Modernize Finance Before ERP: Why Leading SAP Organizations Are Choosing an EPM-First Strategy

Hello, everyone, and welcome to our webinar, modernize finance before ERP, why leading SAP organizations are choosing an EPM first strategy. During today's discussion, we are gonna discuss exactly that topic because we know that many finance departments across the world are working with IT to really decide on their next step in finance transformation, especially being SAP customers.

We know that there's often, you know, preassumed paths, but today we're here to discuss with some experts what some of the options are and what some of the viable options successful companies have been undertaking to get the best value out of their finance transformation initiatives. During the course of today's discussion, we're going to be talking about the cost of going ERP first.

But we also know that there is a preferred and very successful EPM first model. We're gonna talk about how the reporting continuity and really how you go about replacing legacy EPM.

Finally, we couldn't have any discussion without really talking about how this sets a foundation for having a trusted finance data and agentic AI layer to really drive your business forward, and then how to bring this all together, and finally, Q&A from you, the audience. So without further ado, I wanna take some time to introduce some of my co-presenters.

I'll go first. My name is Pras Chatterjee. I'm the global director of product marketing at OneStream, focusing on planning and analysis.

Will, if you don't mind? Thanks, Pras. Very excited to be here with our partners from OneStream. I'm Will. I lead the OneStream Alliance at PwC. I'm very excited to be here today.

Thanks for being here, Will. Tyler?

Thanks, Pras. Thanks, Will. Great to be here as well. Tyler Pietsch. I'm part of Microsoft's corporate strategy team. My team leads our strategy around banking, payments, and finance. So we get a chance to work with customers around the world, understand what their needs are, the technology, tools that we can provide, and the partners that we can work with to deliver them. Again, super excited to join today.

Great to have you here as well, Tyler. So with that in mind, let's move over to our first topic, the sequencing problem, the cost of adopting an ERP-first mentality. So with that, Will, tell us about this.

Yeah, I think when we think about ERP transformations, you know, the market is moving fast. Many organizations are prioritizing EPM first. But when we really think about the cost of ERP first, we kinda analyze it into three different areas. Right? What is the moment? What is the friction? What is the outcome? You have different scenarios. You have scenarios where your S/4HANA is already underway. You have deals and M&A's and carve-outs that happen during the deal. You need a stable layer while all this is happening. And I think this is where it kinda leads into what we're talking about today, why EPM First is so important and becoming more and more important in the current landscape when we think about finance transformation.

So I would like to bring our perspectives that we've seen from the market for what an EPM first model really looks like. And going into it, what anchors around this is finance organizations can no longer wait years for ERP transformation when we think about the sequencing problem we were discussing earlier. Right? We know that ERP transformation is critical for modernizing our planning, our forecasting, reporting, and analytics, but the market is moving so fast. And this is why organizations are now really prioritizing EPM first. Whether it's things that they think about — economic uncertainty, margin pressure, AI disruption, talent shortages, increasing demand for faster insights, or the pressure from the board and the C-suite to make decisions in real time — this is where EPM really comes in. Right? It doesn't compete with an ERP transformation. It helps derisk it. It helps give finance a stable operating layer that isn't really waiting on the ERP sequencing or timeline, and it won't break when the timeline shifts.

At PwC, we really think about finance transformation as a journey and not a destination. It's meant to be multi-pronged. You're never really dealing with just one thing. You're dealing with an ERP program and acquisition, legacy systems, statutory requirements, and they're all moving together at once. And putting all those things together is critical as part of your transformation.

And I think there's a misconception that financial transformation is only the ERP implementation, and once the ERP goes live, your transformation journey is complete. But that's not really the reality. ERP is the transactional backbone — an important one. But financial information is really anchored towards how we get insights to answer business and operational questions. What does it mean? What do we do next? How do we tell the story fast? So ERP helps get our data right, but true financial information gets your decisions right, which is what we're gonna talk a little bit more about on this foundation that we're seeing.

