Discover How Financial Modelers Are Using Copilot & ChatGPT with Global Expert Kenny Whitelaw-Jones

The start of my career, I was with one of the big four, I won't say which one, 24 hours a day, relentless, high pressure restructuring of this large company. And this model in the middle of it just kind of disappeared, went off, vanished, that nobody really understood and everybody was trying to hack stuff into. And I was kind of implicated in that madness. Most modeling, I think it's around 75% expect that AI is going to have a very significant effect on modeling, but a very small number, say 10%, are actually using AI in a very systematic way or using AI for tasks that are related to modeling.

Doesn't mean you shouldn't be using it, but I think most of us feel like it's still coming.

You know, to be a really good modeler, you need to be good at interpreting data, analyzing data, at presenting data. I mean, that's one of the key things, right?

75% of modelers said they do see AI having a significant or revolutionary impact on modeling. So where do you think that impact will be?

I think that's to some degree already changed. You know, I think Financial modelers, I hear this foreign.

Welcome to Financial Modelers Corner where we discuss the art and science of financial modeling with your host, Paul Barnhurst. Financial Modelers Corner is sponsored by Financial Modeling Institute. Welcome to Financial Modeler's Corner. I am your host, Paul Barnhurst, AKA the FP and a guy. This is a podcast where we talk all about the art and science of financial modeling with distinguished financial modelers 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 this week. I'm thrilled to welcome our guest onto the show, Kenny Whitelaw Jones. Kenny, welcome to the show.

Thanks so much, Paul. I've been following the podcast for a long time, so it's good to be here.

Yeah, excited we were able to make our schedules work and have you on the show. I'm excited for our topic here about AI that we'll jump into in a moment, but just to give our audience a little bit of background on Kenny. Kenny is one of the founding partners at Gridlines. He is a leading financial modeling expert in the project Finance market globally and over the past 10 years, he's played a significant role in the development of financial modeling standards and has trained Project Finance modeling to blue chip clients throughout the world. Exciting. Project Finance, that's an area I haven't done much of, so I'm excited to dig into that a little bit, but as we always do, tell me that horror story. Worst financial model you dealt with.

I've seen some absolute basket case financial models. I think the worst financial model I dealt with was maybe when I was implicated and it was right at the start of my career when I was with one of the big four, and I won't say which one, but I was first in financial modeling and the corporate finance team was involved in this restructuring and the modeler had just, I think just under pressure of this 24 hours a day, relentless, high pressure restructuring of this large company, lots of people involved from the firm and this model in the middle of it. And the financial modeler just kind of disappeared, went off, vanished. And so it was kind of left with other people in the middle of this high stake situation to pick up this model. And it was a basket case. It was kind of a template model that was actually never built for that kind of business that nobody really understood and everybody was trying to hack stuff into. And I was kind of implicated in that madness. And it was just, it was that thing of, you know, horribly complex models being misused for the wrong situation. And then the person who really understood the model has gone and you're just left picking up this horror show. It was really embarrassing and career limiting for quite a few of us.

That sounds like an awful model. What was your key takeaway? What was the learning experience from it?

I think I didn't know it at the time, but as my career progressed and I saw, because I was right at the start of my career and I didn't know there was better ways to build models than that. And I think that's really classic. You kind of land as an analyst in one of these firms, kind of look around and you're kind of seeing what's being done and you start doing that because you think it's right or good. And then over time I started to see there's actually really much better ways to build models where it doesn't matter if the original model vanishes because everybody else understands the model, because you're following some kind of a standard. It was just a thing that's been reiterated to me time and time and time again about consistency and standards and modeling and what a lifesaver that is. And I think that just informed, I think a lot of the work that I've done over my, over my career.

And so I'm curious, did you guys end up rebuilding that model or did you continue hacking together?

There wasn't time because the pressure was on. I went into a meeting with the CFO of this company and the partner who was in charge of the assignment, and they were looking for answers from this model and I'd never felt so exposed. They were like, you know, what's the maximum working capital exposure? I was like, trying to, like, find it in the model. It was horrifying. So, no, we didn't rebuild it. We didn't cover ourselves in glory. Nobody walked away with that with any awards. It was a bad scene all around.

Yeah, that's definitely one you learn from. And not exactly the way you want to get parachuted into a new job, but definitely something you'll never forget.

That's right, that's right. Very, very formative, shall we say, as an experience.

Yeah. I could only imagine. Yeah, yeah. I have no idea what the word cap. Let me see. It's 3640. I don't know. Make up a number.

Yeah, yeah, yeah, yeah, yeah. What do you want me to say? I don't know. I don't know where to find it in the model. It was just. It was awful.

