Latest / The Diary of a CFO / Excel vs FP&A Software: When to Make the Switch (with Paul Barnhurst)

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Excel vs FP&A Software: When to Make the Switch (with Paul Barnhurst) · The Diary of a CFO

0:00
Welcome to the Diary of a CFO podcast. I'm your
0:02
host, Wassia Kamon, and each week we explore
0:04
how today's finance top leaders build high -performing
0:07
teams, partner with CEOs and boards, and lead
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through growth and transformation without burning
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out in the process. Today, I'm super delighted
0:14
to have with me Paul Bonhurst, aka the FP &A
0:18
guy. Paul is a leading voice in financial planning
0:21
and analysis. He has delivered corporate training
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and virtual courses to thousands of finance professionals,
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covering FP &A best practices, storytelling,
0:30
business partnering in Excel, and data visualization.
0:33
He also owns the FP &A Unlocked podcast, co -host
0:37
Financial Modeler's Corner, and Future Finance.
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He has built an audience over 112 ,000 followers
0:44
on LinkedIn. He is known for his clear independent
0:46
reviews of FP &A. any software and for helping
0:49
finance team make smarter choices about the tools
0:52
they use. Welcome to the show Paul. Thank you.
0:55
And after that bio that you wrote, can I just
0:57
hire you to be my marketing person? Absolutely.
1:01
I accept all forms of payment. I didn't say anything
1:04
about payment. All right. Let's dive in. So you
1:08
are an Excel MVP and you also review a lot of
1:11
FPNA platforms. So where should Excel remain
1:14
the hero and where does it become a liability
1:16
when you think about it within an FPNA function?
1:19
Yeah. So, I mean, the reality, whether it's Excel,
1:22
Google Sheets, whatever the fundamental spreadsheet
1:24
is not going away. I don't see it going away
1:27
anytime soon. Even if Excel went away tomorrow,
1:29
we would still use a spreadsheet. So the way
1:31
I think about it is there comes a point When
1:34
the need for a database, for privacy, for integration,
1:38
for your model, for greater calculation speed,
1:42
many of those things becomes imperative. They
1:45
outweigh the flexibility, because the reality
1:47
is a spreadsheet, Excel, Google Sheets, whatever,
1:50
all these new ones coming out, is always going
1:53
to be more flexible than an FPNA tool. Just by
1:56
the nature of unstructured data, structured data,
1:59
it's much easier to be more flexible. For that
2:03
flexibility, you give up auditability at the
2:07
level you would get with a true tool, the database
2:09
level at a row permission, collaboration, the
2:14
scalability, the calculation engine, some of
2:17
the multi -dimensional modeling. Yes, some of
2:19
that can be done in Excel. Almost everything
2:21
can be done in Excel or with the Microsoft tech
2:24
stack on your own. It's a question of, do you
2:27
really want to invest all that time and have
2:28
to keep those people? So I think what you have
2:30
to look at is when the paying starts to become
2:33
big, where you start to see errors. You have
2:35
problems consolidating everything. You have privacy
2:38
issues. As those start to grow, you have real
2:41
issues with bringing in all your data. It's time
2:44
to look at something else. That doesn't mean
2:46
you throw out the spreadsheet. You may select
2:49
a tool that very well integrates really well
2:51
with the spreadsheet. You may select a tool that
2:54
doesn't. but you're still going to use the spreadsheet.
2:57
There's always going to be those edge cases.
2:59
You're doing M &A and you're not going to put
3:01
all their data in your planning tool and build
3:03
a model for it to decide if you're going to buy
3:05
the company. Yes. At least I don't think anyone
3:07
is. Maybe there's a tool out there doing it with,
3:10
but not yet. So that's kind of how I think about
3:12
it is when you're big enough and complex enough
3:15
that there's that real pain. to where things
3:18
are going wrong, it's taking too long. And I
3:20
think everybody knows, we've all seen them, there's
3:22
plenty I can list. That's when it's time to look
3:25
and say, what more could I add? And that could
3:28
be as simple now as an Excel agent with some
3:31
of the things they're building there that are
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many ways the light planning tool, all the way
3:35
up to a big, huge enterprise tool, depending
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on your company. Well, thank you so much for
3:40
sharing. And I'm also curious, like a lot of
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teams are stuck in Excel because they're overwhelmed
3:45
by the FP &A software options. I remember when
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I started in FP &A, there's only like couple
3:50
tools, but now I feel as there's a new tool every
3:53
month. And so how should a finance leader logically
3:56
choose an FP &A tool for their team, especially
3:59
when they're moving from Excel to that first
4:01
FP &A tool? Call me. On a serious note, I think
4:06
there's a few things. I look at it as there's
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really three phases to this process. There's
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the narrowing down the tools you want to look
4:14
at. And that's the research part. Talk to other
4:17
people, check out the market maps I've done.
