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Embracing Skepticism To Enhance Financial Modeling Techniques

Ankita Ghosh
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Show Notes

Welcome to the Financial Modeler's Corner (FMC), where we discuss the art and science of financial modeling with your host Paul Barnhurst.

Financial Modeler's Corner is sponsored by the Financial Modeling Institute (FMI), the most respected accreditation in Financial Modeling globally.

In today’s episode, Paul engages in a conversation with Geoff Robinson, to discuss the financial modeling world, blending technical skills with behavioral economics to enhance decision-making in finance.

Geoff Robinson, founder of TheInvestmentAnalyst.com and seasoned financial modeler with a rich background in investment banking and education, notably as a former managing director at UBS.

Key takeaways from this week's episode include:

  • An unconventional entry into investment banking at 43, highlighting how the background in education enriches the approach to financial analysis and modeling, emphasizing the crossover skills between teaching and financial analysis.

  • This highlights how teaching skills are transferable and beneficial in the financial analysis and modeling sectors.

  • An anecdote about a significant error in a financial model, which failed to detect a $29 billion discrepancy, underscoring the critical importance of rigorous validation and diagnostic checks in financial modeling.

  • The role of behavioral factors in financial modeling, adopting a stance of professional skepticism and the need for understanding and questioning the assumptions underlying a model before trusting its output.

  • The importance of simplicity and planning in financial modeling, the most effective models are those that are straightforward, well-planned, and can communicate complex financial insights in an accessible manner.

  • Strategies for mitigating bias, such as incorporating different perspectives and rigorous testing of hypotheses.

Quotes:  

Here are a few relevant quotes from the episode on financial analysis and modeling:

“The diagnostic on this model said if total assets equal total liabilities and equity, okay, and if they did not equal it said okay. So no matter what happened, your balance sheet, even if it was mashed up, the diagnostics said it was fine and when you went into the detail, there was a $29 billion hole in that balance sheet.”

“Financial models are an insight and window into the personality of the modeler. You can see how they think, you can see how they overcomplicate things. You can see if they're sloppy.”

“Models are question-asking tools. One of your questions was is it a primary decision maker, a financial model? I don't think models are decision-makers. I think models are the way you test a hypothesis.”

“I suppose the blunt thing to say is don't trust anything until you understand it.” 


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In today’s episode:  

(01:58) Introduction

(02:44) Guest Introduction

(03:00) Horrifying Financial Models

(04:01) Joking on Big Numbers

(04:24) Approach to Financial Modeling

(05:14) Behavioral Insights in Modeling

(05:56) Best Practices and Lessons Learned

(42:40) Rapid-Fire Question Round

(47.09) Guest's advice for aspiring financial modelers

(47.38) Contact information to learn more about various modeling techniques and tools



Full Show Transcript

Host: Paul Barnhurst:: Welcome to Financial Modeler's Corner, where we discuss the art and science of financial modeling with your host, Paul Barnhurst. Financial Modeler's Corner is sponsored by the Financial Modeling Institute. Welcome to Financial Modeler's Corner. I am your host, Paul Barnhurst. This podcast is where we talk all about the art and science of financial modeling. With distinguished financial modelers from around the globe. The Financial Modeler's Corner podcast is brought to you by the Financial Modeling Institute. FMI offers the most respected accreditations in financial modeling. I am excited to welcome to the show Geoff Robinson. Geoff, welcome to the show.



Guest: Geoff Robinson:: Hi, Paul, nice to meet you. Thanks for having me.


Host: Paul Barnhurst:: Nice to meet you and have you on the show. We're going to start with this the question we ask every guest because I know anyone who's spent a lot of time modeling has their horror storytelling about the worst financial model you ever saw.


Guest: Geoff Robinson:: Oh my goodness. There are quite a few to pick from. I think the slightly amusing and horrifying story is, and I'll not say which bank it was, but looking at a three-statement valuation model, balance sheet, income statement, cash flow, and balance sheets, as you know, need to balance. They have checks-in, they have diagnostics. The diagnostic on this model was said if total assets equal total liabilities and equity comma okay. Close bracket. So no matter what happened, your balance sheet, even if it was mashed up, the diagnostics said it was fine and when you went into the detail, there was a $29 billion hole in that balance sheet. So that's pretty bad.


Host: Paul Barnhurst:: $29 billion. what's 29 billion among friends?


Guest: Geoff Robinson:: Between friends, it's just it's pennies.


Host: Paul Barnhurst:: We used to joke. So I started my career in procurement working for the government. One of the jokes we'd say sometimes just because you spend so much money with the US government, especially defense, which is where I was, we would occasionally joke billion here, a billion there. Pretty soon it adds up to real money, you know. So what was your kind of key takeaway or learning from that experience, from seeing that model?