What do you want the number to be? Right. That's when you know you're in trouble. When that's the response.

Exactly right.

You know, I know you started with one of the big four, but a lot of your experience seems like most of your career has been around project finance, renewable energy. What's attracted you to those areas? What. Why those industries?

In a way, I kind of fell into it, but I joined the firm I trained with. It was early 2000s. There was, you know, I thought I was going into an M and a kind of corporate finance role. I thought I was going to be a big sexy M and A guy. And, and. And that happened at the same time as there was kind of a dot com crash and the M and A teams were shrinking. But there was this thing in the UK called pfi, which was using project finance structures to finance social infra structure, like schools and hospitals and things. And there was a huge wave of projects in the UK that were project finance based as a structure, but being used to rebuild schools and hospitals. That eventually fell out of favour in the uk, got quite bad press and was abandoned as a funding mechanism for social infrastructure. It's still used many, many places around the world. I cited the uk, but it just meant there was a lot of projects then and they were really modeling intensive and I like modeling and I just kind of fell into that area. And that was really before the renewables explosion. And what I could see was as I kind of then started to learn more about infrastructure and energy, I was like, okay, so this stuff's not going to go boom and bust the way that the corporate finance world does. In fact, if anything, it's kind of anti cyclical. Governments tend to spend more on infrastructure during down times. And so I thought this is probably a good place to be. And then I also like the modeling challenge of it. I like the complexity of it. Those models are pretty, pretty complex and even more, way more complex now than we even were mighty, especially around renewables or not mighty. Jesus, I've been 90, but back in starting my career.

How old are you, Kenny?

Back in the day, back in the day when I was building models. I like the tangibility of it. I like that at the end we tend to, we'll see a project through its development and its stage until it gets to financial close, at which point the construction of that thing starts, right, that wind farm or that wastewater treatment project or that hospital, and we tend to kind of lose touch with it. But then what I really like is when I see later, oh, there's a real thing here making a difference in people's lives. There's a real big huge wind farm in that desert or there's, you know, there's a school you can point at stuff that has made the world a bit better. And I think that's especially true of energy transition just now. You know, the explosion in renewables in the past few years has been a great thing to be part of, you know, because we have a good offering in that area. But it's also, it's good to be able to point at being involved in projects which are making a difference in the world, that are making lives better, that are, that are part of our development, I guess, as a species. Right, that's kind of maybe a bit big. But I really like the tangibility. I really felt that we're contributing in our way. Although obviously there's lots of participants in these projects, but we're contributing in the way that we can and the way that we do to creating some lasting and useful change for the planet. And I find that really interesting.

Yeah, I imagine it's fascinating when you actually see something that you worked on and go, oh yeah, I can see that and I can see what it's doing. Do you have maybe a favorite one where you've later on been able to see it and you're just like, wow, I worked on that like a favorite project.

There's lots, I mean There's. There's a couple of hospitals that I, you know, drive by relatively regularly that weren't there before. Like, there's a hospital, you know, I worked on that project. I go. One of my favorite cities in the world is Edinburgh, where I'm, Where I'm from, and I go there, and now there's trams running around the streets of Edinburgh, you know, and, you know, I was involved in, indirectly in that project through supporting some of the people who were. I wasn't building the model, but I was supporting some of the people who were building the model with training and, and consultancy and whatnot. And that was just brilliant. I step on a tram and it's like, you know, and that's making the transport system in Edinburgh more green, more efficient, less, Less polluting, less based on cars making the city center a nicer place because there's less traffic. Like, that's a great thing. It's a great thing to be part of.

Love it. That's a great example. That's cool that it's, you know, somewhere that's home for you.

Yeah, exactly. Yeah.

All right, so you recently did a survey. There are a few hundred finance people around, AI and financial modeling. So tell me, how did the survey come about? What prompted you to do that?

