Process Mining leader Celonis has evolved its solutions into an advanced, AI-enhanced Process Intelligence platform, presenting a living digital twin of any company’s end-to-end processes. This is yielding significant cash impacts, much smarter execution, extra resilient supply chains and and more in the mix during this great discussion with Celonis Chief Evangelist Dr Lars Reinkemeyer – please watch below and read on!
In business since 2011, Celonis has helped more than 5000 of the world’s biggest and best companies improve process efficiency, yield impressive cash impacts, improve customer experience, and reduce carbon emissions. This has been achieved with industry-leading process mining technology and AI, leading to process intelligence, giving everyone a common language for how the business runs, visibility into where value is hiding, and the ability to capture it.
A great example of the Celonis platform at work is with the world’s favourite producer of kiwifruit – New Zealand’s Zespri – which has saved millions of dollars through the Celonis solution. This includes a reduction to its Vendor Invoice Management (VIM) cycle time by 27%, purchase order conformance increasing from 65% to 88% in 12 months, credit memo clearance improving by 68 days in 2024, and the identification and prevention of potential duplicate spend among other benefits you can read about and watch here in my virtual fireside chat with Dave Scullin, the Chief Digital Officer at Zespri, and Pascal Coubard, the APAC Sales Leader at Celonis.
So, what exactly IS process mining, and how did it evolve into process intelligence? What impact is modern AI having, and how will process intelligence continue evolving?
To get answers to all these questions and many more, I spoke with the Chief Evangelist of Celonis, Dr Lars Reinkemeyer, whose 2020 book titled “Process Mining in Action: Principles, Use Cases and Outlook” is not only a best-seller, but which now has a sequel, titled “Process Intelligence in Action: Taking Process Mining to the Next Level”, which combines Lars’ 10-year experience in this field gained at Celonis and Siemens, with 12 best practice use cases from international companies representing multiple industries and domains.
Lars is no stranger to Australia, having worked here during his time at Siemens, and he’ll be back down under in mid-October for the 20th Annual OPEX WEEK: Business Transformation Summit, held 14-16 October 2024, billed as “Australia’s No. 1 Event for Transformation & Operational Excellence Leaders”, where he will give the keynote presentation on process excellent, while also meeting partners, customers, and prospects.
Lars will then travel back to Munich, where he will be part of the Celonis team hosting the company’s annual Celosphere conference, held October 22 to 24, billed as “The Ultimate Process Intelligence Event”, which I will be attending as a guest of the company.
To learn more, our video interview is embedded immediately below, after which is a full transcript of our discussion, so please watch – and read on!
Here is the full transcript of our discussion!
Alex 00:00:07
Well, hello, and thank you for joining me for the Alex on Tech and TechAdvice.Life video interview. Today, I’m joined by Dr Lars Reinkemeyer. He’s the Chief Evangelist at Celonis. Welcome to the program.
Lars 00:00:20
Thanks, Alex. It’s a pleasure being here.
Alex 00:00:22
Thank you for taking the time. Now, Lars, before we continue, can you please recap the Celonis and the Process Intelligence story?
Lars 00:00:32
The story with Celonis started in 2011, some 13 years ago, when three students came across a great innovation from a professor in the Netherlands, which was called CrossMining. They felt this kind of x-ray of business processes has huge potential. So, these three fellows went around and spoke to some companies. And initially I came across them when I was at Siemens.
The idea of x-raying business processes, understanding business processes, understanding where a process goes wrong, is very powerful. So, we started more than 10 years ago with the first use cases, looking into where processes are broken, where processes are delayed, where processes are causing a lot of effort, manual effort.
And across those 10 years the whole capability has been through an amazing evolution in the sense of, not only identifying where a business process is going wrong, but also becoming a kind of virtual assistant where the system itself does help people to identify, but then also to remediate processes and make life much easier for people. So, across those 13 years,
Celonis has taken quite a steep evolution. Today we’ve got more than 3,300 people around the world, have a valuation of $13 billion, and take pride in our customers having confirmed more than $5 billion of savings.
Alex 00:02:00
I can remember when Google first launched its Google Desktop for Windows, and it was a way of searching everything on your computer as easily as you could search everything on Google on the internet. And it was sort of an example of this whole digital transformation which we’ve heard about for the last decade.
But process mining is, I guess, on that particular path, except even earlier, taking advantage of all the benefits of technology to be able to look at a whole swathe of information by extracting a lot of insights very quickly for the benefit of the company. And I mean, you guys have been ahead of the curve for a long time.
