Excel vs FP&A Software: When to Make the Switch (with Paul Barnhurst)

[00:00:00] Welcome to the Diary of a CFO Podcast. I'm your host, Wassia Kamon, and each week we explore how today's finance top leaders build high-performing teams, partner with CEOs and boards, and lead through growth and transformation without burning out in the process. Today, I'm super delighted to have with me Paul Barnhurst, aka the FP&A Guy. Paul is a leading voice in financial planning and analysis. He has delivered corporate training and virtual courses to thousands of finance professionals covering FP&A best practices, storytelling,

[00:00:30] business partnering in Excel, and data visualization. He also owns the FP&A Unlocked Podcast, co-host Financial Modeler's Corner, and Future Finance. He has built an audience over 112,000 followers on LinkedIn. He is known for his clear independent reviews of FP&A software and for helping finance team make smarter choices about the tools they use. Welcome to the show, Paul. Thank you. And after that bio that you wrote, can I just hire you to be my marketing person?

[00:01:00] Absolutely. I accept all forms of payment. Oh, I didn't say anything about payment. Uh-oh. All right. Let's dive in. So you are an Excel MVP, and you also review a lot of FP&A platforms. So where should Excel remain the hero? And where does it become a liability when you think about it within an FP&A function?

[00:01:19] Yeah. So I mean, the reality, whether it's Excel, Google Sheets, whatever, the fundamental spreadsheet is not going away. I don't see it going away anytime soon. Even if Excel went away tomorrow, we would still use a spreadsheet. So the way I think about it is there comes a point when the need for a database, for privacy, for integration, for your model, for, you know, greater calculation speed, many of those things becomes imperative.

[00:01:45] They outweigh the flexibility. Because the reality is a spreadsheet, Excel, Google Sheets, whatever, all these new ones coming out, is always going to be more flexible than an FP&A tool.

[00:01:55] Just by the nature of unstructured data, structured data. It's much easier to be more flexible. But for that flexibility, you give up auditability at the level you would get with a true tool, the database level at a row permission, you know, collaboration, the scalability, you know, the calculation engine, some of the multidimensional modeling.

[00:02:18] Yes, some of that can be done in Excel. Almost everything can be done in Excel or with the Microsoft tech stack on your own. It's a question of, do you really want to invest all that time and have to keep those people? So I think what you have to look at is when the pain starts to become big, where you start to see errors, you have problems consolidating everything, you have privacy issues. As those start to grow, you have real issues with bringing in all your data.

[00:02:43] It's time to look at something else. That doesn't mean you throw out the spreadsheet. You may select a tool that very well integrates really well with the spreadsheet. You may select a tool that doesn't, but you're still going to use the spreadsheet. There's always going to be those edge cases. You're doing M&A and you're not going to put all their data in your planning tool and build a model for it to decide if you're going to buy the company. Yes. At least I don't think anyone is. Maybe there's a tool out there doing it with, but not yet.

[00:03:10] So that's, that's kind of how I think about it is when you're big enough and complex enough that there's that real pain to where things are going wrong. It's taking too long. And I think everybody knows we've all seen them. There's plenty I can list. That's when it's time to look and say, what more could I add? And that could be as simple now as an Excel agent with some of the things they're building there that are in many ways, the light planning tool, all the way up to a big, huge enterprise tool, depending on your company.

[00:03:38] Wow. Thank you so much for sharing. And I'm also curious, like a lot of teams are stuck in Excel because they're overwhelmed by the FP&A software options. I remember when I started in FP&A, there's only like a couple tools, but now it feels like there's a new tool every month. And so how should a finance leader logically choose an FP&A tool for their team, especially when they're moving from Excel to that first FP&A tool? Call me. Nice.

[00:04:05] On a serious note, I think there's a few things. I look at it as there's really three phases to this process. There's the narrowing down the tools you want to look at, and that's the research part. Talk to other people. Check out the market maps I've done. I have even a course that's free that you can go take on FP&A software selection. And so I think first is figuring out the market because the reality is people know of tools, but rarely do they really know,

[00:04:31] hey, are these good mid-market or are these good enterprise or are these good small businesses? Is one good in a certain industry? What type of tools? And so, you know, someone, I can take some questions and narrow down their list to 510 tools quite easily. Okay. So that's the first step is kind of, you know, narrowing it down. And then it's really going through a selection process. I encourage people as much as we all hate it, do a proper RFP. You'll thank yourself in the end. It doesn't mean you have to be super strict. I started my career in contracts, so that's where that comes from.

