Stop Doing Monthly Reports for Analysts to Automate Finance Workflows Using AI with David Dors

The way we currently access data is like, you go into your ERP and you click X for the report. And then you go on you, you configure it and you say, I'm doing this time period. But your agent can just go and get all that data for you without going through a UI and taking all that time. It just goes and it runs connection that gets that data right back for you. So just those things like that were, they might take five, ten minutes, but over the course of a month, a year, it adds up to hundreds of hours. Where, why am I doing this work? If it doesn't require my judgment, I'm just exporting the same report every time. I think it should go to agents. Welcome to another episode of FPNA Unlocked, where finance meets strategy. I'm your host Paul Barnhurst, the FPNA guy. Each week we bring you conversations and practical advice from thought leaders, industry experts and practitioners who are reshaping the role of FPNA in today's business world. Together, one cover the strategies and experiences that separate good FPNA professionals from great ones, helping you elevate your careers and drive strategic impact. Today's guest is David Doors. David, welcome to the show. Hey, thanks Paul. Excited to have you. So let me give a little bit about David's background you know, he started in FPNA and today he is full time working to implement Claude and FPNA software solutions for the office of the CFO. He started his career in banking. We won't hold it against him supporting private equity and wealth management clients. Then moved into FPNA before going full time into finance transformation. He holds a degree from one of my alma mater's Arizona State University. I tried it my MBA. Great school. Number one in innovation. It is a good school. I was there. I lived in Arizona 2006 to 2016. No, 14, 2014 I believe. So it was there eight years. Yeah, I've been here since I think around 2006 as well, but I've stayed. Okay. Yeah, I was going to say, but you were probably a lot younger than I was then. Yeah. I'm old. I know I'm interviewing people that I'm old enough to be their dad. That's what it's scary. So, but hey, what do you do? Like I just the last guy interviewed. This is a business partner of mine on a project and one day we were so they're shouting, I go, you rise, I'm old enough to be your dad. I feel old right now. All right, back FPNA. Everybody's like, just stop stop reminiscing Paul. Get to the point. All right. This is the question we ask everybody. If I asked you to define what great FPNA looks like, what would you tell me? Great FPNA. I think it's definitely around finding the constraints of the business and then changing people's decisions on what they're doing day to day. So every forecast, variance analysis, Ducky build. It's there to help somebody make a new decision or change the decision that they're going to make. So if nothing change from analysis you're providing, there's not much value in what you're doing every day. So I think definitely starting with, instead of starting with the data, starting with who's deciding what do they believe in and what would make them believe something different. And sometimes it's just confirming their beliefs, you know, just making sure that hey, we're going down the right path, but also it can be we need to make a make a change and what would it take to actually convince them to make that change? I really like how you said that if we're not helping people change decisions make better decisions and we're not really fulfilling the purpose of FPNA. There's always some constraint holding our business back and if we're not looking for that every day, if we're not trying to change the decisions we make, we're just going to stay the same or even get worse. So if we're always trying to improve, it's finding that constraint that's holding us back and figuring out what would cost and what it would take to change that decision and change those constraints and removing from the business till we find the next constraint. Yeah, and I really like how you mentioned constraints. I feel like I'm going back to my process improvement or kind of engineering classes and for usually as a bottleneck or constraint that's wholly the business back, not always, but I think it's a good way to look at it as looking for those constraints. That's definitely one way to think about it. So thank you for that answer. All right. So I know you were an early adopter of Clawed. You've been spending a lot of time in Clawed. So I'm going to start with how much time do you think you've put into Clawed in the last two years? Oh, I don't want to know. But I think it's open. You're now your boyfriend. Do you spend more time with her than anyone else? Yeah, it's a replaced Excel for being nothing that's always open 24/7. It's like Clawed is just always open when I work. That's the first thing I reach for. So yeah, it's got to be eight plus hours of that. For since 2025 at this point and beginning of 2025. So it's a good chunk of my time now. And do you have a name for it? You can consider it a he, a she, and I always find that interesting how different people kind of think of Clawed. I've been just Clawed. But you know, on April 1st, they released these like