When AI Does the Analysis, What Makes an FP&A Professional Valuable with Valerie Martin
In this episode of FP&A Unlocked, host Paul Barnhurst and co-host Glenn Snyder sit down with Valerie Martin to discuss how AI is changing FP&A, leadership, and business partnering. They explore why greater efficiency does not automatically create greater value and how finance teams can use AI without losing judgment, context, or trust with the business.
Valerie Martin is a Finance Executive specializing in FP&A and strategic finance, with experience across GTM, SaaS, AI, and value creation. A former Autodesk finance leader and San Francisco FP&A Board Ambassador, Valerie brings extensive experience in business partnering, finance transformation, and helping organizations make better strategic decisions.
Expect to Learn:
Why AI efficiency does not always create more value.
How AI is changing the skills FP&A teams need.
Why judgment and business context still matter.
How leaders should rethink training and development.
Why communication and trust remain critical in FP&A.
Here are a few relevant quotes from the episode:
“AI could help us get the answer faster, but you can't outsource accountability.” - Valerie Martin
“The measurement is about the value, not the production.” - Glenn Snyder
Valerie explains that AI can automate variance analysis, reporting, data cleanup, and other repetitive work, but faster production is only useful if teams turn that saved time into greater business value. As AI takes on more technical work, FP&A professionals need to strengthen their judgment, curiosity, business acumen, and communication skills.
Follow Valerie:
Follow Glenn:
LinkedIn: linkedin.com/in/glenntsnyder
Disclosure: Portions of this episode (such as the introduction or promotional segments) use AI-generated voice narration produced under human editorial review.
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Earn Your CPE Credit
For CPE credit, please go to earmarkcpe.com, listen to the episode, download the app, answer a few questions, and earn your CPE certification. To earn education credits for the FPAC Certificate, take the quiz on earmark and contact Paul Barnhurst for further details.
In Today’s Episode:
[00:00] -Trailer
[01:17] - Hard-Coded Opinion
[04:54] - How AI Is Changing FP&A Skills
[06:16] - Where AI Adds the Most Value
[13:51] - When AI Efficiency Doesn't Create Value
[15:03] - Judgment, Context & Accountability
[19:46] - Redesigning FP&A Work for AI
[20:51] - Why Communication Still Matters
[27:35] - Turning Saved Time Into Greater Value
[34:20] - What Differentiates Finance in the AI Era
[41:22] - How FP&A Professionals Stay Valuable
[46:27] - Closing & CPE Information
Full Show Transcript:
00:01:17.390 — 00:01:22.750 ·Host: Paul Barnhurst
Hard coded opinions where Glenn and I tell you what we're really thinking.
00:01:27.030 — 00:03:02.980 ·Co-Host: Glenn Snyder
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, right? 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 this could be some members of the audience who actually know Swahili. So maybe 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, to 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 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 to find them first to make sure you're not losing your audience. And that's my hard coded opinion for the day.
00:03:03.020 — 00:03:26.420 ·Host: Paul Barnhurst
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. 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
00:03:27.580 — 00:03:28.940 ·Host: Paul Barnhurst
you're a business where FP
00:03:30.420 — 00:04:41.730 ·Host: Paul Barnhurst
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. 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 Paul Barnhurst, and this week, I'm thrilled to be joined by my co-host, Glenn Glenn Snyder. How are you doing?
00:04:41.770 — 00:04:43.130 ·Co-Host: Glenn Snyder
Doing great. Paul, how are you doing?
00:04:43.170 — 00:04:48.250 ·Host: Paul Barnhurst
Doing well. We're treating you well. I know you got a big project. Everything going good?
00:04:48.250 — 00:04:52.450 ·Co-Host: Glenn Snyder
I don't really know what time zone I'm in all the time, but other than that, yeah, things are going well.
00:04:52.490 — 00:04:54.890 ·Host: Paul Barnhurst
Ally time zones. Are you in a week these days?
