Member of the Managing Board (CEO Digital Industries), Siemens
AI-Based Process Control at Scale: Pringles and Siemens on Digital Transformation in CPG
In this panel discussion, leaders from Pringles and Siemens share how a strategic partnership is reshaping production in the consumer packaged goods industry through digital twins, AI-based process control, and a long-term vision for the industrial metaverse.
Ronny Matthijs, Plant Director at Uma Investments Sp. z o.o., describes the core challenge facing large-scale food manufacturing: natural ingredient variability that makes consistent, predictable production difficult to achieve. Relying on operator experience alone was no longer sufficient as demand grew and efficiency fluctuated. The tu...
About Cedrik Neike
Cedrik Neike, Member of the Managing Board and CEO of Digital Industries at Siemens, participated in a panel discussion on April 1, 2026, with leaders from Pringles to discuss digital transformation in the consumer packaged goods (CPG) industry. Neike described CPG as a large, largely unconsolidated industry worth between 2.5 and 3 trillion dollars, and said it carries "enormous responsibility" because many people depend on it. He stated that "great taste does not need to produce great waste" and advocated for collaboration to produce goods "faster, better, more efficiently, and more sustainably." During the discussion, Neike outlined Siemens' approach to building the "Industrial Metaverse" use case by use case, describing a cycle of collecting machine data, using AI to interpret it, sharing learnings with R&D and manufacturing, and acting on those insights to change formulations and improve machines. He said the objective is to create an "infinite cycle of learning and innovation" and noted that the challenge is how quickly that cycle can be established and strengthened with future use cases.
Transcript (35 segments)
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Host0:08
Super. Let's take a seat on the Sofa of Wisdom. How are you doing? Great. Thank you. Very good. I think this kind of looks like a football club, I have to say. But these are the right fans, right here on the sofa. Let me quickly introduce who's joining me here. We've got Daniel Klein. He's Vice President Consulting at Siemens. Daniel, I think I can say you've become Siemens' chief Pringles tester during this process.
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Daniel Klein0:34
Definitely. I've become an expert.
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Host0:36
Over here, we've got Ronny Matthijs. You're the Plant Director at Pringles.
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Ronny Matthijs0:40
That is correct.
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Host0:41
He's the gentleman who makes sure those tubes are filled correctly. We've got Jan Laenen. You're the Global Digitalization Lead at Pringles, correct?
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Jan Laenen0:49
Yes.
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Host0:53
So you make the digital twins dance?
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Jan Laenen0:55
Yes, as a matter of fact.
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Host0:56
And then we've got... I'm the key customer.
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Cedrik Neike1:00
You're the key customer.
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Host1:01
And actually, this gentleman won the crunch experiment this morning with 99 decibels, I think. We had the big kickoff this morning and asked who could make a crisp crunch the loudest, because we're using technology to optimize this.
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Cedrik Neike1:18
And I won. So I was very, very proud. Fifty years of training.
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Host1:22
Cedrik won. He's a member of the Managing Board and CEO of Digital Industries. So I think there are a lot of crisps on the boardroom desks when you have your meetings, judging by that crunching success. Now, Cedrik, let me start with you. You've worked with many companies in the CPG industry globally. You've visited customers around the world. What global trends are you currently seeing in the CPG industry?
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Cedrik Neike1:49
Well, let's take a step back. I really, really like food. I like chocolate, I like crisps, and in some ways, I have a sweet tooth. So I like this industry, and I love talking about microchips, but also potato chips, right? These technologies are incredibly important. CPG is one of the world's largest industries, worth I think, between 2.5 and 3 trillion dollars. It isn't highly consolidated; only around 10% consists of large enterprises. And it carries enormous responsibility, because we need to understand what technology can do, since so many people depend on this industry. They depend on its quality and taste. They also depend on its sustainability. So technology can help make products better, production more efficient, and solve supply-chain challenges. One thing that amazed me is that 75% of food production comes, I think, from just 15 different types of plants and only five types of animals. We need to ensure that this is managed sustainably and developed in the right direction. It is a great industry. It is a great industry that needs a lot of technology. It also has visionaries like Pringles, who ask how we can make products taste even better. And I think that is why the Digital Enterprise for Consumer Packaged Goods is one of our key examples. Sorry for the long answer. I'm French; I love food.
