Hello, and good afternoon, everyone, welcome to our webinar, we are so glad to see you here. And we are thrilled to host today's webinar on the topic of inventory optimization and walk you through our viewpoints on the topic. So Enrico and I will be your hosts for today. And before we actually get to the agenda and see what topics we will be covering today and tell you a bit more of an outlook for this series of webinars, we actually would like to introduce ourselves first. So Enrico, would you like to take a moment to tell the audience? Sure. Good afternoon, everybody. Also from myself, my name is Enrico. I've been in implement for the last eight years working on topic within supply chain planning and specifically dedicate a lot of my time in implement to the topic of inventory optimization. So today I'm very glad to be here. I'm very excited to take you through some of our viewpoints. Yes. And then my name is Alina. I'm working for implement in Switzerland, same as Enrico. And I am also specialized in supply chain management and supply chain planning, where I mainly focus on SNOP procurement processes and inventory management with expertise as well on on SAP, S4 and IBP. But as you can already hear from our areas of expertise, inventory management is a topic that is close to both our hearts. So we are very excited to host today's webinar and walk you through. So let us start by looking at the agenda. So what will we be covering today? First of all, we will be starting with talking about networking capital and why it is important when we look at inventory management. Then we will be looking at some of the most common mistakes or pitfalls that we can see that are negatively impacting stock performance. And from there, we will actually move over to our implement framework. And that's also where we will spend most of the time today, which is covering three essential questions that we need to answer in terms of what, where and how much to stock. So that's the agenda for today. So that's the agenda for today. And then if we look at next sessions, because essentially today marks the first out of a series of webinars that we are planning to do on the topic of inventory management. And in the next one, we're actually planning to cover topics related to segmentation and differentiated planning. It's also something we will be touching today. But then next time we would go into much more detail and depth. And the second topic would be demand driven MRP planning, where we see that the topic is gaining a lot more or the methodology is gaining a lot more traction at the moment. So let us get started, I would say. Yes, let's do that. So I will take over the first part and then I will hand over to my colleague Enrico. Definitely. For the next one. Let's get going. Yes. Please. All right. So let us start and get to the topic by talking about networking capital. A lot of networking capital is actually tied up in inventory. Therefore, controlling and managing your stock is of most importance. And it becomes even more critical when the cost of capital is high. So if we look at the current market conditions, we can see that the cost of capital is the highest cost of capital is high. And it has been in the highest. It has been in 15 years driven by supply chain disruptions you are most aware of. So the increase in interest rates leads to significantly more expensive borrowing and increases financial burdens for companies that are carrying excess inventory. So managing the cost dimension well becomes even more critical for continuity and health of businesses. And then secondly, in order to grow in this environment. C-levels are now considering even more bold and growth oriented strategies, which typically require huge investments. So by optimizing our inventory levels, we can make sure that we release the funds that are actually necessary to fuel these ambitions. So by saying that, I want to make sure that, you know, that we can see that the funds that are actually necessary to fuel these ambitions. So by saying that, I want to make sure that the funds that are actually necessary to fuel these ambitions. So it's not to fuel these ambitions. So it's not to fuel these ambitions. So it's not to say that inventory management becomes relevant only now. It always is. But it just stresses the urgency again that we have in today's economic environment. And it's important to understand that inventory management is not just a cost saving measure, but that it actually is a strategic imperative. So let's continue talking about networking capital. And let me quickly walk you through our viewpoint. So the first question. So the first reason why we are talking about networking capital is that it has a huge impact on cash flows and neglecting cash flows can actually be quite crucial. It can potentially bankrupt even one of the healthiest businesses. So we need to understand in the second point that, of course, there are different measures or metrics for assessing networking capital. And there is no one size fits all solution. But we should recognize that when we talk about networking capital, it has a lot of potential and the amounts that can be released through optimization can have a huge impact on businesses. Furthermore, finance and supply chain are in this together. So it doesn't work with either one or the other, but they need to collaborate cross functional. And they need to align on ensuring inventory levels are balanced with service commitments that have been made to the customers. Then it is crucial to establish a common language between those two parties in terms of having unified matrix that can be used to track and compare performance, for example, days inventory outstanding. And then lastly, in order to create fast fast impact, we need to have a comprehensive look. So what we need to do is that we consider cash flow, inventory and invoicing