So, with that in mind — and you talked a lot about the great value organizations will get with the EPM First model — but one thing that stands out here is often the organizations start getting value within three to six months, way ahead of a full ERP implementation. Can you give us, especially for those considering this option, what some of that value might be in a three-to-six-month time frame?

Yeah. I think the biggest thing, right, is when we think about ERP implementation, we're also thinking about phases, plus many legacy environments. So standing up an EPM environment where you can start looking at the future operating model and how your data will come together — how do we bridge the design to reality, which I'll cover a little bit more on the next slide — really helps you realize that immediate value in the short three-to-six-month time frame.

I love that. You can look at today, but also plan for tomorrow as well. That's fantastic.

Exactly. And this is the pattern that we keep seeing, over and over again. The C-suite, the CFO office, gets their budget approved for an ERP transformation. Everyone gets super excited. Right? We get new data, new system, clean data, modern platform. But then there's always a gap between the blueprints, the design, and the reality of how it plays out. And it's not a failure of any individual or any team on this journey — it's just the nature of a program that big. The design is built on paper, an infinite number of workshops, blueprints. But before anyone can actually see it running on real data, all of that is just still on paper.

And I think this is the part where people don't think enough about — how do we realize or see the real output flowing through the new structures, flowing through the new blueprint. And that's where EPM really helps close that gap. We take the target ERP model — the future chart of accounts, the entity structure, the hierarchy design — and we adopt it inside EPM from a reporting standpoint, way ahead of ERP actually going live, way ahead of the phase-one rollouts, phase two, way ahead of the SITs and UATs. What it does, really, is give finance an opportunity to see and work with the shape of the future state, and potentially even get the opportunity to course-correct early on in an ERP and financial information journey. So by the time we go into your ERP SIT or ERP UAT, the reporting model is no longer a surprise. It's tested. It's used, and it's trusted.

It really helps close that design-to-reality gap well before the ERP will be available and live. And I think that's the real payoff. And accompanying that is the visibility and forecasting within that three-to-six-month timing we were discussing earlier, using the same exact data structure that ERP will eventually inherit. And that's the true story of why we are proposing heavily to our clients that you think of EPM as your foundation to lead into an ERP program.

So much of what you talked about was finance value, finance transformation. But yet I often see that finance departments — and especially those that lean on IT — often think of ERP initiatives as a pure technology play, a pure technology transformation. How often do you see that as the root cause of a struggling implementation?

I think we've gone through enough years of ERP implementations as an industry as a whole. So I feel like, honestly, at PwC, as well as our peers working on ERP programs, we're understanding more and more that ERP implementation is no longer just an IT program. I think the thing I'd like to highlight is what we've discussed a little bit — that design-to-reality gap. I think that's the real challenge we have now: everyone knows that ERP implementation cannot be treated as an IT implementation, but that design-to-reality gap continues to exist. And we really see EPM help bridge that gap. That's not even in the context of SAP, or only in the finance module — there are so many opportunities and so many instances in the past where, because of us thinking about workforce, because of us thinking about project planning, we're challenging how WBS structures are being composed and designed within S/4HANA. So it really trickles down into different areas of your implementation beyond even the core finance areas themselves.

That's some great insights. So tell us about — from boardroom concerns to finance action.

Yeah, so what we talked about earlier is how these insights are really trying to answer the questions. And every board, every C-suite, is really asking the same questions no matter the industry — it's the agility and the speed that we really need. Can we move capital fast enough? Can we spot risk or opportunity? Are our investments actually reinforcing these decisions, or are they pulling in different directions? I think every single one comes back to finance having the right capability.

And here you'll see a handful of core EPM capabilities that can actually help answer the question. We think about scenario modeling and forecasting — the ability to run a rapid what-if, see the trade-off, help align the board on where the capital should be and deciding the right way to leverage capital — and moving into detailed capital investment planning, thinking about allocation and trade-offs, should we reinvest here or move the capital elsewhere. Ways of integrating financial and operating planning, bringing in more sales, supply chain, operations data, so investments in different areas aren't made in isolation. We think through opportunities to have more real-time performance monitoring — whether through dynamic calculations to generate the right KPIs to help provide visibility into your financial health, and how you can use that to recognize risk even before the data is closed in the system. On top of that, AI-driven predictive analytics and agents — we've constantly been testing and experimenting with OneStream, all the underlying agents we can adopt, leveraging the core Microsoft Azure technology in the back end. And lastly, the core of it all, where it all started: financial consolidation and close automation, because we need the numbers to be clean, trustworthy, on a single platform.