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I have even a course that's free that you can
4:22
go take on FP &A software selection. And so I
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think first is figuring out the market because
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the reality is people know of tools. But rarely
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do they really know, hey, are these good mid
4:32
-market or are these good enterprise or the good
4:34
small business? Is this one good in a certain
4:36
industry? What type of tools? And so someone,
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I can take some questions and narrow down their
4:43
list to five, 10 tools quite easily. And so that's
4:46
the first step is kind of narrowing it down.
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And then it's really going through a selection
4:50
process. I encourage people as much as we all
4:52
hate it, do a proper RFP. you'll thank yourself
4:55
in the end. It doesn't mean you have to be super
4:57
strict. I started my career in contracts, so
5:00
that's where that comes from. I wrote RFPs for
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the government before I went back to grad school
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and got into FP &A. And I think there's a lot
5:06
of value in going through that rigorous process
5:09
because it forces you to compare the tools against
5:12
your requirements, not against each other or
5:14
against the whiz -bang features they have. Nice.
5:17
And then the third thing, which is more important
5:19
than the tool you select, is do you have the
5:21
right implementation partner? Have you done the
5:24
work on your data? Do you clearly know what your
5:26
requirements are? And can you implement it correctly?
5:29
Because these tools aren't all that different.
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I mean, how many ways can you plan? At the end
5:34
of the day, they're 12 months in a year. There's
5:37
52 weeks. We all, with few exceptions, have revenue.
5:41
We all have some income stream. We all have a
5:43
cost of goods sold and we all have operating
5:45
expenses. And then we have capex, right? It's
5:48
not... It's not that different. Yes, there's
5:51
a lot of intricacies in between that, but as
5:54
much as the planning tools all want you to believe
5:56
they're unique and there are better ones than
5:59
others, they're pretty similar. Okay. And so
6:03
it's in the implementation part that I think
6:05
we often get in trouble, right? Because we either
6:07
ask someone, like people on our team, and I've
6:11
seen it, to work on it in their spare time, right?
6:14
Who has spare time? And then if you didn't do,
6:17
like you said, the right research on implementation
6:20
partner, that's another problem as well. Yeah.
6:23
And so I'll share an example. I was asked to
6:25
select a new FP &A tool for us and the project
6:27
kind of changed that for time and it came where,
6:29
hey, how about you implement? We're going to...
6:31
implement a US version we'd had at TM1 was the
6:34
tool. And I went through and wrote all the initial
6:37
requirements. But at the time that was about
6:39
80 % of my job. I'd come in new to a company,
6:42
they're still trying to figure out where I'd
6:43
fit. Things had changed a little bit later. And
6:45
I spent a bunch of time with all the businesses
6:47
gathered all the requirements. And I still remember
6:49
one of the vendors implementation partners going,
6:52
this is probably the most detailed requirements
6:54
we ever seen this early. Nice. And that's when
6:57
you, that's what you need is not you need everything
6:59
documented, but you really need to think through
7:01
it and you need time to do that. I had the time.
7:06
It had been three months later when I had the
7:08
new jobs they'd given me, I wouldn't have had
7:09
the time. It would have been nowhere near that
7:11
good. And so without the time, you just really
7:14
can't do it right. And so if you're going to
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invest 60 ,000 a year and a hundred thousand
7:19
in implementation, invest half of somebody's
7:22
time or hire another person if you have to. Cause
7:25
the savings will pay for themselves. Nobody wants
7:27
to hear that. I get it. Or implement AI and find
7:30
some savings, whatever, whatever it might be,
7:33
but don't skimp on the person's time. Cause they're
7:37
your expert. Yes. And it makes buy -in at the
7:39
end also easier when you had someone championing
7:43
the solution throughout. So you'll burn out the
7:46
person if you give them a hundred percent of
7:48
their regular job plus that. Yes. Yes, very true.
7:52
So what are some of the red flags that you've
7:53
seen in FP &A software demos that buyers should
7:56
watch for? I think, one, if they're always kind
7:59
of telling you they're unique, two, especially
8:02
the further you get. That first demo, not so
8:04
much, but what I always recommend is you should
8:06
do some kind of proof of concept. Once you've
8:08
narrowed it down to a few tools, you're really
8:10
into that process. If it's clear they don't know
8:12
your business, they're not paying attention,
8:14
they're just selling you something standard.
