In this episode of the "Financial Modelers Corner," host Paul Barnhurst welcomes Gilbert Hangartner, a financial modeler with a background in science. The discussion delves into the intricacies of financial modeling, the importance of simplicity in model construction, and the application of Monte Carlo simulations to understand risk. Gilbert shares his insights on how to approach financial modeling by asking the right questions rather than having complex formulas.

Gilbert Hangartner is a seasoned financial modeler who transitioned from a career in science, specializing in chemistry and physics, to financial modeling and risk analysis. His scientific training gives him a unique perspective on financial modeling, treating it as both a creative process and a technical discipline. Gilbert emphasizes the importance of simplicity and clarity in building effective models and is an advocate for using models as tools for communication and strategic decision-making.

Key takeaways from this week's episode include:

• Understanding the importance of simplicity in modeling 

• The debate on whether financial modeling is more of an art or a science

• Simplifying a problem and understanding the question before diving into model building.

• Introduction to Monte Carlo simulations for risk management

• A discussion on the limitations of Excel and future of financial modeling
  

Here are a few quotes from Gilbert Hangartner:

• "A good model is not about complexity; it's about clarity and answering the right question." - Gilbert Hangartner

• "For me, modeling is a creative act, much like writing a song or painting a picture." - Gilbert Hangartner

• "Multi-dimensional modeling is key; real-world problems are never just two-dimensional." - Gilbert Hangartner

• "The future of financial modeling lies beyond Excel; it’s time for more advanced, structured tools." - Gilbert Hangartner
  

In this episode, Gilbert Hangartner offers a fresh perspective on the world of financial modeling and challenges the conventional wisdom that financial models must be complex to be effective. Whether you're a seasoned modeler or just starting out, Gilbert's insights on Monte Carlo simulations provide valuable guidance on how to enhance your modeling skills and approach.

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In today’s episode:
[01:16] - Introduction to the episode and the guest, Gilbert Hangartner

[01:57] - The worst financial model horror story shared by Gilbert

[04:42] - Discussion on the importance of simplicity in financial modeling

[06:10] - Gilbert explains his transition from science to financial modeling

[10:11] - Art or Science? The nature of financial modeling

[13:45] - Strategies for asking the right questions when building a model

[17:16] - An overview of Monte Carlo simulations for risk modeling

[28:31] - The advantages of Quantrix over Excel 

[44:47] - A contrarian view on the future of Excel in financial modeling

[47:48] - Closing remarks and contact information

Full Show Transcript

[00:00:59] Host: Paul Barnhurst: 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. The Financial Modelers Corner podcast is brought to you by Financial Modeling Institute. FMI offers the most respected accreditations in financial modeling. This week we are thrilled to have with us Gilbert Hangartner. Gilbert, welcome to the show.

[00:01:34] Guest: Gilbert Hangartner : Hi, Paul. Nice to meet you.

[00:01:36] Host: Paul Barnhurst: Yeah, really nice to to meet you as well. Where are we today? I know you're out on your boat, so where are we at?

[00:01:43] Guest: Gilbert Hangartner : I'm currently in Canarian islands in the middle of the Atlantic Ocean on a little island called La Gomera.

[00:01:48] Host: Paul Barnhurst: Well, enjoy it. I hope you get to go out and enjoy the beach and spend some time on the island. That sounds like a fun trip.

[00:01:56] Guest: Gilbert Hangartner : I will do that.

[00:01:56] Host: Paul Barnhurst: All right. As you know, I always like to start the show with the same question. And it's tell me about that worst financial model you've ever seen, that horror story.

[00:02:08] Guest: Gilbert Hangartner : There are obviously a lot of very bad models, especially complicated models, which are difficult to understand and which give the user a pain to work on. But the story I want to tell you is the model that had the most disastrous effect. And that was new coming new to a company. I was just hired, and the CFO came up to me and said, Gilbert, we just finished this project. Can you look at this model before we go to the board for the final decision? And I took a look at the model and it was they worked half a year on it, ten people. So it was a lot of work, dozens of tabs and thousands of of lines. And you know what? You wanted to understand the calculation. You had to follow a formula over ten steps to find the right number that gets into it. That was horrible in the end. First, they just modeled the new business was a business extension about 20% of the business they wanted to invest in. And then obviously the board asked, well, let's compare this with our traditional business if we won't do the extension. So let me compare how is it with the investment and without the investment? And they were late in time, so they just took the current business we already have.