Lars 00:02:38
Absolutely. Let me give you one example. One of the first things which we did at Siemens is that Siemens was very much into process modelling. People designed the process as they’re supposed to. And then with process mining we compared and said, hey, look, this is the process how you assume a purchase order, a customer order is going through the organisation.
And this is a reality. You never know. And people were blown away since we saw that we have like 900,000 different process variants how a customer order can go through the organisation from an order intake until Siemens gets payment from the customer. So, it’s like Googling the processes.
It’s like visualising what’s really in there, making it convenient for users to see the full complexity, and then obviously saying, okay, so what? What do we do with that? And how do we improve that to make processes much more efficient? And how can we help companies to work with this insight, to define, to take defined actions, and ultimately also improve and realise value with the insight which we’re providing.
Alex 00:03:40
Now we’re going to talk more about process mining and process intelligence in a moment, but the title of Chief Evangelist sounds like a dream tech job. I mean, I want a job like that, right, except I sort of am, except for my own little piece of the publishing sphere. But what does that mean you do on a day-to-day basis, and what does this mean for the future of the company?
Lars 00:04:03
Yeah. Absolutely. I’m really happy to have this role of Chief Evangelist – if you love what you do and do what you love, I think it’s the best what you can accomplish. Basically my mission is to help companies with the experience which I’ve gained across more than 10 years with Celonis, with process mining, with process intelligence, and to help companies how to apply this amazing capability.
My mission is to speak with companies, advise companies, coach on their transformational journey, help them to use the technology in the sense of driving action and impact across an organisation.
My mission is to speak at conferences and basically evangelise on this whole capability of process intelligence, on this whole capability of Celonis helping companies to identify where a process is broken, to help them to improve those processes, help them transform processes from manual touches towards high degree of automation, from a lot of rework towards high efficiency, from a lot of approval steps which many companies find hard to remediate in those kind of approval steps and making the life smoother and easier for people.
In essence, as a chief evangelist, my mission is very much to bring the capability to the people, to the customers, to the organisations, and not only the technology, but also from the operational side, how to adopt it. In my experience, technology is one pillar, but the other even more important part is to drive change and get adoption across an organisation as an evangelist.
I share a lot of experience which I have, how to engage with a sponsor, how to build an operating model, how to get this whole motion into an organisation that people adopt the capability and then drive transformation across the organisation.
Alex 00:05:55
Now as you’ve explained, you’ve been around process mining for a long time, you were also doing work in this sphere for Siemens.
So how did you get involved into that? Was that something you were introduced to at Siemens? And what’s the short version of how this capability has changed over the past, I guess, 20 years since you were first introduced to it?
Lars 00:06:13
Yeah, it seems as though I came across it more than 10 years ago when I was in charge of business intelligence at Siemens. And I felt it’s a different capability, since it’s not about data analytics, it’s not so much about reporting KPI like there’s other capabilities like Tableau, QlikView, SAP Analytics Cloud, whatever you name it there.
But I felt like with process mining, you can not only see the process inefficiency, but you can also remediate, you can improve, you can help the people be proactive by showing them this is the process where they have a delay, where they have an issue which caused a lot of manual touches, and then help them to improve those processes.
So that’s where the journey started 10 years ago. And initially, we looked very much into short-term, long-term, seeing what’s going wrong and then in the later years we started alerting people, supporting people to do their work more efficiently.
At Siemens I established a community of more than 6,000 active users across the whole value chain, from procurement, finance, manufacturing, established a cohort with some 40 people. I think it’s been an amazing support for transforming Siemens from a lot of manual inefficient processes to more high efficiency and it’s been a great experience for me working for that company.
Alex 00:07:35
Now your first book was Process Mining in Action and you followed that up this year with the release of Process Intelligence in Action. What’s the difference between the two concepts?
Lars 00:07:48
I think the main difference is very much the evolution from process mining like getting the insight and seeing, oh, there’s something happening, towards bringing in additional intelligence and not only alerting people. People are saying, hey, there’s something going wrong, but also enabling them with proactive support in executing things smarter.
As an example what our process intelligence platform does is that it brings up payment blocks or delivery blocks or late payments, and then that’s something which we show to the users like every morning or a couple of times per day where we bring that to their attention.
