Name: The FP&A Journey: From Excel to AI
Uploaded: 2026-01-15T17:30:44.466Z
Duration: 54 min 44 s
Description: The FP&A Journey: From Excel to AI

Transcript for "The FP&A Journey: From Excel to AI": Hello. Welcome. Welcome. I see there's a couple of familiar names in the chat room. So great to be here with everyone. I'm just gonna speak very slow while everyone trickles in slowly. Welcome. Hello. Let us know where you are tuning in from, what you're working on. Just drop us a quick hello in the chat room. So just to introduce myself, I'm Christina. I'm the community manager here at Finance Alliance. It's so great to have everyone here. But, of course, we're joined by Daryl from OONAD Software. So great to be with you today. Just a couple of housekeeping rules to let you know, the chat box is free and there to use. Thank you so much for everyone. Chicago Go Bears. Wonderful. Oh, this is my favorite part. Aside from the chat room, we also have the q and a function, that you can see just on the top right. Similarly, you know, we live and breathe on Slack. So if you do have any issues, and you want someone to troubleshoot some stuff, I will be checking the Slack, space as well. So you can always find me there. Recordings will also be sent out, but there are so many great interactive, features coming up, so, definitely stick around for those. And I do think you're done listening to me because you're not here for me at all. I'll hand it over to you, Darrell. Enjoy. Thanks so much for being with us. Thanks, Christina, for doing the lovely intro, and welcome, everyone. I'm thrilled to be here, to talk to you about the FP and A journey, from Excel to AI and, just a little bit about myself to get started here. So I've been doing this for a few years, so it's gonna be a lot of me in this story. I've been at big companies, small companies, variety of industries, and a little bit of a personal story here. I can trace my story back to my childhood quite easily. It was, the LEGO that did it to me. I can remember when I was a kid spilling and spreading my LEGO out over the top, like, protector cloth on a giant snooker table and spreading all the parts out and trying to get build my little pile on the side of the best parts before my friend got to them first, then creating something and using you know, basically taking the entire day from just after breakfast to just before dinner till my mom called me, to, build something and then putting that thing on the side and staring at it for a few days before it got stuck back into the suitcase. I used to get this huge sense of satisfaction building something cool and novel where all the parts matched and colors matched and everything that, you know, no one would ever believe the building. I would never use the LEGO instructions. And that kinda, like, is what I do today. Instead of building with LEGO, I build, you know, with finance systems and processes and data and, a lot of Excel. And, you know, that's that's the finance guy in me. And I love being able to put something together and, you know, create something new. And you'll notice in my career, a lot of times there were growth stage startups or later stage growth companies, even the bigger ones. You know, ATI and WINS were in the growth stage. Virgin was was, I joined prelaunch. When do I join prelaunch? So that kind of thing. But very similar to that whole LEGO experience. And, it's what I love to do, and I'm so happy to be here. And I'm gonna it was growth in every single time. So growing a team, growing not just the finance team, but the organization, and driving growth. And so that's what I'm gonna be talking to you guys a lot about today. So a lot based on a personal story. So I'm happy to be here. So what we're gonna talk about specifically is how technology is the foundation of the FP and A finance maturity curve, at least from my my point of view. I'll try to, persuade you that, you know, my point of view is the right one. Just kidding. But, hopefully, you'll take something out out of this and how to, do things maybe different or improve your situation or feel inspired. And what we'll cover in that discussion is what the finance mission is, how, you know, mindset really helps define that, and that'll take us to the maturity stages and, how that fits into achieving our mission and how looking at it in different way with a different mindset really helps define what that is and can change it, and how technology supports that and, drives drives maturity. But it's really to me, it's a big part of it is it's it's all about that mindset, and it's how you look at things differently when you pick a different objective, when you look at it from a different a different angle. And what an example I like to think about is how finance teams or finance people often find themselves in a pickle, because or they feel overworked or too stressed or don't have time to get you know, they're working all night to get that report out and don't necessarily have time to get to the more important things, especially if you look at it through the maturity lens and what I believe our objectives would be because, they haven't made an investment. So they a lot of teams, and I've been here so many times, they find them especially when they join a company, they find themselves in a situation where they don't have the resources. They don't have the team. That's why they're working so long. Because somewhere along the line, they made the decision that it's better not it's it's better to be miserly. It's better to set the example and conserve resources, not spend too much. And that's what we're always trying to persuade everybody to do is how can you do it for less, and cutting expenses and talking a lot about that. But to me, that's the wrong mindset. And you get there because, know, we made a short term decision without thinking about what the