenuity combined. Um, and that's always been fascinating for me. So I worked first in consulting, did a lot of business process optimization, uh, internationally. Day of international today, um, I um, then joined integration company Crossworld Software, uh, out of Silicon Valley, um, because I wanted to really get down into the weeds of how do we actually connect these. I had so many SAP projects that went wrong because we had um, dozens of legacy systems, dozens of standard software systems. Each and every one had some goodness in them, some specialized need. But together they were orchestrated. And so that um got bought by IBM, which is where uh, Sarah and I met. Um, she was leading one um, education team for one brand and I was leading the education delivery for another brand. And um, we've been um, in touch since then. And um, at IBM, IBM I was like well maybe I stay for a year or so. So um, I said over a decade because I thought that the business is so fascinating how they were able to build synergies between software technology, hardware technology and um, consulting services to make both really shine for customers. And how nobody ever got fired for hiring IBM it was because of their dedication to customers and that's what I learned there as a guiding light. And they were also very well managed. So it was a great experience and Sarah and I really hit it off there. And when um, we met again at Tsia, um, at a conference where she was exhibiting what she was doing with Swiss phone experts and I'm like oh this is really cool, you know, we're going to stay in touch. Um, and so yeah, so at IBM I um, built the um, skill infrastructure really of um, a certain technology and integration technology and application server where we work with customers and partners. And I was on the delivery end and then I moved over to Salesforce, uh because I had an opportunity to work on the development side of things um, and then over to Mulesoft, um because I was able to put both things together and lead the development and the delivery um of um, not just education but really building that um skill infrastructure for a rapidly growing ecosystem. We scaled the company from when I joined it around 200 million ACV to um, where it was when I left was about $2 billion acv. So that's a 10x growth in like 4 and a half, 5 and a half years. Very ah, very interesting. We did this through um, a very strong partner channel, a very strong implementation methodology, a very strong product. The challenge that you mentioned before was that we did not have end users, end users, um, have very broad needs and need to be guided really in order to learn the technology. Um, but it ends with certain use kind of level. Right. Um, with mulesoft we had a highly technical audience who was living down there in the basement somewhere integrating stuff that nobody sees ever. But you know, if it doesn't work, nothing works. So um, it was, it was really interesting work and we scaled it from zero to tens of thousands of um, certified consultants and um, developers worldwide until that was. But Salesforce, you know, back there,

Narrator: that's

Dave Darrington: quite a challenge too because uh, you know I spent some time with certification in this, I can't say a similar product because Mulesoft had been like the leader in that market. But the art of the possible, the capability, the things that you can do with that kind of platform lead you to a very interesting. It's almost you have to have somewhat of a business spoke customized um approach for learning and then towards certification. You need to know fundamental things. But there's a lot that you can do with that platform.

Georg Gottschalk: That's correct, yes. And certification is key simply because it needs to be meaningful, it needs to be valuable, it needs to actually tell somebody who looks at a certified individual that that person knows something, you know, and that you can actually verify that that person knows something. It's not um, it's not so much that somebody attended something or has been present at a session or course, but that um, you go from knowledge uh, to really skills and then a combination of skills that combine into your ability to perform uh, ever increasing complex tasks. And that builds you back to erp, uh where you are building the digital mirror image of a uh, thriving business with all its complexities. And you're trying to make it easy for the user to um, do their jobs whether they're in accounting, on the shop floor or back in it, making everything work together. I have a lot of respect for those people.

Dave Darrington: What a diverse audience too. Because you don't just have one kind of cohort, an administrator or a technical end user or something you have. I spent a lot of time in manufacturing on the chemistry production plant, uh, implementing and manufacturing execution systems and it was such a different kind of environment than it was when I was a laboratory chemist.

Georg Gottschalk: Right. Manufacturing is one of the big verticals that we use in Akumatica and what I find fascinating in that regard is in the end no matter what you do, you are supporting that business. So um, when I look for instance in Akumatica across our partners, those are most successful have a uh, highly specialized micro vertical approach. Not just manufacturing or construction but they're in general construction and they have the top 10 GCs in Manhattan. So um, really um, high ah, amount of specialization to reduce complexity for their clients basically.

Dave Darrington: Right. That's. Wow. I mean this, this has opened up such a, an interesting landscape for our discussion. One of the things I wanted to ask you about though is I, I believe you spent a little bit of time as an advisor with Learn experts with Sarah, um, prior to coming to where you're at now. Right. You tell me a little bit about that transition because now it's interesting because you've, you've kind of dog food what you've done. Now you're, you're now you're at Academica, uh, taking all the skill sets you've had throughout your entire career and you've got this flavor of I'm using this platform that I've actually helped to in some ways sell or consult or advise with. Tell me a little bit more about that.

