When AI Does the Analysis, What Makes an FP&A Professional Valuable with Valerie Martin

The company had 16 years of old spreadsheets and data, and AI was able to do it and rebuild the history in 90 seconds. AI could help you automate manual work, but you still need to earn that seat.

But there's a story that people are not telling, and that is what happens to these skill sets?

Everybody has the same tool. Everything spits it out. Like, what's your differentiation factor? Think about it. What will differentiate you is—

Meet Valerie Martin, Finance Advisory Board member at Meshly, a finance executive with 20+ years leading FP&A, strategic finance, and She joins us to break down how AI is reshaping FP&A and what it really takes to manage high-performing finance teams today.

What makes great FP&A?

For me, what makes great FP&A is really helping making better decisions and faster. AI could help us get the answer faster, but you can't outsource accountability and getting the answer and the trust behind it. So for me, it comes back that AI raises the bar for FP&A. Let's just admit it.

You always got to go and also make sure that AI is producing the right results.

How do FP&A professionals, whether it's leader managers, make themselves invaluable in this era? I think it's— Hardcoded Opinions, where Glenn and I tell you what we're really thinking.

All right. My hard-coded opinion for today is around communication. So much of communication we think is us speaking or writing, but that's not it. Communication is about the other side. It's about someone hearing and understanding not just the words we're saying, but the meaning behind it. And one of the things that really just drives me nuts is hearing people communicate in acronyms. We have this at every single company, Throughout our lives, people are talking in acronyms. Think about when you don't understand an acronym and how you feel about that. So when you're speaking to somebody and you're trying to say something, you say these acronyms, they don't understand the meaning of the acronym. You're basically losing the audience. And if you lose the audience, you might as well be speaking to them in Swahili because they have no idea what you're talking about anymore. Now, I say that, and there could be some members of the audience who actually know Swahili. So maybe I— let me change that to ancient Sumerian. Right? You might as well be speaking ancient Sumerian because no one should really be speaking that language anymore. But the idea is that make sure that when you're speaking to somebody or you're writing something out, you do it in a way that the other person can not only, you know, read and understand it, but they get what you're really trying to say. That's the whole point of communication. It's not about hearing yourself talk. It's about making sure that the other person is hearing and understanding the way that you are saying it and getting the exact same idea that that you have in your head that they now have in theirs. That's the point of communication. So just watch out whenever you're communicating with acronyms. It's okay to use them, but define them first to make sure you're not losing your audience. And that's my hard-coded opinion for the day.

All right. Now it's my turn to share my hard-coded opinion. You know, every so often you see people want to incentivize or tie bonus to forecast accuracy for FP&A. I always have thought that's stupid. Is there some validity to it? Maybe a little, but let's take a minute and think about it. Especially if you're a fast-growing business or you're a business where FP&A doesn't have the control, why should your bonus be tied to that accuracy? It's one thing to hit a forecast. It's another to say you have to be within 2% or whatever. Okay. If you're a very mature business, things are very consistent, sure. Or certain areas where you have all the historical and you should be able to be accurate. It's more about making good assumptions and sometimes taking risks. So I don't think it incentivizes the right behavior. I've never understood it. I've never liked it. And so my opinion is just don't do it. It's a bad idea. It's kind of like the whole idea of token maxing. It doesn't incentivize the right behavior. I don't believe forecast accuracy incentivizes the right behavior. So ask what behavior you're trying to incentivize and focus on that. So that's my hard-coded opinion today. I'm going to keep it pretty simple. If you're thinking of tying bonuses or performance or ratings to forecast accuracy, don't do it. That's it for me. Thanks. Welcome to another episode of FP&A Unlocked. I'm your host, Paul Barnhurst, and this week I'm thrilled to be joined by my co-host, Glenn. Glenn Snyder, how you doing?

Doing great, Paul. How you doing?

Doing well. Work treating you well? I know you got a big project. Everything going good?

I don't really know what time zone I'm in all the time, but other than that, yeah, things are going well.

How many time zones are you in a week these days?

Last week I was in 3. I was on the East Coast and then I came home for a day and then I went to Central Time Zone.

I was going to say, I know you've been in a lot of time zones, so hopefully you get some sleep this weekend.

Yes. Just don't ask me what time it is right now.

Okay. Middle of the day, if that helps. All right. So we're really excited to have you all here for this episode on FP&A Locked, and we have a great guest with us today. So I'm going to go ahead and introduce our guest. We have with us Valerie, Valerie Martin. How you doing?

I'm doing fantastic. Thanks for having me.

Well, thank you for being here. And I'm going to let Glenn tell a little bit about Valerie and she can add a little bit to that. I think Glenn knows her better than I do.

So Valerie and I have known each other now about 4 or 5 years.

Yeah, I would say that.

Yeah. We're both active in the San Francisco Bay Area in finance organizations and we've crossed paths and just really hit it off. So I was thrilled when Paul, when you and I were talking about the topic that we're going to be talking about today, which we'll introduce in a second. And I just thought Valerie would be a great speaker, but Valerie, you could speak to your background better than I can. So I'll let you do a little intro of yourself.