And then with the kind of batch processing, they can just click and execute to remove the payment blocks, the delivery blocks, or make the payments right away there. Helping them to make their work smarter. And that’s where we bring the intelligence into the platform and where we leverage the insight provided with process mining to allow people to work in a smarter and more intelligent manner.
Alex 00:08:49
Yeah. Well, I mean, we’re going to talk about artificial intelligence shortly, but clearly we’re living in the era of things being able to be autonomous and much smarter. It’s only natural you’ve gone from process mining to process intelligence, and in your latest book there are 12 use cases, including Siemens, where, as we’ve discussed, you’ve worked for a long time, but also Bosch and BMW, PepsiCo and Reckitt. What are some of the most interesting findings that you can share, without giving the entire book away?
Lars 00:09:20
I think the three key takeaways are, first, that this whole process, intelligent process mining, is not a one stop. Siemens has shared a chapter, an experience, in my first book three years ago, and they’ve again written a chapter here which shows the continuous innovation and evolution for such a company as Siemens, where there’s always something new, there’s always a new edge, how to use the technology, for example, for resilient supply chains.
In the first book they wrote about the pure auto-processing, and now they’re writing about a much more… or end-to-end process on supply chain and how they’ve been able to build a resilient supply chain across a global organisation. That’s one key topic. Second key topic is that in the second book, supply chain is a major issue.
Supply chain has been a key challenge for many companies, specifically since COVID, and where companies like Reckitt and Kimberly-Clark and Siemens share how they’re using cross-intelligence to build a more resilient, more efficient supply chain across complex global organisations. And third key point, which is probably different in the book, is that it has a much stronger focus on value.
How companies can realise value by using the process intelligence capability, and which also indicates the evolution of what we’ve been seeing there from getting the insight and saying, hey, I’ve got great transparency, towards driving action. Okay, now, what do people do with it? Can I move on?
And now also measuring tangible value by allowing people to see where can I avoid duplicate payments, where can I identify payment term deviations and remediate these, how can I improve my data sales and so a whole range of different value drivers where we have taken a strong journey there towards advising companies how they can measure and realise value by applying the capability of Celonis.
Alex 00:11:31
And one of the recent interviews that I did with your colleague Pascal Coubard and one of the executives from a New Zealand company called Zespri that grows the famous kiwi fruit that they sell around the world and they’ve been using the Celonis platform and they’ve, had millions of dollars in savings after applying the platform and this platform supports many areas as you’ve described, digital transformation, system transformation, the supply chain and you just explained a little bit about this but I understand that supply chain is up to 60% of the work that you do for clients.
So why does the platform have such a big impact on the supply chain?
Lars 00:12:11
Supply chain is a key topic. As you know, companies are really struggling in getting, first of all, transparency across their supply chain. And we can help them with what we call an object-centric process mining, which allows companies to define one object from customer order to manufacturing to shipping to invoicing to have one stringent object, which goes across the whole complex supply chain. Siemens, for example, is processing more than 30 million items per year.
And if you imagine the supply chain, the complexity that they have from customer order intake, to manufacturing, procurement, logistics, and then also the invoicing. This whole specific core supply chain there, it is massive. And lots of inefficiencies where you have overstock, where you have late deliveries, where you have a lot of manual touches, reworks, so a lot of inefficiencies.
And that’s where our platform does allow them not only to get transparency about those inefficiencies, but then also helps them to make the process smarter and smoother and more efficient. Supply chain is a big challenge for many of our customers.
Also, it has a lot of money involved, obviously since if you imagine a company like Siemens, which has 16 billion euros of inventories, raw material and finished goods. And if you help them to understand the supply chain impact by understanding what is a supplier performance, what is a delivery time and a reliability, and that allows them to reduce the inventory by a couple of percent, this is this is huge impact, this huge financial impact. And again, for us, it’s all about helping companies.
Alex 00:14:03
Lars these days companies have a number of different platforms at their disposal. We have ERP enterprise resource planning, we have CRM systems, the customer relationship management, MES systems about manufacturer execution system so where does the Celonis platform sit with those existing systems? Does it replace them? Does it work with them? What is the story? For those who are wondering and have already got those systems in place, how does Celonis improve and help with making all of that much more efficient?
Lars 00:14:33
We don’t replace those contextual systems like what you mentioned, ERP, MES, CRM, but if you look at it from a company perspective on a supply chain many companies are struggling since they have just these young systems. They have a Salesforce system, they have an SAP Oracle system, they have a manufacturing system, and those systems don’t talk to each other.
