How to Save Time in FP&A Using Structured AI Analysis with Nick and Dan
In this episode of Future Finance, Paul Barnhurst and Glenn Hopper sit down with Nick Jain and Daniel Settel, co-founders of Eagle Rock CFO, to discuss how AI is reshaping FP&A and fractional CFO services. Nick and Dan explain how their AI-powered system combines structured data processing, automation, and financial expertise to help companies analyze complex financial data faster, reduce manual workload, and uncover hidden value in their operations
.Dan and Nick are co-founders of Eagle Rock CFO, a financial advisory firm helping mid-size businesses grow faster and improve profitability. They combine AI and technology to deliver operational finance insights at a fraction of traditional consulting costs. Both are Harvard Business School graduates, with undergraduate degrees from Stanford and Dartmouth. Dan previously co-founded FinTech company Zanbato and worked as a professional investor at PrimeCap, while Nick has experience in private equity investing and scaling companies across SaaS, footwear, and trucking.
In this episode, you will discover:
AI works best when paired with structured financial data, not raw inputs
Why deterministic systems still matter alongside AI in finance workflows
How Eagle Rock’s 5-step system improves financial analysis accuracy
Why human oversight is still needed in AI-powered FP&A systems
How fractional CFOs can save 20–50 hours per month using AI tools
Nick and Daniel demonstrate how AI is transforming finance by automating analysis while still relying on structured systems and human judgment. Their approach shows that the future of FP&A is not fully autonomous AI, but a hybrid model where AI enhances decision-making, improves efficiency, and strengthens financial visibility.
Follow Nick:
Website: https://www.eaglerockcfo.com/
LinkedIn: https://www.linkedin.com/in/nickmjain/
Follow Dan:
Website: https://www.eaglerockcfo.com/
LinkedIn: https://www.linkedin.com/in/dsettel/
Follow Glenn:
LinkedIn: https://www.linkedin.com/in/gbhopperiii
Follow Paul:
LinkedIn: https://www.linkedin.com/in/thefpandaguy
Follow QFlow.AI:Website - https://bit.ly/4i1EkjgFuture Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai. Stay tuned for a deeper understanding of how AI is shaping the future of finance and what it means for businesses and individuals alike.
In Today’s Episode:
[00:00] – Trailer
[04:10] – Founding Eagle Rock CFO
[06:21] – Deterministic vs probabilistic systems
[07:22] – Why agents are not enough
[09:13] – Data compression and structuring
[10:13] – Human oversight in AI workflows
[14:51] – Data mess in SMB finance
[18:38] – White-label and consulting model
[22:18] – How to start using AI safely
[29:36] – CFO vs CEO vs CIO experience
[33:45] – Closing thoughts
Full Show Transcript:
Host: Paul Barnhurst (00:00):
Welcome to the Future Finance Show where we talk about treasury management. Future Finance is brought to you by Q flow.ai, the strategic finance platform, solving the toughest part of planning and analysis, B2B revenue, align sales, marketing and finance seamlessly speed up decision-making, and lock in accountability with Q flow.ai. Welcome to another episode of Future Finance. I'm Paul Barnhurst, the FP&A guy, and I have here with me my trusted FP&A guy. Glenn. How are you doing, Glenn?
Co-Host: Glenn Hopper (00:54):
I'm good. I'm good. Good to see you, Paul.
Host: Paul Barnhurst (00:56):
Now you're not in your normal location. Where are you this week?
Co-Host: Glenn Hopper (01:00):
I am doing what all smart business people do and that is combining business trips with checking off family obligations. So I have a client in Greenville, South Carolina, which is where my in-laws happen to live. So I brought my wife with me and we're doing client work and hanging out with the in-laws and thankfully they have good internet. You never know when you're travelling what we're going to end up with, but it feels like we're kind of cooking here.
Host: Paul Barnhurst (01:26):
Got it. So we're mixing business with pleasure today
Co-Host: Glenn Hopper (01:28):
Every day. Yep.
Host: Paul Barnhurst (01:30):
Alrighty. Well we have two guests with us. Glenn, why don't I give you the pleasure of introducing our guests this week.
