The History of Business Process Optimization With Heymen Jansen, ABB

Hey there, you are listening to the Mining Your Business Podcast. It's the show all about process mining, data science, and advanced business analytics. Yakub, are you excited for today's episode? Hell yeah! Heyman Janssen, former Group Vice President of Process Mining at ABB and Consultant for Business Process Transformation, joins us on the podcast today to share with us his wealth of knowledge about process mining and the journey he took to get here. Let's get into the episode. Hello everyone with another episode of Mining Your Business Podcast. And in today's episode, we're going to have here another heavyweight representative of a company, and also a person who, well, arguably, is one of the, well, responsible people for why me and Patrick are even doing what we're doing because he has been there for when process mining was still in, you know, in its early phase in the diapers literally, and helping bringing up this amazing technology, an amazing way on how we can analyze our processes and look at how our businesses are run, and that is Heyman Janssen. Heyman, welcome to our podcast. Thank you. So, Heyman, you, as I said, you've been around for a very, very long time and bringing this process mining into, into motion with your previous employer in ABABA, but obviously your journey originates even further down the road. And when we were talking as a part of preparation for this episode, I have to say it was quite a journey for you. And how you basically went from a chemical engineer into, into helping organizations such as a ABB, putting process mining into generating value. And therefore, could you introduce yourself a little bit and tell also our listeners on what brought you here and at what phase have you, like, I don't want to say, saw the light, but when you finally, when you got for the first time in touch with process mining. Yeah, sure. First of all, Jacob, thanks for having me here, because I'm very much delighted, you know, to share my story, like I also love to hear two other one's stories, because you always can learn from that. I mean, just a quick one on myself, I'm in Yeltschum, Dutch, I have been in process mining for quite a lot of years, I will talk a little bit later about that a bit more. At this moment business transformation, also oftentimes, still working with companies on advising them on how they can implement their processes and improve their processes with or without process mining with automation and so on. And I still am, you know, very much delighted to do so, because process improvement is my thing, continuous improvement, it's really a joy to work with people on that. But of course, there's much more than only a process mining, so let me talk a little bit about where I started, and then we're talking about the 70s. The listeners cannot see the color of my hair, but they could have, then they sure would have known that I'm in the business already for a quite a long time. But before we go there, when we were preparing this, then I thought, you know, what makes it not only, you know, for the last 50 years, but even further down the road, what actually, what we have seen is always that people have been looking for smart solutions to make their life easier, you know, it could be at home or it could be, you know, in the industry or in the factory they are working. And let me start with the story of my father. My father was a fisherman, and we're talking about the 30s of the last century, so 1930, and they were fishing with sailing boats. And for those listeners who know a little bit about sailing, well, important for sailing is that you need to have wind. And if you are lucky, the wind comes behind, or aside, and not is in front of you. So as a fisherman, you want to get as much as possible fish as possible in maybe a few hours or anything, but that's a part one. Part two is you need to get back to the harbor to sell the fish. And you know, sometimes you can have a lot of fish, and then suddenly, you know, there is no wind anymore, and then you are in deep trouble. And of course, and it's still the same with modern technologies and modern businesses. The ones who is first on the market, yes, the best price. So what those guys did, without any technology, or you could even say, maybe it's technology, but very early days, they had a pigeon, a dove, a pigeon. They used, they put a note on the pigeon, Mr. Jensen and so many kilo fish of this sword and that sword, the pigeon went to the market, the market knew, okay, Mr. Jensen has fish. I want to buy it because I have a restaurant and it needs to be fish in the restaurant tonight. So this is a typical example of how to manage network capital in a very easy way. So before the fish is actually on the table in the restaurant, it's already sold. And the cash is there at the moment that you're unloading the fish. So that's one example. Another one, I don't want to make it too long, but another one was, it was maybe ten years back, I was in which, in Poland. That's a city well known because of his industry specifically for cloths, for weaving. Which is quite dangerous at that time, we're talking about late 1800s, no electricity but gas lamps or oil lamps for, and of course with cotton and so on, highly dangerous for getting the whole factory in fire. And then I saw a very