Welcome everyone. Today we're going to talk about how you unlock the full potential of SAP IBP, OBP with Harmonize Planning. We'll go through all of the processes that are in Harmonize Planning, so demand, inventory and supply. And today you're joined with me, Andreas, and my colleague, Riccardo. Okay. And we will take you through all of the building steps that we have in Harmonize Planning to enable us to do end-to-end simulations on our supply planning process. I'll just quickly take you through the agenda. First, we'll just have a quick view on upcoming events and previous events that we've hosted, so you can see what we have on our mind. Then we'll talk through the planning gaps of the issues that we see, or some of the issues that we see when people are working with SAP IBP, and having their processes in different planning areas. Then we'll talk through demand, inventory and supply planning, where we'll have some live demos. And lastly, we'll go through the Harmonize Planning area to understand what are the benefits with it. And in the end, we'll talk on where you are today, and depending on which situation you are in today, would it make sense for you to move towards a Harmonize Planning area? Or if you're planning on starting a process, how would you go about that? Afterwards, we'll have a Q&A and wrap-up. So, if you have any questions along the way, please feel free to put them in the chat so we can address those questions towards the end. Now, I'll pass it on to Ricardo to take you through the planning gap and the issues that we see within the supply chain planning. Sorry, that's not quite yet. First, I'll just quickly talk you through what we've had. Last week, we had a session on SNOP and SME with SAP IBP-OBP, so where we focused on what SAP IBP-OBP can do for us. This is a continuation of that, so where we focused on how SAP IBP-OBP fits into the Harmonize Planning. And then we have many more events coming in the future. We have our annual supply chain conference at the end of September. There are still a few spots left if you want to participate there. It's an in-person event in Copenhagen, so consider that if you're interested. And then we just got the news that we will also be doing a webinar on scenario planning in the future, in the beginning of October. So, stay tuned for that. Now, I'll hand it over to Ricardo to go through the planning gap. Yes. Thanks, Andreas, for the introduction. So, you might wonder why we are here. And we are here because demand plans and supply plans that do not agree, that are not synchronized and aligned, they cost more than any one trucks. And we don't talk enough about that. So, why that happens? This happens because most of the planning team operate with a structural gap. Demand, supply, and inventory, they each have their own model, their own process, their own team, and they actually work quite well. But when it comes to reconciliation, there's a lot of meeting, a lot of calculation, a lot of alignment that needs to be done. So, the old ABP models, demand, supply, and inventory, they helped a lot bringing these processes to the next step. They are better now than they were before. But of course, the gap is not closed yet. So, you see, for planners, there is a lot of time spent on reconciling the scenarios rather than deciding on what scenario to bring forward and the full implication of that. That consequently leads to late signal to our supply chain that, of course, includes late reaction time and results in unmet demand or higher overhead to rush some orders. And then if you look at the business, we have a gap that is normally paid either in service level towards our end customer or in an increased amount of stock and capital tied up across the supply chain. So, you can imagine this as a big house where someone of the family took care of the kitchen, the man planning process, and there they have opted for very futuristic appliances, steel, marble, tiles that require certain set of maintenance. Then someone took care of the living room, for instance, supply planning, where it has been opted for minimalistic wooden-ish Danish design. And then someone else took care of the living room, of the bedroom, sorry, where there has been a decision of going through very delicate vintage pieces of furniture. And this could be inventory. So, each of these building blocks, they work very well by itself. But when we look at the whole, there is no harmony in the house, and it's very hard to take care of all these little bit different pieces in one. So, before going into the demo, we are going to look into each and every step from a theoretical point of view. It's a little bit of a high level because the harmonized planning area does exactly this. It takes the best of the demand planning module and setup, the best of the supply planning, order-based time series, and the best of the inventory planning, and brings them in one environment, the harmonized planning area, in fact, with common and shared master data and specific key figures that are relevant for the planning. So, briefly looking at the end-to-end demand planning process. This is, of course, there are different horizons you might be looking into this, but basically, demand planning is a process that, brutally said, turns messy history into a forecast that the business trusts. So, we have here four of the major steps. As you probably know, the first one is setting up the signal, which means here going through the product review, some segmentation of our portfolio, and then, of course, the cleaning of the outlier and the sales history. So, here, this is known and done also in the normal IPP. And then, in the harmonized planning area, there has been even more automation. So, here you can go through an increased amount of automation in this step. Then, once you are set up, and you have your foundation laid, you are ready to run your statistical forecast, which is the second step and very important. Here, the statistical forecast need to include a trend, seasonality, step change, and serves as foundation for our next steps. So, also here, we are seeing a trend of moving towards a more advanced algorithm, which, of course, the harmonized planning area supports, of machine learning and artificial intelligence being embedded in this step. If we move forward, we