Name: Beyond Efficiency: How CFOs Turn Finance into a Strategic Growth Driver
Uploaded: 2026-10-16T12:41:10.332Z
Duration: 1 h 22 min 12 s
Description: Beyond Efficiency: How CFOs Turn Finance into a Strategic Growth Driver

Transcript for "Beyond Efficiency: How CFOs Turn Finance into a Strategic Growth Driver": Good afternoon, and welcome to everybody joining us today for this Workday European CFO community events. Great to have you back with us again. Now back in May, it seems like a long time ago now, when we were last together, you'll remember we had a terrific conversation with Priya Lakhani, OBE, founder and CEO at Century Tech, and a really big thinker and doer, I think, on artificial intelligence and AI agents. And we were talking about the ROI of AI and driving those measurable business outcomes. And today, our conversation continues on that track, but moves it on, I think, where we'll be exploring today some real world stories about how organizations have evolved their finance function, found some operational efficiencies. And then what? Well, that's the beyond efficiency part of what we're talking about today with the time, resource, capacity that they've freed up through these efficiencies. What in turn does that... Well, might that enable? Ultimately, today, what we're gonna be doing is exploring what's necessary to move finance from a function to a business partner. And key to that evolution are, well, at least two things, freeing up capacity by running the necessary transactions, the operations as efficiently as possible, and then really building the data foundations to enable confident strategy driving decisions. Now I will say I'll fly the AI flag right now because that will be a big part of the conversation here today as it is frankly everywhere, I'm sure you'll agree. But I will make it my job to make sure we keep the AI chat as grounded as possible. And we'll call out areas where AI is already delivering benefits, and I'm sure you'll agree by the end of the chat today that it really is having an impact. But hopefully as well, those areas where, if not a distraction, there's still some room for growth in order for it to have the real impact that I know many people will want it to have. So as always, we have some guests who will be sharing their insights with us today, their insights and their expertise with the community. We have group financial controller at Equiniti, Robert Blore. Joining us again is Robert. Good. Good to see you later on. CFO for UK and Europe at TransUnion, Sharon Naidoo, and also partner and AI leader at PwC, Prasen Shah. And like I say, we'll be meeting Robert, Sharon, and Prasen properly in a few moments time. But before that, just a few quick housekeeping points. A reminder for returning community members and a welcome perhaps for those who are joining us for the first time. The Workday European CFO community brings together finance leaders from across the EMEA region with the objective of sharing and discovering best practices and use cases for strategic finance transformation. Your contributions to the chat, to the polls, to the questions tab, they really help to drive the conversation. And to support that, questions, comments, opinions that you make are made on your own behalf, not in your company's name. We're all on the same side here. That's what community is is all about. So the questions and comments that you share in the q and a, completely confidential. And we also have a dedicated q and a later on in the session today where you have your chance to put your questions directly to our guests or put your questions to your peers and the community. So if something comes up during our conversations today that you want to explore further, please pop it into the on screen chat and q and a as we go. Questions, comments, controversial opinions, they are all very welcome here. And as always, I will do my best to try and integrate your comments into the conversation where I can. I've got them... I've got lots of thumbs up appearing on the, on the chat in there. Good to see. Thank you. I can even see where people are joining from as well. Netherlands, London, lots of London in there. Brilliant. Keep all of that coming in. And finally, before we meet, the first of our expert guests today, our topic of the day is beyond efficiency. So let me welcome the very embodiment of beyond efficient. It's Workday's very own Fred Portau. Fred, are you there? Fred, I can see you, but I can't hear you. There we go. Pleased to, to be here again. For the people who don't know Workday, we are sponsoring that event. We're delighted to run the third session of the fourth year, and, learning more about the community and learning about your engagement and what's your priorities. Workday is a company delivering AI solution for finance, HR, and planning, and, we've been doing that for the last twenty years, reinventing ourselves, pushing the boundaries of agents and AI to support you so you can do more, for finance. So we're here to listen to, and learn. Thank you. Superb. Superb. Thank you very much, Fred. And as as Fred said, this is part of a a series of events. We've had a couple already this year. There'll be another one in December. On December 11, full details of that, we will share later on today. But back to our topic today around efficiency, and perhaps fittingly, I was drawn to a PWC report from earlier in the year when I was doing a bit of reading into this. And one of the quotes that I pulled from it is this, finance for finance increasing efficiency in traditional finance functions and acting as your company's scorekeeper is still important. Good. But finance for business, increasing insight throughout your organization and being a strategic value creator, that can be your key to future growth and success. And it's fitting because, yes, on the one hand, it speaks directly to what we're about here today, understanding and enabling the efficiencies that in turn free up more resource and strategic initiatives. But on the other hand, it's fitting because it was written by the team at PWC where our first expert guest today hails from. In a moment though, because the flip side, that comes from another report this year with a survey that says only 25% of CFOs are seen by the broader business as being strategic partners in value creation. That is being in a position to offer the finance for business that PwC spoke about. So there's a capability gap, a strategy gap, or maybe a perception gap in a good number of organizations. And that's one of the gaps that we hope that we'll be able to bridge here today. We'll have a quick poll on right now just while we mull over, a quick poll to mull over rather while we speak to our first guest. So I'll set that up right now. We We've got a question for... You know how these polls work by now. What is the primary bottleneck preventing your finance organization for acting as a as a true strategic growth driver today? You'll see on the side of the screen, there's chat, a poll. If you can see that on your screen, then great. There's a poll tab that you can click on, and you'll be able to respond to this question. The primary bottleneck preventing your finance organization from acting as a true strategic growth driver today. Those options are legacy technology and disconnected data silos, capacity constraints or time spent on routine operational execution. Is your bottleneck cultural resistance to shifting from historic reporting to forward looking analysis? Or is that bottleneck a lack of real time visibility for rapid decision making? It's one of those good level set questions about where the where the real challenges are. So please share your response. I'm gonna click onto it right now myself just to make sure that I can see it's live. There we go. Share your response. Click on that submit button, and we'll come back to that in a few minutes' time. Of course, on bottlenecks, Peter Drucker said, bottleneck is always at the top of the bottle. He was a good man for quotes, is Peter Drucker. Maybe we'll come onto that in a few moments time, but let's meet the first of today's guests. And our opening guest is a partner at PwC, where he is AI leader and global CTO in the workforce consulting practice, advising clients on strategic and operational topics at the intersection of digital and tech, particularly in the area of workforce and human centered technology. So I can't think of a better guest to talk to, on this topic today. Welcome to the Workday European CFO community, Prasun Shah. Thanks, David. There we are, Prasoon. Yep. Really good to meet you. Where about you joining us from today? you. London. Actually, London. I have the. hot... Charing Cross today. Yes. Of course. I I know the office as well. And I have to say from having a bit of a look on your LinkedIn as well, we both worked at IBM for a good little. while as well. Our IBM buddies. Excellent. So onto the topic today. You've you've heard the setup and you've heard what else your colleagues at PwC, have been talking on on this subject. You have been collaborating with Workday on a paper on the future of finance around the context of Agenctic AI. And one thing you wrote about in there was this concept of compression versus transformation as a means of moving from simple operational efficiency to a finance growth imperative. Can you expand on that for us or on that compression versus transformation thing and and its impact on that strategic finance journey? Yeah. No. It's it's a it's a... An interesting one. And if I had actually read the Peter Drucker quote, I would have probably used bottleneck because it is exactly that that idea. Yeah. So the the way we are beginning to