Guest: Geoff Robinson:: I would say, I suppose the blunt thing to say is don't trust anything until you understand it. I think the more professional way to describe that, and is a great term I got from, one of the the guys I looked up to at UBS was, to adopt an air of professional skepticism. So I need to understand what's going on before I'll start to rely on it. I need to have that trust, that understanding that the robustness is there. So there are different checks I will do as soon as I get into these financial models, which we can talk about. I'm sure you know, people will know what I'm talking about here. But you need to have that kind of confidence before you can even start kind of implying the insights that you're looking for.

Host: Paul Barnhurst:: Got it. So okay and okay is both true and false, and is not a robust check.


Guest: Geoff Robinson:: That's not a good start. So it's things like that, but you see I think financial models are a real kind of insight and window into the personality of the modeler. you can see how they think, you can see how they overcomplicate things. You can see if they're sloppy if you're picking up hard codes if you're picking up formulas that have a cell reference plus a cell reference plus a hard-coded 20. I think when you start to pick up these little kind of tails and ticks, well, I certainly start to form a view on the personality of the person that I'm dealing with and the integrity that they had.


Host: Paul Barnhurst:: Those are some good points. It's amazing how much you can learn about somebody by looking at the work they do.


Guest: Geoff Robinson:: It's that logic. Their personality goes into this model. It's their DNA. I've had situations where I've walked into a bank and I've looked over somebody's shoulder and I've seen their model. I thought, hang on a second, that's got a bit of me in there. Then I talked to the person and it turns out I trained them 15 years ago when they were 21 years old at Citigroup. They've adopted those best practices, and that we're all at that stage. I know you had Mr. Bennett on the podcast a couple of weeks ago, both he and I just cut from the same hymn sheet that you need those best practices in place. So there are bits of DNA that you see in other people's models where you think that's possibly come from me as an influence over the years because I think over the years I probably trained 20,000 plus analysts. So good and bad, I think on my part. But they're all there in the market.

Host: Paul Barnhurst:: You start to see that DNA, makes a lot of sense. So why don't we go ahead and have you tell us a little bit about yourself, and your background? Let the audience get to know you a little bit before we carry on.


Guest: Geoff Robinson:: I would say I'm a teacher. I'm a financial modeler. I happen to have eight years working as a managing director at UBS and Equity Research, which was kind of an afterthought. But the bulk of my career has been building, training businesses, and getting to the stage where we were pretty dominant. Again, you've had Scott Rosson on the podcast. He was a compatriot of mine, competition to me. He was the US, we were Europe. I did that for the best part of 20 years. But we sold the business to Fitch in 2013. Then, UBS came along and said, "Listen, Geoff, what you're doing at the moment?" I was like, hey, nothing, just sold my business, I'm kind of hanging out here. I'm a bit bored." They said, "Well, why do you why do you not come to be a research analyst?" I hadn't done that before. I had trained Morgan Stanley's research business for 15 years, so I had an outside view of it. I pitched up to UBS with no experience and built a research franchise there and had eight wonderful years speaking to investors, financial building models, trying to get people to build better models, seeking better insights, and kind of advise the market. So it's been a varied career. It's not a traditional route into investment banking to kind of have your first day at the age of 43, walking into the business. So I was a late starter, put it that way.


Host: Paul Barnhurst:: Definitely. You rarely see someone in their 40s just starting in the investment, the typical investment banking route. Usually, you see it maybe out of undergrad, grad school, maybe a couple of years of work, but generally it's a very early one of those first type things. So talk a little bit about that experience, maybe how having all that prior experience teaching you prepared, prepared you for it, or how it was different for you coming in at that stage?


Guest: Geoff Robinson:: Well, the first weird thing was having to do my regulation and securities exams at the age of 43. I think in the US, it's series 63. In series seven, if I remember correctly, I'm doing those exams with a bunch of 21-year-olds. I'm the granddad in the corner kind of, trying to work out, is it T plus three that a Japanese bond settles at? So that was a little bit weird. But I'd have to say, I think being an educator was just a wonderful way to then be a research analyst because it's a very similar skill set. You're trying to tell investors something insightful that you've come up with that they, hopefully, if they've thought about it, it's a pointless conversation. So I've got to something new and that's hopefully not priced into the market. That's different. I've got to teach it to them and I've got to make it digestible, and you've got to get your point across in a way that you are not coming across too complicated. It's simple, it's digestible, it's takeaway, and those are teaching skills. I think that's one massive thing. The other massive thing was, it's ironic that most equity research analysts haven't run a business before, and, I'd run a business for 20 years.


Guest: Geoff Robinson:: So probably the first 4 or 5 months at UBS, I just watched the other teams do what they do and built up a sense of, "Okay, there's a bunch of good ideas that they do, but here's a whole bunch of areas where they could do it better and they could analyze the data." One of the reasons, I would say, we were immediately ranked number one in the first attempt that we went at it. I went at it hard because I'm that kind of person. I thought I'd got to beat the person who's been number one ranked for 6 or 7 years. How do I do that? I just worked out the rules of these rankings, and there are rules behind them. It's a game. I got the data and I just kind of found out, okay, I'm not going to ring 300 people because I know these 15 people carry more weight in the vote than the other 285. So I just went through a very targeted, cross-sectional data analysis. I think we won because we were smarter playing the game as well as having a good product, but as knowing the rules of the game, being able to play that game hard.