If you look at these functionalities, I think this is where we really think about what we're discussing today about EPM, and also uniquely why OneStream was architected exactly the way it was. Because when we think about these capabilities, they're not six separate point solutions — they're actually all operating on a single platform where you can do scenario modeling, capital planning, integration, real-time monitoring, AI, and close/consolidation, all sitting on the same unified data model, the same metadata, the same governance structure. That's the real design intent of OneStream, because we don't ask these questions individually — we ask them with an informed answer across all of these capabilities on one platform. And I think that's the most critical thing now.

I absolutely agree. And in fact, that last part you talked about really strikes me because, in this world of AI and things Tyler's gonna talk about later, what finance needs is a trusted data foundation — exactly what you said, a world devoid of point solutions, but rather everything sitting on a trusted platform, a data foundation upon which you can work. So I think that's amazing. But one point I did wanna get into, which resonates with the market — it's amazing that you have scenario modeling and forecasting first. We recently did some research with FP&A Trends, and scenario modeling came out as one of the number-one needs for finance. What was interesting is that only 2% of organizations across the world can really deliver a scenario in two days or less, which means that 98% of organizations, when given a scenario for best case, worst case, upside, downside, take more than two days to get back to their leadership or business constituents to deliver value from the scenario. Knowing that scenario modeling is one of the most popular terms for finance, and it came up number one for you guys as well — what have you seen separates best-in-class companies that can deliver scenarios versus those that can't?

I think it's the confidence toward the data. The legacy or typical planning-type environment we've seen has a huge disconnect between how the actuals flow through into the planning system. Usually it's heavily disconnected — it takes two days just to tie out the actuals and bring them into your planning environment. So this is where a lot of my clients who are on OneStream today recognize the benefits right away, because they no longer have to reimport or bring in actuals from other places — they can leverage them from a single platform to truly accelerate the options they have to create additional scenarios, rolling forecasts based on various actuals, and even push or update run rates based on true actuals data. That's a critical piece my clients are facing and looking at today.

Fantastic. So based on everything you've talked about, I think it's important for customers to realize that, while we recommend EPM First, there are different ways to start. You can start in the middle of your journey, or you can have EPM after the fact once you've gone live with S/4HANA. The reason we mention this is that many organizations we're working with are either on ECC or even on R/3, and they're trying to figure out the best way to get to S/4HANA. They often prioritize ERP as we discussed. But there are true benefits to going with EPM first, or having EPM in the middle of your journey, or after you've gone live completely.

If you're on ECC and BPC, for example, right now, and you're looking to go to ERP with S/4HANA, what happens with going EPM first is you stabilize your close and planning processes. Finance teams can effectively decouple the EPM process from their ERP implementation, so they can get ahead with EPM as well, and it mitigates the risk of an aging BPC platform. For those of you on BPC, you've got some really tough choices to make — by 2027 to 2030, it's the end of mainstream maintenance, and you get into a period where you have to pay for extended maintenance, meaning costs get higher. That's something to avoid. Once you go live with a product like OneStream before ERP, you stabilize your whole planning, consolidations, and reporting environment, and really let finance deliver true shareholder value.

During your S/4HANA transformation, EPM really starts to deliver even more value. You can have parallel ingestion from your legacy ECC or R/3 directly into OneStream. At the same time, you can have ingestion from your future S/4 world. You can do a comparison between what the world looks like today and what it will look like tomorrow. You can also maintain all the historical context for your data. It reduces ledger fragmentation and inconsistencies, and more importantly, finance works with one governed layer.