Yeah, great. Well, it was great meeting you, Glenn, and still having you around. Well, I spend most of my career in FP&A. What I do more specifically is strategic finance. I led a lot of go-to-market and tech companies in the Bay Area. What I really like about FP&A is staying close to the business. So we make better decisions and how do we actually influence get it there faster. I recently spent a lot of time in the Bay Area around the AI space in the last past year, understanding the noise versus the smoke of what's relevant or not and how it impacts our teams. So excited to be here about this topic today and be introduced to you, Paul, today. So that's about me.

All right. Well, thank you, Valerie. We're excited to have you. And I'll let Glenn share a little bit more about our topic before we jump in that. But before I do, I ask every guest this question. So we'll see where you kind of take it. We get some similar answers, but there's always a unique twist. What makes great FP&A?

Well, for me, what makes great FP&A is really helping making better decisions and faster. So basically, of course, you know, FP&A will know the numbers and we're going to go and know what the forecast is, but we're really helping about, you know, the question of what's so what, what do we care, and where should we do things differently? I like to consider FP&A like copilots. So, if FP&A is copilot to the business and we're flying the plane together, our job is not to really read the instruments, it's really understand where we're going, what's changing around us, and how do we need to redirect, and what's the opportunities, and where do we change course. And you can't be a good copilot if, you know, you don't know the context, you don't build trust, and you don't have judgment. So, you need the business to trust you enough. So you can actually make those decisions. And that's what I think FP&A should be.

I like it. And don't crash the plane as the copilot.

Hell no.

Well, I would actually, as someone who's been spending a lot of time on airplanes recently, I love the analogy because I think a lot of times you have a starting point, you have an ending point, but there are sometimes there are storms that come up in the way and you've got to go and say, how do we go over and navigate and change the direction a little bit to go over and reduce the amount of turbulence so that you could get to where you need to go in the right way and make sure a plane lands safely. So I love the plane, the flying plane analogy. It's great.

Awesome.

Glenn, why don't you introduce our topic? Let our audience know what they've won today. I mean, what we're speaking about.

Yes, the grand prize. So one of the things that I've noticed, and I think everybody's probably noticed, is there's been some conversation around the stuff called AI. Right? It's in the news. It's out there. Everybody's saying you have to have it. You know, Paul and I have had guests that have basically said, if you're not using AI, you're going to be left behind, all those types of things. And there's a lot of truth to all of that. But there's a story that people are not telling. And that is what happens to the skill set for people who are using AI? And then how do managers need to change the way that they're managing their teams when their teams are using AI? to make sure they're still going to have the right impact and the trust with the business. And so, that's where we thought Valerie would be a fantastic guest to have here and to have that debate because it's the conversation to me that is just not being had. Everybody's talking about the efficiency of AI and all these things. And granted, now the conversation is more about AI is going to, you know, kill all humans on the planet in the next 10 years. Okay, fine. Let's put that aside for the moment.

And you can't talk about a favorite Terminator and all those type of movies?

Yeah. And the funny thing that I always come back for years, and Valerie may have heard me say this at a few events, there's a couple different views of AI. One of them is we always think we're going to be building Commander Data from Star Trek, but sometimes you're not actually getting someone who's that ethical, right? But really, when you're thinking about if you're using AI, What's really happening? You know, what's the skill set? What are your analysts doing in FP&A around analyzing the numbers? How close are they to the numbers that they could remember it and recite them in a meeting? When they get asked a question that might have a little different twist to it, do they have enough knowledge to answer the questions or do they have to go back to AI to get the answers? And if so, how does the business feel about that? And then, what happens to that trust relationship between FP&A and the business. And that trust relationship, as you know, is so critical because that's how FP&A really gets the insights to not only improve forecasting, but to understand what's coming and try and be proactive to head off some of the issues that could be arising in the future. So with all of that said, Valerie, why don't we start off kind of with your take on how you're seeing AI is kind of being used in FP&A and set the stage around that?

Yeah, I know it's a good question and I'm very excited about the topic. I see AI moving from AI helping to actually AI really doing pieces of the work. So, if you're looking at variance analysis or commentary or rebuild models or repeatable work, cleaning up messy data or repetitive workflows, that's where I see a lot of AI. And I've seen an example where I think a company had 16 years of old spreadsheets and data and AI was able to do it and rebuild the history in 90 seconds. Now, where I see AI a lot is like, that would've sounded crazy a long time ago, it's working now, but it's not because we have that data that actually it turns as valuable data. It's more, what do you wanna do about it? So, what I'm seeing is more and more of the capabilities of AI are increasing, people are using it, but now it's basically focusing on how can we actually bring value to those tools and what we're trying to do and which problem we're trying to solve. And we cannot really, you know, look at the risk of confused. It's more efficient, but are we actually bringing more value in what we're doing with the time that we have saved? So, that's kind of where I'm seeing a lot of the AI moving into testing phases, looking at stuff, but actually doing the work today.

That is helpful. I'm curious, what do you think are the best use cases? Not where you're seeing it being used, but in your opinion, Today, if you had to list the top 3 use cases, what would they be?