buddies. They were like Pokemon buddies or something. You have like a egg that hatches. And I got one that was a cactus. So I really like that one, but now they took it away. They took it away after April 1st. So it was nice to have like my little friend down there. Now he's gone. That's funny. I didn't see that. I, uh, my April 1st was I was launching a beard brand. And a beard bomb had beard bomb beard oil and beard butter. I would buy. I'd be one of the first buyers. I've had a few people tell me that you never know. I might just launch it one day. I'll put it on the, I already have a page on the website. I just got to get the product. Yeah. Hey, have a Clawed help you. It helped me build the website and all the images. I think I use a little bit of chat. GPT. I still find and I know we're digressing for a minute, but I find when I want just a JPEG, a PNG image, I still prefer chat GPT to Clawed. Clawed's got a lot better there. I know most people prefer Gemini. But it's like how many different tools do you want to use? I pay for three. I'm like, I want to pay for a fourth. Yeah, it's tough to find the balance between like going deep into one tool or using what's best from every tool, but they just released the Clawed design and I messed around with that and that can make spread, like make a four decks. It can make websites. So it's getting better there. I think it's improving. I have not played with Clawed design. I didn't see that release. I know they just released 4.7. So I'll have to take a look at Clawed design, but yeah, it, all this keeps getting better. Sometimes it's a little scary, but it's exciting. What made you lean into Clawed? Like when were you convinced that, hey, the tool I really want to spend my time in? Was it because of work? Or how did that come about that you made the decision? I'm going to go deep in Clawed. Yeah. At first, I was definitely like you're saying switching between these tools, like using Clawed for some things, chat GPT chat for others. And then they released Clawed code. And I, you know, we're finance guys. We don't code. But I was like, I wonder what this is. And I looked into it. And I saw that the workspace was your folders. And what it did for you was create files or edit files. And that was like, that's exactly what I do. I work inside file folders. And I go in and edit Excel files and PowerPoints. So when I saw that, I kind of leaned into a Clawed. I was like, oh, they're leaning towards this worker audience. It's not chat where I'm just going and asking for a formula for like Power Query going in there. And it's doing work for me. So I leaned in then. And then they, they really convinced me they just kept policing things. Clawed in Excel, Clawed in Word, co-work. So they're all just leaning towards helping you do work better. So yeah, it's work. Helping you do work better. So Clawed code was kind of really the first one that you saw because I had that workspace and it could work on files and said, there must be something here. How can I use it? Exactly. And I just, I knew AI was like working for engineers. How can I make work for finance? Yeah, there's a lot we can learn. I interviewed a guest who said, look, engineers, developers, 18 months ahead of us, learn how they're using Clawed and copy a lot of what are whatever tool, but learn how they're using AI and copy a lot of it. Yeah, yeah, exactly that. And they're a little more blessed than us. They have really great version control, which we don't have in Excel, which I'm very jealous of using those tools. Like, dang, I wish Excel would do that. We can collaborate so easily across engineers. But it's funny. I was talking to somebody that's building a software where one of the things they're talking about is we're trying to manage the version control. You know, and they still output stuff to Excel is an interesting approach with using AI. And so I think we'll see more and more solutions to get better and better on that front. And so we'll be fascinating to watch. You know, there's there's some modern spreadsheets to do some of these things really, really well. But as I've always said, you're competing against the 100 pound gorilla and the most complete software in the world as far as spreadsheets go as Excel. And there's not a, in my mind, there's probably not a close second of all the different things it can do. Google Well, sheets can do 90% and it can do some things way better. It's probably the next closest. But they just have invested so much in the whole Microsoft ecosystem. It's a really hard disconnect. Yeah, it's been where we've worked. Like everything we do, if the software we have can't do something, we reach for Excel. So it's hard to beat that. It's a fabulous tool. I mean, I love Excel and AI hasn't changed that. I can see areas where it's changing how we work with it when we should work with it for sure. And I continue to see that. But, you know, there's a reason chat, GPT, Cloud and Copilot all have add-ins to Excel. Exactly. They know they can't compete, but they're like, how do we make this better? Make the experience better, which I'll tell you. Correct. Plus they're getting all that data, which maybe at some point they do compete with that. But for now, they recognize of having all that information and building something that