[00:03:17] Guest: Gilbert Hangartner : They took other numbers and then it made a difference. And these are the numbers weren't calculated the same way in the same model. So the difference gave gave a huge positive of net revenue for for for the investment. So the board said yeah cool. Let's let's do that. And then when I calculate that I realized that if you would calculate it correctly with the same assumptions and the same logic, the difference would be very small. So going from a very good business case, 20% invest, 50% increase in net income, it left to 5% of of net income. So it was really not worth doing it. And it increased a lot of risk and a lot of work. And I went to the CEO and said, I'm sorry, this is all bullshit You you have to you have to cancel the project and said, well, you know, we told the board now for months and we can't come up now, two weeks before the final decision and tell them it's all wrong. So they went ahead and they did the investment. And two years later it turned out that, well, the numbers weren't what they had expected.

[00:04:15] Host: Paul Barnhurst: That is a really bad one. And it's unfortunate you weren't there a little earlier before they'd gone to the board. And it's unfortunate that they weren't willing to go back to the board and say, look, this isn't the idea we thought it was. We ran the numbers. There were some errors, but nobody wants to look bad. But at the end of the day, it's like, okay, look bad at the beginning and save the company money or look bad at the end. You know, I would much prefer just owning it up front. It feels like the better way to handle that. But what was the key takeaway from that experience for you? What what did that teach you going through that model and that whole experience?

[00:04:49] Guest: Gilbert Hangartner : It again shows that that understanding the question and and thinking thoroughly about the question in the beginning is much more important than making a complicated model going to all the details. I mean, they really calculate. I always I mean, the first sign seeing a bad model is if the amounts are in dollars and cents. Okay. They calculate everything to the cent and that's not the point. You should not seek precision. You should really seek to answer the question. In this case it was is it A or B? Should we invest. Should we not invest. And then you have two to build a model that gives confidence in giving you the information to make the good decision and not having something complicated, something precise. That's not the point. So understanding the question and think, how can I build a model that reliably answers this question?

[00:05:43] Host: Paul Barnhurst: I love how you said that reliably answers the question. And then also, you know, one of the terms I've often heard is the false idea that increased precision increases accuracy. Now. Like going to the sense like you don't need to. Forecasting every line at a detailed level doesn't make you more accurate. It usually makes you less accurate. You know, knowing your question and focusing on the big picture is so important. I appreciate you sharing that. Can you tell our audience about your background, kind of a little bit of your career story and how you ended up where you're at today?

[00:06:16] Guest: Gilbert Hangartner : That's a crazy story. I started in science. I did chemistry and physics and and I mean, physics is all about modeling, so. So I built crazy models, quantum chemistry with electrons and atoms and so on. So I was always very puzzled by having a problem and not knowing how to solve it and thinking about the problem and, and then go from there and then from from there. Later in my career, I came to a to an energy company. And there we had obviously technical risks. So it was always, well, we don't know how to handle this. Gilbert can you take a look at that. And. And so I came really from the technical side to do modeling of physical processes, of investments, of infrastructure stuff. And then all the more it connected to, to science, because knowing what your risks you have always then goes to, to, to money. How should I invest to, to to reduce the risk. How much would it cost if my plant goes offline? So it goes all back to money. And then I realized having to present my results to boards and to finance the guys, I realized that you can apply the same principle for a from a physical model to a financial model. It's just the problem. And and and modeling the question and this I think this this modeling part and understanding that the model is not the reality. It's a difference between reality and the model. And this difference doesn't harm you just have to know what is important, which behavior you want to make And the model should. Should, as we said before, should answer your question and not to try to be the reality.