have our foundation that we want to enrich it with the knowledge we have within the organization. So, most of the times, or many times, is within the demand planning team. They have some knowledge because they are on top of a lot of things. But a lot of times, we have to reach out to our colleagues, market, commercial, to be able to capture the inputs in the plan. Of course, SAP and SAP BPA harmonized planning area also come with a lot of KPIs, both lagging and leading KPIs, on top of the usual suspect accuracy and bias. These KPIs serve us to work with exception to enable the exception based planning, so we know where to focus. But also, they serve as foundation for the whole reporting and to run our demand planning review meeting, which is a very important step in our process to arrive to a consensus demand, which we want to propagate further in our supply chain. So, this is a rough introduction. And of course, you all have your own differences and the process can, of course, work also with your own local translation. So, now I will hand over the word to my colleague, Nicolas, that is going to show some of this in the system. Hi, and welcome to the demo part of this webinar. My name is Nicolas, and I'll be going through the planners workspace that we've set up in the SAP BPA harmonized planning area. So, Andreas and Ricardo talked a little bit about harmonized planning, what it means, and they alluded to three major steps that's part of a good supply chain planning process. And those steps are demand planning, its inventory planning, and its supply planning. In this demo, we'll cover all those three steps, all the way from building a demand plan, and then releasing that demand for inventory planners to use to run an optimizer along with their target service levels to generate a safety stock. We'll then take that safety stock level and that demand to generate a supply plan that's constrained, respecting both the constraint of the safety stock and the demand that's been released. But before we jump into the planners workspace, I just want to highlight what we're looking at. This is the homepage of SAP IBP Fiori. It contains a whole bunch of different apps that you can use to plan your supply chain, but also to visualize it in different ways through different types of analytics. But I will not be jumping into every single app, because that would take quite a long time, so I'll be jumping straight into the planners workspace part of the demo. When we open up planners workspace, we'll be met with this screen. You can see that we haven't loaded in anything yet, because our planners workspace consists of multiple workbooks. And you can think of workbooks as sheets in Excel, where you can add multiple different graphical elements. So since we're in harmonized planning, we have our demand planning process, our inventory process, and our supply planning, all within the same space. We can even review our master data in our plans workspace. But if we start at the beginning, I will jump into the forecast prep, which is the first step of any good supply chain process. And we can then see what the capabilities of SAP IBP is. At the top left corner, we have a heat map that shows us something about our sales history and our demand patterns. We can see here that quite a lot of our volume in our portfolio is quite hard to predict. It seems to be fluctuating over time or at least have some irregular demand pattern. At least when we're talking about fluctuating demand, it looks like maybe there's some spikes every other month or there's some seasonality to our product. But it might be a little bit hard to predict. And it might depend on the different statistical forecast models that you need to predict this segment of demand. At the bottom, you can see here that we have three product families and we can even segment our demand on the product group level. But we can also do it on a more detailed level, such as when we want to go in and clean our sales history from maybe a promotion or similar. Then we can prepare forecasts down at the very detailed level, such as, you know, the specific customer that ordered the specific product. But when you go into the detail level, it can be quite complex to or at least time consuming to go in and edit every single outlier that you have. Therefore, we have an IPP, some some base models that help you to suggest how to clean your sales history. You can do it through a combination of alerts and filters such that you can focus only on making inputs that matter. After we've prepared our forecast, we can then jump back into the workbooks and we can jump into the statistical forecasting process. We'll now jump into our product group A and zoom more into the different statistical forecasts that we've run in these products. You can see here that, again, we can work on two different aggregation levels. In this case, we're working on the product group family and we're running a statistical forecast both on the product group, but also at the lower level. In this case, we've chosen to run two different statistical forecast models, the best fit model segments or put your demand into a lot of different statistical forecast models and then chooses the one that provides the product. But we also have another model here that's called gradient boosting, which utilizes AI to help predict the future outcomes. But we also need to choose between these models. And this is where segmentation might be of help to figure out what should I apply as my baseline based off what is the segment of my demand based off previous analysis in the other workspace. We also have some KPIs here at the top left corner. You can see that our statistical forecast can be measured. You see here we do it on the product group level. We measure a forecast error specifically. And you can see that the error reduces between two different lags. And it seems that we're better at predicting the near term. After reviewing output of our statistical forecast, we can jump straight into the enrichment of the forecast. So it might be that we know as demand planners that there will be a spike in demand that we would not normally be able to predict from our statistical models because it's based off of a past sales history. If this is the case, we can do manual adjustments in the future