works well with them is a great way to go. All right. So I know you've started your own business now. You're doing training for finance teams. Why is this so important? Why did you see that was a need in the Eiffel? Hey, I'm going to leave my steady day job to start training people. Yeah. I think it was just that aha moment I had. I want everyone in finance to feel that. And I feel like once you get there, it just doesn't stop. I have a lot of friends that use these tools now. They use coworker code every day and ask them, like, what problems do you have now that you're using this? It's basically gone away. They're like, I don't have any problems. I just go and I build my own solutions to problems. And you're not looking for software to solve these problems, though. You can just, you have kind of the whole world open to you outside of Excel now. So that's why I've been focused on the training of just, how do we get people to that aha moment as quick as possible? And just not, it is confusing the technology. There's a lot of different things where you start talking about skills and MCPs and projects. If you don't know what any of that is, it's like, I'm learning to be a software engineer or something. But once you get in and just start using it for your actual work and you can see how it starts saving you time and let's you focus on different things that you much rather spend your time doing. It's a great tool and I think more and more finance will start using this as a platform where they go and do work. Let's break down kind of the different things in a simplistic term, how you describe them. I think this is interesting. So let's start with we have Claude where I can just go to the browser and open it up. So I'll call that kind of Claude chat. Right. We have Claude code work. We have Claude code. We can download it to our desktop. We can download it to our phone. Now we have Claude design. So let's start there. What's kind of the difference? How should people be thinking about this whole ecosystem, almost this operating system, so to speak, that Claude's bill? How do you think about it? I don't reach for chat too often now just because of everything I've built for myself and the other tools. But chat, I feel like, is just the same thing we've been kind of using it forward. So questions like, I want help with a formula or I just want some quick information. That's how I've been using it. And I feel like once you get into coworker code and you start building out like your own personal operating system there, that's where you stop using the chat tools and you switch to either coworker code. They're very similar tools. I prefer code just because that's what I've been using. But coworker just has kind of the nice UI in front of it. So it looks pretty. It's like what we're used to using. And when you get into these tools, you're basically building connections to all the data sources that you already use, whether that's your ERP, a data warehouse, even your email. And then you can have coworker do the work you would normally do, whether that's analyzing data, cleaning it up, transformation. And you can build out what they call skills, which is just, they're all markdown files, which is just very much a, it's a text file that explains your workflow to Claw. If you do something a specific way every time, you turn that into a skill and then Clawed can go and do that every single time. I want to break that down a little further. So we've talked about kind of code chat, coworking chat is really where you go ask questions. If you're doing the serious work, it's doing a lot of try to do it in coworker code. But also is in coworker also designed where it will access your computer and do tasks for you. Does code do that as well? Yeah, exactly. So code can do that as well. Code actually opens in the terminal, which is fancy engineering. It's not that scary once you get used to it, it takes like a few minutes. I watched the YouTube video and how to get in there. But all it does is it opens inside one of your folders. So it can create a file, it can create Excel file for you. It could write code for you. And that happens all on your computer. So both of them are using your computer. So both of them can do that. Like it can go to a website. It could open up an application if needed in code. Just want to make it clear for the audience that you could pretty much almost anything you can do in cowork, you can do in code. The code also has kind of the whole code side of it. Code has more features that some things that haven't come to cowork yet. Code actually does a little better so with things like memory where it'll start to remember your workflows or your preferences. And it'll store that memory. So next time you go and do it, it remembers. All right. So now let's talk. So we have these three. The next thing you mentioned is skills, which you said mark down files way to think of them. The way I describe them is instructions, right? So you're giving it instructions. It really provides a purpose for good documentation because that's usually something everybody was terrible at. Now you want to document it because if you document it well, you can give that to AI. So how does someone get started with the skill? Because it feels like I got to give it all this instruction. Isn't