00:04:54.930 — 00:05:02.090 ·Co-Host: Glenn Snyder
Last week I was in three. I was on the East Coast, and then I came home for a day, and then I went to Central Time Zone.
00:05:02.130 — 00:05:06.210 ·Host: Paul Barnhurst
I was going to say, I know you've been in a lot of time zone, so hopefully you get some sleep this weekend.
00:05:06.250 — 00:05:08.650 ·Co-Host: Glenn Snyder
Yes. Just don't ask me what time it is right now, okay.
00:05:08.730 — 00:05:25.370 ·Host: Paul Barnhurst
Middle of the day if that helps. All right. So we're really excited to have you all here for this episode on 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 are you doing.
I'm doing fantastic. Thanks for having me.
00:05:27.890 — 00:05:34.970 ·Host: Paul Barnhurst
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, because I think Glenn knows her better than I do.
00:05:34.970 — 00:05:39.490 ·Co-Host: Glenn Snyder
So Valerie and I have known each other now about 4 or 5 years.
Yeah, I would say that.
00:05:40.930 — 00:06:02.560 ·Co-Host: Glenn Snyder
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 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.
00:06:02.880 — 00:06:38.240 ·Guest: Valerie Martin
Yeah, great. Well, it was a great meeting. Yeah. Glenn. And so having you around. Well, I spend most of my career in FP&A when I do, more specifically as strategic finance, I let a lot of go to market and tech companies in the Bay area. What I really like about is staying close to the business so we make better decisions.
And how do we actually influence to get it there or faster? I recently spent a lot of time in the Bay area around the AI space in 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.
00:06:38.280 — 00:06:55.670 ·Host: Paul Barnhurst
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 fan?
00:06:55.710 — 00:07:46.950 ·Guest: Valerie Martin
Well, for me, what makes great be a fan is really helping, making better decisions and faster. So basically, of course, you know, fans will know the numbers and we're going to go and know what the forecast is. But we're really hoping 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 like copilots. So it's a copilot to the business and we're flying the plane together. Our job is not to really read the instruments as 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 be a good go pilot if you know you don't know the context, you don't build trust and you don't have judgment. So you need a business to trust you enough so you could actually make those decisions. And that's what I think FP&A should be.
00:07:46.990 — 00:07:50.350 ·Host: Paul Barnhurst
I like it and don't crash the plane as the copilot.
00:07:50.390 — 00:07:51.230 ·Guest: Valerie Martin
Hell no.
00:07:51.470 — 00:08:18.950 ·Co-Host: Glenn Snyder
Well I would actually I. So would 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 your plane land safely.
So I love the plane flying the flying plane analogy. It's great.
00:08:19.310 — 00:08:19.870 ·Guest: Valerie Martin
Fun.
00:08:19.910 — 00:08:26.070 ·Host: Paul Barnhurst
Glenn, why don't you introduce our topic? Let our audience know what they've won today. I mean, what we're speaking about.
00:08:26.830 — 00:09:28.300 ·Co-Host: Glenn Snyder
Yeah, the grand prize. So one of the things that I've noticed, and I think everybody you've 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 is 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 ten years.
Okay, fine. Let's put that aside for the moment.
00:09:28.300 — 00:09:32.820 ·Host: Paul Barnhurst
And you can't talk about a favorite Terminator and all those type of movies.
00:09:32.940 — 00:10:48.570 ·Co-Host: Glenn Snyder
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 where we 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 but really, when you're thinking about if you're using AI, what's really happening, you know, what's the skill set, what's what are your analysts doing in a way around analyzing the numbers? How close are they to the numbers that they can 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 and 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 fact, it kind of set the stage around that.
00:10:48.610 — 00:12:07.680 ·Guest: Valerie Martin
Yeah, I know it's a good question and I'm very excited about the topic. Um, 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 90s. Now, where I see AI a lot is like that would have 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 want to do about it? So what I'm seeing is more and more 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 in which problem we're trying to solve. And we cannot really, you know, look at the risk of confuse.
It's more efficient. But are we actually bringing more value and 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.
