How Illumina Leveraged SAP Integrated Business Planning (IBP) to Drive a 40% Reduction in Excess Inventory

From the Americas SAP Customer Community, I'm Jim Lichtenwalter and this is Asak Talks. A podcast devoted to conversations with the innovators, leaders and change makers shaping the future of enterprise technology and the SAP ecosystem. This week on the podcast, Supply Chains takes center stage. According to the 2026, ASUS calls the SAP Customer Research 57% of Supply Chain Professionals who participated in that survey said that optimizing costs is a high priority for their enterprise. One of the best ways to optimize those costs is by eliminating the waste often associated with running and managing supply chains in order to drive improved cost efficiencies. In this episode, I sat down with Leon Trevitt, Senior Director of Global Integrated Planning at Illumina and Arpanas-Sixaria, Director of Life Sciences Solutions at SAP. They walked us through how Illumina, a biotech company used SAP Integrated Business Planning to dramatically reduce the organization's supply chain waste among other improvements. We also discussed how the organization is using AI and supply chain operations. The roadmap for its IBP implementation and how SAP solutions are currently addressing common supply chain hurdles, those insights and more this week on ASUS. If you're an SAP professional and want to stay ahead without chasing every single SAP news and update, then ASUS first five has you covered. Every Monday morning, we delivered five curated stories on SAP Strategy, Customer Successes, and ecosystem trends straight to your inbox. These are trusted insights, community perspectives, and practical, tangible takeaways all in one place for the ASUS community. The ASUS first five, the weekly briefing, SAP professionals rely on to start their weeks informed. Sign up by clicking the link in the episode description. Well, partner, Leon, thank you so much for joining us and walking us through the great work you are doing. I appreciate you all joining ASUS talks today. Thanks, Jim. Yeah, pleasure to be here and thanks for having me. Yeah. Nice having you here. Leon, I'm going to start with you as a representative of Illumina. Why don't you give us an overview of the organization and the customers that you all serve. Illumina as a business, we manufacture and distribute next generation DNA sequence in equipment. So as you can imagine, sequencing DNA is a huge benefit to improving human health. Our customers range from, you know, in the clinical space, helping people diagnose where disease is and things like that, all the way into the research space where they're doing new drug design, drug synthesis and things like that. So broad applications and also into agriculture. So sequencing crops and seeds to make food more sustainable. So a very broad kind of customer base and application. So Parna, you represent the SAP set of things. You all worked with Illumina, one of your customers, to help improve some of the supply chain planning challenges that they had. To set the stage, when you speak to SAP customers, all out like Illumina, what are the main supply chain challenges that they are facing right now in 2026? Going to the conversation with Lexins, customers in Austin as what keeps them up at night and most of them, at least in the supply chain division, I get answers surrounding, hey, we wrote off a $200 million inventory worth this quarter, or we had about 60% of wastage in our last trial. You know, those are the real numbers that we talk about. $200 million is a bigger number. Of course, if you're looking at it in terms of what that looks like, but it is a very significant number of inventory that companies kind of write it off. And when you look a little deeper into why those numbers are happening, pretty much it always traces back to the same place. The planning systems and execution systems, they're on very different information. It often, this information is not synchronized across the platform. So what I would do is I'll do it, take three examples of what I see on the clinical trials, which have worked very closely on the clinical trials by chain management. The 50 to 60% overage is kind of has been accepted for decades. It's 60% overage, yeah, it's common, write it off. Because it is rather better to have a drug in X's than running out of the drug mid trial and a patient failure, which is a very big huge regulatory event. So it's better to keep all that overage. So companies usually build in huge buffers as insurance. And with the small molecule drug at a lower cost, it is manageable. But now we are moving into biologics. The cost structure is entirely different. It's 60% overage on a biological drug. It is tens and hundreds of millions of dollars. It's not something that is a very small number. And so the map doesn't sit right with the, with the right of that has been happening traditionally. So that is one of the main supply chain challenge that I hear from, at least the clinical teams. And on the commercial side, in the pharmaceutical sex segment, still, usually in the pre-COVID era, the gross margins of these pharma companies were about 77%, 70%, 77% around that range. Dimension right-offs are up to 4% to some 6% of the annual Dimension right-off is pretty much not an alarming thing. But when you are adding up all those 4% to 5% across all, at least the 25 largest pharma companies, it's in billions, the numbers are in billions, we're talking about. So that is something that needs a fix. And that's one of the huge supply chain challenges that I would say I keep hearing from my customers. And coming to Meddywise's side, which I would also ask Leon to comment down that, 20 to 30% again. Inventory sits pretty much in the field. We call it as a field inventory, and it is not accounted for sometimes in the planning systems, and sometimes in the procedure rooms, hospital sites. Even the sales rep trunks, the inventory