it a lot of work to write all the documentation? Yeah, it does take some time. Once you do your first one, you'll start to understand the patterns of you're not trying to give it step by step instructions. You really trying to give it the tools it needs to go and do work that you would do yourself. So if something you're doing constantly is exporting a specific report, you can give it access to that report and tell it how to actually go and pick the right time frame or the right setting. So it brings that report back accurately. So yeah, it is like instructions, but also you're just giving it the how, how it's done and some of the why of what we're doing. And that lets it act more autonomously and get through and give you, it surprises you with once you start giving it different tools to access, it can really go and find creative solutions to problems. You didn't even know you had. Okay. So we have these skills. We have the mark down files. You give it context. You give it why. You give it some instruction, but not necessarily a step by step. Give it that freedom. How big of a difference does it make using a skill versus not using one when you're doing something in clouds? I could give it a prop, ask it to do the same thing. Are you finding it's really a key difference? Yeah, where skills really start to help is when you're doing something every day, every week or every month. And so you're not constantly re-explaining the same, the same prop. You're giving it all those contexts that it needs to do the work correctly. And you can put it inside the skill. And the skill is not always just the mark down file like we talked about. You can give it examples. You can give it assets. You can use to go and see how we did this previously and it can go and rebuild it exactly the way we did it before. So like something like management reporting. If we're always using the same format, we don't want to change the format. We don't want to change it. We give it as an asset or reference for it to go back and recreate that exactly. The model after it. Yeah, exactly. So you always get the same output. Makes a lot of sense. I'm curious. How much time do you think you're saving on average a week? Does talk kind of work wise what were you saving from cloud and then maybe also in your personal life? Yeah. No, work wise honestly, it's so hard to say because every time you cut something out, you always find something that fills it. So you start cutting some of the repetitive work that doesn't require my judgment. It's like pulling data when we're cleaning it the same way, reformatting. That can cut 5, 10 hours every month on just one process that you do every month. But something always finds the way to fill in that time gap and I'm not working any left. So it's like you start working towards things you like to do more and things that find that you find more interesting. Yeah. So it's basically allowing you to focus more on what you want versus, oh, now I work six hours a day. Yeah, it does let you focus. That's one of the things that I found really helpful is instead of switching between all these tabs, you're going between Excel and different browsers and email, I can kind of work in one workspace. And that helps me just focus on what needs to get done. and start delying another work to agents that go and work for me. Okay, got it. Next, you recently, you did, I think it was a post on LinkedIn. You shared the cloud is the way you see it. It's not really a software you deploy. You shouldn't think of it as a software, but you should think of it as someone you onboard as a new hire. Talk to that. Talk to why you think about it that way and what's the difference when you treat it like a new hire versus a software? Yeah. So when you go and use cloud, you don't have just one. You might have a different one for each workflow you do. It could be one for data analysis. And when you say one, you're saying one project, one skill, what do you mean by one? Yeah. So the way I think about agents or co-work is the folder is the agent. So I will have a different folder for different types of work. Got it. And inside that folder, I have different skills that are specifically tuned to what the work I do inside that folder. And it might have different data access inside those folders. And do you have to also load those skills into cloud? So do you just keep them in case you need to change them in the folder, but they're also loaded into cloud or how's that work? Yeah. So I use cloud code. So most of everything I have is saved locally on my computer. But inside co-work, you can save them to the co-worked app. And so now they're saved in the cloud. And so you can get them wherever you need them, which is really nice. But yeah, when we talk about like you're onboarding an agent, it's each one needs different contacts, different instructions, different data access. We talked about like skills and connectors. And they get better over time where software, he set it up, he trained people and it works the same way basically forever. There might be some updates, but it's basically the same. But with your agent, they're constantly improving. Like we already talked about there, leasing all these features every day. And constantly have to work and re-update these agents. Make sure they