How This German Founder Built The Nation’s Most Valuable Startup | First Time Founders with Ed Elson

Thanks for having me.

Came on the subway.

Mhm.

Yeah, I think that's where we started, right? That's, and we've built a lot more around it. We call it a process intelligence platform, so it doesn't just mine the process, it gives you real-time insights in it, it flags when things are going wrong, it helps you orchestrate and optimize processes. But you captured the essence of it 100%.

So when we started, we really—it started, we got fascinated by the technology. You know, we were all students at university and we didn't know much about business processes. And in some ways, when I look back, I'm happy how little we knew because we were naive, right? But one thing we did know, so first we got fascinated by the technology, and then we talked to some prospective clients and some, you know, the university had these businesses that you could cooperate with. There was all sorts of programs at the university to work with businesses. And we very quickly found out that processes are one of the most horizontal opportunities, right? They really are the fabric that run every business, right? The way you sell—I mean the way you produce this podcast is a process. Everything a business does can be described and expressed as a process. So when we look at a company, whether it's a bank or an automotive company or, you know, packaged consumer goods, we look at it as a collection of interwoven and interacting processes.

So I have two stories about this, right? One is the story how it happened, and then the story how we found out about it. So the first is the story how it happened is very simple. So my grandfather, you know, he was a farmer, and he grew up as a farmer, and then he had a potato trading business. He just passed away at 96 years old, so, you know, he got pretty old. So back in the day, you could see the whole process, right? You would go there, you could see potatoes coming, trucks coming, and everything being sorted, it's going out, you know. And if there was an issue, you could see it and quickly fix it. But then obviously companies grew much, much bigger than that, and you had ERP systems. You know, people said, "Hey, we want to digitize our processes in ERP systems." In many ways, these ERP systems, our processes had to fit these systems, so we had to fit our processes into these systems, which generated quite a bit of friction. And then you had more and more systems come along, so it doesn't just stay with the ERP system like SAP and Oracle. You had CRM coming along, you had the cloud revolution, you know, so you had CRM systems coming along. Then you had a lot of cloud applications, HR, IT service management. So over time, we added more and more systems. This really happened in the last 50 years, you know, sort of from the '70s, '80s all the way to today. And now companies have—you know, they have an ERP system, and I think on average big companies have over 250 core systems that operate the different parts of their business: supply chain, HR, finance, you know, inventory, warehouse management, you know, all sorts of processes. Banks, I mean, when I talk to our big banking clients, they have thousands. They're even more complex. And in many ways, our processes had to sort of be stitched together across all these systems, and then you have changing products, you have globalization, you have acquisitions. So over time, these businesses tend to get quite complex, and you can't see the process anymore because it's in systems, not like with my grandfather where you could see it. And in many ways, we also had to change our organizations, our processes to accommodate the way these systems were set up. So companies have a huge opportunity. We say that every process out there is waiting to be optimized. And now with AI coming in, you're going to have a huge wave of what we call process re-engineering, because you want to reimagine your processes in the age of AI. And we can talk about how we think it's going to play out and how we see it playing out. The story of how we found out about it is also quite interesting. So when we started, we actually thought the same as you. We thought, "Well, process mining is kind of an interesting technology, but that's a little bit boring." We were excited about processes, but we said, "Well, but if we could simulate processes, so if we could basically take the mining and then build simulation models where people then could say, 'Hey, if I hire like five people here or if I automate this, you know, how does it change?'" And we built a simulation product that was based on process mining. We took that to market; it didn't work because it was way ahead of its time. So we were about ready to give up until someone said—you know, we explained how the technology works and they said, "Well, this process visibility part, that's really interesting, right? That's where I would like to start." Right? And even though we do way more today, it's like we really found out, and that was a home run, that people need that X-ray of understanding exactly how their processes operate.