is sitting over there. And planning system is usually not looking at any of the visibility. They do not have the visibility of any of these inventory. So the buffers are higher, and when it comes to working capital, you have to have higher working capital because now inventory is at multiple places. So whether it is in a sense, whether it is clinical trial, commercial side, Meddywise's, the inventory, right-offs, or optimization, I would say is the major critical challenge in the life sense of feature. Well, Pana, thank you for that robust overview, Leon. How does that context, does that compare with the challenges you all are facing at Illumina? It does. I mean, I think working capital visibility of working capital and the optimization is a big focus for that. For the longest time, we were, how can I put it, you know, kind of cash rich. So the focus was really on customer experience. As we start to move forward into 2026, there's a lot of geopolitical macroeconomic challenges. The competition is becoming more apparent, and we need to be cost conscious. So I think the focus on optimizing our working capital, making the right investments, and where to fully leverage that is front and center in terms of how we drive forward with the strategy. To be clear, yeah, we don't, we haven't experienced a $400 million dot-write off. That one's scary. But, you know, when you talk about scale, proportionally, yeah, it's a big focus area. Obviously, it's just waste, and we're really looking through lean principles to just take waste out of our processes and make sure that we don't create waste in our manufacturing and processes and just optimize our investment in working capital where it makes sense. We are digging a little bit deeper. Can you speak to the organizational and industry-specific hurdles you all at Illumina were trying to overcome by leveraging SAP solutions? Very specific, so in Illumina's business, it's a bit of a blended supply chain. There's a kind of hardware, you know, maybe more device type supply chain, as Abhana was mentioning. There's also a kind of pharma type supply chain because it's biotech where we're manufacturing and creating enzymes and different biologics and industry-wise, that comes with some challenges around managing shelf life and when products are going to expire. So when we were looking at the SAP solutions, we clearly wanted to have visibility to all of our processes in a quicker, more agile way so that we can make the right decisions in the time you manner. And then also, you know, really think about how do we maximize that investment in working capital and make sure that we don't have any wastage. So as we were looking at SAP solutions, it revolved around optimization, around integration to each of the different tools, and real-time, quicker visibility to make better informed decisions. And now, a brief message about ASUB chapters. Are you moving to SAP S4HANA? Are you trying to integrate systems that were never designed to talk, struggling to keep Master Dana clean with budgets getting tighter and tighter? If any of this sounds familiar, you're not alone. In fact, most SAP customers are facing the same. same challenges you are right now. That's why you should attend an ASUG chapter meeting. They connect you with peers who have already navigated SAP S400 migrations, untangled integrations, and found practical ways to move forward. These are real experiences shared openly, because SAP can be hard, and you don't have to figure it all out alone. Find your local ASUG chapter by clicking the link in the description. Leon, can we you give us an overview then too of the SAP solutions you are using, especially as it relates to supply chain supply chain management operations? Yeah, so we went through a journey as the owner of Global Integrated Planning, and I also went into the supply chain digital road map. Back in, I'm going to say 2016-2017, I built out a digital road map with each of the functions within supply chain, so plan, source, and deliver, and we looked at our current state and we had a vision back in 2016-2017 of what does 2020 look like, and obviously that was like six years ago. We refreshed that every year and kind of pushed out the horizons. We took stock of the capabilities that we had and started to say, what capabilities are we going to need in the future? We need to be able to drive up customer experience. We need to make sure that we're optimizing working capital and making better investments. We need to look at ourselves and operations plan in process, and how do we drive up the maturity in that, so that as an enterprise, we make better, more enterprise level decisions. So we took stock of all of that, we looked at the toolset that we had, and I always knew that we in the future were going to make a transition from SAP ECC to SAP S4HANA Private Cloud Edition, the big long name there. So to a certain extent, as I was building out that digital road map, I also wanted a future proof fit for where we were going to go in the future. So as we looked across the suite of tools, we clearly had a leaning towards simplified integration and things that were in within the SAP suite. So we implemented SAP IBP. We started with the SNOP module and the demand planning module, and then as we progressed through the road map, we subsequently implemented IBP control tower, then we implemented IBP inventory optimization, and then we kind of rounded that off a few years back when we implemented response and supply and transitioned to order-based planning. So that was kind of like on the plan side. In the other legs, the other pillars of supply chain, in deliver and source, in deliver, we implemented EWM, so extended warehouse management and integrated that into ECC. We implemented transportation management, SAP TM, and integrated that into IBP. We also integrated GTS, so SAP GTS, and implemented that. So that kind of put a pin on the deliver side, and then in the source side, we