Georg Gottschalk: Yeah. So um, you know Sarah and I go way back. Um, and I thought they were really onto something. Um, one of the biggest challenges that I always had, um, in any role that I played in any of these companies. Um and it really didn't matter if it was a very technical integration play or it was um, the marketing cloud at Salesforce. It was responsible for the certifications. That was for Clouds, but also for all the acquisitions, uh, from Tableau to Mulesoft to Slack. Um, very, very, very different use cases. Um, the thing that I found interesting about Learn Experts was that it helped um, to eliminate a bottleneck that I had. Um, I had always attempted to get really strong product experts into um, my teams. People who knew the technology, who knew the software, who knew the platforms, who could talk as peers to the users for whom they designed um, the learning experiences because they were the teachers. When you, when you, when you attend a class, you know, instructor led training is still the gold standard if you want to learn something really deep, really quick. You know, um, those instructors, they're, they're role models more than anything else. You know, you believe that they really know what they're doing. And I've seen amazing instructors at any of these abim, Salesforce all around the world. Um, the um ability of software to make that technical competency of your developers shine and m help them to design a learning experience that connects with their audience is critical. And um, it's like speed, quality and technical depth. Pick any two? Uh, well with Lei I can actually pick all three. You know that's what um worked for me because I could have technical experts. They may not have been the greatest curriculum, um, um designers or learning designers. Um but Lei could do that for us. Uh, you know that really helped. Um, or we have right now at Ecumetica we write extremely sophisticated, detailed, accurate documentation. My team does. And that um, documentation um, reads well. It's really good. How do we connect that to somebody who just needs to enter an order? Well, a tool like Lea helps or I make um, everybody also learning designers, on top of being technical writers, on top of being um, technical ah product experts. And at some point in time um, the capacity of the teams to absorb ever new requirements is limited. And um, this technology at AI, I can really unlock that technical depth that we have on our team and that others have on that team. Quite frankly I can use input and um, content from across the company and really build something unique out of it.

Dave Darrington: That is this cuts to the core of what I'd really hope Jorik that you talk about which was that platforms like these are emerging as we're learning AI and Sarah and her team have done an exceptional job. I think I've touched the product work with it. I love to actually leverage it in my own company. Vast, because we're faced with, I think this is relevant to our pertinent discussion because like what you're dealing with, the Vast platform is sophisticated in that we're bridging both hardware servers, clusters, um, and then how do I actually build data pipelines that support AI workflows? And those are uh, for example Pixar uses our platform to basically source and consolidate all of the artistic assets and such but then feed server farms for Nvidia, you know, processing to make movies. Right. And, and this is such a complex thing that require. But we have customers across the board that are, that are. And it's interesting. So now I'm being faced with how do you certify folks to do that? And, and I'm um, now everything you're saying is evoking this sense of nervousness and, and challenge for me to actually implement. So um, I want to jump over to ERP education such too. But can you tell me a little bit more about Acumenica as a whole? You've talked about a little bit. Um, you're in global education there so you are constructing those certifications and you're trying to go in those micro verticals and things like that. Is there any more that we can unpack about? I think some people don't may not know in our audience what an ERP is. We have a vast audience with different segments too. So that might be good to talk about where you are, how you're unique, the partner LED aspect and why education is quite brutal. Um and you're solving those problems now which is what's really cool.

Georg Gottschalk: Yeah, Acumatica is ah, a um very intuitive cloud ERP solution that powers the whole business. That's also where our um, complexity comes from. Uh as we're working in the SMB space Monomitz has businesses our customers don't have the luxury of buying um large enterprise scale applications for each and every niche um use case that they have. So um, we not only provide a financial uh accounting solution but we really build the digital mirror image of the entire enterprise. That is what I find so fascinating. Um this integration, this aspect of really pulling together everything from your suppliers through your production to your customers. We have in January um, a summit in Seattle, your hometown, um we are located and um, what I love about Summit the most is, you know, it's a really solid professional production where you get a lot of information, you learn a lot, you connect a lot, you network a lot. For me the thing that is most, the coolest thing is walking through the hallways. Archimedic does a really great job highlighting its customers. There are these, there are these um, showcases. Um, you have um, like a race car helmet in there. Uh, we have um, a peanut from in um, Georgia, like totally Jimmy Carter style, you know. And then you have the actual products there, um, the various. And they're produced with the help of our software. Um, we have honey bees, um, farms, we have um, people bath ropes, you know, and those are um, fascinating, um, products that drive the economy. Um, when you look at um, the U.S. um, we had a summit in South Africa or when you look in Europe, anything between 60 and 75% of job growth, future job growth is in the SMB space. And that, you know, I mean you, that, that is really carrying the large GDP portion, large economies forward. And we're helping that, but we are backstopping that so these people can really focus on what they're good at. Um, ah, a race car helmet or you know, um, a jar of perfectly roasted peanuts. And we help them to get their technology together, to get their business um, accounted for, to make sure they know, um, their profit, their loss, wherever it is. Um, we are a very um, innovative platform. We have AI ah built in across. It's another interesting aspect. We are using AI as a means, uh, or as an end in itself but um, to really support the businesses, uh, to make better decisions. So anomaly detection for instance, um, all of a sudden you have a product that for some reason is driving you down. You know, the product is highly negative. Why? Oh well, you know what? In this part of the supply chain there was that one thing and it takes um, hours and hours for a human to find that in some remote spreadsheet somewhere. Um, A.I. our anomaly detection in Akumatica finds it, highlights it, gives it to you and within a very quick moment you can really eliminate a problem bottleneck or serve your customers better in general.

Dave Darrington: That's fascinating. I've had some experiences working with different kinds of industries. I recall in a contract I was on, uh, we were talking with Hudson's Bay Corporation out of Canada and they had this thing called jackpotting, which I'm like, this is the cool stuff where you get in and learn from your customers. I love to learn from customers. And, and then I think this is what you're telling Me that you're, you're custom, right? Sizing the things that your software and your applications help them overcome. But then there's that learning function around it. When I was learning about this, it was a jackpotting. Means that something just popped out of the intake when we were receiving and you've lost product. We don't know where it is. On the floor somewhere in some facility or warehouse or, or in a center. And that at the time, that was, you know, early 2000s or so or mid 2000, 2000s. There was no anomaly detection like that. There was no software that you had to code that to figure it out. That's really amazing. Yeah.