Host: Paul Barnhurst:: Now you're not competitive when you play card games, board games, sports, or any of those types of things, right? Not at all.

Guest: Geoff Robinson:: I'm competitive. Yeah, I am. I'm currently trying to figure out if I can outbench my son. He's 16 years old and built like a brick and I'm miles off him. But I'm hoping by the summer I can get pretty close to him. So I'm into census games where I try and turn everything into a game, to be honest.


Host: Paul Barnhurst:: I kind of figured as much as you reversed-engineered it and figured out, "Okay, what are the rules that go into us? How do I make sure I maximize my score here? How do I win?"

Guest: Geoff Robinson:: Definitely.


Host: Paul Barnhurst:: I can tell we have a deep analyst who thinks about a lot of things. So I'm curious what is it that you love so much about modeling valuation and stock picking and that kind of whole exercise with being an equity analyst and trying to find those unique angles to bring to your customers?


Guest: Geoff Robinson:: I think being an equity analyst, financial modeling is a real core part of what we do. what I love about it is the only way you make money is by being able to articulate why you think the market is wrong, and the market's not particularly, it's pretty smart. So to be able to identify an opportunity that you think the market isn't grasping correctly is where models come in to me. I think you've got a question later on. It made me think about the answer. But to me, models are question-asking tools. One of your questions was is it a primary decision maker, a financial model? I don't think models are decision-makers. I think models are the way you test a hypothesis. You have an idea and I want to break that idea. I want to come up with that idea from different angles. I want to ask what would happen if. there's a very high likelihood I'm going to be wrong because I'm trying to forecast the future and none of us have a crystal ball. So I am going to be wrong. I want to know if I'm wrong, how wrong I'm going to be, and at what point does that break my hypothesis? I find that fascinating. Then go out with an idea and speak to, usually, a bunch of people who are super smart and usually smarter than I am, and tell them, I think you've got it wrong. I thrived on that, I loved it. It was scary, the times, but it's a real way to kind of intellectually test the robustness of your thought process. It's great, it was great.



Host: Paul Barnhurst:: It sounds like a lot of times you were right, obviously. I think you mentioned being ranked number one. Was it eight or nine years in a row, your team was the institutional research there in EMEA? Obviously, you had to have a lot of times you were right and doing good research. So I'm curious how did you go about that process, maybe when you started researching a company before you built that model in stock, what were you looking to learn about them to help you in building the model?



Guest: Geoff Robinson:: That's a great question. I think it varies depending on the circumstances that you're in. Sometimes there's just a catalyst that happens in the market. Trump's getting elected in 2017 was interesting because of the tax reform that he did an act going from 35% down to 21%. What I wanted to do there is think about what the legislation was saying and think about as analysts, as investors, how historically we've thought about that legislation and possibly got it wrong. So it's almost you get very behavioral or you've got the theory and the legislation, and then you've got the behavioral implications. Then you're looking for misalignment. My view was, "Listen, I think this is a big deal. We're going from 35 to 21%. But in reality, nobody pays 35% tax. Nobody actually will pay 21% tax." The goalposts are different from the headline. You were then trying to link that back into, Well, how are people reacting to this in the market? Is there scope there for possibly being a little bit smarter in the analysis? For that legislation took, I think it was until, I want to say, April 2018 to be enacted.

Guest: Geoff Robinson:: We, in our publication, were kind of four months ahead of what people were saying because Trump wanted to go down to 15% at one stage. We were like, "Listen, there's no way that's going to happen." 21 to 23 is probably where it would settle. Then the market caught up with that. We were talking to some huge investors. I had a two-hour sit down with Carl Icahn one-on-one talking about US tax reform because he had a trade on the S&P 500. I was saying something quite different from what his trade was. Again, that was something that I'll take away to my grave is a phenomenal experience to take your work to somebody of that level and that kind of standing in the market.


Host: Paul Barnhurst:: I know that sounds like I was in a fascinating conversation. Any takeaways from that two-hour conversation that you can share or what was that like? I can imagine that had to be a little nerve-wracking, exciting, a little bit of everything.


Guest: Geoff Robinson:: Nerve-wracking, terrifying, and amazing. I turned up to his office, which is right next to the Apple Store on Fifth Avenue, and his assistant said "Kyle was going to be 45 minutes late. Go and make yourself comfortable in the boardroom." The boardroom was like entering a museum of just artifacts on the wall of deals that I'd grown up with as a kid and into my teenage years. So Texaco, Marvel, and Pan Am people listen to this or are old enough to remember Pan Am. They know how old that deal is. So I had 45 minutes of just entertaining myself with this kind of deal history. He then turned up and was sharp as a tack. He must have been early 80s at that stage. For a guy who's not a deep numbers guy like myself, he just got stuff so quickly, got straight to the point, and had such experience over the markets. It was just an incredible experience, quite frankly. I'm very thankful.