end objective is, looking at it from a different perspective. If we make an investment in finance, we can earn a return on that, and I think it's a significant return. And, you know, and if we're focused on driving performance and not just conserving, resources, we can make a big return on that so you'd actually wind up in a better place. And it's that mindset that I'm gonna be talking to you a lot about today. And so we'll kick this off with a a short polling question, so I can see who's with me here today. And we're because this is an FP and A presentation, we're gonna be talking a lot about forecasting, so this is key. So I'm gonna, you know, move over into the poll, section and, open it. So how well are we forecasting? So is this, open now, Christina? Did I do the right thing? I can't tell. So assuming that we have, and, Christina, if I have if you could share the poll for me, that'll be great so people can answer. But the question is, how well are you forecasting? Are we are you believe you're amazing? Do you think you're doing a pretty good job? Do you think you can it needs improvement, or does your forecasting need significant improvement? And, I can see the votes coming in, so it looks like it's open. I'll give it a a few minutes. But to me, what it means if you think you're doing amazing, because they're never it's not about being perfect because no forecast is ever ever right. At some point, it's gonna be wrong. To me, it mean it matters a lot about, you know, being closer ish to the mark, but also how often can you adjust, How much data are you are you taking in to to to make that forecast? Are you using early indicators? And, can you adapt quickly? So not just putting out a forecast once a quarter or, you know, or a budget once a year, but if needed, redoing it frequently is all is important to me. So I think we got all the votes in that we need. I'm going to close it and, share the results. And what looks like is needs improvement, is number one. So fifty eight percent of people said they need improvement, isn't a surprise because I always think I could improve. But good to see no one on significant improvement or hardly anybody. And, also, no one said amazing. So self awareness, I think, is important. And as a finance person, I would have been surprised if I saw a lot of people, a lot of other finance people saying they're doing amazing. So this is this this this jives. So we're in a good place. Maybe do a little bit of, learn a little bit how we can do better today. Okay. Back to the slides. How do I get back to the slides? Slides. Okay. So okay. So this is how I how I think of the finance mission. To me, it's all about driving performance. And, yes, we need to pay bills, send invoices, and file taxes. But it's driving performance that makes the difference to me. And the way I look at this is that we are a support organization. And so, yes, we need to pay the bills, send invoices, and file taxes, and all that fun stuff. But our main objective is to support our team in any way that you know, it's to support our team in any way they can. And and it's their objective is not to get just to have their suppliers' bills paid. It's to achieve their objective for why they hired that vendor in the first place. So it's if if their objective, and my favorite example I'm gonna use over and over again, is to drive sales or to drive marketing leads or, some somehow drive revenue, our objective should be to help them do that. Yes. There we're gonna help by paying the invoice, but there's so much more we could do than just that. We can transcend those those invoices. And, how do we do that, is is is what we're gonna talk a little bit about today. But the most important thing is to see that is that's paying that invoice is not is not the end. And it's the same in every organization and every size of organization. So and just like I've been in every size and shape of organization in any industry, it's to me, it's the same. And it's really just about who do we wanna be. And an example I like to think about in this context is even within the more narrow scope of finance is, you know, many of us get a finance reviewed on annually or an audit or something. And a lot of the times, that's looked at as, you know, an unnecessary, thing, kind of a little bit of a waste of time and a pain in the butt. But I think we could actually look at that as a good example of frame of mind as well. So the audit is supposed to be, you know, somebody looking over our stuff and saying, hey. This is right. This is wrong. This is good. That's that's not. But if you look at it as a test of what we should be doing, it's like so it's not just for a third party, but for ourselves just to make sure that, you know, we're doing the right thing. It's about it's something to help us understand how we can do better and what we should maybe be doing differently to be better. Those auditors go to so many different companies. They see good things and bad things, and they can really, you know, in through an impartial lens, take a look at what we're doing and help us do better. So, again, it's about the mindset. Is this audit for an external investor, or can it be for us, and can it be helped to improve? So it's how do we improve our performance, and how do we help the company do better? So how do we drive performance? And I've again, something I'm gonna get to over and over again. What are we doing different, and what is the main thing to drive us to drive performance and and enable us to do it? And to me, it's it's it's all about the mindset. So and not just FP and A. So if I just take a little step sideways here one more time is, as an example, it like, coding invoices. So, you know, if if are we just coding an invoice because it's somebody's responsible for that expense, we wanna make sure that they're held accountable? Or is it also so that