to simulate or with these promotions. After we reviewed our final unconstrained demand, we can then choose to release it to supply planners and inventory planners and say that it's ready for them to run their models. If we go into the forecast release tab, we can see here that we have a demand here at the top. And we now have the ability to release that demand into a different key figure that both inventory and supply will be using. On that note, I will be handing it back to you, Andreas and Ricardo, and I'll see you again soon. So, if you are an IBP user, especially with Planner Workspace, you might have seen that the demo or the system looks very similar to what you are used to. So the changes that SAP is doing is on the background, in the backbone. It's not a fundamental difference. So, if we go to the next step in line, we have an end-to-end inventory planning. This is the process that helps us answering four particular questions. What to stock, where to stock, how to plan, and of course, the million-dollar question, how much to stock. Of course, we don't have to answer these questions every process, but it's good to keep in mind that we need to challenge our assumption and put in the table what we do today to improve our planning. So, if we go a little bit in detail into each of these four questions, IBP supports us with answering all of these. But if we click on the what to stock, of course, we need to ask ourselves whether we have some strategic stock we need to keep or some critical elements we have to keep in stock. We need to follow our business priorities and that reflects that in our stock model. And then we need to make sure that we cover our supply chain risks. And nowadays, it's very common to have products and components at risk. So, when we have this one, we know whether we are going to stock our finished goods, what finished goods, semi-finished, raw material, and so forth. The next in line is where to stock. Of course, we have the usual dilemma, centralized versus decentralized. And then we know every few years the company change, we centralized, we decentralized. But it's not only that. It's more, do we need to be covered in every node of our supply chain, sub-optimizing, or can we do a more end-to-end optimization? And then, of course, SAP IBP, harmonized planning area, coming to help with our multi-echelon model. Then, of course, we have the how to plan stock, whether it's a consumption-based or it's a more forward-looking with the plan. And then we have, again, the most important one, the how much to stock, what we keep in safety stock. And that depends a lot on our segmentation for also the model, how to calculate some safety stock for specific elements. And it depends a lot on the uncertainty of our demand planning, or sorry, of our demand and our supply elements. We're going to see and spend most of the demo on this part in a moment. But I just want to review here that IBP not only gives us the quantity, but also helps us with the breakdown of our safety stock. So we see what element is our safety stock composed of. And then it helps us understanding the profile of our stock. So what we have on hand, on average, what is our pipeline and the target and so forth. So by enabling this visibility, it's much easier for us to take a look at what actually we keep in stock for real. So I'll hand over again to the demo guys. So here we are in the inventory planning world, where we have received our unconstrained demand from the demand planning team. And then you can see here that is one of our main input. So demand planning is one of the main input of the inventory planning. Then we have other inputs that are very important. One is the target service level, which is something that we agree in the team. The level of service we want to give to our customer or to specific locations and products. And then we have, of course, the forecast error coefficient of variance. This is also something that IBP is able to calculate automatically with some specific jobs. So these are the three main inputs on the demand planning side. However, we know that for calculating the optimal inventory level, which is going to happen here, we are going to need some production input as well. So when it comes to production input, we have many, many inputs. And of course, some of the most important are the lead times, the lot sizes, and also here the whole supply lead time variance, whether it's production or transport. So these inputs, they are used by the system to then calculate our inventories. And the inventory planning module provides many inputs. And then some of them are used as internal for the planner. So as you can see here, we have the calculated average service level at any specific node. We have the propagated demand mean and standard deviation. And then as a main output, we have the recommended safety stock. The recommended safety stock is time dependent. And as we said before, can be calculated in specific nodes, which can be either decided up front as a team strategically, or let it free the system to calculate where is the best place and the best amount to stock. We also have some additional information. For instance, the safety stock with no lot size. This could be important and relevant information for the team, because it basically tells us what would be our safety stock if we had no lot size that affects our cycle stock. So of course, the recommended safety stock or the reorder point, which is another output, will be then sent over to supply planning depending on the strategy, or potentially to our ERP systems depending on where we are doing the final bit of the planning. There are moreover few other elements that are interested for the team. So first of all, we have the recommended safety stock. And then it calculates also what driver the safety stock come from. So we have three drivers. One is the safety stock for the demand variability. One is the safety stock for the supply variability. And one is the safety stock for ensuring the service level. So basically, not only we get the recommended safety stock, but also it's three components. On the top right corner, let me just make it bigger. The system provides also different other pieces of information, both as average and as target. And then here you see your cycle stock, so the