How AI is Being Used to Make Better Decisions and Build Faster Models with Nicholas Moen
In this episode of FP&A Unlocked, Paul Barnhurst sits down with Nicholas Moen, CMA and Director of Finance at Section, an AI software company. Nicholas shares insights on leveraging AI in FP&A to streamline financial modeling, automate workflows, improve decision-making, and build high-performing teams. He discusses practical strategies for training finance teams, balancing human oversight with AI automation, and applying FP&A insights to drive operational impact in enterprise organizations.
Nicholas Moen is a CMA and finance leader at Section, where he reinvents finance through AI, helping organizations build AI-powered workflows at scale. Based in Franklin, Pennsylvania, Nicholas specializes in leveraging AI to streamline FP&A processes, automate workflows, and empower finance teams to focus on strategic decision-making.
Expect to Learn:
How AI frees FP&A teams from manual work
Automating reports, spreadsheets, and workflows
Training and empowering teams on AI tools
Key FP&A skills: business partnering, listening, and data understanding
Here are a few relevant quotes from the episode:
"Context is everything. Using AI to capture meeting insights and key assumptions helps teams make smarter, faster decisions." - Nicholas Moen
"A strong FP&A professional understands both data structures and business partnering, skills that AI cannot replace." - Nicholas Moen
Nicholas Moen demonstrates how AI is reshaping the role of FP&A, allowing teams to focus on strategic decision-making instead of manual tasks. By leveraging tools like Claude and Lovable, finance professionals can automate workflows, build models faster, and make more informed business decisions.
Follow Nicholas:
LinkedIn: https://www.linkedin.com/in/nicholas-moen-320a11106/Substack: https://substack.com/@runningfinance
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[02:56] – What great FP&A looks like today[05:14] – Automating spreadsheets with Claude[14:31] – Building micro-apps with Lovable[17:58] – Commission automation[21:26] – Doing analysis on the go[30:12] – Low-hanging AI wins for FP&A[33:58] – Training and knowledge sharing[38:41] – Top soft and technical skills[41:35] – Personal side: music and hobbies[45:53] – How to connect with Nicholas[47:19] – Closing thoughts
Full Show Transcript:
Host: Paul Barnhurst (00:00):
Welcome to FP&A Unlocked. I'm your host, Paul Barnhurst, and this podcast is all about fp and a. It's where finance meets strategy. Each week we bring you conversations and practical advice from thought leaders, industry experts, and practitioners who are reshaping the role of FP&A in today's business world. Speaking of strategic impact we have here with us today, Nick Moen. Nick, welcome to the show. Thanks
Guest: Nicholas Moen (00:31):
For having me.
Host: Paul Barnhurst (00:32):
Very excited to have you. So we're continuing our series. For those who are wondering around ai, we got a lot of episodes where we're going to be talking about people that are leaning in heavily to ai. So before I get into that, let's go ahead and introduce Nick, share a little bit of his bio and his background. So Nick Mon is a CMA and director of finance at section and AI software company that helps enterprises, enterprise organisations deploy AI to their workforces. At section, Nick runs finance people, ops and operations, actively deploying AgTech workflows and an AI native tech stack across all three functions, rethinking how each operates before section. Nick spent nearly six years as a finance operator at Waste Technology Company where he built and scaled financial systems and teams across the combined hardware, software and services model. He has a track record of seeing through operational complexity, identifying bottlenecks and building systems to eliminate them. Love the background and once again, welcome.
Guest: Nicholas Moen (01:45):
Thank you.
Host: Paul Barnhurst (01:47):
Alrighty. We're going to start with this question. I always love to see how people answer it. In your opinion, or from your view, what does great FP&A look like? How would you define it?
Guest: Nicholas Moen (01:56):
I think nowadays the question, the answer to it is a bit of a moving target. And what I mean by that is I feel like with AI and how it's rapidly iterating, I remember when Opus on Claude Opus 4.6 came out, I was not using Claude, I was using a different model and I wasn't really doing as much finance, but Opus 4.6 really transformed how I interact with finances and it's almost completely reoriented how I work. So I'm going a bit long way around this, but even in the past five years I've worked, I've gotten a little bit more removed, especially with AI from the day-to-day weeds, maybe Excel spreadsheet building or anything like that, and moving more and more towards essentially the decision framework of fp a. So what I think fp a, this has kind of always been what fp a has been about, but I think it's more about is how can we reach the right decisions and information in the business?
(03:01):
And AI is really pushing us to that. So in my mind, great FP&A today is what great fp a always been, but just less of the modelling, more of the analysis, deciding what the decisions are, what are the key levers to the business, and just rapidly getting there more quickly and just focusing more on that. And I think it's just going to continue to be pushing teams into that direction as AI just gets more advanced because one, the business is just going to move faster too because finance is not the only part that's getting impacted by ai. And if AI is like velocity, you can do more quicker, that's going to impact the rest of the business. And I mean if you worked alongside marketing sales, the more high velocity teams as finance, you always, I dunno me, sometimes I feel like I'm trying to keep up, they're going to move faster too. So I think fp a teams will need to move faster to keep up with the rest of the business, but they will be able to and I think the AI will be a good equaliser between that. So in my mind, a great FP&A is back to what FP&A is on a fundamental level, which is business partnering and be able to be in lockstep with the rest of the business. And I honestly think that AI is going to be the almost catalyst to that. Yeah,
Host: Paul Barnhurst (04:30):
I've heard a lot of people say something similar of it really allows us to focus on what we should have been focusing on all along and less of the data prep and the cleaning and all the fun things that we all enjoy. Right.