You know, it's interesting because I've stopped thinking about where is AI use case to what's a good case, meaning which problem are we trying to solve versus putting a tool on it. And I think that's where I'm constantly repeating where people are seeing the fancy noise, like the fancy tool, but where I'm sitting, it works really, really well. To answer your question, Paul, is like where it's fairly bounded and repetitive, where the data is reasonably good or the process is simple to automate, and then somebody in the room knows what good looks like, so it's easy to audit and validate. So the first pass of like a variance analysis, just the first pass of it, a recurrent analysis or some cleanup of repetitive work, and then somebody in the room that could say, I could audit that and like, this looks like that, I think it's a great case of AI. Another thing where I'm seeing a lot, and I don't know if you've probably seen that too, is forget the tool. People have a lot of complex processes, so they think by putting AI in, it's going to fix the whole thing. So it comes back to, well, yeah, AI could actually simplify it, but, or make it garbage in, garbage it out. But I think it's really looking at what we're doing today, go back to our teams, redesign why we have that process How do we make it simpler? And then eventually get AI. And I think that's where it's evolving, but it's not there yet. But I think that's something that we need to really look at.

Yeah, no, Valerie, I completely agree with you. I mean, one, you always got to go and also make sure that AI is producing the right results because it's 90% correct, but the 10% can really get you in trouble if you're not catching it, right? So you have that. The other side of things though is everyone's talking about AI and you, it just, as you alluded to, it's around production. You can produce things more, you could get your reports out faster, you could do the analysis, it could put together a deck for you, those types of things. But one big aspect of FP&A is the relationships that you have with the business. How are you seeing right now AI having an impact on that finance business partner role in those relationships?

Yeah. Well, I just need to come back to a foundation, and I do see a lot of changes, to be honest. I think this is a great question, is that if we go back to a whiteboard, you know, the whiteboard days, and we just look at how do we use it, how do we want to use AI, which decision is trying to use and support it, and like, how can we eliminate or simplify it? I think that's kind of your baseline. And if you come back on partnership and AI, I'm like, okay, great. How do you earn that trust and how do you earn that partnership? Is it because you spit a report or because you know the report, you know the data, not necessarily you built it? And then also, do you have— you earn that seat, you know, on the table with the partnership? I'm like, how do you build that context, build that trust, you know, and get that context? That's not what AI is today. AI could help you automate manual work, but you still need to earn that seat. Um, and I think that's an important distinction point.

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I agree. I mean, I think, Paul, when we think back in, you know, through our careers, we've always talked about It's not the great FP&A isn't about the numbers you're producing or doing a budget or a forecast. It's having that impact on the business. It's having that relationship and that trust. And I think that's the thing that AI can't do because you might say, hey, I could trust AI. I could trust the system once you feel like you're actually getting really good results from it. But when it comes to Hey, who's looking out for me? How do we go over and, you know, as Valerie talked before about being that copilot to help navigate around the turbulence type thing, AI can't really do that. And my concern is that people aren't adjusting the way that they're managing their teams in a way that they're so, you know, people manage oftentimes they teach those technical skills. How do you produce the report? How do you do the budget? But they're not Shifting to say, how do we maintain those, that trust with the business?

Okay.

Paul, do you, you, you and I have had similar experience. I'm, I'm guessing you're in the same boat.

Yeah.

I mean, obviously regardless of, I'm trying to think exactly how I wanna say this, but right, AI is nothing but a tool. Although we keep hearing it, we could be setting it at some point, whatever that means. It could kill us all, but it's still a tool. All right, I couldn't resist. Like Excel's a tool, like modeling's a tool. And if you look at each of them over time, when the spreadsheet came out, did it really change the business partner relationship?

No.

When the computer came out, did it change it? No. AI has the potential in the sense that it— those tools were just different way of working. AI can do the work for you.

Yeah.

For us, and so if you don't keep that accurate control now, whether gets it all right, we can have that whole we go we can spend the rest of the time discussing how well it works for us. We know it works. We know people are getting results from it. We know it can help us. But if we don't still keep control of all the relationships and really owning what FPNA is about, we're going to start to to lose. Some of the core things. And the core of FP&A really is business partnering. You know, whether we're building a model, whether we're writing an Excel formula, whether we're doing analysis, those are all designed to help the business make a better decision. If we don't partner, work with, and have relationships with the business, we cannot help them make those better decisions. So I think that, that's kind of the lens I look through it all is we kind of always have to bring it back and say, okay, it's just a tool. How do I make sure that I'm able to maintain the appropriate relationships to drive my goals regardless of the tool I use to assist me?

I think that's fair. And I think the difference is sometimes people are getting very hung up on Look at what I can produce for you business versus look at the insights and look at the problems that we can solve together. And what I've seen is I think there's this natural shift of production of where production comes from. Oh, I don't need an FP&A team of 10 people anymore. I could do it with 5 because I have AI. The production goes up. But that FP&A leader isn't recognizing when production goes up, how are you now making sure that the business is getting greater value, greater partnership, and getting better insight if the production is coming from AI? And I don't think that shift in leadership is really happening. I think a lot of times people are just, they're managing it the same way that they always have. And that is eventually down the road could potentially deteriorate the trust. between the business and FP&A because FP&A is not really doing the work and learning the skills and the data. I mean, Valerie, what's your take?