It's purely personal interest. It's just like, I'm just fascinated by. I've always been interested about how is financial modeling going to. To change? How has it changed? How is it changing? How are the projects changing? And obviously AI is just turning stuff on its head, and I think it's massively exciting. And of course, we can all get lost in our own fear stories about what AI is going to mean for us as a species. But I think it's really exciting and I'm just curious to see how this is going to happen to financial modeling. My hypothesis is it's going to create a lot of change in what we do. And it's trying to look at. Well, it was just really asking the question to other modelers, well, what do you think is going to happen? And just because it's purely interesting and because I enjoy doing stuff like that, I enjoy a bit of research, produce a little report, put it out, just stimulate conversation. And that's been. Doing these kind of things is great. You always make new connections. Somebody turns up and says, I read your report. That was really interesting, and strikes up a new conversation. Good for expanding our network and so on. But it really starts out of personal interest and wondering also, what's that going to mean? For grid lines for my business. We're a sevenly strong team of financial modelers. We'll be 100 by the end of the year. As far as I know, we're the biggest dedicated financial modeling company in the world. Lots of the big firms have more likely bigger modeling teams. I'm not saying we're the biggest modeling team in the world, but as far as I know, we're the biggest dedicated modeling firms. But modeling is what we do. And that's, you know, and so it's also a little bit like, well, how's that going to affect this business? You know, if we are purely focused on financial modeling? And we do, you know, we support infrastructure and renewables transactions, we do model audits, we build models for all sorts of sectors. I can see that AI is going to have an impact on all of that. And it's a little bit of me just trying to get myself ahead of the curve of what, what can we expect to be coming down the track here at us and how can we position ourselves to take advantage of it, not to be running scared, not to be burying our heads in the sand and thinking, well, financial modeling is never going to. That's a unique thing. It's not going to be affected by that. I think that would be a terrible mistake to assume that. And so even though we're not really seeing big changes right now in financial modeling due to AI, I just have no doubt that it's coming. Yeah, so it's just like under. Trying to, you know, just explore the topic for myself and for us as a business and then like, why not share it? Right? We're all going to be affected by these things. We're all going to have to change what we do. And so why not share it now?

So have you released the report? Is it available?

Yeah, we have, yeah, it's available to download. Yeah. Yeah.

Great. So make, make sure you give that to us. We'll put it in the show notes.

We'll give you that link to download it.

Let's start, let's start with obviously you mentioned, you know, kind of did for personal reasons, business reasons. Right. There are a few different things. Want to see what others. So can you tell our audience what were some of your key takeaways from the survey? I mean, what's the key thing you took away from it?

I think it kind of confirmed what I expected to see, which was that I think the biggest thing, most modelers, I think I forget the numbers off the top of my head. Most modelers say I think it's around 75% expect that AI is going to have a very significant effect on modeling, but a very small number, again the numbers in the report, but let's say 10% are actually using AI in a very systematic way or using AI for tasks that are related to modeling. So it's kind of confirmed where I think we're at. This big thing is coming. It hasn't really arrived yet, but we think it's coming. So what's it going to look like? So in a way kind of confirmed what I thought we would see there. But that's also a useful thing to have confirmed like, because I would be a bit surprised if there was like, you know, 80% of models as well. You would use AI to build all our models. I'd be like, oh crap, what have I missed? You know?

Yeah, where have I been?

Where have I been for the last two years? You know, so it was, it was kind of useful from that perspective.

No, makes a lot of sense and that's kind of what I'm seeing. And I think finance in general, you know, modeling, deep analytics, there's areas that can be helpful, but it's not really at the point where it's going to do majority of projects for us. Doesn't mean you shouldn't be using it, doesn't mean it's not incredibly beneficial. But I think most of us feel like, if you want to call it revolutionary, those significant things I think in the finance, financial modeling space is still coming. We're still figuring it all out. And so, you know, one thing I found really interesting, I'm gonna go through a couple things in the report, just love to discuss them as I look through it is one I found is most people who are using co pilot versus Chat GPT in your report were much more likely to use Copilot daily than if they were using Chat GPT on a daily basis. What's your thoughts? Why do you think that was the case? Any thoughts?

I think it's just, it's ease and proximity. You know, if you're, if you're a person who's working in Excel a lot, then you, you mean you're going to use Copilot, you're going to be checking out, you're going to be testing out and see what's there rather than switching over to ChatGPT to do stuff. And I just also think ChatGPT doesn't do very much yet that's actually very useful for financial modeling. It can write vba, it can recommend formulas, but I honestly Feel like if you're a financial modeler who's needing to go to ChatGPT to know what formula to use, you've got some work to do, right? And it's great to discover new stuff. Don't get me wrong, whenever I'm teaching a course, which I don't do as often as I used to, but whenever I'm teaching a course, I always learn something, right? Somebody that's got some clever way of doing something, I'm like, oh, wow, I never would have thought of doing it like that. That's really clever. And then what I do is I take that and I teach it on the next course and pretend it was my own, right? And so always learning something. And I guess chatgpt, these things can be useful from that perspective, but I just don't think it does very much that's actually very useful financial modelers yet I see some interesting. I mean, for example, I try. I took the CSV file of the survey results and I uploaded it to ChatGPT and asked it to do some analysis on it. Some very basic analysis. Just did a really bad job. It gave me inconsistent results. I would ask the same question twice. It would give me two different results based on the same data. I was like, this is, this is some, this is ropey, you know. But I see some interesting things happening. So there's a. There's a company called Grid based out of Iceland. Helmar is the CEO and they built this replica spreadsheet engine on the cloud. It does everything that Excel does, it does everything that Google Sheets does, and they've built this and now they're working on ways to connect that to ChatGPT. In fact, they've figured out how to connect their dedicated, which they can control, spreadsheet engine to ChatGPT. So the idea is both things kind of doing their job well. The chatbot doing the natural language processing, the interpretation of. Of language and instructions, but passing that to the spreadsheet to do the actual calculations. That's interesting, right? So these kind of things are going to start to happen through different technologies merging and being assembled in different interesting ways. So I really think it's because I don't think you can get it to do VBA, but otherwise I don't think ChatGPT's got much to offer financial modelers, to be honest.