Host: Paul Barnhurst:: I can imagine, as I said, you'll remember that one for the rest of your life for sure. So I'm curious, as you mentioned, trying to you gave the taxes and example, trying to look at things from not just hey, here's what's happening, but that behavioral and trying to find where there are misalignments. How did you think about that? Was it mostly looking at the historical data and saying, "Okay, everybody's predicting this will happen, but historically it's been a little more like this, there's a little bit of room here to take advantage of the opportunity because we think people are going to behave differently based on history? Is that a lot of times what you were looking for, how did you think about that?



Guest: Geoff Robinson:: I think I read a lot of Warren Buffett's work and Charlie Munger's work. I'm a great believer in looking at things through multiple lenses and reading broadly, applying different frameworks and just trying to look for an angle. That most people are looking like this because they're under such pressure in their day-to-day work. To have that bandwidth to look at things from different angles is difficult. So history has a rhythm to it. It's very interesting, for instance, looking at the Magnificent Seven and I just have these echoes of, okay, I've been through a.com boom before, I think structurally we're in a different situation in today's markets. I'm hearing people saying this time it's different. I think it was John Stapleton, sorry, Templeton, who described those the four most dangerous words in finance. This time it's different. That's what we heard in 19 90,000, 2001. If you try and visualize life as a normal distribution curve consensus, and the herd is all crowded around that kind of central point of the meeting, I think my job is to force myself to think on the periphery of the tails of where things that could go wrong and when I sit down and build a financial model, I don't put a lot of credence on my ability to forecast the future, as I said before.



Guest: Geoff Robinson:: So what I'm usually doing is, I'm trying to figure out what the market pricing is, and then do I believe the company can fundamentally deliver on the expectations that the market has priced into that stock? Peloton was a phenomenal example of this because when I IPOed, I couldn't get anywhere near its IPO price. Then its IPO price was $29 a share, and then it hit 154 or something like that. I could never get those numbers to work. It was never worth that amount. So it was just a question of waiting for the fall. The fact the stock went down, it's suffered. But the fact that stock is trading on single digits now is no surprise to me if you were able to run these models in a consistent manner where the narrative stood up, you'd never be able to get those numbers to work. So when you do something similar to Nvidia, I think it's a useful exercise to say, okay, I don't know what Nvidia is going to do in the future. But its stock price is way up here. What can I do in my model to try and replicate that answer? What does that tell me about the business and the sustainability of generative AI expansion and GPU development?



Host: Paul Barnhurst:: Now, I think that's a great point. The stock price is at 300 today. I would value that at $50 or whatever the number is. $50 billion and it's worth 400 billion. What would it take to get there? Are those realistic assumptions? For example, I had a guy Sam Severin on the show, and he shared the story where there was an analyst on Wall Street who did some research and said, hey, this stock is going to do this. They doubled the last two years or something. He assumed that would happen for the next eight years. That's never happened to a stock but in isolation, because it wasn't looking at broadly, it was going very narrow and just taking the history. He thought that made sense. He got roasted when it went out public. When one of the guys got his story in a stock market, he goes, you realize this has never happened with the stock. What you're saying is it happened here, like how did you think that was a good idea? So I think putting pressure on testing it and digging in.



Guest: Geoff Robinson:: I said, you stress testing, you're trying to break it. You're trying to break a hypothesis. If you can't break it, you are coming out with a view that's different from what the market's pricing is. Quite frankly, that's when things get interesting because you're in a position to say to investors, "Listen, I think I've got something here that the market's not capturing. That gives some opportunity for some alpha there, some gains in excess of the market basics.



Host: Paul Barnhurst:: Sure. So what advice would you offer to audiences that are listening maybe or doing valuation models? We've talked a little bit about behavior and the hypothesis and things. But what would you say are the key 2 or 3 things they should be thinking about if they're doing valuation models from your experience? In today's business world, financial modeling skills are more important than ever with Financial Modeling Institutes. Advanced Financial Modeler Accreditation program, you can become recognized as an expert in the field by validating your financial modeling skills. Join the Financial Modeling Institute's community of top financial modelers. Gain access to extensive learning resources, and attain the prestigious Advanced Financial Modeler accreditation. Visit www.fminstitute.com/podcast and use Code podcast to save 15% when you register.



Guest: Geoff Robinson:: I think there are certain areas not to spend too much time on. So my view, which may be slightly controversial and people may not agree with it.



Host: Paul Barnhurst:: That's okay, we like controversy. Go for it.