lend heavily into Ariba. We integrated supply chain collaboration or business network, as it is now, into IBP, so that we could have a signal coming from our planning system out to the supply base to get some forecast commit, look at capacity and constraints in the supply base, and then make planning decisions around it. So we integrated that into the source space, and then have other tools like concur and et cetera to manage spend. So you have solutions that are touching basically every facet of your supply chain operations? We do, we do, and I think the big thing for me was doing it in such a way that we had the ability to integrate. So you know, you could have all of these tools that is entirely possible that they could work in their own little silos within the pillar, but you're going to lose a huge amount of benefit and agility if you don't have some sort of integration. So integrating response and supply or order based planning into transportation management and doing deployment. So when you're planning to move inventory between two locations, having that integrated into transportation management so that you can tend to free and make the right decisions around how I want that inventory to move was a great benefit, or integrate in, as I say, IBP when we're planning into business network and collaborating with suppliers. Again, it was about the integration for me, and then obviously thinking about I/O and coming back to that working capital optimization, like how do I make the right decisions that all of the different echelons of the supply chain to maximize my investment there when I'm thinking about the working capital investment. Leon, you said you started conceiving and planning for this back in 2016/2017 area. When did the actual implementation journey begin for you all? And how many end users were eventually impacted by your usage of SAP solutions? We started building out the roadmap 2016/2017, as I said. Obviously, as I wrapped up 2017, I had to go in front of the steering committee and the executive leadership team and put a business case together. That got approved at the end of 2017, and we kicked it off in 2018. And then we had multiple phases of these projects. As I said, as we implemented various modules in chunks to build it out between 2018 and 2024, I guess, actually. We didn't do a big ban, we did it in sequential chunks so that we were making sure that what we delivered and deployed generated the value from the business case. And it kind of created that momentum to say, "Well, yeah, you did that last one. It went smoothly. It delivered the value. Let's now go and implement the next chunk." And that was kind of the approach. In terms of users impacted, there's 500 plus people in the supply chain that are impacted by these various tools and interact with them. And then ultimately, the output and the integration goes into a manufacturing network, which is global. So we have manufacturing in the US, in Asia, in Singapore, as a distribution in Europe. It touched on those as well. We have about, I'm going to say, two and a half, 3,000 people in operations that have started touching on as well. So quite a big stakeholder group. You all recently presented this customer story, this project at SAP Sapphire Nasega Annual Conference. One of the things that struck me when I was going through some of the speakers and attendees of the conference was the way AI was being used in this project. Can you all speak specifically to how AI was actually being leveraged in Aluminas SAP supply chain operations? So from SAP Perspective, before 2025, our planning tool was pretty robust in terms of time series planning. And then last year, we, of course, we released the order-based planning, which was using more of a shelf life. But in 26 or two release, which is our February release of this year, we have strengthened our IBP and shelf life planning capabilities all the way into those semi-finished goods and other bomb components as well. I'm calling that out because in our life sciences world, whether it is farm or clinical, medis, minimum required shelf life and component shelf life are pretty important characteristics. And now planning rungs can check all these remaining shelf life of the API, semi-finished and everything, all with the bomb components. And then can plan appropriately based on your shelf life parameters. And that's a very significant thing for farmer because it really eliminates waste at multiple levels. So that is one of the critical features, the component shelf life that was launched. And you also launched something called a synchronized planning model where we don't have the master data is always in sync. And you do not need to have a lot of integration with respect to your time series and order-based planning. And it is all one big platform that is actually supporting everything. So these are the rock structures I would say is where IBP has really mature to. So once these structures are in place, that is where your AI really comes into picture. And from the AI agents perspective, we actually launched a couple of agents in IBP, demand fulfillment agent, delta planning agent. There was also something on the jewel that we launched, which is looking at compliance monitoring there, which is exclusively for GXP systems and farmer systems. But the demand fulfillment assessment agent, it is actually traces all the fulfillment gap between the shortfall, which batch, which campaign, what is a constraint around it. So it looks at all those parameters and helps you plan those. So there has already been a lot of work that is launched and much more is upcoming. And of course, customers can develop their own AI models based on once you have these data structures in place, all the building laws in place. To be specific around how we were approaching AI, I think upon and nailed it in the early days, so I would say like pre 2025. The AI that we were exploring and employing was more around