stock related also to your lot size and the lead time. Then we have the in-process stock, the pipeline stock, and the average on hand stock. So these four pieces of information are also relevant and important for you to understand the implication of specific inputs in your supply chain. As our, let's say, tool enabled everywhere, we could also run simulations and scenarios here, basically going back into our input and then try to change for simulation. So a very common case is to simulate our target service level, either to customers or internal, and then let's see how the stock profile changes accordingly. Once we have a stock number that we are sort of good at and it's agreed within the team, we can again pass it over, hand it over to supply planning that is using that as one of the main input. You probably know this process of inventory optimization. It's something that you can review every month, but not always you want to change your number every month to account for more stability in your supply chain. However, this flexibility is allowed by the system to either release some, release all, or release none of the numbers. So also here we can prepare some of our charts. Here we have the recommended safety stock, which is one of the main output of the optimization. However, we have even more pieces of information here. The safety stock can be broken down into its components. And then we have mainly three components here. We have the demand variability. So the amount of safety stock that is related to accounting for the variability that comes from demand. The supply variability, which is again the amount of safety stock related to accounting for the supply variability. And then the safety stock for the service variability. So to allow to maintain the service level that we have agreed on. Thank you. Thanks for taking us through that, Ricardo. Both the demand and the inventory. Those are key inputs for the supply planning, which is my favorite topics that we will dive into now. When we will talk about supply planning here, we will talk about SAP IBP OBP. So we will not talk about time series supply planning. Time series supply planning is also covered within harmonized planning area. But it's not something that we often recommend that you would be using. So that's why the focus here is on the OBP part. But if you have any questions along the presentation, remember to put them in the chat and then we'll make sure to answer them towards the end. If time allows. So jumping into the supply planning. And you can say the purpose of our supply planning is really to ensure that we have end to end visibility of our constraints. So and our part requirement, our projected inventory. And with OBP, we will always have that the constraints are applied automatically. So what OBP allows us to do is it allows us to model all of our capacity constraints. That could be production capacity, warehouse and storage capacity, shipping capacity. It could be restrictions on how much suppliers or vendors can deliver to us. It could be subcontracting capacity. It could be shelf life. There's a lot of different constraints that the system allows us to do. When we model these constraints and set them as what we would call active constraints, the system would automatically adhere to the constraints and thereby make a plan that's feasible. Another thing that the system is doing, of course, is that it's making sure that we get the right requirements throughout the system. So that means that it both takes care of distribution requirements. So if we are shipping between warehouses and distribution centers, it takes care of purchasing requirements by exploding the bill of material when we are producing our finished goods or semi-finished goods to make sure that we can get everything in there. Another thing it allows us to do is it allows us to do some sort of supplier forecasting if we have key suppliers that we want to collaborate with, such that we can indicate towards our supplier how much our demand is going to be for a specific raw material or group of materials, etc. The third pillar that we'll talk about here is the projected inventory. The projected inventory tells us something about how much we're going to have in stock for each single skew at a specific point in time at a specific location. So for all of the data that we have in the system, we will be able to see, or for all of the skews at every location, we'll be able to understand how much we are projected to have in inventory at a given point in time. That also allows us to surface if we have any sort of constraints in the short term. So if we have actually inputted production orders or stock transfer orders into the system that are not feasible, it will help us indicate that we will have shortages in our supply chain and help us act on those shortages. So what's maybe super important in OBP compared to many time series supply solutions is that we are working with automatic constraint planning. So all of these capacity constraints that I mentioned or other constraints like shelf life are, depending on which ones we choose to activate, taken into consideration by default, meaning that we adhere to the constraints. We don't just see that there's a problem and then manually the planner has to go and fix the problem. The problem will be solved initially. If there are problems that we cannot solve due to constraints, we will be alerted with what we call gating factors that tells us why we cannot solve a specific problem. Already today when you're working with OBP, not within harmonized planning, it's also possible for us to do scenarios. We can do that quickly because we are doing automatic constraint planning. But the thing that differs and that we'll talk about in a little bit is that right now we can only do changes or scenarios related to our supply planning. So we could do a shutdown of the production plant. We could do some sort of analysis. But if we have changes in our inventory or in demand, it's very difficult to do those scenarios. But first, we'll take a little bit of a look of what this looks like, what supply planning in SAP IBP, OBP within harmonized planning looks like in the system. So now I'll hand over to the demo again. So now we start looking at supply planning and specifically what we're going to