[00:05:01] I wrote RFPs for the government before I went back to grad school and got into FP&A. And I think there's a lot of value in going through that rigorous process because it forces you to compare the tools against your requirements, not against each other or against the whiz bang features they have. Nice. And then the third thing, which is more important than your tool you select, is do you have the right implementation partner? Have you done the work on your data? Do you clearly know what your requirements are? And can you implement it correctly?

[00:05:29] Because these tools aren't all that different. I mean, how many ways can you plan? At the end of the day, there's 12 months in a year. You know, there's 52 weeks. We all, with few exceptions, have revenue. We all have some income stream. We all have a cost of goods sold. We all have operating expenses. And then we have CapEx. Right? You know, it's not that different. Yes, there's a lot of intricacies in between that. But as much as the planning tools all want you to believe they're unique, and there are better ones than others.

[00:05:59] Mm-hmm. They're pretty similar. Okay. And so it's in the implementation part that I think we often get in trouble, right? Because we either ask someone, like people on our team, and I've seen it, to work on it in their spare time, right? Who has spare time? And then if you didn't do, like you said, the right research on an implementation partner, that's another problem as well. Yeah. And so I'll share an example. I was asked to select a new FP&A tool for us, and the project kind of changed that for time.

[00:06:28] And it came where, hey, how about you implement? We're going to implement a U.S. version. We'd had TM1 was the tool. Mm-hmm. And I went through and wrote all the initial requirements. But at the time, that was about 80% of my job. I'd come in new to a company. They're still trying to figure out where I'd fit. Things had changed a little bit later. And I spent a bunch of time with all the businesses, gathered all the requirements. And I still remember one of the vendors' implementation partners going, this is probably the most detailed requirements we've ever seen this early. Nice.

[00:06:56] And that's what you need is not you need everything documented, but you really need to think through it. And you need time to do that. I had the time. It had been three months later when I had the new jobs they'd given me. I wouldn't have had the time. It would have been nowhere near that good. Mm-hmm. And so without the time, you just really can't do it right. And so if you're going to invest $60,000 a year and $100,000 in implementation, invest half of somebody's time. Or hire another person if you have to.

[00:07:25] Because the savings will pay for themselves. Nobody wants to hear that. I get it. Or implement AI and find some savings. Whatever it might be. But don't skimp on the person's time because they're your expert. Yes. And it makes buy-in at the end also easier when you had someone championing the solution throughout. And good chance you'll burn out the person if you give them 100% of their regular job plus that. Yes. Yes. Very true.

[00:07:51] So what are some of the red flags that you've seen in FP&A software demos that buyers should watch for? I think, one, if they're always kind of telling you they're unique. Two, especially the further you get. That first demo, not so much. But what I always recommend is you should do some kind of proof of concept. Once you've narrowed it down to a few tools, you're really into that process. If it's clear they don't know your business, they're not paying attention, they're just selling you something standard. Or you're worried about implementation partner, that's an area where I'd consider running.

[00:08:20] And I saw that with a, I helped a company through the process. And when we started, I expected one tool to win. And we got in the meetings. It was clear one of them had done their homework and understood the business better. And the other was just trying to sell something standard and wasn't listening. So that's, that's the first proof of concept. In the first demo, the big thing watch for one promises, hey, this is on the roadmap.

[00:08:42] If you keep hearing it's on the roadmap, unless you're, you're also really immature and you're confident in the company, probably a good idea to run. You know, or because the reality, if you pick any tool with only a few years, you're going to have to deal with some roadmap. Because it takes a long time to get there. So, you know, just keep that in mind. Don't, don't buy into just promises. So if a lot of promises, that's an area where I'd be concerned. And then if it's a lot of whiz bang or we have this and nobody else does.

[00:09:12] Those types of things always make me nervous when I'm like, I've seen so many tools people like, nobody else is doing this. There's nobody in the space. And what are you talking about? I'm not quite that direct. I want to be sometimes like, you want me to give, and I said to one of them, give you a list of like 10 or 15 tools. No, no, none of them are the same as us. Okay. Like, I'm not going to argue it with you, but you're wrong. And I never heard anything from that tool after that phone call. So they obviously didn't scale too far. And so those are a few things. What about you? What do you think there? What's your thoughts?