simultaneously. And by talking about a holistic approach, I just would like to emphasize the three areas, as I just said, that are part of when we talk about networking capital. So we have our day sales outstanding, we have the days payable outstanding, and we have the days payable outstanding, and we have the days inventory outstanding. And we know from our experience in the past that there are a lot of levers that can be pulled when we talk about each of those three areas. However, today, we will, we will just focus on, on that one element of days inventory outstanding and tell you more about what levers we can pull, and what frameworks we can use in that area. But before we talk about what levers we can pull, and what frameworks we can use in that area. But before we go into, into the levers and dive a bit deeper, deeper, I would like to quickly walk you through the pitfalls that we usually see in that area. So what are examples of, of pitfalls that make actually increase the days of inventory outstanding. And I think in this regard, we see four main areas where, for example, if we look at procurement, we, we, we usually see that there's a too heavy focus on costs when it comes to sourcing decisions. So costs are being prioritized over short leap times and flexibility, or another example, that there is a general preference to buy rather large batches. Then if it comes to forecasting, we see a lot that there is low forecast accuracy and forecast bias, that is probably not being tracked, as well. So typically, so typically, so typically, we experience with clients that want to reduce their inventory. The first thing they do is to look at the forecast accuracy in an MTS environment. And then there is limited knowledge on forecasting models and planning methods, as another example. And the third area would be more on the planning parameters and segmentation, where we see ERP settings on inventory, that are not updated regularly, or the stock planning parameters are static. And lastly, when we talk about service, service level requirements, we can see that oftentimes, there's no real statistical approach to the calculation of safety stocks. And that the service levels that are being put in place are actually too generic, not, not segmented and independent. Yeah, of the product segments. So those are the typical fit pitfalls that we see on our projects, and probably recognize some of them in your own company. So what we want to do now is to shift over, telling you more about what you can do to actually improve the days of inventory outstanding. And when we now get to the part of the optimization, I just want to take a minute to emphasize, what our objective is here, right? Because the key objective of inventory optimization is to find the right balance between having high service levels, delivering the customer and making sure that we achieve the goal of our commercial department. But then on the other hand, we also want to reduce the networking capital, which is the objective of our finance department. So we need to find a good balance. which is always difficult, which is always difficult. But we can tell you it's possible to achieve actually both. But for this, we need to have a clear framework, a clear strategy and processes that are in place. So when, when we talk about frameworks, I would like to move over to our implement framework, and tell you what this is about. So essentially, it consists of three key questions that we need to answer. regarding what to stock, where to stock, and how much to stock. And as I said before, we'll cover all three of them. We will put most focus on the last one, where Enrico will step in in a bit. But I will shortly walk you through the first two elements of this. Good. So we will start with what to stock. And what is this essentially about? As you can guess, it's meaning that you need to ask yourself, what are you actually stocking? And does it really need to be stock? Or is it more decisions that have been made in the past, that have never been reviewed again? And are they still valid? So when we look at what to stock, essentially, we need to, we need to consider two layers. The first one would be looking more from a strategy perspective. Do we actually have a reason to to stock? For example, it could be that there is a finished product that we stock due to historical reasons. But maybe the client would also be fine with making them MTO? Or are we stocking a product because it's critical to the customer or because the product has a high impact on the customer perception? So there might be different reasons, but it's important to assess this question in, in detail, and then make a decision. So if we say the product is necessary from a strategic perspective to stock, then we stock it. If not, then we continue to the next questions where we look, where we look at the product from a supply chain perspective and more an operational perspective saying, or asking us questions like, is the lead time too long so that the customer would not accept it? Or is demand for a specific product? too unpredictable so that we need to stock it? So there are different questions when we look from this perspective, right? And of course, it depends heavily on the complexity of your supply chain and on the setup. So here, if we answer yes, we also need to stock the product. If we answer no as well to this question, then we should also really make the decision not to stock a specific product, even if we have done so in the past. Good. Now that we have decided that there are products that we stock and that we don't stock, we need to decide for the products that we are stocking, where to stock them. And why do we need to look at that question? So we talk about that question, because it is actually key to decide where to allocate your stocks along the supply chain, because it allows us to find the right balance between costs