Often very successful companies with very high margin actually don't have very efficient processes, right? So you have that. I mean, we've seen crazy stories. One of our clients found out that they paid hundreds of millions worth of invoices twice.

Okay, by the way, a lot of clients do that. Usually it's more in the millions to tens of millions what you can save, but one was in the hundreds. It happens in every company. If you don't have a system, you get an invoice, someone gets a copy, maybe it gets into the system with slightly different data. You know, you are from the UK, so the date format is different than the US, so people type it the wrong way and somehow it gets in the system twice. The system thinks it's two invoices, they get paid twice. So that's just one example of a process that's ridiculous, but it happens. We see a lot of friction, or where companies really pay attention is friction in customer-facing processes. Like, you know, if it takes you days to book an order. We had one client once that was in a complex business, to be fair, but they on average changed the date that they confirmed to the customer 13 times.

So imagine that, right? I mean, they were very successful companies, so their products were so unique that customers would put up with it. We helped them fix it, but, you know, imagine on Amazon you get on average 13 emails, it's like, "No, we're not coming on Monday, we're coming Tuesday." You sometimes get those emails, but you don't get them 13 times on average. We have lots of customers that shipped products, but never invoiced them, right? So they had revenue leakage because they shipped products they never invoiced. We have lots of customers that negotiate contracts with their suppliers, but then they actually don't take advantage of them, so they buy off of prices that are actually higher than what they negotiated. So there's like, you know, it's a really exciting space because you can see the impact. And what's particularly exciting, you know, we do projects with Northwestern Medicine. They are looking at, you know, as patients go through the imaging, like a mammography or other imaging techniques, how long is the wait time, how can we cut that cycle time down, how can we make sure that we get it right the first time, what do the drop-off rates look like, right? How can we release patients out of the hospital fast? How can we move them through faster? So they started within finance and procurement, but they moved into the core medical operations. We have customers, a lot of government customers. Now we're talking about government efficiency. So we saved the state of Oklahoma, for example, helped them as they came in and said, "We want to really understand how are we spending money and where's money, taxpayer money, going out the door?" And they were able to save taxpayer dollars and get more transparency into that process. So we work with an increasing amount of government agencies and we're excited about how we can, you know, make sure that government takes better care of taxpayer money. So there is, you know, no shortage of opportunities.

Well, we hope so, right? And it's not just DOGE. DOGE is really facilitating it. It's the agencies on the federal level, the states, and it's really governments around the world that I think have a very strong interest. I mean, you know, with high inflation, with increasing debt, I think everybody has an interest to make sure that government money is spent transparently, efficiently, the same way businesses do. I think everybody can get more efficient. It's the same way that humans always get better, and the starting points are different for sure, but often actually the best organizations, you know, if you want to get better, if you're already good, you need the best and most sophisticated systems, right? So it's not that I would say we work with inefficient companies; we work with everybody. And I think that everybody has an opportunity to get better.

Well, I think one, you know, because you also want to drive impact quickly, right? So if you want to drive impact quickly, the first thing you focus on is where money goes out of the door, right? So you look at procurement, you look at invoicing, you look at the controls around that, all the money flows that go out of the door. How can we make them more transparent? Right? Where do we maybe have, you know, things that we don't intend to happen like that? Where's potential fraud happening? How can we increase the accountability of that? And that's a complex thing because, you know, on the federal level and then even on the state level, you have multiple payment systems, you have hundreds of billions going out of the door of the government every year. So I think that's where I would probably start. Yeah, but then you can get into everything else. I mean, you can get into labor efficiency, you can get into the efficiency of the core processes of servicing the citizens really in every single department, right? So you can get into really the cooperations of these agencies and that provide these services, right? Whether it's you pick up your new driver's license or you hand in a tax return or, you know, you can imagine the kind of use cases, right? As a citizen, you can really go anywhere.