Interesting. I appreciate the answer. I've heard of Grid before and Now I use ChatGPT a little bit modeling and there's areas I found it's good. There's areas of Struggles. I, I think there's definitely some truth. It's not totally there yet. And Copilot is built in to your applications. It gets back to one of the biggest things that we're trying to figure out is building the agents and building it into workflows. And if it's in all my tools, it's much closer to being in my workflows than having to open a browser and go find the application.

Which gives Microsoft an advantage, right? Maybe it says there's a disincentive to build new tools in this area because it's going to be very easy for Microsoft just to build it right into Excel and then you're done. Right? So it's like, you know, the installed base, the network effect. And I think they are being really innovative and they're upping the pace on how they're developing Excel, which is exciting to see. But I think that might mean that there's, it could end up, there's less innovation rather than more. Who knows, right? But it's just interesting to observe how that plays out.

No. And Microsoft's a huge player in all this and they have a lot of built in advantages. But as you mentioned, Excel. I'm just going to deviate a little bit here for a minute. You talk about how Excel's done a ton of innovation over the last few years. Is there a favorite innovation of yours that you've seen over the last few years? Something that has you really excited, right? It feels like every month they're coming out with something new. So what's one thing that you're most excited about?

I mean, dynamic ranges have been great, right? And really interesting. It's interesting for us because most of our models are a very specific kind of model that's probably quite different than a lot of other use cases for Excel. The way that we build these 25, 30 year project finance forecasting models, it's interesting. Quite a lot of the innovations so far haven't really, really change the lot that we do. They have the potential to. So I see, for example, people building models with dynamic timelines, right. That using dynamic and okay, great use case for dynamic arrays. But I think where we are right now is the overhead that that adds to a model just isn't worth it because we just don't change timelines that often. It's not like we know when we're starting a project that there's a power purchase agreement that's 20 years long. We know that we need to build in flexibility for another, say two to five years. Of extension, we know that and that isn't going to change. So adding all this kind of engineering overhead to the model so that you can in a flash change it and all the timelines are going to be changed. And that's a great thing to be able to do, because when we change the timeline of the model, it's a pain in the ass. But we don't have to do it that very often. So now we're kind of balancing. Do we put all that engineering overhead into this thing to make it super flexible? When it's just not a problem, we really have to solve that very often. When we do have to solve it, it can be painful, but it's like a few hours of work and it's done. So it's just that it's balancing those kinds of things, but we stay on top of it. And I really enjoy seeing the people who are experimenting with that. I'm like, yeah, you do the experimentation, you come back and tell me you got it working and then we'll take a look at it. But right now we're not going to spend a lot of time on it. But lots of interesting things, you know, lambdas, interesting new functions, you know, great. You know, Python in Excel, I can see all the applications just in our area right now. It hasn't quite landed on anything that really makes a material difference for us. You know, the biggest thing for us is frankly, calculation speed. If you could just take the calculation speed of Excel and multiply it by 10, 20, 50, 100, that would make a big difference to us, you know, but like, because we've got these models that optimize and they need lots of rotations and lots of iterations, so to kind of land on this optimal tariff that meets a particular return target with a particular debt sizing with these constraints and these constraints, and there's a lot of iterations to land on that converged solution. So just speeding that up would be super helpful. But none of the other stuff has really made a huge difference to us yet. But we're paying attention.

There's a lot of sexy stuff out there, but is it stuff you need yet? And yeah, it depends on what you're doing for sure. I think, you know, most modelers, and I'm in this camp, have said, look, dynamic arrays, great fun. Lots of use cases in Excel, fully dynamic models, not really there yet for the average user. I mean, can you do it? Sure.

It's a fun thing to challenge the fun. Okay, can I build this model like this? If you like to kind of sit for a few hours and geek out about it. Which, you know, sometimes we like to do that. It's good. But you know, as you say, not really there yet for us.