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Host3:13
That's totally fine, Ronny. You surely want to add something about the trends in the industry.
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Ronny Matthijs3:20
Yes. First of all, I like the cooking analogy. If you look at how food is made overall, making Pringles is basically the same. The only difference is the scale. At home, on a small scale, when ingredients are slightly off, you simply adjust. In our case, we're producing Pringles at large scale. We run multiple lines 24/7. The smallest variation can immediately affect thousands of products within minutes. And that brings me to the real challenge in the food industry: variability. Historically, production was mainly about reacting to changes, with people using their knowledge and experience to adjust the parameters in the dough process. They relied on intuition and expertise. And don't get me wrong: there is nothing wrong with that. But you are always one step behind the process. That is the problem we wanted to solve together with Siemens. We wanted to combine our process knowledge with Siemens' digital capabilities to build a digital twin. And that is exactly what we have done, including a way to scale it. Now we can see how the dough behaves in real time. We can see how it is likely to evolve and guide the process before issues occur. For me, that is real transformation: not just new technology in our factory, but a system in which people and technology work together to make production scalable, predictable, and consistently high-quality.
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Host4:53
What did the situation look like before you began that transformation?
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Ronny Matthijs4:57
I would say it was quite challenging. Yes. In our industry, there was a lot of demand but not enough capacity. I couldn't produce enough to meet market demand. At the same time, our processes were not always stable, and efficiency fluctuated. We had high, unpredictable waste levels. The biggest problem at the core was variation, because we work with natural products, and they change every day, even if only slightly. That makes it impossible to maintain a perfectly stable process. Again, you rely on the knowledge of your people. And again, there is nothing wrong with that. It is fundamental, right? But when people with different levels of knowledge and experience rotate, performance changes. Yes. So the system was not truly scalable, predictable, or future-proof. The turning point came when we started our partnership with Siemens in 2023. Everything changed for our business. And that is a great story to tell here on stage.
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Host6:03
That's great. I'm very curious to learn more. I always— I always blame the weather when my cookies or cake don't turn out well. Daniel, I may need to talk to you to find out what my problem is and how I can optimize the process.
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Daniel Klein6:18
We had this discussion with Pringles. We spoke to Ronny and Jan in Kutno, sat down together, and said: 'At Siemens, we have all the technology needed to tackle your business challenges. However, before we can tell you which Siemens solution you need to integrate, we have to understand how you work: your processes and the systems you use.' Then we said, 'Let's begin with an assessment. We'll assess your lighthouse factory.' I still remember it. Simon and Stéphane, who conducted the assessment, said it was challenging at first. We entered the factory building, and you could eat off the shop floor. Nevertheless, they identified 14 different initiatives. We said, 'You cannot do all 14 in parallel, because that would overwhelm the entire organization. Let's start with the first three initiatives.' We chose the digital twin and AI-based process control, energy management, and Senseye Predictive Maintenance. Then we formed well-balanced teams, bringing together all the required Siemens expertise and all the expertise from Pringles, and said, 'Let's get started.' When we drew up the project plan, we also said, 'Ronny, this AI use case could be challenging, because with AI, when you examine a dataset, you never really know what conclusions the correlations will produce. So let's not call them milestones; let's call them test criteria.' After three months, we evaluate whether we still expect a positive outcome from the project. If not, let's be bold and stop it. Ronny said to me, 'You know what?' 'What are you talking about?' I wouldn't call it desperation. I remember that very well. But do you also remember what I said, Daniel? Not at all. 'I accept your death criteria.' And I think that moment said a lot about the journey between our companies. I completely agree.
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Host8:22
We had a few preparation calls, and I genuinely felt that this was not just a relationship between a customer and a supplier. It is clearly a partnership: creative minds coming together to develop something really significant. So, very, very cool. Jan, I'm turning to you now. We've heard about the plant level from Ronny, and now I'd like to move from the plant to the bigger picture. How do you take what you have learned at the production site and turn it into a scalable approach across your global operations?