Guest: Geoff Robinson:: I think you've got two options on the cost of capital, which both involve you being wrong. So you've got a choice of you can be wrong quickly or you can be wrong slowly. So I prefer to be wrong quickly and then run sensitivity analysis to find out and quantify how wrong I could be. So there are certain areas there. I think you've just got to take your views and run the sensitivity behind it Then figure out, okay, if I am wrong, this is what the impact is. But I would say the recurring parts to pick one big recurring theme that I see in valuation, because it's all forecasting, it's forward-looking, is making sure that you've got a consistent narrative behind your story. what I mean by that is that there's an awful lot of time spent forecasting our revenue, and then costs are usually a derivative of revenue. Then it's almost like the analyst gets a little bit bored with working capital. Then, all right, we'll do some CapEx and we'll run that down to depreciation. What can and happens a lot happens in my work. I do this myself and I mess it up. Is that you have the operations of the business? Almost getting carried away. inconsistent with the reinvestment requirements needed to support that operation. There are a million other things that could go wrong and can feed into this issue. But that lack of a consistent narrative, I think is probably the biggest recurring error theme that I see in people's work because the ramifications of this are it'll start blowing up things like terminal values or lower state cash flows. I think personally, a DCF, it's much easier to overstate the valuation than it is to understate it. a lot of it comes through the lack of consistency because it's storytelling at the end of the day, that's what it is. If your story is not consistent, it's like having plot holes, and in a Tarantino film people will spot it and you'll get called out.



Host: Paul Barnhurst:: But if it's a flick that's just there to have a lot of fun then the holes are okay. Probably doesn't work, though, when it's your money.



Guest: Geoff Robinson:: When it's your money or other people's money and your job.



Host: Paul Barnhurst:: Exactly. So that leads me to a question. You talked about often getting lazy the further down you get as you work through everything. You focus on revenue. You feel like you got that right. So I think it leads to two questions. The first is, any advice as they get further and further in the PNL, is it just spending more time? Are there certain areas like the OpEx and capital you think need more work generally, or what's your thought there?



Guest: Geoff Robinson:: I think it all starts with accounting knowledge. So I'm a chartered accountant in the UK. I was not a very good one. I didn't do it for very long. I qualified and I got out pretty much straight away. But it gave me a super solid grounding in how the numbers work. Now you know this, and I know this accounting is not a fascinating subject. It's not particularly well taught. Most people that I come across get taught with T accounts and debits and credits, which is great if you want to be a 16th-century monk looking after a book ledger. But if you want to be an analyst, debits, and credits don't help you because that's preparer language, there's a consequence. I think people just don't learn the accounting as well as they could do. Then they start relying on the numbers. you can be misguided by companies' reports incredibly easily. We talk about I've been writing quite a lot on just having a rant about EBITDA. EBITDA can tie you in knots and you are completely and blissfully unaware of it. So the core kind of ground zero, people can always improve their knowledge of the numbers. The best analysts I've come across are the ones that were forensic with those numbers and then could see the commercial implications within the stock price.



Host: Paul Barnhurst:: They understand the implications of those numbers, how the accounting worked behind it, that language of numbers. We're able to translate that into the commercial impact and how that impacted the business and what it meant.



Guest: Geoff Robinson:: You don't have to be an accountant to do this. You've just got to have taken your accounting training on your grad program seriously and also to keep working on it and that's essentially for eight years, nine years at UBS. I was talking to people saying, listen, your valuation is wrong because your accounting is letting you down here, here and here.



Host: Paul Barnhurst:: Interesting. It doesn't surprise me. I've seen a lot of times, my experience is mostly FP&A, financial planning analysis which is just forecasting. You're usually just forecasting the PNL for big companies, and small companies. You're doing a three-statement forecast. There were times when you saw a lack of understanding of accounting get impacted in those models and like, oh no, that's capital or no, you can't think of it that way Or did you remember this? So I know exactly sometimes with revenue and how are you treating the net discounts and promotions and all kinds of fun little things.



Guest: Geoff Robinson:: One of the biggest issues is just getting a balance sheet to balance. It sounds like it's super easy. We have a case study that I use in my training business that I've run past maybe a thousand analysts. it's not an easy one, but it's not rocket science either. I've had two people get that right out of a thousand. It's not necessarily about a lack of accounting knowledge. It's more to do with a lack of technique of how to apply these accounting numbers in a financial model because we're so groomed to pass exams. I think the way people put numbers together is they'll say, I'll do the income statement. I've done the income statement, I'll do the cash. I've done the cash flow and it's almost like you've got hundreds of one side of a double entry that you've got to put all those jigsaw pieces into place in the balance sheet perfectly and hope to God that you've done it perfectly, and the thing balances. Guess what? It doesn't if you follow that technique. Then you're looking for a needle in a haystack, you're under pressure. Your boss wants something, you want to go home. It's 10:00 at night. Then I can see why people then think, oh, you know what? I'll just put a cheeky little formula in here that's just going to plug that balance sheet through retained earnings. I know it's not right but it looks good. My boss is happy. Everybody goes home. Hopefully, it doesn't blow up in my face.