we can do a nice a good analysis, make sure that data is in the right spot? And, you know, it's one thing that FP and A people often complain about is, you know, not coded properly, or they're always in there fixing, and sometimes a source of tension between the accounting team and the FP and A team, but it doesn't need to be. And it I would say the onus is on the FP and A team, in part here, to help make sure people understand why it's important and how that even helps drive performance. So it's the whole team that needs to get behind us and is in in part our job even as an FP and A person or, absolutely if you're the CFO and everybody reports to you or the VP finance. It it's the whole department, and it's having that mindset to understand why you're doing something, what the end objective is that makes a difference even in something like that, coding an invoice or the financial audit. It's all about the mindset. So here, another polling question. How do you control uncertainty in your plans? So open the poll. Share. Okay. So is it a little trying to be a little funnier. Finance joke. A wish and a prayer. Is that what it is? Or do actually, trying to manage it. Input from sales. And so definitely something that, you know, I always try to get even if it's, you know, I have all the data I need. You never know what you're missing. Always important to be curious and asking questions and another way to get buy in. Comparing the historical trends, 100%. But trends in what? Investing in processes and technology, and this kinda gets to the root of what we're talking today. And what do you do with that? Is it scenario analysis and contingency planning? Is it just collecting the data? Is it automatically disseminating reports? What is it that we're doing with technology that really helps us? So I've got a lot of votes in here. I'm going to close and see what comes up here. K. This is good. Scenario analysis and contingency planning. That's really good to see. Lots of that. And I'm interesting to see that investing in processes and technology is is so low. I would argue that, this one is actually a bedrock in in to me in ensuring that you have a handle on uncertainty, and I'll explain a little bit more on that. But at a high level, it's because it helps me do better scenario analysis of contingency planning. I love the fact that, you know, we're all going right to scenario analysis contingency planning because that is the ultimate objective, though. Okay. I'm back to slides. Okay. How do I get back to slides again here? Doing this again. Slides. Okay. Thank you. So back to this view, where, you know, we talked about setting invoices, filing taxes, and driving performance. So again, it's about this mindset. You know, when we answered that last polling questions and responded that the way we control uncertainty with scenario analysis and contingency planning, I love that. And this is where it sounds like a lot of us on this call are aiming to drive performance. So we're we're, you know, we're skipping past well beyond just paying the invoices. We're trying to get insights out of that data we've collected. And, you know, this is where it starts to get interesting is, like, what are we using in the scenario planning? And so, you know, once you've got invoice data, and you've got, you know, that data kind of segmented, then it's like, well, what more data can I connect to that? So where did that lead come from? So start to think about things that aren't in your financial system. So it's, where did it come from? Who brought me the lead? And, you know, how many leads do I need to get to that invoice? And what was the conversion rate from lead to invoice? And maybe there's more steps in between. And so once I start to accumulate this this information and, you know, connect with the sales and marketing team, we'll probably have a pretty good view on that. Do they do they understand as well as you would expect, or are they maybe missing some things? And so this is where we start to be able to add some real value and get to that scenario analysis and contingency planning. So it's like and if you were able to do it frequently and do it for every every weekly go to market meeting rather than just quarterly, you know, and do it well and quickly and not have to spend a lot of time reconciling your data connects with the with the marketing and sales data so that it's, believable, and there's not a lot of debate on whether the numbers are right. Then we're nearing the top of the curve, and it's like we're driving performance. So it sounds like a lot of you are are on this path or somewhere there. But it's interesting. Sometimes you can get lost on the way there because there's the steps, and then there's the I mean, the tasks that we're doing, and then it's, like, achieving the objectives that we're aiming for. So, of course, at the very bottom, it's it's it's the the root. It's the accounting, the compliance. And then we, in FP and A and the finance team altogether, are doing budgeting forecasts budgeting and forecasting and reporting. And but sometimes that can be the end. And scenario analysis definitely fits a little further above that. But if we're stopping there, we're really a finance leader and and you know? But we're not necessarily a strategic leader. And it's when we start to think about the objectives of our business partners and what they're trying to achieve that we become different. You know, helping them set those objectives and thinking about the contingency plan. And this might not seem intuitive, but it's also aligning the team. So when we have a good plan and everybody knows who's responsible for what and confident that everyone's objectives fit together like a puzzle, you know, then we're able to drive really drive the performance. And so one this point that I'm gonna try to try to stop saying soon, but