ingenious sprinkler system, even before the name sprinkler was there. They had water pipes in the whole factory. On top of the roof there was a kind of a big swimming pool for water, for rainwater supply. And there were small holes in these water pipes and they were filled with bebecks. So at the moment there is a fire, the bebecks will melt and the water will get out of the small holes. So a super efficient, let's say, sprinkler system, then a little bit less back in the past. So I started in 1970s as a engineer, I'm a team engineer so I was sailing on the big oceans, working in a machine room. And that's, I think, I mean, I was 18, 19 years old when I started. I think that was the first time that I saw that technology and specifically micro technology came into the play. Normally you would be in the machine room together with your other engineers for 7x24, always people there to check temperatures, to check pressure, to make sure that you're not getting stuck somewhere in the middle of the ocean. And then I saw the first sensors, monitoring pressure, monitoring temperature. So that was the first time that we were moving from completely manually managed machine rooms into completely automated machine rooms. So we had, instead of 38 degrees in the machine room itself, we were in an air conditions, control room, working from 9 to 5, everything was managed by sensors. So that was already a big, I would say, a huge impact on the life of, let's say, a sailor doing, you know, a 9 to 5 job instead of, you know, working in the middle of the night and having four hour shifts and then, again, again, four hour shifts. So there was a huge difference. And then later on, I came to work in a test laboratory for microelectronics, totally different world. And yeah, like I said, I already have a gray, almost white hair. We were talking about, we were talking about the time that we were testing 256 K memories. And we were very excited that we were in the middle of moving to the one megabyte. And so you can see, you know, it's a totally different era, but we saw, you know, technology is going very, very, very fast from 256 to 1 to 4, and so on. And there we implemented a completely paperless autoflow system. So everything from order preparation, planning, the testing itself, electrical test, burn out, text again, including the marking of the devices, including the print out of the test report, it was completely paperless. I remember in those times, we were also working for a region. So that was, let's say, a military act that we got some, some visits from the audit visit from some U.S. generals, and they didn't accept that we didn't have those stamps on the paper. You know, electronic signature, they didn't accept that. Now they sure would do, I think. So you can imagine then moving from completely manual, let's say, order management into completely paperless workflow was again something that was only possible because you had then the first EAP systems were coming. And come to think of that there are still some companies that are even today not completely paperless. Yeah, I know, that's quite interesting actually. And then my next step was moving into industry in plastics, rotational mulling, setting up the first EAP systems, ISO systems, and so on, and also the first robot. So that was, let's say, in around the 90s. And then I made the move to an EAP company, and that was 1996. And then we were implementing what we called dynamic enterprise modeling, because we said, you know, EAP systems is fine, but nobody of the business understands actually an EAP system. We need to make it visual. So we started to model our software in terms of a process. Right. And so the first thing would be, okay, what is your company? Are you in make the stock, are you in engineering to order, are you in aerospace and defense or in food and beverage? So making the profile of a company. So if you are in make the stock, you probably don't need engineer. So we would model, top down, how should we configure the software? So the process was visualized already in the software itself, but also configured by the software itself. It was a big step, because now you could talk with business people about their business process instead of about tables and fields and so on. And that was quite a nice thing to do, that was in late 90s. And then I also understood how important it is to make the bridge between business and software and IT, you know, because there's always this gap. And then also the same company, we started to monitor processes from customers remotely. Normally, you would go as a consultant to the customer, you travel, you have lots of, say, discussions, interviews, meetings and so on. And then I was able to already extract the data remotely from the business. So when I moved to a customer, I already knew a little bit where is the issue. That was also a big step, of course. And then, yeah, then when I joined ABB, then I was hosted by a factory. In Germany. And as you know, as one of the process mining companies was also located in Germany. And still is. And there are my colleagues were doing some pilots on process mining. And so I had a global role, but I was hosted there, I saw it and I was directly, okay, this is it. It was for me absolutely, you know, there was no question about it. This is what I always have on it. And then we started the first pilot in our