think about this, David, is, when when you have a piece of work and you try and make that go a bit faster, so when you break work down into its atomic units, then the idea of compression is when you use AI to make that go a bit faster or go a bit cheaper. In other words, you're not changing any of the underlying processes, roles, decision rights that sit inside the operating model. They largely stay intact. Whereas transformation actually fundamentally looks to redesign the work itself. So in other words, what we call work rewire by reallocating the decisions across human beings and AI, rebuilding all the roles, rebuilding, where decision rights and accountability sits inside the operating model and actually embedding governed autonomy into the model. And, I was actually talking to the AI leader, of a very large investment bank the other day, and we were talking about this whole compression versus transformation construct. And one of the things that he said stayed with me when when he understood the the difference between compression and transformation, he said, so what that means is if I... Right now, the way I'm approaching it is I take a couple of steps in my process and I apply a bit of AI. Sure. It makes it go faster. But if I don't change the thing that is on the right hand side of that box, what ends up happening is a whole bunch of output comes out ostensibly faster, but my old operating model sits on the right hand side and it can't catch that. So my... Actually, the weakest link in my operating model still stays the same. So it's another way of thinking about compression versus transformation. I think the different ways in which we've seen organizations embrace artificial intelligence and, obviously, AI itself is is a big umbrella term for some technologies that have been around for decades now, of course. But this current wave of AI that we've been riding for the last, what, three, four years perhaps. I think it... One of the ways of looking at it is through the the the three p's as I heard one CIO describe it to me as there's the productivity piece. How How can it help me write this e... This this email, write this difficult email or this PowerPoint presentation? There's that stuff. There is the process piece actually integrating it into your business processes. And then there is depending upon the nature of your business, actual product. How can I iterate? How can I create new value for me and for my customers as a result of AI being at the heart of that? And the way you speak there about compression versus transformation, it seems to me as though that first step that the journey that many people have been on is putting Copilot. Other technologies are available on people's desktops and helping people to write that easy email. That's the kind of low hanging fruit piece there, but that might do the compression. But that doesn't. fit to the... That doesn't speak to the prod... To the processes, which I think is your transformation down. It's really integrating AI right into the heart of your business. Indeed. And and and if you if you think about why this... You you quoted this, study about the 25% who are talking about not necessarily, being able to unlock value. And then there's very, very such numbers that are being, quoted in various reports. But when you double click that, what sits behind it is it's actually not doing any real work in the operating model other than doing, what you described there, David, as day to day tasks. And, hence, I think, fundamentally, we need to think of stepping back and unlocking if... How you unlock value is about stepping back and saying, how do I actually reimagine work itself? How does work get done in my finance operating model? How do I make decisions that truly drive value, risk and performance? And and then how do we allocate all of the, who who is still accountable for this? Where does AI play a role? Where do human beings play a role? In other words, you're you're looking at... If you if you think about the core construct here, what AI energetic more fundamentally has done is it's changed the unit of work itself, which has changed from output to outcome. And this is about how do I reset the whole operating model to address that outcome piece. It strikes me that one of the one of the things you really need to understand in your organization, if you are to bring AI into the processes, the the the transformation piece that you're speaking to their person is that you need to have a really good real world grip on what your business processes are. You know, those business process management tools, whatever it is. But if what's documented is substantially different to what's actually happening on the ground, Yeah. then you can't hope to really optimize those processes because it's it's gonna be AI almost kind of making things up. You need to know exactly what's happening in your business, and that's that's gonna be quite a journey for some organizations, I presume. Indeed. Yes. Cool. So, compression, transformation, I guess. What are the kind of indicators, if you like, that an organization is starting to move beyond the compression and the and the task space stuff onto stuff that looks like it is true agentic automation or or through agentic transformation. What are the kind of key indicators that you would look for in your work? I think, it's where you start seeing the shift away from tasks to decisions. Decision automation is where where the real unlock is. And if you then go back and say, how do I know actually that's what what we're doing? The the key indicators there would be for you to be able to work out that there are... The decision rights are really, really explicit, that you have governed autonomy around what agentic or what AI can do and where you need autonomy around human beings doing things and where human beings need to review things that AI have... Has done. It's about knowing where the human actually has named accountability. How do you define rollbacks, how do you define, the decision rights in the architecture, all of that needs to be explicit. That's when you start seeing this shift. I would say almost the indicators, if you will, of the... That the operating model is beginning to shift away from tasks to decisions. And this... And one one simple example I often have is... And you take the finance function. A lot of the things that we do there... And and not just finance, frankly, any function. The KPIs used to typically be outputs, number of x things processed, time taken to do y. And that is when you're looking at outputs. Whereas when you pivot to decisions... So an example might be, in, working capital management, and if that is what you want to optimize and maximize, you might choose to say that, actually, I don't want to pay all the invoices on time because I I I could still be, incurring late penalty and have the money sent in my treasury and get me more working capital. So this is where you're making a decision, an explicit choice in the operating model. Whether it's done by a human being or whether it's done by an agent is sort of the risk appetite and a bit of a moot point in in one sense. But the shift away from saying I need all... I... I'm gonna measure the efficacy or the value returned by this value chain by saying how many invoices were processed the first time the right way, or what's the quantum of invoices process versus if the objective that the CFO has set out is I wanna maximize my working capital, then my answer may not necessarily be that I process all invoices. So it's being able to make that paradigm shift away from measuring physical output to measuring outcome. And all of the things that I mentioned there are decision rights, named, accountability, the sort of line of sight and traceability into why I'm making certain decisions, these are all indicators that you're moving into that kind of an operating model. Yeah. And again, from conversations with people in organizations who are adopting, adopting agentic AI, it's that accountability that you mentioned there, Preston. It's actually... You know, every human member of the workforce has a manager, has job reviews, has got all all the processes that that we're used to. Since we start moving into a world of agents, those processes, whether that's HR processes or all of the other kind of life cycle stuff, they don't exist. So that accountability line who is responsible for making sure that this agent works within their ground rules, within the guardrails, and doesn't start encroaching into other areas, what their performance management looks like, That's that's kind of not a technical thing. That... That's very much a kind of procedural thing that we also need to evolve towards, I think. K. In terms of the processes then, traditional processes, they tend to focus on sequential tasks. That's how our human brains tend to work. You know, first, make this report, then, I don't know, calculate variance, email a manager, whatever whatever it is. How do you then begin to map a finance workflow when an AI agent is the one who's determining the sequence, you know, when it finds a more optimal sequence in order to achieve its mission? How do you start to understand what that finance workflow looks like when it varies from what, as humans, our processes have looked like up until this point. Yeah. You're right. As in, when you take a sort of a traditional process centric lens, what we've done always is we've treated the steps, the sequences of the process as the main object that we are trying to streamline, optimize, and organize. Right? So if you if you are shifting away from that, I e moving towards more of an agentic first operating model, then what you're doing