I really wanna hamper it over and over again, it's it's about the mindset. Why are you doing it? Why do you it's it's not just about the task. It's about the objective. And this is what underpins this finance maturity journey for me. If we're aiming to drive performance, then we will push ourselves up that that that that journey, push ourselves up that maturity curve. And whether you're if you're building a team, building a company, and you're also building the performance and trying to to grow performance in those teams, but also as an individual, we're gonna be able to to do more and feel more satisfied with what we're doing. And, you know, we talked a little bit about the tools that are the reports, the forecast, the budget, quoting invoices proper properly, but it's bigger than that. And this is a perfect example of how the mindset makes us think differently. It's about the people, the data, the processes, how we influence the people with the data and the processes, and what role technology plays into that. And especially these days as technology is changing so so much. I mean, it's evolved over the last twenty or thirty years, but now it's accelerating at an incredible pace. And that's why, in part, why I believe the technology part is so important and whereas not necessarily wouldn't necessarily have been on this list, a while back, but today, it certainly certainly is. And not to forget the, grit, determination, and alignment, because to get this all right is is not easy. And, if, you know, we're beginning out with in a in a less mature organization and we did wanna achieve these objectives of driving performance, we have a lot of work ahead of us. Maybe the finance team doesn't have the respect, get the time, or, I mean, for as an example, finance team isn't invited to the meetings. People don't come to you. It's all us going to them. We will need some grit to get where we wanna go. Polling question number three, what is the foundation of finance maturity for you? What what do you think? Gonna open this poll. Oops. Did I just close the biopsy there? Yes. I did. Open. Okay. Is it the people? What do you believe is the most important thing? The data, the process, the technology, or the influence that we exert on the process in our organization? I think you kind of, like, foreshadowed a bit what I believe here, but interesting to see what other people believe. And it's interesting. I've asked these questions before, and I often I'm surprised that the answers are are different, So different sometimes depending on the group. And so this this I'm feeling is pretty complete, but you can you're getting there anyway. So you can see process coming ahead. And many times I've seen people be the number one. And but almost every time, it's not data, and it's not technology. So here's where I'm gonna try again to make maybe, look at it through a different lens. So I'm gonna close this, move back to the slides. But it's hard to do these things that we're talking about, to to coordinate the people and put processes around, that enable them, to get to the point where people have the confidence in their plan and us so that we can influence them, it's not easy. And, you know, back to the example that I really I really have experienced over and over again is connecting the to the sales and marketing team. And, you know, I've been there so many times where the data doesn't match. It's too dirty. You have to hire people to reconcile it all the time. Going into meetings and the marketing team's like, no. That data's wrong. It's hard. But it's, you know, it's it's necessary if we wanna get to where we wanna go. And the reflect and it's not just me. It's so many other people see this, and I'm it's like across the industry, people having challenges with the, with the finance data and connecting to revenue and coming up with great forecasts. I don't know if you're familiar with this like I am, but this kind of a, you know, this this kind of a waterfall chart, would show if I could. But, basically, you know, you've got this year's forecast, what was next year's forecast, or this current year's budget, and what's what were the, you know, the bridging the bridging factors and general optimism and being, like, a, like, a big kinda like, we don't know. And, you know, would we be love to be able to bridge that? And, if in doing so, we're gonna we're gonna do a much better job of the forecast. But, you know, it's again, it's hard. And, these are the things that I've been running into. So data overload, and a lot of people complain about data being inconsistent and inaccurate, doesn't connect, and ultimately not enough resources, which we we covered earlier. So move to a different analogy here is, use this Roman temple as an example of, you know, how I see a role. So there's the foundation at the bottom and, you know, these columns holding up this this beautiful pediment, that points to the sky. And inside, there's that there's that that that room where, you know, the deity, like, some statue would be, like Nike or something like that. But it's it's it's like this in my mind. It's the people, the process, and the data are in the middle, and it's it's what ultimately builds up to the beautiful pediments, which is the influence in how we're able to drive performance. And that's the part that you find in the museums where everyone goes, wow. That was great. How did he how did they do that? And that we admire. But all of that is built on on the technology. And this is what the maturity matrix looks like. So if you put this in context of a forecast specifically, there's the buffer that I think is the measure of how how how we're doing and, you know, how accurate that forecast is, how reliable if we think we're doing great, a fantastic job, or a good job, or it needs improvement. And and why that's so important is a buffer is is