be looking at is the order-based planning within the harmonized planning module. So we have gotten our safety stock inputs from inventory and we have gotten some demand from the demand planning process. One of the things that is important to understand when we're talking about order-based planning is we're generally working with an automatic constraint system. So in the top here we have a graph that tells us something about the ability to deliver to the demand in our system. So currently we can see that we have a little bit of demand that we're going to deliver late in September. But generally speaking, we are going to deliver on time and throughout the rest of the year. I just quickly want to show you that if we were looking in a different scenario, we might see that because it's a constraint system, it is not going to deliver in the same way. So I'm just going to change to a different scenario here where we have inputted more demand to illustrate that what it would look like if we are incapable of delivering on time. So here we can see that we have more demand in the next coming months that we are not going to deliver on time. Just to quickly give you an idea of that when we are working with the supply plan, it's important to always look at the end product. Are we capable of delivering on time to our end customers? Of course, when we look far into the future, unless we really have some big bottleneck constraints, we will see that our demand is going to be met because we are just able to prepone production, etc. So if there's no larger constraints like shelf life, etc. or capacity constraints, we will generally see that far into the future we are capable of delivering on time. I'm just jumping back to the baseline scenario here to go back as well. So one of the things that's important to understand when we talk about order based planning is that we are not just getting a number, we're actually working with the orders. So when we get a demand signal from demand, we get it as an unconstrained forecast, but we are still pulling in all of the actual sales orders from our EOP system. Directly into the system and it's using that in our forecast consumption to make sure that we are not over planning our demand. So in this case, we can see, for instance, that we have a forecast of 700 and the sales order of 150, meaning that our open forecast, so the forecast that we're actually planning for becomes 562. One thing that's interesting to look at here is that we can actually see all of the order information for these specific sales orders as well. So we're not just talking about a number in a bucket that could be a week, a day, a month, as you would do in traditional IBP supply planning in the time series world. So if I open the order information here, we should see that it opens up and tells us specifically what are the orders that are inside that time bucket that we're looking at. So here we can see that we actually have two different sales orders for the same customer, but on different days of respectively 50 and 100. On top of this, we can, of course, look into specifics of how much demand we're actually going to fulfill. So we have some different tabs that tells us something about demand fulfillment, late and unfulfilled demand, etc. Filtering out only specific cases such that we can focus a bit more. If I quickly jump into the demand fulfillment here, it tells us something about on product level, how much are we actually going to deliver on time, either in the total or in a specific period. So in week 36, for instance, we can see that we're not capable of delivering on time, but we will be delivering later. And as we progress further into the future, we see that we're able to deliver more and more of the demand. So this could be because we have a lead time constraint. So we're not capable of getting the finished goods to the customers in time, but the customers are willing to wait. So therefore we are delivering to them at a later point in time. To understand a little bit better what this might look like in terms of our capacity utilization, we can of course go in and have a look at the specific capacity utilization on the different lines that we are producing on. So in this case, we see up here in the top a heat map that shows us week by week what the capacity utilization is at the different machines we have. In certain cases here, we see that we are actually reaching our max capacity of 100. But because it's an automatic constraint plan, what the system will do is it will push the production to other production lines. And it will try to prepone production if possible. So we see here in the initial stages in week 38, week 39, if you remember, that's also where we saw that we are not capable of delivering on time, that we are having an overload. So we cannot actually process enough materials right away. So therefore we are being late. Here is also one of the places where we have opportunities to go in and make adjustments to our plan. So as a supply planner, we could go in and make simulations on what would it look like if, for instance, our machine one was not available in two weeks. So if we go in and make adjustments to the available capacity, simulate it and run a simulations, we would immediately be able to see what impact does it have when we do that simulation. So what impact does it have on our capability to deliver to the customers? So if we have constraints that we have simulated or we actually do have constraints in our supply chain, we can also, of course, go into our gating factors. Now I've just opened a tab here that we will jump into to get an idea of why certain pieces of forecast might not be fulfilled. In the gating factors, we get a lot of information for specific products, why we are not able to fulfill it. If we choose one, we can get some more information about the specific order that we are trying to fulfill and what the issues are. So in this app, we will see all of the problems in the supply chain, you could see. If you select one and go to show order network, it will open up and tell you which gating factors are relevant. So here we can see that for the demand, which is a sales order that we are trying to deliver, there are some problems with lead time for both semi-finished goods and our raw materials, and we have a