Host: Paul Barnhurst:: We've all been tempted, I've been there. When I was taking the Advanced Financial Modeler from FMI. This was just a couple of months ago. I've done very little three-statement modeling. So the hardest part was kind of the balance sheet, just building out all those pieces because I was a PNL guy for my career. So I'd done it a few times and got in there taking that test. I've been super tired from trying to study and run a business during the week, and it didn't balance, and I was about ready to say, just screw it, I fell. I spent about an hour and it turned out it was something as simple as I had my parentheses.



Guest: Geoff Robinson:: It's always easy, it's always something simple.



Host: Paul Barnhurst:: Am I working capital? I just put the parentheses in the wrong place. It was summing it up wrong. As soon as I fixed that formula, Voila.



Guest: Geoff Robinson:: It's interesting you say that Paul because I reckon it wouldn't surprise me that half the balance sheets you see around the planet probably don't balance. There are little cheeky formulas in there. But if you gave me a balance sheet that wasn't working, the first place I would go to is the cash flow statement. In the cash flow statement, I'd go to working capital because it's like there is a human mental block on what signs you put for an increase in receivables. Is it a negative or is it a positive? Depending on how tired you are, you can convince yourself of the incorrect answer very easily. We've all been there. I've done it myself. So you do see patterns in human behavior and where those errors go wrong. There's like a heat-seeking radar for me when I look at people's models and think, okay, that's not working right, Working capital cash flow statement, if not, let's go check the balance sheet, let's check CapEx, if not, let's go check adding back DNA in the cash flow statement. Invariably you find where the the issues are.



Host: Paul Barnhurst:: No, I saw Schnoor recently did a 10-part video series of "Your Balance Sheet Doesn't Balance." Just walk through where you should be looking. I remember one time I had it not balancing and I went through his list and he'd only done 7 or 8 of them at the time. It was none of those. It was just something a little stupid where I'd forgotten to copy a formula over, and I didn't highlight it when I was working.



Guest: Geoff Robinson:: Try and find that when you're tired. You've got to be holding on to a cross, hopefully, to be able to find it.



Host: Paul Barnhurst:: I Got lazy and just did not make sure, it was clear that I had done something there that I wasn't supposed to as I was trying to figure something out. So I'd know to come back and fix it later. I forgot.



Guest: Geoff Robinson:: You don't want people interrupting you halfway through a modeling exercise. I used to wear headphones on the desk at UBS, and it became an unwritten rule. If I've got my headphones on, stay the hell away because I'm in the middle of something. Because if you're in the middle of modeling something Somebody comes across for a chat and you lose your flow, trying to pick it up again is difficult.



Host: Paul Barnhurst:: I agree with you. It was one of those where I had left it and come back. I had to go do something and came back to it so you'd forgot what you'd done and you didn't document it. We've all been there. It happens but it's when we get when we get lazy is when it happens. So I'm curious. You talk a lot about the behavioral side of modeling. We'll talk a little bit about that. So how big of a role do you think human bias plays in the modeling process? Then any thoughts on how we compensate for that?



Guest: Geoff Robinson:: I think it's huge. I spend more of my time these days talking about the behavioral aspects. today's a bit of a sad day. If you saw Daniel Kahneman, 90. I mean thinking fast. that's had a huge impact on how I go about my modeling and forecasting, the idea of having an inside view, which is our expert view on life. Then just having this more data-driven, kind of context-agnostic outside view is one of the ways that you can deal with bias. Because we're all biased. We're all biased by recency, by confirmation, by affirmation. It is in our work all the time. That's why as analysts, we're just wrong a lot because of those biases. So I think one way to try and manage this is to look you said earlier in the podcast, history's got a rhythm and a relevance. If you're looking at something that has not happened before ever, let's not say it's wrong, but what's your evidence to back that up that comes outside? There's no point in you saying I think this is going to happen. It's all right. I don't care what you think. Where's your evidence to support that? So it's using that outside view, so I mean Daniel Kahneman's work has been huge in that respect. The other guy who was deeply influential at UBS kind of 2015 to 20 was a chap called Phil Tetlock who wrote a book called Superforecasting, which talks about how there are certain skills that we can work at that make us better forecasters.



Guest: Geoff Robinson:: Some of fairly simple stuff, if you make a mistake, analyze why you made that mistake and do a post-mortem, but also do a pre-mortem and try and figure out, okay, if I was correct, how often do we do this? We get something right. We're normally just. Yes, got it right, brilliant. You don't tend to go through and figure it out. How did I get it right? Is that repeatable? Was I lucky and just trying to work on that information? I think you can work at managing those biases, by looking at some of those techniques. So those are two books. Absolutely, I would recommend that people pick up and have a look at Kahneman, very well-known. Phil Tetlock's Superforecasting is pretty well known, but it's an excellent read. I think that's what it is, it's "Read a lot." I read more than ever now. It's hard to do it when you've got a Wall Street job. You're trying to get the job done. But I think Charlie Munger said he never met a smart person who didn't read all the time.