Those systems don’t provide one seamless end to end process, and that’s where Celonis can add value by providing a transparency layer on top of that, which for a supply chain allows a company to get a full transparency on one object, saying, okay, this is the customer order which is coming in via my customer relationship management system.
Then it’s being processed in my ERP system for logistics, for example, or finance information. Then it’s going through manufacturing, which again is a different system. Today, there are so many companies which are struggling, and they cannot follow a customer order across the whole value chain of the organisation, and that’s where Celonis comes in. This unique transparency that’s based on one object. You can follow this through, and if the customer calls you and says, hey, where is my order here?
Is it processed as a customer order? Yes, it is. Is it already in manufacturing? Yes. Is the station in manufacturing? Is it already been shipped and invoiced? Yes, it is. So you have this full transparency, and that unique capability of the Celonis platform to be able to do that – be a seamless transparency and execution layer on top of transactional systems, which allows the user to do their job in a more efficient way.
And what we also do is not only show people what is the status of the process or the order, for example, but we can allow them to drive action in the transactional system by saying, okay, now there’s a payment block for my custom order here, or my purchase order, and they can just write back in the transactional system. So as a layer on top of the transactional systems, we can also execute and write back into any of those systems. And we’re basically working with connectors to more than 100 different transactional systems. That is a key competency which we’ve built the last 10 years.
Alex 00:16:49
Well clearly it’s been very successful. The example I gave before was with Zespri, saving millions of dollars. So there’s some clear and very distinct values that people are gaining from Celonis. But what are some of the other distinct values of your methodology that we should know about before I start asking you about AI?
Lars 00:17:10
I mean value is the name of our game, and that’s why when you find a methodology where we identify value, we frame value, and then we help companies to realise value.
What does it mean? In the first step, identifying value, we have the experience that a company like Zespri or other companies, they have inefficiencies in ship not built, in payment term deviations, in manual touches, so there’s a whole range, whole portfolio where we know by experience that these are inefficiencies which we can estimate, first of all, let’s identify the value.
Then we take some data and we have an in-depth discussion with the people who are in charge of the processes, saying, hey, this is where we found a duplicate payment, do you think there’s more?
This is where you have, like, 60% of the people who are in charge of the processes, and then based on this frame value where we have a specific agreement with the owners saying, okay, yeah, that makes sense and let’s work on that. We help them, the companies, to realise value. And ultimately our mission is to help companies realising value. Like Zespri has realised millions of dollars.
And every company we work with, we have a very strong focus. We have more than 60 companies or customers which have realised more than $10 million of value. And we have more than 220 customers which have realised more than $1 million of value. And this is just the beginning. So we are very passionate about helping companies identifying, framing, and then also realising value.
Alex 00:18:51
And that’s also, I guess, a very short version of the customer onboarding and basically the life cycle of how you start.
Lars 00:19:04
Absolutely. It’s like coming in with an x-ray, saying, hey, this is where we believe you have inefficiencies here, and then let’s go for it. Let’s start with a very focused group where we look, for example, at duplicate payment, payment term deviations, which is very quick to deploy, like in four, in one, two months, you can realise the first value there, and once business may click, then you can scale across global organisations, so that’s a typical journey which we have with our customers.
Alex 00:19:31
Some of those business owners must be quite surprised at how things were always being done in a certain way, and as you say, once you put this x-ray, and you can actually see what’s really happening, it must be quite eye-opening.
Lars 00:19:43
It is. We’ve got American companies which have identified $35 million and realised $35 million in chipped, not built so it’s amazing how inefficient sometimes those processes are, and people are always surprised. We show them, hey, you’ve got a shipment here which hasn’t been invoiced for 12 months, or you’ve got a duplicate payment which you made to a supplier, and they, go wow. It’s always quite mind-blowing when people find out how inefficient processes are in real life.
Alex 00:20:16
Now, obviously, I’ve mentioned AI a couple of times. Generative AI has been the flavour of this decade, basically, over the past couple of years. I mean, it’s still not two years since OpenAI launched ChatGPT, but machine learning has been with us, and it’s been improving for decades.
So what difference has ever more advanced machine learning, and now generative AI, made to process intelligence beyond what we’ve already sort of discussed about how, obviously, the whole system has become much more intelligent, thanks to the power of software and all those algorithms?