And finally, once you go live on S/4HANA, you have a unified EPM layer alongside ERP. The key thing I always tell SAP customers going onto S/4HANA is: you're going onto S/4HANA for one reason — the universal journal, having all of your data sitting in one table versus all the disparate tables sitting in ECC or R/3. Well, that's what OneStream is. With OneStream, all of your transactional data sits in one table, and there's financial intelligence on top of that data that delivers planning, consolidations, reporting, account breaks, or whatnot. So it avoids all the disparate point solutions that customers often end up with using various other EPM tools. Finance teams really benefit from moving onto OneStream to complement their S/4HANA investment, and to get the most out of their SAP and S/4HANA investment as well.

So we're gonna move now onto reporting continuity and really replacing legacy EPM. During this phase of the journey, there are a couple of different options. There's the option of stabilizing your consolidations and planning now, before the cutover, independent of ERP timing — transitioning from whatever EPM solution you're on, whether it's SAP BPC, legacy Oracle solutions, or even Microsoft Excel, and moving directly into a unified solution like OneStream.

As I talked about earlier, during the cutover is the most important part of the process. There's a parallel ingestion of data directly from your ECC environment as well as any other ERP environments you might have, because we can't assume every SAP customer only has ECC environments. So while you're deploying central finance and having ECC and multiple other SAP stacks or non-SAP stacks flowing through central finance into an S/4HANA environment, OneStream can ingest all of that consolidation data from the different ERPs you have, all the trial balance data directly from your legacy ERPs as well as your future S/4HANA, with no reporting blackout — meaning finance gets to do their job, finance gets reports, finance gets to be a true and trusted business partner, and finance really gets to thrive and deliver shareholder value.

Now what happens afterward is probably most important. You've gone through this arduous process — as we've seen, these processes for ERP can often take two to seven years for some customers. Once you've gone live with your ERP, you've come out of this war, and OneStream continues as a unified EPM layer. There's no rework needed, no remapping. If you've changed your chart of accounts, your legal entity structure, your profit center structure, your cost center structures — any type of true transformation — OneStream can mirror that immediately and on the fly, so your business continues and runs smoothly, and you as an individual, and your finance department, are delivering true shareholder value.

Some things to keep in mind: BPC maintenance, as I mentioned, ends between 2027 and 2030. I implore all customers to really look into that, because the last thing you want is to work on a platform SAP is winding down, going into extended maintenance, which leads to higher costs. BPC is effectively a platform that does planning and consolidations in one, and OneStream is really a natural extension of that — OneStream also does consolidations and planning in one. But whereas in BPC, the data sets sit in different app sets and different applications and there's ETL often needed, script logic to move data from planning to consolidations, and often different ingestions of data into different applications — with OneStream, the data is moved once. The financial intelligence built into the platform lets you do all the logic for your planning and consolidations. If you're worried about accuracy, OneStream also has full lineage and drill-back right down to the transactional level, so you can see the aggregation of your data and also drill right back into the transactional level.

More importantly, what's really different from a BPC environment is that it's finance-owned. Thousands of OneStream customers around the world have succeeded and thrived because OneStream allows finance to really own the data, own the business logic, own the transformation, without dependence on IT or the ERP timeline whatsoever. So while the ERP project is starting, ongoing, or finishing, the reporting, consolidations, and planning that finance thrives with can move forward and succeed as well.

Any thoughts on this part, Will?

No, this is very well captured. I think the one thing I'd also add is that ERP implementation is never linear. There are so many changes that can happen during this time frame — carve-outs, additional acquisitions, changes in commercial behavior that need to be adopted. I think EPM becomes that stable platform and layer that can really react dynamically to these situations. We've helped many clients adapt quickly because of having a very robust EPM layer.

Fantastic. So with that in mind, let's now talk about trusted finance data and agentic AI. Will and I talked earlier about having a trusted data foundation, and OneStream really sets finance ahead with that. Tyler, tell us about Frontier Finance and the vision for finance in a digital world.