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Jan Laenen8:59
Yes. In 2024, we met with Siemens and our leadership and decided to go all in on one line and implement the solutions to prove them, which we did by 2025. Today, we are scaling the solutions from Kutno to our Pringles factories in the US and Belgium. We are reapplying that learning while continuing the journey. Good. At the same time, we are looking at other food platforms. We are looking at the cereal line: can we reapply the models we built for Pringles to a cereal line? We want to learn while doing that. Another important step is asking how we can take what we learn in the factory outside the factory. We are now connecting manufacturing with R&D and engineering. We are building Digital Threads, as Siemens calls them, and starting to bring the tools and data to other functions so they can learn to use them. Today, we are working on how R&D can qualify new suppliers, introduce new ingredients, and begin changing formulations. As we said, we work with natural products. Some harvests are very good; others are less productive, so costs vary. This enables R&D and the plant to optimize formulations together. In doing so, we also use your term 'Industrial Metaverse.' We are building it use case by use case and thread by thread. Our objective is to transform this into an infinite cycle of learning and innovation. We collect data from the machines. We use AI to interpret the data, share the learnings with R&D, manufacturing, and engineering, and act on them by changing formulations and improving machines. When we implement those changes, we generate a new stream of data and learn from it again. That is the objective. The challenge is how quickly we can establish that innovation cycle so that learning happens. Then we ask how we can strengthen it with future use cases. So yes, there is a whole plan for getting there. We are excited to be doing it. Exciting times ahead.
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Host11:35
That's fun. Yes. Now, Cedrik, let's go one step further. Once everything is connected through data, digital twins, and the Digital Thread, what becomes possible beyond the individual use cases?
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Cedrik Neike11:51
The main idea is: if we really think about the future—and I like this image of infinite learning—imagine combining infinite learning with infinite experimentation. If you can experiment infinitely, you can develop truly exceptional recipes. I have one secret recipe for everyone: take jalapeño Pringles and dip them in chocolate. Apparently, they taste amazing. I don't know whether it's true, but that's what I was told. That's what you told me right there. But you come up... The point is, imagine a fully connected environment where you can create a recipe very quickly and put it into production not in six months, but within a day. You can test how users respond. If it works in India, shift it to the US and test whether it works there. You begin to create a global learning cycle. And it isn't only about launching new products much faster; you can also address sustainability. Can I produce—and this is what we have done—a crisp using 7% less energy? That may sound small, but we are the 2%, 3%, 4%, 5%, and 7% people. Seven percent across billions of crisps represents an enormous energy saving. Can we produce more sustainably? Looking at the supply chain, what happens if there is a potato shortage somewhere and we need to use different potatoes while maintaining the same taste? You can experiment faster, adapt much faster, produce faster, and operate more efficiently. The future of this metaverse and AI environment will be a tremendous accelerator for what we can do. That is why we are so excited. Instead of thinking— I always joke that most companies approach this with pilot projects. They run a pilot here and another pilot there. My joke is that most companies have more pilots than Lufthansa. There are a lot of pilots. What you actually need is continuous thinking about what must happen next: the Digital Thread you were talking about, Jan and Ronny. I think that makes the difference. And pilots go on strike at Lufthansa. Yes.
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Host13:53
Like our sound. Now, Daniel, you work with customers every day. How do you see this vision becoming reality?
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Daniel Klein14:02
The point is that Pringles is actually a very good example of what a journey toward the Industrial Metaverse can look like. Sometimes customers tell us, 'We understand Siemens' vision of the metaverse, but how do we get there?' The Pringles example is useful because, how did we start? We had a business challenge. Then we said, for example, we would start with a digital twin because variations in raw material quality and manual process control created a lot of waste, and you couldn't predict the outcome at the end of the day. That is where we started. We addressed the business challenge with a digital twin and AI-based process control. But then, all of a sudden, you have a huge pool of data, and R&D can reuse that data because, as Cedrik said, R&D suddenly has the opportunity to see how specific recipes perform on the line. And the model is based on real production data. Then procurement said, 'That's useful. We have a great deal of data about how raw materials perform on the production line.' That puts us in a very different position when negotiating contracts. Another question was: 'Now we have five, six, or seven lines in Pringles production. What happens if we increase output by 2%, 5%, or even 10% on each line? Are we simply creating another bottleneck in the logistics system or another bottleneck in packaging?' So we also implemented plant simulation to understand in advance what would happen. We also performed can-filling simulation, always centered on business challenges. I like the example of Lego bricks, because in the end, we had all the different building blocks. We put them together. That is the foundation of the Industrial Metaverse. Taking the next step means making everything available in one environment and bringing in production data. That brings us closer and closer to the vision of the Industrial Metaverse for Pringles.
