Poker, Probability, and Financial Modeling with Dan Mayoh
In this episode of Financial Modeler’s Corner, host Paul Barnhurst sits down with Dan Mayoh to discuss his career in financial modeling, lessons from model auditing, and why he sees Excel as one of the world’s most accessible programming languages. Dan also shares how mathematical modeling, poker, and probability have shaped his approach to risk and decision-making under uncertainty.
Dan Mayoh is the Founder and CEO of Fintega Pty Ltd and a financial modeling and spreadsheet specialist with more than 15 years of experience. With a background in actuarial studies, Dan began his career in model auditing before moving into financial modeling and consulting. He also placed second in the inaugural ModelOff competition and was an early CFM holder with the Financial Modeling Institute.
Expect to Learn:
Why Excel can be viewed as a programming language.
What model auditing teaches you about model design.
How Modeloff helped Dan grow as a modeler and consultant.
How mathematical modeling helps quantify risk and uncertainty.
Why good decisions should not be judged only by outcomes.
Here are a few relevant quotes from the episode:
“Excel is really just the most accessible programming language in the world.” - Dan Mayoh
“Sometimes you win. Sometimes you lose, even when you make the right decision.” - Dan Mayoh
Dan explains that strong financial modeling goes beyond formulas and functions. Structure, navigation, error checks, usability, and designing around the end user all play an important role in creating models that are easier to understand, update, and trust.
Follow Dan:
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Disclosure: Portions of this episode (such as the introduction or promotional segments) use AI-generated voice narration that has undergone human editorial review.
In Today's Episode:
[00:00] - Trailer
[03:40] - Dan’s Financial Modeling Journey
[06:05] - Building a Career in Financial Modeling
[12:14] - Modeling as Software Development
[15:09] - Financial Modeling Horror Stories
[19:19] - Lessons From Model Auditing
[22:03] - Competing in ModelOff
[27:39] - Mathematical Modeling of Games
[32:04] - Modeling Risk in Real-World Projects
[35:13] - Decision-Making Under Uncertainty
[40:53] - Rapid Fire: Excel & Modeling
[44:22] - Closing Thoughts
Full Show Transcript:
00:00:28.760 — 00:01:18.910 · Host: Paul Barnhurst
Welcome to Financial Modelers Corner. I'm your host, Paul Barnhurst, the FP&A guy. And in this podcast, we talk all about the art and science of financial modeling with distinguished guests from around the globe.
The Financial Modelers Corner podcast is brought to you by the Financial Modeling Institute. FMI offers the most respected accreditations in financial modeling, and that's why I completed the Advanced Financial Modeler and encourage you to do the same if you haven't. This week, I'm thrilled to welcome Dan Mayoh to the show.
Dan, welcome to the show.
00:01:19.190 — 00:01:24.470 · Guest: Dan Mayoh
Hi, Paul, thanks for having me. It's good to know your long, distinguished guests sneak in from time to time.
00:01:24.470 — 00:01:29.670 · Host: Paul Barnhurst
We get all types and I would say distinguished. I mean, you came in was a top three and model off right?
00:01:29.710 — 00:01:31.310 · Guest: Dan Mayoh
Top two. Actually, in the first year.
00:01:31.950 — 00:01:34.990 · Host: Paul Barnhurst
I thought it was second, but I wasn't. I couldn't remember for sure.
00:01:35.070 — 00:01:40.190 · Guest: Dan Mayoh
Yeah. And I was one of the earliest CFM holders in the Financial Modeling Institute as well.
00:01:40.190 — 00:01:49.310 · Host: Paul Barnhurst
So this is the chair financial modeler. And you know, many of our guests are interested to know you do a fair amount of poker playing. You've done some professional poker playing, right.
00:01:49.350 — 00:02:00.460 · Guest: Dan Mayoh
Yes I do. I made some money. I came in playing poker. It would be nice to do it, I think full time professionally, but hard to do that at the moment with the traveler would require and so on. But yeah.
00:02:00.500 — 00:02:07.860 · Host: Paul Barnhurst
Yeah. As to say you're in Australia as the case, I guess for wondering, I'm going to guess most of the tournaments aren't in Australia that would allow you to make a full-time living.
00:02:07.900 — 00:02:28.820 · Guest: Dan Mayoh
There are, particularly if you want to point, know them and hold them. I think there's enough in Australia that you could certainly play full time. Whether you could earn enough to make a living full time is another question, but I tend to prefer the mixed games. Things that aren't. Know them and hold them and they're not as popular.
And so yeah, for the really big events there, you do have to travel to the US from time to time.
00:02:28.820 — 00:02:35.660 · Host: Paul Barnhurst
And that makes sense. And I do like how you said you could definitely find enough games to play full-time. That doesn't mean you'll make a full-time living.
00:02:35.740 — 00:02:48.420 · Guest: Dan Mayoh
Yes, literally. Tournament poker. It's very high variance. People can do everything right and still have an edge theoretically, or, you know, have a long-term expected value and still lose $100,000 in a year as well. Doing that.
00:02:48.780 — 00:02:50.740 · Host: Paul Barnhurst
There's still a chance component to all this.
00:02:50.780 — 00:03:16.440 · Guest: Dan Mayoh
Of course, if it wasn't, it wouldn't work as a gambling game. It would be like chess ahead of time, who's likely to win the game? Just the better player and those better players are therefore find it harder to get action. To say, getting action would be like finding someone to play against you for money. A good game for that needs the right balance of luck can prevail in the short run, but skill will prevail in the long run.
And poker and backgammon are good examples of that.
00:03:16.480 — 00:03:27.400 · Host: Paul Barnhurst
Yeah, makes a lot of sense. You want you need enough of a skill component that people feel confident that over the long run, they can come out ahead. There's an element that kind of also can be fun to.
00:03:27.440 — 00:03:40.080 · Guest: Dan Mayoh
Yeah, otherwise the weaker skill players won't ever put up their money against the more skilled players you figure to lose 99 times out of 100 or 100 times out of 100, they need to win, you know, 20 or 30 times out of 100 to make it worth that.