[00:09:40] For me, like you said, when it comes to demos, I like to see that a company did their homework. Because I work right now in a not-for-profit space. So not-for-profit, I don't, I'm not like a food bank to have like inventory. I'm closer to a bank, but I also getting grants. So my financials are quite complicated because I have to follow the financial institution audit, but also the not-for-profit governance.

[00:10:09] And so I was shopping for FP&A software last year. And so, yes, the one that I eventually narrowed down were the one that could show me how did they put the financials of a not-for-profit in their system. What is grand tracking going to look like? Because you show me cost of goods, what I'm like, it doesn't fit my business model. Yeah, they're showing you a manufacturing example and you're like, what? And that leads to one other thing, I couldn't usually mention that, that just came to mind a little different.

[00:10:39] But make sure your implementation partner knows FP&A and ideally has some experience in your industry. How do you surface that? Because, you know, oftentimes the people that are doing your demo and other people that are actually going to implement, like you're dealing with the sales team and then the implementation is like... The smaller you are, the more likely they're doing the implementation. The larger they are, the more options you have for implementation. I mean, vendors may have their preferred implementer, but less control they have over who you choose.

[00:11:05] So I think a couple of things, ask for resumes of the implementer, ask for references, say, look, I want someone that has this experience I have. I don't think this makes sense. Or let me interview them. If I'm not comfortable, I'm not signing the deal until I'm comfortable. So if it's one where they're doing it in-house, would ask. What's the worst they say? No. And then you're like, well, that's a red flag. Maybe I'll go elsewhere. Yes. Because then they're not transparent for sure. Right.

[00:11:31] And then if they're one that uses a hundred implementation partners and that's a pretty big name tool, then go talk to other people that have implemented it. You know, do a little bit of your networking versus just trusting the company. Yes. I mean, networking has worked really well for me because I'm part of the CFO leadership council. And I just put in, I'm looking at these two solutions. What would you have? And I had like 20 CFOs coming back. Nope, nope, no. Stay away. Yes. Yes. So it definitely helps a lot trying to narrow the right solution. Yeah.

[00:12:00] They're a great organization. I'm big fans of them. I'm getting ready to interview their head, Jack McCullough Monday.

[00:12:35] Oh, yeah. I think it's going to be useful. I think it's seeing more and more of that. Anomaly detection. Machine learning AI is already very valuable. And you can combine that with Gen AI to help you learn some of that, to build better forecasts, to bring in external data. I think where AI is most rapidly improving with Claude coming out for us is modeling. What it can do in Excel now compared to what it could do three, four, five, six months ago is night and day.

[00:13:04] I got an episode coming up Tuesday where we tested Claude and we were extremely impressed. It did some very complex stuff extremely well. Wow. And then I think the hype is in this idea that you can almost fix it and forget it. It's the promise of, oh, it can do all. It's going to save you hundreds of hours and it can do everything. I don't know many people that are working 20 hours because they have AI. We're still pretty much all working 40 hours.

[00:13:33] As Inch Noor said on my podcast, he goes, I guarantee you the lights are not going off at five at the investment banking houses because they're all using AI. It just means they're all doing more work than they were doing before because they can get more done now. And so I don't know if that makes sense, but I think that's the hype. This whole idea of, oh, it will just do everything. And the second one is you don't need to review it. You can just trust it. No, it's still human led.

[00:13:59] If it's deterministic, just like if I automate a process with Power Query, Power Automate, machine learning, and I've run it a few times. Okay, fine. I can trust that. I don't take my Excel formula every month to make sure it's still working the same, but it's never going to return me a different answer unless I change the inputs. That's not true with generative AI. Gosh. Can you tell us a bit more about one?

[00:14:21] I'm curious to hear about your Claude experiment, but then also the difference between deterministic and probabilistic, like those two different models and how they come together. Yeah. So let's start there. So something that's deterministic always has the exact same answer in the end, right? Two plus two is always four. If I do a sum is formula and I give it my sum range and my criteria, my criteria ranges, I do all that.