Georg Gottschalk: Ah, you see, that's where for instance, Lei came in for me. Um, interestingly enough, we solve serious, um, business questions. We help our customers, um, build, um, really complex processes, but we do so in an intuitive way, we do so in an elegant way. Uh, we are, uh, frequently rated as the most usable ERP for SMB in the marketplace against all our competitors. I'm very proud of that. Uh, but how do we connect that? When I joined Akumatica, um, I quickly realized we have an amazing team. We have amazing subject matter experts, um, we have amazing documentation, we have very, very, very good content, but it's not connecting with our end user. And um, that's when I brought in Leah, actually, um, learn experts in Ottawa, Canada. And my team is in Ottawa, Canada too. We, um, have multiple locations, but one of the locations is Ottawa. And they were already in touch with learn experts before I joined. Uh, the fascinating thing is that, um, it helped unlock that very, um, solid content that we already had and connect that, uh, when um, we formulated our new vision, basically fun, engaging, personalized education at scale, um, it was only made possible with, um, tools like Lehigh because we had the content, but we couldn't make it fun, we couldn't make it engaging. We're still working on the personalization. We have more to do there. But, um, that's really what, what it allowed us to do is to take solid, technically accurate material and make it fly.

Dave Darrington: Make it fly. Let me pause you on this here because I'd like to dig in deeper. What your vision is saying to me, this is a really good vision and it's also challenging. Uh, one of my most recent job history examples was I worked at Atlassian, where, you know, we don't buy Atlassian Jira Confluence. I mean, how can we avoid that? It's everywhere. Um, but then again, what, what you're evoking in Me is that we had millions of customers and different and partners and all this vast ecosystem that was really complicated. But there was a hypothesis that said, well, we can't really make that progress personal or we. And even there was this thrust to say, no, we should never say bespoke or never say custom. And I always said, baloney, no we can. But now we have to be smarter about it. We need systems to help us achieve those goals. And at the time we were starting to explore AI quite a lot. We had Rovo in house, which was our AI tool. Um, but I've had to fight those counter, you know, those, those headwinds to get to the personalized journey. I think that was really important because when I would, I worked as, um, prior to Atlassian, as a partner where I was articulating learning experiences that would go alongside implementations. And a lot of the times that got left behind we just say, well, here's everything, good luck. And what I said, no, I want to learn about your industry. What do you do? What are the workflows? How does this platform map to what our product can do for you? And that was often missed. And now I'm seeing with lie that now we have tools. I'd like you to talk more about that. Uh, how does a sausage made? How does that unlock the value in practice? Which I think this is a unique way to do it. I can do it with, try to do it with AI with CLAUDE and stuff, but I don't know if I'm going to be able to do anything as much as I could with this platform.

Georg Gottschalk: Yeah, I mean the difference when you look under the COVID uh, you have obviously a lot of capabilities now with AI. Um, we're using Claude and um, ChatGPT. Um, we're using a lot of specialized tools in AI as well. Uh, Leo being one of them. Um, but what you don't have is this embedded, uh, design mastery really. Um, I think for me Lyre is AI plus best practices combined. And that's um, telling you. Okay, when you um, you know, don't put this into a table, make a flipkart out of it. Um, just little tips and tricks and the ability to condense, uh, design elements, um, with your content together into uh, engaging course is very powerful. Uh, you mentioned certifications. Um, certifications are tricky. They're very difficult to do. Right. I uh, have a lot of respect for those who develop certifications. Psychometricians are involved. Um, that is, ah, as much art as it is science. Um, I remember a team where I had a double PhD working on this. Um, um, what Lingey does is these individuals are very, very specialized. They have a lot of in depth skills and knowledge and you take the grunt work out for them so they can really shine and um, really bring the value to the table. Where they've been most valuable was maybe 10, 15% of their time before and it's now 85%. So that unlocks an incredibly sparse rare resource for you and you can really do so. As an example, when you generate quizzes, um, the first couple of runs, it's just like when you generate any text with um, any of the AI tools, um, it's great but you notice immediately this is AI the way it's phrased, it's superficial. You cannot with AI create something out of nothing. You have to have a starting base somewhere. Right? Um, what Lei does for instance with quiz generation is it makes those specialized individuals who really know how to design certification exams, um, so that you actually m measure a skill and validate an ability of an individual. You make them effective because you don't have to create all these different ah, sheets of quizzes and all that. Um, you do it for them and then they can make their magic really work. So that's what um, I find fascinating and for me it's. The other thing is really bottom line, um, we would not be able to do what we are doing right now if it wouldn't be for like Lei for instance. When you look at um, where's our product going, more features going up like this, where's our resources going? You know we are public choir Laugh well you know, I mean we are uh, pe, uh private equity owned vistas, uh, um, our investor, very, very focused on AI and leverage and all that. Um, we're not going to be able to just hire our way out of the predicament that you have. When you have increasing um, functionality and basically uh, a steady state, um, resource base, there's a gap. That gap is filled because now I can start with 10%, then 25%, then 35% of the work that is um, machine doable in the end. Um, and um, have something like do this work so that the team that has this combination of unique insights, product knowledge and human ingenuity, um, really shine and build their value on top of that and have the grunt work taken out. Um, so that's where I see it help in the um, production process, in the content creation process, in also the validation process. The way that Acumatica does certifications by the way is very interesting. We CERTIFY companies, we don't have proctor certifications. We have a batch process. We get uh, individuals badges. But since we are uh, entirely uh, indirect in our um, sales process, we have an indirect channel we sell through our partners. Uh, we um, where we uh, have to make sure that these partners actually know what they're doing. Uh, um, by um, certifying that a partner is what we call gold certified, um, we know that not only do we know that they work with our customers the right way, our customers do so too. So they know that they can trust these partners to know what they're doing and um, sell them the right solution for their business needs. And that's what we certify that certify the capabilities of an organization, not just the abilities of an individual.