primarily in the demand planners face. So we were using a lot of AI and ML around demand forecast optimization, outlier detection, anomaly detection. So we were using various tools and algorithms to try and get a better quality forecast. That was primarily where we were trying to leverage AI in the true sense. Then as we start to step forward into 2025 and then some of the capabilities that Aparna was talking about, there are other capabilities that SAPU deployed within IBP around. And I'll call them assistance as opposed to agents because they they were more in the natural language space, helping explain results. So forecast display and ability. So unless you're a data scientist or you're really into forecast algorithms, then there are people that are. Knowing the nuances and the details of double exponential smoothing and the impacts of an alpha beta and a gamma on your forecast model isn't really intuitive. So the ability and the capability of an assistant that can in natural language explain why your forecast result is your forecast result is been a huge win. So we've been exploring that and using that capability. Similarly on inventory optimization, and I know that I keep coming back to working capital optimization, but that's where the dollars are. Explain in why your safety stocks at that node in your supply chain and your hierarchy is that safety stock. So is it increased because you increased your service level? Has it increased because the demand for latency or variability is increased or is it decreasing in this node but increasing in this node because a lead time has been reduced and your manufacturing is really humming and they're in their lead times. Explaining that in natural language is a huge win in terms of engaging people to use the tools, making it intuitive and really exploring the capabilities that we've enabled to drive a benefit and a value. So those are the ones that are kind of front and center. We're exploring right now the idea of actually not an assistant but an agent that can actually go do things. And I think the panel touched on one in terms of the demand for film and agent. And then where can we actually have a true agentex solution to be able to take on some of the work. So some of the teams can add more value in generating a better quality forecast as opposed to the steps that I have to go through to actually execute that forecast and demand plan through the supply chain. So we took a kind of slower approach, our approach around AI and generally transformation is to look at our business processes and redesign them to take out waste. Then we look at technology to see where we can automate as much as possible and drive efficiency. Then we look at AI where I can use AI to get insight and that would be kind of like in the assistant space, insight that's intuitive, that's in a natural language and people can understand it without being technically deep. And then we step into an agentex space where I can have AI or an agentex solution actually go do things for me. And we've kind of been taking that that four step approach as we've been thinking about transformation generally and it all happens to be within the SAP suite. - Okay, great. Leon, you mentioned earlier that all organizations, not just once in your field are contending with global business disruptions, supply chain disruptions. - Yep, when we think about today, how has aluminum supply chain operations changed and become better equipped with SAP solutions to contend with these disruptions? - Yeah, now, okay. We have a really, really good use case in this example. So as I mentioned about our roadmap and our deployment, we did it in chunks. The second chunk that we implemented in and around control tower to drive some visibility and integration into the business network with Ariba and then inventory optimization. We deployed that during COVID remotely. - Fun. - Yeah, it was, so yeah. So there was a lot of scenario planning that we did in the previously deployed elements around demand planning and SNOP. We were using that for time series based on planning. We had the ability to be able to do scenario plans around the impacts of what we were going to be doing during COVID to be able to make sure that we could deliver the additional capabilities on control tower and get more visibility and inventory optimization. And then, first forward, when we've got the whole suite, whenever these macroeconomic or geopolitical challenges coming up, we've got tools that enable us to quickly be able to scenario plan and try and assess risk. So we can have multiple scenarios and when something plays out, whether it be tariff related or whether it be some sort of transportation challenges with not being able to ship to certain countries, we can scenario plan the impact that that has on the business really quickly. Now, historically, that would be a lot of heavy spreadsheet work. You'd have to make sure that you kind of reconciled it. So it's made that much more agile around how we respond to some of these challenges. And it's a huge opportunity, as we think forward, into the agentex space to say, well, can I create an agent that is ready to go when I need to assess one of these scenarios and just let them do all of the work and then come back with the recommendations with a human to be able to say, yep, I approve with that right. Well, we'll change shipping from Asia and source it from Europe now because there's a thing that I know the impact, I know the cost, so on and so forth. So that's the future, but where we are now, just leveraging the tools that we had to be able to scenario plan and have those options ready, much more agile and quicker than it was before. - Lea, related to that value, can you give us an example of some immediate ROI, alumni recognize, when it implemented, IBP and Business Network Supply Chain collaboration solutions? - Basically, the big win for me was, we got better signals to manufacturing. So we were able