Guest: Nicholas Moen (04:41):
I love it too. Yeah, I love doing that stuff and it's like a bittersweet, it's like you're kind of giving it up, but at the same time you're kind of doing what really drives the value too.
Host: Paul Barnhurst (04:52):
It's exciting for sure. All right, let's get into AI and Claude, you talked about AI as a velocity tool, so when you and I chatted, and I want to start with this question, you mentioned that you haven't used a spreadsheet for a new analysis in a few months, I think you said since January or something, but basically since you began using Claude, talk about that.
Guest: Nicholas Moen (05:14):
I would say again, it was like Opus 4.6 was the turning point for me. I stopped making spreadsheets and I didn't stop using them. I stopped making them and at a certain point I just started asking Claude to make them. Now I gave it all the information, all the context it needs, but I've started to realise that what Claude's, the first version it makes is actually pretty good, especially if you tell it the right things, you kind of have to treat it like an intern still maybe not even an intern. I think it's gotten a little better than if you grade these competencies based off it might be the junior
Host: Paul Barnhurst (05:52):
Analyst
Guest: Nicholas Moen (05:52):
Or whatever. Yeah, it's more of a junior role now. It's kind of getting a little bit more smart. It's done with college, it kind of has a few reps under its belt and it's like you can probably give it a task and can give some fairly coherent. Yeah, I think it's at that point now,
(06:08):
I don't think it actually nails it right out of the gate. Usually I have to take the last mile, it gets me 80% of the way there and then I bring it into a spreadsheet and we use Google sheets, so I bring it to Google Sheets and modify it, challenge the assumptions, maybe tweak the assumptions, maybe fix some kind of dumb formulas that it did. But I think for the most part it does a lot of the bones and the framing quite well, and that's time. If you open up a new spreadsheet, you have to build that. And I'm assuming you've done a lot of modelling and I'm sure a lot of people listening have done a lot of modelling. Those framings are not exciting work or anything like that. Building out your assumption rows and your tabs and all that, and especially if you can give Claude your way of modelling, you can especially replicate that.
(07:04):
It can build that version one for you and then you can take it and mount it from there. And it's a meaningful amount of time and especially when I'm building and I kind of have an idea of what I need to model, but it's not fully formed, so it helps me talk it out. With Claude, I kind of go back and forth, it gives me a mockup and I'm like, no, that's not it. That's not it. That's not it. I need to, what if we change this variable? Like no, we need to rethink how we waterfall this out. I was actually doing that today and it can reiterate and even rebuild an entire model a lot quicker than I could rebuild an entire model. So if I just start off a bad way of my assumptions were just all wrong and then when we built it out, it's like, no, this is not working.
(07:50):
We need to go. It can just take it apart and rebuild it a lot faster than I can. Then when I feel like I actually have something good, then I bring it out over and then I own the spreadsheet. Especially if it's a reoccurring model, then I refine it, I get the formatting correctly. I always say cloud is still bad on the formatting. It's really bad in formatting actually, but that's okay. That's an easy fix. I can do that part and I'm still doing that. I still haven't had a reason to change that method. It allows me to build things a lot more quickly.
Host: Paul Barnhurst (08:17):
And how much time do you spend validating? Because we all know Claude or any AI makes mistakes. How do you think about that with all of it? Yeah,
Guest: Nicholas Moen (08:25):
I think that's a good question. I spend a good amount of time validating, but I put it kind of on a sliding scale of who is using this information and what decisions is it driving If it's pretty low stakes, yeah, I'll go look through the assumptions and make sure the formulas tie on everything like that. But if this is for, let's do an extreme example. If this is for reporting numbers to the board or CEO, yeah, I'm probably going to date pretty hard and just check everything else out. But I'd be doing the same thing with any employee as well. I kind see that the same thing and really it's a balancing act of how high stakes is this information. There's just how thorough you need to be because one thing else I do is I'll take the model and have Claude or you could use chat PT or anything and I'll tell it, okay, now go check your work.
(09:21):
Go look at everything, go look at the formulas and it actually does come back. It's like, oh, I made a mistake. Let me go fix that real quick. And then you do that a few more times and say, okay, now go check your mistakes. Go review your work. You can even copy and paste the prompt and it's going to keep doing it over and over again. Eventually you'll say, yeah, everything looks good, and then you can take that and then you could maybe save yourself some, you could still check everything. You're still going to want to check everything, but it's going to be pretty clear, especially if you tell it to design it in a more, I'm very much a fan of the KISS principle. I want to keep things as simple as possible because it makes it as easy to audit. So if you have a design, it's also a lot easier to validate everything as well, especially if you have the assumptions flow instead of having one, the heath of a formula
Host: Paul Barnhurst (10:06):
Makes sense and yeah, no, I've heard someone else say to me, if you're using ai, make sure you ask it to check itself at least three times for model building. It kind of goes in line with what you said and it will find mistakes and get better. We asked one to figure out early on, none of them could tell me why the balance sheet didn't balance and we'd always ask them to correct it. Favourite answer I got along the way was your balance sheet is out by 1.2 million. That's only 30 basis points. That's an acceptable error rate. No, you don't understand how balance sheet works. That is not acceptable. You're
Guest: Nicholas Moen (10:44):
No longer the balance sheet.
Host: Paul Barnhurst (10:46):
You are fired. Actually, I think it was early, they may have been using Claude. It wasn't Claude's Excel, but they were using one of their early models and this was six months ago now, but it even been a little longer and it was like, oh boy, we got a ways to go if this is the type of answers we're getting.