[00:07:59] Host: Paul Barnhurst: I like it, really try to answer your question. So I have a question and I think we know the answer. But you started your degree in physics today. You do a lot of financial and business models. It sounds like you had a role where they kind of had you start doing that. Did you find you liked it and wanted to continue to do that, or was there a specific moment when you said, hey, I really want to be more of a modeler than focusing on kind of that physics and chemistry side. Like, how did that transition come about?

[00:08:27] Guest: Gilbert Hangartner : It was just interesting. It's such a creative work for me. For me, making a model is like for others, maybe doing a painting or writing a song. It's a kind of of a creative act. And each time I did that, I liked that, and it was very rewarding. And I have seen that you can really bring a benefit to the company. People like them because you can come up with with insights that didn't have this one thing. And the other thing I discovered when I was starting to move from from the technical modeling more to the financial modeling, that a good model can bridge a gap, because often in companies you have different world, different, interest zones, and especially between technical people and financial people, there is often not that much communication going on. And I really learned that if you build a good model, you can take everything that's important to one guy and his assumptions into the model from the technical guy and to the financial guy, and make them agree on their inputs. And then you you have a systematic method to, to to get to the results. And then they believe in the results. And I often had the situation where finance wanted to do a and technical wanted to B to B b. And in the end, thanks to my model, they could talk to each other and they understood each other's arguments and and they found a common solution which was backed up by the entire company. So? So a good model is a tool to think. A good model is a tool to communicate mainly. And it's not all at all about the numbers.

[00:10:01] Host: Paul Barnhurst: I really, like you said a good model is to think good model is communicate, and we'll definitely dig more into that. But one thing I really liked is you said you love the creative process. So I'm just curious. Your take is modeling more of an art or a science? Do you have an opinion on that?

[00:10:17] Guest: Gilbert Hangartner : It's an art.

[00:10:19] Host: Paul Barnhurst: It's an art

[00:10:19] Guest: Gilbert Hangartner: Definitely.

[00:10:20] Guest: Gilbert Hangartner: I don't know, maybe I'm too stupid or maybe I don't know the right people.

[00:10:25] Host: Paul Barnhurst: There's not a right answer to this.

[00:10:26] Guest: Gilbert Hangartner : I cannot think that you can really learn this or have a systematic process. It's a creation. It's really like writing a piece of of art or creating a piece of art.

[00:10:38] Host: Paul Barnhurst: I like it, I figured that's what you say, but I just kind of wanted to get your take. You know, some people think of it more of a science. Some think of it more of an art, some are in between. And so, you know, a lot of different opinions. And I think it's a little bit of both, but definitely is a big part of art to it, no question. In the in the creative, I just worry sometimes when people don't follow a little bit of science and the structure. Right. But that's a different story. When you and I chatted and you've already hinted at this quite a bit, we talked quite a bit before we met here about the importance of making sure you understand the question before building the model, why is it so important that you really understand the question and what you're trying to solve before building the model?

[00:11:22] Guest: Gilbert Hangartner : When we agree that that the model can't be a complete exact reality, then you always make some simplifications and there are some simplifications that hurts and others don't. And if you if you don't understand what is the finite goal that the ultimate goal of the model, you cannot choose the right simplifications. You cannot make it a reactive thing. Very often people think on a deterministic equilibrium point okay. They know their business and they say, well, this is like it has ever been. And we just calculate this. And I want maybe to know if I move ten centimeters to the right or ten centimeters to the left, what happens. But this is not especially when you're going to risk management and things. Then you have to to to to have big movements. What happens if Covid happens? What happens if Ukrainian war happens? What happens to my system if the energy prices are not 5% higher, but if they're times ten, okay, so you must really make a model that acts more or less correctly if you make big movements on your drivers. I mean, if you just start and do anything, then then you have a model that moves in all directions. So you have really to understand what is constant and what will stay and what can move, and how are these interactions and are they interactions can I for I mean, you can make a linear extrapolation.