is you're doing... You you really redesigning this right to left, and your right hand side is about the outcome and the decisions. And as you move right to left, you start saying, in order to get to the decision, what are the actions I need to take? What are the data elements that I need to use? What constraints am I working with? Where does my accountability around the decision rights model sit? Based on those, then you're allowing various pathways to work through these to be able to arrive at that outcome. That's almost a new normal, if you will, of what used to be a process sequence, would now essentially be an orchestration layer that generates that sort of decision... The the pathway through these decision blocks. Think of these as LEGO blocks that would need to get rearranged based on the outcome that you're trying to solve for. So in other words, just as in Lego, you can assemble and disassemble them and and make it what you want it to look like. That pathway actually starts becoming dynamic. However, the thing that is constant in all of this is the decision rights that you define, the guardrails that you define as an organization and or, yeah, various regulatory and industry constraints. They need to be explicit and they need to be static. The bid that orchestrates to that is the pathway that connects these decision blocks together. Yeah. So taking... Right. So, again, on metrics, taking month end close as, as an agentic workflow, for example, where where does the kind of task reduction piece stop being that primary metric? And what what kind of metrics do you look at then that that take its place that that are useful, that are helpful? Yeah. So if you take that example, I I won't say that, you know, task reduction disappears. It is... It almost becomes the the secondary corollary, if you will, of redesigning interagintic output. So it it is it is still there, Still shrink. Yeah. the more sort of forward looking measures I would think of would be things like, closed cycle time or, first resolution or number of decisions that have been actually made autonomously in the model. By definition, if you're making decisions autonomously, it means it's lower human touch, lower cost, and more straight through. Number of control breaches that have been prevented or... And or, solved for, things like what was the total time to close as opposed to, how how long it took me to close. So I think the... You... You're beginning to see some of these parameters shift more towards outcome orientation than counting output. And... Yeah. So that that... That's. that's how I would I would think about it. And, again, it's your starting from right to left, starting at the right, and working backwards to what that. outcome is. But, clearly, the more you can shrink whatever happens from the outcome or what comes before the outcome is a good thing. Please, do keep your questions, coming in. And, I did say that I would try and integrate questions from our community today into our conversation. And we had one in really early on from, Elaine. Thank you for your question. And, Preston, I'm gonna ask it to you right now just while we're kind of in this in this flow. And it's it's, obviously, it's related to what we're talking about, but it is on a slightly different bent. Coming back to the compression versus transformation piece, Elaine's provocative maybe or or or point certainly, but question is transformation is presumably an order of magnitude more expensive than compression. So that's the that that's the point she... That she's making. And the low hanging fruit that I think we spoke about about the compression, that's one thing. Soon as you start looking at rearchitecting your processes, the the transformation piece, there is a lot more expense in that. There's a lot more resource that's required, but I'm expecting you to say, but it will be worth it. How do you address, questions like that? Yeah. No. Look. I think I think it's it's a really important, point to talk about because, I I think I think the answer is true that, when you when you're looking to transform something fundamentally and fundamentally redesign both the operating model as well as the... As all all of the infrastructure, if I can use that word, that sits around an operating model, it inherently will feel like what I sometimes describe as heart and lung surgery. Having said that, there's also on the flip side, the... There's enough number of stats right now. So starting with the MIT report back a couple of Christmases away, to PWC's AI performance index study, which we ran six months back. In order of magnitude, less than, 10% of enterprises are actually getting true... Are are being able to unlock true value from agentic. In other. words, the disproportionate number of us out there in enterprises who are saying, we're doing stuff with... Everyone's doing stuff with AI, but I... But we're not getting value. Then you start saying, what are they doing? They're actually doing Yeah. transformation or compression? So you you might feel like, you're... It's easier. It it definitely is easier to do compression. I would argue that when you look at the ultimate cost and the total cost and or the value not returned, the opportunity cost missed, the cost of compression is probably way higher. And and and that is because it's easy to do these POCs. They're very easy, and and we are beginning to see pilot sprawls and POCs then not returning value. However, if you step back and say, what's the outcome that that I can get to if I transform fundamentally, we are actually seeing a lot of our clients beginning to... When when they grapple with that concept, they realize that it is not just an efficiency conversation. It is a value unlock conversation in a very different way. And that's where the true value unlock... So it becomes a growth vector, not just a cost efficiency play. And that comes back to the big overarching theme of this session here today, Preston. It... It's beyond efficiency. What what can that enable? What can that unlock? Brilliant stuff. Before I let you go, for now, and I'm gonna ask you to stay all. the way through. Elaine, thank you for your question, by the way. Please keep your other questions. You know, the stuff coming through on the chat. Like I say, I will try and feed it into the conversation, and we do have time later on today. But let's just reflect on the poll that we opened a few moments ago, Prasun. We asked what is the primary bottleneck? There we go. The bottleneck's back. Preventing your finance organization from acting as a true strategic growth driver today. Is it the legacy tech that is being the headache for you? Legacy tech disconnected data silos. We're gonna be talking about data in a moment. Is it the capacity constraints? Not so much. I mean, I think it's the legacy tech and disconnected data silos that are right at the top there with almost two thirds. That, I don't know. Is that a surprise to you based on the conversations you have with with your clients and with your peers that it is legacy tech being the ball and chain holding back organizations rather than some of the more strategic, we need to bring AI into the heart of the processes that we've just been speaking about there, the transformation rather than compression. What's your reflection on the question and the responses from the community there? I think, the the two. are not mutually exclusive. We we are definitely, so, you know, why are you not being able to transform? Transform? Why you do end up compressing is because of the underpinning technology in many cases. Even if you have the mindset to change, you may not necessarily have the right digital core foundations to be able to do that. And this is why it's really, really critical, especially for functions like finance, to have a clean... What what I sort of loosely describe as a clean core connected digital, heart. Mhmm. And then you you can do what you need to do with it. Right now, many of our clients don't even have that core basic infrastructure to be able to solve for where the true opportunity is. And with some of the, you know, changes and some of the, advances that we are seeing around multi agent models, being able to take advantage of some of that to be able to, use... Move away from UI and UX as the constraint and to actually operate more headless. Some of those, you do need your underpinning core digital. infrastructure to be in place. Alright. Thank you. If there's another bottleneck, I'll just put this out for the chat. If there's another bottleneck that wasn't well reflected in the polls that we've just had, let us know in the chat, and we can have a chat about those later on as well. Prasen, thank you for now. Don't go anywhere. Like I say, we'd love to welcome you back later on for, a broader conversation with our next guests and to to respond to more questions from the audience. But, Thank now, Prasen, you. thank you very much. Thank you. Right. Let's quickly open our second poll of the day, which centers on digital transformation, ROI and maturity. So any moment now that, poll will come open in the panel on the side of your screen. The question is, where is your finance function currently focusing its digital transformation over the next twelve or eighteen months? There we go. So live right now. Where is your finance function currently focusing its digital transformation over the next twelve to eighteen months. Questions we have for you are automating core operations to drive baseline efficiency, upgrading FP and A and real time scenario planning, accelerating m and a readiness and post merger integration. That's something we'll be chatting about in a second. And scaling operational