00:12:07.680 — 00:12:19.800 ·Host: Paul Barnhurst
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 three use cases, what would they be?
00:12:19.840 — 00:13:42.830 ·Guest: Valerie Martin
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, not like the fancy tool, but where I'm sitting, who works really, really well.
Um, to answer your question, Paul, is like where it's fairly bounded and repetitive, where the data is reasonable, 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 part of like a various analysis is just the first pass of it, a recurrent analysis or some cleanup of a 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. And another thing where I'm seeing a lot and I don't know, usually probably send that to is forget the tool. People have a lot of complex processes. So they think by put in AI in, it's going to fix the whole thing.
So it comes back to, well, your AI could actually simplify it, but or make it garbage and 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.
00:13:42.870 — 00:14:26.510 ·Co-Host: Glenn Snyder
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 if you're not catching it. Right. So you have that. Um, I think the other side of things, though, is everyone's talking about AI.
And just like you alluded to, it's around production. You can produce things more, you can get your reports out faster. You could do the analysis, you could put together a deck for you, those types of things. But one big aspect of FPN, 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?
00:14:26.550 — 00:15:21.980 ·Guest: Valerie Martin
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. Um, 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 and like, how do you build that context, build that trust, you know, and get that context.
That's all AI is today. AI can help you automate manual work, but you still need to earn that seat. Um, and I think that's an important distinction point.
00:15:22.020 — 00:16:11.250 ·Host: Paul Barnhurst
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00:16:32.930 — 00:17:40.800 ·Co-Host: Glenn Snyder
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 and 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 in 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 and, you know, as Valerie talked before about being that copilot, 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 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 guessing you're in the same boat.
Yeah. I mean, obviously.
00:17:44.040 — 00:17:55.240 ·Host: Paul Barnhurst
Regardless, I'm trying to think exactly how I want to say this, 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.
00:17:57.640 — 00:19:34.630 ·Host: Paul Barnhurst
Or I couldn't resist. Like Excel's a tool, like modeling the 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 a different way of working.
AI can do the work for us. And so if you don't keep that accurate control. Now whether it gets it all right, we can have that whole goal. 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 FP is about, we're going to start to to lose some of the core things.
And the core of a really is business partnering. Now, 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 relationship with the business, we can help them make those better decisions.
So I think that that's kind of the the lens I look through at 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.
00:19:34.630 — 00:20:46.220 ·Co-Host: Glenn Snyder
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 a natural shift of production of where production comes from.
Oh, I don't need an opinion. A team of ten people anymore. I could do it with five because I have AI, the production goes up, but that a leader isn't recognizing when production goes up. How are you now? Making sure that the business is getting greater value, great, 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 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 FPN, because FP&A is not really doing the work and learning the skills and the data.
I mean, Valerie, what's your take?
00:20:46.260 — 00:23:18.360 ·Guest: Valerie Martin
I think this is spot on. I think AI can help us get the answer faster, but you can't outsource accountability and getting the answer and the trust behind it. So for me comes back that AI raises the bar for a let's just admit it, um, 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 answered 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? Because in the past, like I think you mentioned that Paul is, you know, there are in Excel and in Excel, you have to think about the architecture and how it's built and what's assumptions going to do.
And then you kind of test them. You kind of understand the architecture behind it. Now what I assume AI does the whole thing, right. So as a leader now, when you're actually challenging your analysts 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 reverse 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 users so they could be sitting in the room to have a debate and see why the questions are happening. Um, 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 will know we'll 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 partners where 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 going to be trained AI, it's trained how we actually train them. So I think we need to rethink that and we need to think out. We look at, um, that learning from that talent pool.
00:23:18.440 — 00:24:15.590 ·Host: Paul Barnhurst
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 analysts 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 does people get training. But there's also the question, how does that change the way we need to be a leader? And 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 there are 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?
00:24:15.630 — 00:24:29.270 ·Co-Host: Glenn Snyder
No way. No accountability. There's no one when you know who's going to go over. It's like 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.
