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

Exploring Supply Chain Optimization and Cost Efficiency From the America's SAP customer community, I'm Jim Lichtenwalter and This is a Suck Talks, a podcast devoted 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 take center stage. According to the 2026 Acid Pulse, 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. On this episode, I sat down with Leon Trevit, senior director of global Integrated Planning at Illumina, and Arpana Saxaria, 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 as supply chain operations, the road map for its IBP implementation, and how SAP solutions are currently addressing common supply chain hurdles. Those insights and more this week on ASIC Cox. If you're an SAP professional and want to stay ahead without chasing every single SAP news and update, then ASIC 1st 5 has you covered. Every Monday morning, we delivered 5 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 ASOC community. The ASOC First five, The weekly briefing SAP professionals rely on to start their weeks informed. Sign up by clicking the link in the episode description. Addressing Inventory Waste in Life Sciences and Med Devices Well Parna Leon, thank you so much for joining us and walking us through the great work you are doing. I appreciate y'all joining ASOC talks today. Speaker 2 Thanks, Jim. Yeah, pleasure to be here and thanks for having me. Speaker 3 Yeah, nice having you here. Speaker 1 Lid, 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? Speaker 2 Illumina as a business, we manufacture and distribute next generation DNA sequencing equipment. So as you can imagine, sequencing DNA is is a huge benefit to improving human health. Our customers range from, you know, in the clinical space, helping people diagnose rare diseases and 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. Speaker 1 Aparna, you represent the SAP side of things. You all worked with Alumina, 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, a lot like Illumina, what are the main supply chain challenges that they are facing right now in 2026? Speaker 3 Go into the conversation with license customers and ask them 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 were this quarter are we had about 60% as a wastage not 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 in terms of what is what that looks like, but it is a very significant number of inventory that companies kind of write it off. And when you look 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 3 examples as what I what I see on the clinical trials, which I work very closely on the clinical trials of 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. And because it is rather better to have a drug in excess 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 building 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 10's and hundreds millions of dollars. It's not something it is a very small number. And so the map doesn't sit right with the with the write offs 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 Pharma 6 segment still usually in the pre COVID era, the gross margins of these pharma companies were about 77 percent, 70%, seventy, 7% around that range. Inventory write offs are OK up to 4% to some 6% of the annual inventory write off is pretty much not an alarming thing. But when you are adding up all those 4 to 5% across all at least the term 25 largest pharma companies, it's in billions. The numbers are in billions we're talking about. So that is something that needs to fix and that's one of the huge supply chain challenges that I would say I keep hearing from my customers. And coming to Med devices side, which I would also ask Leon to comment on that 20 to 30%. Again, inventory sits pretty much in the field we call it as a field inventory where and it is not accounted for sometimes in the planning systems and sometimes in the procedure rooms, hospital sites, even the sales Rep trunks, you know 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 this inventory. So the buffers are higher. And when it comes to working capital, yeah, you have to have higher working capital because now inventory is at multiple places. So whether it is so in a sense whether it is clinical trial, commercial side Med devices, the inventory write offs or and optimization I would say is the major critical challenge in the life sense of theater, yeah. Tackling Shelf Life and Integration for Better Decisions Yeah. Well, Parna, thank you for that robust overview. Leon, how does that context, does that cohere with the challenges you all are facing on Alumina? Speaker 2 It does I mean I think working capital, visibility of working capital and the optimization is a big is a big focus for that for 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 centre in terms of how we drive forward with the strategy. To be clear, yeah, we don't, we haven't experienced the $400 million stock right off. That one's scary. But you know, when you talk about scale, you know, 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 processes and just optimize our investment in working capital where it makes sense. Speaker 1 We are digging a little bit deeper. Can you speak to the organizational and industry specific hurdles you all at Alumina were trying to overcome by leveraging SAP Solutions? Speaker 2 Industry specific, so in alumina's business is a bit of a blended supply chain. There's a kind of hardware, you know, maybe more device type supply chain as Aparna was mentioning, there's also a kind of farmer 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 in a quicker, more agile way so that we can make the right decisions in a timely 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. Speaker 1 And now a brief message about a sub chapters. Are you moving to SAPS for HANA? Are you trying to integrate systems that were never designed to talk? Struggling to keep master data 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 challenges you are right now. That's why you should attend an A sub chapter meeting. They connect you with peers who have already navigated SAPS, 400 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 Acer by clicking the link in the description. Integrating IBP, EWM, TM, and Ariba Across Supply Chain Leon, can 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? Speaker 2 Yeah. So we, we went through a journey as the owner of Global Integrated Planning and I also owned the supply chain digital road map back in, I'm going to say 20/16/2017. 