Host: Paul Barnhurst:: There's real value and always reading and learning and gaining wisdom from others, whether it's listening to books or whatever. But I'm a huge believer. You need to be looking to learn all the time because just part of having that growth mindset. So I appreciate that we'll throw both those books in the show notes. So this next question is a fun one we like to ask people, what's your favorite Excel shortcut and why?



Guest: Geoff Robinson:: I think "Copy and paste special links." I don't know if people use that quite often. So I think one of the fairly common errors is when people try and link data. Between spreadsheet tabs are that they just pick up the wrong cell, and I can't explain why this is the case, but I think if you go to the cell you want to pick up and you copy it, and then you go to your destination cell and say, I'm going to do paste special. If you do paste special, that menu comes up, the bottom left-hand corner has a little button that says paste links. You hit links and it creates the connection for you. I think you've got a much lower chance of screwing up the data connection, and that is one I use an awful lot. I think I'm a huge fan of shortcuts because they make you quicker, as we all know, and you're probably saving 4 or 5 times the speed compared to somebody on the mouse. I just want to make fewer mistakes because ultimately "I want to go home" is in the back of my mind. I want to see my family and I want to see my son. If I'm just in the office because I've just been a bit rubbish, that is not a good use of time.



Host: Paul Barnhurst:: Spoken like someone who started banking at 43 instead of the 20-year-old, that's "I don't care if I'm a little late in the office."



Guest: Geoff Robinson:: I want to see my family. I want to go home. I say it when I'm dealing with the younger kind of cohort within the banks, is that modeling is quite fun and people want to get on and do it. it's almost like, can you build this? Yes, I can bang straight into the keyboard. Whack, whack, whack, whack. If you don't plan, I think you have overcomplicated the modeling process. I think I think my models are disappointingly straightforward and simple. they did clever things. So being able to build something clever and simple, I think is the real skill. Modelers should be aspiring too, but that will only happen if you have a little think about what you're doing. I have a pen and pencil and I draw stuff, and I think about the layout and I think is it best doing this vertically or horizontally. I just take a little bit of time over it now as life and time goes on, it's almost like you have this kind of encyclopedia of templates in your head. I know how to build a loss memorandum. I don't need to plan it. But at some stage in the past I planned it. That's code which could get incredibly complicated. In fact, actually, I think in my AFM exam, I had to build a loss relief memorandum where the losses only had a five-year life, which gets hugely complicated. if you didn't plan it, oh my goodness, the code would be horrific. But if you do plan it, the code is not that bad. that's when I think you have a situation where your code becomes simple because your planning was good.



Host: Paul Barnhurst:: I absolutely couldn't agree more with what you're saying there. I loved when you said the models are embarrassingly simple and easy. One of the sayings I use all the time in my training, especially with Excel is "Complex is easy, simple is hard." Because it takes time to design and think through it and often making it simple is more work than just throwing in that nasty if statement that we've all used before, or whatever it might be.



Guest: Geoff Robinson:: Honestly, Paul, it's you making me want to grow a beard now.



Host: Paul Barnhurst:: Go for it.



Guest: Geoff Robinson:: We're on the same sheet in that respect. I had a quote, and it was my quote. I wrote a book at UBS called Build Better Models and in the massive font on the second page was something along the lines of, "Good models do clever, Great models do clever simply." It's the same thing.



Host: Paul Barnhurst:: I like that. I'll remember that one for sure. So we're going to move into our rapid-fire section. Here's how this works. I think we have about 10 or 11 questions here. You get no more than 10 seconds to answer. You can't tell me, it depends because I know it could be the answer to all of them. You got to take one side or another, and then after we get through the whole list, we'll run through them. Then you can expand on 1 or 2 answers to give a little more nuance because I recognize there's nuance to all of these. So circular or no circular references?



Guest: Geoff Robinson:: No circular.



Host: Paul Barnhurst:: VBA or no VBA?



Guest: Geoff Robinson:: No VBA.



Host: Paul Barnhurst:: Horizontal or vertical model?



Guest: Geoff Robinson:: Vertical.



Host: Paul Barnhurst:: Excel dynamic arrays. Yes or no?



Guest: Geoff Robinson:: Yes.



Host: Paul Barnhurst:: External workbook links. Yes or no?



Guest: Geoff Robinson:: No.



Host: Paul Barnhurst:: Named ranges or no named ranges?



Guest: Geoff Robinson:: Named.



Host: Paul Barnhurst:: do you follow a formal standards board when you're modeling?



Guest: Geoff Robinson:: Yeah, it's in my DNA.



Host: Paul Barnhurst::: Okay.



Host: Paul Barnhurst:: Will Excel ever die?



Guest: Geoff Robinson:: It should.



Host: Paul Barnhurst:: Okay. I'll be curious to learn more about that one. Will AI build the models for us in the future?



Guest: Geoff Robinson:: Probably.



Host: Paul Barnhurst:: It will be interesting to watch. So should we use sheet cell protection in our models?