Co-Host: Glenn Hopper (01:37):
I hate reading intros, Paul, but I'll dive in and give this a shot. Hey Nick and Dan, I'll go ahead and introduce you to our audience and I'm really looking forward to talking to you guys. Our guests today are Nick Jain and Daniel Settel, co-founders of Eagle Rock CFO tech enabled fractional CFO firm that uses proprietary software to automate core FP&A work for its clients. These two have pretty different paths to the same company. Nick is a Harvard MBA out of McKinsey and Bain Capital who then went the operator route. He was CEO at Idea Scale, a B2B SaaS company where he nearly quadrupled EBITDA margins at 18 months and he's been CFO at a logistics company and an e-commerce startup. Dan is a Stanford Chemical engineering grad and also a Harvard MBA who spent almost seven years at Prime Camp Management, which for those who don't know, it's one of the most respected and secretive fund shops in the business. Before co-founding Zendo, a VC secondary trading platform that grew to over a billion in annual volume. He's also an active growth equity investor in AI and Frontier Tech through Green Sands Equity. Together, they launched Eagle Rock earlier this year to bring AI powered analytics and fractional CFO services to the mid market. Nick, Dan, welcome to Future Finance.
Guest: Nick Jain (02:51):
Thank you for having us, Glenn.
Co-Host: Glenn Hopper (02:52):
Yeah, I feel like you're gunning for our jobs, not the podcast host jobs, our day jobs,
Host: Paul Barnhurst (02:57):
Everybody's gunning for finance.
Guest: Nick Jain (03:00):
I mean, AI is gunning for all of our jobs, let's be honest. Right.
Host: Paul Barnhurst (03:04):
So what will you do first, Nick, when AI takes all your jobs?
Guest: Nick Jain (03:07):
Well, Dan and I are just trying to stay about a year or two ahead of it to be honest, but I've got an 18 month hold at home and I don't know what the future holds for him, to be honest. Yeah,
Host: Paul Barnhurst (03:16):
We will get to the real questions here in a minute, but it is pretty crazy to watch the speed of all this. Do you sometimes just go, where does this end? What is going on? Do you ever have those moments? Who would've thought they would go this quick and change this much?
Guest: Nick Jain (03:30):
I'll let Dan take that. I dunno, I love this stuff. I am drinking the Kool-Aid from the fire
Co-Host: Glenn Hopper (03:36):
Hoses.
Guest: Daniel Settel (03:37):
Yeah, I'm pretty much counting on Nick and hopefully he makes some agents that help me survive the AI apocalypse ahead.
Host: Paul Barnhurst (03:45):
Yeah, Glenn's my survival toolkit, so I get it, Dan. Alright, I guess we should get a little serious here now that we've had a little bit of fun. So love the backgrounds. Why don't we, I think we'll start here on this question. We'll start with you Nick, and then Dan, we'll let you add anything you want. So tell us just a little bit about yourself and how you started building Eagle Rock CFO, how that came about. Sure.
Guest: Nick Jain (04:10):
So Dan and I have spent our careers both being investors and operators and AI started becoming a thing a couple of years ago and as Dan and I finished up our last professional opportunities, we connected, we'd been friends for about a decade. We had never really worked together. We started talking to AI last summer and said, Hey, there's something here. Where can we go build something really cool and exciting? And an obvious area seemed to be, hey, AI is really good at analysis and dealing with complex multi-part situations and we understand how businesses make money. Let's stick those two together and launch a AI automation business for the FP&A world. So
Host: Paul Barnhurst (04:49):
Yeah, they are gunning for our job, Glenn. Exactly right. Dan, did you want to add anything to that?
Guest: Daniel Settel (04:55):
Yeah, I mean I think I've just been blown away by this whole process. Probably the part that scares me the most is just when I compare the tools that Nick has done, most of the engineering work on our side, what he's built. When I think about comparing that to the chatbots I interact with as a consumer every day, oh man, the accuracy rate is just so much better. And Nick can go into the details later about why it doesn't hallucinate, but it's just a different world. What we're doing for v FP&A function than I see what's chopped GPT day to day.
Co-Host: Glenn Hopper (05:29):
That's the world that I'm living in. And so my day job, when I'm not doing podcasting, I'm doing AI implementations and they're all bespoke. Every client I have is a snowflake. We haven't productized anything. But also, so I do implementations, but I also do a lot of training and I was working with our head developer, we're building and LMS system for a Fortune 500 company to train their team on how to use ai. And I was talking to the developer and he said, this may be the last thing we build because the agents are getting so good, if everybody can use them, they don't need us anymore. And it's super, like you guys were saying, really I would say with the last four months, because everybody's been calling everything that they build in AI and agent and true agents haven't really been a thing until very recently where they could go off and do long range functions and all that.