capacity without increasing headcount. So what's the focus of your digital transformation over the next year, year and a half? We would love to know. Fill out your responses on the poll, and we'll take a look at those again in a moment. Right. Time now to welcome two more guests to the stage to share their experiences of finding efficiency in their finance functions. First of all, a returning guest, friend of the show, Rob Lord, group financial controller at Equiniti. Welcome back, Rob. I'm pleased you're here. How are you doing? Very good. Thank you, David. Thank you for, the return invite. Good to know that I, I behaved first time to come out the second time. Thank you. You behave... You behaved well enough, should we say. But we've... We're we're gonna put you to the sword again, this time as well. And it was actually this time last year when you joined and you were towards the beginning of a kind of new leg of a finance transformation journey. So what I want to chat with you about is, really what the last twelve months have brought in terms of efficiency, what that has enabled for you, but hold the thoughts there because I also want to welcome our other guest for this part of the show. It is Sharon Naidoo, who is CFO for UK and Europe at TransUnion. Hello, Sharon. Sharon is gonna join the stage. We we can't... So this is this is the magic of these live sessions. There should be a join the stage button on your screen, Sharon, and that will allow you to join. There we go. Thank you. So hi, David, Robert, everyone. Thank you very much, for having me. It's been a pleasure or it's going to be a pleasure. Yes. Yes. The the the pleasure will be all ours, but I hope you enjoy the journey, and the chat with the community here today as well. And you're on a transformation journey too and maybe working through some of the same questions that Rob has faced... Is still facing. So, I I think I'd love to hear today where you are and what you're looking towards on your journey there at TransUnion. But first up though, Rob, remind us what you do and who you do it for there at equinity. And then just kick us off by by painting a very quick picture of that journey that you've been on over the last twelve or so months. Yeah. Sure. Thank you, David. So, I am the group financial controller at Aquinity. That's my full kennel name. Most things finance related, process related, accounting output related sit within our team. So we run an ERP. We run all our group audits and so on. So the usual, items is under that very heavy process, a lot of m and a integration that we've done on some recent disposal. And just very a very quick. check back. Sorry. Just just very quick check back. Equiniti, I think we were calling UEQ this time last year. For for anyone who doesn't know, just paint that picture for us quickly. Yeah. Sure. So Quinity, we we are a, chair registration agent in The UK and and a transfer agent in The US. So, basically, we we manage share holdings on behalf of PLC, specific to the PLC, US listed companies, and the end client to manage the records. It's quite a complex banking type operation, pay dividends, manage tax informational returns and we process something like $500,000,000,000 of cash movements a year so very much like at a banking sector business. We're going through a big transformation from our ownership structure. We will soon be acquired by a US listed corporates and we will be separating out part of our UK business, it's a share business into its sorry it's a pensions business into separate ownership under PE. So fascinating times and when we thought we were busy we're busy by a multiple of about five or six. So, this time last year, like I say, when we last spoke, it... You were, at the beginning and and looking around you, looking at what others were doing, I I think it's fair to say. Just talk to me about where you've been to since then, and you mentioned a lot of m and a activity. I know that's been part of your journey over the last twelve months. Yeah. Very much so. So m and a has always been part of what we've done, and we've we've we've we've got a good ERP platform that allows and facilitates that. But it went to a different scale. Just over a year ago, we bought a business, that's operated in 17 countries. Prior to that, we were in three. And anything that operates multi territory brings in a whole level of of, of of of new risk and challenge, and there's 1,200 people in that business. So whilst we were very confident about the ability to bring in at a process level and map into our existing activities, we knew that a lot of what we do wouldn't be right for the business we were acquiring. So as well as that business, the acquired business, the target transforming, so do we. We have that same need. So we're sitting looking at that thinking, we've got good skills. We know what we're doing, but it's a very different application, a very different use case. And then how how do we break that down? That was at the same time as the whole, you know, AI, I would say, kind of the next phase of the AI explosion was was was was was taking place. And it's fascinating hearing, Prayson, earlier put things together very articulately and diligent and and very, very... In a very clear fashion. I love to say that we have this brilliant method that we use, but it was actually... You know, we were driven by two things really. We've got... I've called it the. four f's, and they aren't... It's not really the the polished consulting term, but we were in the first two stages. The first one was FOMO. So, So, you know, everyone's using it. We've got to use it. And then it went to Feral. So it was everywhere. So our challenge was how we could use what was available to us from a... From from an AI perspective to really drive and make a change in, up to to facilitate the transformation required and to make sure that 1,200 people coming into, our new infrastructure, our new ways of working was a truly transformational and exceptional experience for them. So we focused very... On a couple of really key areas, which were around, the expense claim process, because that touches just about everybody and people policies. And we were able to use an AI component to support all of us. And there's a significant amount of compression because it compressed the work that we needed to do to enable the transformation. There was quite a lot to unpack around that, which we can go into. And then the other parts of the f's was... We then took that into a more formal arrangement. Once we have got our arms around and our heads around the method, and then it's become, much more pervasive through the business as full on. That's the final f, and that's where we are seeing quite a clean and and and neat use case that's come out and and repeatable methods. And we've got some some some very good, wins that we've been building on and working with Workday on actually around, profitability models, and data insights and data decision making. And it's taking a process and then turning it into, a proper decision support tool. So, yeah, we've got the full gamuts there, but there's a very, very, for us, transformational use case around, Yeah. using the expense process in that in that take And... Yeah. And that, on. bringing on those 1,200 people, that feels like it was a a a great kind of size of project to to test and... Well, Yep. just to to prove, I guess, the, I guess, compression as well as transformation journey that you've been on there. I'm a sucker for a three p's or or four f's. I was a bit worried when you started off there, but FOMO, feral, formalized, and full on. They certainly work for me. Thank you. Thank you, Rob. Hello, Sharon. Tell us a bit about what your remit is at TransUnion. And then, characterize with the letter f, other letters are available, right now where you are as regards finance transformation and finding those efficiencies that you need to find there. How do you how do you feel you are there? Okay. So no pressure on the question, David. So let me start by saying, so TransUnion is a credit reference agency. So typically a credit bureau, and we will typically compete with the likes of Equifax and with Experian. So in terms of who TransUnion is, that's exactly where we are. Most companies, or corporates in the... In Europe would use some sort of TransUnion platform in the background because we do provide the credit scores, for all sorts of mortgages, bonds, credit cards, etcetera, as well as we do have a lot of fraud products that sit at the background in gaming, all types of avenues where, you know, there's there's anything touching fraud or ID verification or use some sort of TransUnion product to get. That is TransUnion. It's... We basically... The way I like to say it in simple forms is we're the middleman between the company and the consumer. And we'd like to think that all our information passing through us is actually used for good. So that's, TransUnion. So I am the chief financial officer for the Europe business. So it includes The UK as well as parts of Europe. Currently, we have, an office in Spain, and we're looking to to grow more into the Europe, area as well. My remit within TransUnion is a bit on both. So I look after the accounting side as well as the, FP and A side as well as some other parts of finance. We... We're quite split. We have a cent... We have cent of excellences all over the world in terms of treasury and tax and internal audit as well as, we have shared service centers or financial service centers in Pune that looks after a lot of our transactional processing, for The UK. So as you can see, it's it's it's quite complex. So when I think finance transformation, we moved into the