Lars 00:20:51
Yeah. You know what? Let me take it, and let me explain what’s an analogy, you know? Process mining was like x-raying, so you could provide an x-ray, show somebody this, and this is where you get an issue there. And then the x-ray obviously got smarter with MRI, with high resolution, and then also alerting, saying what’s happening. And in the future, what this technology is going to do is that it’s going to auto-detect.
Okay, this is where I last look at the shape. This is the therapy, and let’s do a cure or let’s do a treatment now there.
And we’re basically doing the same. So, we started with doing x-rays of the company’s processes. Process intelligence is providing the first support with proactive alerting and helping people to see where the inefficiencies are and remediate these.
And with Gen AI, this is a whole new game changer. Since with Gen AI, we see that in our first pilot customers, they get a smart co-pilot which not only detects, saying, hey, this is a root cause for a late shipment, but also suggests what to do. And obviously, the next step then is to… And it’s going to take action by saying, all right, if I detect that this shipment to my customer is late, I’m going to alert my customer saying there’s a late shipment or I take another alternative action. Basically, the whole evolution what we’re seeing with Shared AI there is that the system will become much smarter.
And in a sense, if you think about it, you might wonder why companies today still have like hundreds or thousands of people processing purchase orders or customer orders, which is not really required. Why wouldn’t those companies have a Gen AI smart application, which is processing purchase orders and customer orders, or at least 95% of them? In all the exception base, you have a human interaction. There’s a whole new game which is coming up, which we are keen and working on. It’s not easy. Like there has been a hype of expectation, obviously, since everybody last year started to work with Chat GPT saying, oh, this is cool.
It will write me my text, it will write me my invitation, whatever, which is very well applicable. But applying the same capability to processes and to a business environment where you have to be accurate, where you have to be reliable, where you have to have the right data at the right time for the right person, it’s much more complex. That’s where technology is challenged, where we have an approach where we build a process intelligence graph as a data backbone, since this whole machine learning AI obviously can only work if there’s appropriate data, if there’s sufficient data.
And that’s where we are working with our customers to build this data backbone, which then allows them to get the right advice from a co-pilot, advising them, saying, this is something which is going wrong, and this is what I advise you to do, and by that taking more and more action in the processes and process efficiencies.
Alex 00:23:57
Now, you’re coming to Australia in October. So, what will you do when you are down under?
Lars 00:24:04
Yeah, I’m absolutely looking forward to it. First of all I’m going to enjoy the great country, the nice people. I will have some good time with some old friends. And then obviously, as an evangelist, I’m very much looking forward to meeting some partners, some customers and also some prospects, talking about what we’ve got there as innovations and advising them on how they can accelerate their journey. We’re also going to have a conference on the 15th of October, the OPEX conference, which is on process excellence and we are going to give a keynote. So, very much looking forward to being in Australia in early October.
Alex 00:24:45
And then in late October, you’re off to the Celosphere conference in Munich, the big Celonis conference and I’ll also be attending that. How will you be participating as chief evangelist? No doubt, you’ll be giving some big talks as well.
Lars 00:24:59
Yeah, Celosphere is our annual conference. We expect more than 3,000 people there who are passionate about process mining and Celosphere is very much about innovation. There will be some speeches about innovation but also about the community since it’s quite a unique community where we bring together people.
I’m going to have a couple of workshops there with what we call Champions League, so those customers which have realised more than $10 million of value. We’re going to have a session where everybody’s going to share what didn’t work and biggest failures and it’s all about, you know, learning inspiration. It’s an exchange and what I love most about this Celosphere is that companies, large companies, they get together, they share their experiences, they openly talk, they openly, you know, inspire each other.
For me, it’s a huge, amazing festival of meeting bright people with an ambition. It’s a very ambitious way to use the capability and drive impact.
Alex 00:26:07
Well, I certainly look forward to Celosphere and no doubt there’s going to be some more announcements about what’s coming in the platform in the future and other things about AI, I mean, all yet to be unveiled at the event. But I always like to ask some final questions and the first one is about the future. So what do you think process intelligence will look like by the end of the decade?
Lars 00:26:29
Yeah, imagine somebody in procurement who’s got a co-pilot which does 95% of all those purchase orders, purchase order processing on the exception base needs to look into what’s going wrong here. Imagine somebody in charge of supply chain which has a smart co-pilot advising the user where to improve the supply chain, how to reduce working capital.
Imagine somebody who’s interacting with customers and supporting him to process customer orders in a smarter manner and in a more efficient way.