I think this is spot on. I think AI could help us get the answer faster, but you can't outsource accountability in getting the answer and the trust behind it. So for me, it comes back that AI raises the bar for FP&A. Let's just admit it. Data is more available faster and so on. So our value is not necessarily getting that done anymore. but it's really understanding how do we answer the real questions, right? So, how do we answer judgment? In order to get judgment, you need context, and you need to know which questions to ask, and you need to challenge something, and you need to have that relationship as you're talking about. That hasn't changed. But what changes, like, how do we train our teams? 'Cause in the past, like, I think you mentioned that, Paul, is, you know, they were in Excel, and in Excel, you have to think about the architecture, and how it's built, and what's assumptions gonna do, and then you kind of test them, you kind of understand the architecture behind it. Now, with AI, assume AI does the whole thing, right? So as a leader, now when you're actually challenging your analyst to do the job, like you need to challenge them on assumptions. Have you, like, what's your assumption? What do you think? Which questions are you trying to answer? Okay, well, there's a great report. It's served for what? What's your judgment? So it's like, how do you lead and challenge your, you know, the reviewing part is the key part here. So How do you view where the work? And also, it's like, how do you pull these people more into those conversations that we're used to? So, bring them closer to the business units so they could be sitting in the room to have a debate and see why the questions are happening. An example that I like to say is like, imagine that you're in a room and you're— there's a $10 million assumption on, I don't know, let's just say marketing spend. And you're like, you don't know where that's going, so there's debates in the room that said, is it $10 million or $20 million? There's trade-offs. What does it mean? And risk and so on. If AI is not sitting in the room, like, AI won't know, will just spit a number. But if the leader does not bring the junior analyst or challenge it or learn it, you'll never learn the context. So, for me, it's AI will bring the bar, but the leadership needs to challenge the assumptions even more, ask the questions, make sure they make them think. And also pull them in the business sooner so they have that context because judgment is not going away. It's just how do you train that judgment that's different now? It's not gonna be trained by AI. It's trained how we actually train them. So I think we need to rethink that and we need to think how we look at, um, that learning from that talent pool.

I think you make a lot of good points. I think there's, right, a ton of discussion right now. I think we're mostly seeing is around the education system. If AI is starting to do more and more of what was often the junior analyst's work, right? What we sometimes call grunt work, dirty work, whatever term you want to use, not trying to be negative, but it's often just the stuff that had to get done to get to that deeper level. And so if a lot of that's done by AI, there's, I think the conversations are happening. How does that change education? How do people get training? But there's also the question, how does that change the way we need to be a leader? And they, like you said, we need to think about our teams, we need to manage them. Those frameworks are going to change. There's also the question of how far do we let AI go? So I think they're two kind of two separate things. And what I mean by that is right now there's a lot of marketing hype of autonomous finance. If you could have an entirely autonomous finance department, would you want that?

No way. No accountability. There's no one. When, you know, who's going to go over and say, when mistakes are still going to happen, who's accountable for them? Who goes in and fixes them? If you don't have anyone there, that's, yeah.

Even let's just say it makes no mistakes in the sense of the data. All the reports are right. Even if you make that assumption, my answer is still no.

Absolutely. There's no insight. There's no, hey, tell me what I'm not thinking about. There's so much more value than just the data that we bring.

Even though it can do that in some situations, even if I assumed it could give me insight and ideas. Someone still has to ask the right questions. Someone still has to decide if that's the right insight, even if it could, let's assume it does all that, you know, does those things well. You still need a human judgment or a human layer here. That's why I cringe when I see autonomous finance. Are there areas that's low risk and it's automated? We already have autonomous finance today in some areas that it just does it and there's a spot check. And if ag is areas where that makes sense, continue to use No problem with that. But this idea of, yeah, you almost don't need a CFO. It's like, there's 2 things you need to address. There's a Q1 element from judgment and there's the leadership. Valerie.

I think this is spot on because I think FP&A leaders, we just need to manage differently or think about it differently. It's like, we're not, we need to redesign the work, not just deploy the tool. AI is going to do it. So if you think about work, I see 3 pillars, right? There's the work itself. Does AI does it, or does it augment it, or do we leave it human-led? Like, that's the work. Then if you look at controls, because we need to be SOX controlled and audit, or all the above, it's like, what needs validation? Who owns the output? And what happens if it's wrong? You know, like, what's our risk here, and what's our risk tolerance? But then there's a talent pool, right? So what experience do people need judgment on, and where do we fit it, and how do we challenge it? So, all this still exists. He's just never— we need to, we need to go back to those whiteboards again, or like, whatever it is. But it's like, which problem are we trying to solve? What are the workflows? What are we automating? And where actually the judgment stakes, because this is where we need to focus how to make sure that we train them well, and train to give them the context and the trust. And AI is not gonna do that. Leaders need to do it.

And Valerie, I'm gonna add a 4th pillar for you. Which is going to be— it's communication. No, communication.

Oh, yes.