(06:21):
People were just calling their modified chatbot an agent or whatever, but we're just with whether it was the open claw experiment or even especially I guess what C Claude is doing right now, what Anthropic is doing with agents is just amazing. And I guess all that preamble to talk about this, and I'll throw this to either one of you, but if your tech handles the heavy lifting, I'm wondering, because we were talking a little bit before we came on air too about deterministic versus probabilistic. The trial balance has to balance what we know we can automate. Sure, but we don't need generative AI to come in and weigh on it. So I'm wondering for you guys, how did you make those decisions and what is your stack without giving away any secret sauce proprietary information, but what's the approach you guys took to this is hardcore just python or math that we're doing standard here and this is where we're putting AI in? Or are you just leaning more heavily into letting agents run?
Guest: Nick Jain (07:22):
So no to the latter half. If you let agents run, they basically make stuff up or head off in the wrong direction. Or my favourite thing, sometimes they miss the forest for the trees and sometimes they miss the trees for the forest and they do that consistently. So look, let me attend the tech stack and then I'll go back to some of the design principles. Our tech stack is really five pieces only, two of which use AI in any way and not honestly, not a agent ai, although Dan and I personally do most of our work using agents, our client work and the software and technologies we offer to our customers tend to be basically software solutions that leverage AI rather than agents. So our tech stack is basically five things, right? It requires a data ingestion engine. How do we eat data? A little bit, very little AI is involved there.
(08:06):
That's just traditional old school code. Secondly is compressing data because one of the things you run into with AI is if you drop a giant spreadsheet or a hundred thousand word book into ai, it starts hallucinating in very predictable ways. So you got to compress that a hundred thousand words or that spreadsheet with 4 million lines down to something smaller. So we do a little bit of data compression, that's still old school technology. Thirdly, we do a little bit of tagging of the data, still old school technology, python scripts, JavaScript scripts, whatever. Okay. Level four. The fourth piece is where AI comes in. So we now have this huge chunk, this smaller chunk of data that is well categorised and organised, and then we ask ai, Hey, help us figure out what's going on here. And we ask that very, very tactically across thousands of questions like, Hey, what are the major expenses?
(08:54):
Hey, are there vendor consolidation opportunities? Hey, is there accounting fraud? So rather than just asking ai, Hey, what's up? We'll ask it an entirely vetted targeted list of thousands of questions and that we rely on domain expertise. And the fifth piece, it's not fancy. We leverage a little bit ai, we make it look pretty by creating a presentation layer. But really the cool stuff is what happens in the kind of levels or phases, one through four data ingestion, compression, tagging and asking the AI to make synthetic or synthesis decisions. The presentation layer just makes it look cool. So clients pay for it. You
Co-Host: Glenn Hopper (09:28):
Guys are solving for what every finance team, what every CFO's office is trying to figure out right now. And then I guess that probabilistic versus deterministic and your answer made perfect sense. But that's what everybody, if you've never done anything with machine learning and you're not familiar with the technology, it just feels like magic. And people are just thinking, oh, take whatever process I'm doing and just sprinkle some AI on it and boom, it's fixed. And so I loved hearing your approach to it and yes, we are in an AI era and it's all driven, but the fact that you go back to leaning on just the fundamentals of deterministic coding and this is what we're creating, this is the same for all businesses,
Host: Paul Barnhurst (10:13):
Glenn. It's almost like two plus two supposed to equal four.
Co-Host: Glenn Hopper (10:17):
Yeah. Unless you ask generative ai, right? Yeah.
Host: Paul Barnhurst (10:21):
Well I had a roommate in college that had a shirt that said two plus two equals five for larger values of two too. He also had one that said, if you can read this, you're overeducated. And it was in Latin and about 10 others like that he wore every day. So it made for fun. Alright, so talk a little bit about how your kind of fractional CFO model works. Obviously there's a technology behind it, there's a human, and so how are you managing the workflows? Where does the human step in? Kind of take us through a little bit of the process here.