It's a lifestyle that you have to embed. I think what some people think, it's like they are too on and off about it, right? So to your point, like, "Let's get a meeting, fix this process, and then never talk about it again," that usually doesn't work. It's more about how do you get 1% better every week. Okay, so, you know, one of the things I always tell our teams is, you know, we are really selling a lifestyle, and the lifestyle is called continuous operational improvement. How do you get better all the time? How do you find these increments? It's like the little changes that add up to really ultimately a revolution, right? That's really how you have to think about it. And, you know, the one thing who really figured this out initially were the whole culture on the Toyota quality management system, Kaizen, and optimizing manufacturing processes, because manufacturing processes is like you need perfect quality. It's very expensive if you screw something up. Like, if you have a car and you're missing one little screw, the whole production line stops, okay? So those companies invented this Kaizen lifestyle, right? And that's really not from a technology standpoint, but culturally what we are evangelizing. And when you think about it now with AI, that is exactly what companies need. Every company needs to embrace this, I'm like 100% convinced, because the way AI is going to manifest, you're not going to have this like one AI system. You're going to have lots of agents in your processes. So a company is going to have, I don't know, 100,000 employees and 100,000 agents, right? And these agents are going to automate little processes and things and tasks so that ultimately the whole organization is much more efficient. You know, one person is going to have way, way more impact and it's going to do way more. And in order to do this, you have to think of each of this agent as a small process change, right? And you're not going to do that overnight, and you're not going to do this with one big bang or one one-year, you know, sprint. You're going to do this by implementing this tool set, educating the organization, and really promoting this as a lifestyle where people are constantly automating, constantly optimizing, constantly embedding AI into what they do. And then, you know, two, three years later, they're going to be way more efficient than before. That's how it's going to work.

We have a big Celonis for Celonis program, and that's exactly how we approach it, right? How do we get better every day, right? Like, how do we make our customer experience better? How do we make our customer onboarding better? How do we make our customer support better? How do we really embed those processes? And, you know, for us it's challenging because we're growing so fast and we have grown so fast that sometimes you take the eye off the ball, even though you are, you know, the process company, you take the eye off the ball. So it's something we constantly remind ourselves and go back to.

We already see this, that organizations are moving from like very functional organizations—yeah, like think about the process of getting a lead, converting it into an opportunity, selling your product, shipping your product, maybe manufacturing it, and then billing it is called lead to cash, okay? It's a very important process. So today you have like a sales development team, you have a sales team, you have an engineering team, you have a post-sales team, you have deployments, you have invoicing. So it's like seven different departments or so that are involved in this. And what we see already is that people are embedding process owners, so Chief Process Officers or enterprise process owners for end-to-end processes. So what already a lot of companies are doing is that they're moving from a very functional structure to more of a process-centric structure of the organization. And as AI can automate more of those process tasks, that makes a lot more sense, right? So that you can really look at this end-to-end and say, "What's customer experience?" Because if, you know, I send them the wrong invoice or I provision the thing that they haven't bought, those breakpoints really hurt the customer experience, right? Customer experience is an outcome of a process, it's not just your product. So we see already that companies are sort of pivoting their org charts towards more of these process-centric structures.