Because how do you communicate the results? How do you package it? You got to know your audience, what's going to resonate, right? You can't go over— I've been in meetings where I've shown detailed spreadsheets to marketing leaders and they're just like, I don't like looking at Excel. Give me a picture. Give me something in PowerPoint. Right? I love people—

You cannot go with Excel in a meeting, by the way.

Yeah, no, no, right. But I mean, I love marketing people. But a lot of times, marketing people, they don't want to get into data. That's not their skill set. That's not their comfort zone. They want to give them a PowerPoint deck with a graph and a picture that they could comprehend and see in a much better way. So, how you communicate that, not to mention the fact, if you're going over and you're having a meeting and you're communicating something to an accounting person, you could be in the weeds, in the numbers, and that's where they're going to be comfortable. If you're presenting to a board of directors or you're presenting to an executive, you got to bring that up. Well, what's the bigger impact? Not just in the details of the data. But how does that work within the confines of the company or the industry or the market that you're in? What's the overall impact? And the message could change based on your audience. So, It's understanding how you not only get to do the work and, you know, and work through it and what the, you know, the results are gonna be and who's gonna do what, but how it gets communicated. 'Cause at the end of the day, if you're not communicating it to the business, then why are you doing it at all?

It's interesting 'cause that communication, I think it's a great pillar and I'll add it on my 4. It is like how FP&A is taking complexity and make it simplicity where people could understand it. And that's where a pillar of trust. If you think about it, because how are the business leader going to actually trust what you do is when you put something in front of them and they're like, okay, first, yeah, I trust it comes from you and you know, and you did your validation, basic FP&A. But 2, do I understand it? Do I just like, do I understand it? How does it work? What does it mean to me? Why should I care? How does it tie to the whole company picture? And I think you're spot on by saying storytelling or communication is a key criteria that we need to make sure our teams continue to focus on.

And one other little thing, because you mentioned the trust aspect, saying, I trust you have the data right. But when it comes to the individual from a business perspective, they're also saying, do I trust that you've analyzed it in the right context of my business that's going to add value? Because that's where the business leaders are really looking for is to say, hey, if you go to a business leader and you keep on putting ideas out there and they're just like, Do you not have any idea what we do here? Like, it just doesn't make any sense. You're not going to have that trust in the business. You got to make sure it's going to resonate with the people you're talking to.

And I think you're wrong. You're right. Not wrong. Right, actually. It's like, it's like—

Wrong, Glenn.

I had to put that out there, but I know you're right. It's like we have to earn our seat differently. It's like the same thing, but we just need to earn it saying, well, Yeah, AI will raise the bar. You could get your number. Yes, whatever. Like, forget that. But it's like, it's exactly what you're saying is like, what is the context? Where's the judgment? Knowing the business is super, super important. So, that's what also we need to make sure our teams understand that, and which questions to ask. And you don't know if you're not exposed to those debates, or how to be courageous and ask those questions. Like, it's not just accepting it as is, like, just challenges, you know, the 5 whys. And having the relationship, like you just said, that actually influenced the decision. And that's the key point here.

Today's episode is brought to you by our sponsor, Lineos. Lineos brings live ERP data directly into Excel, allowing your team to build reports with fresh data. No stale files in sight. More on that in a few minutes. I think, you know, we've all kind of aligned, obviously, There's a huge judgment element that you have to maintain. There's partnership there, and AI will disrupt some of that. So let's talk about what do you do? Let's assume, you know, AI is— not assume, we all know AI is going to continue. It's not going away. It's going to continue to get used. So what should the leadership leaders be doing? How do they manage their style? How do you manage what You know, with a team of AI. I've never done it. And running my own business now, I don't know, you know, yes, I use AI, but I'm not managing employees that are regularly using AI in kind of an FP&A environment. I don't know that anyone really knows the full answers yet, right? We don't know the full implications, but how do you think about it? What are things that maybe managers need to be careful about? Because managing an agent, even though sometimes say, hey, treat it like an employee. There's obviously differences and you have an employee and I can see Glenn cringing a little bit. Why don't we have a hard-coded opinion in his head coming?

Oh, that's a good idea. But no, Paul, you know what? You're spot on. I think, you know, some of the challenges with managing people who use AI is the production happens so fast. They want to move on to the next thing, but you think, wait, no, you got to slow. And one thing is you got to change where you got to tell people to slow down. You know, great, the numbers came out fast. Make sure you're looking at it. Don't go through the numbers so quickly that you're not really catching those mistakes because those mistakes are going to lead to credibility questions. And so you have to slow down. Also make sure that your analysis is thorough. A lot of people, they go over and it's so easy to do elevator analysis, right? Which is this went up and that went down. But that's not insightful, right? What's the underlying metric? How did you get there? What's the impact going to be? Why does somebody care whether that was over budget or under budget, right? So, you got to be able to— and you can't just go over and write a half a page for everything that you're trying to explain. How do you do that succinctly? So, those are some of the things that you have to coach people on. But the other piece is to go and say, hey, Guess what, FP&A analyst? You have now a lot more time because you're not manually producing these reports. AI is putting that together. Good. So what do you do with your time? You should be learning more about the products. You should be learning more about the customers we have, the markets that we work in, the government regulations that we have to abide by so that now you could take the numbers and put it in a broader context that people at a higher level can start using to make decisions. And it is a different kind of coaching. I think it, it's not so much about you gotta get the numbers out, gotta be on time, gotta be right. And then, you know, that's the majority of the work. Now it has to be, it has to be in the right context and adding more value because you have time to put that in. At least my, that's, that's my take. Valerie, what do you think?