Guest: Daniel Settel (10:58):
It gave you a sense for how the system works. Most of the time the technology can handle just about everything. I think there's some reluctance, it's not just in fp and a, it's kind of everywhere. People that trust ai. Nick talked a lot about the data tagging and the organisation of the data that we do before we ask questions. And that's really kind of the key to reducing the hallucination rate along with some verification layers. But we still do have the human element there essentially to handhold with the clients and get them comfortable with the answers that the system has figured out. Nick has told me that maybe one out of a hundred questions, the AI will still get wrong, and we do do a little bit of human cleanup, but from what I've seen from the AI answers, it seems to be close to a hundred percent correct. We're doing a lot of extra work with our early clients just to make sure they're really happy. So there are some cases where a client has asked us to go help find a loan or help find insurance policies and we haven't developed any AI bots that will take phone calls for us yet. So if we're talking with another party about financing or some sort of outside service that we need to get to the company, then we're still doing a little bit of that human monkey work ourselves.
Host: Paul Barnhurst (12:14):
Did you just call our job monkey work?
Guest: Nick Jain (12:20):
Aren't we all just hairless monkeys? Some more hairless than others? Yeah,
Co-Host: Glenn Hopper (12:24):
I was going to say Paul is not a hairless monkey. One thing I wanted to hit on though is your go to market. And I think you're hitting a pretty interesting segment, and I think this is just one of the segments you're hitting, but going after the fractional CFOs, I know I see so many of 'em out there, single shingle fractional CFOs who are trying to come in and do a turnkey solution, and that means they have to be an expert in a lot of areas. And it could be maybe that if it's a small enough one, maybe that fractional CFO is actually doing some basic bookkeeping and doing controller work and more strategic 13 week cash flows and all that. How did you nail down that market? What did you see that said, Hey, fractional CFOs need a tool like this?
Guest: Nick Jain (13:10):
Well, let me take a crack at it. I think it's three things potentially. Number one, what do Dan and I actually have no expertise on, right? I don't have any expertise on let's say the creative side of marketing, so maybe Dan does, but that's would probably not be a good area for us because we couldn't speak credibly or acquire clients or seem intelligent to them. So finance is an area where we have domain expertise specifically on the FP&A strategy side. Number two is where are people still doing a lot of manual work either on blackboards or on Excel or pieces of paper? Obviously FP&A is another kind of category for that. And number three is where are there missed opportunities for value creation and how companies run themselves. So for example, in any normal company over probably five or 6 million bucks in revenue, no one is going through every single cost line at them every single day because people have lives to live, right?
(14:01):
No matter how big your finance team is, they're not looking at every single line item them. Guess what? For an AI tool that's a penny of cost. So as you think about the confluence of those three factors, what are we good at? Where are people still using legacy tools that can be empowered or made better or using better tools? And where is there a lot of real hard value creation left in how companies are leaving money on the table in their operations? And that's where we came together and said, look, FP&A is an area that is ripe for automation and AI powered tooling, and it's an area that every company really has. Almost every single company has an FP&A department CFO or a co o or somebody who's basically looking at the numbers to try and figure out how to make the company better every single day. And that's an area that Dan and Dan are passionate about to add icing on the cake.
Co-Host: Glenn Hopper (14:51):
And I guess the follow up on that, if you're talking about fractional CFOs, I've lived this world and I've seen it a lot. That means they're coming into companies that have got QuickBooks or maybe zero and they might have HubSpot or some other pipe drive or something. They've got some disparate systems, data's a mess. If it's a founder-led company, their chart of accounts could be that the default QuickBooks chart of accounts and there's sort of a blend between cash and accrual accounting. I mean that's what sort of shingles small firm CFOs are dealing with was that part of your build was how can we help them clean this up? Because it's always so painful when you first come in and you realise, oh, it's going to take me 60 days just to understand the chart of accounts here.
Guest: Daniel Settel (15:39):
I think that's exactly right. If you look at a big company, they already have a team of analysts and data science people who can help them get the answers. But when you're talking about that single shop FP&A fractional CFO guy, he's got to figure out how to do it all himself. So giving him the tools or her the tools to do this the way that a big company could as a single individual I think is a big part of our mission too.