Guest: Nicholas Moen (11:02):
Yeah. Oh, one thing is actually, I got this from our CTO and I quite love this prompt is he just simply says, what would you do if you were me? Simple thing, and especially since these tools are kind of understanding who you are as a person, the more they use it, they kind of understand you. They know, Hey, I'm Nick, director of finance, and it kind of gets my analytical profile and it'll just run through the same things, but maybe it'll take it from my perspective, kind of like that prompting method where you sign a persona, you're kind of doing that in a way of assigning your persona to Claude or chat GPT, and then it's going to take that approach and think of it from what it thinks my perspective is and then again, copy and paste that three more times and it's going to keep running it through and running through. It's actually quite effective. One of those classes cases is a very simple thing you can say That's very powerful.
Host: Paul Barnhurst (11:48):
I haven't tried that exact one, so I'll have to give that a try. I was already thinking in my head, I'm wondering what I would say about this. So thank you for that. That's a good one. The other one is just I'm reminded to keep checking and so I think we will keep going here, but it sounds like in the spreadsheet, your advice to people is just start using AI to help you build.
Guest: Nicholas Moen (12:07):
I think that really what it comes down to is like don't try to boil the ocean. Don't take your most complicated thing and try to have AI do it. Keep that to yourself, that's okay, make that your special sauce, but try to eliminate all those little things that you don't maybe are not as value add. It doesn't even need to be fp and a. It could be your emails, get an agent to run through your emails. It could be having it summarise If you have Slack and you integrate with Slack, have it summarise your Slack messages for the day, maybe teams, anything that's not so to speak to that special sauce, try to get rid of that so you can focus on those things that are really valuable, especially if going back to what great fp a looks like, anything that gets you closer to business partnering. I think that's really how, in a great way to start using AI is try to eliminate those. It might be five minutes here, might be 10 minutes there, maybe 30 minutes there, but all those minutes add up to hours over the course of the month, which gives you more time to actually put your brain power to something that's actually valuable and that requires brain power.
Host: Paul Barnhurst (13:18):
That's good advice. I know you mentioned you've been using Claude Code and lovable quite a bit. Had you ever written code before you started using them?
Guest: Nicholas Moen (13:27):
I was fine. Decent FVBA, not going to say I'm the best enough to kind of hack together solutions, struggled through S-Q-L-S-Q-L enough to accomplish a few projects, but I'm not going to say I could probably look at SKO code and be that looks like gibberish nowadays. Other than that, no, I don't code. I've never really had strong desire to learn. Yeah, so with Vibe coding, I know it's making code. I don't know what it kind of means. I could probably read some variables, especially with this string text, you could probably work your way backwards and I've modified string text, but yeah, I'm not a coder by any means and nor would I ever claim to be one.
Host: Paul Barnhurst (14:13):
So what made you decide, Hey, I'm going to try to code some stuff. Was there a need where you thought, Hey, this is supposed to be good enough, I can solve a problem, or it was just like, Hey, this looks interesting. So how did you decide, hey, coding using lovable others could potentially help me in my work?
Guest: Nicholas Moen (14:31):
Yeah, I was given a lovable subscription, so I decided to try to use it. The real story is it was, it was an AI summit and they had a vibe coding like here's lovable and we're going to vibe code. And it's like, okay, well I'm here, I'm going to do it. And I was blown away that I could have a mockup app in five minutes of prompting and I'm talking like an actual SaaS app now. It was a mockup. It's nothing production. It was I believe what is, is it inventory tracker for my sister's nonprofit where she clicks baby supplies for families that need it and she has a bunch of supplies and just random bits and end, but she doesn't have a way to track it. So this isn't a Google sheet, and it was kind of a mess. I'm like, Hey, this is a great use case.
(15:16):
It's pretty low stakes and let's see if I can get some inventory tracking. It did it so well and I was like, this is crazy. It is so easy. And then to iterate on it, if you're using chat GPT or Claude, you can use lovable. It's the exact same method. It's just this exact same prompting methodology and just because it's writing code is not really any way to be intimidated by it. It's doing that for you. You don't even have to worry about it. I'm not going to say the code's great. I've heard from engineers I've talked to, it's not good code. So if you're trying to make it like an app to sell to the world, you may want an engineer to take that code and make it not breakable. Sure,
Host: Paul Barnhurst (16:00):
You might want to treat it as an MVP.
Guest: Nicholas Moen (16:03):
Exactly.
Host: Paul Barnhurst (16:04):
Or a wire frame or
Guest: Nicholas Moen (16:06):
Whatever you want
Host: Paul Barnhurst (16:06):
To call it, but not production ready, so to speak.
Guest: Nicholas Moen (16:10):
Right, exactly. And there may be a time when it gets there. I don't think it's that time right now, especially if people are going to pay you money for the app, but it's pretty simple and pretty quick to use. I think for me it was starting because it felt intimidating. It's like I can't build an app that's not my skillset. And then when I did one in five minutes, I'm like, oh, I can build an app. This is different. This is way different. Yeah,
Host: Paul Barnhurst (16:40):
No, makes a lot of sense. So you ended up building a commission software for the company. How long did that take you?
Guest: Nicholas Moen (16:47):
Less than 60 minutes, honestly.
Host: Paul Barnhurst (16:50):
And how often are you using it?
Guest: Nicholas Moen (16:52):
We use it every commission cycle now. It completely calculates our commissions.
