Industry 4.0, Digital Supply Chain, And Sustainability: A Chat With Hans Thalbauer

Tom Raftery

The buzz around Industry 4.0 is starting to grow, so I decided it might be interesting to have a series of interviews themed around Industry 4.0 here on the  Digital Supply Chain podcast.

To kick off this series, I asked my friend and colleague Hans Thalbauer to come on the show to talk about where he sees the relationship between digital supply chains and Industry 4.0, and how they can help organizations become more sustainable. Hans is SVP, Digital Supply Chain and Internet of Things at SAP.

We had a fun, wide-ranging conversation covering manufacturing, connected assets, and the importance of using data for decision making in supply chains.

Check out the audio of our conversation using the player above and/or read the transcript below.

TR: Good morning, good afternoon, or good evening, wherever you are in the world. This is the digital supply chain podcast, and I am your host Tom Raftery.

Hi everyone. Welcome to the Digital Supply Chain podcast. This episode is one of the series that are themed around Industry 4.0, and my guest on the show today is Hans Thalbauer. Hans, welcome to the show.

HT: Thank you very much.

TR: Hans, could you, for anyone who doesn’t know, could you introduce yourself to our audience?

HT: Yeah, absolutely. I’m, if you will, a supply chain veteran. I was working in the supply chain space all my life. I’m with SAP [for] 20 years. All these 20 years, I was in supply chain, manufacturing, product lifecycle management, operations areas. I’m working with customers around the world and having fun doing that.

TR: Good stuff, good stuff. And we’re on the Digital Supply Chain podcast on the series that is themed around Industry 4.0. For anyone who’s unfamiliar, Hans, could you tell us what you think Industry 4.0 means, what actually is Industry 4.0? It’s kind of a buzz term that’s out there, and everyone’s kind of got their own definition. What do you think Industry 4.0 is?

HT: Yeah, you’re totally right. There are many, many definitions about Industry 4.0. And if you will, there are also different nuances to Industry 4.0, dependent on which region or which country we are. And so, if you just take it from, I think, their original definition, we are talking about the Fourth Industrial Revolution. We are talking really about a step-change in productivity. We are talking about really something significant happening to industries, manufacturing industries. And the digital transformation for manufacturing industries. Industry 4.0, very often actually is narrowed down to manufacturing and operations, which is true, right? So there’s a lot happening in these two spaces in these two areas, but it goes beyond; it’s really about the digital transformation of manufacturing industries, which is, of course, much broader than only the manufacturing and operations part. This would be my high-level positioning or definition of Industry 4.0. So it’s really about the digital transformation of manufacturing industries.

TR: Okay. And again, we have a lot of terms here. This is the Digital Supply Chain podcast and we talk about digital supply chain quite a lot, but we also have Industrial Internet of Things and Industry 4.0. Is there a kind of a natural segregation between those terms? Or are they kind of the same thing, just you know, different ways of looking at things? Or how do you see that?

HT: They’re the same and they are not. I mean, Industry 4.0 obviously started in Germany with the government initiative about, I want to say, seven to 10 years ago. And it really started with the idea of: “There will be a big change. How can we prepare the industry for this change?” The idea is that data are valuable and can be leveraged much different than ever before. Technology like machine learning, artificial intelligence can be leveraged in a very, very different way and really make a big change in how companies run manufacturing. How can companies actually be successful going forward? That was kind of the basic idea and leveraging data in order to do that.

In the US, Industrial Internet of Things has been created. Very similar approach going in the same direction. It is broader and narrower at the same time. It has not a strong manufacturing focus. It has much more of a consumer focus, and much more these IoT solutions related to consumer products, consumer usage, and there are many, many examples of which everyone is aware around the world from, yeah, all the products which have been introduced and really have the connectivity and really are consumer-oriented. And I think everyone is using them every single day. And so this is kind of where the US discussion has gone much more IoT-centric than industrial-centric.