to increase our efficiency within manufacturing. Numbers probably, you know, out of the gate, probably 10 to 15%. The real interesting one was when we then subsequently implemented inventory optimization, we had a 30% improvement in our turns. We were better at where we needed to focus the inventory and then the other one, the optimization of our excess on obsolete, and we were able to reduce that by 40% as well. So we could reduce 40% in our excess on obsolete and we improved our turns by 30% overall. - And now a brief message about ASAP TechConnect. In a world of custom code, system upgrades, and constant pressure to keep the core clean, SAP developers are being asked to do more faster to modernize applications, to improve performance, and to prepare for what's next. That's where ASAP TechConnect comes in. Join fellow developers for deep technical sessions, hands-on labs, and real solutions, you can take back to your organization and use on your systems. If you build, extend, or support SAP, this is the conference where work gets done. ASAP TechConnect. Registration is open now. Click the link in the description to learn. (upbeat music) - You hear those figures being thrown out. I think it speaks to the relationship that SAP had with Illumina. Can you go into a little bit about how you all collaborated with the organization during this project? What did that relationship look like? And how was it maybe a little different than a regular software vendor customer relationship? - I mean, from SAP Perspective, if you look at how Illumina embarked on this journey, they didn't have the perfect on-cloud kind of conditions or everything to be perfect. You know, they started their journey with playing when they were needs to see, not even on export. So that is a great story and how a collaboration works. I would actually leave again to Leon as how he worked very closely with SAP on that collaboration, but it was a three-in-the-part Illumina SAP and the SAP partner for Illumina who has actually worked on these things. With ECC connection and IBP was, I would say also still not yet matured when actually Leon was implementing IBP. But the story here is that Illumina did not wait for RISE, perfect conditions to be on the cloud, for all the GXP master data on the cloud. These shots started it pretty early in their journey when with ECC connection. So that's something that is really commendable over there. - To answer a partner's question around collaboration. So when we were going on this journey, I actually went into SAP and tried to build that relationship there. And we went into value engineering as a function that SAP provided. So I worked really closely with the value engineer in team and tried to assess where are all of the levers and the benefits that we can really tease out when we're going through this implementation. So the partnership with SAP on value engineering was invaluable in ultimately getting the business case aligned and approved with the senior leadership team and driving that forward. Also to a partner's point, yeah, we didn't wait around for things to be in the cloud or go on to RISE. We did it when we were still on ECC. Another thing I would add is when we were going through it, I was continually assessing, 'cause we were quite early in the IBP journey, I was continually assessing the maturity of each of the products. So our first tranche of implement in IBP for demand and IBP SNOP, SNOP was the first IBP module actually. We went that route because at the time, I wasn't confident on the maturity, and this is back in obviously 2018. I wasn't confident of the maturity of the, what was called supply and response at the time, and then, naming convention about changed over time. So we actually implemented APO. So we implemented IVP for demand, we implemented IVP for SNOP, we implemented APO SNP and we also implemented GATP and APO. So that was the suite that we implemented and that was interesting because it was a bit of a double edged sword because you know, I'd kind of done the big sell on IVP and how this was the future. And when we deployed APO, rock solid, then it was like, well, you promised me a Tesla, but you gave me a Datsun, but it was really, really rock solid. So then there was a journey of, you know, taking pieces off the Datsun and replacing them with Tesla parts, you sure we were implementing the other bits, but it was really around capability and maturity. So we didn't just jam in a product, we really looked at the need and how I was going to make sure that that product and the adoption and the implementation were successful and it delivered the value. So we didn't really wait around for things to be unrized, it was really driven from business value. And now, you know, we are where we are, all of the suite within IVP is rock solid, it's integrated to all of these other, I'll say, boundary kind of elements within the supply chain. I mean, it's built a foundation that we can then subsequently say right now to use Christian's words. Now I can step into the autonomous enterprise. Now I can go with assistance and agents and it took a while, but the premise was always build a foundation, make sure that a future pure fit for RS4 journey. And then we've got this really rock solid foundation that we can springboard off. As we end today's conversation, APO, I do want to talk a little about the SAP supply chain solution roadmap. How is AI factoring into that? AI is everywhere now. You have heard it on XFR, the DIA, autonomous, regulated manufacturing. And when we say autonomous, regulated manufacturing, we are actually bringing in a lot of business functions under this all the way from procurement to finance, to supply chain planning, manufacturing, execution. So it's all one big umbrella. So we are heavily investing in that and there are so many use cases that are coming up in that. And the use cases for autonomous, regulated manufacturing, ARM, what we call is not limited to SAP