[00:14:47] It's going to return the same answer every time unless the inputs change. If I add more rows to it, I change a number, it will change. I use generative AI. Gen AI's whole idea is the more stuff we can train it on, the more likely it will be right. The more we can fine tune the model. There is no guarantee anytime it's going to output the right answer.

[00:15:12] Where a deterministic, I know if I put two plus two in, I'm getting four every single time. And so the probabilistic is it's using probabilities to give you what it thinks it wants. That's actually one of the biggest weaknesses of Excel agents. I ask it to build the exact same model two minutes later and 40% of the formulas could be different than it uses to solve it the next time. I've run that test multiple times. Opus 4.6 was almost the same.

[00:15:41] It was probably 80% similar, but this is only a model that needed five different types of formulas. When I ran it before that, I'd get completely different results in almost every formula and how they solve them. And that's because they're taking probabilities to get to the solution. And then give me the second part of it again, because I forgot the other part of the question. Sure. Claude, tell us more about your experiment with Claude and how he's helping with modeling. Yeah.

[00:16:09] So what we've done is we have this Mod Squad series. You can find it on YouTube. It has its own playlist with Inch Knorr, who's the executive director of the Financial Modeling Institute, which does credentialing for modeling. He's a world-class trainer. And Giles Mel, who runs a modeling house. So the three of us have been testing all the tools. We've tested eight or nine tools now. Now we've done 12 episodes and we tested Claude about a week and a half ago.

[00:16:36] And we gave it an AFM case, one of his cases that you do in four hours with instruction. And it was 80, 90% of the way there in 10 minutes. I mean, it was really good. It picked up on a lot of things. We gave it a CFM case, which is the harder case. And it was probably 90, maybe even a little higher. It was a debt structure, layered debt structuring model that you had to build, just that section, just the debt section. And it did very, very well.

[00:17:02] Like, it's at the point now where I would trust it to build something with my inputs, with my review, with proper checking. Where before, I might use it on little sections and a ton of prompting. Now we're starting to get to that point where people are going to use it to build a model regardless. They were before. But I mean, good modelers that know what they're doing are going to be much more comfortable having a build sections and parts and models. Yeah, and you can see your formulas and you can trace them.

[00:17:32] Because that was always my biggest thing. Like when AI came in, I would test to see how it does with modeling. I'm like, I need to trace my formulas. I need to know. I don't want to see a hard-coded number. I need to know where it's coming from. And you still get the occasional hard code. So that is an issue. But getting much better, you still get more complex formulas than you would write in many situations. And that's why anyone that's an expert in this space is saying, look, AI is a magnifier. You've got to know the fundamentals.

[00:18:01] And that's true in data viz. It's true in financial modeling. It's true in most places. The people who are going to get the most out of it have taken the time to learn what they're doing. True. And so if a finance team has zero AI right now, what would you say is one low risk but high ROI place to start? If they have zero AI, let's just say, I'll start with the simplest. They haven't used it yet in professional. Get an LLM and start experimenting. Get comfortable with it.

[00:18:31] I think 90% of people have at least done that, either professionally or personally. Hopefully, they have. So I think the next two areas is, one, use AI to document a process. And then try either with some of these tools out there, Cloud Cowork and N8N, Zapp here, depending on how deterministic versus depending on the task and what you need. Try automating it. Try building out with the help of Gen AI that process. I think that's a great area.

[00:18:59] Pick something that's really manual and think about why it's manual. And I always like to use, you know, the framework is make a list of your pain points. Look at the highest ones. Say how much could AI help on these. And then try some. Now, for that first task, maybe pick something that's low time, fairly simple to get your hands wet or, you know, hands dirty, so to speak. So that'd probably be that.

[00:19:22] The third one, I would say, if not that, I think everybody should at least install and be testing a spreadsheet agent. Not saying turn your five-year financial model over to it and let it build it, but start using it. Have it audit some of your files. When you got to do a next investment, have it maybe build. And you can still build on your own or, you know, review it. But don't just do it all on your own. Start using it to assist you, writing formulas, whatever it may be.

[00:19:50] And where do we start with those Excel agents? Because some people, till this day, when I speak with a lot of people, all they know about AI is ChatGPT. They don't even know about fraud. There's about 30 tools out there. I just did a post today on MarketMap. If you're in Google, you know, check out what Google has. There's a few other tools. If you're Excel, I think there's a couple places to go right now. You can do the co-pilot route. And it's good.