division on improving network capital. So they sales outstanding, they spurges outstanding inventory turns and so on. And that was quite a success. And then we said, okay, let's roll this out within the division worldwide, together with another division. We did that. And then we're talking about 2016 or so. And so in a very early days of process mining, actually quite, it's actually quite fun. I mean, I didn't have a clue about process mining. And they didn't have a clue about the business. Yeah, it's the ideal combination because then you can work together, you know, if you trust each other, we say, okay, you know, we do not know anything about the technology of process mining, but we are very eager to learn about, but we of course will explain, you know, how is our business running that is, of course, part of the deal. So that was a quite nice experience. And then I was asking 2017 to start off a global practice. So in 2018, I started and then we started also to roll out process mining on a global level in all the units and all the countries and so on. That's a brilliant introduction. And again, it's just a super interesting to hear about this journey and about all these places and all these areas that you managed to interact with. And eventually bring up or formulate and accumulate these ideas into then transforming the business where you were at a later stage of your career. And I have a lot of questions actually and one of them already comes to this time of when you were saying that you were digitalizing this order process that it was not, it was paperless, basically you made it paperless. And I wanted to ask how do you look at the difference between the actual technical implementation and the transformation of the mindset of the company because you know, you can implement a lot of things technically within a company and there is a lot of cool stuff out there. And we are, I mean, we are living in the age of AI and in robots and everything. So implementing things is one of things. But then transforming the company using and leveraging these best practices, these technologies, I guess it's a whole different story. Yeah, that's correct. And I can say many things to that. First of all, I mean, if you are in a technology engineering environment, I can tell you those people, they love tools. And so that is probably then also the reason that we had a lot of tools. So that's the first part, you know, it looks good, you know, you think the tool is going to solve my problem which is of course not the case because you need always to solve the problems yourself. The only thing is with the tool, you can do it maybe in a more efficient way. So let me first tell about, you know, what we try to do at the moment that we were starting to roll out process money. So we said, okay, we have a good continuous improvement culture, which was actually the case. Years on years, you know, build up an organization for continuous improvement, including people who were dedicating every day in a factory or in a service center or in the sales office, using their time only for continuous improvement. And that takes time of course, has nothing to do with tools it has to do with, you know, creating a mentality looking to continuous improvement, which means that at that time we put targets on finding waste. There are a lot of companies who call that, let's say, costs of poor quality. We thought, you know, there's a much too negative call. So we called it opportunities for perfecting quality, basically finding waste because finding waste is not a shame. With finding waste, you give people the opportunity to to continuous improvement because you're never done. And that gives a positive attitude to the people working on solving issues, finding waste and solving waste. We put targets on that so that also people were measured on those components finding waste and solving waste, which I think was a big success. And then of course, the next step is, okay, if those people are busy with taking waste out, improving quality, improving efficiency, lead times, inventories, etc, then we should give them the right tools. And at that time, but I'm quite sure in a lot of companies exactly the same also now. A lot of things done on Excel, a lot of things on, you know, getting data out of SAP or Oracle or whatever and then put it in Excel and then combined it with another Excel. And so what we saw, if you, we were following a lean six sigma, so the D mic cycle, if you follow the D mic cycle and you don't have any data, then 60% of the time you're using with data crunching, which is also a waste, because you want to use the brains of the people, you know, to solve the problem, not in crunching data. And so we saw an opportunity in using process mining, because you have granularity of data to the lowest level in the organization, up to the highest level in the organization. So easy to find, okay, what's the impact on the country, on the factory, on the business unit, on the division, up to how is, let's say, the order flow or how are the inventory transactions managed. So you have full transparency, which can help you a lot in preparing, first of all, where is the low hanging fruit, you don't want to spend four weeks on investigating something which doesn't make any sense because it's almost perfect. So you want to have a low hanging fruit and you want to start the