00:03:40.080 — 00:03:57.790 · Host: Paul Barnhurst
Well, let's jump into the episode. We'll talk a little bit more about gaming. I know we have that on the schedule, so hopefully people enjoy that. But before we jump into a couple career questions I want to ask, do we have a career corner section? Why don't you just take a minute and tell our audience a little bit about your background.
Just kind of give them the rundown of Dan.
00:03:57.990 — 00:04:55.740 · Guest: Dan Mayoh
Yeah, sure. I'm a mathematician at heart, and when I was at university, that came through and I did a degree in actuarial studies, so I got an actuarial background. And then it was around the time of finishing university, and I did a 12-month placement overseas in Colombia, working with PricewaterhouseCoopers in South America and a lot of the work there.
I sort of got exposed to financial modeling, and I think I made the decision then I wanted to make my career out of financial modeling. And so when I returned to Australia, I sought out a job in that field. And that was 20, 21 years ago now. So it feels like a while. And my first job was as a model auditor when I was working in a team where probably half the people in that team, ten out of 20, had actuarial backgrounds.
I guess there was just something about the skills and the way how we approach logical problems and details, oriented or not, that made us good model what it is. And yeah, that's where it began. And then do you want the rest of the quick career highlights from there as well?
00:04:55.780 — 00:04:59.740 · Host: Paul Barnhurst
Well, sure, sure, if you want. Go ahead and give us another minute or so. A couple of the highlights.
00:04:59.780 — 00:05:42.780 · Guest: Dan Mayoh
And then five years in that model auditing team, which I was living in Sydney at the time, we did Job Australia and all around the world, as well as probably half Australian projects and half international projects, and then I left that took an in-house job at what has become Australia sort of green Bank, the Clean Energy Finance Corporation.
I got in there at a very ground level. There was a little pilot company called Low Carbon Australia started a few years before that and got in there. The ground level was there. Financial modeling Guy did that for a few years and then branched out into my own consulting business, and I've been doing that consulting business for 12 or 13 years now, essentially building spreadsheet models for corporate clients with a little bit of model auditing and training on the side.
00:05:42.820 — 00:06:05.330 · Host: Paul Barnhurst
I love the background. Appreciate that. The first one I want to ask is, I'm curious, when did you realize kind of financial modeling could be a career path. Right. It's not. It's like it's never been a degree in school. Historically, it hasn't been a career. It's just part of a job you do. But today, really financial modeling.
Some people will call themselves the financial modeler. So how do you think about that?
00:06:05.810 — 00:06:14.370 · Guest: Dan Mayoh
Yeah, I think it was probably maybe during that year when I was in Columbia with PwC, um, that I mentioned, when I did
00:06:15.490 — 00:06:34.489 · Guest: Dan Mayoh
realize that it could be a career. Um, I remember even learning about, you know, actuarial studies as a, as a thing and being an actuary, I was only sort of in year 11 or 12, like immediately before university when I first heard of that and learned about it. Um, and I think it was just
00:06:35.570 — 00:06:57.870 · Guest: Dan Mayoh
playing around with building, you know, spreadsheet models, um, and building, you know, either something for a client or something to use in-house, like a, you know, a calculator tool that did something specific. Um, which I would now think about is essentially, you know, you've been tasked with writing a piece of software and you're just using Excel as the programming language to do it.
Um,
00:06:59.030 — 00:07:24.190 · Guest: Dan Mayoh
yeah, it was probably at university. And that first year after university where I, I kind of realized, um, okay, you can actually make a career that you can find jobs that specialize in this and you can become really good at that. Um, and you can learn best practices similar to how, you know, software programming would have best practices as well.
Um,
00:07:25.630 — 00:07:46.110 · Guest: Dan Mayoh
so then I went looking for jobs in that area. Um, and they'll come back to Australia. They were in Sydney or Melbourne, and I grew up in Canberra. I was living in Canberra at the time. Um, so I knew I'd be moving to one of those places. And yeah, I found a job in, in Sydney. It was actually, um. No, I'm not going to tell you that story.
Doesn't matter.
00:07:47.980 — 00:07:49.859 · Guest: Dan Mayoh
Um, so yeah, that was it. And now
00:07:51.580 — 00:08:27.660 · Guest: Dan Mayoh
I look at it now and I you can't absolutely make a career out of it. Um, I think there's a lot of industries, like in investment banking where, you know, the modeling is given, you know, to people at the very earliest stages of their career when they go into investment banking and they're maybe not taught properly or taught to the same rigor, um, how to do it well, or they're just expected to want it themselves.
Uh, and then they'll do that, you know, for a few years, and then they leave it behind as they move on to, you know, other tasks that investment bankers do. Um,
00:08:28.740 — 00:09:16.050 · Guest: Dan Mayoh
and so people that have gone through that kind of track, you know, whilst they certainly know their way around a model, um, I think aren't as skilled or they certainly it's noticeable to a professional whose whole career is financial modeling. Um, you know, there's there's noticeable gaps in their skills.
Whereas someone who was, you know, chosen to specialize in, um, has, yeah, advantages. Um, and yeah, most, most of those people end up in consultancies, I guess, and working for, for specialized financial modeling consultancies, either, you know, running their own businesses or as part of larger businesses.
You know, like your prices at the world and so on. Um,
00:09:17.850 — 00:09:24.890 · Guest: Dan Mayoh
and then, yeah, I don't know what it's like now in the US. I remember, you know, ten years ago, certainly
00:09:26.130 — 00:11:01.260 · Guest: Dan Mayoh
being of the view that, you know, Australia and the UK had quite mature markets, um, for financial modeling professionals and even with model auditing as well. Um, those markets used formal model audits or what more um, as part of their transactions, whereas in the US it wasn't. It wasn't as common a thing.
Um, and so that's definitely been eye opening for me, I think. Ever since model I've started really, which was 2012. Um, and then in every year through that, I was branching out internationally and I was, you know, meeting people and meeting other top quality models from around the world. Um, including from the US and learning, um, you know, the different ways, different approaches to financial modeling in different parts of the world.