systems. So the information sometimes rests in different systems. A third party system, sometimes it's a regulatory information management systems or a third party planning solutions. We are not asking customers to rip off everything and put SAP before you can do AI. So we are leveraging a lot of information from other systems as well, but bringing in the right source of truth and being able to do what if scenarios all the way from start of the scenario, all the way into the execution of the scenario. That's where AI is going to sit. And we are also envisioning that the launch pad for supply chain users are actually for all the business users in future is going to be AI launch pad rather than getting into a GUI or a transaction code or a fury app. It's going to be first to start your conversation with your AI bot and then you dig deeper into those things. But I want to highlight that none of this is possible if you don't have the right set of data and the right set of tools that actually give you the data. Because I'm explicitly calling that out because now I'm seeing with all the AI wave writing in, companies want to implement something pretty quick, but that would be a bandaid fix because if you are implementing AI in a siloed system, it only knows the boundaries of the system, the data that is in the system and what it can think through in that system. But if you are looking at something which has a wider impact on inventory, working capital, finance, every function like supply chain, it needs information from a lot of systems. Whether it is GTS, your third party system, sometimes not only a support system. So you need to look at when you're building an AI agent, it's important to look at that. I would say the orchestration capability of multiple agents and the dashboard that you want to see in future rather than just putting in a small fix, a small AI agent and it actually gives you wrong information as well. So wrong information because the boundary conditions are entirely different. So yeah, with SAP, as we are launching a lot of AI capabilities, but emphasizing again on clean core and master data being synchronous. And like Leon was mentioning, actually it's a textbook way of doing it. What Illumina and Leon team has done it there is I go through the value of engineering. I identify what your KPIs are, putting some numbers for those KPIs, what those KPIs mean in terms of numbers where do you want to reach out and then look for what systems and solutions should be in place to actually reach those. I don't meant that a little bit further as well and say, and maybe this is any kind of advice to organizations that might be thinking about this sort of similar transformation. I'm always looking for the business problem that I'm trying to solve. The biggest challenge that I have with AI, hugely capable and very exciting, is that there's a lot of people running around with an AI hammer trying to find a mail to hit. So, you know, your CEOs or your COOs or CFOs would be saying, we should be doing AI. You go and find, you know, a use case for AI and they'll run around the organization just trying to make AI fit and sometimes to a partners point that will just be within one silo and you won't get the value. So I mentioned it earlier, but the approach of redesigning your business processes and taking out waste, finding out how you can drive efficiency through automation and then looking at where AI can add value to make you make higher quality better decisions quicker and then where can I automate and use or where can I use an agent to actually take on the work. That's kind of the four steps. One of the other things that I'd kind of wrap up with is we're also using SAP's toolchain. So we're using a Signarvio, Linae, yes, and WalkMe as a toolchain to map out all of our business processes. We're using process insights to say, where have I got challenges in that process? Where could I redesign that process to make it more efficient? I've also got AI within a Signarvio and within the toolchain and the future that we could explore would be that Signarvio could tell me where one of these 200 agents could drop in and help me with that process. So I think there's a hugely exciting roadmap with all of the assistants and agents that are being released and to a partners point, it's about finding the right fit for those tools in your process as opposed to trying to fit those tools into your process. I love that advice, Linae. We have your advice in hand. Why don't we end today's episode with Arpanha when we think about enterprises that are about ready to embark on similar transformations to this? Is there any other advice that you'd like to add on to what Linae just gave our listeners? Yeah, I mean, I would emphasize value-engineering, identify KPIs and most importantly, don't wait for the perfect conditions to start. Yeah, like there is a lot to learn from this story. ECC transformation with IVP and now where they are, it's a phenomenal. Well, Arpanha, Linae, thank you all so much for joining us up talks and walking us through this transformation journey we've all been together. I appreciate your insights. Thank you. Thank you again, Linae and Arpanha. Let's take a look at what's happening around the ASUG community. First, learn how the upcoming SAP for utilities conference taking place in San Antonio, Texas from October 6th to 9th can help attendees contend with common utilities challenges. Click the link to the description to learn more about the education and knowledge sharing opportunities at the events. Then, join ASUG on August 20th for a community conversation focused on how SAP Lean Iax and SAP AI Agent Hub come together in a single governance control pane, giving enterprise architecture teams, visibility, accountability, and runtime enforcement that they need to cover AI with confidence. Click the link to the description to register for the webcast. For ASUG, I'm Jim Lichten Walter. Thanks for listening.