shared service environment about two years ago. So December was gonna be two years ago. And I think we starting to introduce AI. Well, actually, we're starting to introduce Microsoft Copilot, on on a premium and advanced level, into the team. So I think transformation is... I like to look at it in three places. I don't know if it's all gonna rhyme and if it's all gonna be with an f, but, the way I look at it is it's gonna be people. That's that's that's the first part of transformation. It has to start with people. The second part is our processes and our data, our systems. And the third part of it is what AI or where AI fits into us... Into this. And the way I like to think about AI is in two parts. One is the agentic part of it, which could possibly in in the future, even though it seems like much much further away for some companies versus other, is AI could be your business partners, you know, where you could have a CEO that has a personalized agentic AI. That's that's financial planning that answers your specific questions. So you almost wanna look at those as your agents or your very basic, finance business partners. The the second. part of the AI AI is how we actually use the data and how we use AI to be more efficient in processing of data, where we can free up a lot more finance time in providing insights, providing information, providing direction, you know, as opposed to, you know, pushing out data and and doing kinda less of the insights. So I think the journey is still very... You know, I'd like to say it's still being pioneered. I think, you know, when I sit at the CFO conferences and spend a lot more time with the CFOs in in London, you know, we're all kinda in the same places. Some people have a lot more advanced FP and A in terms of having AI that can do predictive modeling at the moment. I think the biggest challenge for all of us is structured data and how we create a structured data layer where we can start to use AI more efficiently including Copilot. The biggest challenge with Copilot right now is that, you know, your data is unstructured. So you spend a lot more time with the agentic AI trying to tell it where to go as opposed. to spending some time upfront. I mean, I personally have to say I did try to use... I did have an agentic AI, and then I got tired of quoting, numbers as opposed to saying, can you find the insurance sector? And it will come back to me and say, what is the code of the insurance sector? So I felt like I needed to read you my memory in order to train it. So. I think that... That's kinda where we are. The first step has to be structured data. And how do we get all of our data of multiple systems across the business into kinda one database to start to use the AI more effectively? And I think that speaks really interesting. Thank you, Sharon. And you speak about the complexity. Obviously, the nature of TransUnion, it's a data heavy bit... Really, really data heavy business there. And what you just spoke about around the challenges around unstructured data and so on, I think that talks to the results of our opening poll a few minutes ago about, the primary bottleneck at the moment being legacy technology disconnected data silos. And I saw, in fact, in the chat, Catherine, thank you's left a... Yeah. There we go. Hold. That's the second poll. Ignore that. We're gonna come back to the second poll at the moment. I'm still reflecting on the first poll. Catherine said she could select multiple of those, but she agreed. I agree. It comes back to the data. It all comes back to the data, junk in, junk out, or garbage in, garbage out. What have you been doing then, Sharon? And, Rob, I'll I'll throw this over to you as well in a moment. What we've been doing about data to try and address these data silos, to try and make sure that the right tools, be they agents or or other things, have access to the right data in the right format with the right degree of trust and confidence. Yep. And and I think this is where we have to break up, you know, break up... Because within a function, you're going to have one, you've got to get the day to day done and you've got to meet the deliverables of today. So, you know, data structuring or data reorganizing cannot be the side of somebody's desk. And the the second part of it is that, you know, finance teams are very, very excited and passionate to be on the AI journey. So you have to kinda have that Microsoft Copilot premium licenses. Right? I hear it everyday. Can I have a premium license? So I think to bring finance teams on the journey is is is to have that... Whether it's Claude, whether it's ChattyPity, whether, you know, some sort of that platform. Right? So then you get the team engagement, you get the team curious. As well as with the team, what we have done is given the the agents, the the basic coding on the agent and, you know, you're gonna have some people that are a lot more curious and some people that are a lot less curious. Some want a developed agents, some is willing to develop an agent. So I think opening those tools to drive curiosity with people is important. And then we come to the beast. And the beast that we're solving is the structured database. And that has not been... That is not a new problem for finance. You know, that has been the problem when we had Power BI being rolled out. It's the problem when we had, Tableau being rolled out. It's the problem when normal BI existed because to bring in the systems together requires somebody that doesn't think finance but thinks across the business. So, you know, you'd wanna bring... Okay. Where does your actuals come from? That is your ERP system. Where does your forecast come from? That's your your kind of FP and A system. You bring those two together, but those give limited real time information. Right? It just tells you what have you done versus what will you do. Then you wanna bring in the Salesforce or the sales pipeline into that information because that gives you a richer database because now you can start to train out with probability. Where would you land. and you can start to have more constructive conversation with the sales team saying, okay, here's your way... Here is where you're at, here's where your deals at. You know, you can start to go into what is the probability of deals closing. Sure. Then you you can bring into the GT part of it, which is how we're building out solutions. When are we rolling out solutions to customers? And I think that's where the true beauty of the structured database comes in. And I call it the beast or it's, you know, that old saying that says, how do you eat an elephant? And it's one bite at a time. Because when you search with teams, you get so excited and you want the end pro pro... The end goal when you gotta realize the small bites is if you could just get your basic systems together first and then start moving it, and then you get... At the same time, you concurrently... Or building people's curiosity. So you're not waiting for the database and then getting the team to use it because you're all doing this in stages. So. what. we're doing right now is just outsourcing the structured database building into our BI teams and saying, here's the finance systems, here's the requirements, I'm the exec sponsor on the project. Can we have these kind of systems together so that you're getting the drive behind it? But you are equally bringing finance on the journey by saying, here's your Copilot licenses or here's your, you know, equivalent licenses. Here's the the agents that could. you use driving the curiosity of people into it. Back to that curiosity word again. So so many points to unpack there as well. But, Rob, I wanna come to you. And, again, on this data foundations, then maybe applying it to the journey that you've been on with regards to the m and a activity. What's been the biggest bit of data work for you in what you've been doing, and how has the... Well, what way has the m and a, that bringing on that 1,200 or so people added to the complexity, and what have you kind of done to overcome that? Yeah. So everything Sharon says, I completely recognize and identify with, and those are, I think, some some of the critical success factors to enable things and curiosity is key. And along with sort of applied or, acquired skill, and federated skills, so where across the business can you bring that in, and it can be in the finance team. It can be outside of it. In some cases, you want people who don't think like accountants but understand the data, and can understand the system or a process. They can ask the right question. They can speak the right language. So, we we... We're very fortunate that we've got a a mature, shared services operation in Chennai, and it's a it's a captive organization. It's a full part of the quantity. So they were fully embedded in our m and a journey, but also very much understand the processes for finance not necessarily for wider for the business. So they do it brilliantly internally as a team. And so again we knew we had to operate differently because we're bringing in this large acquisition that operates it so very differently. But what we find... We were able to find sort of a micro level as using AI to go through all our policies, and we have multiple to say, is this actually what we want? And then we got into this conundrum of how do I make the policy right. We use AI to look for the gaps in the policy. And you use it as a self feeding machine, basically. It isn't necessarily right, but helps to conform things. It gives the structure. And that conformity in a policy is the piece that removes some of the compression issue, but also helps to say, here is how the data needs to operate in