Um, and even, you know, your FMI, which which sponsors this podcast. Um, I've had quite a few debates with, um, with Ian in the early days of FMI about, um, you know, what is best practice and, you know, and I'll, um, you know, working with him on developing the AFM Naming them and creating cases for the CFM exam.
You know, um, and, you know, the, the norm way of doing things in Canada and the US is maybe different to what I feel is the normal way of doing things and the best way of doing things. And so it's just interesting to be aware of that.
00:11:01.300 — 00:11:44.650 · Host: Paul Barnhurst
Yeah. You bring up a great point. And definitely, you know, it's and it's different in profession. You know how project finance goes about it is different than maybe what best practice is for M&A or best practice if the model is going to be used again and again versus a one time transaction. And so there are I mean, there's there are certain things that should apply to every model no matter what.
But then you get into the okay, well here I have to do it other places. I probably shouldn't do it. Like there are some places where you might have to have some circular references. There are others where it's like, you know, the general is not at all or just different things. So I totally agree with you. It's interesting to see how different it can be depending on how somebody was brought up and what area to focus on.
00:11:44.690 — 00:11:53.410 · Guest: Dan Mayoh
Yeah, but ultimately, if you're writing the model for someone else, um, yeah. You got to be a little bit to what they want and what they expect and how they're going to use it. You know.
00:11:53.450 — 00:12:14.570 · Host: Paul Barnhurst
Correct to your audience and their skill level. And there's so much that goes into that. So I have one more one more question I kind of want to ask in Career Corner. And then we'll, we'll move kind of the main part of the interview. So what's one skill kind of over your career that you've developed as a modeler that you think most people would be surprised by, that they don't typically think of as the skill modelers have to develop?
00:12:14.690 — 00:12:25.850 · Guest: Dan Mayoh
Yeah, I, I don't know, I read this question, you know, earlier today, um, knowing you would ask it and struggled to really think of an answer. Um,
00:12:27.410 — 00:12:51.560 · Guest: Dan Mayoh
maybe the thing that comes to mind right now is just the similarities between modeling and software development, I think, um, and just thinking about, you know, uh, a model being like a, you know, a computer program that you're developing in Excel is just the language that you're writing in it. Um, and
00:12:53.520 — 00:13:31.919 · Guest: Dan Mayoh
yeah, some people have never thought of Excel that way. Um, and that it is really just, you know, the most accessible programming language in the world. Um, you know, it's a great open sandbox for anyone who wants to play around with it. Um, but then you can also write, you know, um, professional, um, you know, models in it, um, that underpin, you know, transactions in the tens of billions of dollars as well.
Um, and it is still the tool that the industry uses at the big end of town for those things. Um, you know, and it's
00:13:33.040 — 00:13:39.190 · Guest: Dan Mayoh
I could go on and on about, you know, Excel here and that it just, you know, and people,
00:13:40.990 — 00:14:20.510 · Guest: Dan Mayoh
um, a lot of businesses might start using Excel for one kind of thing, and then they grow to a certain size and they outgrow using Excel for that thing. And they need a better, you know, solution and database type work. CRM type work is an example there. And then they, uh, you know, make the mistake of assuming that because Excel is not appropriate for that task, when you get too big, that means Excel is not appropriate for any task when you get to be an important.
And and that's absolutely not the case. Um, because when it comes to financial modeling, it is it is still the best software that is, um, you know, still used on the biggest transactions.
00:14:20.510 — 00:14:38.060 · Host: Paul Barnhurst
So there's a reason a billion people use it. So I like that computer programming — you know, learning programming skills is not something people often think about. But you're right. I mean, Excel is the most accessible programming language in the world if you want to think about it that way.
00:14:38.100 — 00:15:04.659 · Guest: Dan Mayoh
Yeah, and I think designing a financial model on paper, before you start building it and all the components it'll have and how they'll link to each other, um, you know, can be quite similar to, you know, when you want to write, you know, a piece of software that does something and designing the flowchart of the logic of the software on paper as much as you can as well, before you, you go and start building it, um, as well.
There are similarities there. So
00:15:05.700 — 00:15:09.740 · Guest: Dan Mayoh
that's probably the best answer I can give you to that specific question that works.
00:15:09.740 — 00:15:15.100 · Host: Paul Barnhurst
All right. I know you have a horror story about your modeling career. Tell us that.
00:15:15.380 — 00:15:45.040 · Guest: Dan Mayoh
Yeah, that was the other question that stopped me, you know. Tell me about your worst financial model ever. And if I split this into models that I've kind of built from scratch versus just models that I've seen or, you know, been tasked with as an auditor or, um, been tasked with to rewrite sections of, you know, as a consultant.
I think they're quite different answers. Um, models that I've, you know, built from scratch. Yeah, not many horror stories there.
00:15:45.080 — 00:15:45.880 · Host: Paul Barnhurst
That's good.
00:15:45.920 — 00:16:05.480 · Guest: Dan Mayoh
That's. Yeah, there's a lot where the goalposts move. You know, in the middle of the project or at the end of the project, to adapt. Um, and there's some models that I would have written, you know, 15 years ago that if I opened it up now and have a look at it, I would I'd just be shocked at, um,
00:16:06.840 — 00:17:15.709 · Guest: Dan Mayoh
that I was capable of producing something of, you know, such low quality as I would do now. Uh, but I guess that's good as well, because it shows up being, you know, wanting and advancing those skills. Uh, but nothing truly horrible there. Um, but from an auditor point of view or from a, uh, you know, a consultant where, um, you know, acquiring might ask you to, you know, take their model and, you know, maybe take their template and use that as the basis for writing something for a certain transaction or, you know, take their model and just rewrite one part of it, but, you know, not touch the rest of it.