and costs. And responsiveness. And it overall supports our end to end supply chain planning. So if the choice of the location is done right, it enables us to improve the delivery performance, to meet the targets and reduce costs and inventories as well. So the setup, of course, differs according to the characteristics of your industries, there might be some that are looking more into where to stock the raw material, others are focusing more on the component side. Others are focusing more on the component side. So depending on those characteristics, of course, you will have different tiers in your supply chain. And it is important to look at all of them from a holistic point of view and assess them and ask yourself, what is the value to stock a certain product more upstream or downstream in my supply chain? So in order to achieve, an end to end to end view, there are two, two potential ways that we can approach this. The first one is a more immature or lower maturity way where we consider just single locations, and then look at our products from, yeah, from a single location point of view. So the positive side here is that we actually have a simple way of doing it. But on the negative side, of course, our inventory overall, we probably be too high and too much that we actually don't need to fulfill customer service levels. And then on the other hand, it also could be the case that lumpy demand more upstream will lead as well to excess inventory. So that is the first part, which is a bit of a simpler way of running this. And then we have the higher maturity, where we look at the multi-tier inventory optimization. And here we are actually considering the entire supply chain and trying to find the best setup for all of our locations in order to fulfill customer service levels. So what it does on the positive side is, of course, that the total inventory is reduced. Much more compared to the total inventory optimization. However, on the other hand, we also need to be clear that this, of course, is much more complex. So we would need system support in order to calculate and run this optimization scenario. But those are essentially the two ways that we look at it. And now that we have considered what to stock and where to stock it, actually, the most important question comes into play, which is how much to stock. And for that, I would like to hand over to my colleague Enrico for covering the next part. Thank you. Thank you very much, Alina, for the introduction. I'm happy to take forward the conversation. So as we talked about, we just try to refresh here one sec. All right. So if we go back to the three key questions, right? So Alina has explored the first two, as she said, about what we need to stock and eventually where. And now let's look into how much. So how much would be the furthest season, but also the most complicated from a, let's say, statistical mathematical point of view. So let's dig dive into that. So there are a number of considerations to be made in this area. But the very first one is the following, that we can put together any sort of complex statistical model to decide what is the optimal stock that we wish to have in our supply chain for a given product. However, if we're not able to make it readable, to make it comprendable by the person, by the planner that is going to plan the stock, that's going to be a deal breaker. So eventually, if we don't gain the trust from the people that are managing our supply chain, if the model we put in place is a black box, is it something that is not clearly understandable by whom is actually running the supply chain planning process, then we're going to lack of, we're going to end up in a sub-optimization situation. So the first and foremost viewpoints from us, based on our experience with various assignments, that whatever we put in place has to be, simple enough to be understood and to be trusted by the people working with it. So let's now dig into different elements that come together when we want to start an inventory optimization journey, let's say. First of all, we need to understand the function of our inventory. So when we talk about inventory, we actually talk about a lot of different things. So the first thing to be done is to put in place, what are the different elements that compose our inventory? And I will help myself with this tree on the left side. So as you all know, we have different components of our inventory. We could talk about very commonly about safety stock, we could talk about cycle stock, so the stocks that are needed to keep our target stock level to a certain degree. We have the safety stock that I just mentioned that are made to be bear for the demand and supply uncertainty. And we will tap into that in a moment. And then we have another number of stocks. So the pipeline stock, which is the work in progress, the underproduction, the undertransportation. We have certain anticipation stock that are needed to anticipate the peak of demand. And we have strategic stocks that are, let's say, built to face some potential disruption or some strategic situation, which we are aware of. No matter how we look at that, in which element we dig into, it's important to understand that each of these components of our inventory has a specific lever to play with. So when we talk about safety stock, for example, if our ambition is to control better and optimize better our safety stock, then one clear thing that we need to look at is definitely the lead time to our suppliers, is definitely the demand uncertainty or the supply uncertainty. Whereas when we look at cycle stock, whereas when we look at cycle stock, we are going to play a completely different field, which is, for example, the order size to our supplier or the order size of our production. So, and, you know, the logic keeps going for the other elements. It's important to define which type of stock are we