improvement itself as soon as possible. So getting inside as soon as possible is to know where do I focus on. And then making the analysis, I'm talking now about root cause analysis, which is then already more or less prepared with the process mining tools, that shortens the whole d-mic cycle. So the idea was, okay, if we were talking about 7,000, 8,000 projects per year, which is a lot, if you can improve that, for all those people are working on that, and shorten the d-mic cycle with a couple of months, there is huge value in that. And besides that, you're motivating people because they are doing what they like, improving things, and not planting data. That actually brings me to a question and that is, that not every organization, at least for my experience, when we start working on these projects, and we bring this technology and bring these ideas and we are trying to push this mindset of continuous improvement, not every organization seemed to be ready and in prime position to start doing that. And very often, what then happens is that they are surprised, okay, now we actually need to invest into resources to be even able to do that in these departments. And my question would be, what would be the recommendation for you, for these companies that are, let's say, at the very beginning of this journey, who still receives their processes as perfect, that they don't have any problems, and trust me, there are companies that think really that their processes are efficient and without bottlenecks. And that need to get over this big hump first of thinking, okay, we actually need to invest first to start re-eping the value later. That's a great question, I mean, I also know that there is still a lot of all school thinking. So I guess it also takes time, and this can take maybe even a generation. But things are moving fast, and I think there is, at least if I talk with my peers of many other big companies worldwide, I think there is at this moment more sense about using data and analytics, at least for supporting the business. So I think it's improving a lot over the last years, also because, you know, process mining technology is quite new. So I mean implementation in the business started, we started in 2014, and then we were really one of the earlier adopters. So I think there are still a lot of companies just starting up. And of course you need to first use the tools to get insight in what can I do. It is an important element, and that's of course trusting the data. And we have also seen that, I mean, we've seen that we need to involve all the people in the organization, from top level to shop floor level, to make sure that they are involved in implementing the software. So they need to validate their own data, because it's basically the purchase order or the sales order they are responsible for. It should not be a top-down approach by, okay, I see that something is wrong here. Please solve it now. First make sure that they see that the data is correct, and also the root cause analysis makes sense. Because otherwise you can get a lot of push back. And since we were coming from manual reporting and moving into using process mining as the single sort of truth, of course we saw a gap between what was manually reported in what we saw. Not necessarily because we were seeing the truth, but because you know, we needed to validate both insights in how these KPIs build up. And so we moved together to each other. And that was really important because then we also could take the conclusion, okay, maybe it looks worse than we thought, but at least one where we are, so we can improve again. So again, a positive attitude. And that was important because if you don't do that from the start, also later on for later implementations for other process domains, you will have the same issue. So gaining trust is important then regarding management. Yes, of course, management may be data and analytics in general and process mining specifically is new. So I think the first thing which you can do, and you can do that maybe in a pilot or so or a pilot implementation is creating awareness. So and after creating awareness, creating sense of urgency, youth audit, it was all okay. We see that there is still a lot of improvement potential and we see actually there is a lot. So there is something to gain and I think that is the way to make sure that you get all levels in the organizations you get into the play. Now with someone like yourself with so much experience in the process mining space, and I think a lot of people, whether it be the owners CEOs or department heads or whatever, maybe thinking is process mining right for me or is process mining right for my business? Can you tell us based on your experience what are some of the key indicators that you would say makes a company a perfect candidate for using process mining and using it effectively? Yeah, thanks for the question. I mean, in general, I think process mining is good for every company. But of course it needs to make sense. I hope you can sort out your own problems in this team. So you need to have a kind of a size. And I'm talking about the size in terms of employees. I'm talking about how distributed is the community. So are you working in one site, in one country or across the whole globe? So their communication also plays a role. And of course also the size of the data. In my last