I think the primary reason is the venture capital infrastructure. I think it's gotten a lot better, but the structure around risk capital in the US is absolutely phenomenal. In the US, companies that have a 10% chance of working out can raise $30 million seed rounds, right? Think about that. So people are willing to give a team that doesn't even have a product yet $30 million, and maybe it has a 1% chance of working, right? But there's so much capital that goes into technology and emerging companies that sort of on the whole that system works, right? Some people are more successful than others, but on the whole that's an incredible infrastructure that doesn't exist in Europe. In Europe, you have an increasing amount of venture capital, but, for example, when we started, we bootstrapped for almost six years with no funding. And part of that because there wasn't enterprise-oriented venture capital infrastructure, and the few VCs that were there said, "Oh, you know, you're early 20s, you're too young to start a B2B business, thank you," you know. And then we were just—we were fine bootstrapping, but that doesn't work for every company. So I think that is the primary reason. I think there are other reasons. Obviously you have a huge domestic market, so that helps. I think you have a very entrepreneurial culture, very good culture on failure. But look, you know, people talk about the entrepreneurial culture in the US. I mean, companies were started in Europe, right? BMW was started in Germany, right? There was an entrepreneur there that wasn't afraid of failing. And, you know, it's like I think that the cultural differences are not the biggest deal. I think there's a tremendous amount of entrepreneurial history and heritage in Europe, and a tremendous amount of great talent, right? You have a pretty strong education system. I think the top European schools are just as good as the top US schools, I think. And you can actually say that in Europe, education is more affordable and more accessible for people. So I think that the infrastructure around education, the talent in Europe is actually quite phenomenal. Could certainly be improved a lot, but I think that's not the primary reason. I think the primary reason is that the venture capital infrastructure is so much less developed. And for technology companies in particular, you need capital, right? It's a capital-intensive business; with AI even in some ways more capital-intensive. And I think that's the biggest gap. And obviously because we didn't have that, you then have the issue that you are really behind. So, for example, out of Celonis, you know, I get calls every month from former Celonauts starting a company, or I just actually put an angel check into one of them. And there's great companies there, right? I don't know how many of them will work out, right? But obviously these successes feed the next successes. And because we didn't have as much of that, you know, the US gets further and further ahead. I am bullish on Europe from an entrepreneurial ecosystem because of the talent, quality of life is very high. I think people want to live there, I think people from all over the world—still a very attractive place. So I think Europe has a lot of opportunities if Europe is able to use them. I think there's a lot ahead, but I would say the capital infrastructure is the main gap.

I think America is rich for sure, but Europe is actually also quite rich. So, for example, in Germany there's a lot of wealth, but that wealth isn't going into risk capital, right? So, for example, if you have a pension in the US, there's a high likelihood that a portion of that goes into the top VC funds. If you ask like the top VC funds, "Who are your investors?" they will say

Exactly, teachers' pensions, right? Right. In Germany, that actually used to be forbidden. Pension funds couldn't invest in risk capital. Right now they can, like a very small percentage. I think there's some changes, but it's a whole different scale. So actually, Europe historically was, you know, I think we're falling behind more and more. But there's a lot of wealth in Europe that could be directed to its riskier asset classes that just hasn't.

That's what everybody says. I don't know if I totally agree. I think, when you think about the founders' epoch in Europe and particularly Germany, there was a tremendous amount of risk-taking. You look at Siemens, you look at BMW, you look at BASF—a lot of those companies actually got started within a reasonably short time window. So it's not that like the cultural heritage is totally risk-avoiding. Certainly there's a different culture around risk, which is also not necessarily all bad, right? Some of the good US companies, they took risks, but they were also built on solid principles of entrepreneurship. So I wouldn't expect Germany to have been the leader in the early days of the crypto industry or something like that. That is certainly true; there's a more conservative mindset. But if you think about deep technology where you need to make long-term bets, you need to have an engineering-driven mindset, I think that Germany actually has a great heritage on that and there's a lot of risk-taking. I think that the system didn't enable it, right? Like if you say, "Hey, we can't invest any of our pensions in venture capital," how would you expect the venture capital industry to work, right? So it's not that there's like 80-something million people that are afraid to take risks. I think there's a system that didn't encourage people to invest money into technology ventures. And I think that is the primary challenge. SAP was bootstrapped, too, right? And that's been a long time ago, obviously. That was a different time; venture capital wasn't a thing then. But still, that was the last big German technology company that went public and went on to be successful, and there hasn't been any really big successes since.

Yeah, exactly. And the car companies got started way, way earlier, right? So hopefully that changes, but I think the culture and attitude also has strength. I don't think that's the main reason. I think the system is to blame in these other European countries, too.