order to work effectively. So we're able to take micro steps on those areas. So simple things like, do you wanna fill an expense claim? We want to understand very clearly about what's incurred at where it's come from, what's client related, what's internal cost, etcetera, etcetera. So all the use of the rich work tags, the project codes, and so on. But present that to an individual, it's baffling. So how do you guide them through that? So so what we also have was, an AI agent that set... Sat across everything, people could ask questions of and go in and say, what does this. mean? What does that do? And what we want from that next, the next piece of development, which is really really the bridge between curiosity and sort of, demand really, I think, is say, right. We want that in our ERP because that's all very consumable. That's all very manageable. How do we how do we manifest that? And do we use Copilot? Do we work with Workday? Do we take Sana? But we've created, if you like, a, a tangible desire and and and, a hunger, for that. So we now know what we want from it. So that's one parcel that came from the acquisition. I think another piece that really struck me about what Sharon was saying is how you bring these multiple data sources in. And for the longest time, for about up until about a year ago, a big chunk of our business build off spreadsheets. And, I don't think that's uncommon, but it's, Nope. you know, it strikes terror into the heart of anybody who's Titleist controller. And, you know, everythings are done well by human beings, but can be done inconsistently. So your data is presented inconsistently. So we went through a process of automating all of that using best of breed billing system that present data in an accounting way. So we had to build a a bridge. That bridge has basically conformed every data attribute that comes in, and it isn't just data that comes from a bill, it's data that comes from our systems of record. So we we we found ourselves in this position of knowing, having the luxury of... We use Workday, but using the work tags in Workday, we know what they're for. We've... We have set our owners in our business that that there are data owners, data stewards of the component parts that make up a string of a transaction, and we've been able to say for that to work effectively, we need the data presented in this format. So that's been automated, and then we have a position where we... Process where we will review what's coming in to make sure it's right. And so they are automation act... Items, but they facilitate that insight and they facilitate a reliability and a trust position that you can put on for a Genesys consumption. So that, you know, that... That's very much been the flavor of what we've done... Been doing in the last twelve, eighteen months, and I think that curiosity has been... It's exactly right. And that's helped us build more of a method and more of a a way of doing things. We have to be careful that it doesn't just, just bounce off and go and do other areas that we're not thinking about carefully and how we keep the return and how we could demand more from our partners. And we've got to bottle it, really, and, you know, make it make it a real thing. But we've we've had a couple of really strong use cases that I think have helped us loads more to do, and. we still find issues and problems. But I think that that, you know, they are... You mentioned earlier about grounded and, you know, how how things operate in the business, and we've been fortunate that we've been able to take a little bit of time to reflect on some of the things we've done, whether it worked well, what we learned from it, what do we need to do better. Yeah. So that you can go again having those lessons learned from this program. And it sounds like, Rob, you've got an awful lot of change just around the corner as well. So I wish you all the best with that. Just, obviously conscious of the time. I wanna make sure that we're able to address, I can see there's some more questions that have come into the q and a there. If you've got questions, again, questions, comments, opinions, whatever, please do feel free to share. We've got some time for q and a at the end. Sharon, compression, transformation. In in terms of structures, once you start bringing AI, once you start bringing automation into the heart of your business, it starts to look different. It starts to be structured differently. So I think my question to you is what what are the... Do you know where you're headed towards? What way do you seem you... Do do you see your teams working differently, maybe structured differently with automation and AI more at the center of the processes of what you do there, and what do you hope those outcomes will ultimately be? So I'd... It's it's it's a great question, David. I think it's like a 100% thought reflection a 100 of the time. Right? I think there's there's three ways. So if we talk about organizational design... And when I say organizational design, I mean, Gen AI as well. Right? So if we. take shared service centers, I think Robert mentioned that, you know, we've also got the shared service center that's starting to work very well. You know, it's been two years into the program now. So it's... We're starting to see that output and delivery and the value add come from it. Then you've got the second leg of this, which is the AI component and where the technology fits in the system. Because I think for a long time, AI is still gonna fill a technology and enablement le... Lever within the team. And then you have the HI, which is probably the human intelligence. Right? Or human intuition. And I think where where we're gonna start to move teams from is away from data processing and pulling the data together and manual reporting and copying things of spreadsheets into multiple spreadsheets. And we're gonna start having the team move more into true business partners. And the true business partner comes in by saying, you know, where do we see ourselves going? What is the return on investment of business cases? Are we prioritizing the right things? Are we deprioritizing enough? What does... You know, we're gonna start to partner more commercially with the business in true partnership, not necessarily. Let me pull a piece of model for you, give it to you at the last minute because we're all rushing time and then you find your own insights. I think finance has become... Gonna become a lot more of an advisory role. I think even within the accounting, teams, it's exactly the same thing. You know, we spend a lot of time thinking about AI within FP and A because it's where your data comes, your modeling comes, you know, your predictive analysis, your target setting, your strategic part comes out of it. But I think even within the accounting side, you're gonna see a lot bigger step change where you're gonna have accounting advisers, all from the base of statutory compliance, etcetera, etcetera, but approaching the business more differently. And I probably at some stage, you know, you'll see a lot more overlap in mud... Overlap between the two functions. Like, you get into a month end and you've got the accounting part that brings all of the actuals in, but then you also got the FP and A part that's starting to explain. And I think they, you know, with AI and technology or enablement bringing in those numbers faster, what does that day after look like? Yeah. Do you know in all of the conversations that I've had around AI over the last three or four years in particular, you know, while it can be a technology conversation, I found myself reflecting, actually, what... What's the value that humans bring? Yes. What's the value that technology bring? But what's the actual value that humans bring? Because that's the thing that we really need to be leaning into. And I think your point there about a lot of those processes can be compressed, can be automated, can be done whatever they are, leaving the humans to be the ones who are being the strategic partner, like you say, really supporting the business in value creation there. That's another way of expressing it. Thank you. Thank you. Thank you. Thank you. There's still more questions that I want to ask, but here's what I'm gonna do. I'm going to take a look at the second poll that we opened a few minutes ago. I'm gonna bring Prasim back onto the stage, and we'll continue the conversation with Prasim. And then any final questions that we've got from you watching today in the community, then please do share those, and we'll address those as well. Welcome back, Prasen. Let's just take a look at the results of that poll. Where is your finance function currently focusing on its digital transformation over the next twelve to eighteen months? And more than 50% are saying automating core operations to drive baseline efficiency. Correct answer, everybody. I think that very much fits in with what we're talking about today. And also, I I think as Sharon was talking about a moment ago, upgrading FP and A and real time scenario planning. No surprises there, I guess, team. I think, hopefully, with the conversation that we're having today, it's understanding the value that bringing automation to core business processes. That's that... That's really important. Let's quickly open up the third poll. Hopefully, we've got time to get some responses on this. The third poll asks, how confident are you that your current financial architecture can support rapid business model changes or economic volatility? I won't read through the answers or the the options there because you can read them through yourselves, but it's all about confidence. How confident are you that your current