8:16
or you're worried about implementation partner,
8:18
that's an area where I'd consider running. And
8:21
I saw that with, I helped the company through
8:23
the process. And when we started, I expected
8:25
one tool to win. And we got in the meetings,
8:27
it was clear one of them. had done their homework
8:29
and understood the business better. And the other
8:32
was just trying to sell something standard and
8:34
wasn't listening. So that's, that's the first
8:36
increase of a concept in the first demo. The
8:39
big thing watch for one promises, Hey, this is
8:41
on the roadmap. If you keep hearing it's on the
8:43
roadmap, unless you're, you're also really in,
8:46
in mature and you're confident in the company,
8:49
probably a good idea to run, you know, or because
8:53
the reality, if you pick any tool with only a
8:55
few years, you're going to have to deal with
8:57
some roadmap because it takes a long time to
9:00
get there. So, you know, just keep that in mind.
9:04
Don't, don't buy into just promises. So if a
9:06
lot of promises, that's an area where I'd be
9:08
concerned. And then if it's a lot of whiz bang
9:10
or we have this and nobody else does those types
9:13
of things always make me nervous when I'm like,
9:15
I've seen so many tools, people like, nobody
9:16
else is doing this. There's nobody in the space.
9:18
And what are you talking about? I'm not quite
9:20
that direct. I want to be sometimes like, And
9:24
I said to one of them, I can give you a list
9:25
of like 10 or 15 tools. No, no, none of them
9:27
are the same as us. Okay. Like I'm not going
9:29
to argue it with you, but you're wrong. And I
9:31
never heard anything from that tool after that
9:33
phone call. So they obviously didn't scale too
9:35
far. And so those are a few things. What about
9:38
you? What do you think there? What's your thoughts?
9:40
For me, like you said, When it comes to demos,
9:44
I like to see that a company did their homework
9:47
because I work right now in a not -for -profit
9:49
space. So not -for -profit, I don't, I'm not
9:52
like a food bank to have like inventory. I'm
9:55
closer to a bank, but I also getting grants.
9:58
So my financials are quite complicated because
10:02
I have to follow, um, the financial institution
10:05
audit, but also the not -for -profit governance.
10:09
And so I was shopping for FP &A. software last
10:12
year. And so, yes, the one that I eventually
10:14
narrowed down were the one that could show me
10:17
how did they put the financials of a not -for
10:20
-profit in their system? What is grand tracking
10:23
going to look like? Because you show me cost
10:26
of goods when I'm like, it doesn't fit my business
10:28
model. So - Yeah. They're showing you a manufacturing
10:30
example and you're like, not quite. And that
10:35
leads to one other thing, as you mentioned that,
10:38
that just came to mind a little different, but
10:39
- Make sure your implementation partner knows
10:41
FP &A and ideally has some experience in your
10:44
industry. How do you surface that? Because, you
10:47
know, oftentimes the people that are doing your
10:49
demo and other people that are actually going
10:50
to implement, like you're dealing with a sales
10:52
team and then the implementation is like... The
10:54
smaller you are, the more likely they're doing
10:56
the implementation. The larger they are, the
10:58
more options you have for implementation. Vendors
11:01
may have their preferred implementer. but less
11:03
control they have over who you choose. So I think
11:06
a couple of things, ask for resumes of the implementer.
11:08
Ask for references. Say, look, I want someone
11:10
that has this experience I have. I don't think
11:12
this makes sense. Or let me interview them. If
11:15
I'm not comfortable, I'm not signing the deal
11:17
until I'm comfortable. So if it's one where they're
11:19
doing it in -house, would ask. What's the worst?
11:23
They say no. And then you're like, oh, that's
11:25
a red flag. Maybe I'll go elsewhere. Yes. Because
11:29
they're not transparent for sure. Right. And
11:31
then if they're one that uses a hundred implementation
11:33
partners, and that's a pretty big name tool,
11:36
then go talk to other people that have implemented
11:37
it. You know, do a little bit of your networking
11:39
versus just trusting the company. Yes. I mean,
11:43
networking has worked really well for me because
11:45
I'm part of the CF leadership console. And I
11:48
just went in, I'm looking at these two solutions.
11:51
What would you have? And I had like 20 CF was
11:53
coming back to no, no, no, stay away. Yes. Yes.
11:56
So it definitely helps a lot. trying to narrow
11:59
the right solution. Yeah, they're a great organization.
12:01
I'm big fans of them. I'm getting ready to interview
12:04
their head, Jack McCullough. Oh, yeah. I had
12:08
it on my podcast last year. Yeah. He's a great
12:13
interview. Great guy. Yes, absolutely. So I'm
12:16
curious to hear, you know, when we look. out
12:19
at the future of FB &A and we hear a lot about
12:22
AI, our favorite topic these days. I don't know
12:25
if you've heard about AI, but where is AI already
12:29
genuinely useful in FB &A and where do you think
12:32
is mostly hype? I mean, I think variance commentary,
12:35
it can be very useful. I think it's even more
12:37
and more that anomaly detection, machine learning
12:41
AI is already very valuable. And you can combine
12:44
that with GenAI to help you learn some of that,
12:46
to build better forecasts, to bring in external
12:48
data. I think where AI is most rapidly improving
12:53
with Claude coming out for us is modeling. What
12:57
it can do in Excel now compared to what it could
13:00
do three, four, five, six months ago is night
13:03
and day. I got an episode coming up Tuesday where
13:06
we tested Claude. And we were extremely impressed.