And that sometimes doesn't really work. Um, there's just been some bad ones that with more experience now, I was just going to say no, you know, to the to the, um, to the brief, much earlier in the process. Um, and then from a model, the worst ones would just be every now and then as a model auditor, you just see something that's truly shocking and is almost,
00:17:17.069 — 00:17:27.109 · Guest: Dan Mayoh
well, can't really be audited. Well, because there's just too much wrong with it, you know? Um, and it just needs to die and, uh, be reborn
00:17:28.220 — 00:17:31.020 · Guest: Dan Mayoh
The uniform. Um, and
00:17:32.740 — 00:18:03.460 · Guest: Dan Mayoh
yeah, I, I. But from the auditing point of view, I can't. I mean, I know things like that have existed, but I can't remember specifically what they are from the. Here, take my model and, you know, use that as a starting point for the work we want you to do. Uh, yeah. A couple comes to mind, but I don't want to name names of certain clients that have done that and so forth.
I'll just say that, um, with more experience now, I know not to get myself into those corners to begin with.
00:18:03.500 — 00:18:19.980 · Host: Paul Barnhurst
Good way to put it. There are times when it's like I've learned. I'm steering clear of that one. Not surprised to hear you say that when you get some models that you're auditing is like, this thing just needs to be needs to die and reborn. We've all opened a spreadsheet before and we're like, what were they thinking?
00:18:20.500 — 00:18:25.339 · Guest: Dan Mayoh
It's a challenge as a consultant, particularly, you know, working for myself with
00:18:26.370 — 00:18:51.689 · Guest: Dan Mayoh
You might be at a, you know, just a point where, you know, you're desperate for the work and desperate for revenue and say you'll say yes to something that, you know, you should have said no to, um, or, you know, you'll agree to do what the clients weigh, when you should have pushed back harder, you know, to do it a different way or something.
Um, and then, yeah, you just get yourself into a real hole. Um, and
00:18:53.050 — 00:19:18.330 · Guest: Dan Mayoh
yeah, you either painfully get through it or you, you know, admit defeat far wider than you shove and, uh, pull the plug on the thing and just wasted everyone's time and money for a little bit. So it's, uh, it. Yeah. My learning from that is to, um. Yeah. Listen to the little voice in your head that tells you you should say no to something, even if you're, you know, really desperate for the work.
00:19:19.410 — 00:19:47.950 · Host: Paul Barnhurst
You know, that's one of the most important lessons you have to learn as a business owner is when to walk away, when to say no, you're like, but the revenue is good. Yeah, but it's just not worth it in the long run sometimes. So I'm not surprised to hear you say that, because that's definitely one I've had to learn.
All right. So you started your career in auditing? I'd love to dig into that a little bit. What did you learn from auditing models that you've taken with you today that's shaped the way you build models?
00:19:48.030 — 00:20:07.950 · Guest: Dan Mayoh
Yeah. Just, you know, being exposed to lots of different styles of models. You learn pretty quickly what works well and what doesn't in terms of design principles. Um, for the most part, and you know, the exact syntax of a formula or exact choice of a function used is,
00:20:09.830 — 00:20:56.740 · Guest: Dan Mayoh
I think, far, far less a part of the learning than just, you know, how to lay out the model, how to structure the navigation around the model, how to structure your error checks, how had a, you know, not nicer ways to, you know, build a table of contents that can, you know, dynamically, update easily and, um, you know, nicer ways to just lay out each sheet to, to be able to find your way around the model and find the part you're looking for.
And, um, you know, even in terms of, you know, what you do with the first, you know, 12 columns of each sheet for, you know, different labeling and helper cells and things like that, you know, before you get into your timeline and, and just what works.
00:20:56.740 — 00:21:03.900 · Host: Paul Barnhurst
Well, that makes sense. There's just there's a lot of value in being able to see a lot of different ways of doing things. Yeah, yeah.
00:21:03.980 — 00:21:55.969 · Guest: Dan Mayoh
Um, but then, you know, an auditor is a bit unique in that they have to, you know, pretend to be a user of the model as well as have to, you know, really investigate in every cell the models that they really need to learn what the model's doing, um, and drill into that. Um, and so you pick up on every little thing that makes that easier, you know, to do.
And, and then you can put your developer hat on and, um, you know, and when you need to make adjustments to the model or you need to update one section of the model or some goalposts move and you got to amend one thing, or you've got to add a new feature to the model. There's um, definitely design principles you can follow that make those development tasks easier versus other as well.
You know like sort of
00:21:57.010 — 00:22:03.450 · Guest: Dan Mayoh
and I could get into that. But it's um, you know, it's beyond the scope of what we're talking about today.
00:22:03.490 — 00:22:18.010 · Host: Paul Barnhurst
It makes it makes a lot of sense. Appreciate that. So I want to ask one question. You competed in model off, right. You mentioned that I think you came in second in the world. You mentioned that really helped give you confidence to start your consulting business. So maybe you can share a little bit about that.
00:22:18.090 — 00:23:10.360 · Guest: Dan Mayoh
Yeah. So this was in 2012, which was the very first year my life was wrong. And I, um, I learned about it. I think I was I was a member of, um, an online sort of learning platform called, uh, Excel Hero Academy, uh, which was, you know, paid course run by a guy named Daniel Ferrer. Um, and then, you know, one of the, the sort of the bulletin boards on that, um, website, you know, I learned about model off the competition and signed up out of curiosity to what a financial one competition would be like.
Um, yeah. Ended up qualifying for the the finals in New York. They flew me in New York and I was one of 16 from around the world came second in that. Um, and so that was, I guess, the first eyeopener that, you know,
00:23:11.640 — 00:23:18.829 · Guest: Dan Mayoh
previously I and I ever know. And I was like the best Excel guy in my office. Um, you know, And now I had a
00:23:19.870 — 00:23:29.950 · Guest: Dan Mayoh
benchmark against, you know, um, a much wider, you know, group from around the world on that, um, so that, yeah, I guess gave me a,
00:23:31.710 — 00:23:48.630 · Guest: Dan Mayoh
made me aware maybe of the, um, the level of my skills, but more so it was actually the organizers of model off that I met, um, and, you know, three, three names, um, John Persico and Johann ODU, who,
00:23:49.750 — 00:24:17.890 · Guest: Dan Mayoh
you know, were behind the model of competition. And Joseph McDade, who was, uh, wrote the questions for the model of competition for the first year. I'm sure a lot of your listeners might be aware of. Joe McDade has since gone on to work for Microsoft in, uh, Redmond as one of the Excel program managers and boards, dynamic arrays and all those things.