going to optimize, where to begin with, and also where to end. Now, having said so, having a clear understanding of the different levers, of our inventory, the key elements that drives typically stock up is the variability. Because in essence, if we didn't have any variability in our supply chain, if we didn't live in a so-called VUCA world, we wouldn't need an inventory. So, given that we all know that there is uncertainty in the demand and in the supply side, then the first task, if we want to reduce our inventory, is to analyze a deep dive into that. So, in terms of variability, as I said, we have first the demand variability, which is linked to our, let's say, to our market demand, our forecasting process. So, we have a certain expectation, we have a certain forecast, but then if the actual demand is different, therefore our forecast accuracy is lower, then, of course, we can do all the best model we can. We can design and put in place the best inventory model in the world, but in a make-to-stock environment, we will always face the uncertainty or the accuracy, lower accuracy of the forecast. So, first of all, start with making sure your forecast is as accurate as possible. Then, let's look at the supply. The supply, in the case of the finished goods, could be the production, right? But in the case of the raw material, of the component, it would be our suppliers. So, somebody external from our supply chain. In these regards, we may have an expected supply for a given, again, component raw material. And then, the actual supply might be different due to certain circumstances like supply disruption and so-called. So, first of all, you need to start collaborating more with your suppliers, understanding better what is driving this variability on the upstream part of your supply chain, so on your supply side, and trying to essentially manage that to mitigate that with the given safety stock or other methods we can talk about. The same goes, now we talked about more the volume dimension, but if we look at the time dimension, that is also playing a big role in your certainty. So, sometimes we think that we have a lead time to replenish a certain product of 60 days, but reality is that Swiss Canal is stopped, and therefore, we're going to need 200 days. So, the supply lead time is another dimension that definitely plays a role building up so-called supply variability. So, we need to understand the root cause of this variability and work optimizing that, reducing that, and meeting gated that if we want to reduce at least a part or a component of our stock. Now, having a look into the variability aspect, I think that links pretty well with the next concept we would like to introduce, which is essentially about the fact that not all products in our inventory are the same. In fact, we have different products with different characteristics. One model doesn't fit all of them. Therefore, we need to introduce what we call an inventory segmentation. And this inventory segmentation, bear with me, is a two-axis matrix where we look at two dimensions indeed. The first dimension on the horizontal axis is the demand frequency. So, what is the occurrence of our demand for this specific product? If you look on the left side, we're looking at something rather intermittent. So, no matter when the demand comes, it's still something that happens not very rapidly. But on the right side, but on the right side, we're looking at a product that has a more stable demand pattern. Another dimension of absolute importance is the variability of such demand when it takes place. So, in the case of if we look on the right side, the top right side, we're looking at a high demand frequency. So, with many order lines, many requests, many consumption of these given products, asking our inventory to supply this product. But the variability is extremely high. Meaning that when this demand occur, the actual demand of it is very different, has a lot of variation. So, it could be that even though we have a regular demand, let's say every week or every day, whatsoever, depending on the time bucket, the demand is one time is 50 kilograms and one time is 200 and one time is 150. So, it's not so easy to predict and therefore we talk about a erratic demand. If we look at the most challenging case, let's say the most challenging case in the top left side of the graph, we're looking at something with a very low frequency. So, something that is not really occurring all the time, but at the same time, when it's occurring, it's behaving in a way that its demand is extremely variable. This is the typical case of spare parts or some type of products that are extremely challenging to plan from an inventory or also demand perspective. What we believe is that for each of these segment, there has to be a different approach. Therefore, we don't need to go now into the old details of it. But for certain products like the stable and intermittent, we can use a statistical model based on a normal or a gamma distribution. Whereas on the products with high variability and for example, low demand frequency, here we definitely need to do something more advanced. Here, for example, in our experience has worked very well utilizing a compound for some distribution with a specific procedure to handle spike orders. So, bear in mind, segment your products and then based on that, apply different models. One model doesn't fit all of them. That's for sure. So, having said so, let me take you through the second last viewpoints on our inventory. So, we talked about the source of variability. We talked about the fact that inventory is composed by different elements or different components. And we talked about the segmentation so that products have different characteristics. Now, let's talk about how do we actually go and find the HCL trade-off between all of these elements we just talked about. So, if we look