effectively, stranded resource. It's you know, if a if a forecast is believed, the people have a confidence in the forecast, and it's, you know, historically been pretty accurate. People feel good about it. You're gonna have smaller buffers. But if confidence is low, you're gonna have this bigger buffers, because nobody wants to underperform. Everyone's aiming to overperform or, I mean, at least least get close. But if there's a lack of confidence, you put in this bigger buffer. And the buffer is effectively a stranded resource. And why is that so important in concepts of driving performance is, you know, you park that money to the side. It's not earning a return. It's there just to make sure you don't miss it. And then, I mean, if there's a chance you do miss it, it'd feel dysfunction. But if you weren't going to miss it or if you hadn't had that buffer, maybe people, your team would have been better aligned on hitting that higher objective, and you wouldn't have stranded those funds on the side and parked them not earning a return and called it a buffer. And, I mean, I have this this one of my favorite examples is actually an inventory example at a manufacturing company I once worked for. And, we had this yield yield issue and and time time production time issue that combined into big inventory write offs every year. Effectively, we had to sell our inventory long before the manufacturing process was was completed, and the engineers put up all these yield estimates. And everyone put their little bit of buffer and, one layer on top of the other. And at the end, the prediction was, you know, on inventory that was gonna arrive included a huge buffer, because everyone wanted to exceed performance there. And so what happened is every year, we would do better, than expected. The buffer was bigger than it should have been, and what that led to was a bunch of inventory lying around that we couldn't sell because it had already been spoken for way earlier. And, so we were we would wind up with a big inventory write off. So a very visceral example of how, you know, how people not having confidence and in in a forecast in a forecast process that wasn't so good, you know, how that causes a real problem. In that case, it wasn't, you know, it wasn't an easy problem to solve. But, once we did connect the, all the data together and worked harder on that that forecast and really thought about our objective, we were able to get that down in that example. So that's so but a great example of how a buffer can lead to lead to problems. So here specifically is the tech tech part of that maturity. So, you know, this is not the same everywhere. It depends. One size doesn't fit all, but I think this is a good representation. It's also in it's interesting that, you know, mindset doesn't change in here. So even if you're just spreadsheets and your manual you know, it could be the stage of your business where you're you don't have a system yet. It's just getting off the ground. And another good example of how spreadsheets can be interesting, even if you have the right if you have the right mindset, is it could be a great tool to iterate because you don't want to invest going right up to best in class integrated FP and A system without knowing exactly what you want to integrate, what you want to use it for, what the outputs are that you need. But you can see how, you know, the from you know, in a manual spreadsheet, it's difficult to integrate a lot of data, and it's difficult to do it on a repeated basis. And, you know, obviously, there's gonna be a lot of manual effort. So for me, the maturity for finance on the tech side, you start to see some systems, less spreadsheets, and eventually at the top, lots of integrated systems that are highly automated. And, you know, today, the new layer in here, even over the past couple years, in any case, you know, beginning at a at some point in the middle, you start to see some ad hoc AI, or more general applications of, you know, broader, not application specific AI. But then, you know, as you become more and more mature, it's application specific AI. You know, very all kinds of data being fed into the AI to connect dots that you wouldn't be able to connect before. But the way to get that is you need still need that foundation. So going from spreadsheets and manual to, you know, a data mart, and, then to automate that data mart. And just to, move along here because I'm, like, really behind now. So it's AI being the supercharger of the things that we need to do. So it's how can that help us, you know, connect the dots in the data? How can it help us reduce the manual work? How can it, improve our ability as a storyteller and then ultimately drive action? So before I dive into more detail on the AI, specifically, one last poll. How are you guys using AI today? I'll open the poll here. Go to polls tab. Okay. Christine, can you help me open this, poll here? There we go. Thank you. Yeah. This is this is, I think, very common for a lot a lot of us just experimenting. The good news, which I'm gonna get into, more detail in a second, is I find that Whereas earlier on, we really had to, work hard to implement AI, I would say, find AI, you know, customize it, tune it. But now a lot of it is just available is available in the tools we have. So this is interesting. Experimenting conversational analysis, excellent. Autonomous starting to happen. I see this autonomous thing happening a lot in more operational finance. So, again, back to invoices and such, which can be important because it can really accelerate your time to close the better we do in those those things. So get the story out sooner, but less so in absolute finance. So this is interesting. Okay. Close poll. Stop sharing. Okay. Oh, shit. So now I'm not sharing that anymore. Thank you. So where can we deploy AI, and how does it happen? And