Host: Paul Barnhurst (16:57):
FP&A guy here, ag agentic AI is one of the biggest shifts in finance ever, and most FP&A leaders are still struggling to figure it out. On May 21st. I'm hosting the FP&A and AI software showcase with two of the leading AI agents in the marketplace, Concourse and sapien plus leading planning tools, drivetrain and Una ai one sitting real demos register at the fp a guy.com/fpa software showcase. That's FP&A guy.com/fpa software showcase. See you on the 21st. And did an engineer have to do any coding with it or you did a hundred percent of it? Is it sitting in the cloud? Talk a little bit about that.
Guest: Nicholas Moen (17:52):
Yeah, so what we did and we're iterating on it, but so you're not going to
Host: Paul Barnhurst (17:58):
Claim it's perfect.
Guest: Nicholas Moen (18:00):
No, it's not perfect. The calculations are perfect. I'm going to make that clear. Our reps are being paid accurately. But that being said, I would say the app is not good
Host: Paul Barnhurst (18:10):
Clarification point
Guest: Nicholas Moen (18:11):
For
Host: Paul Barnhurst (18:11):
Reps listening right now going what
Guest: Nicholas Moen (18:15):
The apps are good for me to use. I would not give it to somebody else because it's a bit more of my brain as an app and no one wants that. But that being said, how I actually went about it is, I don't want to say it's a simple commission structure, but it's a very nuanced one and there's multiple triggers. I, I actually did this at two part, mostly because lovable has more expensive to use, but I gave Claude our commission agreement and basically pull the calculations out and the triggers, analyse it, understand it, then give me a prompt that I can give to lovable. I did actually say lovable. It gave me a prompt, took that prompt copy paste in the lovable and lovable gave me basically something that was accurate in the first prompt, but it wasn't quite what I needed to be because I couldn't finesse it as I need.
(19:05):
I hard coded the rates, I didn't want hard code rates, so I want to be able to change those. So this would've been a very complicated workbook to make and that's actually what kind of started it is I started making the workbook and I'm like, I don't want to do this. This is so much I would have to do this per rep and there's just so much I'd have to build out. This is at least 300 rows. So I'm like, you know what? Let's try it. At worst, I'm 30 minutes out of my day if it doesn't work. But if it does work, I am sitting pretty. So I gave it to Claude and gave it to Lovable and I'm like, this is way easier.
Host: Paul Barnhurst (19:39):
No, yeah, I'm already thinking of, I've been meaning to, there's two things. I'm wanting to divide code and I just need to sit down and do it.
Guest: Nicholas Moen (19:47):
What are those things?
Host: Paul Barnhurst (19:48):
They're not fp a things, they're just some stuff for my business, some
Guest: Nicholas Moen (19:52):
Process
Host: Paul Barnhurst (19:52):
Things, something I want to get on my website. Basically some questions you'd fill out and it would give you different options type of things, see what kind of questionnaires to give you options. So
Guest: Nicholas Moen (20:05):
Yeah, that's a great use case for it as well. Yeah,
Host: Paul Barnhurst (20:08):
No, I think it'll be good. I have the data now. I've done a lot of the work on all the backend stuff and I'm like, okay, I'm sure it could help write some of the logic and just work through it all and see what I can build. It's just time. You know how it is. You just got to sit down and do it. We all pick where we spend our time and I haven't spent enough time on it.
Guest: Nicholas Moen (20:27):
And I think the touch is a good point. What's great about a tool like Lovable, you can use cloud for this as well. This is what I challenged my team to use this stuff for is lovable is great from making that micro app that's completely bespoke to who you are. So if you have that one process that's just uniquely you, and I wish there was software for this, but no one's going to make it. That's what lovable can do. It can make those little SAS apps that you've always wanted but never could have because no one's going to build it. There's not a big enough market for it and an engineer's not going to build it for you internally because it's just so nuanced and bespoke. That's where I'm finding a lot of power in it. It's just something I need this automated, especially with agents nowadays, agents also kind of filling that gap as well.
Host: Paul Barnhurst (21:12):
Alright, so when you and I chatted a few weeks ago, you mentioned you finished an analysis for the CEO using Claude on your phone while putting your son to bed. Tell us the story.
Guest: Nicholas Moen (21:26):
Yeah, so this was classic end of day request. It's like, okay, I was going to log off and go make dinner. Obviously I realised that this needs to be done.
Host: Paul Barnhurst (21:39):
Yep. They wanted it yesterday,
Guest: Nicholas Moen (21:42):
Right? Yep. So what I did was it wasn't one of those things where it's like, okay, I'm going to just get this done in 30 minutes. This was a pretty massive deep dive in our model assumptions. So I gave Claude all the documents it would need that's on my computer. I gave it our model, I gave it other supporting documents, anything that it would need to have for this analysis, had it as a conversation. And then I closed my laptop, made dinner, played with the kids for the evening. My youngest is two, so we still put him to bed and any 2-year-old, he lays there awake for an hour, just not going to sleep. So I knew that, okay, I had all the context I needed in the chat, so I pull out my phone and I just start prompting. It has the context, so now let's work through the analysis.
(22:30):
So I'm just telling it, this is how you analyse it, this is how you should look at it and now build the spreadsheet. And I'm reviewing the spreadsheet on my phone and that was painful, but I wasn't typing in at least and I was understanding the assumptions, the model redoing it. Essentially we were supposed to, we wanted to view some cost assumptions and buckets. We didn't really have it modelled out and viewed. They basically just described everything it needs to think through and how it can pull the assumptions, where it can pull the assumptions and how it can organise those assumptions better based off the vendor or the supposed vendor. Then structure that into an output that I can give back to the CEO. That's a bit more to the point. Cut all the fluff and get to the point. And I did that over the course of just the night just putting my son to bed. I didn't need my laptop or anything. I think that to me was like, this is a completely different way to work. I never thought I could do a full financial analysis on my phone. You got to get creative when you have kids.