00:24:29.310 — 00:24:37.870 ·Host: Paul Barnhurst
You can't 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 still no.
00:24:37.910 — 00:24:45.310 ·Co-Host: Glenn Snyder
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.
00:24:45.310 — 00:24:50.710 ·Host: Paul Barnhurst
Even though it can do that in some situations. Even if I assumed it could give me insight and ideas,
00:24:52.030 — 00:25:29.590 ·Host: Paul Barnhurst
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 those 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 AI is areas where that makes sense continue to you know problem with that. But this idea of yeah you almost don't need a CFO. It's like there's two things you need to address or cue an element from judgment.
And there's the leadership ballot.
00:25:29.630 — 00:26:34.500 ·Guest: Valerie Martin
I think this is spot on because I think for 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 to deploy the tool. AI is going to do it. So if you think about work, I see three pillars, right? There's the work itself. Does AI does it or does it meant it or do we leave it human led like that's the work.
Then if you look at controls because we need to be SoCs, control and audit and all the above is like what needs validation? Who owns the output and what happened if it's wrong, you know, like what's your 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 fin it and how do we challenge it?
So all this still exists? He's just there. We need it. We need to go back to those whiteboards again or like whatever it is. But it's like which problem we're trying to solve, what are the workflows, what are we automating. And we're 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 going to do that. Leaders need to do it.
00:26:34.540 — 00:26:37.220 ·Co-Host: Glenn Snyder
And Valerie, I would add a fourth pillar for you, which is going to.
00:26:37.220 — 00:26:37.460 ·Guest: Valerie Martin
Be.
00:26:37.700 — 00:26:41.300 ·Co-Host: Glenn Snyder
Missing. It's communication. No communication.
00:26:41.660 — 00:26:42.140 ·Guest: Valerie Martin
Yes.
00:26:42.180 — 00:27:02.500 ·Co-Host: Glenn Snyder
Because how do you communicate the results. How do you package it. You got to know your audience. What's going to work it 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 of a PowerPoint, right?
00:27:02.540 — 00:27:07.020 ·Guest: Valerie Martin
I look for Excel in a meeting. And by the way, yeah.
00:27:07.050 — 00:28:11.480 ·Co-Host: Glenn Snyder
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 a bigger impact, not just in the details of the data, but how does that work within the, you know, 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're not only to do the work and you know, and work through it and what the, you know, the results are going to be and who's going to do what, but how it gets communicated. At the end of the day, if you're not communicating it to the business, then why are you doing it at all?
00:28:11.520 — 00:28:52.440 ·Guest: Valerie Martin
It's interesting because that communication, I think it's a great pillar and I'll add it on my fort. Um, it is like how I have taken 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 get your validation basic. But to do I understand it, do I gestures 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.
00:28:52.440 — 00:29:29.520 ·Co-Host: Glenn Snyder
And one of the little things that you mentioned, the trust aspect thing, 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 leads are really looking for, is to say, hey, if you go to 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've got to make sure it's going to resonate with the people you're talking to.
00:29:29.560 — 00:29:34.040 ·Guest: Valerie Martin
And I think you're wrong. You're right. Not wrong. Right? Actually, it's it's like.
00:29:34.080 — 00:29:34.440 ·Host: Paul Barnhurst
Wrong.
Wrong wrong wrong.
00:29:35.400 — 00:30:18.790 ·Guest: Valerie Martin
Wrong again. 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 can get your number. Yes, whatever. Like, forget that. But it's like it's exactly the same. It's like, what is the context?
Where is 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 five whys and having the relationship, like you just said, that actually influence the decision.
And that's the key point here.
00:30:18.950 — 00:31:39.300 ·Host: Paul Barnhurst
Today's episode is brought to you by our sponsor, Lineas. Lineas 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 an 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 the 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 using AI in kind of an environment. I don't know that anyone's 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. I can see Glen cringing a little bit. Why do I have a hard coded opinion in his head coming?