work correctly still. And when you're no longer managing one agent, you're managing 10. It's a completely different structure. They still need the same things a team needs, whereas like a clear scope, good data, the bright authority, and somebody to actually own these outputs. So that's why I think it's more of building this environment for a team of agents to go work in instead of just a software that you turn on one day. Got it. And I mean, so from the new higher perspective, it sounds like it's really about giving it the context and training it that's kind of a similarity. Yeah, exactly. You're teaching at your business model, the quirks about your business, why something gets done a certain way, and what you would learn when you're starting in a role. Your job is just now to teach Claude the same things that you learn when you when you onboarded and when you took on different responsibilities. So what is the low-hanging fruit that you think FPNA people shouldn't be doing anymore because of AI, whether it's Claude, ChatGPT, Copilot, what's one or two low-hanging fruit that you would say, hey, if you're doing it this way, you should be rethinking how you're doing it. Definitely around accessing data, where the way we currently access data is like, you go into your ERP and you click Export or Report, and then you go on you, you configure it, and you say I'm doing this time period, but your agent can just go and get all that data for you without going through a UI and taking all that time. It just goes and it runs a connection that gets that data right back for you. So just those things like that were, they might take five, 10 minutes, but over the course of a month, a year, it adds up to hundreds of hours, where why am I doing this work? Got it. So the first area, the lowest-hanging fruit is exporting data, the manual exporting. Yeah, just giving it access there, then a lot of the transformation we work we do is the same every month. If we're doing the same calculations, that logic doesn't change, that can go to your agent next, and you're just rebuilding your workflows, but in a way that an agent can do them. Got it. And if somebody's listening to the show and they're trying to figure out where to start, do they start with some cloud training? Do they start with trying to automate something from your opinion? Where would you recommend they start? This is somebody, let's assume they've done, they've done prompting in AI, but they haven't automated any processes. They have built an agent. They don't know what a skill is. They've heard the terms, but they haven't done anything. What should, what would you recommend is that place to start? Yeah, when I think about it for a team, like a team of analysts or finance team, I think it should start before the tool, before you even get into cloud, just making sure everybody has access, any sort of friction before actually going and getting to that aha moment I was talking about, it's just going to stop people from using it. So if they don't know what data they can use in there or what cloud can actually access, I would start there and make sure everything's explicit where everybody knows what they can and cannot do with it. That really just helps for, you know, once you go in there and you start using the tool, if you have access to everything you need and they can do the work, you can go and build the solutions your own way, whatever way you see fit. But it's really about having that the access in the beginning and just figuring out that governance layer. Where are the challenges? You know, we hear a lot about, hey, AI hallucinates, it doesn't do things the same. Whether things you need to be watching for, because I'm assuming whether you have an agent doing it, whether you're prompting throughout, you know, working with it and it's a back and forth process, there needs to be this human in the loops. How do you think about all that? What are the things people should be watching for? Because, you know, right? Just like a human, we know this can make mistakes. Yeah. So we want to have our processes be as deterministic as possible before they get to the agent. If the data can be made up by AI, then everything after that's going to be terrible. So making sure we have access to data that is deterministic and it's going to be accurate 100% of the time, that's that should be your baseline. And then now once you're going in and doing the actual work and transforming data for finance, we we will almost always need a human in the loop to go and validate those outputs. But it's giving AI a way to actually check its work and make sure it actually is accurate. Just like how we do with checks, like check sums and you're always validating all the data, you want to give agents the same tools you have to make sure we can go and check and make sure everything we did is accurate, everything ties, everything picks out. So giving agents a way to go and evaluate, evaluate their work is a really good way for you to not be fixing a lot of small problems and you're fixing more root cause problems and set a little one off. And elaborate on that is that something in the instructions is that reference sheets is that giving them access to another tool where they're supposed to check the number. What what do you mean by that? So