[00:12:45] Guest: Gilbert Hangartner : And if this happens that the price changes and I will produce the double, but you can't. So you have really to understand what is the capacity? Where can you shrink, where can you expand. And you really have to understand how the business functions. And the trouble is, when you come to a company, often you talk to specialists and they know 5% or 10% of the company, but you very rarely find people that understand how this little thing on this edge of the company interacts with something else, somewhere completely in another part of the company. But this has to be in a model. If you want to make a model, it has to be an end to end model which connects all the pieces of the company. So you have to talk to all the people and always try to get to this higher level to, to to have the overview of the company to make a model that in, in this big picture works the right way.

[00:13:37] Host: Paul Barnhurst: And so it sounds like if I'm hearing you right, I mean, a big part of it is you really got to understand the business and the right people to talk to in the business. And so how do you ensure your you're kind of reaching the right people, especially if you're working on a project. Maybe you're not, you know, super familiar with the industry. You're new to the company. How do you make sure you're asking the right problems? And you know, when you've really defined the problem to ensure you're able to build that end to end model? How do you go about that, making sure that you've kind of covered everything because it's hard to know what you don't know, so to speak.

[00:14:07] Guest: Gilbert Hangartner : Don't be afraid to appear stupid. I always say, I'm sorry, this is too complicated for me. I didn't understand, and very often, you know, I'm in a meeting with three, 4 or 5 guys of the company, and one of the guys explains, well, you know, it's very easy. It's like this and this and this and this. And I said, I'm sorry, maybe I'm stupid, but I didn't understand. Can you explain me this in an easy way? And then the four other people after the meeting tell me, oh, that's the first time that I understood this. So even in the company, people are afraid to understand and everybody is a specialist and nobody wants to to show that he has no clue.

[00:14:46] Guest: Gilbert Hangartner : About how it is working. And often, you know, I'm trying to all this complex stuff to reduce it to the bare minimum. You know, what is the essence? What is the very, you know, all details apart. What is A plus B equals C, what's what's the basic equation. And I'm digging as long as I have it. And if he can't explain it in a simple words then then I'm not satisfied. And only when I'm there. And then in the end it gets very simple. And once it gets simple, then I'm sure that I have understood.

[00:15:16] Host: Paul Barnhurst: I really like that. So basically keep asking questions till it feels like you can explain it in a simple way. Yeah, it's like the whole I think Reddit has a site in other places where you hear explain it to me like I'm five. Yeah, right. You know how you explain it to a little kid? Yeah. Because if you explain it in simple terms, it's going to be much easier to understand. No reason to use big words, but I, I love the just keep asking questions. I had someone on a show that said, one of the best signs of a good CFO is they keep asking. They ask a lot of questions. So I think there's some truth to that. In a modeler, don't be afraid to keep asking until you're comfortable. Otherwise, you never know if something you're modeling is really that important, or if you understood the other implications, your assumptions. It's much easier to make a mistake.

[00:16:07] Guest: Gilbert Hangartner : And as long as you aren't so complicated that you can't even understand it, it will be too complicated to model you will. You will be lost. You will model to a precision which is not worth doing it. And the most questions are rather simple. And the goal is to to make it simple.

[00:16:24] Host: Paul Barnhurst: Yeah, I've always said, and I'd love your thoughts on this. One of my favorite quotes I use it a lot in training is simple, is hard. Complex is easy. It's often easier to build something that's complex. What's your thoughts on that?

[00:16:39] Guest: Gilbert Hangartner : I couldn't agree more.

[00:16:41] Host: Paul Barnhurst: That's what I figured you'd say just from the way you're explaining it, right? You really know you. You really know you understand something when you have to explain it to others, and you have to make it simple enough so they'll understand it. If they don't understand it, there's probably a question of how well you understand it. Not always. Sometimes you're just using big words. But I know for me, training people when they get it and I'm like, alright, I really know this, this subject. So I want to move on and talk a little bit about risk, because I know when you and I chatted, we talked quite a bit about risk. I know it's a big part of what you're doing. Big part of your work. First, let's start with what tools do you use to model risk? Because I know if you're doing statistical modeling, that can be a real challenge in Excel. So if you used add ins, do you use a different tool? How do you go about modeling risk, especially if you're doing any kind of Monte Carlo or other statistical methods, which I'm sure coming from a physics chemistry background, you probably have a very strong math in there around risk modeling.