Um, but Joe, at the time, you know, was just working for his own little Excel consultancy out of Melbourne with a couple of business partners.
00:24:17.930 — 00:24:37.410 · Host: Paul Barnhurst
Appreciate you sharing that and kind of, you know, it's amazing how often the connections help us. Not so much. I mean, I'm sure you learned a lot from model off itself. Great experience to compete, but it's the people you met that really kind of helped you saying, oh, I can do this. There's a lot of other there's others doing it kind of help me get it set up because I can.
Yeah, absolutely.
00:24:37.650 — 00:25:48.200 · Guest: Dan Mayoh
It shows you how to do it, shows you that it's it's possible. It's not that hard. Um, you know, and whilst I, I guess I had, you know, the, the, the technical skills, um, you know, to, to sell them out as a consultant, um, you know, yeah. The resulting model of made me aware, you know, that, um, you know, I was.
Yeah, maybe more elite than I was aware of. Um, on that technical side. Um, but, yeah, it was really just just the people that showed me how to to follow that path. Um, yeah. I'm still friends with them all to this day. I remember, you know, conversations with with Joe, um, you know, the teams prior to dynamic arrays coming out.
You know, I, I'd signed an NDA with, with Microsoft so he could talk to me about these things and, um, you know, chatting with him about certain features of dynamic arrays and how they would work and what syntax would use. So things like the symbol and the hash symbol and what they do with the A's and, um, you know, all these, all these conversations, um, where I'm bouncing ideas around, you know, with Joe's, uh, it's good fun.
00:25:48.240 — 00:25:58.680 · Host: Paul Barnhurst
It's funny, when you mentioned dynamic arrays, you know, I was teaching that yesterday, and it's never ceases to amaze me how many people are still have no clue that Excel can spill.
00:25:59.360 — 00:26:00.080 · Guest: Dan Mayoh
Yeah. Okay.
00:26:01.120 — 00:26:15.390 · Host: Paul Barnhurst
Yeah. I mean, you and I know it, but just it's it's pretty amazing how many people are still unaware that it's dynamic by nature now. Still operate always in single cell. And there's times you need to. They did a great job of allowing it to do both.
00:26:15.430 — 00:27:00.269 · Guest: Dan Mayoh
Yeah they did. And but you're right. We just had that little shift of, um, you know, not needing the control shift into anymore because every formula is by default heading as an array. And you know, the day that happened, which is led to also the spilling, it's. Yeah, I get that people who aren't power users, you know, and don't keep up on, you know, reading of that Excel developments might never be aware of that.
Um, and, you know, I remember even when Excel 2007 came out, um, which was, you know, the, the start of the larger grid, you know, we could go beyond column IV, you know, and beyond row 16, um, 65,000, um, you know, and
00:27:01.670 — 00:27:12.180 · Guest: Dan Mayoh
at the time I was working in this model auditing team. And so, you know, there's 20 of us and we were all Excel professionals, but it was still quite useful for, you know, 1 or 2 of us to
00:27:13.420 — 00:27:25.659 · Guest: Dan Mayoh
deep dive into it about everything. Knew that Excel 2007 could do. And then we ran a little, you know, training session, answering one day for the rest of the team so they would be aware, um, you know, and I guess
00:27:27.500 — 00:27:39.780 · Guest: Dan Mayoh
if even power users still needed that, um, you know, I get that. How. Yeah, a lot of casual users might be oblivious to the developments in the last ten years of Excel.
00:27:39.820 — 00:27:56.220 · Host: Paul Barnhurst
It's easy to do when you don't use it as as often as power users do. Great point there. So I want to talk a little bit. I think everybody is a little interested. I know you've done some mathematical modeling of games, so talk a little bit about that kind of what what you're doing.
Yeah. Look, I guess that just comes.
00:27:58.380 — 00:28:10.759 · Guest: Dan Mayoh
From, you know, having this consulting business and having an interest in, um, analyzing games and, you know, the actuarial skill set, um, and
00:28:12.560 — 00:29:02.199 · Guest: Dan Mayoh
Excel being my programming language of choice. Um, you know, I've, I've done quite a lot of, uh, yeah, building models of games that might have a random element or have a find the optimal strategic way of playing this game element to it sort of thing where, uh, you're kind of modeling out the game tree. Um, and I think some of the first examples I did this was when I was still working as a model audit of, um, and there was a time in 2008, I spent about three months living in, in Colombia again.
Um, I went back for three months and I was just doing my Sydney model auditing job remotely from Colombia for a few months. Um, but I
00:29:03.200 — 00:30:46.420 · Guest: Dan Mayoh
befriended a, uh, the owner of a small poker room slash casino in Bogota. I was playing a lot of poker there. Um, is there an American man who, you know, in this little casino? Um, and he was, you know, offering some sort of variations on blackjack rules or some side bets on these blackjack games, and, you know, kind of wanted to know a bit more about the mathematics of what he was offering.
And if they were exploitable to card counting and things like this. And, um, he had already banned me from playing like Jacky disestablishment at this point. Um, but I was friends with him, so I was happy to help him out. Um, and yeah, so build up some models to, to run some numbers in on these questions he was asking and, um, yeah, gave him his answers.
Um, and that's kind of where I started. And I guess I just realized I had a bit of a knack for it and quite enjoyed it. Um, and yeah, done a lot of it since then, you know, whether it be actual work for a client or something I'm just doing for myself because I'm interested in it, and it could vary from, um, yeah, you know, casino based examples and wanting to, you know, know what's the best way to play, you know, a certain casino game where you have decision points during the game.
Um, and what the edge is if you do that, um, you know, to things like hypothetical questions like, um, you know, if you had this extra a little bit of information which, you know, you're not meant to have, but like, if you could see that, you know, this dealer's card here was or I mean, if you knew it was a high card or a low card and, you know, if you had that information, how does that change the edge of the game?