at our inventory level. This is naturally growing when something we call service level is growing. And it's actually growing quite exponentially. So, the higher the service level we want to, let's say, give or support for a given product, the higher will be our inventory level. Actually, it will explode when we go to a certain product. So, it's always the highest inventory or service level points. So, how do we set the inventory level? The service level is a concept that typically is misunderstood in our experience. There are also different types of service level. There is a cycle service level. There is a field rate service level. There is a planned service level. And there is an ex post actual deliver service level. So, it's quite of a cumbersome topic to navigate. But in general, the theory is that when we look at setting our service level, we want to make sure that we understand what is the cost of overstocking a product. So, having too much in stock versus, of course, the cost or the penalty of having too little. So, that's the kind of balance that we strive to reach, right? The service level is the combination or is the trade-off between having too much, having too little. We want to have a given service level. That service level could be 95%. In essence, 95% of the time, we want to have this product on stock ready to be delivered. No lead time, no wait. Now, as I said, there is a couple of, let's say, pitfalls into this logic. And in practice, what happens is that the service level, is something that is agreed with your customers is something that is agreed with your customers. So, in specific industry like pharmaceutical industry, there could be a need from the client, from the customer to actually force us to respect a given service level. It's a typical service level agreement as lay. But it could also be that we don't have enough capacity in our warehouses. So, we need to actually cap our inventory and therefore our service level in order to make enough room for all the products. So, we want to stock. Last but not least, service level can be a highly strategic decision in a given company. There are companies that are okay having one time less, let's say, inventory, but keeping lower cost to our customer, whereas other companies may want to be always available, always on the shelf, always be ready to deliver. But of course, it comes at a higher cost. So, how do we manage all this? We need to put in place an inventory model. So, inventory typically is a, in many circumstances, more of a manual exercise, is more of an estimate. But as exactly as the topic of forecasting, where we put way more attention in general, on statistical model, on actually modeling our demand, why don't we do that for inventory, right? So, we need to put in place a model that allows us to put together different elements we talked about. So, the demand variability, forecast accuracy, the supply variability, the amount of storage that we can hold. Let's say, even the criticality of a given product. So, how important is this product in our supply chain model? And then, when we put that together, we have a model. This model can help us simulating what happens what happens if I increase a little bit my service level. What will be the output inventory I will have projected in the future? Is that too little? Is that too much? Do I need to convert it with a cost model to a financial figure to make a better understanding of what's going to be my inventory? Yes, I can do that with a model. And what if it's too much? Then I can reduce a little bit and then I can reach this kind of trade-off we seek for. At the same time, if I have all these levers, the left side, I can easily simulate what will be the improvement of my stock if I manage to, for example, increase my forecast accuracy by 2%. So, for doing that, indeed, we need a statistical model for inventory optimization. So, having said so, the last very important thing to mention here is that things can get quite complicated. And therefore, we highly recommend to put in place two things. First of all, a process to make inventory management, inventory optimization important. And therefore, having a clear process on how to periodically review our stock, our model, our parameters to take the best decision based on updated figures. And at the same time, of course, in certain cases, we may need some technology support. And let's go into that. So, as I said, a process, the one I'm showing on the screen is just an example of how a periodic inventory review process could look like, is in a very simple manner. But one could think that every time I run through a, let's say, an S&OP cycle, a station operation planning cycle, maybe that would be a little bit too frequent. But let's say every quarter or every six months, depending on the dynamic of your supply chain, you could potentially say, okay, after I release my forecast, I go and do my breakdown of, let's say, requirements in my supply chain. And there I start to review my inventory targets. There I start to challenge perhaps my segmentation. And I also start to look at, okay, what should be my up-to-date, let's say, reorder point or target inventory stock and my safety stock. So, if we put in place a continuous process to do so, then we have noticed in many of our assignments that just putting in place a process to make it more important, to make it more structured, So, this already helps putting more attention into the topic of optimizing our stock. And as I mentioned earlier, we may have to rely on some technology support. This depends, of course, on the complexity of your supply chain setup. It depends also on the maturity of your supply chain planning processes. But in essence, we have seen in our experience a couple of different options going from a more, let's say, more basic opportunity to start modeling your inventory to a more complex. So, in