Dave Darrington: M.

Narrator: Do you ever feel like your product team ships faster than you can build training? Yeah. Me too. And that's why I've been checking out

Dave Darrington: what the folks at Learn Experts are doing.

Narrator: Their AI platform called leo, takes your existing content, docs, slides, wikis, recordings and turns it into full training programs publishing in multiple modalities to nail blended learning for your customers 85% faster than traditional methods. And get this, when your product updates, Leah can update the content faster by automatically incorporating it into your existing outline content and even your end of course test or exams. Learn Expert shares that their customers are reporting 90% efficiency here. Now that's time back to actually focus on strategy or let's be honest, to

Dave Darrington: finally take a lunch break.

Narrator: Plus it connects with platforms like skilljar and others so that you can publish straight to your academy without missing a beat. Check it out at learnexperts AI celab and see how you can keep your learning and test in release mode. Learn Experts build like an expert update like a pro.

Dave Darrington: That's fascinating. That's a little bit different and more nuanced than other places that I've seen, but it actually is again here I'm working to build that kind of ecosystem with our, with our partners. Now at Vast, I led the uh, Atlassian training partners program at uh, of course Atlassian Double Mean. But that, that's really sophisticated and hard. If those individuals are, those companies are certified, that, that is so much trust that we have now that I know. Okay. Yeah. And I want that as the company that's validating the partners and as the customer. So how, how important is that? One thing I wanted to go back to too is I'm sort of orbiting around the. But the um, the, the iron triangle of content development is something that you're is emerging out of this where you say, I can not just have one or two, I can have all three. And now you're unlocking the potential. What I'm hearing here, and this is something that's really helpful to me as well. I think everybody in the audience, I'm looking for platforms and tools that will help me build and construct that more customized, more personalized content, then also support the certification process. And I need to do it at scale because. Because what I found is when you get into an organization and you say, okay, I can just do certification myself. No, I don't need a psychometrician. No, I don't need a tool. I'm just going to sit down with Claude and I'm going to make question sets. Yeah, you can do it. But the one thing that Lehigh, uh, has brought to the table is that you're imbuing. Sarah and her team are imbuing that product with the best practices, with the knowledge of 20, 30 years of instructional design capabilities, so that now I can say, let's focus on not being, doing that process. I have a tool that I can trust and now that I can move faster and move better once I understand that tool and it can implement it. And now you're servicing and you're using. You were, you're an advisor there and now you're actually leveraging this, eating the dog food or drinking champagne appropriately. Say, this is fascinating and I don't want to focus on any numbers. It's the unlock the capabilities that you now have where, you know, I have subject matter experts that I work with all the time. And it's just really hard to go back to them and get all their time. When I can get them on stage, I can get them, I can drive them, I can shepherd them, I can work to push them to answer the questions that me as a education professor know we need to cover. But now they don't have to have that heavy load. Right?

Georg Gottschalk: Yeah, I mean it goes back to um, what we originally discussed, like uh, the complexities of the software and the business that we mirror, um, when you look. And that has nothing to do with our particular technology. We are an AI first, um, ERP provider, uh, for a certain market segment, um, that is actually growing really rapidly in double digits and all that. Um, but also with AI, um, when you look at um, AI, any technology as these platforms scale, the bottleneck to really succeed wildly is not the technology anymore. It's a human skill layer around it. And I used to joke the gap between what the platform can do and what the users are actually able to reach is where value goes to die. Closing that gap at ecosystem scale is what we really do here, what I do, and what Lehigh helps us do.

Dave Darrington: Wow. You know, I was at a con, I was in a, um, workshop last night with ATD here in Seattle. And this was actually the core of what we were trying to talk about, that gap where. And we're also concerned about keeping humans firmly in that loop and not seceding power to some kind of thing that's going to just generate slop or garbage. We shouldn't be scared of AI and tooling to be able to allow us to do more and unlock more. But we have to ride along with that. We have to find the best approved products and tools and approaches and to fill those gaps. That is, that is gold. I really love that.

