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Dr. Patrick Lechner

Head of Process Mining, Robotics Process Automation (RPA) & Low-Code/No-Code

BMW

How BMW aims to leverage automotive process mining and AI

In an era when businesses are pressured to enhance efficiency and embrace sustainability, process mining and artificial intelligence integration have emerged as pivotal strategies. For BMW Group, automotive process mining is of key importance moving forward.Companies these days must seek to get the most out of their data that they can. But organizations with the right data must also optimize their processes, according to Patrick Lechner (pictured), head of process mining and robotic process automation at BMW Group.Patrick Lechner of BMW Group talks with theCUBE during Celosphere 24.“At BMW, we saw that only with optimal processes can we win, we can be the leader in our field,” he said

play_circle_outline Driving Success: Process Mining, RPA, and Data Optimization at BMW

play_circle_outline Scalability and growth of process mining at BMW

play_circle_outline Challenges in bringing different groups along in process optimization

play_circle_outline Future goals include digital twin, broader user base, and AI utilization.

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Dr. Patrick Lechner, BMW

Dr. Patrick Lechner

Head of Process Mining, Robotics Process Automation (RPA) & Low-Code/No-Code BMW

The Celonis community in Munich, Germany, hosted a segment featuring Patrick from BMW, discussing the importance of data and optimizing processes to stay ahead in the industry. Process mining has been successful in various departments at BMW, enhancing transparency and efficiency. BMW's Center of Excellence focuses on operational excellence and process optimization, with over 1,600 users benefiting from Celonis tools. The challenge lies in scaling the implementation internationally. Patrick emphasized the importance of flexibility in using AI tools to drive o... Read more

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What does process mining look like at BMW? add

What is the current number of users utilizing AI technology within the organization and how has this number grown over time? add

What approach did the IT guys take to convince the experienced paint shop employees to use process intelligence tools? add

What advancements in technology and processes have been made at BMW to optimize every single process? add

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Dr. Patrick Lechner, BMW

Savannah Peterson

>> Good afternoon, Celonis community, and welcome back to Celosphere here in Munich, Germany. My name's Savannah Peterson. Delighted to be bringing you our final four segments of the day with my co-host, Rob Strechay. Rob, it has just sped on by, hasn't it?

Rob Strechay

>> It has. It has. And we get our musical introduction to this. It's like we cranked up the music in the car with the top down right now, going down the highway.

Savannah Peterson

>> That's exactly... What a great analogy, Rob.

Rob Strechay

>> Thank you.

Savannah Peterson

>> And what a nice segue into introducing our next guest, Patrick from BMW. Thank you so much for taking the time to hang out with us today.

>> So great to be with you. I'm really looking forward to it.

Savannah Peterson

>> Yeah, you've had a busy day. You've been doing some presentations. You're in charge of process mining and RPA at BMW. You're a busy man.

>> Yeah, but it's really fun. And I've been responsible for the process mining at BMW for seven years now, and every single day, you learn so much new stuff. And here, you also meet so many nice people that you have met before. And it's like coming home.

Savannah Peterson

>> Oh, I bet it is. And I bet it's great to see your community. So, break it down for us, because now that we've got the audience's attention, everyone's a BMW fan. I know Rob's a BMW fan, I'm a BMW fan. We're not just saying that. What does process mining look like at BMW? What does your day look like?

>> Yeah. Here, at BMW, we realized that data is really central. And getting the best out of data is really crucial. So, if you have the right data, you also have to optimize the processes. And at BMW, we saw that only with optimal processes we can win, we can be the leader in our field. And therefore, it's really crucial to combine data and processes the best possible way. And we really managed to do that in the last couple of years. And we have started basically in the main processes, like engineering, like production, like customer support, but we've grown since. And now, for me, it's really working with the different business units to understand, what are their needs? Whether they maybe have pain points with the processes. How can we help them to create transparency end-to-end of their processes? And this is really the exciting bit.