resource overload on our packaging line. This can be expanded, of course, so you can see all of the elements that are relevant to actually deliver the sales order. So all the way from the sales order to the stock transfer requisition, planned order, purchase requisitions, etc., indicating where in the supply chain we actually have gating factors. This can also be illustrated in a graphical view, where it highlights how the sales order is being fulfilled, and everywhere we have a red intersection is because we have some sort of constraint that is preventing us fulfilling this sales order at the time that it was requested. If you want to get more insights on exactly what is happening for a specific product at a different specific location, you can, of course, navigate to the Projector Stock app as well. In the Projector Stock app, we have the overview per location product number. So up here in the top, you can see we have different product location combinations. And then when we select one, we see down here at the bottom what you might be familiar with as the MD04 view in S4. It is not exactly the MD04 view, but it's built in the same way. I'm just going to expand it so you can see it a little bit better. Where we have the stock as our first point, of course. And then we have different either demand or supply elements that tells us something about the stock projection. So in this case, for instance, we have zero stock at the beginning, but we get some forecast already today is the fourth. So already today that we are, of course, not able to fulfill on time because there are some lead times in our system. So we cannot deliver it already on time. So we see that our stock projection is going negative. And then at some point we start replenishing via stock transfer requisitions in the system, such that we can actually fulfill those pieces of forecast. These you might see here are our order numbers as well. So this is very tightly linked with your S4 system or ECC system, because it's actually the orders that are flowing back and forth. So if someone goes in and transforms this stock transfer requisitions into an STO, we would also immediately see it inside of IVP due to the real-time integration. From here, you can also manually go in and make stock transfer requisitions, deployment requisition, purchase requisitions, or planned orders, depending on what master data is set up, which would allow you to do so. So this is an app that is super nice for people to really investigate specific issues and understand a specific product at a specific location and substitute a lot of the things that you were previously doing in MD04. The reason that we need this app instead is that there are some of the constraints that we might not be able to reflect inside of MD04. So for instance, if you have shelf life constraints, MD04 cannot take that into consideration. But this app would be able to understand if we are planning to expire specific products. Cool. Now we've had a look at both demand, inventory, and supply. And maybe it doesn't look too different from what you know today if you're already working with SAP IPB. And from the looks of it, it isn't too different. Because what we've looked at is the three different pillars that already exist today. So demand in its own planning area, inventory in its own planning area, and response and supply in its own planning area. So the supply chain planning, OBP. Today you can do all of these things in their own planning area, and the process works very well. The problem is that when we, for instance, want to make a scenario in demand planning, we want to see what happens if we're increasing or creating a big promotion for a product, what happens on our capability to deliver. Because traditionally, IBP has been in separate planning areas, the scenario planning functionality doesn't allow this. The scenario planning sits within one planning area. So that means that you cannot transfer a scenario directly from demand to supply. So we cannot see the effect of the scenario that we're doing within demand. The same goes for inventory and, of course, supply as well. Supply doesn't affect the others so much, but it takes the inputs from both demand and inventory. So this is what it used to be that we required that we have replication from demand to inventory and from inventory to supply and also from demand to supply, of course, to enable us to do some sort of simulation. In the new system in SAP IBP Harmonized planning area, all of these building blocks are in the same planning area. That means that the master data is the same, the key figures are the same, we have the same time profile, etc. And it enables us to create scenarios across all of the different modules. So now when we make a scenario within demand, we can directly see the impact on response within supply. The same goes for inventory. If we make a change to the service level for our A products, for instance, we can directly see, okay, what does that mean in terms of our capability to deliver in the future. So we really manage to tie together end to end within scenario planning when we are within harmonized planning area. So maybe to get a little bit better understanding of what that might look like within IBP, we'll have a short demo just to see how the scenarios can be compared as well and some examples of scenarios that you would be able to run when you're in a harmonized planning area. After we've generated our finite supply plan, we've shown that within the same planning area, we can generate a demand and release that to both our inventory optimizer and inventory planners, as well as our supply and production planners, to generate a finite plan that respects the constraint capacities that we set in the system, that respects the orders that's coming from S4 and ECC, and that respects the recommended safety stock levels of the inventory planners. However, if we want to take this one step further, we might want to say that we need to be able to simulate different plans at the same time. And luckily, that's quite easy in SAP IPP through this concept of using scenarios and all versions. So, Andreas already showed that this scenario where we had an increase in demand led to that we couldn't fulfill or at least that we were quite constrained on our packaging and processing