Oh, that's a good idea.
But no.
00:31:42.740 — 00:33:36.930 ·Co-Host: Glenn Snyder
Paul, you know what? You're spot on. Um, I think you know, some of the challenges with managing people who use AI is that the production happens so fast, they want to move on to the next thing, but you're like, wait, no, you got to slow. One thing is you got to change where you got to tell people to slow down. You, 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 one up and that went down. But that's not insightful right. What's the underlying metric. How do 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 build and you can't just go over and write a, you know, 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 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 market that we work in the government regulatory, you know, 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's not so much about you got to get the numbers out, got to be on time, got to 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 to put that in. At least that's that's my take.
Valerie, what do you think?
00:33:36.970 — 00:33:48.810 ·Guest: Valerie Martin
I think this is right. It's like AI is not going away and you can't be in the sidelines, so it's there. So how do you use it? But balance the benefit and the risk. Um, so I would say is like
00:33:50.250 — 00:34:43.439 ·Guest: Valerie Martin
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? If the 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 you invest in storytelling, how do you build trust? And 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 um al create scenarios. Well, which one is worth discussing and bringing to leadership like your marketing example.
They're like, okay, why? Why should I care about that one? Um, AI could drop a recommendation, but, you know, is it really the right decision and does it make sense? Like, challenge those scenarios and actually train all the above? I think at the end of the day, it's like
00:34:44.720 — 00:34:58.480 ·Guest: Valerie Martin
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.
00:34:58.520 — 00:35:25.200 ·Host: Paul Barnhurst
Great point. And I think 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 FAZ is producing?
Yep. Valerie all the time.
00:35:27.280 — 00:35:28.440 ·Guest: Valerie Martin
Absolutely. Yes.
00:35:28.440 — 00:36:01.430 ·Host: Paul Barnhurst
I've been there too. So there's now you have to really think how can they add more value? 1 a.m. 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 questions never been more important in my mind. And the second thing I think you hit on, I really kind of think of three things.
You got to be able to write the ask questions. You got to be able to audit. We are 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.
The auditor.
00:36:02.030 — 00:37:05.940 ·Host: Paul Barnhurst
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. We were 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 two or more, I think the most critical is one.
How do you make sure they're deeply understanding the operations of the business? If you want 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 you're learning and development is around the soft skills that allow them to be that partner that's going to 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 of my head, because I haven't thought about it this way before.
00:37:05.980 — 00:38:07.500 ·Guest: Valerie Martin
Yeah. And it's interesting because another thing I think we need to think about is like, if you look at our new poll in your generation of a, you know, they're learning, I feel like AI accelerates the learning curve where they sound smart, very quick because AI helps them. Whatevers are 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 doesn't 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 does it always make sense to me anyways.
Um, 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 like my ask for all these leaders is make sure that your analysts 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.
00:38:08.220 — 00:40:21.200 ·Co-Host: Glenn Snyder
I think that the defending part is it's incredibly valuable because when you're presenting the data, you can be challenged on it. You got to be able to defend it. You know, the funny thing is that Paul, when you were talking about, uh, you know, the the focus on soft skills and value, what you were just going to I it made me think of the progression.
Someone has an A, right. You start off as an analyst and 95% of your job is technical, 5% 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 the soft skill side. You go to senior manager and it's probably 7030. You get to a director, it's about 5050 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 in your career, it's not the technical skills that's going to advance you. It's to 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 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 the 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 managing. 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, it makes sure that they understand and how to 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.
00:40:21.240 — 00:40:25.960 ·Guest: Valerie Martin
No, it's your take. But let me make it even more realistic or scarier, because that's the reality.
00:40:27.360 — 00:41:03.200 ·Guest: Valerie Martin
No, I'm not going to talk about Terminators, but I could talk about how you could be scarier. Um, but if I assume this right, AI produced similar resorts for everybody. Everybody has the same tool. Everything spits it out. Like, what's your differentiation factor? Think about it. So two people have the exact same data, same report rate AI.