[00:17:38] Guest: Gilbert Hangartner : There is a very big battle battle, about statistics and and simulation, especially with one client I have, they have a very big a lot of people working on very good statistical models, and they are afraid of simulation. I'm completely against using, statistics for risk management because statistics would assume that, you know, the result. And normally a normal person, a simple person doesn't know the result. And that's the advantage of Monte Carlo methods. You just build easy bits one by one, and you let the simulation figure it out. What what then the statistics is and the statistics is not the input but it's the result. So that's that's the first first thing, which is very complicated. And often people are very afraid of it because they think it's complicated. And that's not true. Simulation is used because it's so simple. And you should always make it simple and you shouldn't be afraid. Oh, I don't know the distribution. I don't know the probabilities. And so it doesn't matter if you understand the problem right, it will be very easy. Just formulate it. Very stupid. Make the most simple assumption and it would always be good enough. So what tools do I use for Monte Carlo? I did it in Excel. I did it in Excel using asterisk, which I liked quite a bit for a time, and then people didn't want to buy this add in, so I did it in Excel with a little VBA. It's possible you can do you can do quite, quite a lot of Monte Carlo simulation just in Excel. That's maybe not a good tool, but it's possible because it's so easy. You can you can do it in Excel. Now I'm using it in Quantrix. So I built a little plugin, very stupid little plugin to extend Quantrix to be able to do Monte Carlo simulation. But there are obviously other tools. Goldsim or real, real simulation tools. But for the normal business model, modeling, it's not it's not worth it. Doesn't matter. You can use anything you want. It's the simple.

[00:19:41] Guest: Gilbert Hangartner : Monte Carlo is the simple part. You know, if you have a business model, understanding the business is the hard part. And doing the Monte Carlo and the risk on it is the easy part.

[00:19:51] Host: Paul Barnhurst: What advice would you offer if you have someone listening? They're like, I haven't done Monte Carlo. Do you have a resource you'd recommend they go to, or a way to get comfortable on learning how Monte Carlo simulations work?

[00:20:02] Guest: Gilbert Hangartner: Take the ISIS or a deck of cards and and and play and try to model this game afterwards. Start with simple questions and go. Go until you really understand it.

[00:20:15] Host: Paul Barnhurst: I like it, so I need to get a deck of cards. I think I got one back there. We can play cards because I might need to understand it better. So basically just starting to understand the whole idea of risk. But any like as far as setting it up, is there any math stuff they need to know of how to do a monte Carlo simulation? Do you recommend kind of reading about it if they're not familiar with the concept at all? Not not so much the idea of simulation, but just how to structure one is there. Like you need to know certain statistics or anything like that. Like is there any different beyond, you know, kind of your typical modeling for risk that you need to understand?

[00:20:51] Guest: Gilbert Hangartner : No, obviously.

[00:20:52] Guest: Gilbert Hangartner : There there is a lot of theory and, and a lot of a lot of statistics, but you don't really need most of that stuff. You really need the basic thing. Okay. I have a random variable, a dice, and I throw the dice. I mean, just do the basic exercise, take two dice, throw them and write down the numbers and make the statistics out of it. And if you really understand this, then you have understood everything. And then go from there and and and do a budget little company you know the, the, the, the, the revenue, you throw the dice and the cost, you throw the dice and then you add it together and once you have you did that and you, you, you get the, the distribution of of the net income. Then you're done. Then you have understood what what simulation means to to financial modeling. It's not more complicated than that, really.

[00:21:47] Host: Paul Barnhurst: Like the way you put that right. If you take a dice, we all know what six sided or whatever it is, you roll it, you got 12 different, you got six, you got six, you got, you know, 12. Whatever the outcomes are, you roll it each time you get your different numbers and you kind of figure out what the probability is going to be, and then you're so you're just running those simulations and figuring out the probability and what that looks like. So you have an idea of all right I think I'm going to do 5 million, but my range looks like 3 to 8 and it skews toward the eight or it skews toward the three. Right. Isn't that kind of the thinking. So you have an idea to say there's really if I think five is where I'm going to end up, there's probably about a 60% chance that I end in that range.