Georg Gottschalk: And when you look at technologies like it's a connectivity, connecting tissue, basic connectivity between um, what your ecosystem needs and where you are, um, there's a huge gap there. Uh, so what we're doing right now is for instance, um, we are building the skill infrastructure of our ecosystem to make sure across, um, all audiences, from customers to partners, they are really good at what they're doing with our software. But the capabilities that we are building, um, when we looked at it is we walk backwards from the customer to where we are, our progress. And there is this huge gap, right, uh, uh, we have to bring it really back into where we were. We have this really, really in depth, sophisticated documentation and then we have this vast ecosystem out there. And we didn't really even have much of, um, customer delivery or customer training going on. And so we walk back. Well, between the customers and us is our partners, um, between the partners, NASA, our technical infrastructure and documentation. So, um, uh, once we derived that, we figured, okay, let's step it up, um, let's take what we have, make it better. We use layout for that for partners first. And so then we build out our partner education. And then we thought like, okay, well what we have could actually be really fascinating for our, uh, customers too. What is the one thing that we would really like to improve? Not burning the ocean, but where do we really hone in? We figured, okay, the first moment a user comes to our system, we want to take them by the hand and really train them at scale so that they know exactly what they're doing. Their first impression is really good, and then they can go into day to day and do whatever they need to do. Right. And so, um, after we build out Our infrastructure and we build our partner education. We building out now our customer education function. And um, um. Our first um, uh course for customer onboarding really uh came out in May, was widely successful. We had a certain amount that we wanted to get in there and we overachieved about 20x factor. Yeah, it was like. I was like oh really? This is cool. Okay.

Dave Darrington: This is hitting 20x of the materials and all the pieces and parts and the modules that you were creating.

Georg Gottschalk: Well 20x of our audience had actually involved um and um, we only were able to do that. We were able to um, come up with a whole host of content based on what we already had within a very short period of time, um, with the help of a lot of tools, one of which was Liai basically. But um, we didn't have to triple our team um for that which initially was kind of like what we felt we needed to do. Two years ago you couldn't do what ah we're doing today without a much larger team and now we have a very focused approach. But that um, you know that, that, that capability system that we're building um across customers through their onboarding and then beyond that um, for really adoption. Um so they get the ROI of their investment to our software and we get the benefit of them using it more and more and more. It's, it's another thing that differentiates Akumatica um by the way, you know there's as Apocalypse um talked about where um people say like we're your user base, you know and we don't need as many users anymore. Or that may be true for like um, um you know products like service cloud, um with Salesforce, but um ERP systems, the stronger your customers become the more transactions they run. And so we democratize access to our software right away. It's all always a site license. Everybody in our customers can use Acumatica. Um we only charge for what they actually use, um the actual transactions that are in the system. Um and based on that we have a bill of rights. Uh not only do we democratize that but we also teach them how to use it uh for free without charging. I used to run a lot of P Ls um now we really want to train them at scale, scale. And so that capability system allows complex platforms to grow through skilled partners, educated customers and also very quick go to market teams. And that's kind of the sweet spot where um, we're trying to operate now and where technologies um, um really help us. Technologies like lea help us to take what we have and connect that build, that last mile basically to our end users, but also uh, to m, our solution architects, to our um, business consultants to our developers. Uh, we have a partner only conference coming up in August, so inaugural Ascent. And um, that is for technical, uh, individuals for technical ecosystem, real hands on training for those solution architects, architects for the business consultants for the developers and also for our uh, practice owners and executives to come and join and really you know, supercharge their businesses.

Dave Darrington: This is so exciting because you guys, you've mentioned so many different audiences and roles and things. It's fascinating. The other thing that pops into my mind now, you talked about adoption which is onboarding. I like to call it everboarding too because we're always onboarding people. Um, but you've mentioned go to market teams. Within that is that marketing edge. How do you architect that adoption cadence of hey, you're a customer or your partner, we've got a new thing or how do I drive you deeper or along with little dosages, uh, across time are those things that are within your uh, remit?

Georg Gottschalk: Yeah, um, again it depends on your audiences. Um, we work in my area mostly with external audiences. So um, we're not the L and D department, we are the customer partner, education department. Um, so you have at its most fundamental the user of your software. Uh, that's the most basic because of the individuals who work every day, day in, day out on what, what you provide. You need to make sure that um, for them, it's not that, it's the, the, the technology that we provide is becoming for them, um, as intuitive and easy to use as, I don't know, brewing their morning cup of coffee. You know, um, it's, it's, it's literally that they don't even think about it, but that they think about, well, what do I need to do to serve that customer, to ship my bags of peanuts to, to make sure my racing driver really has the best helmet in case they crash. So um, that focus is what we allow by reducing the complexity for them. Um, but then also we have uh, the technical audiences, uh, solution architects for instance. Um, we used to call it technical sales or pre sales. It actually is prior to an implementation connecting the needs of the customer with the capabilities of the technology and finding that sweet spot, but also then being able to say no, this is not what we do, or this is not where you should use us, but here's actually where our technology helps you solve your business problems and makes you run better, faster, quicker than the next guy. And so that's A critical thing there. But then we also have our consultants, they help uh, from um, really being uh, on the strategic level for our clients. But um, bring it all the way back down into deploying our software, integrating it into other systems and then our developers, our developers um, most profit from the um, no code, low code abilities that we've built into the platform already. Um but they also do a lot of integration work. Build.com is one of our biggest partners. Uh bill.comm um has massive volume and we um, are uh, integrating a rapid flow of information into a back end ERP system that makes really their customers win as well. And so we are building all these audiences and the way that we can do this is by um, focusing on the business outcomes that they need to drive and walking that back in an outside in perspective to um, what does our product do and what do we have? Um, how can we build a release node that actually tells you this is why this helps you. Not like that was bad in the old product. No we fix it. But this problem you solve that way with our uh, technology.