Just just for fun things like that. Um,
00:30:47.540 — 00:30:51.900 · Guest: Dan Mayoh
or it could just be, you know, then other, um,
00:30:53.500 — 00:31:15.930 · Guest: Dan Mayoh
you know, non gambling related games. I remember when Wordle came out and, you know, it was all the craze for a while. Um, myself endearment early going back and forth with, um, you know, ideas and building some spreadsheets on kind of use, you know, building an Excel tool to help you solve Wordle, for lack of a better word.
You know, um.
00:31:16.010 — 00:31:18.850 · Host: Paul Barnhurst
Why am I not surprised you work with them on that? That.
Yeah.
I mean, Tim has a similar.
00:31:23.490 — 00:31:36.450 · Guest: Dan Mayoh
Mind to myself. Um, when I met them through model of, um, when he competed in model, uh, you know, before he became the, uh, superstar he is now. Um,
00:31:37.530 — 00:31:47.290 · Guest: Dan Mayoh
and, you know, Jim is a strong mathematician as well. Um, and so we we yeah, we had a lot of shared interests.
00:31:47.330 — 00:32:04.110 · Host: Paul Barnhurst
Yeah, I can definitely see where there's translation from the math, the math and the actuarial to the game side. I mean, right, there's a lot of you're trying to narrow options down a lot around uncertainty, reducing that uncertainty. So when you're playing the game is a lot of what you're modeling.
00:32:04.510 — 00:32:43.150 · Guest: Dan Mayoh
You got it can be that and it can just also be building simulation models, you know, running Monte Carlo simulations or, you know, if, depending on the problem at hand, building a deterministic solution that rather than just does simulations, actually looks at every possible. Yeah. Uh, way the the game can unfold with precise probabilities attached to each, you know, to give you exact answers on certain things.
Um, and those sorts of skills have been useful in, uh, you know, paid consulting work, which I think was in one of your questions as well around, um, you know, abatement modeling for,
00:32:44.350 — 00:34:00.730 · Guest: Dan Mayoh
you know, say, if I'm working or, you know, I've done a lot of work on infrastructure transactions and people bidding for things like, you know, the concession to run a public transport franchise, you know, to run a train network in a city or something like that. Um, and, you know, as part of that bid. Yeah.
Which is really this consortium I'm looking for. Uh, submitting a price that they want in order to run the network. You know, there'll be elements in the contract that say, well, if you don't meet certain performance metrics, you know, you have too many trains canceled or late arrivals or things like that.
You know, then you get these financial penalties. Um, and, you know, at the bid stage, the consortium needs to be able to budget an allowance for that or, you know, to quantify, you know, how much do we actually expect to to incur in these penalties or earn in bonuses or whatever it might be, the performance related.
Um, and they would have some data from their experience or any other networks, for example, around the frequency of of events like, you know, a light rail vehicle hitting a car or,
00:34:01.810 — 00:34:57.400 · Guest: Dan Mayoh
you know, a train. The line being shut down due to a power failure or whatever it might be. You know, they would have, you know, set some probability around the frequency of these events. And, you know, and I would turn that into, you know, dollars at the end of the day, you know, to to budget and allowance, along with a, um, not just an expected value but a, a probability distribution to, to sort of show at different confidence intervals, you know, um, how it might look and, you know, the way a lot of those abatement contracts work is you might budget, you know, over a 20 year contract.
Yeah. Let's say for argument's sake, it $10,000 a month plus. But it turns out that, you know, 95% of the time you actually lose zero, and the 5% of the time you lose massive amounts. You know?
00:34:57.440 — 00:34:58.760 · Host: Paul Barnhurst
Yeah. You lose $1 million.
00:34:58.800 — 00:35:11.880 · Guest: Dan Mayoh
Yeah. Yeah. You know, and and but but, you know, they want to understand that and, you know, and it's the same sort of skills, you know, that I talked about with the mathematical modeling that can, um, you know, that I can use to, to do that sort of modeling for them as well.
So I want to ask one more question here. Then we're going.
00:35:13.800 — 00:35:18.640 · Host: Paul Barnhurst
To kind of move on to rapid fire, in which I'll lay how the how that works. So you've.
Done obviously, a lot of math.
00:35:19.720 — 00:35:31.400 · Host: Paul Barnhurst
Modeling, game modeling. Any lessons you would give our audience of how it's helped with kind of decision-making and uncertainty? Because, right, there's a lot of uncertainty in any of that you're doing.
00:35:31.520 — 00:35:46.360 · Guest: Dan Mayoh
Yeah. There is. Um, and yeah, I saw this in your list of questions as well. And I think it was related to, you know, the, the poker background as well and how that helps with the, um, making decisions in uncertainty. And.
00:35:48.560 — 00:35:52.800 · Guest: Dan Mayoh
Yeah. I think actually like the way I like to answer this, you know, the,
00:35:54.110 — 00:36:04.830 · Guest: Dan Mayoh
The experience playing poker has probably helped even more. Than just the pure modeling of it. Although one reinforces the other. Which is to say that, um.
00:36:07.270 — 00:36:10.670 · Guest: Dan Mayoh
Yeah, I've learned, you know,
00:36:11.790 — 00:36:33.909 · Guest: Dan Mayoh
what uncertainty is and that you can't be outcome orientated. You know, all you can do is be confident you made the best decision with the information you had available at the time. Um, and then and when there's an uncertain element to it, well, you can't really judge yourself based on
00:36:35.270 — 00:36:42.430 · Guest: Dan Mayoh
the outcome that happened then. Um, you can only judge yourself based on, you know, did you make the right decision with the information that you had?
00:36:43.630 — 00:37:01.050 · Guest: Dan Mayoh
And sometimes you win. Sometimes you lose, um, even when you make the right decision. And that's fine, You know, and I think you with enough time playing poker. You learn to accept that quite easily and move on from that quite easily.