Host: Paul Barnhurst (16:04):
Makes a lot of sense. But I'm curious, what do you guys do? How does the tool manage that? If the chart of accounts is a mess, do you go work with the company to clean it up or how do you deal with that? Because we all know in this small space it's rarely clean from day one and Nick is laughing,
Guest: Nick Jain (16:22):
I'll check. So yes, a hundred percent true. We actually one our look, our tool does a bunch of things. One of the features that it does is it looks through all your data and says, Hey, here's where it's a mess. And sometimes it says it's a mess because it's wrong for technical reasons. Like one plus on is equal in three, which is we know in accounting shouldn't be true. And sometimes it says, Hey, this journal entry, it kind of looks fuzzy. Instead it should be over here. And sometimes it says, Hey, your chart of accounts is a mess and you need to go fix it up. So generally we are not going in there unless it's a quick task and actually changing the chart of accounts that is our client's work or their accountants' work or their controller or their fractional samples work. But the good news is our technology does figure out when it is either technically or qualitatively an area for improvement because as funny as it is for one of our clients, we said one of the biggest areas for value creation for them was actually just getting their accounting right because they couldn't figure out their p and l correctly.
(17:16):
Ever
Host: Paul Barnhurst (17:17):
Feel like your go-to market teams and finance speak different languages? Misalignment is a breeding ground for failure in pairing the predictive power of forecasts and delaying decisions that drive efficient growth. It's not for lack of trying, but getting all the data in one place doesn't mean you've gotten everyone on the same page. Meet Q flow.ai, the strategic finance platform purpose built to solve the toughest part of planning and analysis, B2B revenue QOO quickly integrates key data from your go-to-market stack and accounting platform then handles all the data prep and normalisation under the hood. It automatically assembles your go-to-market stacks, makes segmented scenario planning a breeze and closes the planning loop, create airtight alignment, improve decision latency and ensure accountability across the team. Well, we had one that told, I saw equity owner's equity going through revenue on a company
Co-Host: Glenn Hopper (18:30):
Makes perfect sense
Host: Paul Barnhurst (18:32):
Yourself, then put it back into the business and call it revenue. I love it. That's my new model.
Guest: Nick Jain (18:38):
That sounds like, isn't that like a Ponzi scheme basically? Exactly.
Host: Paul Barnhurst (18:42):
Is that something like what Enron tried to do, but in a more sophisticated way? Another question I just kind of want to ask is we noticed you guys are doing some white labelling of the platform, so obviously that's quite a bit different than running a consultancy business. You have some human stuff. So how did you come up with the approach, what's kind of driving it, what's the uptake been like? It sounds like you're offering the software obviously to other fractional services, but you're also offering some of your own fractional services with the software. So how do we walk us through all that?
Guest: Daniel Settel (19:15):
Certainly from the perspective of what we've built, it can be applied both to a company that has a CFO in place or to a company that doesn't have a CFO. So the white label is our version for fractional CFOs for full-time CFOs, for somebody who wants to use this without our hand bolding. And I think a lot of good finance people are capable of doing that. There are some people who just don't want to deal with the technology directly. Technology is not their thing and that's where our consulting service comes in. And we can either work directly with the existing CFO of a company or we can work directly with the CEO if they're kind of at the stage where they're thinking about bringing out a CFO not ready for a full-time person. So maybe it is kind of a fractional CFO consulting in its own way in that service, or it could just be kind of the early stages of starting to implement some of those things as the company is scaling over time.
Co-Host: Glenn Hopper (20:11):
And what's your sense of, I know it's early days still, but what's your sense of how much time can be saved, how much more the real value proposition of this for whether you're going into a firm or through white labelling through other fractional CFOs, it's going to be what's the time savings, how fast are we closing the month? What insights do we not have before? What's your sense of, because again, I spent a lot of time in this space, I just coming in where there was no CFO before or there was a glorified bookkeeper called head of finance or something and it's just kind of a mess and getting to the other side. I think when Dan, I think to your point, there's always that precipice of we kind of need a CFO, we can't yet afford A CFO, what are we going to do? And I think that's probably maybe a sweet spot for you guys, but what's your sense of the company that comes that brings you guys in what they're saving and what they're having that they didn't before?