The better 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 you your curiosity, your judgment and the understanding of the business that will make it more valuable. And it sells.
00:41:03.240 — 00:41:06.800 ·Co-Host: Glenn Snyder
Yeah. And then again, I'd add that fourth pillar of how you communicate it out.
00:41:06.840 — 00:41:09.000 ·Guest: Valerie Martin
Yeah, I will get it in after.
00:41:09.280 — 00:41:09.800 ·Co-Host: Glenn Snyder
You got it.
00:41:11.160 — 00:41:12.960 ·Guest: Valerie Martin
Absolutely. Yeah.
00:41:13.040 — 00:41:15.400 ·Host: Paul Barnhurst
Glenn just likes to talk about communication.
00:41:15.480 — 00:41:21.760 ·Guest: Valerie Martin
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.
00:41:21.760 — 00:41:26.760 ·Host: Paul Barnhurst
We need the base layer. It's not a pillar. It's the foundation. How's that? So, yeah.
00:41:26.960 — 00:41:31.560 ·Co-Host: Glenn Snyder
I'm actually laying that foundation for my hard coded opinion that's coming up.
00:41:32.520 — 00:41:42.910 ·Host: Paul Barnhurst
I'm not surprised. I I'm excited to hear it. So there's a tease for everybody although. I'll. Then I'll stick it at the beginning and everybody will be confused when they listen. That's right.
00:41:43.670 — 00:41:46.190 ·Co-Host: Glenn Snyder
This is what happens when you put things out of order. Yeah.
00:41:46.350 — 00:41:51.750 ·Host: Paul Barnhurst
No, I know put it at the I'm just having fun. So at the end there will be a hard coded opinion for everyone. Um,
00:41:52.830 — 00:42:48.100 ·Host: Paul Barnhurst
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, you know, the soft skills have always been important. They become important earlier.
And the hiding behind why I just need to master my technical skills is going to become less of an excuse and less of an ability. Not that you say technical 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?
00:42:48.300 — 00:42:50.980 ·Guest: Valerie Martin
Uh, every day, like every hour. I'm old.
00:42:51.220 — 00:42:55.900 ·Host: Paul Barnhurst
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.
00:42:56.220 — 00:43:05.660 ·Guest: Valerie Martin
Oh, my God. I use AI for cooking. I think I picture in my fridge and I say, what do I do today? And I'm like, they just give the recipes for me. I use AI for cooking.
00:43:05.860 — 00:43:08.620 ·Host: Paul Barnhurst
Yeah, I mean, great example. Glenn, is there something for you?
00:43:09.180 — 00:43:24.500 ·Co-Host: Glenn Snyder
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.
00:43:24.540 — 00:43:29.300 ·Host: Paul Barnhurst
Anything in your personal life you're using AI for that you like? Wow, so much easier now AI.
00:43:29.340 — 00:43:42.500 ·Co-Host: Glenn Snyder
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 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 yourself.
00:43:42.540 — 00:44:43.610 ·Host: Paul Barnhurst
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 automate. 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 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. They 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?
00:44:43.770 — 00:45:21.410 ·Guest: Valerie Martin
For me, it's always like looking at a process and you decomposed it. So really understanding what can AI will come and introduce and go watch what do we need to get our control 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 is 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 a leader. It's part of our job is just taking more percentage points, as we mentioned that we did before.
00:45:21.450 — 00:45:25.010 ·Co-Host: Glenn Snyder
Yeah. You know, I mean, for me, I look at it as
00:45:26.170 — 00:46:10.800 ·Co-Host: Glenn Snyder
how are you now strategically having an impact not with the data, but with the ideas. And how are you presenting it? You know, it's 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 a nirvana to me, right? That's that's where you want to get to. And it was, you know, it was not only just 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 kind of feel like Rickey Henderson a little bit.
00:46:10.840 — 00:46:12.880 ·Host: Paul Barnhurst
I just say Carmelo, he's a third person guy.