Host: Paul Barnhurst (23:32):
What can I say? I do have a daughter but a little older now. She's 13, so she puts herself to bed. What's your thoughts on the whole idea of AI is going to take our jobs?
Guest: Nicholas Moen (23:41):
I think the answer is nuance. I feel like that's just a bad framing in general. I'm not going to say it's not going to eliminate jobs, of course it's going to eliminate jobs, but I think it's not as simple as it's just going to completely decimate work. And to be clear, I think any company right now that's saying, oh, we eliminated so many jobs, so we're layoffs because of ai, that's false. They just overhired. That's not the case. They're just using, they found a serendipitous moment where they could have a reasonable excuse to just lay off 20,000 people.
Host: Paul Barnhurst (24:15):
I said that was my view on when Square did that, a lot of people disagreed with me. Some agreed I could believe there's some that are due to ai, but when you're making huge cuts and saying it's all ai, you overhired, so I'm mostly with you. I think it's nuance, but yes, there's definitely an OVERHIRE component.
Guest: Nicholas Moen (24:39):
No, I do think they have AI gains and maybe some of those rules were actually cut because of ai, but
Host: Paul Barnhurst (24:49):
Not 50%.
Guest: Nicholas Moen (24:51):
No, I don't think so. I would be very interested in how they've utilised ai. If they cut 50% of their workforce,
Host: Paul Barnhurst (24:57):
I would as well, and I agree with you. I mean, I talked to somebody who is very close in the investment banking industry and he is talking to the banks all the time and he said right now they can't eliminate a single position because of ai. Now they have people that are all being more efficient, but they're not at a point where they could actually cut people. Now will they get there? I'd say yes. I think most areas will get where there could be cuts, but this idea that huge layoffs are all due ai, I'm with you.
Guest: Nicholas Moen (25:22):
I
Host: Paul Barnhurst (25:22):
Don't buy it. I think that's a messaging versus reality for the most part.
Guest: Nicholas Moen (25:26):
I think where the answer gets more nuanced is I think it's going to have a reckoning on entry level work.
Host: Paul Barnhurst (25:34):
Yes, I've had a lot of discussion around that
Guest: Nicholas Moen (25:37):
And I think it's going to be a question I think collectively as people, how we've figured that one out because obviously if you don't have internet entry level workers coming in, you don't have people to train up to be back into the middle career and senior career, so you basically s the top of the funnel, so there's nothing going in the funnel. I don't think I have an answer to that very hard answer to find because what a lot of AI is really good at nowadays is the entry level work.
Host: Paul Barnhurst (26:07):
Yeah, no, I've said, okay, there has to be some changes the way we do education. There's a question of how much time you have to invest in somebody and fundamentals, what does that look like? If you think of a lot of skill trades, you do an apprenticeship for several years, is there almost going to be some kind of apprenticeship type thing where you're working along a IC? You get those good fundamentals. It'll be interesting to see, but I'm with you. Something has to change. I don't know the answer either, but it's a fascinating thing to discuss and to think about because I think education has to change. I think for many companies that entry hiring also has to change how much of each, what does that final look like? I don't know. I don't think anyone knows yet.
Guest: Nicholas Moen (26:53):
I think to the point entry level work exists, you just raise the floor to be more complicated. Of course, then you have the problem of having people, the skill sets to do that. The apprenticeship is a very interesting concept and I'd be willing to bet that companies would be more and more interested in that as a recruiting tactic. It's not like, oh, we're going to just take these unskilled people and get no value from them. It's very much an intentional investment approach, and I think you see that with bigger companies that have rotational job programmes for new workers and stuff like that. They exist. It's probably just going to have to be more of it.
Host: Paul Barnhurst (27:28):
I mean, it also creates a little more risk in that the younger workforce turns jobs a lot more than we used to historically, and if that first year you're getting less value, you really want to, you're taking more risk in the sense of knowing they could leave early. So it'll be interesting to see how they work through all that.
Guest: Nicholas Moen (27:46):
And at this point we're getting out of finance talking more into talent retention, but I think that's to your point though, it becomes a function of how do you retain talent? Now you got to be a bit more competitive,
Host: Paul Barnhurst (27:58):
But at the end of the day, I mean it's an fp a show and many of us lead people, so these are things we have to start thinking about on fp a as well. But definitely we've got a little out of the typical lane, but I'm trying to bring it back.
Guest: Nicholas Moen (28:11):
Yeah, yeah. Well, I think even for my team, I do think very consciously in how to keep them retained and keep them engaged. A lot of work to recruit and retain very exceptional people.
Host: Paul Barnhurst (28:22):
Hiring people is expensive and it's easy enough to make mistakes. You don't want it to compound, and so you got to think about these things
Guest: Nicholas Moen (28:31):
And I think that's what AI is going to push us more into as well, especially as senior leaders is we're going to have to think more about our teams too. We already do, but I think we're going to have to do more of it, especially in the early days where we especially have to, if people are good at ai, we wanted to make sure we want to keep them because it's harder to replace that. Maybe over time that will normalise a little bit, but
Host: Paul Barnhurst (28:54):
Sure, right now it's like anything early computer, early spreadsheet, there's a new technology. You want to keep that person that knows it well because it's going to be hard to replace them five years from now. It could be a very different story,
Guest: Nicholas Moen (29:05):
Chaotic time. It's got to change the frameworks every six months.