Yeah, so I'd start with thinking about not just finance, but really every line of business across an organization and how they think about leveraging new AI capabilities to take themselves to what we call the next level — the frontier firm. When we think specifically about finance, there are lots of different challenges, and we've discussed many of them already — fragmented data and tools, lots of manual handoffs, siloed operations, and of course this idea of change capacity and culture. When you think about the culture side of the business, these aren't just about tools, but about ways of working that really need to change to become agentic, to really take advantage of AI tools and become that frontier finance.

At Microsoft, we're excited to work with OneStream, PwC, and many of our customers around the world to guide them on this journey and help them understand how these AI capabilities can be used. For example, when we look at Microsoft's own finance journey, we've implemented AI everywhere across our platform and operations. We've standardized data through AI using a common taxonomy. We've embedded AI automation — reconciliations, variance explanations, narrative roll-ups — directly into governed workflows, which reduces handoffs and increases quality. We've shifted analysis from spreadsheet rebuilds to agent analysis. Those agents are able to do self-service drill-throughs to understand the core KPIs across each of the transactions. And of course we've leveraged Copilot to summarize commentary, surface anomalies, and speed up planning cycles — directly inside the finance process, not as an add-on.

One thing I'd absolutely encourage everyone to think about with this frontier finance transformation: when you're looking at your processes in an agentic world, don't think those processes need to be augmented with AI or improved with AI. Rather, the biggest success we're seeing, especially in finance, is where you look at those processes and think — wait a second, what is the outcome we're really trying to achieve? And then you recreate the process, reenvisioning it around how to achieve those outcomes with the tools now available. Those AI and agentic tools weren't available two years ago. Some of them were available two months ago. The ones that will continue to pop up may not be available now, but they will be in the next two weeks, two months, six months, and beyond. So that agility, and that cultural ability to change and take advantage of those tools as you go forward — that's Frontier, and that's really what we're working with customers and partners around the world to achieve.

I love that you mentioned agility, because I think agility is something finance teams need to adopt — especially as you said, some of these tools didn't exist two years ago, or even two months ago, but they exist now. Even from my own experience — while there's a wealth of AI tools I can work with to do analysis, especially what you provided with Microsoft — something as simple as Copilot for Excel has been transformational. Being able to analyze the data at hand, do calculations, do formulas, and really communicate with the data in a way that wasn't available a year ago has been transformative. There's so much more that's possible too. Tell us more.

So maybe if I took a step back and talked about the journey together with Microsoft and OneStream — we have a really strong "better together" story. OneStream is built entirely on Azure and integrates across the Microsoft stack. When we think about all the capabilities and challenges on the page here, it really is about doing this together, as an integration across the entire process. A couple of things to call out: when you think about the challenges you have, think about not just the process today, but how you might reimagine getting to the outcome those challenges require you to solve. Then think about the capabilities at your disposal — OneStream has tons of capabilities, that common data foundation, the analytics that run across it — and how you can infuse those with different opportunities, whether it's Copilot, Copilot in Excel, or building your own agent to solve these challenges. Core to this is making sure there's that foundation, but also security, compliance, making sure that data stays yours and isn't training other models. On the model side, we also think about what's the best model required to do the task or function — cost is a big part of this conversation, and some models are more expensive and not actually required. So it's a multimodal approach to using AI to solve finance problems, which gets you to that ideal target state — understanding the impact AI is providing in your finance workflow. Are you doing it faster and more efficiently, but also at a lower cost model than before? What are the actual insights, the outcomes you're delivering to your organization or your customers? Those are all key KPIs for challenging how you use AI across each finance process.

That's fantastic. I do have some questions on this. Obviously AI is a huge topic — it's in the news, it's in everything we do. But there are many organizations just starting out, dipping their toe in the water. If you were asked what's the prerequisite most organizations underestimate before AI works for them, what would you say?