Yeah. So it'll be interesting. Watch. I mean there's definitely some that are pushing it and I'm excited to see the development. So I'm like you watching it closely and excited to see how it all plays out. So you had hinted at this number earlier where, you know, 75% of modelers said they do see AI having a significant or revolutionary impact on modeling. So where do you think that impact will be like you personally in the next couple years? Where's the biggest area they're really going to change? Modeling FP and a guy here and.

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Well, what would it need to do for me to be excited? I guess is maybe I'd come at this question right is like what are our pain points that I could foresee AI having an impact and if I look at our typical project that we do, I'm going to split between our model build team and our model audit team. So for building model, typically we are building a model as part of a bigger mandate that we're doing which is supporting a project through to financial close and developing this project. And if you look at the split on time, probably 10% of total project input is on building the model and 90% is using the model to support the commercial negotiations that are going on around the project. And therefore we're spending a lot of time running sensitivities and scenarios and producing recommendations and testing out different debt structures to see what's the most competitive. And so yes, making the model build process faster would be really, really useful. And I think that's absolutely going to happen. We, and I know that because we're already working on technology to do that. So, you know, speeding up that process will be super useful because a lot of modelers or models are very similar. You know, say some of the models we build, It'd be like 70% the same as another model, but that 30% is really different. So, you know, it's getting, it's getting more efficient at building models. Having the ability to run hundreds of diff. Asking questions, ask questions in natural language about assumptions in the model and have the model run 200 times and give me a tabulated set of results that let me go, okay, there's the optimum there really easily. That would make a big difference to me. And then on the model audit side, model audit is made up of two kinds of processes. One is kind of software checks that are happening already. We have software for checking basic integrity stuff in a model. And then there's the more commercial checks. And for that we're kind of currently using, we'd be having somebody read the project contracts and then check does the modeling of that payment mechanism or that debt structure, does it match the contract? And so far that's being human, but I can see all of that being used. There's lawyers already using LLMs, chat, chatGPT type structures to work with contracts. And we've been playing with that of having a chatbot read a contract and then recommend the way that that should be modeled and then seeing can we pass that straight to our model build software and have that all work and there's no reason that can't be done for audit as well. So I just think a lot of routine things, but a lot of things where there's interpretation required will be able to be supported by AI in the future. I think that's just a question of time.

Yeah, makes sense. I appreciate sharing that. So with all these changes coming and they're coming right, as you said, we none of us want to stick our head in the sand and think, oh, it won't impact me, it's too unique. What I do think that. At your own risk, right. So what do you think will be the changes in skill set that will be needed as we adjust to this AI world? Is it going to change what a financial modeler needs to be successful?

I think that's to some degree already changed. I think financial modelers, I hear this in the market, I think there's maybe a perception of financial models, oh, they're just the number crunchers, there's just the formula writers. And I don't actually see that to be true. I see that modelers already, to be a really good modeler, you need to be good at interpreting data, at analyzing data, at presenting data. I mean, that's one of the key things. You can model stuff all day long, but if you can't communicate the results of what you're doing in a way that's really effective, you may as well not have done it. It's about being able to interpret separate business logic about ask good questions. I think there's already a broader skill set there and a really good financial modeler that I don't think a lot of people maybe recognize is there. And when they just see modelers as kind of the number crunchers, as the spreadsheet guys. But I think as the routine tasks are going to become more automated, I think we are going to have to be much more in those added value areas. Strategic interpreters of business logic, interpreters of model results into recommendations and actionable decisions in a way that's clearly communicated. Thinking of what will the objections be? What does this data mean? And being able to speak human around the data, I think is going to be really important like that.

Being able to speak human. Yeah. So it feels like. Yeah. Which I've heard from a lot of people. Definitely more on the soft skills which we've seen change. There's this view that we're just number jockeys and we all we can do is work in a spreadsheet. And there's so much more to modeling than that. I mean, the reality, if you're a good modeler, you're not spending the most of majority of your time in Excel or at least you shouldn't be on the, on the average project, there's exceptions, but on average, I would say. Any other final observations or kind of key takeaways that you want to share from the survey that we haven't talked about? About.