resources, which led to a lot of demand being late delivered. We might then simulate different scenarios based off of this and say that, okay, maybe we can solve this issue by working overtime. And we can create all these scenarios that we can compare with each other. So, say here that we're working overtime where we increase the capacity on our lines. You can see here that we have 248 hours on our packing machine instead of the usual 168. And that seems to actually smooth out quite a lot of our resource constraints by actually opening up these resources. So, what's a good way of actually working with scenarios? Well, we have a 12-month outlook view here that allows us to IPP visualize what happens at the same, or we can comparatively visualize what happens in our overtime scenario versus in our base plan, what happens in our shutdown scenario versus our base plan. And then we can kind of compare these plans. Now, maybe we're not happy with our shutdown scenario because of this constrained resource on processing that looks very red. We're not fulfilling a lot of demand in September. So, if we want to actually go back to our overtime scenario and make that our standard based off of the KPIs and different metrics that we want to measure ourselves on, then we can promote this as our new baseline plan. And the way that you do that is that you go to scenarios and then you promote this scenario. If you click this button, the scenario will become a new baseline. And there's no limits to the amount of views that you can create. For example, you could also simulate what happens if you constrain your raw material intake. You can do that through some key figures. You can also say what happens if I run a different demand process session where I prioritize one customer always over another. What does the customer deliveries look like? Or you can go in and say what does my projected stock development look like in these different scenarios. So, IBP is quite a powerful tool where we're talking about harmonized planning because we can simulate everything from inventory to demand spikes to service level changes all at the same time. Now, if we want to compare more than one scenario, we have this ability of scorecards. So, for example, if you want to look at the six-month demand fulfillment, then we can also include more scenarios in our selection and compare them at the same time before we choose to promote anyone. I think that that is everything I wanted to show you so far. And I'll give it back to Andreas and Ricardo. Thanks so much. Right. So, now we spent some time talking about scenario planning and that's, of course, one of the really cool things that harmonized planning area brings for us. But I would like for Ricardo just to take you through some of the other reasons why it might make sense to migrate to a harmonized planning area. Of course, Andreas. And needless to say, this end-to-end embedded scenario is quite cool. But, of course, there are three more main reasons you should consider the harmonized planning area. So, the first one is that this is the future-proof environment where SAP IBP is going to be developed. So, of course, there will be new functionalities that are going to be released also to the old planning areas, demand, response and supply and inventory. But most of the effort will be put in this one. And then, of course, with time, that's going to be the only place where the new releases will be put. So, of course, if you are intrigued by new functionalities and you want to always be up to date with the latest releases, then that's the place to be. The second point, which is sort of the foundation of why we can do these super cool end-to-end scenarios, is that we have one version of the truth. So, some of these key figures that normally were replicated, some of the master data that were adapted for different needs, now they reside on the same data model. And every planner can look at that key figure and be sure that that's the number that all the other colleagues and all the other departments or teams are actually looking. And this one is the foundation also to the third point, which is very trendy nowadays, rightfully, which is the possibility to utilize AI and machine learning tools within our model. Of course, you might also have external AI tools and models, but also SAP is investing quite a lot in this area. And there are a lot of embedded tools in SAP ABP, like that is Joule, like our Gen AI. There is the agentic part that is going to be happening soon. And then, of course, all the models like the machine learning forecast and so forth. So, this edge, if you want to edge AI, the most important thing is that you have one source of truth, one data foundation. So, we can exploit it for real and we don't have to sort of bridge three different models and extrapolate answers. There are also other benefits, but these three plus the scenario are really paying the effort of this. Yeah, and I think there's a lot of small functionalities that they're also adding on the harmonized planning specifically. Of course. But yeah, main building blocks here. Yes. So, Andreas, it was very fun to be here with you and with you guys this morning. But as we all know, all good things come to an end. And we want to conclude by putting you at the center. So, we have drawn these three cases where you might find yourself. And then we want to give you our sort of best practice or our idea of how you could move forward. Of course, you might find yourself in a situation where you don't have SAP IPP or you don't have a planning tool and you are considering that. If that's where you are, then there are no specific reasons of why you should not start with the harmonized planning area. Also because it's implicit, but harmonized planning area has everything in itself, but you're not forced to do everything at the same time. Or you're not forced to do everything at all. Right? If you just need demand planning for now, you can start and implement your demand planning and let the rest be. But at least you have the foundation. Second case, you might find yourself in the process of implementing IBP as we speak. And you might be asking, is it too late to do this change? Well, first of all, you should consider at least a change and see if the decisions that you made, they