Rob Strechay

>> And I think part of it is that you said that before this, that every car is basically touched by Celonis in a way that the process mining works across all those different divisions. What is it that the Center of Excellence that you need really focus on in helping the rest of the organization out?

>> In our Center of Excellence, we have got the operational excellence, we have the tool excellence, and we have process excellence. And this is really what we-

Savannah Peterson

>> All the excellences, yes.

>> Yeah. We try to really bring this to our customers, to our end customers. And we work together with so-called Centers of Competence in the different clients' different business areas, to be able to excel for them, to really help them to get the best out of their processes. And this is really, I think, a key factor for us, that we have got this central theory where we can basically see, okay, where do we have to go? Where can we get better at BMW, and how can we create this transparency? Because, the automotive world is changing so fast, and the nature of change has changed. So, we really have to adapt constantly to new competitors, to new demand from the outside world. And this is where we help our businesses to get even better.

Savannah Peterson

>> And just to add some data to the scope of the amount of processes and different things you're getting data from to optimize, BMW shipping 2.5 million vehicles worldwide. You have 30 production sites, and you've got sales in over 140 different countries. That's a lot of data.

>> Absolutely.

Savannah Peterson

>> How do you prioritize which processes you optimize when using a tool like Celonis?

>> Yeah. Yeah. We really look at, where can we get the best business value out? So, we look at, how big is our process? How much is there potential to improve? Also, where do we have, maybe, targets to achieve? And how can we help, with tools like Celonis, to achieve those targets? So, it's really talking to the business, evaluating their processes, and then deciding where to go. And this is, of course, together with our business experts, because they know best. They know their processes, and they know how can we help them.

Rob Strechay

>> And you talked about, before we were on here, about how you actually brought some of the business users that are here, actually talking this year. What are some of the improved efficiencies that they are realizing, that got them excited to come here? Because you start to talk about it, and it's like, it's nothing if you can't hear from the business side of why they embraced this. Because change is not always easy for organizations.

>> Absolutely. When we started in 2017, just to give an example, we started in the plant here in Munich. And they had just introduced a new paint shop, and they were looking at, how can we improve our paint project? It was the most modern paint shop in the world, but of course, when you start a new technology, there is always some things that don't work smoothly yet. And we said we came there as IT guys. We said, "We can help you. We can help you to understand your process." And this is really what happened. And they were really excited about it. And, yeah, after some time, we managed to extend this to all the plants. You mentioned those numbers. We are active in all regions now with this process intelligence, this process mining. And this is really where we have to go. So, we start. We're looking at a small use case, to see, how can we help them to improve, in this case, this paint shop? And then, see, how can we make the process transparent so that people really understand and they can communicate? Process mining, for me, is also language. So, normally, you only know the process in your small segment and you optimize your small segment, yet you never look at the process end-to-end. And this is really where Celonis comes in. We can really make people talk to each other, from purchasing, from customer support, from production. They speak the same language, they speak process language, and they can understand and optimize the process end-to-end.

Savannah Peterson

>> I love that you just titled it that, process language, across those 30 different plants. These are in different countries. Everyone's speaking a different language natively, probably, in these use cases. What does the upskill process look like internally? How has adoption been? And how do you teach each one of these unique environments to leverage Celonis?

>> Yeah. So, we really give them the right training. So, we have two approaches. We do self-service, so people can really use Celonis as a self-service tool. And we also help them to adapt by giving them implementation support. So, both is possible. And we have so many different people. You have someone from financial services, you have someone from production. And they think very differently, so we offer their dedicated support in the way they need it and they want it. And we also see the cultural differences, of course. So, some people are maybe a bit worried that we might do naming and blaming, which we don't do. We really want to optimize processes. And we don't want to blame anyone for things that maybe don't work right, as long as they really want to improve and get better.