Host: Paul Barnhurst (29:09):
It's a time of incredible change. It's part of me is like, man, I would love to be working for somebody and automating and seeing all this. And there's another part of me who was like, no, I wouldn't. I was saying that the other day. That is someone explaining to me the stuff he's doing with Claude. He has to be in the one 10th of 1% of finance people if not even higher. I mean, the way he's thinking about the stuff he's doing is just off the charts and it's like, that would be really cool. And then I'm like, that'd be a tonne of work, but I'm figuring out more and more use cases. So speaking about use cases, I want to ask a question here on that and then we're going to go back to training for a minute, but in a little different aspect to talking about the whole new employees. So what's the one workflow that you think every FP&A person should automate first? Where would you say they should start? I mean obviously I know it's not going to apply to everybody, but what's kind of that low hanging fruit that you say, if you're not doing this, try it.
Guest: Nicholas Moen (30:12):
This might be a little bit of a different answer, but for me, context is everything, especially when I'm building assumptions, trying to understand things. So getting a lot of the business partnering. So one thing that I utilise a lot is a software called granola, and I mean I think we've all been on calls, sales calls or any type of call where a bot comes in and just records everything.
Host: Paul Barnhurst (30:38):
Yeah, I join every call now and there's usually some note taker before there's a person. I'm like, I'm here with your three AI tools, thanks for joining.
Guest: Nicholas Moen (30:45):
Yeah, they're five minutes late, so you're just kind of sitting awkwardly with the robot. I
Host: Paul Barnhurst (30:49):
Start saying things to it. I hate to see if they notice.
Guest: Nicholas Moen (30:53):
Yeah, test their recap notes, but granola is a little bit different. It sits on your machine and it transcribes, so it doesn't actually need access to the meeting. I'm assuming it takes in the audio for the meeting and just transcribes it and it's actually pretty good. It's actually really accurate. And one thing I like about is just completely agnostic what you use. So if you need to do a teams call, it's not on your calendar. It'll pick it up and start recording. Why? This is probably one of the most key linchpins pieces of software for me lately is I take all the information I get from granola and feed it back into Claude because they have an MCP, they can connect. I have it query a lot of the context that I pull from meetings, so I don't need to really focus on note taking.
(31:35):
I can just be engaged with the conversation. I mean, today I was building out an assumption model and I already had a lot of conversations about this assumption model. So now that I'm actually building it, I'm querying Claude that's pulling from my granola, get all the conversations and put everything in a neat tidy format so I can just jog my memory. I think that something like that is incredibly helpful for me to be more effective at picking smart assumptions, building out things that are actually impactful to business and more importantly just gets everything grounded back to reality because I can think of all the assumptions and how things should be done, but it's Mike Tyson quote, everybody has a plan until get punched in the face. It's kind of the same with my plan's. Perfect until it hits operational reality and then all the assumptions go topsy-turvy. That to me has probably been the biggest lift for finances. Even if it's not a finance workflow,
Host: Paul Barnhurst (32:28):
I often hear finance leaders say, I know I need FP&A software, but I don't even know where to start. That's why I created the FP&A software showcase. So you could see top tools in action. This year we're featuring drivetrain and UN a AI on the planning side, and for the first time ever, we're adding two leading AI analyst agents on the market, concourse and sapien. These tools are already being deployed at public companies. You will get to see actual demos without the pressure of a formal sales pitch. Ask your questions and compare tools all from the comfort of your chair. Join me on May 21st for the showcase. Register for free at the fp a guy.com/fpa software showcase. That's the fpna guide.com/fpa software showcase. See you there. So I appreciate that. Thanks for sharing that. Let's talk training. How are you training your team? Any tips? I mean obviously you guys have been using this pretty heavily. You have several people kind of rolling into you, so how are you going about training and making sure your finance team is using AI and that you're consistent across the org?
Guest: Nicholas Moen (33:58):
Yeah. Well, I want to qualify this because I'm very fortunate that the company I work at, I know everybody has different security policies, especially depending on how large they are. We're AI transformation company, so naturally we're going to use any AI tool we have because it's a strategic advantage. I have access to a lot of AI tools. That being said, how I get my team to use it more often, I do have advantage that my team is motivated to use it because it's baked into our culture. But tactically, I think one big thing is hackathons, team hackathons, it's a sit down, carve out some time and let's pick lovable as example. It's like you pick a use case that you need start by coding lovable. We'll all do this together, we'll do our own thing. We'll do a show and tell at the end, see which one people like.
(34:50):
And I like this approach for two reasons. Once it gets people actually using it, and I think a lot of part of AI is just people not familiar with it. It's a tool, it's a software, but it's not like traditional SaaS. It's a completely different kind of software. So the only way to get used to it's use it so it gets people used to it. It gets past the point I had with lovable of the starter gun at the beginning of the race. It's like, okay, now when I start running, I can finish the race. It gets people started on it so they feel less intimidated. And then it has, the second thing is it gets people to show what people have made and then you can ask questions, well, why did you do it that way? Or how did you even do that? And then people start knowledge sharing because I think that's the other component of getting your teams trained is you want them to share knowledge.
(35:35):
There is no progress and training if people are hoarding AI knowledge themselves, whether intentionally or intentionally. So knowledge sharing is quite important. It's like, Hey, I did this or I noticed that AI can do this now. And that has almost like a compounding effect on learning because now people, I mean this is also just kind of basic learning principles in general, but when people can work off of each other, they can move a lot more quickly, a lot more fluidly because now let's say you have a team of five and they're all just in isolation using ai, every discovery is just them learning more versus if they learn different discoveries from the four other teammates, now you have five other potential events of discovery on how to use ai. And I think that's a big thing about AI too, is I don't think everyone's quite even fully realised what it's capable of. Yeah,
Host: Paul Barnhurst (36:29):
I would agree. I mean we're still all learning. I don't think anyone who claims they fully understand the capability is lying. That would be my opinion. But
Guest: Nicholas Moen (36:37):
There's people that are quite good at it. I'll give 'em that. But yeah, I think we're seeing where it's an iceberg where we're just seeing the top of it.