[00:22:26] Guest: Gilbert Hangartner : Don't even think about probabilities. I mean, it's okay, just just throw the dice.

[00:22:32] Host: Paul Barnhurst: I Like it. I might have to do that on the next show. Bring some dice and I'll throw them.

[00:22:37] Guest: Gilbert Hangartner : I always bring some dice when people. When I'm teaching a course on Monte Carlo. Monte Carlo simulation. Or when I want to convince people, you know, they say, well, let's make the model simple, let's make it deterministic. And I say, well, if you make it deterministic, it's wrong. Yeah, but Monte Carlo is complicated. So then I bring them some dice and then we do a little game and , then they understand it's not more complicated. The only thing that is complicated, I must be honest. There's one thing which really bothers people. The calculation is straightforward, but you get a stupid result. You don't get one result, but you get a lot of results. And this is where people have problems with because they're used to accuracy. They want to say, my net revenue is X million point seven $0.75. Okay. And if the $0.75 or $0.76, then they have a problem because they believe in this number. But once you accept I mean, take your last year's budget and compare it to what really happened. Take your budget. You you made in 20 before Covid and take the result you got the year after. I mean, it's nonsense. The budget has no no connection to what happens in reality. And when you accept that your planning is wrong anyway, then you can make the next step and accept. I'm doing a model and I'm not getting one number, but I getting some kind of a distribution. I get an uncertain result, most probably here a little bit up to there can be very worth. I get something okay. It's about that. And this is the only thing which is difficult to accept. You don't get an exact number, but numbers are anyway wrong.

[00:24:22] Host: Paul Barnhurst: FP&A guy here. And as you know, I am very passionate about financial modeling and the Financial Modeling Institute's mission. I have been a huge fan of the FMI for years, and I was super excited when they decided to sponsor the Financial Modelers Corner. I recently completed the Advanced Financial Modeler certification and loved the entire experience. It was top notch from start to finish. I am a better modeler today for having completed the certification. I strongly believe every modeler needs to demonstrate they are a qualified financial modeler, and one of the best ways to do that is through the FMI program. Earning the accreditation will demonstrate to your current and future employers that you are serious about financial modeling. What are you waiting for? Visit www.fminstitute.com/podcast and use Code podcast to save 15% when you enroll in an accreditation today.

[00:25:27] Host: Paul Barnhurst: Yeah, as I've always said, if I could forecast the right number, I would have invested in the stock market and be sitting on a beach somewhere. Not , building models. Because you're right. Anytime you rely on an individual number, it's never going to be right. Or having a range and understanding kind of where that range falls.

[00:25:48] Host: Paul Barnhurst: Like you said, being able to see that distribution gives you a comfort level to say, okay, we think we will be between here and here. That risk is acceptable. And yeah, you may take the midpoint and say, okay, that's the goal of where we want to be. But if you have the understanding that there's a range around that and that that that's just a point, not really that you're not going to hit. I mean, nobody ever hits the exact number, at least any complicated model. Maybe something super simple. But as you know, in general you're just you're it's estimates. So I, I agree with you definitely an area I need to get better. I've played a little bit with Monte Carlo, but I never really used it in my career, which I think is a common challenge. Why do you see? You see most people don't use it for their further complicated. In your experience, what percentage of companies and people are modeling do you think are actually using Monte Carlo? Do you have any fill on that?

[00:26:43] Guest: Gilbert Hangartner : Nobody.

[00:26:44] Host: Paul Barnhurst: Very low. Interesting. I mean, I've seen it in a few areas.

[00:26:49] Guest: Gilbert Hangartner : Most people are doing quantitative risk analyzer using statistical methods, and they're not all of them, but very often they get the wrong results.

[00:26:59] Guest: Gilbert Hangartner : Because it's too complicated and because you're basically knowing the result before, and then you're doing the statistics about it, and then you have some nice looking graphs. But if you're doing Monte Carlo modeling, you're doing the other way around. You don't know the result, but you know what happens in the real world. And you put that to the model and the model explains you, then what will be the result? And maybe I'm wrong, but I know very few decisions really been taken more in technical domain But in the financial business decisions, not that much.