Guest: Geoff Robinson:: Yes.



Host: Paul Barnhurst:: Okay. Do you believe financial models are the number one corporate decision-making tool?



Guest: Geoff Robinson:: No, they don't make decisions, humans make decisions.



Host: Paul Barnhurst:: What is your lookup function of choice? Choose Vlookup, index, match, Xlookup, or something else I didn't ask.



Guest: Geoff Robinson:: Xlookup. Xlookup is a gift and then why it took 30 years?



Host: Paul Barnhurst:: I love Xlookup. It's so much easier to train Xlookup if somebody doesn't know Excel.



Guest: Geoff Robinson:: Makes sense.



Host: Paul Barnhurst:: Big fan there. All right, so which 1 or 2 you'd like to elaborate a little bit?



Guest: Geoff Robinson:: Let's talk about "Will Excel die?"



Host: Paul Barnhurst:: You said it should. Why should it die? Let's start there.



Guest: Geoff Robinson:: Because that means you haven't evolved. You know that in the last 24 months in Excel, the evolution has been more than the last 20 years, a huge amount of pressure. AI, ChatGPT, and Python coming in, if you think what in 1969 we sent people to the moon with less computer power than what's in your iPhone.



Host: Paul Barnhurst:: Less than what's in my watch.



Guest: Geoff Robinson:: Exactly. So what I would hope is, I'm not saying Excel is becoming extinct or obsolete, I would hope it evolves to such an extent that it is almost a completely different beast in 20 years, if we are still doing something that is just sort of like a user experience evolution of Excel, I think that would be surprising to me because look back at history. Everything dies.



Host: Paul Barnhurst:: That's what I always say. It's a question of when, not, if. Just based on history, that's what I say. Some people have answered., they'll say yes, but I hope not in my lifetime. I hope not to learn something all new. So any other one you want to elaborate on?



Guest: Geoff Robinson:: Well, give me a real rerun of that. Just run through those questions again.



Host: Paul Barnhurst:: Circular or no circular, VBA or no VBA.



Guest: Geoff Robinson:: No circular, so we'll do this quite quickly. There are two occasions I will use circular reference reluctantly, but the danger of circular reference is as soon as you switch iterations on, you've given the model over to the computer. So I think Ian Schnur's view is it's okay if you understand it, even if you understand it, you switch the iterations on. We can all find new ways of screwing things up in a new way, and you've got problems at that stage. The VBA one is, in my world, there are not enough people that understand VBA. So if I build something in VBA, I'm creating problems for people who are using them.



Host: Paul Barnhurst:: That's usually the biggest, I think, issue with VBA is downstream.



Guest: Geoff Robinson:: If we kept it internally and it was just my team, we would build things in VBA, Python, and R, but it was for our benefit. It didn't go anywhere else, and we used the data analysis off the back of that in order to figure it out.



Host: Paul Barnhurst:: That makes a lot of sense. So we're heading into our last questions here just to wrap up. So the first one, if you could give our audience one piece of advice that they should follow to be a better modeler, what's your one piece of advice?



Guest: Geoff Robinson:: I think it goes back to what we said before, it's planning. Just take a breath, take a knee, get a pencil out, and just have a think. Even if you don't write anything down, just having a pencil in your hand is just going to halt you for a second, and you can save yourself an awful lot of time by just taking a breath.



Host: Paul Barnhurst:: Great, love that. So last question before we let you go. If somebody wants to get in touch with you or learn more about you, what's the best way for them to do that?



Guest: Geoff Robinson:: I move out of the way, there's that thing there. So if you can see it behind you can see it.



Host: Paul Barnhurst:: Theinvestmentanalyst.com, I love it. Great marketing there.



Guest: Geoff Robinson:: I said I'm not trying to build empires here. I'm just a very experienced analyst I've taught for a long time and I love teaching. I'm not teaching people Excel. I'm teaching people how to value companies. So I spent a lot of time with hedge funds, asset managers, bankers, and private equity. So that's where I come from. Excel has always been, financial modeling's always been a tool that I'm using to get to the point of being able to portray the insight.



Host: Paul Barnhurst:: I love how you said that because that's really how it should be treated. I had an interview, who once said, "Remember, your product is not the spreadsheet, it's the insights and the decision-making that you help derive because of the spreadsheet." It's basically what you said there. I think if people remember that, you think about it differently.



Guest: Geoff Robinson:: Absolutely, Touche.



Host: Paul Barnhurst:: Well, thank you so much for joining us. I enjoyed chatting with you today, Geoff, and I look forward to sharing this episode with the audience.



Guest: Geoff Robinson:: An absolute pleasure. It's lovely to speak to you, Paul, every time. So thanks for having me on your podcast.



Host: Paul Barnhurst:: Financial Modeler's Corner was brought to you by the Financial Modeling Institute. Visit FMI at www.fminstitute.com/podcast and use code podcast to save 15% when you enroll in one of their accreditations today.