where can we get this from? So one area that I've found AI to be incredibly helpful, and you can see this increasingly in tools, so a lot of FP and A tools, you know, they will have AI agents right right in. And so even some a lot of the older vendors that have been around us, so if you're one of these finance people that is has a CPM solution, maybe even if, you know, little earlier generation, AI tools are just starting to show up. But we're the new new, tools you're starting to see, and, you know, it it could apply at any stage in our in in in our maturity. So even if we're using a lot of manual and spreadsheets in in ad hoc kind of environment, you're starting to see significant improvements in AI even in Excel. But all across the ranges and right to the high end, examples that I've been seeing more recently are for example, if you're implementing a new system, that system might have automatic, report builders. So you can you know, once you've uploaded the data, it'll automatically, for example, produce a set of financial statements. They're not perfect. And so this is one thing that we are reading I'm reading a lot about, but we have to keep our eye on is having the human in the loop so that you know, and and ensuring that the AI gives us the ability to to, adjust and tailor and find issues. So, it's also showing up in so that's, I would call, automatic mapping, but also an error in an anomaly detection. So it can really help and speed up our month end review process as an example. I can still remember the days going down, you know, with a ruler line, you know, line one line at a time looking for the weird trends, and, you know, that taking a considerable amount of time, you know, doing it at a departmental level, at the you know, on the balance sheet, not a consolidated level, because you never know what you're gonna find. But, now, you know, a lot of the systems will do that for you. So, again, what's interesting here is that, you know, getting can get a system, and if your system already has this and or is starting to to you you you include these kinds of features and functionality, you're automatically picking up AI. And you can experiment with those features, but the time to implement and the the success level of the implementation is gonna be a lot higher because it's purpose built. Trying to build you know? And it's it's interesting. It's like earlier on, you know, in my career, I'm building my own data marts, because there was just no such thing available. But it was difficult. You needed a team. It was expensive. I'm so, you know, happy that I don't need to do that anymore because a lot of the different CPM solutions right now include a lot of the data the ability to connect all the data. And, the AI really helps accelerate making the connection, but then analyzing the data. So this is an area where AI is having a major impact and can have a major impact on us finance people in the FP and A trying to drive performance. Another area is, is so it helps you connect the data, but it can also really facilitate what has been extremely difficult, data integrations in the past. So there's the AI agents that can help you. So for example, a data modeler agent I I just described, but also in the heuristic thinking. Whereas in the past, the part part of what made it so difficult for me to connect the data was the fact, you know, going back to the marketing example sales and marketing example is that, you know, it's unreliable data, and it doesn't necessarily connect well with the finance data. Sometimes it you know, there's an integration built, and that's great if that happened because this isn't so much a problem. But in more cases, more often, the finance system was implemented, you know, it didn't connect with Salesforce or HubSpot, and it's just too difficult. So people try to get the data. If you're really trying to drive performance, really get those insights, but it's really, really hard, and you're stuck with a lot of manual fixing and reconciliations and debates over definitions and such. But with AI now, you can connect that data and get insights almost, you know, super quick, and on a repeatable basis, even if it's imperfect, what'll happen is an AI tool that can do this will give you, options. It'll say, hey. I saw this. Your data is, like, 80%. Okay. These are where you could do a better job connecting the data, but these are some of the low hanging fruit that I can see. So this is something that's super exciting, the ability to use imperfect data. And some systems, will even help you correct that data. You know? And and what's in in the past, you could do that based on rules, but now with AI, it's a it's a it's a lot more effective because sometimes there was always a rule that didn't or some kind of exception to the rule. And so it's something you would discover and then need to build a new rule for or something. But today, the machine is able to do that. So in basic integrations, but in particular, difficult integrations like revenue integrations, this is this is really powerful. And my last example, for today is, you know, being the storyteller. And so the many of us on this call who are trying to do scenario analysis, and contingency planning, this is amazing stuff. So when you have all this data to power through and, you know, you just can't get through all of it, and, you know, hopefully, you do have that. If you're just relying on the finance data, I would say you're a little bit earlier in the curve. Once you've connected a lot of data and you've got, like, a lot of rich connected data, your ability to tell a story is significantly enhanced. But if you can't get through that data to find the story, then, you know, it's it's, you're you're not quite there yet. So AI today, can really help you get to it. So just like, you know, when you're doing a search online with Google, you