13:10
It did some very complex stuff extremely well.
13:13
Wow. And so, and then I think the hype is in
13:17
this idea that you can almost fix it and forget
13:19
it. It's the promise of, oh, it can do all, it's
13:23
going to save you hundreds of hours and it can
13:25
do everything. I don't know many people that
13:28
are working 20 hours because they have AI. We're
13:31
still pretty much all working 40 hours. As Inch
13:34
Noir said on my podcast, he goes, I guarantee
13:37
you the lights are not going off at five at the
13:39
investment banking houses because they're all
13:42
using AI. It just means they're all doing more
13:44
work than they were doing before because they
13:46
can get more done now. And so I don't know if
13:48
that makes sense, but I think that's the hype,
13:49
this whole idea of, oh, it will just do everything.
13:53
And the second one is you don't need to review
13:55
it. You can just trust it. No, it's still human
13:59
led. If it's deterministic, just like if I automate
14:02
a process with Power Query, Power Automate, machine
14:05
learning, and I've run it a few times. Okay,
14:07
fine. I can trust that. I don't check my Excel
14:10
formula every month to make sure it's still working
14:11
the same, but it's never going to return me a
14:14
different answer unless I change the inputs.
14:16
That's not true with generative AI. Gosh, can
14:19
you tell us a bit more about one? I'm curious
14:21
to hear about your Claude experiment, but then
14:24
also the difference between deterministic and
14:27
probabilistic, like those two different models
14:29
and how they come together. Yeah. So let's start
14:31
there. So something that's deterministic always
14:35
has the exact same answer in the end, right?
14:38
Two plus two is always four. If I do a sum is
14:42
formula and I give it my sum range and my criteria,
14:45
my criteria ranges, I do all that. It's going
14:48
to return the same answer every time unless the
14:51
inputs change. If I add more rows to it, I change
14:55
a number, it will change. I use generative AI.
15:00
Gen AI's whole idea is the more stuff we can
15:02
train it on, the more likely it will be right,
15:06
the more we can fine tune the model. There is
15:08
no guarantee anytime it's going to output the
15:11
right answer. Where a deterministic I know if
15:15
I put two plus two in, I'm getting four every
15:17
single time. And so the probabilistic is it's
15:21
using probabilities to give you what it thinks
15:24
it wants. That's actually one of the biggest
15:26
weaknesses of Excel agents. I ask it to build
15:30
the exact same model two minutes later, and 40
15:33
% of the formulas could be different than it
15:35
uses to solve it the next time. I've run that
15:38
test multiple times. Opus 4 .6 was almost the
15:41
same. It was probably 80 % similar. But this
15:44
is only a model that needed five different types
15:45
of formulas. When I ran it before that, I'd get
15:48
completely different results in almost every
15:50
formula and how they solve them. And that's because
15:54
they're taking probabilities to get to the solution.
15:58
And then give me the second part of it again,
16:00
because I forgot the other part of the question.
16:03
Sure. Claude, tell us more about your experiment
16:06
with Claude and how he's helping with modeling.
16:09
Yeah. So what we've done is we have this Mod
16:11
Squad series. You can find it on YouTube. It
16:13
has his own playlist with Inch Noor, who's the
16:15
executive director of the Financial Modeling
16:18
Institute, which does credentialing for modeling.
16:21
He's a world -class trainer and Giles Mel, who
16:25
runs a modeling house. So the three of us have
16:27
been testing all the tools. We've tested eight
16:30
or nine tools now. done 12 episodes, and we tested
16:34
Claude about a week and a half ago. And we gave
16:37
it an AFM case, one of his cases that you do
16:40
in four hours with instruction. And it was 80,
16:44
90 % of the way there in 10 minutes. I mean,
16:46
it was really good. It picked up on a lot of
16:49
things. We gave it a CFM case, which is the harder
16:51
case. And it was probably 90, maybe even a little
16:54
higher. It was a debt structure, layer debt structuring
16:57
model that you had to build just that section,
16:59
just the debt section. And it did. very, very
17:02
well. Like it's at the point now where I would
17:05
trust it to build something with my inputs, with
17:09
my review, with proper checking, where before
17:14
I might use it on little sections and a ton of
17:16
prompting. Now we're starting to get to that
17:19
point where people are going to use it to build
17:20
a model regardless. They were before. But I mean,
17:23
good modelers that know what they're doing are
17:25
going to be much more comfortable having a build
17:27
sections and parts and models. Yeah. And you
17:30
can see your formulas and you can trace them.