experience, we're talking about in 2018, 19, about 50 terabyte of data, which is a lot. So you're talking about millions of transactions per day, which means that it's just impossible to do that manually. It's impossible to take a look at 60 million order lines to find out, okay, where is your initial? So you need to structure that, and that is why process mining is there. And the word itself says it already. It's deep down under and you need to mine it. You need to have tools for that. So it's something which you cannot see on the service. You need to go deep, but you want to do it in a very efficient way. So on the finger click. And that's why I think that process mining in general is suitable for any business, any company, any type of industry, whether you are in manufacturing or you are in, let's say, food beverage, banking, whatever. That's a, thanks for that. I had a follow up to that. So is there maybe also a cultural aspect to some of these requirements, like can you tell based on some of the, a lot of the clients that you've worked with, if they're culturally ready to take this process mining step? I didn't see, actually, I didn't see any resistance. So in principle, I think all people are embracing the concept of process mining. I think where the trouble starts is that a company say, okay, I love the tool. I see potential, but how am I going to address my issues? Because it's not only the tool, of course, you also need to have people who are driving not only the chain, but also domain experts who know everything about order management or purchasing or supply chain or whatever it might be, because they need to use the tool to make the improvement. So it's a combination of getting transparency by a tool, which is fine. Having people on board who can make the analysis, so typically black belts, master black belts, and so on, they can drive, let's say, the improvements. And then making the improvements happen, it means that in programs or projects where you want to tackle a specific issue, you need to have domain experts, process managers, process owners, together with application owners, together with data analytics, people to drive, let's say, the improvement itself. I'll just make a comment on Patrick's previous comment, whether every company's process mining, well, we are a 50 people company now, and let me tell you, we could probably improve some of our processes ourselves. Yeah, we are using process mining, actually, yeah, we're being a process mining company, we should probably work on those as well, get rid of the bottlenecks. I actually had a very interesting thought when I first talked to you, and that was, I always saw a good result of process mining, was being able to generate some value and get some money back. While I'm starting to switch this mindset a little bit into shifting away from generating value, not the saying it's not important, it's still, you care about the money, obviously. But I also, also, and almost see a good result of a process mining initiative within first months and years, when you are able to trigger a lot of follow up projects, basically, you go into the data and you have this moment of clarity when you're seeing, okay, so we really have to do a lot of work. And therefore, not everything is easily, it's so easy to put a number on. You can't always say that if you improve here, this is going to result in 10 million savings, although sometimes you can do that. But I almost see, and I think we are in alignment here, that this result of a good process mining initiative is you get this mindset going that I need to improve, and for that, I need to run a lot of projects to get these improvements in place. Would you agree on that? I guess so. I mean, I think it's kind of a mixed back. I mean, you're not going to get a huge amount of money from the management. If you cannot explain that there is some value, the other question is, what is the value? Of course, there is a value in, let's say, taking a cost out. And so, there always need somehow, how there needs a component so that you can show that we can basically reduce cost or maybe support growth, or it can also be two things at the same time. Now, what we did in the past is this mixed back. There were, I think, quite some obvious cost out elements of which we said, okay, this is fully agreed. So, even when we only would work on this topic, could be very, very small, like, for example, missing cash discounts. Right. So, it's very simple, it's a very small scope. You know, okay, this is the volume of missed cash discounts, we're going to work on that. So, at least, you know, we have a full payback of the software and including the organization to run it. And then is the second element, but what you are addressing, I think, I absolutely agree on that. There is also another value. For example, we followed a little bit, a lab breeding approach is setting up all kinds of analytics, nobody asked for it, or maybe just the person in the organization was asking for it, could be, you know, a black belt or a master black belt. Could you help me to improve this or that? And that help us a little bit, if that was potential value in a certain process domain to explore with process mining. And we're also pilots, just, you know, we stop with it because there is too less value, but doing a lot of different, let's say, investigations, where is value in an