financial architecture can support rapid business model changes or economic via volatility? How resilient are you feeling today, people? Right. So, Prasen, welcome back. And Sean and Rob are still here as well. So let's talk about challenges, shall we? And I I think we spoke about challenges a bit with Sharon. Prasen, I'll ask you about challenges in your work with clients. We've been talking about the kind of Nirvana of bringing AI, bringing automation right into the heart of business processes here. What are some of the biggest challenges in introducing these technology, processes, I people? Where do you see the main challenges at the moment? think it's, mostly we come up against technology and not having the core basics, in place. And the other big thing that, often trips us up is, culture and mindset within the organization. Process less of a thing because you are... That is essentially the core that you are actually addressing. Yeah. But it is the whole mindset shift. It takes, it takes leadership. It takes road modeling. It takes a fundamentally different way of reimagining work itself where where the challenge lies. Yeah. And humans find challenge, find change challenging, shall we say, and particularly when it's expensive and when there are some lower hanging fruit that you can take a bite out of straight away. Rob, same same question to you, really. In your experience over the last twelve months or so. What's been the biggest challenge to achieving the outcomes that you have? I I think it's a common understanding. You know, we've we've... We have been a bit feral about the way that we've gone about things, and I think that's part of the, the... That prolific rise of AI, and it's how you distill it, how you how you get things to be structured, and how you... It's... And you don't wanna stifle creativity, but you want to be able to bring a level of conformity, cadence to things. And I think that that it conflicts with some of that. And, also, you know, you you can spend quite a lot of money doing things that don't really give you anything back because you are understanding what the capability of the product is. So I think that's certainly been our experience over the last twelve months, but what's helped container is that we've had some really, really tight deliverables. So we've somehow had to fail fast or succeed quickly, And that that... That's helps bring a, a method to things that we perhaps wouldn't have had if we were doing this as a more, at our own pace type change. And I guess in terms of the the processes piece there as well, Rob, you know, gone are the days, maybe you've gone are the days where it's the big waterfall project management processes for IT implementations and so on. It's much more agile, fail fast, learn less, and move on to the next sprint and so on. Have have your processes in terms of rolling out new processes and new technologies that support the transformation, have they also had to go on a journey so that you can reflect, and reposition as quickly as you need to it in order to deliver the business outcomes that that you've been searching for? Yeah. Yeah. Absolutely. Critically. I I said earlier that we have some very good processes for finance. They they need to be processes there for the business. There needs to be processes that enable things as well as give compliance, give give conformity. We have global process owners. That's one of the neat things that we've got about our shared services set up and our and our our functional distribution. So we've all had to challenge ourselves a bit, and I found myself being challenged as... Well, I didn't realize, but I realized I was a compressor and not a transformer. And what... Someone in my team had been gone through all of the policies, and I've written some of the policies. I was quite defensive about them. And then all these all these all these inconsistencies came out. So I thought, well, actually, you know, that's the federation. That's the beauty of of of of of how you can look at things so very differently. Yeah. So it's been it's been quite a roller coaster of, of discovery, I think. Oh, that... Know thyself and all that. Are you a compressor or are you a transformer? Sharon, are you a cup... Are you a compressor or a transformer? Do you think... And also same sort of question. Obviously, we've been talking about some of the challenges here. We spoke on people and culture, people not finding change all that easily sometimes. What's been your experience with a journey that you've been on so far? So I think I'm the opposite. I'm the transformer. I think I love chaos a bit too much. But I think, you know, with that comes the different challenge. Right? You know, you can see the path. You can see the transformation. You've... You know that you're playing this... You're playing for the long haul. You know, I always tell the team, don't play for the match, play for the championship. So, you know, playing for the championship means that you've gotta address three things, take the hard decisions. Sometimes, you know, you're explaining and re explaining. People... I mean, one of the biggest things about transformation is change. And it's the resistance to change. It's about my spreadsheets work. Why should I change? You know, it's also my life works. Why do you wanna change my routine? So, you know, it's the team works. Why why should... When somebody leaves and you have that whole... You know, sometimes transformation feels like if you know the four stages of the team, you know, it starts with... What is it? Forming, storming, norming, and performing. And sometimes with transformation, you feel that you're stuck or you're bouncing between the forming and storming, and you kinda wanna move into the storming and norming phase a lot more. So I think, you know, the dynamics of change and, you know, it's gonna be constant. You you cannot resist it. You've gotta be part of it. And how do you start to embrace it? What I've learned, especially with my personality, is rather, you know, go smaller with the change. You know, reiterate it. Take smaller chunks of it. And the moment you get people comfortable with starting to change, losing a process, losing the way I did something, you know, having to navigate multiple projects at the same time, you start to win slowly. And then eventually, as a team, You forget that you're actually resisting change and you're starting to embrace change because it becomes a natural thing of your day. But it is the transformation and change is not, is not the easiest thing, especially in a finance function because, you know, it's not like you can deprioritize a month end and say, you know, I don't feel like doing it this month. I'll do it next month. Oh, it's not like you can deprioritize your. tax returns or your statutory. Everything has to happen, and it's about how we walk that. So I think it's breaking it up for the team, showing them the way forward, also managing the different generations just with humans itself. Right? You've got the gen... Whatever we call the newest generation track. of people really have. Almost stuck. You know, you've got that generation that's coming in and often people would say I've done a month end and I'm like, can I do something different? So I said, well, finance is a month end. I've done it for twenty five years. There's nothing different. What's different about a month end is that new challenges come with every month end. New processes come. New transformation comes. It's like I've done a batch return. Unfortunately, we've gotta do it every year. So. it's it's very exciting. It's it's an exciting time to be in finance because, you know, even if you look at the the... And we haven't spoken about universities and the finance fraternity or the finance professionals and graduates that are coming out of universities Because that also has to change from a typical way of how we do finance, how we learn accounting, what we expect, you know, where does all of these different degrees fit into functions. So there's a big change and it's gonna have to come from the academics into, the corporate environment as well. Yeah. I... And and that... That's probably a separate webinar to be fair, but that whole thing about the way in which automation, AI empowered automation is changing the workforce, changing how people get on, how... Take those first couple of rungs on the ladder when AI has removed potentially those first couple of rungs in finance, in legal, and in technology. It's, it's a big topic. One for another day, though, but thank you for raising it. One that I do wanna bring up, and, Preston, I'll I'll come to you first on this one, is is trust. Trust is important for change. Trust is important for adoption and ultimately realizing value going beyond just the efficiencies that we're talking about today. And people need to trust in the technology, and it's not just colleagues. It's it's board members as well. So what have been your experiences in building trust in the systems so far, not just amongst finance team colleagues, but across those senior stakeholders perhaps as well who are maybe signing, in a checkbook to sign off on some of these projects. Yeah. And and, look, I I... You can't over index on this. This is so so critical in getting this, shift in operating model right. Now a lot of us, when we talk about trust and we talk about trust in AI, we tend to very rapidly get to the observability, auditability, traceability, and all of the component parts that would be there in the whole AI engineering stack. Now that is really, really critical, especially in some of the recent events that we've seen as well. Our agents going rogue and so on. But in a way, I