17:32
Cause that was always my biggest thing. Like
17:34
when AI came in, I would test to see how it does
17:37
with modeling. I'm like, I need to trace my formulas.
17:39
I need to know. I don't want to see hard coded
17:41
number. I need to know where it's coming from.
17:43
You still get the occasional hard codes. That
17:45
is an issue, but getting much better. You still
17:48
get more complex formulas than you would write.
17:51
in many situations. And that's why anyone that's
17:56
an expert in this space is saying, look, AI is
17:58
a magnifier. You got to know the fundamentals.
18:01
And that's true in data viz. It's true in financial
18:05
modeling. It's true in most places. The people
18:08
who are going to get the most out of it have
18:10
taken the time to learn what they're doing. True.
18:13
And so if a finance team has zero AI right now,
18:16
what would you say is one low risk but high ROI
18:20
place to start? If they have zero AI, let's just
18:23
say, I'll start with the simplest, they haven't
18:25
used it yet in professional. Get an LLM and start
18:29
experimenting, get comfortable with it. I think
18:31
90 % of people have at least done that either
18:33
professionally or personally. Hopefully they
18:35
have. So I think the next two areas is one, use
18:39
AI to document a process and then try either
18:43
with some of these tools out there, Cloud Cowork
18:46
and N8n, a Zapier, depending on how deterministic
18:49
versus depending on the task and what you need,
18:52
try automating it. Try building out with the
18:55
help of Gen .ai that process. I think that's
18:58
a great area. Pick something that's really manual
19:01
and think about why it's manual. And I always
19:05
like to use the framework is make a list of your
19:08
pain points, look at the highest ones, say how
19:10
much could AI help on these. and then try some.
19:14
Now for that first task, maybe pick something
19:16
that's low time, fairly simple to get your hands
19:19
wet or your hands dirty, so to speak. So that'd
19:21
probably be that. The third one, I would say,
19:24
if not that I think everybody should at least
19:27
install and be testing a spreadsheet agent, not
19:30
saying turn your five -year financial model over
19:33
to it and let it build it, but start using it.
19:36
Have it audit some of your files. When you got
19:38
to do a next investment, have it maybe build
19:42
And you can still build on your own or, you know,
19:45
review it, but don't, don't just do it all on
19:47
your own. Start using it to assist you writing
19:49
formulas, whatever it may be. And where do we
19:51
start with those Excel agents? Cause some people
19:54
till this day, when I speak with a lot of people,
19:57
all they know about AI is chat GPT. They don't
20:00
even know about fraud. There's about 30 tools
20:03
out there. I just did a post today, a market
20:05
map. If you're in Google. You know, check out
20:08
what Google has. There's a few other tools. If
20:10
you're Excel, I think there's a couple places
20:13
to go right now. You could do the copilot route
20:16
and it's good. I wouldn't say it's the best in
20:19
the market, but it's good. Claude right now is
20:23
one of the best I've seen. Opus 46 is the best
20:25
model they use. So those are your first two options,
20:28
probably your cheapest and the ones that will
20:30
make the most sense for most companies, because
20:32
almost everybody has Microsoft Office. And if
20:34
you don't have Office, many people have Claude
20:36
or can get Claude within the company so you can
20:38
use it in Excel. If not one of those, then you
20:40
got to look at a third party add -in. And there
20:43
it's deciding what you really want. It's a little
20:45
more of a process. But again, it's nothing like
20:48
an FP &A. You don't need to do a formal RFP and
20:51
FP &A tool. I mean, we're talking their prices
20:53
are anywhere from 10. I think the highest I've
20:55
seen is 500 a month for a user, but most for
20:59
small companies are going to be somewhere in
21:00
the 20 to $50 a month range. Not a big investment.
21:04
Okay. So I remember when we spoke about AI in
21:10
finance, you gave a very nice framework on how
21:13
people should use AI first. You mind sharing
21:17
it again? It was like a quadrant thing. Yeah.
21:20
I'm trying to remember what my quadrant was now
21:22
that I shared. So I know, I know there's a pain
21:25
point of how you select something, but I think
21:28
beyond that, you know, something you have to
21:30
think about is one, is this a task I'm going
21:32
to repeat? Because if it's a repeatable task,
21:36
GenAI is probably not the right place. You're
21:39
going to need something deterministic in the
21:41
sense of, it's repeatable. I need the exact same
21:43
answer every time. Then it's look and say, Hey,
21:46
should I automate this with Power Query or Power
21:48
Automate? So I think you first, you need to understand,
21:50
is this the one -off? Is this a repeat task?
21:53
And then is what's the level of variability?
