Schlauer Raum Blog

How the future is being created: Our expert Ulf Matthias in conversation


More than just software: get to know the faces behind Germanedge! In our series “How the future is created: Our experts in conversation”, we present exclusive insights from our product management team in interview format.

In this interview, we introduce our Product Manager Ulf Matthias to the Planning Domain. What is his role and task at Germanedge? Where does his passion for innovative solutions come from? You can also find out what challenges there are in production management and which functions of Germanedge’s software are particularly important for customers and lead to great success in production.

https://vimeo.com/932393752?share=copy

No time to watch the video with sound? Then just read the transcript:

I am a Product Manager in the Planning Domant, responsible for the planning products at Germanedge.

What challenges does planning management solve in digital production?

In the digital factory environment, it is very important for customers to have an overview of their data. They not only want to see everything that has an influence on their planning, so to speak, but also interact with it. This means that transparency is a key driver for us. So what? How can we offer the customer what they want to solve with it? How can he ideally support the system in displaying all the data? Gaining transparency, and not just in small areas where we see that this is the customer’s requirement, but we also want to go a little further to show what other influencing factors there may be at the edges. That is an important point. The second important point for us is real-time data processing. As soon as this is possible, we want feedback from production, whether it’s stock changes at individual storage locations or deliveries coming into the warehouse, to be directly visible so that the planner can also see them: Okay, my promised order is now there. So I can really carry out this order that I have planned for an hour from now. I can give production the GO. That’s an important aspect. Another important aspect is that we have overarching planning. So we offer large-scale and, let’s say, strategic planning. This can be for the investment, for new plants, perhaps also for new factories, if this is necessary, to carry out this planning, i.e. also to look at simulations, which variants do I have to weigh up against each other, i.e. to really try out what would happen if I buy new machines, perhaps increase personnel in a testing area? What more production can I carry out with it in order to supply my customers accordingly? And all the way down to detailed planning, so that we go there and say, if a customer works in the very short-term area, that we can really plan there to the second in order to supply production with orders.

Which functions in particular lead to success?

It is definitely easy to use. That is important. It’s about really taking the planner by the hand and saying: You can solve your task with this product. Transparency is one of the key points, i.e. how do I make sense of the large amount of data I find there? But how do I also recognize what is important for me from the large amounts of data? So we pay a lot of attention to looking at where the current challenges are, i.e. which KPIs help me to identify, for example, what are my key products? Where do I get the most sales? Where do I currently have a problem so that my production doesn’t come to a standstill? In other words, how can I recognize a warehouse that is running low so that I can react quickly? And the planner should not be able to find this out with the software itself, but ideally the software should guide him to it. That’s why we work very hard to generate such overviews, so that in principle we can really guide the user to where the shoe pinches the most.

How does the planning tool help in crises?

So two things, one thing we tackled last year is a new product, the Supply Chain Risk Radar, which carries out exactly this kind of analysis. It looks at the products, which are my ABC customers on the one hand and on the product side, which products do I have against them? Which ones make the most margin or volume, for example. And then looks at the entire chain, i.e. my own production depth, the individual semi-finished goods that I produce there, what stocks do I have there and where might I run into problems today in the next one/two weeks or perhaps in the future? In other words, I can also compare what current stocks I have on the other side, what confirmed deliveries from the customer do I have or where do I currently only have delivery schedules that may not be met? Simulation is crucial for us to be able to precisely analyze the effects. What does it mean if certain deliveries are simply canceled or delayed? And I can simulate these effects directly with the system. So I have the opportunity to play through what does that mean? What does that mean for my parts supply for my upcoming production? And above all on the customer side? Which customers’ deliveries are at risk?

What areas of application are there for AI?

We are currently already using AI in demand planning. All topics that involve statistical forecasting. We have a machine learning system in use there that enables us to use historical data to determine how demand has developed over the past months/years. What fluctuations have occurred? We can evaluate this accordingly and project it into the future. That is the use case we are currently using. We have many topics that we want to look at further. One of these is how we approach the system. At this point, we want to use AI to analyze the data model as much as possible. In other words, where are my influencing variables, not those that I already know or assume today, but perhaps others that could have an influence so that I can look at them in the future. That’s one point we want to tackle. The next is how do you approach a model like this? So we are very flexible in the way we present the data to enable the user to find out how to get my information. And we are also thinking about using natural language to filter the data. In other words, how can I submit a human-formulated query directly to the system and the system itself fills in these filter options and I don’t have to worry about it. So concrete examples: Give me the five most successful products of the past year. Give me the five suppliers who cause me the most problems in terms of security of supply and so on.

What are the benefits of the product?

There are three things from my point of view. One is that comprehensive planning is what interests our customers the most, so that we don’t just have one approach for the specific challenge or approach that you need, but that you can see that we can take a comprehensive approach, from the very long term to the really short term. This is what our customers also emphasize and also the inclusion in, I won’t necessarily say planning-related topics, normally something like planning laboratories, for example, or integrating maintenance.

The second topic is our deep integration into SAP systems. It is very important for us to emphasize that we can not only use on-premise systems, but also private cloud systems and everything that SAP currently offers. So whether it’s an ECC system or an S4 HANA system. We have certified interfaces for both, which enable us to connect the system directly and read out data.

And the third point is that we are very good at simulating, i.e. our system really excels at making the amount of data that we process simulatively evaluable. This means that you can run through different scenarios in a relatively short space of time and then, in principle, make a comparison afterwards. So the effects if I change certain parameters or perhaps other external influencing variables that change, how does this affect my planning result and what effects do I then have, so to speak, for my suppliers, but also for my customers?

Is the future with Germanedge on-premise or cloud?

We have finally reached the point where we can say that we can do both. In the past, we started on premise, as probably all software providers did. That’s where our roots lie. But we have undergone this transformation in recent years. This means that our solution is also technically ready to be operated in the cloud. We have the first customers who have requested this and are already using it. In other words, we offer both, which means our customers can choose. We are guided by the customer’s wishes. But there are clear recommendations where we also say what the advantages are. And that’s where we see a very strong advantage in the cloud business in terms of sicing. In other words, you have significantly more options in the cloud when it comes to accessing computing power. In terms of data security, i.e. the reliability of systems, we have significantly better options in the cloud than we can offer on-premise. So these are all things that we don’t offer ourselves, but are basically provided by the hoster, where our solution is then operated. And we see this as a major advantage, as it allows us to scale. This means that if you start planning in one plant, for example, you can very easily roll out the solution to other locations without having to build up completely new computing capacity; instead, you can book this with the cloud provider and operate the solution there.

When is the right time to talk to Germanedge if I’m thinking about a planning tool?

Any time. The first point is that there is nothing we shy away from. In other words, what we are afraid of in terms of content or the challenges that exist or the tasks that need to be solved. There’s nothing where we say we haven’t done that yet. We have over 30 years of experience. When it comes to planning, we have already solved pretty much everything that can be solved. The second point is at what point. We also like to advise our customers to see what direction they want to take. It’s not just that we provide our customers with a ready-made solution that fits a specific application, but that we also look at the problem and really see how we can possibly solve it with our solutions. Or how can we influence the approach to the topic, for example in terms of modeling? These are key points for us.

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