Thanks. Thanks. Thanks, Paul. I think one of the things that struck me, we asked one question which was about what would you like AI to be able to do? And we asked that as a free text response, which is never a good idea in a survey because you can't actually analyze the data. You got to actually go through it manually. And so that's time consuming. But it was interesting because the answers were all over the place, all over the map, you know, whatever you could imagine. It was like hundreds, 200 different answers. There were, there were themes and patterns in it, which we pulled out for the report. But I thought that was really interesting because I thought wow. We are, as a group of modelers, we are imagining a world where this will be done by AI, which means, for me, it kind of means what's going to happen, because we can imagine it happening. And so that's where all innovation starts, is somebody thinking, I think we could do it like this. I could see this happening. And so, as it becomes possible for all of us to develop tools and agents using AI and deploy that in different ways, these tools, even if they're really little micro tools that somebody develops for themselves, they will get developed. This change is going to happen, and it's going to happen in really interesting ways in lots of different ways. Because I realized that in project finance, we are a very narrow niche area of financial modeling. I mean, the super narrow. And I don't necessarily have the perceptual apparatus to know what everybody's doing in models everywhere. Right. But what it showed me was, wow, there's so many ways this is going to change what we do. And I thought that was really interesting.

That is fascinating. And I agree with you. Right. There's so many different types and ways to model and things people consider models. Right. Even just how you define a model asked by people get six answers. It's kind of like if you ask economists, you get multiple answers.

Exactly.

So I agree with you. It'll be fun to watch. And it does start with imagining what it can do, and somebody figures out how to make it do that, and you're like, oh, wow, I would have never thought it could do that.

And that's exciting, right?

It is. It's really exciting. All right, so I'm going to move on to a little bit more of, kind of some of the standard questions we ask our guests. First one is favorite Excel shortcut, F11.

Quick chart every time.

All right, thanks. I like that. What's the number one lesson you've learned over your career that's helped you the most?

Don't be a dick.

Just.

Just. Just treat people nicely and fairly and be reasonable and just try not to be an asshole whatever possible. I haven't always succeeded. I mean, I really haven't always succeeded in that front, but I'm trying, you.

Know, the life lesson is treat people like they want to be treated and be nice.

Yeah, yeah, exactly.

The things we learn in kindergarten.

Exactly. Our Sunday school teachers are onto something.

Yeah. It's funny how often that's true. The things that were, like, you look at it and go, hey, what's really important? Oh, those things they taught me way back when. All right, so what's the most unique or funnest, kind of funniest thing you've created in your personal life? Using Excel?

Using Excel.

It could be Google Sheets if you want.

Okay, no, I'll go with Excel, because I generally can't use Google Sheets. I keep trying. I'm like, where's my shortcut keys? Nothing works. I'm not sure call it a model, but there's broad definitions of model. I made a great spreadsheet for Christmas Day once, which was like. Because I had different people coming for dinner with different dietary requirements and different allergies. So I wanted to get the timings for everything I was cooking down and the quantities. I had this great spreadsheet for all of that. It was really a thing of beauty. And Christmas dinner was fabulous.

I'm going to have to start asking guests to send me these models, and I'm going to have to put them on the guest I had last week. Last Monday, he built one for his upcoming marriage to help them know how they were doing and had a dashboard and asking each other questions. And I'm like, and how did your wife take that? Our future wife? She didn't quite appreciate it as much as I did.

He didn't. She didn't appreciate the work that got into that.

Yeah, it was. It was pretty funny. So we had Christmas dinner. I think my favorite was the guy who built one to track how long, how often people were going to the bathroom or something.

I mean, that sounds a little bit creepy, if I'm honest. Never mind.

Yeah, I did think it was a little creepy. I can't really. Let's not name names.

Let's not name names on that one.

Oh, I'm not. You can find the episode. He had talked about it.

You can track him down.

He's in the uk. I'll leave it at.

You know that.

All right, so now we're gonna move on to Rapid Fire. I know you've heard the show, so you know basically how this works.

I know the format.

No, it depends. So you gotta. Come on.

You're killing me.

Sorry. And then at the end, you can elaborate on a couple. That's the fun. If I give you it depends, you're going to be a consultant. Say that exactly.

Everything's an. It depends. Right. For a consultant, yeah.

All right. Circular references, yes or no?

No.

Vba?

Yes.

Do you prefer a horizontal. So lots of sheets, or a vertical model, kind of stacking all your schedules in one sheet?

Horizontal.

All right. Using. Not fully dynamic, but using dynamic arrays and models. Yes or no?

Yes.

Okay. External workbook links. Yes or no?

Never.

I get that one from time to time. What was that again? Was that never named ranges? Yes or no?

Yes. If I'm allowed to elaborate later.

And yeah, you could elaborate on that. I already know your answer. On fully dynamic models. Not there yet. Do you follow a formal standards like one of these boards like Smart or fast or when you're building models?

We follow fast, fall fast.

All right, perfect. Do you believe financial modelers should learn Python in Excel?

Yes.

How about Power Query?