Guest: Nick Jain (21:08):
Sure. I think our value proposition happens in two ways. Number one is if you have someone actually analysing the books, so ignore the technical side of doing the accounting and closing the books. We do a little bit of work there, but really our focus on the FP&A side for that FP&A side, if the person has time, they're probably spending somewhere between 20 to 50 hours a month just peeking around the numbers saying, Hey, I can create more value here. I can adjust pricing here. I believe our tool cuts that 20 to 50 hour exercise down to a few minutes, a human time tops. So it is 20 to 50 hours per month of time savings directly. But here's the big kicker and a lot of companies, people are just too busy managing the day-to-day. So there's not somebody who's stepping back often and just thinking about the numbers and looking through the data and doing analysis. And for those companies, this is just a purely value additive service where you don't have somebody trying to go around optimise your costs or think about vendor consolidation or pricing or whether you have all the right insurance policies because people got stuff to do. And that's an area where it's not a time saving, it's just directly accretive to your bottom line.
Co-Host: Glenn Hopper (22:12):
Makes total sense. Paul, do we have time for one more question before we get into our AI generated?
Host: Paul Barnhurst (22:18):
We always have time for one more question. Glenn,
Co-Host: Glenn Hopper (22:21):
You have the domain expertise. You've been through building this. We talk to finance people all the time who, I mean at this point I think the wave is we've jumped over the top of the Gartner hype cycle and I think we're Now, if you're not doing something with AI in your business, you are officially a laggard at this point, but I know I talk to finance teams every day, they want to start automating, but they don't have the trust yet or really the understanding, and I'm sure this is an area where companies like you guys will come in and help them, but for A CFO or a controller, somebody that wants to just get started using ai, bring automation in, what guidance do you have for them if they're really like, okay, I understand I'm behind the curve. What do I need to do that's not just uploading all my financials directly into chat TPT or clot or whatever?
Guest: Daniel Settel (23:15):
Yeah, so I mean I think the big issue with loading financials directly into one of these chatbots is as Nick mentioned, when they're looking at a lot of data, the AI will either miss the forest for the trees or miss the trees for the forest. They can't summarise, get the big picture of what's going on with the data. It'll get lost and hallucinate and give the wrong piece of data for the wrong question. So I think that's where working with a system like ours that has the structured financial knowledge and content built into it is going to ensure the AI gives the right answers. Otherwise that 2050 hour task that Nick was talking about, I mean maybe you could speed up half to work by going question by question data point by data point drew as a CFO or FB and a person, but it's still going to be a lot of time that's still probably 10, 25 hours out of a week to go through, find the right data, do the right calculation, and then feed the right data, the right kind to the AI system. So it gives you the right answer. Makes
Host: Paul Barnhurst (24:20):
A lot of sense. Alright, Glenn, who do you want to ask the personal question to? You get to pick. Alright,
Co-Host: Glenn Hopper (24:28):
Am I going first on the questions this week? Well
Host: Paul Barnhurst (24:31):
Why don't we have you go first, Glenn. I don't think we've done that yet. That's
Co-Host: Glenn Hopper (24:34):
Right. You normally go, so alright, so here's what we do guys, every week we take your LinkedIn, these are really weird and technical this week, so good luck guys with these questions we're asking. So every week we
Host: Paul Barnhurst (24:45):
Langley ai, not us. That's what we do When it's wrong,
Co-Host: Glenn Hopper (24:48):
We take your LinkedIn profiles, we take whatever public information is out on the web and we move around. I've been on Claude a while just because I'm doing everything in Claude these days and we say come up with some quirky personal questions for each of them. So my approach is always, well AI created the questions. Sometimes I'll tell it, pick your best or pick the best question to ask and I let AI do it. Paul has a little bit like an, I don't know if you're doing this in Excel, you want to explain what you do on your side? No,
Host: Paul Barnhurst (25:18):
I do one of two things. I either let you keep a human in the loop and pick a number between one and 25 or I use the random number generator on the web, whichever one comes up first when I search it and pick a number between one and 25. Oh, I could use AI to be that random number generator, but I'm afraid of my hallucinate and give me 26 instead of 25. I just don't quite trust it yet. So I go with the deterministic site.
Co-Host: Glenn Hopper (25:43):
Yeah, you know what Dan, I'm going to put you in the spotlight first and I'm just going to go ahead and have AI select a question here. So let's see, Paul, it's number one. Again, we're in some kind of weird, if we're at the roulette table, we would be getting the last three weeks.