would argue that once that's complex, that's that's actually the less difficult part of it. It is important. It is critical, and you need to have faith in the technology that you're deploying and have all of those component parts in place. The more difficult part is the bit that you mentioned, David, there about, how trust gets distributed within the operating model. And as human beings, and we've all grown up generations of... It was just human beings, we now have a synthetic workforce where we've got human beings and AI beings. And right now, when I'm running a finance function, I know I'm very comfortable with this because I know I can point a finger at Shannon and say that was Shannon's task, and I can hold it to account. I can hold you to account, David. But now suddenly, that whole thing, it gets distributed. So So you've got an operating model where I, as an individual, as the... Ultimately, I'm the human in the loop who still needs to sign off on things, but I can't point to, Robert, David, or a Shannon and say, who is accountable in this model? More so than you're dealing with a multi agent framework, not just agents from one organization, but multiple agents working in tandem with human beings, handing decisions and tasks off to each other. Now suddenly, all of us need to get comfortable with this idea of, distributed accountability model, and that is the real, real big shift that needs to happen. So the way we we think about it is, going back to that point I mentioned earlier, not think about tasks and process sequence steps, but think about decisions. And think about all the core decisions that you need to make inside a value chain. Take those decision blocks, and then with the right stakeholders in the operating model, debate whether that decision can and should ever sit with an agent and be executed autonomously. And if yes, what are the risk guardrails that you want. to act around... Put around it? And and I always think about it in a sort of very simple two by two, model of one axis you think of business outcome, and on the other axis you think of risk. And risk in turn has two component parts, mainly liability and reversibility. I... If I want... If I ask an agent to... I'll I'll give a non finance example. So take a call coming into a call center. We've got the technology to identify it. We can have every single traceability, auditability, observability in the loop in place. But if I tell you that that call is coming into a 999 call center, I can guarantee you probably... Definitely all four of us and probably all of us on this call would not be very comfortable for an agent to run with it. Why? Because the. liability is very high and the reversibility is very low. So in that context, you evaluate every decision. And as long as you've got your stakeholders... And I know it's easier said than done, and this is the hard bit of the transformation bit that Chan talked about. It... This is why transmission is hard. It... And I I I always call it heart or lung surgery. Regardless of what your... The technology, it's the it's the human beings in that operating model and hardwired work that you're redesigning. Sure. So as long as you can get them aligned around the decision rights of every single decision block, then you know where it sits. And that, to me, is how you almost reimagine trust. Okay. Right. So we've got about six minutes left. Thank you. We've got about six minutes left. I wanna make sure that we come to our questions from our audience as well, and then we'll see if we've got some time for a wrap up final next action thing. Shall we take a look at our poll that we asked very quickly? We, we asked a moment ago how confident you are that your current financial architecture can support, the rapid business model changes or economic volatility. They aren't in order there. But what I can see is that right at the top is only slightly confident. We still rely heavily on manual workarounds and spreadsheets as Rob mentioned earlier on. Yes. They are a reality, and that just speaks to the journey that we're all going on right now, I think. Let's not reflect on that right now. Let's reflect on some questions, and we've had a we've had a late run of questions from our community here today. Let me, we spoke to Elaine's question earlier on. Tao, I'm afraid... I I don't know if I'm pronouncing your name correctly, but you'll know if this is you. From a finance perspective, can you define or explore AI value drivers other than primarily realizing efficiency and effective decision support ecosystems? Can you define or explore AI value drivers? Rob, I'm gonna throw this one your way because in a way, you have... Well, in lots of ways, you have realized some real value from the journey that you've been on there. And, I can't remember if Tao asked that before or after you and I spoke, But if you could summarize very, very concisely what the key values that you've received, what value you've received is, I think that might be helpful. Yeah. I I think it was a statement of intent around how we want the business to operate and a high degree of credibility for a new cohort coming to join us. So 1,200 people, weren't put off, their first interaction with a new business and a new system, and we had also take... Made a step change in the way that we operate. So if if you like, it's a it's a, our particular use case there was, not necessarily process, wasn't necessarily compression, in the conventional way it's been discussed. But it was a huge amount of enablement and allowed us to do quite a lot of self reflection around things and to do what would have taken us an awful lot more time and an awful lot more cost, with probably more risk as well attached to it. And on that topic of risk, I want to come to a question that came in a late one that flew, under the wire from Catherine. And I think this this sits quite neatly on the back of the trust question. And we've spoken about building trust throughout the organization and what that means. Of course, there are some things that we can control and some things, some external factors that are more difficult. Catherine asks about the recent hugging face story. And of course, this is, sometimes agents go rogue. We've named that already and how that could impact the finance function. I think this is just, a question really about... It builds on the trust question, and there will always be questions asked about AI can be very, very powerful. And in the wrong hands, it can be very powerful too. Should we be trusting that with our internal systems and how resilient are we to those? I don't know, Rob Prasen or or Sharon, if you get questions about about the external impact of AI and the potential risks, cyber risk, call it what you will, on your organization. Sharon. I think... So we we still looking... I think a big... If I if I think about the industry networks and the CFO networks that I've been through, I think there's still a lot of questions around... I think Rob mentioned this briefly as well and, around who takes accountability for decisions. How do you hold people accountable? When a decision is made and it's the right decision, everyone's gonna jump on the AI and say, yeah. And if it's the wrong decision in terms of IFRS or a policy or something recognized, then who takes the accountability? So I think the jury is gonna still be out on on that part of it specifically. I think that what I've seen right now is more of a focus on AI has been in the data modeling, and the value. There was a question around where the value is coming from and it's coming from that perspective because what it takes a lot of... It takes parts of our team a long time to crunch numbers. We're crunching numbers much faster, but we're still having core decision making, core intuition, you know, even whatever co pilot rights. The accountability is a 100%. with the person using the AI as a tool. The AI right now is not making finance decisions. It's just providing. in... It's providing data and information that you are using your own intuition with. So I think that journey is gonna change as we start to... I wanna say I'm gonna use a weird word, but then as the AI starts to get intelligent. Right? So I think. there you can have the challenge because it's not intelligent right now. It's like a child learning to walk, but you're still holding its hand. So you're still. guiding where you're going, and you're still pointing out. what are the dangers in front of you. So It's back to what it is to be human and and understanding the value that we bring and what the automation brings. And I think that's a really invaluable, really valuable point to end on today. Obviously, we're talking about AI AI empowered automation, but then understanding where the value comes from and the role that technology can play in that, but the role that humans can play in that as well. That's it. Like I say, we are almost out of time for today. Robert, Prasen, Sharon, thank you for joining us. Thank you very much indeed. And thank you to Fred and all of the team from Workday behind the scenes as well. We will be back in December for our final European CFO community event of the year. Details are on the screen right now. Our speaker is a big thinker, a big global leader on innovation, digital transformation, the future of business, six time best selling author, lecturer all around the world at some really, some huge companies there, Apple, LVMH, BMW, Microsoft, and so on. Peter Hinson, reporting for change from insights to outcomes. That's on the December 11. And to find out more about upcoming events, zap that QR code to join the community. But for now, from me, David McClelland and everyone here, thank you.