Host: Paul Barnhurst (36:44):
Well, it's a lot like Excel. If anyone tells me they understand all the formulas, all the functions, all the languages, they're an expert in everything in Excel, we're call bs now multiply that times 10 for ai. I mean the best in the world is maybe using 20% of Excel. The best in the world might be using two to 3% of probably what all the use cases and capabilities are for ai.
Guest: Nicholas Moen (37:05):
I thought it was pretty good Excel and then I watched the Excel championships. I'm like, I don't think I'm good at Excel.
Host: Paul Barnhurst (37:11):
Yeah, I've interviewed several of the world champions and you want to be humbled on your Excel skills, watch them for about two minutes.
Guest: Nicholas Moen (37:21):
Yeah, I felt that way when I tuned into that, it was a few years ago, I was like, wow, you
Host: Paul Barnhurst (37:26):
Want a great video
Guest: Nicholas Moen (37:27):
Video? I share this
Host: Paul Barnhurst (37:28):
That I'll share this to anybody. So last year's world champion, he's been a world champion before Dim early, dear me at early, he's originally from Ireland, he lives in New York and he's a Microsoft MVP and he recorded a video with Nadella, right? The CEO where he is showing him about the formula he did. He's teaching Nadella Excel and he's looking, he has this look on his face like, wow, you could write something like that, you could do that. It's just a classic, what better promotion video can you have than you are teaching the CEO of Microsoft how to use Excel almost. You could see him just having this look like, wow, you're doing that in Excel.
Guest: Nicholas Moen (38:10):
That'd be a great moment.
Host: Paul Barnhurst (38:11):
Yeah, it's a really good go out on you. Just put it up this week. Go out on LinkedIn and you'll see. Check that out. It's worth watching. It's just two minutes long, but it's a good little video. I know the guy, I've interviewed him, great guy, but we digress there. So there's an example. Alright, so we're getting close to our time, so I'm going to pick a few more questions here. First, I like to ask a couple FP&A questions, so I'm going to ask two and then we're going to get, do a couple get to know you questions. What's the number one soft skill fp a professionals should master?
Guest: Nicholas Moen (38:41):
Yeah, I'm going to give you two answers. Try to make 'em quick. I think the one is kind of obvious is partnerships. AI is going to really stress that we're going to have to be very good partners because that's the one thing AI can't do. I'm still on the belief that people want to talk to people generally, so
Host: Paul Barnhurst (38:55):
I am as well. I agree
Guest: Nicholas Moen (38:56):
With you. Yeah, so I'm banking on that, but I think the other soft skill is learn how to be a product manager because the way, and I've been fortunate to work with product managers, and if you're not in tech, it's just basically the person that helps design the product and gives s schematics to engineering. They take what a customer wants, understands what they need, and then has an engineering to build so a good product manager can build, suss out what a customer needs. AI is very structured to think that way. At least right now it is. It's being able to understand a question behind the question or a need behind the need and essentially ask really smart questions, really think through things in a very nuanced even first principles way and describe things in an articulate, clear manner. You can almost think of your LOM as the engineer, so you need to be able to translate a vision, a thought into something that Claude or Chate can understand and build correctly.
(39:55):
And I think that type of skill will extremely benefit anybody in finance as they're trying to build things, especially having a model being built into a spreadsheet. Prompting is will live or die, how good that model will be. What about technical skill? I still bank that understanding data structure is probably one of the biggest technical skills. Probably even before air, I went pretty hard. I'm no data scientist, but I got pretty good, at least competent enough to navigate data schemas to at least understand it. And I think that's just compounded pretty massively. Just being able to understand how data is structured, especially with AI and be able to structure it so it's context able for ai, it can understand it a bit more clearly. Messy data, it's added garbage in, garbage out, so be able to structure it.
Host: Paul Barnhurst (40:47):
When I'm interviewing people that are using AI a lot, that is becoming a more and more common act or some kind of data thinking systems thinking, understanding data structure, what they all answered in a different way, but that theme, I might've heard it once in the last year. I've now had it three times in the last week and that's scenario I'd always prided myself. I was a little bit more of a data person in FP&A and I'm seeing now, I've always said that's a very important skill and it's just getting raised up the list. It's going to be a non-negotiable hearing. Excel is the number one technical skill. It's really interesting to watch this transition.
Guest: Nicholas Moen (41:25):
Yeah.
Host: Paul Barnhurst (41:26):
All right. We're going to get to know you a little bit and I might tweak some of the questions I have here. I might have a little bit of fun. Are you a music person?
Guest: Nicholas Moen (41:35):
I love to listen to music. I've tried and failed to learn an instrument. I do and do enjoy music theory even if I can't quite grasp it fully.
Host: Paul Barnhurst (41:43):
We'll go with the music question then. You could only listen to one album for the rest of your life. What album are you picking?
Guest: Nicholas Moen (41:51):
This is like, pick my favourite Child.
Host: Paul Barnhurst (41:55):
Yes. What is your favourite child? I'm just kidding. Go
Guest: Nicholas Moen (41:58):
On, let's get that on record then
Host: Paul Barnhurst (41:59):
I'll send this to your wife.