Host: Paul Barnhurst (25:59):
It's all been one through five. So if that continues and we can take those nods somewhere else, maybe we can make some money. Glenn.
Co-Host: Glenn Hopper (26:05):
Yeah, so number one again. Alright Dan, the question is, this one's not bad, some of these are just weird, but this one, this is a good question actually. You studied chemical engineering at Stanford. How does a chem E end up in fractional CFO services?
Guest: Daniel Settel (26:20):
Oh man, that's a good question. I ended up doing some research work while I was at Stanford on project finance. There was a professor I was working with at the time, really interesting guy who's doing work on building cities from scratch in the Middle East was the first project I did with him was looking at special economic zones around the world, how these cities were being built and creating a database of all the different countries in the world and the cities that they were doing that. So that was my introduction to the world of finance and it led to one finance thing after another. And here I am not really ever having done any chemical engineering in my career 20 or so years later, but I do like to think that the engineering background helps me to think about companies, gives me a better understanding of the science that they're working on a lot of the time. And sometimes that does have implications for the finance too. I mean you don't want to buy the wrong chemical and then have your plan explode. So I like to think I've heard that man, I don't cut the wrong hos at least.
Co-Host: Glenn Hopper (27:23):
And obviously your dog is a cow fan. We said Stanford and you just went nuts in the background.
Guest: Daniel Settel (27:30):
Oh, you can hear the dog. I was hoping that these modern microphones were shutting her down in the background, but she likes to bark. There must be some sheep walking by outside my house, which she's hurting. All good. Not a problem.
Co-Host: Glenn Hopper (27:42):
I was going to say, I do think that engineering, it's a lot of the same mindset that goes into, it's that problem solving mindset, it's that sort of understanding how and why things work and it's so the same sort of thinking that pushed you through engineering, I would say applies pretty well in strategic finance too. So it is actually they seem correlated. Yeah,
Host: Paul Barnhurst (28:04):
I found many of the best people I worked with in FP&A had an engineering background because that analytic and that problem solving and math nature they brought with them. So I not surprised to see you ended up finance.
Guest: Daniel Settel (28:15):
Yeah, I think that's right. I think it's all an optimization problem. You want to make sure that you help the company make as much money as possible while maintaining a high quality of service and making sure the customers are as happy as possible as well.
Host: Paul Barnhurst (28:29):
Glenn, what do you think? Should we hire them to optimise our businesses?
Co-Host: Glenn Hopper (28:33):
I think our businesses are beyond hope. Paul, I don't.
Host: Paul Barnhurst (28:36):
I know they probably are, but we've got to do a last ditch effort. Come on. But we could at least talk, you can talk with the best of them.
Co-Host: Glenn Hopper (28:42):
That's right.
Host: Paul Barnhurst (28:44):
That's about all Glen and I can do, Glen can do ai. I can talk and grow a beard. That's all I have left for me at this point. I'm going to lean into the beard more and more. Alright, no, back to the questions Nick, you got one of two options. Do you want to pick the number between one and 25 or you want the random number generator
Guest: Nick Jain (29:05):
17.
Host: Paul Barnhurst (29:06):
He didn't even hesitate. I already know what number I want.
Co-Host: Glenn Hopper (29:09):
Nick, a roulette player. You were committed
Host: Paul Barnhurst (29:12):
Poker.
Guest: Nick Jain (29:13):
I've never played
Host: Paul Barnhurst (29:14):
Roulette, but I'm a very good
Guest: Nick Jain (29:15):
Poker
Host: Paul Barnhurst (29:15):
Player.
Guest: Nick Jain (29:15):
Okay,
Co-Host: Glenn Hopper (29:17):
That was the question. Do you like poker? How weird.
Host: Paul Barnhurst (29:21):
Alright, we're done. Thanks. Oh, you've been C-E-O-C-F-O and CIO at different companies. Which hat fits best and which one did you find the hardest?