I think this is right. It's like AI's not going away and you can't be on the sidelines, so it's there. So how do you use it but balance the benefit and the risk? So I would say is like time save is not also necessarily creating value. So how do you make yourself more valuable? I think that's your question, Glenn, is like, well, how do you invest yourself to be more valuable as well? How, if you, information is cheaper and faster, then it's how do you create judgment? How do you, you're curious? How do you build business acumen? How do you, your communication pillar, like how do you invest in storytelling? How do you build trust? I think AI could do the analysis, then what do we do? Well, we need to know which one matters. So challenge which matters and the so why. AI will create scenarios. Well, which one is worth discussing and bringing to leadership? Like your marketing example, they're like, okay, why should I care about that one? AI could draft a recommendation, but is it really the right decision and does it make sense? Challenge those scenarios and actually train all the above. I think at the end of the day, it's like you need to put people in the room to answer the business question and defend the assumptions. It's basically defend assumptions and recommendations and not just the answer. I think it comes back to a skill that we've done in the past, and it's even more and more and more important to do it today.

Great point. And I think, you know, you both said something, Glenn, you really hit on something that is really important. As leaders, there can be a tendency. We got AI, so now we can pump out more. We can do more and more and more. That extra report probably isn't adding the value you think it is. What percentage of reports never get read today? Glenn, in your career, have you ever gone into a situation you find out nobody's reading 80% of the reports FP&A is producing?

Yep.

Valerie? Happens all the time.

Absolutely. Yes.

I've been there too. So there's now, you have to really think, how can they add more value? One, am I teaching my team to ask the right questions of AI? Because AI can give us an answer and sound confident with just about anything. The question's never been more important in my mind. And the second thing I think you hit on, I really kind of think of 3 things. You've got to be able to write the ask questions. You've got to be able to audit. We're becoming more of auditors, whether we like it or not. And that is not as fun of a job. People have to realize that. I'm auditing an auditor. Who enjoys auditing a model versus building it? Like, who has more fun auditing the model? Again, nobody raises their hand, right? We, we didn't go with, we, we're, we're not auditors for a reason, but we have to do more of that. And so that's something managers have to understand how they manage that. I think the, the next 2 are more, I think the, the most critical is one, how do you make sure they're deeply understanding the operations of the business? If you want FP&A to provide a lot of value, don't have them build another report. Use that time to help them better understand the business, the deep operations. And then the fourth, instead of so much training being focused on technical skills, and that's what we train people on, make sure your learning and development is around the soft skills that allow them to be that partner. That's gonna drive the business forward. So those are my thoughts as I hear kind of everything you've said and kind of bring it together. It's been trying to crystallize it the last 20 minutes in my head because I haven't thought about it this way before.

Yeah. And it's interesting because another thing I think we need to think about is like, if you look at our new poll, new generation of FP&A, you know, how they're learning, I feel like AI accelerates their learning curve where they sound smart very quick because AI helps them with it very, very quick, you know? However, the other side of flip of the coin is because AI sounds very smart, the answer really sounds really smart, but does it make sense? And this is where we need to push back. So yes, we have the benefit of that learning curve, but how do you challenge it? And because obviously AI sounds smart, but it doesn't always make sense to me anyways. But it comes back as leaders of how do you make sure that you redesign how you teach them and how you challenge them. So, really make sure, like my ask for all these FP&A leaders is make sure that your analyst explains the output to you. Make sure you put them with business partner, understand the context, and make them defend the recommendation, not just produce the answer. And I think it's even more important today.

Yeah, I agree. I think that the defending part is incredibly valuable because when you're presenting the data, You could be challenged on it. You gotta be able to defend it. You know, the funny thing is, is Paul, when you were talking about, you know, the focus on soft skills and value, what you were just going through, I, it made me think of the progression someone has in FP&A, right? You start off as an analyst and 95% of your job is technical, 5% is leadership or soft skills. Then you go up to a manager level. And you're about maybe 80/20, 80% on the technical side, 20% on the soft skill side. You go to senior manager and it's probably 70/30. You get to a director, it's about 50/50. And then you get to the VP level and it's about 20% technical, 80% on the soft skill. What's the moral of the story is that if you want to move up in your career, it's not the technical skills that's going to advance you, it's the soft skills. And one thing is, it's always easier to teach technical skills. I mean, we've all had to think of people who taught us how to build models or how to construct something. And it's very technical and say, oh yeah, here's how you could apply that over. But rarely do you get people who say, hey, let me sit down and talk with you about how you should coach your team or how you could build out better trust with your business partner. That's stuff that you usually learn by making a mistake, getting yelled at, And then not doing it again the next time, and that's how you sort of pick it up. But it is in a way, I think, just for anyone who's out there who's managing people, that's the hardest part of management. It's easy to go and tell somebody how you put a budget together. You can go look at the trend of this, and yeah, let's go, and here's how you forecast that out. Great. But to go over and explain to somebody why it's important and make sure that they understand and how to apply. apply it to help other people make better decisions and how to go and build that trust and engage with people and how to speak up when you're not comfortable. Those types of things, those are the skills that are not really being taught, but that's what really needs to be emphasized because the production side of things is moving to AI. That's my take.