21:56
What's the level of tolerability? So can I have
21:59
it vary every time? Like variance commentary.
22:01
I doubt you look to say last month, well, you
22:03
used a different word here with the same variant.
22:05
Yeah. Nobody cares. And if they do, they have
22:09
too much time on their hands. Right. And so you
22:12
have to understand that. What's the toleration
22:14
for error? And that will help you decide, is
22:17
this somewhere AI makes sense? Then it's a matter
22:20
of understanding, okay, is it gen AI that makes
22:22
mistakes? Is it machine learning? Is it just
22:24
general automation? That's kind of the framework
22:26
and how I really think about it. is kind of asking
22:31
yourself those questions, then deciding where
22:33
to tackle first is that whole framework of where's
22:37
the biggest pain point, where is AI the best?
22:39
That's the ideal quadrant. If it's a low pain
22:43
point and low AI is not good, that's human. All
22:46
right, if it's a high pain point and AI is not
22:49
good, that's a wait or look to non -AI. Because
22:54
even if it's a high pain point, if you can automate
22:55
it, great, you may be able to do it with non
22:57
-AI. And then the last one is, all right, well,
23:00
if it's a low pain point and AI is good at it,
23:04
I'll put that toward the end. Or I'll use that
23:07
to experiment on because it's easy if it messes
23:11
it up because I know it's a low pain point anyway.
23:14
Yes. Yes. Thank you so much for sharing. And
23:17
I'm also curious as we are... embedding, like
23:20
you said, kind of a roadmap. I look at my high
23:23
pain point, I look at AI can really help. And
23:25
I have this whole plan of how I'm going to implement
23:30
and embed AI in my workflows. So what do you
23:33
think an FPNA team will look like if AI is fully
23:37
embedded into the workflows and processes? It's
23:41
a good question. I'm still, to a certain extent,
23:43
trying to figure it out a little bit. I think
23:45
one, you see tools. You know, there's confluence
23:49
payload, I think is others and others are these
23:51
AI analysts are coming out a lot more. So I think
23:54
what you'll see in every tool, every team is
23:56
off some kind of AI analyst. That thing can work
23:59
24 seven. And then within any large FP and 18,
24:03
you're going to have an AI kind of architect
24:05
specialist that can help with agent stuff. Cause
24:08
no matter what every company wants to make it
24:11
simple and, and do that. There's going to come
24:13
a day where nobody's going to outsource all their
24:16
agentic AI to have someone else build that workflow
24:20
or that agent. They're going to start doing that
24:22
in -house, just like nobody has all their modeling
24:25
outsourced. You build some of that. So I think
24:29
there will be an AI architect that will help
24:32
bridge that gap. Kind of like you've seen in
24:34
the last 10, 15 years, 20 years, many more finances.
24:38
Sometimes FP &A transformation people are kind
24:40
of systems people. I think you'll see the equivalent
24:43
of an architect. I think structures, especially
24:47
bigger companies will become a little more flat.
24:49
You won't need as many analysts. Now that's not
24:52
to say other jobs won't come about because you'll
24:54
have the AI architect. You may even have an AI
24:57
implementation person, depending on the size.
24:59
Someone who trains, they may be company -wide,
25:02
they may be... you know, FP &A or finance, the
25:05
whole office specific. But those are some of
25:08
my thoughts right now. And I think you'll continue
25:11
to see more and more of the collaborator style
25:14
in FP &A. I'll give an example of that. My last
25:16
job before I started my own business, my job
25:19
title was director of finance, operations and
25:24
data analysis, something like that. I didn't
25:27
manage a single person. I didn't even actually
25:29
build the budget, funny enough. I coordinated
25:32
between FP &A, operations, and our data analytics
25:38
team on what all our reporting was going to look
25:40
like and how we were going to make the transition
25:42
to a SaaS business with leadership. And so it
25:45
was much more of a coordination and collaboration
25:48
role where they're looking from experience because
25:51
you're managing and having conversations. OK,
25:53
let's clarify what bookings means across the
25:55
company. And so I think you'll see more and more
25:57
of that collaboration. And strategic, not just
26:00
tactical, but a lot of strategic collaboration.
26:03
I think that will become a more prominent role.
26:06
Even more than it is today. Okay. And as you're
26:09
training corporate teams and you know, the curriculum
26:13
is probably changing. Maybe you seeing CF was
26:16
already asking you to emphasize more things than
26:20
others. Like what have you seen lately? So, you
26:22
know, I'd say over the last few years and starting
26:25
to see more and more of AI training, but soft
26:29
skills, and Excel. Those are the two biggest
26:33
that I see quite a bit. On the soft skills side,
26:38
a lot of storytelling, sometimes around managing
26:41
time or conflict, but I say storytelling and
26:43
influencing. So many are like, I need my FP &A
26:47
to be a better business partner. I need them
26:50
to be curious. I need them to understand operations.