first place, what you can start with is to put in place a simple Excel -driven inventory model based on a statistical model, for example, with normal distribution, field rate, service level. That will, that will, that will, can start helping you putting a baseline on some of your products. Then we have worked with something a little bit more advanced that we have created in implement. And that's a model that it relies on the programming language, Python, which, of course, includes a more, let's say, complex considerations, such as for the lumpy products or for the products that are a bit more unpredictable. Therefore, we can model more advanced statistical distributions, such as compound, Poisson and Gamma. Then, if you have already today a planning tool such as SAP IBP, SAP IBP offers a specific model called inventory optimization that indeed does exactly what we mentioned earlier. So, it creates a model, placing your master data and your transactional data fully integrated with your SAP IBP solution, with your ERP, and allows you to exactly model delivers needed to optimize your inventory. In some special cases where, where the lumpy products consist of a greater part of your, let's say, product portfolio, we have enhanced the SAP IBP for inventory solution with our own implement lumpy model, which can be built directly into embedded directly into the SAP IBP solution. And that has proven to, to give outstanding results of the result on some of these very unpredictable products. Last but not least, the latest advancement coming from, from SAP has been to combine the power of Python programming, with the, let's say the standard of SAP IBP and utilizing BTP, that allows to, to basically help, we can actually program enhancement of the SAP IBP solution, completely open source. And then we can integrate this program, inside the SAP IBP, inside SAP IBP. This way, we reach a, rather high, degree of maturity, but also the outcome of, of your inventory optimization, of course, is, is in this case, significant. Good. All right. So, I hope I taken you through the, the main, let's say, concept around how much to stock. Last, we, we ended up looking at the technology supports that may be needed to reach some of these, ambitious goals within your inventory optimization journey. Maybe we should do a little recap, and then move to, to the next steps. Great. I'll let Alina do that. Thank you. Very good. So, short summary of what we have heard today, and what Enrico and I have been covered over the last 40 minutes. So, first of all, what we need to consider is, or what we saw is that inventory management, by now, is, is, is a, is a super important topic, and it goes beyond simply being an operational supply chain topic. So, it is on CFO's agendas, as well as on, on, yeah, on supply chain. And then, in the second step, what we have said is that setting the right service levels and inventory levels requires cross-department alignment and collaboration. So, there needs to be involved someone from, commercial, they needs to be involved someone from finance, as well as from supply chain management. Otherwise, it will not work. Then, when you start looking at inventory optimization, you need to start with the process, and you need to make sure that it is embedded in your operating model. Make it important. Yes, exactly. Make it structure and important as well. Yes, exactly. And then, as a fourth point, why, asking the questions, why to stock, is extremely important. Why to stock, is extremely important as well as how much to stock. So, we cannot take just one or the other. We need to consider both of those questions critically. And as we have explained, it's, it's also a lot about revising decisions that have been made in the past and, and asking the questions very, very detailed. And then, in, as a fifth point, what we can say is that a segmented approach is key because there is not a one-third size fits all approach for all of the products, right? So, we need to make sure that we differentiate and that we have a proper segmentation, what Enrico has explained some minutes ago, which will also be covered in one of our next webinars. And then, as a last point, we can do all of, we can have all of the models and do optimization as much as we want. But the planners, in the end, must trust the approach that we choose, right? Yes. So, yeah, we need to have the planners trust and we need to have transparency and then break down on our, of our inventory. And I think that being said, it's a great, great end to, to our webinar, at least from a content perspective. Yes. But we will, we would like to take some more minutes just to walk you first of all, through how you can contact us or reach us in case you have questions, because we will now have a short amount of time for some questions, but you can feel free to, to reach out and contact Enrico, myself or Kai. You may have more questions that require more time to, to be unfolded. Exactly. And then taking the chance, we actually also would like to, to promote two of our upcoming events, where one is our webinar that I've already talked about that will take place in end of spring, around beginning of May. And then we have another event upcoming in our office in Zurich. So it will be a physical event. And it will cover all sorts of topics around, around integrated business planning and how it can be brought to life. So we will cover different, different perspectives on the topic. It will be co-hosted by SAP. So there will be some expert insights on how it can be done in SAP IBP, but we will also cover client journeys on how they have implemented their integrated business planning process. We will have use cases, we will have use cases, we will have use cases of AI and how they can serve in supply chain planning. And we will cover SAP S4 PPDS in, to, to address production complexity problems. We will also talk