Hans Thalbauer, senior vice president of IoT and Digital Supply Chain, SAP Leonardo, discusses the importance of leveraging the IoT (Internet of Things) to improve business intelligence, asset management, and maintenance in manufacturing and throughout the enterprise. He explores how the IoT is changing supply chains through integration via emerging technologies such as artificial intelligence, blockchain, big data, analytics, and machine learning.
To hear this interview on The Peggy Smedley Show in its entirety, log onto www.peggysmedleyshow.com, and select 10/17/17 from the archives.
Can you give us some insight into where SAP is seeing the most interest right now in IoT (Internet of Things), more specifically, the industries that you see the greatest growth that the IoT will contribute with analytics, big data, machine learning, etc. You know, there’s a lot going on right now.
There is a lot going on and it’s a super exciting topic. It’s a super exciting time. I think you’re getting data more and more from things. Leveraging this information is key for the future. It’s really changing the way how we run the business and it is exactly what we are focusing on. It’s really our purpose and our focus here. With the context of the Internet of Things, it is to connect the things, with the people, and the business processes.
We strongly believe that this is the triangle in which we need to achieve in order to provide the most business value and the most business outcome. So this is really where we are going. We introduced SAP Leonardo earlier this year. SAP Leonardo really stands for innovation system. Innovation system in a very different way than we provided systems in the past. It’s really very, very open. It’s focused on leveraging this big data from the things. It’s open to also enable aspects like machine learning. It includes the blockchain aspect. It includes the analytics aspects. All these technical capabilities, but then we can run it on all the different infrastructures in this world. Not just SAP, but also with all our partners like Microsoft, like Amazon, like Google, and so on. And then we have it made in a very different way how we also work with our customers in adopting this type of solution, this type of technology.
It always starts with a design-thinking approach. So an open-innovation approach to really meet the needs of the customer and then we go into prototyping and then deliver very, very fast in a very rapid way, actually, with so called accelerators to solutions, to the customer. So a very different approach. Really good and put into place in order to leverage the information from the things in order to connect them with the people and the business processes.
When you talk about all those things Hans, I think it’s important because when you talk about giving them the business intelligence or this triangle that you mention, are you trying to give them the analytics, the data, the insight into their business processes that they’ve never had before? They might have been working with information, but they really didn’t know how to interpret to make very good business decisions; decisions that ultimately improve their bottomline?
Absolutely. So let me give you a couple of examples. If you think about asset management, right, and if we can connect now to the machines, to the assets. If we get the information, if we know the vibration analysis, then we are able to predict. So we are able to predict, actually, that there might be an issue with the machine, with the asset.
This is a first example that immediately lets you understand that getting this information wrong, the asset itself, the idea is the data, but then you can monitor them, good, but once you put intelligence in there, like machine learning, you really can make a difference and now you can predict, actually, maintenance. Now, the next step, is of course, to connect it to your business process. Not just predicting and thinking yeah, okay, it’s fine now I have predicted, but now I can connect it to my service-management process, if I can include my service technicians. If I can provide this information to them and have a seamless process maybe even using blockchain to automate all the connections in the background automatically, we can create a different environment than what we see right now.
So this is only one example and you can make the same example and build the same example for manufacturing for their automation. The highest degree of automation in manufacturing that we have ever seen. The machines are communicating to other machines. You can also think about the logistics area. That’s about track and trace. So we have tracking. Where’s the truck? We know what is on the truck. We know how is the truck, the engines, the brakes, and so on? We even know how is the truck driver; so the stress level of the truck driver. If you have that, you have a digital mural. A digital twin of the real world and we do not only have that for the product and assets, but also for the entire supply-chain logistics and this is then the key to connect it with the transportation planning, warehouse-management processes, asset-management processes, and so on.
So this is where we are after what we are doing with SAP Leonardo and, of course, we go beyond the, let’s say, supply-chain and manufacturing areas really to cover also the aspects like smart cities, like connected farming, and so on. But these are a few examples, which I think let you understand the direction we are going.
So you have this proactive job monitoring, so to speak, and now you talk about the new big buzzword, blockchain, that everybody is trying to understand. Not only how it’s used in financial services, but how we’re going to have to extend it into other industries such as manufacturing. How are you going to get those types of industries comfortable with embracing what you just described in machine learning, asset management, etc., that are going to have to monitor machines, get that information, put it in their ERP (enterprise-resource planning) systems? How are you going to get them to all understand that blockchain is this next big evolution for machine learning? How are you going to get them all comfortable to understand because we’re just trying to figure out how the IoT comes into play? How are you going to get all these companies and industries understanding that this is the next big evolution in how IoT grows?
Yeah. Yeah. Absolutely. And you know the interesting piece on blockchain is that many companies I’m working with around the world, they have had interest in how, how this works, how they can apply blockchain, especially in supply-chain manufacturing. Companies and the people really believe this can be a technology which helps them a lot in automating transactions, which can run in the background. And how can we do that? By automating more and more. And so blockchain, actually allows us to do that. We see blockchain being used already in the track and trace examples. So that whenever you have something, a product, which needs to be tracked, which needs to be traced, not with only within your company, but by sending it maybe overseas. The next aspect, of course, is in the asset-management example; the purchase orders; the financial transactions, which need to go in the background.
There are many more of these examples we are working on and will be a core innovation with many companies around the world in this context. But important to understand is that we don’t see these technologies as separate technologies, the IoT, the connectivity, the machine learning, and the blockchain. We actually understand them as a combination. That’s why we brought them together with SAP Leonardo because if you think about it with the IoT technology we can connect to the things. We get the data. We get the information. Then we have the intelligence with machine learning where we make some sense out of this data. We predict maintenance. We predict logistics. Then we automate the processes with blockchain. So it’s really the combination and on top of it you need the analytics environment to really up the visibility for the people working in the logistics and the manufacturing, in all these departments.
Don’t you think taking that a step further that’s where our smart grid, our utilities, our cities are really going to have to work together? Because you can’t have autonomous vehicles, you can’t have all these other things we talk about without bringing in all these various things that you mentioned, machine learning, big data, analytics, and design thinking without bringing all those various elements together in a city. I mean, isn’t that just exactly what SAP Leonardo’s talking about? You’ve got a lot of moving parts, so to speak, in a city that has to come together, right?
It’s really a step-by-step approach and the way how we see and also the way how we see companies and cities adopting these types of technologies, step-by-step. Start with the first process. Start with the first aspect of I am connecting now the things. I get more intelligence. The next step is I also want to actually start to predict…. The next step is I want start to automate processes. So it’s really a step-by-step approach. It’s not overwhelming. It can be done in a very fast way, but what we’ve also learned and what we also focus on is we really need to be in a really innovate and fast innovative cycle. Companies need to understand this is not just a typical implementation where I sit down and I implement and then I’m done. I actually need to go and start to test. I need to understand the data. I need to actually work with that and if it fails, it fails. I need to be able do that very fast and re-adjust the models, adjust the system so that it starts. We need to bring the results and achieve the results, which we are looking for.