No, it's your take, but let me make it even more realistic or scarier because that's the reality. Oh, scare me. I'm not gonna talk about Terminators, but I could talk about how it could be scarier. But if, assume this, right? AI produced similar reports for everybody. Everybody has the same tool, everything spits it out. Like, what's your differentiation factor? Think about it. So 2 people have the exact same data, same report with AI. The better FP&A partner may ask different type of questions. And then when it comes back to what you said, right? What will differentiate you is, Where are you, your curiosity, your judgment, and the understanding of the business that will actually make you more valuable? And it's self-awareness.

Yeah. And then again, I'd add that 4th pillar of how you communicate it out.

I will get it in after this.

You got it.

Absolutely. Yeah.

Glenn just likes to talk about communication.

Well, I think it's key. I think for me it's a given. That's why I don't mention it. I think it's a given, but you know what? You're right. It's not a given. We need to mention it.

It's the base layer. It's not a pillar. It's the foundation. How's that?

So yeah, I'm actually laying that foundation for my hard-coded opinion that's coming up.

I'm not surprised. I'm excited to hear it. So there's a tease for everybody, although, well, then I'll stick it at the beginning and everybody will be confused when they listen.

That's right. This is what happens when you put things out of order. Yep.

No, no, we'll put it at the— I'm just having fun. So at the end, there will be a hard-coded opinion for everyone. I just lost my train of thought. This is really bad. I'm doing great on this episode. All right. So back to, I think there's a lot of great points every, everybody's making here as we kind of talk about this. And I think what it does is the soft skills have always been important. They become important earlier. And the hiding behind, well, I just need to master my technical skills, it's going to become less of an excuse and less of an ability. Not that you say technical skills are not going away, at least in the short term. They're still important. You still need to learn how to use Excel and modeling and all those things, but there's a clear shift. And I'm seeing, you know, it all getting better and better. And I think the whole idea of producing similar results is a really good point. So I think we're all in alignment. AI is here to stay. I'm going to guess, Valerie, how often do you use AI today?

Oh, every day, like every hour. I'm always with it.

What's something you can't do now without AI that you couldn't go back to the old way? It'd be really hard for you.

Oh my God. I use AI for cooking. I take a picture in my fridge and I say, what do I do today? And I'm like, they just give the recipes. So for me, I use AI for cooking.

Yeah. I mean, great example. Glenn, is there something for you?

I don't use AI as much, but part of it is, is that the role that I'm in is more strategic in nature and it's more about the discussion and being present in the discussion than producing the results.

Anything in your personal life you're using AI for that you like, wow, so much easier now?

AI, the one thing that I do use AI where it's great is just doing research. Hey, I need to go and understand something. Go comb the web, figure out what's, you know, give me some, you know, ideas about different things. And I think AI is great for that. So much faster than Googling things or Yeah, I agree with everything you said.

You know, mine is I do a lot of podcasting, and when I started, I had to go listen to the episode to put together my script. I don't have to do that anymore. AI can summarize everything. It can write that first draft. It prompts my mind and all the mate, and then I go through and put my own, you know, spin and wording on it, but it saves me just hours and hours of Time. And that's the world we live in. It's going to continue here. So how do we, what are the kind of things they should, FP&A should really be watching out for to make sure, you know, they're getting the benefits without letting the kind of the risks kind of take over. So any thoughts on, hey, it's here to stay. We've talked about leadership, but just people If the biggest thing they need to make sure they watch for so they can take advantage of the benefit and minimize that risk. Valerie, what do you think kind of those, those things are?

For me, it's always like looking at a process and you decomposed it. It's really understanding what can AI will come and introduce and go watch. What do we need to get our controls so we don't spend more time validating AI than actually our cost of control? And then the rest is like, where do we need our judgment and how do we retain that judgment? So, if it's not building models like we used to do, it's like, how do you make sure as leaders that we carve out the time that we have now of not doing research or cooking or whatever we need to do to challenge your team? And that's something that we're accountable as, as a leader. It's part of our job is just taking more percentage points, as Glenn mentioned, that we did before.

Yeah. You know, I mean, for me, I look at it as how are you now strategically having an impact, not with the data, but with the ideas? And how are you presenting it? You know, one of the best compliments I ever had in my career was I had one of the executives that I was supporting who said to my boss, and it showed up in my annual review, I want Glenn at the table when I'm making decisions. That is, to me, that's like FP&A nirvana to me, right? That's where you want to get to. And it was, you know, it was not only, it's a great compliment, but it basically said it's not about the data that Glenn is producing. It's about how he's showing up. And I know I'm talking to myself now in the third person. I kind of feel like Ricky Henderson a little bit.

I was going to say Karl Malloy. He's a third person guy too.