00:37:01.090 — 00:37:35.570 · Host: Paul Barnhurst
I think a lot of times people think, you know, I worked in PA and we always had to submit a budget with a number. And, you know, a lot of people would just do the number and it's like help people understand the risk around that because you're never going to hit that exact number, you know. How confident are you in it?
And so I think what you shared, there is a lot of what I had to learn in, you know, in a different way in my career is trying to help people understand, okay, well, this, this and this have to be true to hit that number. How likely are these to be true? We've never done one, we've never done two, and we've never done three.
So let's reassess that number. You know those type of things.
00:37:35.610 — 00:38:46.520 · Guest: Dan Mayoh
Yeah I think that's that's a different it's a slightly different thing like um covering up your downside and and looking at, you know, risks. Um, and yeah, this comes up in the infrastructure bidding for contracts as well. You identify all these risks and you might quantify them. You know, what's the chance of this risk happening?
And then what's the cost? If it does happen and, you know, you add all that up. Over 100 risks. You get a yeah, a risk register and a risk allowance that you put in. Um, as well as wanting to know, you know, what are the really bad ones that could actually lead you to default on the contract? Um, but I think that's a.
Yeah. And that that's a skill that modeling helps. Um, but it's a slightly different thing to just, um, making decisions with imperfect information and being able to, to do that. Like, you know, it can be as simple as, like, you know, is this a go or no go on some capital expenditure decision, you know, um, and or on a, on an M&A acquisition or something.
Um, and just, uh,
00:38:47.600 — 00:38:53.670 · Guest: Dan Mayoh
yeah, I guess being comfortable with uncertainty and probability, um, and,
00:38:55.070 — 00:39:09.310 · Guest: Dan Mayoh
you know, and experience in things like playing poker. Um, yeah. You become much more comfortable in just understanding that. Well, you'll never know everything. You'll never have perfect information.
00:39:09.310 — 00:39:59.980 · Host: Paul Barnhurst
That's a good example. And I think we could we could spend a whole episode on this, this whole thing talking about here. But, you know, I'll say two things that we'll move to rapid fire. I, I loved how you mentioned, you know, it helps you just be able to make decisions within perfect information, which is some everybody needs to be able to do.
It's a core skill. And then, you know, the whole idea of the randomness impacts the penalty. And there's a lot of situations. Drunk driving is a great example because there are some people that it's it feels like a slap on the wrist and there's others that it's much more serious because of the outcome. Even though they both, they both made the same stupid decision at the end of the day, but because of a random chance, one ended up in a lot worse of a situation.
And so yeah, there's a lot of examples like that, and it's an imperfect world. So you bring up some some good points.
00:40:00.020 — 00:40:53.320 · Guest: Dan Mayoh
Yeah, I mean, that can happen on the flip side with like, you know, executives being rewarded for our performance. And sometimes it's just random chance and not what they did well where they get it. And as a poker player and as someone you know, who you know, tries to get better as a poker player and look back at the decisions you made and to learn from them.
Um, we try to very much take an opposite view, you know, where we're not, you know, if you made a poor decision but then got lucky and won, you know. Well, you still made a poor decision and you should still learn from that, you know, even though you might have won the tournament, um, and vice versa. You might have made the right decision and got unlucky, you know, and lost.
Um, but when you look back and as self critiquing, you know, how you did, you say, well, I still did everything right and I made the right decision here, you know.
00:40:53.800 — 00:41:17.200 · Host: Paul Barnhurst
And so all right, so rapid fire on this one. Here's how it works. You have to pick a side. No it depends. No elaboration. Just kind of quick answers. And then at the end you can elaborate on the one that you feel like there's the most nuance because we know there's exceptions to everything. It's more just kind of fun.
If you had to pick a side the majority of the time, how would what would you recommend?
So the first one.
00:41:18.200 — 00:41:21.120 · Host: Paul Barnhurst
We'll start here: circular references and models. Yes or no.
00:41:21.160 — 00:41:21.800 · Guest: Dan Mayoh
No.
00:41:22.440 — 00:41:23.440 · Host: Paul Barnhurst
No VBA.
00:41:23.840 — 00:41:24.560 · Guest: Dan Mayoh
Yes.
00:41:25.760 — 00:41:27.840 · Host: Paul Barnhurst
Lambdas in financial models.
00:41:27.840 — 00:41:29.320 · Guest: Dan Mayoh
Yes they can be used.
00:41:29.720 — 00:41:31.920 · Host: Paul Barnhurst
Okay. External workbook link.
00:41:31.960 — 00:41:39.040 · Guest: Dan Mayoh
No. If possible and under very specific you know ways of using them if required. Yeah.
00:41:39.680 — 00:41:42.120 · Host: Paul Barnhurst
Merge cells. Are they ever acceptable.
00:41:42.160 — 00:41:44.590 · Guest: Dan Mayoh
The C circular References. No.
Do you think financial?
00:41:47.270 — 00:41:49.470 · Host: Paul Barnhurst
Should modelers learn Python in Excel?
00:41:49.870 — 00:41:51.830 · Guest: Dan Mayoh
I haven't needed to yet.
00:41:51.870 — 00:41:55.870 · Host: Paul Barnhurst
Okay, I'll take that as a no. What about power BI?
00:41:55.910 — 00:42:04.550 · Guest: Dan Mayoh
Again, I haven't needed to yet. It's not to say they shouldn't, but you can make a career in financial modeling without either of those two things.
00:42:04.590 — 00:42:06.070 · Host: Paul Barnhurst
What about Power Query?
00:42:06.950 — 00:42:14.310 · Guest: Dan Mayoh
Are you saying you don't need it? Okay. It's useful to have a big toolbox, but no, it's not needed.
00:42:14.550 — 00:42:21.670 · Host: Paul Barnhurst
I'm curious what you say on this one. Should every financial modeler be able to build a fully integrated three statement model?
00:42:22.230 — 00:42:22.950 · Guest: Dan Mayoh
Yes.
00:42:23.310 — 00:42:26.150 · Host: Paul Barnhurst
Okay. Will excel ever die?