Yes.

Power Bi?

Yes.

All right, so we got three yeses. Let's see if we can get a fourth. I'm going to guess we don't. Will Excel ever die?

Well, at some point the sun's going to blow up and we're all going to die, so to that extent, yes. But before then probably not, because I think Microsoft are going to keep innovating it and the thing that Excel does, the problem that it solves, is not a problem that's going to go away. So I think not in our lifetimes is my answer.

Yeah, you're not the only one who said that. I had a few others who said, I hope it's not in my lifetime because then I got to relearn a.

Lot of stuff I'm going to buy to school.

Do you think AI will build the models for us in the future?

Yes. Or at least it will instruct software that builds the models. Yeah, they'll play some kind of intermediary interpretation and instruction role or maybe just build the whole thing. I don't know.

All right. She sell protection, yes or no?

No.

All right. Do you believe financial models are the number one corporate decision making tool?

No. What is intuition?

Yeah, that's usually the answer we get. My favorite answer I've had on the.

Show is politics, but that's also that. Yeah, but it's my intuitive answer about what the politically right answer is. Decision is.

Yeah, political way of saying politics. So for a financial modeler, what financial statement is most important for them to understand? P L? Balance sheet or cash flow?

I have to choose. I have to choose one.

Yep, you got to pick one. You can elaborate at the end on that.

Cash flow then.

All right, and then what's your lookup function of choice? Are you Vlookup xlookup Index Math xlookup.

Every time these days.

I like it. I'm a big X lookup. All right, I know you wanted to elaborate on a couple. I think the first one was named Ranges. So go for It.

Well, the name range and the VBA kind of go together, like so. I would want to use VBA sparingly in a model. I never want to see the logical flow of a model being kind of determined by vba. I want it to do things that are little tasks that speed up our lives and make our lives easier. And for that you need name ranges. Right? To make the AVBA work. Other than that, I simply load models that are built completely with named ranges. It makes me want to smash myself in the face. I can't stand it. And so VBA and named ranges, both sparingly, I'd say.

How was that? Was that smash yourself in the face?

Just punch myself right in the face. It drives me crazy.

I'm going to send you a model that's nothing but named ranges.

I've seen them. I don't need that in my life, Paul. I've seen that. I'm trying to stay away from it, you know, I'm older now. I'm trying to live a calm life.

You know, I really think I should get every guest to send some kind of model and start putting them up on the site. Could be kind of fun.

Yeah, yeah. Or send somebody else's model that we seem. That they really hated and take apart.

Yeah. All right. I think there was one other you wanted to elaborate on in there.

Which one was that? I think it was the financial statement one, I think. I think all three are essential. I mean, they're just essential just to get it. If you're only building a cash flow and that can be good for a quick and dirty analysis, that can be good. But if you're doing something serious, you need all three. And all three tell you something different. All three tell you something different. I do think, though, that one of the benefits of spending some time as a modeler, even if you go on to other things in your career, which lots of people do, they kind of start out in modeling and then progress onto other things. Spending that time in modeling, I think it really gives you a good intuitive understanding of how numbers move together on the financial statements. Being able to have a strong expectation of, well, if this changes the income statement, that's going to change in the balance sheet, that's going to change in the cash flow, and having that intuitively available to you, because I think you then can smell out numbers that don't make sense a lot easier. And I think that's a useful skill set.

I completely agree. Understanding the flow between the models and being able to relate that back to business Business like, oh, we extended our credit terms. What does that mean? Okay, well, cells may go up, but your cash is going to be delayed. Well, what impact does that have on everything else? And do I have to borrow more? And what's the rate? You start running it all through and you're like, maybe that's not a bad idea, or maybe we should do that. Right. But without being able to understand the flow and think through all the impacts, it's really hard to say if that's a good or bad idea.

So when I'm teaching modelers, I'm always banging on about, always have a hypothesis before you make a change in your model. What do you expect to have happen? Because if that thing doesn't happen, one of two things are right. Either your hypothesis was wrong and you don't really understand the flows, or your model is wrong, and both of those things are good information. Whereas I see it so many times that somebody will run some numbers in the model, the model tells them an answer, and they'll get busy rationalizing what the model tells them and coming up with a story to make sense of what the model tells them, which is all the wrong way around.

Yeah, that's the worst one. And I've definitely done that. Sometimes I'm really good at thinking on my feet. And there's more than once where I was like, oh, yeah, I still remember in grad school, we did this case, this accounting case, and I told everybody this, this has to be the answer. And, you know, we were really struggling with it. We even asked a professor, and the professor's like, you guys aren't able to solve it. I'm guessing someone's dominating the conversation. That was me. Everybody went and wrote it up the way I said. I went home and thought about it some more, and I go, logically, that just can't be right. And I completely changed my answer. I got the A, and, like, half the class got, like a C on it. They did not. That day you got an A, but.