Guest: Nick Jain (29:36):
I think for me the hat that fits the best is the CEO and the hardest was the CFO because in the CFOI think there's, I'll mention why the CFO one has been the hardest for me, the math and analysis side, that's the easy part of the CFO job. It's some of the kind of delicate, call it the politics around being CFO on two dimensions. Firstly as CFO, you're often the bad cop in a good cop bad cop way, right? When customers, if you're increasing pricing on customers, you have to tell your sales guys blame the cfo, I've done this myself. Tell my sales guys blame me. I'm the CFO. Blame it on the evil CFO or, and then conversely, you officially, in most companies, CFOs have limited hard power. They are the keeper of the money. They have some governance rights, they can say no, but you can't just say no because it's a wrong decision to build.
(30:26):
You don't have a lot of direct control over the operations of the business, although you are theoretically one of the smartest people in the room when it comes to knowing what's going on in business. And I found that very difficult, both always being painted as the bad cop. Again, sometimes by choice, but it hurts, right? And then secondly, having limited direct power and having to use a lot of influence. I think that's really difficult, especially when I see, hey, we're doing this wrong. Why can't I just go fix it when that is someone else's kind of purview or scope, you don't want to step on toes. The CEO head I think solves that problem quite a bit because you have the latitude to just go do everything again. You still have to be delicate by not disenfranchising people or disintermediating your senior staff, but there's a lot more latitude to move fast and change things as the data or evidence changes over time rather than stick to an arbitrary plan because someone above you said to do this,
Co-Host: Glenn Hopper (31:16):
Nick, that's so interesting. I don't know Myers Briggs or any of these personality things, everything that you just said, I would completely flip. I loved being the jerk OI loved, it's like bring it, let's go. And I served, I was, I've never had the CEO role. I've been A-C-O-O-C-F-O and kind of a half-assed CTO at one point too. But the CFO role I always felt like as the CFO, you got to be the adult in the room. I keep thinking of the WeWork founder showing up with his long hair and barefoot and being the big vision guy and then someone's got to be in the background who knows socks and not socks as
Host: Paul Barnhurst (31:56):
Who understands community adjusted ebitda. Glenn, is that what you were going to say?
Co-Host: Glenn Hopper (32:00):
Yeah, I mean it's funny. And then the CEO O side, it's like the visionary part just seems exhausting and dealing with all those people seems exhausting. It's like, let me be the right hand person and just solving problems and anyway, it's very funny. As you were talking everything you were saying I was exactly 180 from,
Host: Paul Barnhurst (32:21):
And I haven't been any of those so
Guest: Nick Jain (32:25):
Arose by any other name.
Co-Host: Glenn Hopper (32:28):
Paul, you're the chief of my heart officer. I don't know. Is that
Guest: Nick Jain (32:33):
Wow of
Host: Paul Barnhurst (32:34):
That
Guest: Nick Jain (32:35):
Glenn, we might CCVO, chief Beard Officer, right? Done.
Host: Paul Barnhurst (32:42):
I go, well I've been told by people I need to start a beard brand.
Co-Host: Glenn Hopper (32:46):
Absolutely. Looking
Host: Paul Barnhurst (32:46):
At this podcast, I don't see many customers and therein lies one of the problems. Everybody who's followed me is in finance. I don't think most finance people have big beards. I don't think it's a high target audience. Is beard the first thing that comes to mind when you think finance?
Co-Host: Glenn Hopper (33:03):
No neck tattoo is.
Host: Paul Barnhurst (33:07):
Alright, so as you start a tattoo parlour, before I start a beard brat, how did we get so off the rails guys? How did you let it go like that?
Co-Host: Glenn Hopper (33:19):
Well Nick and Dan, we really appreciate you coming on and I think you guys have hit a sweet spot. I wish you guys the best of luck because I know there are so many fractional CFOs who are trying to figure this out themselves and help their clients too. So I know you've got your own consulting too, but I think there could be a real sweet spot in having a tool that fractional CFOs could come in and be armed with. So super interesting to see how this shakes out for you.
Host: Paul Barnhurst (33:42):
Thanks for having us on. We really appreciate it.
Guest: Daniel Settel (33:45):
Thanks for having us.
Host: Paul Barnhurst (33:46):
Thanks for joining. Really appreciate it Nick and Dan, and we hope you guys have a great rest of your day and good luck building. I know scaling is always an exciting and scary time at the same time. Thanks for listening to the Future Finance Show. And thanks to our sponsor, QFlow.ai. If you enjoyed this episode, please leave a rating and review on your podcast platform of choice, and may your robot overlords be with you.