organization that is already a value in itself, because you want to find best. And you don't want to say, okay, I only have a problem in here. And that is what I'm going to explore because you don't know that it's only there where you have a problem. You could have a problem somewhere else, where you never thought about it. And I've experienced that also in life that, you know, I thought, you know, oh, I've got a long experience in process improvement, I never would have thought that we would have an issue here, you know, and that is also, of course, direct value and, of course, supporting and driving a continuous improvement culture and organization. Now, in regards to, I mean, all process mining implementations take time, take money, you know, capacity away from people to help implement all these things. Is it a hard sell then to say, okay, we have looked for waste to eliminate and we turns out we don't have any. So this is good. I mean, it's one of those things that, yeah, it's good to know that we don't have waste, but we have implemented this process, which took a lot of time and money. Is that a hard sell to some sort of superior? I would have loved over the last 45 years to tell my boss, all the problems are solved. But unfortunately, when you have solved the problem and other problem comes because we are in a dynamic world, we are changing our product, we are getting new customers, we are getting new suppliers, we are migrating ERP systems all over the place or buying other systems. So there is never, and I would not say unfortunately, but there is never a time of moment that you're done. So I do not think, but if there are any listeners on the call who said, you know, I've done it in such a perfect way that after two years, we have divested process mining software because we were done, let me get me a call. So I have one more question, and you mentioned that you usually focused on this waste reduction. What I'm curious about, how you technically tackled that, like you, let's say you starting with some of the processes, be it ordered to cash, be it something in manufacturing, then you implement it and then what did you and your team technically do to start addressing and start looking for these waste? Was it more like you talked to the business and they told you, or you should probably focus on this and that area, or where you actually this hardcore data analytics team that went into the process explorer and started, you know, convey all these different variations and possible bottlenecks that could have occurred in the process. Now, I think you do it from both sides, so you need the data and analytics guys because they know the technologies, they know how to extract the data and to model the data to show something and you need the business process experts owners to explain what kind of issues that they have and hopefully you're coming together there. And of course, it always starts with the basic setup of a data model and of some analytics and then the business says, okay, that's cool, but I also would like to see it from another angle. Maybe a modified software in such a way that I also have this other angle, but it's always a combination of people doing it, by the way, of course, we were not only focusing on continuous improvement, but for example, also process automation, and so if you talk about the bottom-up approach we took was kind of a power to the people. So we are giving the experts our continuous improvement leaders, black belts and so on. We get them better tools, so that we get the benefits out of it. More from a top-down perspective, we were looking for, okay, how could we improve our overall supply chain, reduce overall lead times in our supply chain, which is quite complex. A lot of countries and factories are involved in it, in distribution centers and front and sales and so on. So that's the other side of it, and that's of course much more an approach of looking to your footprint, looking to how can I improve the end-to-end supply chain from a feed effect through to the end customer, and then you talk about much higher volumes and you're not so interested anymore in a single customer order or a single purchase order, but more in your logistical flows across your company. One of the things that I also found very interesting when we had this first chat a few weeks ago was that you mentioned that while working for ABB and trying to, you spend a lot of time basically preaching for the technology and making sure that it actually flies, and you also said that it wasn't always just this straight line going upwards, that it would just be going better and better by week and by month, but there were also, and that's actually Tim O'Peteer saying there's this despair wallet that sometimes you just go down and you have to almost start over, start getting this support again. How did it look for you when you started growing the initiative? Yeah, you're quite right, and I have bad and sweet memories about those times. Sometimes, I had this great feeling idea when somebody was just getting the story and starting with it, even when it would only be somewhere in one location, and also those moments that I thought I looked like Martin Luther King of process mining, spreading out the gospel all over the place, and telling people I have a dream and so on, and they didn't get it, and so what I can tell everybody