Rob Strechay

>> So, again, back to what Savannah was saying and what you were saying, it's a worldwide implementation. And to get to that scale, how has it been to scale that up? Because you have a lot of partners, you have a lot of data, a lot of different environments around the world. How did that scaling across your entire environment go with Celonis?

>> We started with two user licenses, so it was really a very small start. And now, we have already more than 1,600 users. And we are growing much faster because now, what we have is AI, gen AI. And so far, we mainly use it for experts, for people who understand the tool, who want to use the tool in the right way, and who are somehow also a bit into IT. But now, we also have the possibility to go for every single BMW employee. And processes, these are not just about experts. Everyone is having processes every day, and we want them to improve their daily work. And also, when it comes to data, we have got a so-called Cloud Data Hub at BMW. So, a central data lake, you could say, where we store most of our IT systems, our push IT systems. And these also have to scale fast because now, we can access the data. There's data in a great quality, and we can implement our use cases much faster than we could in the past.

Rob Strechay

>> So, it would seem like, because you just brought up AI and, of course, you can't go anywhere and not hear the words AI right at the moment, how do you look at AI? And to your point, there seems to be a flexibility to how you can use Celonis to influence agents and copilots and things of that nature. How are you using it? How do you look at it?

>> I think this is really the important thing, that we have got this flexibility to use it in different ways. So, we are using the Copilot, but we are also using the interface, the API, so that we can really use those agents in systems or in models that we had before. And so, I think this flexibility is very important for us. So that for each use case, we can choose the right way to use it. And yeah, it's really working fine. We have already implemented some first AI use cases, so gen AI, but also other AI use cases. And we are really happy so far with the results. And I think there's a lot of potential soon to come.

Rob Strechay

>> Yeah.

Savannah Peterson

>> How does the driver benefit from all of the hard work that you do, both leveraging AI, but in general, optimizing these processes? Is it lower prices? Is it more efficient supply chain, more reliable vehicles? Talk to us about the human benefit.

>> I think all of them. For us, the customer is always in the center. And we always try to optimize our processes, so that we have happy customers. And this is really important. So, in production, we ensure that the quality is perfect, that the production times are optimal. So that also the cost can be reduced, that we reduce energy consumption, which is also, of course, important if we have the sustainability. But we also look at the customer journey end-to-end, to see, how can the customer get their car faster? How can we improve the quality for the customer, the customer experience, to really have happy customers in the end? And this is really crucial for us. Of course, we also do process mining for our colleagues, for our employees. But in the end, it all has to be for the customers, so that they have better experiences with BMW.

Rob Strechay

>> So, how did you bring along the different groups? You talked about paint, and the paint is very specific. There's chemicals. There's all kinds of stuff that goes into that part of the manufacturing process. How did you bring them along, where they're not experts in process mining? They may know their process, but they're not experts in the technology side. How do you bring somebody? And it could be another group. I'm just using them as an example.

>> That's really a challenge. Those paint shop guys, they have been working in the paint shop for 30 years, some of them, so they know really all their stuff excellently. And then, they know what to do. And we came in as IT guys and we had no idea about the paint shop. So, for me, it was always, "Yeah, it's quite easy. You bring the car in and you take it out and it's painted." But it's much more complex. So, we really had to convince them that this tool can help. And every BMW employee is different, so you really have to approach them and understand their needs. So, we normally get their data, do some first proof of concept and show them what is possible. And then, they come up with so many new ideas that they want to implement, that they want to do. So, it's really a bottom-up approach. We don't force anyone to use process intelligence, but we give them the tool, we enable them and show them, "Okay, it's a great benefit for you, you get insights. And maybe also you get data insights." So, there was an issue before they knew about it, but they could not quantify it. With Celonis, for the first time, we can really say, exactly how much benefit can there be if you improve this process in this and this way? So, this is very important for us.