Dave Darrington: Fascinating. I've loved how you have articulated this tapestry of different consumption consumers and different learners in your field and you've found platforms that have really helped you advance that, that have had AI imbued in them. I think the next question I have for you is what's next you as a thought leader, I've seen that you've been out there talking a lot. I'm inspired by listening to you because you're in such a sophisticated environment where it's challenging. Tell me about your future, tell me about where you're headed.

Georg Gottschalk: So um, when you, when you look at what we have always been trying to do in our industry, in our ah, um particular function, uh, where we are building these um, skill infrastructures out there across all these different audiences, we've always tried to make it relatable to the individual. Uh, we um, build foundational courses. Everybody has a getting started kind of course. Um, funnily enough at Acumatica and at Mulesoft that was literally called getting started. Um but um, everybody has that. And then what do you do next? You don't stop there you go, well okay, now you are started. Now you're becoming maybe um, a level one, a level two, a level three level. Uh, you're building up capabilities, um, or um, you're adding specifics. When um, you look at Salesforce for instance, you know, we um, know it's all AI but it used to be like you know, sales, cloud services, cloud Marketing cloud. Maybe you want to specialize in those areas or you're on the platform area or you're an admin. We had a lot of these accidental admins who just got into them and fell in love with platform.

Dave Darrington: Accidental admins. I love that.

Georg Gottschalk: Yeah, you know, that's, it was really a thing. Um, and they just couldn't get enough of it and they started to learn. And one of the mechanisms that Salesforce uses was trailit, which was really brilliant in getting those um, casual users becoming experts. Um, but um, in the end, um, you then have your industry verticalization. We are very strong in manufacturing, it's very different in construction. Um, and we're doing these industry verticals. Our partner thrives through micro verticals. Um, in the end it drives an ever greater personalization of um, your content to the um, individual. And where AI can go and solve this for us in my mind is the ultimate hyper personalization at scale, where you know exactly what this individual needs in terms of skills. Where you have like a radar image with peaks and valleys, uh, of that person because you know what the person is doing. You have telemetry into your technology, into your product. Um, you build that. Well, you know, that's where it's going. It's really not there in many cases. Um, but you know, that's where it will be in some point in time. Um, you combine the data that you get through telemetry. We see data that you um, get from basically zooming out and seeing your entire ecosystem and how it acts. And you're feeding that into AI and have AI hyper personalize what an individual needs to know tomorrow, not today, but tomorrow, you know, so you can make them ever better. Create this really broad skills infrastructure in the ecosystem and raise that up. We see help of AI on a hyper personalized level for each individual because in the end, you know, it's like fractals. Um, when you zoom out, you have a big ecosystem. Um, but when you zoom in, in the end it's about humans. AI serves humans, not the other way around. And that's where it's really strong, cutting edge AI technology with human ingenuity, that's for me the killer combination. And in a learning environment, an education environment, when I'm really enabling and building the skills in the ecosystem, I can make this super personalized, super fun, super engaging so that these individuals get really good at their jobs. You know, as a software vendor, you're all about your own software. That is completely not the point. The individuals need to get better at their Jobs, not your software. Your software is just an enabler for them to really thrive. And I think people forget that. You know, they get in, they fall in love. As a technology, it's really cool stuff. I mean at Ecumatica we're doing really cool stuff. Uh m. But in the end it's about that peanut farmer or the person who builds Basro, how they can build their business with our help.

Dave Darrington: This is, this is inspiring. This is inspiring because. And it's also cool because there's been a lot of folks who haven't put to connect the dots or fail to want to do that. I like how you're articulating how AI is in service of humankind. Right. And that is something that we own, we can drive, we can curate. For me, I've always been wanting to get to that personalization layer. There's a couple of questions that emerge out of this. One is. So then I would, I would imagine if so I talk a lot about product telemetry because I've fortunately been working at Gainsight and other companies where cool had that right. Where you have the product platform data that's atomized down to an individual, to a, to a cohort, to a company. And then I've had my learning management technologies, which has always been kind of extrinsic to that.

Georg Gottschalk: Right.

Dave Darrington: Myself, Salesforce CRM, I have all these other pools of data. Now you, I can tell by just talking to you for an hour and, and, and absorbing what you're saying to me, you've been in this whole space, you're seeing how these tendrils come together. So for you, do you have some. This is a little bit more technical. You don't have to answer this specifically just in generalities because we don't give away any sausage, how the sausage is made. But do you have a concept of a unified ID that gets that presents that into individual such that now that's in a tableau start or it's in um, a snowflake, you know, data repository somewhere where I can go, okay, hey AI, I'm constructing a course and I have an MCP connector back to this data lake or whatever. And now I can pool the cohort and make a cohort and then go back into LIA and other tools and be able to construct things out of that. You know, I'm just a little curious to go to just one layer deeper to see how you're making. You're making that happen.