[00:20:17] I wouldn't say it's the best in the market, but it's good. Claude right now is one of the best I've seen. Opus 4.6 is the best model they use. So those are your first two options. Probably your cheapest and the ones that will make the most sense for most companies. Because almost everybody has Microsoft Office. And if you don't have Office, you know, many people have Claude or can get Claude within the company so you can use it in Excel. If not one of those, then you got to look at a third-party add-in. And there it's deciding what you really want. It's a little more of a process.

[00:20:47] But again, it's nothing like an FP&A. You don't need to do a formal RFP, an FP&A tool. I mean, we're talking their prices are anywhere from 10 to I think the highest I've seen is $500 a month for a user. But most for small companies, you know, are going to be somewhere in the $20 to $50 a month range. Not a big investment. Okay. Okay. So I remember when we spoke about AI in finance, you gave a very nice framework on how people should use AI first.

[00:21:17] Do you mind sharing it again? It was like a quadrant thing. Yeah, I'm trying to remember what my quadrant was now that I shared. So I know there's the pain point of how you select something. But I think beyond that, you know, something you have to think about is, one, is this a task I'm going to repeat? Because if it's a repeatable task, Gen AI is probably not the right place. You're going to need something deterministic in the sense of it's repeatable. I need the exact same answer every time.

[00:21:45] Then it's look and say, hey, should I automate this with Power Query or Power Automate? So I think first you need to understand, is this the one-off? Is this a repeat task? And then is, what's the level of variability? What's the level of tolerability? So can I have it vary every time? Like variance commentary. I doubt you look to say last month, well, you used a different word here with the same variance. Yeah. Nobody cares. And if they do, they have too much time on their hands. Right? And so you have to understand that. What's the toleration for error?

[00:22:15] And that will help you decide, is this somewhere AI makes sense? Then it's a matter of understanding, okay, is it Gen AI that makes mistakes? Is it machine learning? Is it just general automation? That's kind of the framework and how I really think about it is, you know, kind of asking yourself those questions, then deciding where to tackle first is that whole framework of where's the biggest pain point? Where is AI the best? That's the ideal quadrant.

[00:22:41] You know, if it's a low pain point and low AI is not good, that's human. All right. If it's a high pain point and AI is not good, that's a wait or look to non-AI. Because even if it's a high pain point, if you can automate it, great. You may be able to do it with non-AI. And then that last one is, all right, well, if it's a low pain point and AI is good at it, I'll put that toward the end.

[00:23:05] Or I'll use that to experiment on because it's easy if they make it, if it messes it up because I know it's a low pain point anyway. Yes. Yes. Thank you so much for sharing. And I'm also curious, as we are embedding, like you said, kind of a roadmap, I looked at my high pain point, I look where AI can really help. And I, you know, and I have this whole plan of how I'm going to implement and embed AI in my workflows.

[00:23:32] So what do you think an FP&A team will look like if AI is fully embedded into the workflows and processes? It's a good question. I'm still, to a certain extent, trying to figure it out a little bit. I think one, you see tools, you know, there's Confluence, Payload, I think is others and others are these AI analysts are coming out a lot more. So I think what you'll see in every tool, every team is I have some kind of AI analyst. That thing can work 24 seven.

[00:23:59] And then within any large FP&A team, you're going to have an AI kind of architect specialist that can help with agent stuff. Because no matter what, every company wants to make it simple and do that. There's going to come a day where nobody's going to outsource all their agentic AI to have someone else build that, that workflow or that agent. They're going to start doing that in-house. Just like nobody has all their modeling outsourced. Right? You build some of that.

[00:24:28] So I think there will be an AI architect that will help bridge that gap. Kind of like you've seen in the last 10, 15 years, 20 years, many more finance and sometimes FP&A transformation people or kind of systems people. I think you'll see the equivalent of an architect. I think structures, especially bigger companies will become a little more flat. You won't need as many analysts. Now that's not to say other jobs won't come about because you'll have the AI architect.

[00:24:54] You may even have an AI implementation person, depending on the size. Someone who trains. They may be company-wide. They may be FP&A or finance, the whole office specific. But those are some of my thoughts right now. And I think you'll continue to see more and more of the collaborator style in FP&A. And I'll give an example of that. My last job before I started my own business, my job title was director of finance, operations

[00:25:23] and data analysis. Something like that. I didn't manage a single person. I didn't even actually build the budget. Funny enough. I coordinated between FP&A, operations and our data analytics team on what all our reporting was going to look like and how we were going to make the transition to a SaaS business with leadership. And so as much more of a coordination and collaboration role where they're looking for experience because you're managing and having conversations.