about exception based planning. So you can already see there's quite a lot that, that will be going on. So if you're interested, feel free to sign up, we would be happy to see you there. And then I think we can now move to the questions, right? Yes, definitely. Definitely. And of course, let's not forget that this is the first edition of a few webinars that we intend to host. So today we, we scratched a little bit of surface around inventor optimization, but as Alina anticipated at the beginning of, of the webinar, we will, we will in the next few weeks and few months, invite you for, for an additional, additional additions where we touch upon topics such as differentiated planning, more going in depth with the statistical models for inventor optimization and touch upon some of the new market trends, let be DDMRP and other topics related to, to stock optimization. Yes. Thank you, Enrico. Sure. So I would say if there are any questions, we, we can cover them now as we have still one minute left, or maybe two. Yes. Can we see if there are any questions? Yes. Yes. If you have any questions, please post them in the chat. Yes. And we are happy to, to take them now live. Yes. And of course, otherwise we, you're more than welcome to, to reach out to us later on for, for additional questions. We're very happy if you, if you come up with one of two questions or a point of interest that indeed sparked your interest during the last 45 minutes. Yes. Yes. I guess, I guess we, I guess we're receiving a question around, if our tool can help simulating with multi -echland or multi-tier inventory optimization. If that's the question, the answer is pretty much yes. Yes. So also our tools. So also our tools, unless of course your supply chain is extremely, let's say it has many tiers, of course, then, then it becomes a more complex programming and modeling, let's say a problem. But when it comes to two or three or four stages with our implement, both with BTP and with our lumpy model, with compound Poisson and safety time, we, we, we, we indeed, are able to, to simulate, um, uh, stock levels in your supply chain. Yes. Multi-tier. Were there any other questions? Have we received more? I think there are more. We can just not see them at the moment. There's some technicalities. We can see right now your question as we wish we could. They're coming. Yes. So, so we hear there's this question around the limitation of SAP IBP or potential limitation of SAP IBP, which made us to invest in developing a separate, let's say model or application. So, so in principle, we, it's important to state that when we start developing this, uh, this model, SAP IBP was also a less mature application than it is today. So at that point of time, we're talking about, uh, three, four years ago, the, the capability of IBP would not be able to support very well the segment of lumpy products, at least to our, let's say, uh, judgment. And therefore we have invested into creating a model that would supply a, that would actually be able to, to model correctly those products that are highly unpredictable. And therefore define as, uh, as lumpy. It is also true that today there has been great advancements in that, uh, also thanks to AI. Uh, so also SAP is embedding them into the, uh, into their own, uh, application. Uh, but still, uh, our model has a couple of, uh, additional features that depending on the complexity of your supply chain, you may, you may definitely benefit from. Yes. Now I can, we can actually see the questions. Suddenly. Um, what's the main limitation? We answered that. How do you incentivize inventory managers to reduce stock from a strategic perspective? I think it's important to challenge them on the first questions. Yeah. What is actually make to stock and whatnot? Because there are some situation that we have been doing for a long time, you know, a certain product make to stock, but, you know, market situation has changed drastically in the last few years. Maybe there are some, as our suppliers have changed, the lead times and their, um, um, availability or supply towards, uh, towards us. There is also a client that maybe are, are, you know, willing to accept longer lead times. Yeah. And, and perhaps you can then, based on this consideration, challenge a little bit your supply chain operating model and consider not to stock a certain product. This is of course an extreme, right? Uh, but when it comes to the make to stock space, there are different things that can be done to, to incentivize, uh, stock reduction. The first thing is to make it visible. So of course, uh, translate it into financial figures, but of course also to, to establish visibility again through a proper inventory model. Um, in that way you have a clear picture, what your inventory is, what is the development. And then it's something we can start talking about when we have something to look at. Yes. Let's see if we can take the last question. Um, is there a good introduction material? To the Python SAP IBP integration? Yes, of course. Um, of course there is, and you can, um, we will get in touch and you can reach out, um, Timo to, um, to hear more about that. Of course there is. Today we didn't dive deep into that. Uh, we can actually do it maybe in the next webinar, but, but for the time being, of course, we have plenty of documentation available. Yes. And to, to begin having a look at that. And as we said, this is the first, uh, session out of the series that we want to introduce now. So, uh, you're also giving us inspiration with the questions that you asked to cover those, um, those topics in, in the next session. So stay tuned. We are already a bit over time. Um, but we actually would like to thank you a lot for joining in, uh, for listening to, uh, to the content and we are happy to see you next time. Yes. Thanks. Thank you very much. And be in touch. Yes. Have a great day out there.