like I built my agent, I run it and the numbers come back, let's just say quite a bit off. How do I get it to check most of it itself? Is it you know writing in your instructions, check two or three times, specifically look at these areas, giving it access to other data, what are some of those things that reduce that variability in the errors beyond, hey, I gave it a skill, I gave it the data, I gave it an example. With like say we go and we have a build excel report for us. So just having it build in the same checks we would use, you know, where we can go and make sure all the data ties out to the different source data and giving them the checks we can we can do at the skill level where we're giving it the checks that we would normally do when we go and look over and review our work and telling it, hey, go through and make sure you you validate these three things. Or there's also the option of having more of a review agent where there's another agent that reviews work specifically. And so you have one agent that does work, another one that reviews it all before it comes to you. So let's walk through an example. We talked about let's take reporting. You mentioned we need to reduce frictions, you know, making sure you have access to everything, you understand the tools. And then you also talk about, hey, you're going to need to write the skill. But I would imagine another key area here is process. You need to be able to document outlying what that process should work like. So let's walk through kind of how all of that looks. So we're going to automate our monthly P&L reporting as an example. Kind of the process and all that. Walk me through that. Yeah. So the first thing I would do is figure out what your actual process is. Because we know the process we go through every month and do. But it's a lot different when you start and try trying to explain this to an agent, you know, build a skill. will build the tools that can go and do this for us. So I'll definitely go and use one of these dictation tools where you can use voice and just go and talk to Cloud for a minute and explain your process. Tell us what the inputs are, what transformations you do, and then what the outputs are, and what they should look like. And that really gives us a good starting point to go and start building these automations. And then once you have that mapped out, you can kind of see where biggest bottlenecks are, what takes you the most time. Sometimes it could be really easy to go and pull the data yourself. It might take you a minute. But what really takes a lot of time is the formatting and getting everything into PowerPoint decks. And so that might be the process you want to start with first. And so building out the skills that your agent would need, everything they would need to do, to do it the same way you would do. And we can create that as a skill, give it our processes, give it access to the data sources it needs. And it can go and do the transformations for us, if we need. Or it can go and do the formatting and building out the reports. Got it. No, that's helpful. Thank you. What's the coolest thing to talk more personal life? You've built with Cloud Code. Something you've vived coded. Oh, something I've vived coded. Or just a problem, as you've done. My last guy, I'll give example. He goes, the only area my wife and I ever argue over is what mill we're going to do. So they use Cloud. He goes, I never want to do a mill plan again in my life. And it built an app that helps them do all their mill planning. He used an open source, and he built it all. And so I mean, it could be totally different. But that's an example of kind of a fun one I had. He's like, now we just use the tool to figure out what our mill plan is based on what we have, what's easy to get, what will be healthy, and a way we go. Yeah. Now, I did that where I vived coded a Apple app, actually, on my phone, where I like to track, if I have any habits I like to do, like working out every day, or eating good foods, and not sticking to my habits. So I had it vived coded and app for me that was-- like I kind of tried to gamify it where it was every time-- every time I did my habit, I'd log in on the app, and it would like level me up by starting to get experience. And my little guy started getting like higher levels. He was getting better. No, didn't get buffer, as he went, like stronger. Yeah, so that was one that I did. And I've never used-- I forget what the software is. But it used the software for me inside to create an Apple app. And I've never done anything like that. So that was really awesome. I'm able to do that, and that's on my phone. That's cool. Yeah. I'm hearing just amazing stories of what people are doing. If you didn't see it, you'd think we live in a sci-fi world, sometimes, with the stuff people are able to do. All right. So I want to ask this, what's FPNA going to look like in five years? Yeah. It's so hard to even know it two years. And I know we're guessing. I mean, if you're right, I'm coming back to you and we're going to Vegas. Yeah, exactly. The way I see it is everybody's going to be managing a team of their own agents. So everybody's going to move up a level. If we're the analysts, now are the analysts that manages 10 other agents that did the work we used to do. So when