00:46:15.120 — 00:46:41.920 ·Co-Host: Glenn Snyder
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.
00:46:41.960 — 00:46:56.400 ·Guest: Valerie Martin
And it comes back to, you know, I think my original what makes FP&A great, right. How 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.
00:46:56.400 — 00:47:14.440 ·Co-Host: Glenn Snyder
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 acknowledgment that the person that wants you right there next to them.
00:47:14.600 — 00:47:16.000 ·Guest: Valerie Martin
You've earned that seat.
00:47:16.040 — 00:47:16.640 ·Co-Host: Glenn Snyder
Exactly.
00:47:16.680 — 00:47:18.480 ·Host: Paul Barnhurst
We've now hit Nirvana.
00:47:18.760 — 00:47:21.760 ·Co-Host: Glenn Snyder
That's right. And a nirvana. A great place to be.
00:47:23.320 — 00:47:43.550 ·Host: Paul Barnhurst
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 Glen, and I'll share a few thoughts. How do FP professionals, whether it's leader managers, wherever you want to take, that make themselves invaluable in this era?
00:47:43.590 — 00:48:14.630 ·Guest: Valerie Martin
I think it's to be curious. You know, like, be curious, ask questions, thinks differently. Everything's possible, but actually lean in. Don't like I control it. This is which problem we'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.
00:48:14.670 — 00:49:23.900 ·Co-Host: Glenn Snyder
In fact, by the way, Paul Little flashback when Valerie said, be curious. First thing I thought about a year ago, we were talking about private equity in the impact. And you asked a question, what's the number one thing that you that private equity looks for in a person? And the answer was curiosity. So I think there you go.
I mean, and I think Valerie, that's, that's I mean, it's curiosity and I think it's connection. I think that would 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. It's 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, 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.
00:49:23.940 — 00:50:35.530 ·Host: Paul Barnhurst
I'm going to go in a totally different direction, because I think both of what you said is really well said, and I don't want to repeat it. One thing, especially right now that I recommend for 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 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 Glen and Valerie talked about where you can add that huge value.
00:50:35.570 — 00:51:03.770 ·Co-Host: Glenn Snyder
And Paul, just to add to that, I think a lot of people today in their 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 that.
00:51:03.810 — 00:51:10.530 ·Host: Paul Barnhurst
You're not going to get good intelligence from AI, because if you give a good context, the output is much better and good data.
00:51:10.570 — 00:51:17.570 ·Guest: Valerie Martin
Context layer is super huge. So but you need the data foundation and how it's architect to add the context layer for sure.
00:51:17.610 — 00:51:26.840 ·Host: Paul Barnhurst
All right. Well I think we'll call it there. Any last thoughts? Anything you want to leave the audience with before we, uh, thank you and let you go to enjoy your weekend, Valerie.
00:51:26.840 — 00:51:38.600 ·Guest: Valerie Martin
Well, enjoy this podcast. I hope everybody enjoy 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 is an amazing spot to be today.
00:51:38.640 — 00:51:45.760 ·Host: Paul Barnhurst
So I think that's a great note to end it on. Any last words from our our wise sage Glen, our friend.
00:51:45.800 — 00:52:15.120 ·Co-Host: Glenn Snyder
Although you should always be watching out for when AI is trying to do the extinction event, but regardless, you should be looking at 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 reporting, 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.
00:52:15.200 — 00:52:17.360 ·Guest: Valerie Martin
And tracking skills. Thank you.
00:52:17.920 — 00:52:19.480 · Speaker 9
On that note, everybody watch.
00:52:19.520 — 00:52:25.840 ·Host: Paul Barnhurst
AI, we hope we don't have an extinction event before this episode is released. And thanks for joining us.
00:52:27.160 — 00:52:27.800 ·Guest: Valerie Martin
Bye.
00:52:28.560 — 00:52:50.000 ·Host: Paul Barnhurst
That's it for today's episode of FP&A Unlocked. If you enjoy FP&A Unlocked, please take a moment to leave a five-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.