Georg Gottschalk: Well, I mean in the end, um, where we are going is not just hyper personalization but also integrating learning into the workflow, into the product. Um, you know, it's something about doing. It's more than that. It's like, well, you need to have a foundation, right? It's like, you know, you're 16, you're trying to learn how to drive a car. Uh, you know, you, you may have been in a car, but you should know what the steering wheel is and what the brake pedal is and what that gas pedal does when you really hit it hard. Um, but besides that theoretical knowledge, in the end, you only get better in driving when you drive. And so, um, where we are going is the combination of hyper personalization and the ability of integrating into the product means that we can build learning into the workflow. Um, and when somebody is stuck, we can guide them right then and there when they need it, but we also can zoom out and we can give them the basics and the um, methodologies and the conceptual, um, skills. But in the end it goes in there and it goes hyper personal to the individual level, because that's where they are. But here's another fascinating thing, by the way. Tomorrow, um, we had traditionally, um, taught humans. We build enablement and education for humans. Well, guess what? We are now starting to look into how can we, um, build enable machines. Um, even two months ago, you know, um, ChatGPT was a chatbot then, um, with projects. You had more, um, like a memory function in there. So, um, it started to build, um, intelligence about you, not just the general stuff out there. Um, and then, um, everybody was, um, building GPTs. Well, you know what, um, this technology is so fast now. It's agentic. Um, and not just agentic, but you can create skills for machines, skills that um, are, um, teaching a machine consistently to produce better results. And we are thinking about how can we build these skills for machines based on how we build skills for humans.

Dave Darrington: That's amazing. I've seen that a lot. I mean, one practical example I think would be Claude. I'm in Claude, Cowork, chat, whatever. But skills are right there. I'm teaching my instance, my environment in Claude. I use cowork heavily. But then when I say, well, I've got a workflow and I can do these things, but I want to generalize this because it's repeatable, modular concepts. And now I'm. I love where you're going with this because that, that concept of teaching machine allows that the machine to teach others as well. So we've got that compounding lever for. And it's not dehumanizing because you're keeping the human in the loop to coach and to build that and you can, uh. And I'm wondering, uh, one of the things I've seen emerge is I'm in an application, I'm working with it, I'm stuck. I see that coach on the side of my screen kind of waver a little bit, pop it up, and I go, well, heck yeah. Did you know how to type? Type something in. I actually did this with Claude. Yes. No, this week because I couldn't get Claude cowork to work, right? And I engaged with their chat bot and agent and to learn some things. And in the five minutes I knew where the problem was and I didn't have talk to anybody. The agent was fluent and relevant and it solved my problem immediately. And that was a support thing where I used to be a customer support. I was customer success, customer support scientist of all things. And that was my job to really do sophisticated things that you couldn't do, but now that platform can do it. But then I start getting interested because once I solve some problem, then I'm, um, unlocked to do more things. And I'm right there at that point in time. So do you have like a intrinsic coach or some kind of tooling within the app itself that, uh, you know, feeds that curiosity or answers those questions or proactively pops up and says, I see, I see. Is it not Clippy, but I see your challenge. Look at this.

Georg Gottschalk: Yes, Clippy came to mind when I first saw like our, you know, um, AI assistants popping up everywhere. And it's like, hey, back to Clippy. Okay, fine. Um, it was actually pretty good. You know, Microsoft, I think, was a little bit ahead of its time there. Now, uh, we have AI assistants who are actually looking like, you know, a little pop up thing and it's all cool. No, but the thing is, um, we actually have a conversation right now, uh, where we are realizing not only, um, do we need to think about how machines learn, not machine learning, but like literally producing skill files in addition to, um, modularized courses, you know, um, because these skill files are basically teaching machines, like the modular courses teaching humans, um, but also how do we write this stuff? Uh, so, um, when. What we found is that when you write your, um, copy and you write your documentation, when you write your copy courseware, um, you optimize it towards human, uh, reading it. Um, but that's not how an LLM would read it. So now we have this conversation. How do we also produce content that is LLM readable? Because what you just Said is where we are going. Our customers are not going to um, just Google something. They're going into Claude, into Open, OpenAI, into GPT and um, Gemini and all the other that they may use in their um, environment. And they're expecting an accurate uh, response from the AI. Our job as educators is to teach that AI how that accurate response actually. Right. You know, and so right now what we have is I had a fascinating conversation with our machine learning uh, uh, uh, executive the um, last two weeks ago, I'm also in Canada. Um, he said look, you know right now AI gets about 60% right. Based on the really strong material that you do. If you even just get a little less precise in your content, that amplifies our failure rate and we drop immediately to like 30%. But our customers don't know that for them it's so transparent. And so um, the data and AI is powerful but the input that we provide is critical. And so we need to figure out how we not only teach humans how to use our software, but how do we teach the LLM to read the right way? How do we teach the machine to advise the humans who use our software the right way.

Dave Darrington: You're the first person I've talked to that have articulated that in such a, well, well defined way.

Georg Gottschalk: Well, thank you.

Dave Darrington: And something I want to expand on this just a little bit. I'm cognizant of time here. However something that has popped up recently is relevant to. Okay, I have to expand this a little bit. When I was working at Atlassian, we were looking at our engagement, our educational engagement over time, month over month we were seeing that engagement in our direct properties. Right. Our academy and university going down. And it took us a while to actually work with our, you know, our data scientists and team to actually formulate the right hypothesis. Why is this uh, why is this happening? Well some of the things that are emergent in is we've been seeing people create content about Atlassian, outside Atlassian, not within using our structures or maybe going through our training and then subsuming it and building their own. So what I've been thinking about, more of it really aligns with how you've articulated things. The concept of maybe an MCP connector.

Georg Gottschalk: Right.