you're talking about how are you going to train the next generation, it's going to be really tough when agents are going to handle a lot of the work we do today. It's really going to change just the way a lot of businesses operate. If you've already seen, there was somebody that had a billion dollar business, and it was just him and his brother, and they ran the whole business using AI agents. So the way FPNA is going to change, I think we're going to be embedded into a lot of different processes, helping make decisions across the business, where agents are going to handle a lot of the standard reporting we do, building forecasts, and we'll be off trying to help the business. Got it. All right. If you had to go back before Gen AI, what's the one thing you just couldn't do anymore? You couldn't go back to the way it was before? It's really just the work that I already hated doing. When you're doing the same thing every single month, for years, nothing changes about it. It's you do the same exact process. I would never want to go back to that. I didn't know how to automate some of this work, and I was just doing the same thing every month. Fair enough. So it's really the stoorpetitive tasks. You just couldn't do that again. Yeah, exactly. The things where I wasn't adding any value. I was just doing the same thing every single time. That's my career. I don't know if I ever added value, not. Yeah, you did. I didn't hit that. I think everybody learned so much from this. Just being able to hear other people's experiences, and it gives them ideas on what they can go and do. That's one of the reasons I'm so excited about doing the AI series. There'll be a few other episodes intermixed, but you're the fourth person I've done a heavy, hey, how are you using AI? To walk me through things, let's talk about examples, and I'm learning a lot. I'm already thinking I need to do this, and I need to do that, and it's exciting. So I'm hoping others get the same out of it in their day to day work. I really think spending the 10 hours, let's say I do 10 episodes, probably even five hours, listen to that double speed, you'll get some great ideas. But the key is, as you know, you have to do. Orson watching YouTube, you can do that all you want, but you just have to jump in. That's the thing I'm realizing more and more. And I've started to build a couple skills. I started play with it a little bit, I know I just need to jump in more. It's just as simple as that. Once you dive in, there's no going back. And I'm starting to realize that more and more as I, like, I'll give an example. I'm building a deck, I'm doing a keynote speech for an event, and I've probably spent three, four hours in PowerPoint. Okay, I've got this section done. Here's what I'm trying to accomplish. Give me ideas, tell me how I'm thinking about, well, and sometimes I'll have it redo the slide. I may still edit, I'll edit them after, and I know I always like the looking fill, and everything isn't quite like I want. But it's incredible how much I can use it as a thought partner, ignoring the agents, ignoring the automation, just the thought partner part to augment what you're doing. Is incredible. Then you add all the efficiency gains if you go, which is where I need to go, that next step, and how do I automate my workflows? Like, we have a CFO on who said, "I look at AAs, my thought leaders." Kind of a lonely position. There's not many people I can go have certain discussions within the company, but I can go use AAs, my thought partner. And so it's just so versatile. You know, kind of like you could do anything in Excel. There's a Stremler with AI. It's kind of that new world. If there's the tool that is gonna be as ubiquitous, right? It's Gen AI, whether it's Claude or ChatGPT or Copilot, we'll see which one it is. Everybody has opinions, I have mine. But I think you're kind of looking at that. Like, you know, the modern day, and it more powerful, it costs more areas, but kind of spreadsheet in some ways. Now, if that makes sense, but that's kind of a little bit of how I think of it. - No, yeah, the options are unlimited. You can go build whatever you wanna build now. You're not forced into what somebody else wants to build for you and fitting cleanly into what they built. Pretty wild. - Yeah. - Yeah, customize as you want it to be. - Yeah, I have so many things. I need a three months off to just be a AI person. Anyway, all right. What's the number one technical skill that FPNA professionals should master today? - I don't think it's excel anymore, but I think it's understanding what Excel does for you. Like, the operations underneath. Like, what happens when you do a lookup or when it creates a pivot table? Because, yeah, I can do so much for you now, where if you can direct it at the most base level of what it's doing, or cutting out these UIs, we're not going in and, you know, going through our ERP's nice screen and clicking download PNL for JDWary. AI can do that for us, and it can do all the transformations that we want it to do, as long as we understand what it actually needs to do. Not how to do it in Excel, but how do you do it at the most base level? - Got it. - All right, what's the number one soft skill we should master? I think clear writing. Because, and Grona, yeah, you were here in