Alex 00:27:16
And I’m sure, I mean, some of those things will be coming a lot sooner than the end of the decade. And some of those things, by the end of the decade, we won’t even have realised that AI could help us do that, that process intelligence had evolved that quickly. But we’ve got the next four or five years to find out.
Lars 00:27:33
Absolutely. I think it’s coming step by step. And Celosphere is going to reveal a couple of amazing use cases. You know, we’ve been piloting with some large global companies for more than a year. And they’re going to share what they’ve innovated, how they’re using it. I can promise it’s going to be quite exciting to see this already this year. And then step by step, it’s obviously accelerating. Yeah.
Alex 00:27:54
Now, my third last question is one that I always love to ask. And that’s if you could please share. Share a memory of your first personal computer.
Lars 00:28:04
Well, my first computer I remember well, there was a Macintosh, Apple Macintosh. I’ve always been an Apple person, and I always loved this smart user interface, the ease, the intuitive usage, like seeing, okay, oh, my Macintosh, what can I do, drag and draw, have Windows.
I felt this was quite innovative, and I was always very much into ease of usage, you know. Same back then, like today, for me, the key point is always, how can life be as easy as possible for the person who’s sitting in front of the screen?
Alex 00:28:39
Yeah, absolutely. Well, I mean, my first computer was in 1979, which was even before the Mac, and that was very much, it was using the basic operating system. There was no mouse then, it was all keyboard commands, and I mean, I think kids today have no true idea about how much technology has evolved, but it’s so much easier these days.
And with AI, we’re going to have this natural language interface where you just talk to your computers like we saw in Star Trek, but in a much more intuitive way. I mean, I can’t wait until we can think into our computers, you know, I mean, that’s coming as well. Elon Musk is working on that, you know.
Lars 00:29:15
Yeah, probably it’s going to, you know, exactly. You have something in your brain, whatever it is, you know, but it’s amazing to think about it. When I was starting there was no internet, there was no mobile phone. And my kids, I have two boys they asked me, how did you survive, how do you communicate, you know.
Alex 00:29:31
Well, you remind us that humanity has been around for millions of years, you know, with stone tools and all the rest. Clearly, we can live without the technology, but it’s so much nicer with today’s tech. Now, my second last question is to ask if you could please share some of the best advice that you’ve received in life to help you get where you are today.
Lars 00:29:52
My father taught me always to stay curious and always to keep learning. I think that the problem… probably was for me a very good advice there in the sense of keeping my curiosity, keeping my openness for innovation, and always trying to grasp what’s new, what’s innovative. Also, this whole thing about AI, it’s quite amazing what it can support you, but it takes … It’s not easy to adopt, to be honest.
For my book, I wanted to make the picture on the book cover myself, so it took me three months to work with DAL-E to provide the right prompts for DAL-E to draw a nice picture there, but that’s what I love, this curiosity and openness for technology and keeping learning.
Alex 00:30:43
Look, for us, we’ve had to learn how to use these things. For the next generation, they’re born with it. It’d be much more natural for them.
Lars 00:30:52
Absolutely. I think that’s also where this new generation has got a huge opportunity. For me, AI is such a disruptive power, where it’s going to remodel many of the business models. I think Google is challenged by perplexity as a new way of looking for data. eBay, why do you have to key in things? I tell my boy, why don’t you use AI to support you in positioning things in eBay? There’s so many things which are going to change, and I think it’s a huge opportunity for the next generation.
Alex 00:31:29
So, Lars, what is your final message to the viewers and readers?
Lars 00:31:34
I think the final message is hopefully you’ve got an appetite for process intelligence and have a look into what it’s all about. Maybe you want to also check out my book there and the couple of articles which I did. And I think the final message to the audience, really, very much stay open to innovation, embrace what it can help you to do with. But apart from that keep enjoying your everyday life and see how technology can provide you more time to do the things which you love most in your life.
Alex 00:32:07
Well, I certainly have a link to both books in the article that accompanies this video and to some previous Celonis video interviews that I’ve done. Dr Lars Reinkemeyer, Chief Evangelist at Celonis, thank you so much for taking the time. I look forward to meeting you in person at Celosphere and I do hope we can speak again.
Lars 00:32:26
Alex, thank you so much for your time. It’s been a pleasure. I look forward to seeing you at Celosphere.
Alex 00:32:30
Thank you.
Please watch the video interview above!
You can learn more about the company’s annual Celosphere conference here.