You had no friends the rest of that term. You were. You're. You're sunk.

Yeah, they were. They were not happy with me. But I just went home and I kept thinking, I'm like, this can't be right. I had to be not thinking about this. Right. And so I was pretty funny, but that's right.

Love that story.

Yeah. So not. Not a good way to do it. All right, we're going to do one more fun question, then we're going to wrap up. This is a surprise for you.

A surprise One that's not in the contract.

If you could not do modeling for the rest of your life, you could no longer be a modeler. Anything to do with financial modeling, what would you do for a career?

I'd be a psychotherapist.

I'm not sure if I should be scared or excited by that. Why a psychotherapist?

Because I find people fascinating and I'm actually training kind of part time to do that. And I find people fascinating. And it's really interesting how Mike, my own interest has progressed over the years. I still love the financial modeling, but even in running grid lines, my primary motivation now is more about the people in the team and the wellbeing and the culture within the company. And it's just part of how I've evolved as a person. I just find that stuff really, really, really interesting there. So that's what I would be doing.

Cool. I like that one. All right. If you could offer one piece of advice to our audience to become a better financial modeler, to be better at financial modeling, what's going to be your one piece of advice? Be a psychotherapist or is it something else?

Psychotherapist. I think it's around the soft skills. Just what you don't, don't think that it kind of comes back to. I've said to people like, just because you're good at using Microsoft Word, it doesn't make you a good writer. Just because you're good at Microsoft Excel, it doesn't make you a good modeler. There's a lot more to it than that. And understanding the breadth of it, understanding how to communicate stuff really effectively that requires you to understand who you're communicating to and what their interests are. And that gets into the politics. What constraints are they under? You know, just that interpersonal soft skill stuff of knowing who you're dealing with, knowing your audience being, you know, there are some really simple but effective, you know, data visualization skills that are not difficult to learn, but man, they make a difference when you come to actually presenting data. So it's like learning that stuff, learning that. Actually nobody cares about your model. Like, they don't care about how you're, you know, our clients don't really know. There's exceptions here, but they don't really care about how we've structured the model. They just want to know the answer. They just want to know what is the model telling them. And we get so lapped about the axle, about, are we going to use vlogup? Are we going to use index match? We get ourselves all upset about that stuff and nobody cares, really.

I hate when people are like, if you use Vlookup, you're stupid, it's creating risk. Or if you use xlookup, then you're smart, you're new in Excel and I'm like, understand the differences between them, know the strengths and weaknesses and use what works and move on. Like, I could care less. I don't assume a model is bad just because it has Vlookup or xlookup or Index match. Now, are there trends you can start to figure out? If somebody's always using really old formulas, they probably can start to assume either they haven't updated themselves, maybe they don't know Excel as well. There could be some risks, but in general, it's just a dumb argument, like f. Like I said, focus on the soft skills.

Yeah, absolutely.

All right, last question. If our audience wants to learn more about you or you know your company grid lines, maybe get in touch with you, what's the best way for them to do that?

Go to gridlines.com that's our website. All our stuff is on there. They can reach me. They can reach out directly by email. Kenny Gridlines.com. those are the two best places to find me or look me up on LinkedIn. Yeah. Kenny Whitewell Jones on LinkedIn. I'm forever posting dumb stuff on LinkedIn.

Aren't we all? I post stuff so I understand. In fact, I'll post this interview in a few weeks. I hope it's not dumb stuff, but I will post.

Hope so.

No, I thought it was great. Thank you so much for joining me. Kenny enjoyed chatting with you and I hope our audience will enjoy it just as much as I did because I had a great time. So thanks for coming on, Paul.

I'm really grateful for people that do things in the financial modeling space to open up conversations to build the profile of financial modeling as a thing, as a profession. And so I'm really grateful to you. I'm grateful to the Financial Modeling Institute for the work that they do around area. They've really brought some transformational change to the space, which I really admire. So thank you for the work that you do as well.

Well, thank you. I appreciate that. And keep building those projects, more hospitals, schools, energy, all that stuff.

We need all of that.

All right, thanks.

Thanks, Paul.

Financial Modelers Corner was brought to you by the Financial Modeling Institute. This year I completed the advanced Financial Model Modeler certification and it made me a better financial modeler. What are you waiting for? Visit FMI at www.fminstitute.com backslash podcast and use code podcast to save 15% when you enroll in one of the accreditations today.