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, 2020, 17 of what does 2020 look like? And I'm going to see that was like 6 years ago. We, we, 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 optimising working capital and making better investments. We need to look at our sales and operations planning 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 tool set that we had and I always knew that we in the future were going to make a transition from SAP ECC to SAPS for Hannah Private Cloud edition on guys a 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 a leaning towards simplified integration and things that were in within the SAP suite. So we implemented SAPIBP. We started with the SNOP module and the 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, SAPTM and integrated that into IBP. We also integrated GTS, so SAPGTS and implemented that. So that kind of put a pin on the deliver side. And then in the source side, we lent 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 concurrent etcetera to manage spend. Speaker 1 So you have solutions that are touching basically every facet of your supply chain operations. Speaker 2 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 integrate in 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 tender freight and make the right the right decisions around how I want that inventory to move was a great benefit. Or integrating as I say, IVP when we're planning into Business Network and collaborating with suppliers. Again, it was, it was about the integration for me. And then obviously thinking about IO and coming back to that working capital optimization, like how do I make the right decisions at all of the different echelons of the supply chain to maximize my investment there when I'm thinking about the working capital investment? Leveraging AI for Forecasts, Explanations, and Automated Actions Leon, you said you started conceiving and planning for this back in 20/16/2017 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? Speaker 2 We started building out the road map 20/16/2017. 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 17 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, to build it out between 2018 and 2024. I guess actually we did it in a, we didn't do a Big Bang. We did it in sequential kind of 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 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 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 our manufacturing network, which is global. So we have manufacturing in the US in Asia and Singapore and some distribution in Europe. It touched on those as well. We have about, I'm going to say two and a half 3000 people in operations that it started touching on as well. So quite a big stakeholder group. Speaker 1 You all recently presented the customer story this project at SAP Sapphire Nasal 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 in this project. Can you all speak specifically to how AI was actually being leveraged in Illumina's SAP supply chain operations? Speaker 3 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 IN26O2 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 pharma clinical 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 finish 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 pharma because it really eliminates waste at at multiple levels. So that is some of the that is one of the critical features, the component shelf life that was launched. And we 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, see order based planning. And it is all one big platform that is actually supporting everything. So these are the rock structures, I would say where IBP has really matured 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 pharma systems. But the demand fulfillment assessment agent, it is actually traces all the fulfillment gap between the shortfall, which batch, which campaign, what is the constraint around it. So 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 this data structures in place, all the building blocks in place. Speaker 2 To be specific around how we were approaching AI think upon and nailed it in the 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 planning space. 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, in the true sense. Then as we start to step forward into, you know, 2025 and then some of the capabilities that Aparna was talking about, there are other capabilities that SAP 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 displaying abilities. So unless you're a data scientist, so you're you're really into forecast algorithms and there are people that are. In the nuances in 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 has been a huge win. So we were, we've been, 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 explaining 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 volatility or variability is increased or is it decreasing in this node for 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 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 centre. We're exploring right now the idea of actually not an assistant, but an agent that can actually go do things. And I think a partner touched on one in terms of the demand fulfilment agent. And then you know, where can we actually have a true agentic solution to be able to take on some of the work so that some of the teams can add more value in, 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, we took a, 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, you know, technically deep. And then we step into an agentic space where I can have AI or an agentic 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. Speaker 1 OK, great. 40% Reduction in Excess Inventory with SAP IBP Leon, you mentioned earlier that all organizations, not just once in your field are contending with global business disruptions, supply chain disruptions. When we think about today, how has aluminous supply chain operations changed and become better equipped with SAP solutions to contend with these disruptions? Speaker 2 Yeah, no, okay. We have a really, really good use case in this example. So as I mentioned about our road map 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 Arriba and then inventory optimization. We we deployed that during COVID remotely. 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 S and OP, we were using that for time series based supply and 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 Fast 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, 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 agentic space to say, well, like, 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. We'll, we'll change shipping from Asia and source it from Europe now because there's a thing and 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. Speaker 1 Leah, related to that value, can you give us an example to immediate ROI Illumina recognized when it implemented IBP and Business Network supply chain collaboration solutions? Speaker 2 Basically the big win for me was we 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 and obsolete and we improved our turns by by 30% overall. Speaker 1 And now, a brief message about a subtech connect. 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, improve performance, and prepare for what's next. That's where a Subtech Connect 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 Extender support SAP. This is the conference where work gets done. A Subtech Connect registration is open now. Click the link in the description to learn our partner. Building a Rock-Solid Foundation for Autonomous Enterprise You know, you, you hear that 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? Speaker 3 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 on everything to be perfect. You know, they they started their journey with flying when they were needs to see not even on S4. 