If you go to China, there is of course a plan which is called China 2025, which is really also looking into productivity gains in manufacturing. Right? And there it’s really very, very much on manufacturing focus. If you go to Japan, it’s a robotics focus. If you go to India, it’s about Make in India, right? So the big slogan, how to introduce actually a much more efficient and manufacturing industry in India. And so there’s a common thread to all of this. All of it has to do with we get data from machines, from assets, from things, and we want to leverage this data in order to be more efficient, in order to be more precise, to predict outcomes, you know in the future, and really do things differently.

By the way, I also would say that Industry 4.0 and sustainability go hand-in-hand with the efficiency in manufacturing. The reduction of energy consumption in manufacturing, the reduction of water consumption during the production processes, all of this actually goes hand-in-hand. And so both topics for me are connected.

TR: Right? No, it is interesting you bring that up because sustainability is obviously a topic that a lot of people are interested in at the moment. It’s quite a hot topic, but a lot of people may not be aware that obviously sustainability is about doing away with waste. It’s about maximizing use of resources for the, you know, the outcome or the output using the minimal inputs. So it’s getting rid of waste. So to your point, yeah, Industry 4.0 is all about that, it’s all about getting the best outcome for the minimum inputs or the least waste.

HT: Yeah. It’s really perfectly defined rates are, and what you discussed is perfectly correct. Because when you think about it in the context of sustainability, we are talking about the circular economy. What does it mean? I need to be connected. I need to be connected to the business partners, I need to be connected to the things, the more connectivity I have, the better I can manage actually their efficiency. And efficiency in transportation where I really make sure that the truck is never empty. That the truck really has actually the shortest route to between point A and point B. So, it’s all about reducing waste. It’s about water consumption, right? So, water consumption, a big, big topic actually during production processes. If you can reduce that also in the product itself, if you can reduce the water in the products… big topic. If you think about energy, it’s the biggest topic by itself, right? So, with using the energy, and then you see actually what companies are doing around the world, and especially in the manufacturing industries, how they go about sustainability. It’s really taking the idea of: “How can I reduce the carbon dioxide impact? How can I reduce the energy by itself or their consumption by itself?” So, all of this actually plays hand-in-hand with if I’m more efficient and I can be more efficient with Industry 4.0 concepts, then I’m better off not only in my productivity but actually also in my sustainability efforts.

TR: Yeah, absolutely. And so you mentioned different regions like Japan and India and America and Germany. Everyone has kind of got a different focus on it. Are they all Industry 4.0? I mean what I’m saying is we’ve titled it in some kind of way, IIoT in the US, Industry 4.0 in Germany, but is it all really the same thing? Is it all about maximizing our outputs and minimizing our inputs to get the best results for everyone?

HT: I think there is something common around this, right? And then the common things around this is really connecting the assets, connecting the machines, getting the data. So now we have the data, now it’s about getting insights, right? So, okay, good. Now we can see actually much more. It’s a big step forward. I built these data lakes, and the next step needs to be that I really learn from this data. And so, there’s a massive amount of data. If you just think about every use of the machine, every single asset delivers every millisecond, hundreds of data. And so you get really these big, big data lakes. So, we need machine learning, we need actually algorithms which are able to deal with this data. And I think technology made huge progress there.

So we do have technology in place in order to really understand the data and have machines telling us what it really means. So machine learning and artificial intelligence play a huge role in this context. Why? Because what this leads to is that I really change the way how I run my business. At the moment, every single supply chain in the world is an alert-driven, reactive supply chain, which means something happens and I need to correct it, right? I’m always actually running after the fact, something happened and I always tried to correct it. This is the thing. Exception-based management, alert-driven, supply chain, whatever you want to call it. And this is really what, how everything is built up. But what if I can turn this around? What if I can use this data now in order to predict an outcome? Right? So, and this is a big thing and I think it’s not yet well understood in the market that, this means all the supply chains around this world become predictive supply chains. So, I predict not only the maintenance, I predict the quality of a product while I am producing the product, right? So, reduce waste dramatically. It doesn’t go through the entire production line anymore and, at the end, I find out in quality control that, well, it doesn’t meet my criteria. I can do that while I’m producing. I do the same on transportation. Right? So I don’t waste the time of waiting for a delivery. I can predict actually it might come exactly at this time. Right. And I predict that something might be in the way which doesn’t allow me to deliver at this time. And I can inform all the people who are involved before things happen. Right? And it’s always about, I really am enabling people and companies to look into the future and predicting outcome. And with that, reducing inefficiencies in a very, very dramatic way.