that it's just hard work, but it's not only with the process mining that's with everything in life, but if you believe in something, then I hope that everybody also gets the energy to do so, but it is really hard work because you need to convince all levels in the organization about the value, and that some people, we're skeptic about it, I actually do not blame them, because if you do not know what it is, it's very hard to get what is the value I can get out of it. So I think if you want to convince people in a step on board, at least you need to make sure that they understand what is it actually, and that's an important thing. So from your experience, what has been the best way to show people what process mining is, do you use some sort of demonstration and proof of value, or how do you do it? Yeah, of course, very small projects, bigger projects, and so on, so on the small projects, it's just by giving support and coaching people, that is, I think, very important. So you want to help them, you know a little bit how the technology works, so you can help them in solving their day-to-day business issues. So that is, if you talk about bigger implementations, like for example, we started at that time in measuring all time, believe me, lead time for the whole company, then you're talking about big programs, and then you need to have a structure in place. So like we said about a governance board, all the business areas were represented, both on the business side as also from data and analytics side, so that you have a governance structure in place, maneuvering your program from, let's say, a group level, down to a local level. So it's not only, you know, preaching and spreading out the gospel, it's also structuring the way how you want to make change. Now you speak about structuring, and I can imagine that if you worked in ABB and that's a massive organization with a lot of teams across basically the whole globe, I know we could probably go for hours just talking about how to set it all up, but what were some of your best practices on how you set up this data analytics team in a way that it was working efficiently and possibly as far as possible? I probably only can talk about experience and all about plans, because when we started, we didn't know anything. I must honestly say, I think we were a little bit lucky that there was already recently a pilot being started up in Germany, and there was a center of excellence for ERP. So a couple of guys from that center of excellence were being created as a kind of a team who did also process mining. So learned a lot about process mining, and in the meantime, you know, also doing projects on ERP sensor. I think we were lucky on that, and that was also the reason when we started the global road out, we said, "Okay, let me use that team. Let us use that team." Because it takes a long time to build up knowledge. And why throwing away that knowledge and starting all over again? So that's the reason that we started with a very small team, in doing the first projects in one division and the other division, and then after a couple of years. And I think the team was mature enough to also do the global road out, and build the data models and build the analytics themselves. And I think a very important element of that was that those people were also used to do global projects, all a specific domain, for example, implementing Salesforce, implementing SAP, or implementing all kinds of other things, workflow systems, service now, and so on. So that is already a good combination of people, where at least you know, have a huge experience in talking with business people about business problems, being trained in the beginning on how data and analytics, and specifically process mining works. But it was really a journey, going hand in hand, and learning by doing. So not a specific plan, let us set up a center of excellence, and this would be the skillsets of the people and so on, absolutely not. Right. Now, a little more personal question I would have, and that would be, "What are you particularly proud of on this journey with process mining, would you be able to pinpoint some of these moments?" And I'm sure there were many. But some of this that you say, now looking retrospectively, "Wow, this was really really cool." And I was just happy to be proud of it. Yeah, thanks for the question, I mean, we have worked very, very hard over a lot of years. And like I said, you know, it goes up and down, but what I think, where I'm proud of is that in the beginning, it was just about process transparency, creating awareness. What is the potential, and then everybody has this wow effect. And now, I think, and my successor is doing it in a perfect way. Now Shawn, okay, we are moving from reporting to descriptive analytics to prescriptive analytics, so making the move in a more forward-looking way. So looking to risk in process, using machine learning technology, using automation in the processes, action, engine, and so on, now moving into, let's say, really the steering view in the organization, how to guide people in what are their highest priorities for the day. So basically work flow management, still making sure that the people can make their own decisions. But giving them much more information about what potentially goes wrong, or what are the priorities for the day, and I think, I'm quite proud of