Guest: Nicholas Moen (42:01):
Yeah, I told my kids I'm going to be on YouTube and yeah, let's get that on recording. Yeah, so what's my favourite album? I will say I'm going to do a cheap thing. I would say one of my favourite albums right now that I could listen frequently. I started getting, I just got a record player and started collecting records. The one I'm listening to a lot, black Holes and Revelations by Muse. It's phenomenal on record. I've been listening to Muse for quite some time and it's a great end to end album. You can list it from beginning to end and it's just the story that built itself.
Host: Paul Barnhurst (42:37):
Nice. Alright. This is going to be another kind of fun one, but it's much easier answer even though you haven't prepped Claude a he, she or it.
Guest: Nicholas Moen (42:46):
I think I say it more than anything.
Host: Paul Barnhurst (42:48):
And have you named any of your agents?
Guest: Nicholas Moen (42:51):
Oh, okay. So this is lame to admit. I have an agent that helps me fill out bank forms because I got sick of writing bank forms for vendors, or excuse me, customers. So I made an agent that could fill out the forms for me. Phyllis as in Phyllis form
Host: Paul Barnhurst (43:09):
Peace. Oh, fun. And then last personal one and then we'll wrap up here. If you could go anywhere in the world tomorrow, you're taking a two week vacation, where are you going?
Guest: Nicholas Moen (43:22):
Maui,
Host: Paul Barnhurst (43:23):
Mau. Have you been before?
Guest: Nicholas Moen (43:25):
I've lived there for about five years.
Host: Paul Barnhurst (43:27):
Ah, got it.
Guest: Nicholas Moen (43:28):
I know it on a local level and it's one of those places that will probably never be replaced as my top destination point.
Host: Paul Barnhurst (43:35):
Alrighty. As we wrap up, first one, any parting advice you want to give our audience around being a better business partners? We know that's becoming more and more important. Any advice you'd give?
Guest: Nicholas Moen (43:47):
Yeah, I would say learn some skills from your sales team. Good ones. Let me
Host: Paul Barnhurst (43:55):
Not the diva ones in case anyone wants.
Guest: Nicholas Moen (43:57):
Not the diva ones. No. The ones that are really good at selling and you'll know why they're good at selling is they're very good listeners. They really try to understand what your problem is and understand the pain that they're trying to solve and they really, someone would say this to me all the time is listen to understand, not to respond. So being able to really pay attention and understand what people are saying, understanding their issues or what they're thinking or where their mind is and not trying to sound smart or anything. Just really trying to understand and listen is going to probably do more things than any other scale or technique you could ever do. When it comes to partnering,
Host: Paul Barnhurst (44:41):
What you said there, the way I sum it up is on the listening, one of the best ways I've heard is Steve r Covey, seven habits of Highly Effective People Seek First to understand, then to be understood. That's what I always think of when I hear that it's just so critical and I forget myself doing it, but you want to learn to get better at listening. Do 400 podcast episodes.
Guest: Nicholas Moen (45:05):
It's a skill too. It's a skill that you have to develop. It's not something, I mean some people probably come across naturally, but it is a skill that you have to develop and can develop. There's techniques out there, you can look it up, but on how to kind of develop that. But it is something very anyone can do.
Host: Paul Barnhurst (45:22):
A hundred percent agree. It is a skill that can be learned. Different people are better at certain aspects of it than others. Naturally, just like some people are better athletes in certain ways than others. We all have our strengths and weaknesses, but most everything can be learned in life, I believe. Yeah, definitely. Not everything are exceptions, but, alright, well we'll go ahead and wrap up here. I think this is a good place to stop, so if anyone wants to get in touch with you, learn more about you, LinkedIn, the best way to do that or how should they reach out?
Guest: Nicholas Moen (45:53):
LinkedIn's always great. Just tell me that you message me or connect with me. Just message that you've heard me from the podcast or else you're just going to probably go into my BDR purgatory and I just ignore you. So just
Host: Paul Barnhurst (46:07):
Say you heard about Nick, you're excited because you saw him talk to some guy with a big beard
Guest: Nicholas Moen (46:14):
Because
Host: Paul Barnhurst (46:15):
It'll be like, Hey, big what? I better read this
Guest: Nicholas Moen (46:18):
An big beard and I don't know where you heard me from.
Host: Paul Barnhurst (46:23):
Well, you do know, I'm not sure if you're a basketball person at all, but you know who James Harden is?
Guest: Nicholas Moen (46:29):
I do not, no.
Host: Paul Barnhurst (46:30):
Okay, so he's a huge basketball player and his Twitter handle is the beard.
Guest: Nicholas Moen (46:35):
There you go.
Host: Paul Barnhurst (46:36):
Look him up online. He has a huge beard.
Guest: Nicholas Moen (46:38):
Oh, that's great. Brandy
Host: Paul Barnhurst (46:39):
Name. So I'm like, because people have said you need that. I'm like, he already has it
Guest: Nicholas Moen (46:44):
Can't
Host: Paul Barnhurst (46:44):
Take his handle. So if someone's like, you need to do a commercial with, they joke James Harden like, great, and I just got to laugh. So anyway. Well, I think covered, we've covered beards, we've covered the education system, we've even covered some fp a. We've covered coding. Do you ever think you'd be on an FBNA podcast and cover those topics?
Guest: Nicholas Moen (47:02):
I didn't even think I was going to be on any podcast though.
Host: Paul Barnhurst (47:06):
Well, there you go. Well, thank you for joining me. I've really enjoyed it and good luck with things. Continue to build out AI and exciting times. So thank you again.
Guest: Nicholas Moen (47:17):
Thank you. And thank you for having me.
Host: Paul Barnhurst (47:19):
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.