Arizona. Our schools, they teach us how to write these long essays. You're always trying to hit some character limit and, you know, get past a certain amount of words. You're stuffing it with unnecessary words, and then you get into finance and nobody cares. They know how to use all these nice words. They just want to know what decision do I need to make? How do I make it? It just be clear, be simple. - And size communication, written, verbal, whatever it might be. - Yeah, I really wish schools would focus on that that side of writing more, because I feel like you don't get that. - All right. I know you've used Excel a lot. What Excel mistake taught you the most in your career? - Trying to make the most, the crazy nested lookups, index matches that have all these dependencies, that you never know when something breaks. I would try and fit everything into one formula just because I could. And then I realized like, I don't even know what's going on in here. And when something, when you send something out, that's just completely off because of a formula, you feel so stupid. And you're just like, why did I do it this way? Break it out cleanly, show all the steps. I had a guest once who said, open your model a week after you built it. If you don't understand the formulas, it's too complicated. Right. And I've opened files. I'm like, what was I doing here? And you have to pick it apart. That's a sign that you did a poor job. And we all do it because at the end of the day, design, design design is critical to Excel. Yeah. That's why I love Power Query so much where you could, you really just listed out all your steps. And now going to using I so much where, doesn't really work well with Power Query. You're your back to the basics. So that's what I've been trying to relearn. Yeah, they'll figure out how to make it easy. Bring AI into the Power Query interface at some point or they'll figure some other solution. But crazy world. All right. This is the Get to Know You section as we wrap up. If I asked you where you would go, if you could go anywhere in the world tomorrow for vacation to go see a place you haven't been or maybe even somewhere you've been, where are you going? I'm going to Japan. Why? I think the food is amazing. Everything I've had over here at least, that's Japanese. I think their country is beautiful. The culture is just amazing. They always, they should get so obsessed with different things. And I love how obsessed they are about mastering one thing. And if you ever read Shudog from Phil Knight, who was the, of course. Yeah, yeah, yeah. But yeah, from Phil Knight, he's the founder of Nike. He just had this like life changing experience when he went to Japan. So going in October. Awesome. Well, let me know how it goes. Excited for you. All right. You get to spend one day, one day only with any person in the world so somebody alive, who you have spent in the day with and obviously outside of me, of course. All right. All right. Now I got to think about it. My first option's gone. Yeah. Whatever. If I can do two, a little combo, my wife and son, I already spend every day with them, but smart answer. If you listen, she'll like it. And I know it's legit. I get it. But no, I really is legit. They just, they're, they're why I do everything. So just another day with them, I'll take it. I'll take every day I can with them. Love it. All right. If someone wants to learn more about the services you offer, this is your, uh, time to kind of plug what you're doing as far as services share a little bit about that and how they can contact you. Yeah. So LinkedIn's probably the best way to reach out to me. David Dors. I share a bunch of information on cloud, how to set it up for your finance team. Post a lot of workshops where we go in and we, we build with cloud co-work or cloud code. And then I have a lot of longer, like how two articles on how to get this set up. So if you're, you're building anything cool with cloud or in finance, just message me on LinkedIn. And I want to know what you're building. All right. Awesome. Well, thank you so much for joining me, David. Appreciate it. I hope you enjoy the rest of your day and excited for the audience to get to listen to this. So thank you for coming on the show. Thanks, Paul. It was, it was great to be here. And it was great conversation about where we're going with finance. Yeah. It's an exciting time. So I'll, I'll leave with this party words. If you're not using AI, just get on the boat. Even if it's simple, I can't say by any means I'm an expert. I'm behind a lot of people, but I'm continuing to jump in and that's all you can do. Just got to get on there and start using it. Alrighty. Well, that's a wrap. Thank you, everyone. That's it for today's episode of F P and A Unlocked. If you enjoy F P and A Unlocked, please take a moment to leave a five star rating and review. It's the best way to support the F P and A guy and help more F P and A professionals discover the show. Remember, you can earn CPE credit for this episode by visiting earmark CPE dot com, downloading the app and completing the quiz. If you need continuing education credits for the F PAC certification, complete the quiz and reach out to me directly. Thanks for listening. I'm Paul Barnhurst, the F P and A guy. And I'll see you next time.