26:53
I can't tell you how many times I get people
26:55
saying some combination of what's most important
26:58
for FP &A is, as far as being a better business
27:00
partners, understanding operations, being curious.
27:04
I've had many people say the most important soft
27:06
skill is empathy. Now those aren't the things
27:08
you think of when you think of your FP &A person.
27:10
When you're hiring, you don't think, I wonder
27:12
if they have a lot of empathy. I never did. I'll
27:16
admit it. I never once thought, hmm, wonder what
27:18
their empathy's like. Yeah, that's an area that
27:22
I think FP &As they're wanting to see more and
27:24
more of. And then recently, obviously, the one
27:26
everybody's asking about is AI and not getting
27:29
left behind and how can I use it? And I just
27:32
trained a large makeup company recently in cosmetics.
27:36
There are staff of about 40 people on copilot.
27:38
And so when you think about how CFOs will need
27:41
to reskill their team to thrive in this environment,
27:45
because like you said, soft skills, it's kind
27:47
of hard to teach. So I'm curious to get maybe
27:50
a one -on -one business partnering from the FP
27:52
&A guy right now. Yeah. So, I mean, definitely
27:56
there are aspects that are hard to teach. For
28:00
me, if I'm telling someone to be a better business
28:03
partner, the things they can easily control and
28:05
where they can start. One. You can learn the
28:08
business, regardless of how good your communication
28:11
skills are, regardless of all your other soft
28:13
skills. You can go out and ask for those meetings.
28:15
You can really come to understand the operations.
28:18
Two, you can learn to be humbly curious. And
28:21
when I say humble curiosity, the reason I use
28:24
that term, it was someone, it was coined by a
28:27
guest I interviewed, is because we all have the
28:30
person who's curious just because they want to
28:32
prove you wrong, or they're curious because they
28:34
want to be right or look smart. You need to be
28:37
curious because you deeply want to understand
28:40
your business and your business partner. I think
28:42
those are things everybody can easily work on.
28:45
Three, which will tremendously help your soft
28:48
skills, is learn to be good at data storytelling,
28:52
but also data visualization. And data visualization,
28:55
there's a lot of science to that. By learning
28:58
what a good visual is like, you can go a long
29:01
way on the technical. That allows you to then
29:04
tell a better story. which is going to eventually
29:06
allow you to be a better influencer. So sometimes
29:09
you can start with those easier things that really
29:12
are about effort, then work on fine tuning with
29:15
your bosses and hey, where are my biggest weaknesses
29:17
and really tackle those. Okay. Your boss like,
29:21
well, you're really bad at pushing back. Okay.
29:23
What's the plan to do that? Or I'll give a personal
29:25
example. I was way too detail oriented. I literally
29:28
had a director who wasn't my director, but he
29:30
kind of was because the other team was all elsewhere.
29:33
And so we talked quite a bit. He told me, he
29:35
goes, look, every time you get too detailed,
29:37
I'm going to tell you. And he would just, I am
29:39
in a meeting and he's like, bring it back up.
29:41
You've lost everybody. And you know, that really
29:44
helped a lot. And then I had a general manager
29:46
that looked at me one time and he said, Paul,
29:48
I'm going to teach you the bluff principle. I'm
29:50
like, I don't play cards. What are you talking
29:51
about? And he goes, bottom line up front. He's
29:54
like, just get to the point in your messages.
29:56
Then you can add whatever you want to the bottom.
29:58
Cause I was trying to give the entire background
30:01
and all of them. And so it stalled my career
30:03
for a while. And so that's something that I would
30:06
recommend. Okay. Thank you. And now I'm curious
30:10
about, you know, now that you are training more
30:12
and more teams, what do you hear from the professionals
30:16
that you are training? Not so much the companies,
30:19
but the actual FP &A analysts and managers. What
30:22
are some of their concerns or worries right now?
30:25
Or what do they want to learn more about? You
30:27
know, they're all interested about AI right now.
30:30
Okay. You know, a lot of them are, they often
30:32
have a certain situation or what do you do with
30:34
a difficult partner? That often comes up a lot.
30:37
We're having conversations like, well, what if
30:39
the business is not listening or how do I manage
30:41
that? And so we'll often try to walk through
30:43
different situations. But I think right now the
30:46
overarching for most of them is really trying
30:48
to figure out what the impact AI is going to
30:50
have because everybody's afraid to change. And
30:53
the pace of change in the last, what, six years
30:56
since COVID has been unbelievable. I think almost
31:00
everybody, whether they say it verbally or not,
31:04
is just the constant changes on a lot of people's
31:07
minds and it creates anxiety. Even though I think
31:09
in the end it will be a good thing. I think on
31:12
the whole, we could benefit in society. There
31:14
will definitely be impact. Yes, there will be
31:18
for sure. So what is the best career advice you
31:22
ever received or usually give to FP &A professionals?