really had to, you know, go through pages and pages, but now it just gives you a good answer right off the top that you can then refine with increasingly pointed queries. Same thing now in a lot of the different, CPM or FP and A tools that have the natural language queries. So I saw some of some of you, doing that, this is definitely, a great a great way to do trend and variance analysis more quickly, more in-depth, and, also get to quicker reporting and presentations where, you know, it could take could have taken a long time to get a nice chart. I just ask the machine to give you a chart. So I would love to give you some examples, actual live examples, but I didn't think this was long enough. But I do want to encourage you, if you want to know more and see some of these functions and features, AI enable enable the FP and A in action, You can reach out to me. I'll give you my contact information at the end of this. Or you can reach out to a team member, from my company, Oona, who does do a lot of this stuff, and we can give you a demo tailored, for you on how, AI can help. And a lot of other vendors, you know, can do some of this, and, you can also reach out to them. But, you know, the most powerful thing of all of these that I that I like, that I know, is not so common out there is how is leveraging imperfect data, how to get the, you know, low hanging, you know, pretty transformational insights from data that, you know, in the past, it was really just impossible to connect. So I guess back to the technology point and why it's so important today. Although the mission remains the same, It's you know, it doesn't matter what size of company you're you're at or what I'm at. I'm always trying to drive performance. And, you know, in the past, you know, if you're just, in Excel, there were certainly advantages to, know, getting a bigger database so you could, you know, connect more data, do it on a repeated basis, do it more quickly, and, you know, begin to connect more powerful data, introduce automation so that you could do it more reliably and more quickly and have more time to do the analysis. It's you know? And, you know, it was you would get to a point, and then for a few years, you could stay there. And you could make smaller incremental investments, but things weren't really changing. But today, the technology is changing a lot more quickly. And, I took I mean, AI is, to me, is like a platform change, and it's kinda like, you know, when mobile rolled around. So at the beginning, you know, when, you know, the mobile applications with the, know, iPhone one and two, you know, started to show up, there was most of the mobile experiences were just web experiences pushed onto the web, and so they weren't that useful. It wasn't until people, be you know, began to experience, the actual mobile use case that the mobile app started to get really exciting. And maps to me was the best example where, you know, when the map was a piece of paper, you had to unfold it, but you could get to a to z, but it was a little cumbersome and you needed a copilot. But maps today is like an assistant. It's it's someone it's a guide. It's not actually a map. It's it's the cameras is the same thing, whereas before you had this, like, this bulky heavy lens thing and, you know, you couldn't carry it around all the time, so you missed a lot of photo opportunities. It's the instant ability to take a picture that's transformed photography by being so small and being able to transmit those images because it's really connect it's in the phone. It's the mobile phone experience. It's not just taking pictures anymore. And I think AI is that kind of transformation in the finance department. I think right now, part of the reason why we're all still experimenting is we haven't seen that big shift, but it's coming. And if our mission is the same, but we can do a better job with better technology and the technology is moving so quickly, it's important to me that technology be increased in the level of importance and why it's so important today, where it would have been people was definitely the number one thing. Organize those people with process. If they're not organized with a process, you're never gonna be able to communicate properly, so you need that process to communicate. With AI, because all that's gonna change so much, we need to invest if we haven't started to, or we need to start to experiment with how this can help us. So we're there, and we've learned, and we understand what's good and what's bad and where we need to be. Like, so, for example, a lot of people saying or have been, and but this is changing is, you know, I need my data to be perfect. I need these things to connect before I can start thinking about it. Actually, no. You can use AI to help make it better and help to connect it and, you know, to accelerate your path to being able to do even more with AI. And because it's changing so fast, if we're not adapting and changing, we're basically falling behind. And this is what's so important to me about technology today. And where it has been always a cornerstone in driving performance, I think now it's been elevated, it's risen to be probably the most important thing in my mind because it enables everything else. And I can see, you know, in the so this is, like, basically, an illustration of a downward spiral or vicious circle for finance. If you're not strategic and you're really just doing the invoices, you're not driving performance. And if you're not driving performance, you don't get invited to the meetings. People don't come to you. You have to find them. So it's but once you've earned the respect because you've come up with value, you've demonstrated that you understand your business partner's objectives, and you're helping them achieve them, you're able to attract investment. People start coming to you. But if