I think it's pretty high right now. The great thing about AI is ubiquity and understanding how to use it — the barrier to entry keeps getting lower. Most customers might have heard the term low-code or no-code to develop AI capabilities, and the shift is really to completely no-code. For example, if you want to build an agent, you can literally describe in natural language what you want that agent to do, what tools you want it to connect to, what systems you want it to connect to — and it will build out all of those processes and workflows on its own and serve that up to you. It doesn't get any easier than that, but most organizations don't truly understand how easy it is. So there's a core awareness of how the tools work that organizations still need a better handle on, and we're helping them with that. The other piece, which is really core — and we mentioned it earlier — is that standard, core data required for AI to work. When we talked previously about OneStream providing that core data platform and data lineage, it's super important because that's what runs AI. So there's an understanding of what AI can do, how easy it is now to build these capabilities, plus you layer that on top of the core capabilities OneStream provides. I think that's a winning combination, and we're excited to continue working with customers on that.

Fantastic. You mentioned Copilot and agents — I think that's really transformative. If you think about the regular day-to-day finance user, how do Copilot agents and Microsoft Excel Copilot really change the day-to-day experience for someone in finance?

I think there's a core trust notion that needs to be worked through — really understanding that when you, as a finance operator or analyst, ask Copilot or an agent within OneStream about the data, you trust the numbers coming out. That takes some time and some white space to really get right. Once you have that foundation, and you know you're doing it on governed data and a governed model, then it just explodes in terms of the number of opportunities that can come forward. Whether that's faster scenario modeling, better communicating what the numbers are actually saying, the narratives it can create, updating forecasts, reconciliations, keeping plans current and actionable — AI can do all of these things for you. And if you're building agents, you can have those agents as your own analysts working for you twenty-four seven, better understanding the data and bringing it to you. That completely changes how operations within finance can work. But again, it's all based on understanding the data, having it in the right shape, and using the tools to effectively change that culture — thinking about what your processes are today versus what they could be in that frontier version tomorrow, because agents are your new workforce that can help drive better understanding and better overall operations as you move forward.

What gets me so excited about this is — I have a bias toward FP&A, being an FP&A professional and a CPA myself — and I think about how much time as a practitioner, before moving to technology, I spent aggregating and consuming data and bringing it together, versus how little time was spent on actual analysis and taking advantage of my CPA. Now, with everything mentioned about agents, you can really move from the planning piece fully into the analysis and use all that brainpower to drive value.

Yeah, that's absolutely right. Again, that's why it's all about changing how you think about things and moving into that frontier firm of a new agentic workforce.

Absolutely. So with OneStream, with everything you've talked about with agents, we have what we call sensible AI directly inside OneStream. It sits directly within our platform. As you build out your core foundation — doing your consolidations, bringing all your data from SAP and the various ERPs into one foundation, as both Tyler and Will mentioned — sensible AI is already there. As you do your core finance tasks — planning, consolidations, reporting — and then move on to operational planning and analysis, like supply chain planning, marketing planning, sales planning, on a trusted platform without moving data, the beauty is that AI sits on top of the platform, not as an add-on tool. It's already there. It's not bolted on. With that, you can do forecasting, AI-powered variance analysis that's always on, and you can also leverage agents with Copilot to get the best out of the Microsoft tools you're working with on top of the OneStream platform, bringing it all together to drive much more value as a finance individual.

So we've talked a lot today about a path forward — ERP first, EPM first, and how EPM complements your ERP investment and journey, and how AI brings it all together on top of that data investment. Now let's talk about how to bring it all together and what the right path forward looks like. Whenever you start, there's a first move — you can evaluate starting your ERP and EPM journey, powered by AI, on top of OneStream, at the outset, mid-migration, or once you're live on S/4HANA.

But that brings some questions customers might have. One thing I think about — Will, for you — is it as clean a process as layering EPM first and then ERP, or do these buckets not really make sense in practice? Is it a messier process? How should finance firms approach this?

I think what we've done with all our clients is understand the investment areas they're engaged in and the road map — as much as there is one — and take that into consideration. We see clients coming in at all three of these different stages. Our usual advice, from a timing standpoint, is that as you get into ERP blueprinting, that's when you really think through and pair that up with how your OneStream data model will be designed. You can combine that effort into something like an enterprise data model workstream, pulling resources and teams from both the ERP implementation and the EPM implementation, and leverage the synergy between the two.