31:25
I think the best advice was an advice. It was
31:29
watching how much my dad was willing to serve
31:32
and work. And so seeing that is something I've
31:35
taken into my own life. I'm a big believer in
31:37
the best way to help others is to serve others.
31:40
And I had to learn, not everybody shares that.
31:42
Sometimes you have to take different approaches
31:43
in leadership. But I think being willing to work
31:45
hard and serve. And then the advice I give people,
31:48
usually they're people wanting to break into
31:50
FP &A. And so I break it out different depending
31:53
on where they're at. But one of the biggest things
31:56
to say, look, if you want to be good at FP &A,
31:58
One of the biggest advice that I always give
32:00
is learn the business. If you're trying to get
32:02
into FP &A, create that roadmap, figure out your
32:05
weaknesses, make sure you can do Excel, make
32:07
sure you can do financial modeling. But remember,
32:10
because most advice to get are people reaching
32:12
out wanting jobs and in that area. And one of
32:16
the biggest things I try to tell them is your
32:17
job is to make sure the hiring manager doesn't
32:21
feel risk in hiring you. If you can reduce that
32:25
risk, I'll give an example. Let's say you're
32:27
hiring someone and one looks like, Hey, they
32:28
have the potential to be a superstar, but they
32:30
might completely flame out. So there's a little
32:32
bit of high risk, but you can see there's a really
32:33
high reward. Are there's one that, okay, they're
32:35
going to be a good performer. I'm not sure they're
32:37
ever going to be a superstar, but I have almost
32:39
zero risk. Who are you typically going to go
32:41
with? The second person. Right. And especially
32:43
in finance, we tend to be risk adverse. Yes.
32:46
You're going to take the second. So I think,
32:48
you know, helping people realize you're really
32:50
trying to mitigate risks. So think. understand
32:53
what their pain points are. And that's more job
32:55
than career. In career, I think the biggest advice
32:58
I would give is learn how to serve within whatever
33:02
you're doing. Thank you so much for sharing.
33:05
I can tell, you know, from how you helped me
33:07
with my podcast and so many others. I know I
33:10
joked I call you the Oprah of finance podcast.
33:14
Put that picture of Oprah with a beard on LinkedIn.
33:17
Oh, that was That was DHA marketing, yum, out
33:21
of France. Oh, gosh. But yeah, I can see and
33:26
I'm super grateful for the work you've done,
33:28
not just, you know, on LinkedIn, but also behind
33:31
the scene on LinkedIn. People may not see all
33:33
the DMs you send to support, you know, the whole
33:36
community. So thank you for that. I think I appreciate
33:38
that. It's been fun. What's it been now? Three
33:40
years? Yep. Three years already. Yeah. We're
33:44
getting old. No. 39 .99. Inside joke. Sorry,
33:51
everybody. Yeah. Inside. No, completely. We're
33:55
going to keep it inside. Last question. What
33:58
is your favorite thing to do outside of work?
34:00
Outside of work? What's this you talk about?
34:02
No, there's a few things. I like spending time
34:05
with my family. I have a 12 year old daughter.
34:07
I get to spend a lot of time with her. I enjoy
34:09
running. I usually run every day. And then I
34:12
like young adult fiction. I'll admit it. There's
34:14
my guilty pleasure. Oh, okay. Nice. I'm in Netflix
34:18
and recently I started lifting more ways than
34:22
Cheetos. So it's getting there. What brand is
34:25
heavier than Cheetos? Yeah. Cheetos. Like I haven't
34:30
had any Cheetos since the Reno 2026. So to me,
34:34
this is like a big achievement. No, I need it.
34:38
I, I'm continuing trying to eat better. I had
34:41
a I had some health challenges in 25 and I got
34:44
to be better with my eating. So I get it. But
34:47
you run so much. How many miles a year in a day?
34:49
Um, usually it varies whether I'm doing a speed
34:53
or long run, but three to six, although I've
34:56
missed this week, unfortunately, but probably
34:58
three to six miles. I'd like to get more of about
35:01
eight, eight on average a day. So about 50, 60
35:04
a week. I want to run the Boston marathon. Oh,
35:06
good. Good for you. I ran my first marathon when
35:08
I was 17. Fun fact. Well, we'll continue cheering
35:13
you on for a distance. When I go to Boston, I
35:15
expect you to be there at the finish line. Oh,
35:20
okay. We'll try not to finish. I cannot promise
35:25
that it won't work. Well, thank you. Thank you
35:31
so much for being on the show. Well, thank you
35:33
for having me. Always a pleasure. Thank you.