Savannah Peterson

>> That's got to be really fascinating, to go in and learn from those vertical experts. Now, I'm just thinking about the material science and the complexity of paint, and the conditions in the factory. And to really think about, I bet you'll get to solve problems you didn't even know existed, or overcome challenges that you wouldn't have even thought of.

>> Absolutely. And once you have got the data in, they come up with so many ideas. And for us, as IT guys, it's so much learning new stuff. So, every day, we meet new people, we meet new challenges. So, yeah, it never gets boring. It's just processes sometimes sound quite theoretical and quite boring, but it's not at all. Because you work with people and you try to help them to solve their problems. And this is really what drives me every single day.

Savannah Peterson

>> I got to ask, what do you drive and what color is it? Since we're talking about paint color, now I need a visual of your vehicle.

>> Now, I've got an X3.

Savannah Peterson

>> Sweet.

>> And it's a silvery color, so really, really nice. And yeah, I enjoy driving it every day, so it's good fun.

Savannah Peterson

>> That's awesome.

Rob Strechay

>> No, I think, to me, that's the whole thing. It's about the people and how to show them how this can help, and how it's going to bring them to the next thing. What do you think is the challenge that you see next? Is it AI, that how do you better use and use cases for AI?

>> There are several things. First of all, so far, we do process mining within the company. For me, it's also, we also have to do process optimization with our suppliers, with our dealers, and so on. So, it's also important to do this first, company process mining. This is one next step. Also, one other next step is to get the best process with the help of AI. So, really to help the people who are maybe not the biggest experts to understand, how can we improve the process? What are the next steps to take in an at least semi-automated way, so they are faster in getting those challenges, and that they are faster in adapting to those challenges that are in the outside world? Because I think this is really so crucial for the automotive world, that we are the first ones, the fastest ones, and the most agile ones.

Savannah Peterson

>> Well, we're excited to continue to tell that story. And speaking of, Patrick, this has been awesome. It's flown by, even with the live band in the background as our accompaniment for this ride. Final question for you. When we have you on the show next year, same time next year, what do you hope to be able to say then that you can't yet say today?

>> Yeah. I want to say that we really do processes end-to-end, that we have a digital twin that really helps us to do this end-to-end, look at process mining. I also want to say that we have extended the user base even further, using these new technologies like AI. So that really, we are a tool for every employee at BMW to optimize every single process. Also, in process areas where we are maybe not so strong yet because it's a very IT or system-agnostic tool. So, we really have to use it in an even broader way. I think we are in a good way at BINW, but there's always more potential. And I'm very happy to do this and achieve this potential with our colleagues and our end users.

Savannah Peterson

>> Awesome, Patrick. Well, we can't wait to hear all about it this time next year. Also, can't wait to check out the number one most visited place in Bavaria, aka the BMW Museum. I know Rob's been there.

Rob Strechay

>> It's fantastic. It's just such history, rich history. Just awesome. Love it.

>> Great.

Rob Strechay

>> Love it.

>> Great to hear. No, it's a really good place.

Savannah Peterson

>> You all are selling me on a new car.

Rob Strechay

>> And the café right above it has great coffee. I was very happy about that, too.

Savannah Peterson

>> What a fantastic anecdote.

Rob Strechay

>> Yes, I-

Savannah Peterson

>> Patrick-

>> But nice to see you back there.

Rob Strechay

>> Yes.

Savannah Peterson

>> Yeah.

>> So, maybe next time we will run into-

Rob Strechay

>> Yeah, we'll connect up.

>> It would be nice.

Savannah Peterson

>> It sounds like we all need to go get a coffee and check out some BMWs.

Rob Strechay

>> Yes.

Savannah Peterson

>> Patrick, thank you so much for taking the time to be here with us. Rob, thanks for your insights as always.

>> Thank you so much.

Savannah Peterson

>> And thank you all for your wonderful attention that you've given us all day today here at Celonis Celosphere in Munich, Germany. My name's Savannah Peterson. You're watching theCUBE, the leading source for high-tech news.