Dave Darrington: We have these now for many LMSs where internally I can use that and get information about my, what's in there, how it unpacks, form files, do all this kind of stuff. But I think the next logical step is exactly what you're saying, where you're teaching computers AI how to process Them and be able to teach as a, as a secondary. They're a partner right in that, uh, educational partner. How is that conveyance going to look? And that, and what you said really means a lot to me because you're building models for AI to teach. So it's almost the equivalent of, hey, no, now I can create an MTP connector to Acumedica's learning and documentation and know that it's curated and it's the best of breed. Or Claude can just pick that up and say, oh, you're looking for information. I'm going to seek out that repository because I know you and your team have curated it. It is not wild field, kind of anybody built it, what we get on YouTube, but it's actually going to the heart. And that's a holy different kind of thinking. I, I, uh, commend you for that. That is really exciting. That's a huge takeaway. Thank you for bringing that to the attention of all of our audience and I'm really looking forward to seeing how you at Acumenica implement that going on. I'll be following you for sure.

Georg Gottschalk: Yes, it's, you know, that's the thing. It's. It really will not get boring. It's very fascinating. And um, I think for me it goes back to that, that, um, skill infrastructure, that skill layer, um, it's becoming ever more critical. Every technology that comes out right now has to build and skill infrastructure, a skill layer, uh, in its ecosystem. Um, because technology is going so fast. Um, and that's the other thing. You know, it's like, um, if you're building for your audience, if you're building for your ecosystem, um, it's not just anymore the um, Silicon Valley model of fail fast. Um, it is, don't even think about what you may fail. Just be fast, get out there, don't be afraid. Just do it, do it now. Um, see what resonates. Um, because tomorrow the world changes already. And just go and do it. Go try something. Don't be afraid. Just go. Do, do it, do it now and then. Iterate, iterate, iterate. Just crank it, you know.

Dave Darrington: And this was very prescient because just last night I was in this workshop with ATD folks and it happened to be Keith, who is with Acorn Learning, um, and he was so excited, we were all so excited because that word experiment, just do things and try and have that. And this is something that I would say, say if you're a leader listening to this, we need that psychological safety and space to be able, we're not going to fail. Right? We have a, uh, we have a lot more support structures. We have to try and we have to do so. That is one heck of a, uh, an important leave behind for our audience. Get out there and try these things, which is what the heart of the. That's why we call the customer education Laboratory because I'm a scientist trained, went to school for it. But that experimentation, that playing and trying to do things, I could see in your eyes and in your voice the joy that you have for and the excitement you have for learning still after a long career. And that fear of AI is starting to diminish as we see what's possible.

Georg Gottschalk: Right?

Dave Darrington: Wow. Okay, let's start leading out. We have so much. Thank you so much Bjork, for this time with you. I really, really appreciate and it validates a lot of things I've been thinking about that haven't been able to articulate and I think our audience will love it. Um, what are the things that, apart from LinkedIn, of course, that uh, we would instruct, um, our audience to connect with you on? Of course, go to Acumenica's learning site. Um, what other things would you like to bring to front?

Georg Gottschalk: Well, I mean what we do at Acumatica is really communicate with our ecosystem. Um, so look for our podcasts, look for our posts in social media and LinkedIn, um, and just you know, follow us, um, follow me, follow um, where the industry is going. We are, you know, when you look at the gardener quadrant, we always up and to the right and area. So I think we have a pretty winning combination here. We're growing at double digits, um, high double digits, um, year over year, quarter. And so that's really fascinating to see. And also um, you know, when you, when you look at um, across the industry, what um, did the big companies, the publicly traded companies are doing is really fascinating. You see um, them changing. I mean like, um, you see companies like Oracle almost getting out of the stock software business and into the data center business, you know, and um, very fascinating by the way. Um, you know, they Netsuite, um, is one of our competitors. They let a lot of people go. We welcome them, come to our partners. We need more people. We are actually investing in this. We see a tremendous growth. We don't, we don't, you know, reduce our size. We are growing, we're growing fast. And to those Netsuite folks, check out Akumatica Partners. We need you, we want you. You're welcome.

Dave Darrington: You know, Amen. This is so great. Again, thank you so much for your time and also give a shout out to Sarah Sedgman and learn experts, uh, for, for the audience. If you haven't checked it out, check it out. This is not meant to be just a testimonial. This is, this is a practitioner leader who's been using this platform and that's the other through line. Apart from all, all of the tips and guidance and experience that you've had Georg, that I m so much appreciate it and I know our audience will too. So um, with that I'm going to do the outro here, you know, and again, before that experiment, get into AI don't be afraid of it but listen to folks like Igor, Kara and others that have done that are really interpreting and guiding us. So once again thank you audience. Hey, if you want to learn more, you know where to go and if you don't, it's Customer Education is our website. You can find us everywhere. We're on all the pods, uh, Spotify included. Um, we are out there on LinkedIn heavily. So again, come to us, you can learn, learn from us, connect to your peers. And we're in particular looking for voices just like you, uh, to come in and talk with us and talk with everybody about how, how we're learning together. Special thanks to Al and Kota for our theme music. Um, and if it helps you out, give us a help uh, others by sharing our podcast. Leave a five star rating on Apple podcast dude. And it helps us so much.

Narrator: So to our audience, thank you for joining us again.

Dave Darrington: Get out there, educate, experiment, double, double, underscore that one and find new people. Thanks everybody. Thanks Jordan.

Georg Gottschalk: Thank you.

Dave Darrington: It.