One thing I've noticed talking to many customers is that often finance gets excited about EPM first — they talk to us about whether to start with consolidations, planning, or both, and how to layer that journey. But then something happens where they talk to IT, and for some reason they talk themselves out of starting now, and instead work on an ERP-first plan. What do you think is the most common reason finance departments start with this excitement but then talk themselves out of EPM first? And what can they do to get out of that mindset?

I think a lot of times it's really a resourcing problem. Many IT organizations are extremely well run, but at the same time there's always a bit of a resourcing problem, and responsible IT owners are always juggling the ability to support business-as-usual for existing systems and assign the right resources to new implementations. So sometimes it's about the appetite for running both programs at the same time. One of the things we bring to clients a lot is the conversation — we help map out the resources they'll actually need during the EPM journey and implementation. Once we map it out and show them the resources actually required for each step of the process, it's often a lot lighter than they were expecting, because this really is a finance-run platform. A lot of times we eventually get buy-in and comfort from IT teams that this can be managed. It's a great question, and it comes up all the time — it could honestly be its own webinar on how to set up the right governance structure around that.

Absolutely, I couldn't agree more. EPM projects are, for the most part, finance-led, finance-funded initiatives with very little impact on IT resources. I think that's something that's often overestimated and overplayed when it comes to EPM, and it shouldn't be — in fact, it complements your ERP journey, as we've discussed today.

So what organizations really need to realize is that once you've gone live with your EPM project, the first ninety days are directionally most important. It's a sequence, not a stopwatch, and the value shows up early and starts accelerating and compounding with each additional win. For me, with regard to the EPM journey, the first ninety days are most important — building on the three-to-six-month period we discussed earlier where finance can get true value out of their EPM journey. These phases are often divided into three parts: stabilize, extend, and realize.

To stabilize is bringing all your disparate ERP/EPM solutions and processes sitting in different products into one governed platform with trusted data, and having reporting continuity. Then you extend the value by layering in more operational planning, more planning processes from different departments across a hybrid landscape. More importantly, finance is able to operate completely independent of the ERP timeline — doing more of the analysis that adds value, because now they have a trusted data foundation, they can take data feeds and use Copilot in Excel and the agents they build, truly extend the value of all their data, and start automating the work. Treating an agent as a coworker, as mentioned, can really help accelerate the insights and value finance can bring.

I often say that in my case, when I worked in finance, I was probably one of the worst financial analysts of all time, because when business partners came to me with a question, my response was, "I'll get back to you." Now, with everything discussed, finance doesn't have to say that — they can get back to you immediately, and they can also deliver insights proactively, because they're way ahead of the game with all these capabilities, especially going EPM first compounded with AI on top.

So, before we conclude — Will, where do most organizations get stuck in this process?

I think that goes back to what we were talking about earlier — the gap between design and reality. You could define a beautiful target state on paper through workshops, even now with AI blueprinting and other tools, but operationalizing it — getting data fully loaded, transformed, generating the reports out of ERP — is a little bit slower. That's where many organizations get stuck in their financial information journey. EPM is really an opportunity to help push it forward a lot, and treating these ERP journeys as more of a transformation is a critical mindset for organizations to calibrate around their end goal.

And Tyler, for organizations thinking about starting this process — what does agentic AI realistically enable as part of their finance transformation?

We see that AI is going to be everywhere, across all lines of business, and specifically in finance. We think finance is going to be customer zero for AI across organizations, because it can demonstrate the value AI provides across all lines of business, both internally and for external customers and partners. AI improves cycle time, improves accuracy, learns and understands things like seasonality and what those drivers are, and frees up analysts to better understand how to leverage the data to get to outcomes in new ways. AI can help be proactive — proactive variance explanations, proactive automated root-cause narratives, shifting from "what happened" to "what should we do next." And anomaly detection — highlighting issues as they come about, identifying where leakage might happen or where costs might spike. Doing all of that with AI on top of a governed data platform with OneStream — those are things every finance professional should be thinking about: how do I change my operations to move forward with the frontier firm of the future?