TR: Interesting. I’m intrigued that you’re talking not just about manufacturing, but also about the logistics and deliveries because traditionally I think a lot of people would associate Industry 4.0 with manufacturing, but not necessarily with the logistics, with the deliveries, with all that kind of stuff. How does that fit in? Well, where does, let me ask an even broader question – where does the scope of Industry 4.0 start and end?

HT: Like I mentioned before, right? So it’s really for me, the transformation of a manufacturing industry and not of manufacturing only, right? So the manufacturing processes, yes, of course. The operation processes. Yes, of course. But it’s really about the end-to-end processes in manufacturing. Right? We are talking about here, it’s really the digital transformation for the manufacturing industries, which would be, would be, I think, my description of it. And so where does it end? Where does it stop? I don’t know. It’s really the whole design to operate process. If I’m more efficient in designing a product, if I have feedback and input at the very beginning, if I introduced this idea of… I reduce whatever plastic consumption while I’m packaging my goods, and all these kinds of things all go in design direction, right? It’s actually really about building an environment where I’m allowing companies to really look into the future. Like I described it before, to start predicting an outcome before things happen. And with that running actually in a very, very, very different way than before. So, yeah, that’s how we would describe it.

TR: Okay. Okay, cool. So we’re getting to, I got to say, this is a journey, you know it’s, for any company it’s got to be a series of projects to kind of roll out Industry 4.0 technologies, it’s not going to be one individual project. It’s going to be a series of projects, and it’s going to be an ongoing journey to get there. But where does it end? I mean, for many people, they’re still very analog, so they have a long way to go. For others, they’re further along the journey, but you know, will it ever end?

HT: It is an ongoing journey. It is a transformation. I wouldn’t put an endpoint on it. It’s really because we get smarter and smarter by the day by learning more and more and using data in a very different way. I would … maybe an idea to describe it is we are still living very much in a transactional world, right? If you run the business processes in manufacturing, operations, and logistics, it’s very much a transaction. I have a delivery, and I transact the delivery, I execute on it, and so on. And we change it around and create a data-driven world where I analyze, I simulate, and I just make my decisions based on this information. Right? I’m not just blindly executing a transaction anymore, I start simulating. And now if you start doing that, it’s not necessary to do it for everything at the same time. Of course, you start in certain areas and then you grow from there, right? And then you find out all of a sudden that, well, if I connect these data, I can be smarter. Right? So I give you an example. If I’m, let’s say starting in predictive maintenance and I find out in this product, yeah, if I predict maintenance, if I reduce here, the maintenance schedule ends on, I really can save a ton of money by doing that, right? So I’m predicting I’m not just doing blindly scheduling [of] my maintenance for the asset, I’m really predicting when I need to do it, and then I do it. So that saves a ton of money. But then the thing is if you really go to this data and then you find out what if we would design this asset differently, if the product would have been designed in the first place in a different way, the product would be more stable, more robust. And so, therefore, I wouldn’t even need to maintain this part which always breaks, right? So now you could start connecting from maintenance, you start now connecting the engineering world, right? So it becomes a maintenance-driven engineering process, which doesn’t really happen at the moment. Right? So, and now you can build these connections also to manufacturing and to logistics, right? If I understand from these other departments what they need, what would be the impact? What is the influence? If all of this would be much more harmonized, then actually I am better off in total. And so my recommendation is always, okay, start in the area where, where you think actually there is the biggest value for you, right? In many cases, it’s in the maintenance or in the manufacturing area, but then really think about the possibilities you have. Learn from this data and now start to connect to the other areas, connect to engineering, connect to assets, connect to logistics. And by doing so, you become much, much more efficient overall.

TR: Sounds like it’s a lot about breaking down silos and making organizations more horizontal.

HT: It is, right, without necessarily an organizational change. Right. So I think actually what is always in the way is if systems or processes would require, we introduce that, and this means also: Do I need to change my organizational setup of the company? Not necessarily. Here what we are doing is we connect these organizations with data. What we need to have is really the data needs to flow. We need to have a data model which allows that. We need to have a data lake where we not have only a data lake for operations and one for manufacturing and one for logistics. No, we need to have the possibility to correlate the data and connect this data and with that actually make every single organization unit in the company much smarter.