[00:25:52] Okay, let's clarify what bookings means across the company. And so I think you'll see more and more of that collaboration and strategic, not just tactical, but a lot of strategic collaboration. I think that will become a more prominent role even more than it is today. Okay. And as you're training corporate teams and, you know, the curriculum is probably changing. Maybe you're seeing CFOs already asking you to emphasize more things than others. Like what have you seen lately?

[00:26:21] So, you know, I'd say over the last few years and starting to see more and more of AI training, but soft skills and Excel. Those are the two biggest that I see quite a bit on the soft skills side. You know, a lot of storytelling sometimes around managing time or conflict. But I say storytelling and influencing. So many are like, I need my FP&A to be a better business partner. I need them to be curious.

[00:26:51] I need them to understand operations. I can't tell you how many times I get people saying some combination of what's most important for FP&A is, you know, as far as being a better business partner is understanding operations, being curious. I've had many people say the most important soft skill is empathy. Now, those aren't the things you think of when you think of your FP&A person. When you're hiring, you don't think, I wonder if they have a lot of empathy. I never did. I'll admit it. And I never once thought, hmm, I wonder what their empathy is like.

[00:27:20] And so, yeah, that's an area that I think FP&A is what they're wanting to see more and more of. And then recently, obviously, the one everybody's asking about is AI and not getting left behind and how can I use it? And I just trained a large makeup company recently and cosmetics. There's staff about 40 people on co-pilot. And so when you think about how CFOs will need to reskill their team to thrive in this environment, because like you said, soft skills, it's kind of hard to teach.

[00:27:49] So I'm curious to get maybe a one-on-one business partnering from the FP&A guy right now. Yeah. So, I mean, definitely there are aspects that are hard to teach. For me, if I'm telling someone to be a better business partner, the things they can easily control and where they can start. One, you can learn the business regardless of how good your communication skills are, regardless of all your other soft skills. You can go out and ask for those meetings. You can really come to understand the operations.

[00:28:18] Two, you can learn to be humbly curious. And when I say humble curiosity, the reason I use that term, it was someone, it was coined by a guest I interviewed, is because we all have the person who's curious just because they want to prove you wrong, or they're curious because they want to be right or look smart. You need to be curious because you deeply want to understand your business and your business partner. I think those are things everybody can easily work on.

[00:28:45] Three, which will tremendously help your soft skills, is learn to be good at data storytelling, but also data visualization. And data visualization, there's a lot of science to that. By learning what a good visual is like, you can go a long way on the technical. That allows you to then tell a better story, which is going to eventually allow you to be a better influencer. So sometimes you can start with those easier things that really are about effort,

[00:29:13] then work on fine tuning with your bosses. And hey, where are my biggest weaknesses? And really tackle those. Okay, your boss is like, well, you're really bad at pushing back. Okay, what's the plan to do that? Or I'll give a personal example. I was way too detail oriented. I literally had a director who wasn't my director, but he kind of was because the other team was all elsewhere. And so we talked quite a bit. He told me, he goes, look, every time you get too detailed, I'm going to tell you. And he would just IM me in a meeting. And he's like, bring it back up. You've lost everybody.

[00:29:43] And that really helped a lot. And then I had a general manager that looked at me one time. He said, Paul, I'm going to teach you the bluff principle. I'm like, I don't play cards. What are you talking about? And he goes, bottom line up front. It's like, just get to the point in your messages. Then you can add whatever you want to the bottom line. Because I was trying to give the entire background in all of them. And so it stalled my career for a while. And so that's something that I would recommend. Okay. Thank you. And I'm curious about, you know, now that you are training more and more teams,

[00:30:13] what do you hear from the professionals that you are training? Not so much the companies, but the actual FPN analysts and managers. What are some of their concerns or worries right now? Or what do they want to learn more about? You know, they're all interested about AI right now. Okay. A lot of them are, they often have a certain situation. Or what do you do with a difficult partner? That often comes up a lot or having conversations like, well, what if the business is not listening? Or how do I manage that?