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 pod Illumina SAP and the and the SA partner for Illumina who has actually worked on these things with EC ECC connection and IBP was, I would say, also still not yet matured when actually on was in 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. They started it pretty for pretty early in their journey when with ECC connection. So that's something that that is really commendable over there. Speaker 2 To answer a partner's question around collaboration. So when we were going on this journey, I actually lent into SAP and, and tried to build that relationship there. And we lent into value engineering as a function that SAP provided. So I work really closely with the value engineering team and tried to assess, you know, where are all of the levers and the benefits that we can, we can really tease out when we're going through this implementation. So the partnership with SAP on value engineering was invaluable in in ultimately getting the business case aligned and approved with the senior leadership team and driving, 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 because we were quite early in the IBP journey. I was continually assessing the maturity of each of the products. So our first tranche of implementing IBP for demand and IBPSNOPSNOP 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 the naming convention of that changed over time. So we actually implemented APO. So we implemented IVP for demand, we implemented IVP for SNOP, we implemented APOSNP and we and we, we also implemented GATP and APO. So that was the suite that we implemented. And that was interesting 'cause 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 were 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, which we were implementing the 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 in the adoption, in the implementation was successful and it delivered the value. So we didn't really wait around for things to be on rise. It was really driven from business value and now you know we are where we are. All of the suite within IBP 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 then subsequently say right now to use Christian's words, now I can step into the autonomous enterprise. Now I can go with assistants and agents. And it took a while, but the premise was always build a foundation, make sure that I future pure fit for RS4 journey. And then we've got this really rock solid foundation that we can springboard off. Strategic Advice for AI Adoption and Transformation Success As we end today's conversation, Aparna, I do want to talk a little bit about the SAP supply chain solution road map. How is AI factoring into that? Speaker 3 AI is everywhere now. You have heard it on XFR, the AI autonomous regulated manufacturing. And when we say autonomous regulated manufacturing, we are actually really 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 11 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 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 Launchpad for supply chain users, actually for all the business users in future is going to be AI Launchpad. Rather than getting into a Goi or a transaction code IT or a Fury app, it's going to be first you'll start your conversation with your AI bot and then you dig deeper into those things. Yeah, but but I want to highlight that none of this is possible if you don't have the right set of data and the set of tools that actually give you the data. Because I, I'm explicitly calling that out because now I'm seeing with all the AI wave riding in, we want companies want to implement something pretty quick. But that would be a Band-Aid fix. Because if you're 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 GPS, your third party system, sometimes not only escort systems, right. So you need to look at when you're building an AI agent, it's important to look at that, 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, it actually gives you wrong information as well, spits out wrong information because the boundary conditions are entirely different. So yeah, with SAP as we are launching a lot of a 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 go through the value engineering, identify what your KPISKPIS are, put in some numbers for those KPI's, what those KPI's 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. Speaker 2 I don't meant that a little bit further as well and say, and maybe this is any kind of advice to organisations 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 nail to hit. So you know, your CE OS or your Coos or CF OS will be saying we should be doing AI. You go and find, you know, a use case for AI and, and they'll run around the organization just trying to make AI fit. And sometimes to upon this 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, 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 SA PS tool chain. So we're using Signavio Lean IA and Walk Me as a tool chain 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, where could I redesign that process to, to make it more efficient? I've also got AI within S Signavio and within the tool chain. And the future that we could explore would be that Signavio 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 road map with all of the assistants and agents that are being released. And and to a bonus 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. Speaker 1 I, I love that advice, Leon, and we have your advice in hand. Why don't we end today's episode with Arpana? 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 it Leon just gave our listeners? Speaker 3 Yeah, I mean, I would emphasize value engineering, identify KP is and most important, don't wait for the perfect conditions to start. Yeah, like there is a lot to learn from the story ECC transformation with IVP and now where they where they are, it's it's a phenomenal. Speaker 1 Well, Arpana Leon, thank you all so much for joining a sub talks and walking us through this transformation journey of all been on together. I appreciate your insights. Thanks. Speaker 2 For your time, Jim. Speaker 3 Thank you. Speaker 1 Thank you again Leon and our partner. Let's take a look at what's happening around the A Sub community. First, learn how the upcoming SAP for Utilities conference, taking place in San Antonio, TX from October 6th to 9th can help attendees contend with common utilities challenges. Click the link in 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 IX and SAPAI Agent Hub come together in a single governance control pane, giving enterprise architecture teams visibility, accountability, and runtime enforcement that they need to govern AI with confidence. Click the link in the description and register for the webcast for ASUG. I'm Jim Lichtenwalter, thanks for listening.