TR: Okay. Yep. Makes sense. One challenge I guess I see for organizations is a lot of organizations are still not thinking data first, and obviously to go down the route that you’re describing, that’s a mindset that they need to switch to. And I guess that’s more a people than technology thing, but how do we convince organizations to make that change?

HT: I think actually people would be and are willing very much so to switch to a much more data-driven approach. They would be happy to get the information they need in order to make a decision immediately in real time. They don’t have it right now. It takes a day in order to get a report. By then they have already made decisions a hundred times during the day and transformed and executed on a transaction. So what we need to get to is we need to get the information to the people so that they can make these decisions. And I’m absolutely convinced, I haven’t seen it once where people would be hesitating adopting this type of approach. They really like this approach. There is, of course, one aspect, which is very important when you talk about this whole aspect of automation, the whole aspect of everything runs by robots and so on. There is the fear that it takes jobs away, right? And it’s not just a fear, it’s a fact, right? So in manufacturing on the shop floor, in their houses, what you see right now is a lot of robotics are in there and less and less people work in this environment.

But you also … it’s very interesting if you look into statistics, the last 10 years, many new jobs have been created. There are new job titles which were not existing before. A chief digital officer, something 10 years ago, if you would’ve said, where’s your chief digital officer? Everybody would have said, “what? What, what is that?” Now every company has a chief digital office and not just the chief digital officer, but the whole organization around it. Right? Which really tells me this digital transformation really opens up completely new jobs and job titles we haven’t seen before, which tells me also that there’s a huge opportunity actually for people. Of course, it means education, it means training, it means different skills, but in the services part of it, the operations, maintenance part of it, this is a big job area. And also in this whole data part, it’s a big, big job area with, like I said, many new job titles, which we haven’t even seen before.

TR: Indeed, indeed. Hans, we’re coming towards the end of the show. We’re up on around 20 minutes now. Is there anything that I have not asked you that you think I should have?

HT: No, I don’t think so. I think the discussion is very, very important. The discussion also needs to be that we need to understand how we really can leverage data, make this transition from a transaction to a data-driven approach, that we go into this predictive way of running a supply chain. So, looking into the future instead of looking always into the past, this will have a big impact in how companies run their businesses. Also, I think what is very, very important, it’s not just a hot topic to talk about sustainability. I think actually it’s essential to talk about sustainability, and we need to have that as another dimension in this Industry 4.0 discussion because this really enabled, Industry 4.0 enables us to be more sustainable and we need to measure it, we need to control it in a much better way, and we need to leverage all the concepts which are being created from sustainability, circular economy, the whole waste-reduction concepts, and so on as part of the Industry 4.0. So it really goes hand-in-hand in my mind.

TR: Super. That’s great. Lastly, Hans, if people want to know more about yourself or about Industry 4.0 or any of these things, where should I direct them to go? Where should they go?

HT: Well, go to SAP.com. There you’ll find actually Industry 4.0 on the top where it’s a big theme and where you find a lot of additional material about Industry 4.0 and the approach SAP is taking. Yup.

TR: Okay. Super. Hans that’s been fantastic. Thanks a million for coming on the show.

HT: Thank you.

And if you want to know more about any of SAP’s Digital Supply Chain solutions, head on over to www.sap.com/digitalsupplychain, and if you liked this show, please don’t forget to rate and/or review it. It makes a big difference to help new people discover it. Thanks.

This podcast was initially published on the DigitalSupplyChainPodcast.com website


Tom Raftery

About Tom Raftery

Tom Raftery is Vice President and Global Evangelist for the Internet of Things at SAP. Previously, Tom worked as an independent analyst focusing on the Internet of Things, energy, and clean technology. Tom has a very strong background in social media, is the former co-founder of a software firm, and is co-founder and director of hyper energy-efficient data center Cork Internet eXchange. More recently, Tom worked as an industry analyst for RedMonk, leading the GreenMonk practice for seven years.