not, you don't get investments, and you're not investing. And it's hard to justify an investment, and so you just get overworked. And then you have less time to do analysis, and it just you just get less strategic. So we can't get trapped. It's so important not to if we're trying to drive performance. It's about it's about excelling and creating your way out of here. And, you know, if I, you know, look at this sometimes and not think about it in smaller pieces, it's easy to get overwhelmed and freeze. And, I've definitely seen people freeze, and they get stuck in that trap, and start because they're not able to see they can't see achieve their objective, they don't see the objectives and kinda give up. And I think these are my tips for getting out of that. It's, do something now. Don't procrastinate. So experiment. I think that's a great idea. But push it. And build credibility with early wins. I talk to my staff about this all the time is, don't work on something really big and look at it as one big chunk and deliver it, like, two weeks from now or a month or, you know, a year from now, especially bad. Try to break it into as small chunks as possible and establish credibility with early wins, and people start to see you're adding value. So it's and every one of those little wins along the way, you know, is worth something. So it's really important to build build your list of what you wanna accomplish based on those long term objectives and then chunk it out into low hanging fruit, small quick wins, and always have some on your calendar. So it's like try to achieve an you know, the OKR process that I've been, you know, using for many, many years now is such a great way to look at this. So I highly encourage people breaking things into smaller parts and doing it in a systematic way using a process like OKRs or something similar. And, ultimately, invest in the right technology to make that happen. And a lot of those projects on your to do list might be technology implementations, because those are what's going to enable you and your team to get the data, combine it, automate the process, and get to a story, get that story out as often and as quickly as possible to really influence and drive business and drive performance. And because of where we're at today with rapidly changing technology and, you know, you know, our ability to get better and more powerful so quickly and for a lot less investment, it's let's try to keep ahead and keep on investing and not find ourselves in that situation where we're being overworked and, you know, getting buried by data and not able to get done, what we wanna do. K. And I'm just about at the end here, but, for the last thing, a word from our sponsor. So I'm the CFO at Oona, and, we are a CPM platform, for FP and A, so corporate performance management. We connect data sources from across your organization and, use AI to supercharge every part of that, and it really helps you get to, story more quickly. So, again, if you wanted to know more about this, I'd be thrilled to, to talk more or get my team to assist you and, give you some live examples. And I encourage you to check us out and also other other other vendors that do, the modern ones especially, who do this kind of thing. So takeaways. Highest level of FP and A for me is to drive performance. I think many of us on the call agree. Or why else would you be doing, sensitivity analysis? I'm thinking of contingency planning. To do this, you need influence. You know, it's great to bring forward an analysis, but it's amazing. And you're really I think, you know, the measure of whether we're doing a great job is whether or not we're influencing the organization and driving change. I think we could be able to chart a direct path between what we're doing and, you know, actual performance, be that reducing an inventory write off. You know, historically, a lot of the times, it's the same write off. It's just a matter of scale. How do you get rid of that? It could be driving revenue, and that could be through better goal setting, you know, finding, you know, insights like you don't have enough leads to get to that number, so either reduce the number or get more leads. It could be about reducing cost of activation, cost of acquisition, or cost of sales, like, in selling things so that you are, you know, able to redirect those resources to more effective uses, whatever. But to do this effectively and to the maximum of our ability, because we really are equipped with the skills and experience to do this kind of thing, it's about doing more, doing more efficiently and doing more frequently, building our the confidence of our team in our work so that we can, have that influence. And we are the best way to do that today, I believe, is the technology, is investing in the newest technology, experimenting with it, but, know, doing at our own pace, but certainly not watching it and standing still. And the highest level of FP and A today is just regularly looking at continuous improvement and making regular investments in enabling our teams either through training or, you know, more people, but most importantly, through technology. And that's it for me. Thank you for tuning in. Okay. Thank you. Oh, sorry. Just, wanted to say a big thank you, Daryl. We do have some q and a time, but I think everybody is giving you a thank you. Thank you. Big claps all around. Did you wanna share your LinkedIn or anything for people to keep in touch? That's completely up to you. You need a follow-up email. Up to you, Daryl. Are you happy to wrap up now? Or Yep. I'm good. perfect. Thank you everyone for joining, and, obviously, thank you so much for your expertise and your time. So great to hear about, you know, your whole journey here as well as Una, and we really hope to see you on our screens again. Thanks so much. Okay. Thanks, guys. Thanks for seeing.