are compatible with the harmonized planning area. So if that is, then it's merely a technical exercise. It is still a small assignment, but it's more technical. If you have made some decisions where the data model does not fit very well or you need to rethink, then of course, this might be a bit more tricky. You need to open up some decisions that were closed. But remember that the more ahead you go, the farther you go, the more expensive it becomes to do the switch. Then there is the last case, which is that you have a system that is already up and running, and then you are happy with it. So in this case, you might be wondering, is there any need for me to change? Well, before blindly move into the new platform, we would recommend you to think and build a case. Of course, we have seen now four major benefits that you might want to have, but it's not a given. And of course, we know also that SAP is going to provide tools that support the migration. But of course, it is an option to already start migrating. Moreover, and then Andreas, you can of course pitch in here. We know that you might have a couple of modules already up and running, and you want to have a third one maybe starting up. So let's say you have demand and inventory and you want to implement supply. So what we would recommend in this case is to create a new planning area, harmonize planning area, run your supply, create the foundation to eventually move the rest of the solution. So with that, we close. Of course, we hope you had fun. And then now it's your turn, guys, to ask a question. And of course, take a few minutes to think. And we are here for you. Yes. And I can see we already got one question in the chat. Reading in terms of people capabilities, do you think this will allow to centralize supply planning and production planning roles? How we can establish the boundaries between the roles? And I think it's a follow up question on the same here. Are we going on the end to end planning role with the support of AI? So I think, of course, there is an opportunity to centralize the roles more because OBP is doing network planning. So we are doing the full network planning. But there might be still a distinguishment between production planning and supply planning because OBP only works at a day level. So we still won't have the distribution of production orders throughout the day, for instance, in the IPP, OBP. There is possible to use PPDS or ePPDS to do the actual production planning or scheduling. But allowing OBP to do the bulk work of what should we actually be producing and then only having PPDS ensuring exactly at what time are we going to produce. So there might still be a distinguishment between production planners and supply planners. But the intention of the supply planner is to be end to end, but maybe not on the very short horizon for the production. And maybe to answer on the support of AI, harmonized planning in itself doesn't give us AI, you could say. But it enables us to develop AI in the future on top of the harmonized planning area. And so there are functionalities being developed continuously by SAP, both SAP IBP dual inside of SAP IBP, but also the ERP dual that can be added on top via SAP BTP. So just implementing harmonized planning won't give you a lot of AI support from the get go. But it enables us to build that AI capabilities on top for the end to end planners. Maybe if I can just follow up on this question. I think generally this more automatic way of planning with some, as you said, embedded AI or external AI, it's shifting a bit the role of planning to a output based plan where we spend the time making the plan rather than an input plan where we have the tools that are now providing us a plan. And we need to make sure that the input we feed are correct, like our customer priorities or our service level, our variabilities and so forth. So there is a bit of a switch in the planning role that we are seeing lately. Cool. Again, if you have any other questions, feel free to put them in the chat. Otherwise, Ricardo, maybe you could just talk about quickly if we're actually already doing this at any of our clients. Are we actually already working with the harmonized planning area? Yes. So actually we have a couple of cases. One, at least that I'm part of myself, where we are starting a full implementation with harmonized planning area that I started a few months ago and then we had some discussion. And then of course, at the end, we opted for the harmonized planning area. It's going to start small and then it will increase. And also we do have some cases that during the implementation phase, we have decided to switch and maybe readjust a bit the plan, readjust the resources to move into the harmonized planning area with at least part of the solution. Let's say the one that was the more behind on the schedule in the plan, sorry, and move it into the harmonized planning area. So now we have the harmonized planning area where the foundation is laid and then we are moving soon in all the other trucks. Cool. Good. But it doesn't seem like we have any more questions. No, but you're always free to contact us, right? Yes. Yes. And yeah, of course, we know that this is a little bit simplified and there's a lot of considerations to take when you actually have to make a decision like this. So what we showed here, it is a bit simplified, right? But it's to give you an idea of the general direction that we would recommend. So if you're actually in the situation where you have to make any of these choices, really feel free to reach out and ask because there are technicalities that we haven't covered in here that could mean that you have to go a different direction than exactly what we're proposing here. It's like the analogy of the house we did, right? No matter where you are in the process, whether you are starting building, you are already there in the process or you're already living in a finished house, there might be a good reason to see if we can harmonize more our environment. Yes. But then I think we will say thank you from our end and thank you for tuning in and listening to this talk. And as I said, please reach out if you have any questions related to harmonized planning or any other supply chain planning problems that you're seeing. Thank you. Thank you.