that, that despite also, you know, disappointment we had in the past, it goes up and down, like I said, that now we have already evolved from, you know, just showing, okay, how bad it is, our good it is, into moving it into process execution. Now you have witnessed the infancy of process mining to where it is now, and you've also mentioned a few things, like prescriptive process mining and things like that. If you were to take a guess at what will happen in the future, what do you think will be next as the big innovation in the process mining field, what do you think will have the biggest impact? Yeah, it depends, of course, on, because business improvements, that's actually where I started. People always are looking for improvements, and the tools are making the improvements possible. So it always will be something, you know, business triggering the tools people, you know, I need to have this, and tools people making it possible for people to achieve something. It's for me, it's very, very difficult to answer. I know that in 2019, 2020, I start to think about a digital twin of an organization, together with Gardner, and, you know, conceptually it was all done, and even, you know, in 11, 5, it was all working perfectly, and last year I saw that when I was on a Ceylonan's event that this process sphere was launched, and I thought, okay, this is what we were working on in 2020. It was technically not possible yet to get real time. I mean, you know, connected sales, purchasing, inventory, management, production, and so on, now it's possible. So that is already, you know, a big achievement to make or dream through, which we had already in 2020. And then, yeah, what will be next? I do not know, but for sure, I know that a process automation will be much more integrated in process mining, that is absolutely what will happen. Because it makes a lot of sense, why have different tools for finding, you know, how the process should work, and then another tool for automating the process, doesn't make any sense. The same is for replanting, and process mining will also be more and more into one technology. Why should you have a different tool for reporting performance, and another tool for improving performance? So it doesn't make any sense. You should be always be on one single sort of truth, source of truth. And so I'm a firm believer that all those tools will grow together. Secondly, and that's not an easy task, I think, but what I think the future of process mining will also be in task mining. And this is really super complex. But it will come. It will come somehow, because at least, you know, we are not interested all only in, you know, having a kind of a feel about, you know, how a process runs, you know, you want to know how you can people, how you can make people more effective in their day-to-day work. And then you're talking not about an EAP system, then you're not talking about Excel, you're not talking about Salesforce or servers now, you're talking about a person on this computer. And that will take some time, I think. Yeah, well, I would say if you know an expert in task mining, please recommend, because I don't think we have covered this topic quite well at all, Patrick, have we? We have done an episode in depth about it, so I think it's really important. I actually have one person who is there, an expert, yeah. All right, and let's get back to that later, so that also maybe our audience is then surprised if we bring on the board. Either way, Hey man, we are coming to an end, unfortunately, but my last question would be, where can people find you to eventually reach out and find out more about you or get in touch? Yeah, of course, and I don't know if you are sharing that as well in the podcast, but they can reach out to me via LinkedIn, of course, and that's probably the most easy way to find me, and then I can make sure that I can contact those people for any of this question. I'm absolutely open for anything, you know, if people want to have the files or they just want to have a brainstorm or whatever that might be, you know, I'm absolutely volunteering to help people in this space. We will for sure post the link and everything on our social media and also in the description of the episode where you're listening on Apple podcasts, Spotify, or on our website. Hey, man, all I have to say now is big, big thank you, not only for coming to the podcast, but also for what you've been doing for the community and for the whole process-mining world, because as you mentioned, you have been one of the pioneers, and if there wouldn't have been success with ABB, maybe there wouldn't be the show about process-mining today. So thank you very much. It's my pleasure, and I will continue in spreading out the gospel. Please do. Perfect. We will try our best to do the same, but we are doing decently because, well, looking at the numbers of the podcast, it's super nice to see that people, such as yourself, are listening to us. So thank you for that. If you have any question, you can also find us on LinkedIn. You can also drop us an email at [email protected]. We will be very happy to hear from you what you think about the show, if you have any ideas, any guest recommendations, we are always open to that. So thank you for listening. If you like us, leave us a rating, and tune in in two weeks for next episode of Mining Your Business Podcast.