But, you know, it's about when you're listening to something and it's okay. Here's my thought. Here's what's coming into my head. It's not running it by AI. It's just, I'm engaged in the conversation and having that impact and having that value. And to me, that's the new measurement. The measurement is about the value, not the production. And it used to be about the production.

And it comes back to, you know, I think my originally what makes FP&A great, right? How do you get closer to the decision and how do you get that? You challenge, you bring value, and you're being that copilot. And the copilot is basically being in that room and having that debate.

And, and I would say the real value is when the executive comes over or the pilot comes over and says, I want you to be the copilot versus just assigning yourself into that role, but having that acknowledgement that the person that wants you right there next to them.

You've earned that seat.

Exactly.

We've now hit nirvana.

That's right. FP&A nirvana. It's a great place to be.

All right. So as we wrap up, let's kind of, I want to bring a real practical ending to this. We'll go Valerie and then you'll go Glenn and I'll share a few thoughts. How do FP&A professionals, whether it's leader managers, wherever you want to take that, make themselves invaluable? In this era?

I think it's be curious, you know, like be curious, ask questions, think differently. Everything's possible, but actually lean in. Don't like, I control it. This is which problem you're trying to solve and how can you actually improve and bring value? And you'll see by default, by being curious, you'll see it's really like the communication, the storytelling, the soft skills. You still need to understand your foundation, but the value is shifting of building reports, to actually making an impact in the business and make sure that the results are valuable to them.

In fact, by the way, Paul, a little flashback when Valerie said be curious. First thing I thought of about a year ago, we were talking about private equity and the impact, and you asked a question, what's the number one thing that you, that private equity looks for in an FP&A person? And the answer was curiosity. So I think there you go. I mean, and I think Valerie, that's, That's absolutely— I mean, curiosity, and I think it's connection. I think that'll be the one for me. It's having that connection with the business where they feel like you're part of their business. They recognize that you have a job to do as well, but they want you there with them when they're making decisions. They want you part of the leadership team. They want you engaging with people and the products and the clients and so on that they're working with so that you can add even more value. That having that invitation to be a part of that group, I think that's really where the value add comes in. Because I mean, we can think about people in our lives. When you see somebody who's like, they give you great advice for something, you start thinking about, well, what else should I be asking them? You know, how else can I engage with them? And that's what you want with that natural expansion of that trust.

I'm going to go in a totally different direction because I think both what you said is really well said and I don't want to repeat it. One thing, especially right now, that I recommend FP&A, especially early in their career, learn foundational understanding of data and workflow design optimization. Because if you understand how the data works, you can understand the processes. You're going to be much more efficient and better with AI. I've had several guests say they see a shift to what the most important technical skill is. To around that data thinking, the data foundation, the design. I think those have always been critical, but they've been a shortcoming of FP&A because we learn financial modeling, we think from a financial perspective, and building a model and understanding how to normalize data are different tasks. They require a different way of thinking about data. And the more and more you're going to get benefit out of AI, data workflow optimization. So you need to understand how to be able to do those if you want to get the most out of AI so you can do all the other things that Glenn and Valerie talked about where you can add that huge value.

And Paul, just to add to that, I think a lot of people today in their FP&A roles, they're spending a lot of time cleaning up data and they are maybe implementing a new system and aligning data dimensions. And if you don't have that understanding about how to create that clean data dimensions and how, where the intersections need to be, you're not going to develop the right system. You're not going to have the right organization for your data, and that's going to have downstream impacts as well. So 100% agree.

You're not going to get good intelligence from AI because if you give it good context, the output is much better and good data.

The context layer is super huge. So, but you need the data foundation and how it's architected to add the context layer for sure.

All right. Well, I think we'll call it there. Any last thoughts? Anything you want to leave the audience with before we thank you and let you go to enjoy your weekend, Valerie?

Well, enjoy this podcast. I hope everybody enjoyed the conversation, but I would say just be curious. I'm like, there's so much to learn and it's so much storytelling to do. And FP&A is an amazing spot to be today.

So I think that's a great note to end it on. Any last words from our Our wise sage, Glenn.

I would just say, although you should always be watching out for when AI is trying to do the extinction event, but regardless, you should be looking and making sure you're watching AI for just making sure that the data is going to be lining up because although it is going to be correct, a lot of times there are errors and you got to remember that your name on there, not the AI's, for in the reports and the analysis. And so on. So just, you always kind of still got to keep an eye on AI, plus to make sure it's not trying to poison you in some other way.

And my cooking skills. Thank you.

On that note, everybody watch AI. We hope we don't have an extinction event before this episode is released. And thanks for joining us. Bye.

Thank you.

That's it for today's episode of FP&A Unlocked. If you enjoy FP&A Unlocked, Please take a moment to leave a 5-star rating and review. It's the best way to support the FP&A Guy and help more FP&A professionals discover the show. Remember, you can earn CPE credit for this episode by visiting earmarkcpe.com, downloading the app, and completing the quiz. If you need continuing education credits for the FPAC certification, complete the quiz, and reach out to me directly. Thanks for listening. I'm Paul Barnhurst, the FP&A Guy, and I'll see you next time.