00:42:26.230 — 00:42:32.270 · Guest: Dan Mayoh
The short answer? No. The literal answer. Well, yes. I mean, I'm not going to be using anything.
00:42:32.390 — 00:42:33.790 · Host: Paul Barnhurst
Everything dies in the long run.
00:42:33.990 — 00:42:34.470 · Guest: Dan Mayoh
Yeah.
00:42:34.830 — 00:42:39.590 · Host: Paul Barnhurst
What financial statement do you think is most important for modelers? Income statement, balance sheet or cash.
00:42:39.590 — 00:42:41.030 · Guest: Dan Mayoh
Flow income statement.
00:42:41.220 — 00:42:46.580 · Host: Paul Barnhurst
Okay. What's your favorite? LM do you like Claude? Copilot ChatGPT or something else?
00:42:46.700 — 00:42:54.700 · Guest: Dan Mayoh
I'll defer to my wife. She likes Claude. I haven't used them enough to kind of know, but my wife uses them a lot. She says, quote.
00:42:54.740 — 00:43:02.860 · Host: Paul Barnhurst
I love it. If you could pick only one for all your models, you could only do one. Would it be sensitivity or scenario analysis?
00:43:02.940 — 00:43:04.300 · Guest: Dan Mayoh
Can you elaborate?
00:43:04.340 — 00:43:17.900 · Host: Paul Barnhurst
So sensitivity in the sense of you know, you have this output if you change it, here's what happens. So you're running sensitivity tables scenarios is you're creating different scenarios I got my best case my worst case or off the model.
00:43:17.900 — 00:43:22.940 · Guest: Dan Mayoh
I would say it's the same thing. The scenario is just letting you change ten sensitivity as a once guess.
00:43:22.940 — 00:43:24.940 · Host: Paul Barnhurst
You could argue that I get what you're saying.
00:43:25.140 — 00:43:27.620 · Guest: Dan Mayoh
And that is how my mind thinks about it. You know.
You're the first one that's.
00:43:28.700 — 00:43:39.420 · Host: Paul Barnhurst
Asked me that way, so I like it. All right. So we'll give you that. So you can do your scenario and make your sensitivities from there. All right. Do you believe financial models are the number one corporate decision making tool?
00:43:39.690 — 00:43:41.210 · Guest: Dan Mayoh
No, but they probably should be.
00:43:41.290 — 00:43:45.010 · Host: Paul Barnhurst
That's not an uncommon answer. What's your lookup function of choice? Which one do you like?
00:43:45.050 — 00:43:45.810 · Guest: Dan Mayoh
Index.
00:43:45.850 — 00:43:50.650 · Host: Paul Barnhurst
All right, you're an index guy I like it. And then last question. Favorite Excel shortcut.
00:43:50.770 — 00:44:01.250 · Guest: Dan Mayoh
I love putting things in the quick Access toolbar. And so I can just, you know, a shortcut for me will be like alt six. But that's going to be different for someone else.
00:44:01.330 — 00:44:05.650 · Host: Paul Barnhurst
Correct? Your favorite are the ones you create yourself. Yeah, yeah. From me. But from to.
00:44:05.650 — 00:44:12.250 · Guest: Dan Mayoh
Give you a better answer, the one that I use really quite a lot is just inserting rows, which I r works.
00:44:12.290 — 00:44:16.690 · Host: Paul Barnhurst
Yeah. I was just going to say oh legacy. Oh I see alt ir. Yeah yeah.
00:44:16.730 — 00:44:22.330 · Guest: Dan Mayoh
Yeah. But it is also just alt four for me and my quick access toolbar inserting rows I use a lot.
00:44:22.370 — 00:44:32.090 · Host: Paul Barnhurst
Okay. All right. Thank you for joining me I've enjoyed the conversation. If you want to share anything about your business or any last stops before we wrap up, anything you want to share before we go?
00:44:32.210 — 00:44:36.370 · Guest: Dan Mayoh
Nothing comes to mind. You'd have to put me a little bit with a question or something.
00:44:36.410 — 00:44:42.750 · Host: Paul Barnhurst
Well, I'll give you a final question. All right. So people want to learn more about you, Dan, about your business. What's the best way for them to do that?
00:44:42.790 — 00:44:44.830 · Guest: Dan Mayoh
Okay, so my business is fintech.
00:44:45.990 — 00:45:18.510 · Guest: Dan Mayoh
The website needs an overhaul. It kind of got corrupted at one point. And so it still exists. But it's a lot of like float ipsum type but text on that. By the time this airs, perhaps I would have fixed it. But that's where you can reach me if you want any consulting work done. Otherwise, learn more about me. I've taken a backseat in the last few years of being an active member of the global modeling community, compared to sort of what I was five years ago, and so have less time these days with my family.
00:45:18.590 — 00:45:20.070 · Host: Paul Barnhurst
What a treat for that one.
00:45:20.110 — 00:45:49.100 · Guest: Dan Mayoh
Yeah, or I've just decided I'm too old to be a regular participant in industry debates and things like that. So I don't know. I guess I've chosen to be on this podcast on I'm on the, you know, the FMI Global Leaders Council. So there's certainly still a part of me wanting to remain an active member of the global community in financial modeling.
That's it. Otherwise, just. You can send me an email. Dan. Com or find me on LinkedIn and reach out. If anyone wants to follow up with anything, I respond.
00:45:49.140 — 00:45:55.380 · Host: Paul Barnhurst
Thank you for joining me, Dan, I appreciate it. Great chatting with you. I'll go so you can enjoy the rest of the evening. But thanks, Dan.
00:45:55.420 — 00:45:57.380 · Guest: Dan Mayoh
Thank you Paul. Enjoy your day.
00:45:49.140 — 00:45:55.380 · Host: Paul Barnhurst
Financial Modeler's Corner was brought to you by the Financial Modeling Institute. This year I completed the Advanced Financial Modeler Certification and it made me a better financial modeler. What are you waiting for? Visit FMI at www.fminstitute.com/podcast and use code podcast to save 15% when you enrol in one of the accreditations today.