[00:30:41] And so we'll often try to walk through different situations. But I think right now the overarching for most of them is really trying to figure out what the impact AI is going to have. Okay. Because everybody's afraid of change. And the pace of change in the last, what, six years since COVID has been unbelievable. I think almost everybody, whether they say it verbally or not, is just the constant changes on a lot of people's minds. And it creates anxiety. Even though I think in the end, it will be a good thing.

[00:31:11] I think on the whole, we could benefit in society. There will definitely be impact. Yes. There will be for sure. So what is the best career advice you ever received or usually give to FP&A professionals? I think the best advice wasn't advice. It was watching how much my dad was willing to serve and work. And so seeing that is something I've taken into my own life. I'm a big believer in the best way to help others is to serve others.

[00:31:40] And I had to learn not everybody shares that. Sometimes you have to take different approaches in leadership, but I think being willing to work hard and serve. And then the advice I give people, usually they're people wanting to break into FP&A. And so I break it out different depending on where they're at. But one of the biggest things is to say, look, if you want to be good at FP&A, one of the biggest advice that I always give is learn the business. You're trying to get into FP&A, create that roadmap, figure out your weaknesses, make sure you can do Excel, make sure you can do financial modeling.

[00:32:09] But remember, because most advice to get are people reaching out wanting jobs and in that area. And one of the biggest things to tell them is your job is to make sure the hiring manager doesn't feel risk in hiring you. If you can reduce that risk. I'll give an example. I see you're hiring someone and one looks like, hey, they have the potential to be a superstar, but they might completely flame out. So there's a little bit of high risk, but you can see there's a really high reward. Or there's one that, okay, they're going to be a good performer.

[00:32:37] Not sure they're ever going to be a superstar, but have almost zero risk. Who are you typically going to go with? The second person. Right. And especially in finance, we tend to be risk adverse. Yes. You're going to take the second. So I think, you know, helping people realize you're really trying to mitigate risks. So think, understand what their pain points are. And that's more job than career. In career, I think the biggest advice I would give is, is learn how to serve within whatever you're doing. Mm-hmm. Thank you so much for sharing.

[00:33:05] I can tell, you know, from how you helped me with my podcast and so many others. I know I joked, I call you the Oprah of finance podcast. You're welcome to put that picture of Oprah with a beard on LinkedIn. Oh, that was DHA marketing. Yum. Out of France. Oh, gosh. But yeah, I can see. And I'm super grateful for the work you've done. Not just, you know, on LinkedIn, but also behind the scene on LinkedIn.

[00:33:31] People may not see all the DMs you send to support, you know, the whole community. So thank you for that. Thank you. I appreciate that. It's been fun. What's it been now? Three years? Yep. Three years already. Yeah. We're getting old. No. 39.99. Inside note. Sorry, everybody. Yeah. Inside note. Completely. We're going to keep it inside. Last question. What is your favorite thing to do outside of work? Outside of work?

[00:34:01] What's this you talk about? No. There's a few things. I like spending time with my family. I have a 12-year-old daughter. I get to spend a lot of time with her. I enjoy running. I usually run every day. And then I like young adult fiction. I'll admit it. There's my guilty pleasure. Oh, okay. Nice. I'm in Netflix. And recently I started lifting more weights than Cheetos. So it's getting there. What brand is heavier than Cheetos? I'm just kidding. Yeah. Cheetos.

[00:34:30] Like I haven't had any Cheetos since the beginning of 2026. So to me, this is like a big achievement. No, I need it. I'm continuing trying to eat better. I had some health challenges in 25 and I got to be better with my eating. So I get it. But you run so much. How many miles are you running a day? Um, usually it varies whether I'm doing a speed or long run, but three to six, although I've missed this week, unfortunately, but probably three to six miles.

[00:34:59] I'd like to get more of about eight on average a day. So about 50, 60 a week. I want to run the Boston marathon. Oh, good. Good for you. I ran my first marathon when I was 17. Fun. Wow. Well, we'll continue cheering you on from a distance. When I go to Boston, I expect you to be there at the finish line. Oh, okay. We'll try not to do that. I can't wait till I finish. I cannot promise that. It won't work.

[00:35:29] Well, thank you. Thank you so much, Paul, for being on the show. Well, thank you for having me. Always a pleasure. Thank you.