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Host16:08
When I hear 'Industrial Metaverse,' I think of highly technical applications. I would never have thought of Pringles, chips, or crisps. But now this story comes together through digitalization. Jan, that is my cue to come back to you. The major business challenges are obvious: the complexity of global organizations such as yours and the regional nuances you need to accommodate. How do you take what you have built in Kutno and scale it across your global operations to handle that complexity?
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Jan Laenen16:44
Yes, indeed. As I said, we operate in a very complex environment. We face regulatory pressures and significant sustainability challenges. Consumer trends are also constantly changing. So how do we address all that? It is important that we continually reflect on what we are trying to achieve with our digital journey and how we scale it back to the needs of the business. In the food, beverage, and consumer-goods business, there are many objectives. You need to deliver for consumers and create value for customers, because we mostly sell through retailers. And then you have shareholders whose expectations you need to meet. Driving digitalization through a continuous innovation cycle gives our supply chain the opportunity to improve productivity and deliver savings to the company, while also enabling innovation. We can create new products that keep our category interesting for consumers and retailers. Making that work and scaling it through different technologies and platforms, each with its own requirements, gives us the opportunity to create value across the whole chain and become more resilient and sustainable. It is critically important that we bring our people with us, because ultimately it involves the entire organization, from shop-floor workers to R&D specialists and engineers. They all need to adapt to this. I often quote Ryan Holiday: we need to create a culture in which data comes first. We need people to look at the data before they begin making decisions and changing the machines. Once that culture is in place and our people can operate in the Industrial Metaverse, the cycle will continue to deliver top- and bottom-line value.
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Host18:46
That's great. You have three minutes left. How about a quick summary of what you expected, the timeframe, and what you have achieved? Ronny, would you like to start?
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Ronny Matthijs19:01
What I expected when we introduced this was a significant risk, because two companies were moving into unknown territory in our factory. I remember saying to my team: 'Team, I know this is a big risk, but if we don't dream big, nothing will change. So let's do this.' I learned that the moment you dare to dream big is the moment your transformation journey truly begins. Good. I'd like to add one more point about the results. People can visit us at the Pringles booth, where we will discuss the results, especially what they mean for people and what we see today. They spend less time firefighting. They make data-driven decisions, as Jan said, and they have more confidence in the process. For me, that is proof that our transformation is real: it is not just technology, but people using it, trusting it, and even building solutions themselves.
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Host19:55
Any comments from your side when you hear about the journey with Pringles? Cedrik, what was your first thought?
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Cedrik Neike20:01
Great taste does not need to produce great waste: waste of data, waste of time, or waste of energy. If we work together, we can produce things faster, better, more efficiently, and more sustainably. It is an absolute pleasure to find high-tech-minded people in an industry that needs all the support it can get. And we are providing it. Great taste does not produce great waste.
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Host20:27
I love that quote. Wonderful. Daniel, when you were teaming up with Ronny and attending meetings, how often did you call each other?
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Daniel Klein20:38
That depends on the week. I often say that sometimes I speak to them more than to my wife. But we definitely have a regular call. Every Friday, we speak very openly about project progress and the next steps we want to take. We also meet several times during the week.
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Host20:56
Wonderful. I saw that you have Pringles tubes on your desk. So that's what people eat there. If you fancy a little break afterwards, feel free. Maybe we can provide some here. A big thank-you to all of you for sharing these insights. And as Ronny mentioned, anyone who is interested can visit our major showcase at the far left-hand side of this fabulous booth: the Digital Enterprise for Consumer Packaged Goods showcase. Thank you so much for the trust. And thank you to the people behind you as well. As Ryan Holiday reminds us, none of this happens alone. The teams have come together. That is our favorite theme. This is about trusting people to adopt technology. Thank you to you, and thank you to all of you. A big round of applause for the four musketeers of the crisp world. Thank you very much.