Perfect, thank you. So the first win in a finance deal — it's exhilarating. You've automated, you've transformed, you're able to deliver business value. I encourage customers and prospects watching right now to talk to customers who've gone through an EPM-first journey — you'll see it feels amazing. But to get there, you have to go with EPM first — have EPM as part of your ERP journey, or immediately after ERP, to deliver value on top of all that transactional data. What I'd tell a CFO waiting for S/4 to finish is: that's just the transactional layer — you need insights from all that data before you can add true value. Will, then Tyler — any thoughts on that?

I think what's going on right now, accelerating rapidly since Q4 last year, is the AI tools we have access to — it's really disrupting and accelerating the timeline of many things, giving us way more capability than we've had in the past. Organizations need to start thinking about how finance defines the sequence of what's really required by the business to support decision-making, and let the technology support it — versus having the technology timeline dictate the sequence like it used to. That would be my biggest takeaway from what we're experiencing right now.

And Tyler, what would you tell a CFO waiting for S/4HANA to finish, in the context of AI?

I would certainly say: start now if you haven't already. Figure out where the right space is, who the right partners are — including OneStream and PwC. Make sure it's done in a governed space, and really get to a place where you can prove out value in weeks, not months — this is really key, because that's the value AI brings. In some cases, prove it out in days, not weeks. That will help CFOs show tangible wins that lead to better outcomes — fewer manual reconciliations, faster narrative cycles, higher forecast fidelity — and then industrialize that across all of your entities. That's core. And showing those wins and outcomes, along with upskilling your teams — finance analysts need to have, whether it's Copilot or something built with sensible AI, that coworker as part of their day-to-day. That's gonna take some time, but CFOs need to start that journey now.

Fantastic. So with that in mind, we have just a few minutes for Q&A. Some questions have come in during our discussion, so I'll get to these quickly.

The first one is for Tyler: there's so much noise about agentic AI in finance right now that it's hard to tell what's real. What are you actually seeing deliver value today versus where it's still more promise than practice?

I would say, of course, with AI — start with the data foundation, let's make that clear. But once that's there, you really want to start targeting high-friction workflows. We talked earlier about reconciliation, variance narratives. We're seeing some really interesting agents coming into the market — the idea of an AI-driven financial assistant, being proactive, looking at data, running analysis, freeing up analysts' time. We're seeing a lot of agents in collections and payments — automating data extraction, categorization, validation of data from documents. Those use cases work not just for collections but for multiple lines of business and outcomes. And lastly, automated risk management and compliance — leveraging AI to understand operations policy, risk posture (for a bank, for example), and legality across different jurisdictions with different regulatory requirements. AI can do that in an automated way, surfacing exceptions or key insights for analysts to use in their day-to-day.

Fantastic. And Will, this one's for you: we're in the middle of our S/4HANA program, and the internal guidance has been to wait until it's done before touching anything in finance. Is that caution justified, or is waiting costing us more than we think?

To be fair, depending on what EPM stack or reporting stack is being built, we do see a lot of clients with very robust data lake capabilities on Azure, for example, that have come up with a technology solution to help bridge in all the required reporting. But I'd challenge whether there's enough thought being put into how the planning process is being centralized. I think that's one critical layer — the rolling forecast and the planning layer really can't wait. Having a well-thought-out strategy and road map is extremely critical from an FP&A and planning standpoint.

Fantastic. Well, thank you very much, Tyler. Thank you very much, Will, and thank you everyone for joining. I know we weren't able to get to all the questions, but please keep sending them in — we'll make sure they get addressed by myself, Tyler, and Will as soon as possible.

Thank you to everyone watching. And again, the main message I want to leave you with is: please look at EPM first. EPM can complement your ERP journey, and this is something that will really drive value for those of you looking at S/4HANA and wanting to make the most of your S/4HANA investment. With that, thank you everyone, and we look forward to seeing you all again. Thank you.

Thanks, Pras. Thanks, Will.