[00:27:37] Host: Paul Barnhurst: I would agree with you, especially in the financial. I think there's some other areas that use more, but I've seen at least in corporate finance, it's rarely used there. I think there may be some, you know, risk project modeling and some areas where it gets used. But I would agree with you.

[00:27:53] Guest: Gilbert Hangartner : Project risk. Yes. Project is often , and I don't understand why because it's so easy and it brings so much benefit.

[00:28:02] Host: Paul Barnhurst: Like I can tell you. In fact, in my career, I never used Monte Carlo.

[00:28:07] Guest: Gilbert Hangartner : I could use it.

[00:28:07] Guest: Gilbert Hangartner : A little demo model together once. When you have time.

[00:28:11] Host: Paul Barnhurst: I have to do that. It'd be good for me. So I'll take you up on that sometime. We'll do a little demo model. That'd be fun. We'll, when I get back from vacation, I'll reach out.

[00:28:21] Guest: Gilbert Hangartner : In two hours. We have the first model.

[00:28:23] Host: Paul Barnhurst: All right. Sounds good. I'll. We'll schedule that. Guests will know coming in the future. A demo model for your Monte Carlo. All right, so I want to move on to a little bit. I know you spent a lot of time excel in your career. You still use Excel some, but recently you were introduced to Quantrix and I know you're a big fan of Quantrix. You really liked it for modeling. You mentioned you even built a little Monte Carlo simulation. What were the benefits you were seeing in Quantrix? Why do you prefer that over modeling in Excel?

[00:28:53] Guest: Gilbert Hangartner : It has two features which are crucial crucial to modeling which Excel doesn't have. The first is Multi-dimensionality. It's just stupid having columns and rows. I mean, the world is not two dimensional. Never. No problem. I mean, every problem has five, ten, 15 dimensions, okay? So you cannot do a two dimensional model. And if you want to model it in Excel, you have to do a lot of work to, you know, to cut your your problem in slices and put it on, on, on this flat paper. So this is the first multi-dimensionality. Definitely. And second is flexibility and scalability. I mean, in Quantrix I first solved the problem very easy.

[00:29:40] Guest: Gilbert Hangartner : With two examples or three. I make everything works right, the formulas work right, the structure works right, and then I pump in 100,000 10,000 items. Doesn't matter and it will all be the same and it will not be an error. There will be no formula to be adopted. So the scalability, the security, the stability of the model is just another word. And I was very, very funny because I built a rather good model and stable model which was used for production, a simulation model in Excel. And I showed this to somebody when when I worked with Quantic Dream and I did, I created a little VBA to create this Multidimensionality, and that created a formal parser so that I could write the real language formula into Excel which then were translated into the cell reference formula of Excel. So I basically built my little Quantrix in Excel without knowing that Quantrix exists. So these things are really and again, Quantrix is not a good modeling tool. Context is a good business, , finance modeling tool, but not Monte Carlo. It can't do that. It's not very good on this. So I added this. But again, the business model is the complicated part. And this is so easy, so clean in Quantrix. And then just the Monte Carlo stuff is easy peasy to add on top of it.

[00:31:06] Host: Paul Barnhurst: Got it.

[00:31:06] Host: Paul Barnhurst: So it sounds like one of the things you really appreciate. And you mentioned a couple there, but the multi-dimensional modeling is a really big one. And I would say that's one of the biggest strengths of when you model outside of tools like Excel. Is that multi-dimensional? Whether it's quantrix causal, there are others out there, quite a few that I can list that allow the multi-dimensional modeling. That is one of the biggest limitations I love Excel. I use it for just about everything, but I also recognize that there's definitely some trade offs you're making when you choose to use it, and you've liked it so much. You mentioned that your youngest child, you taught them Quantrix versus Excel. Talk about that for a minute. I found that very interesting.

[00:31:50] Guest: Gilbert Hangartner : I have four child, so the older three are a little bit older and the younger is ten years younger. So I always try to teach them excel. You know I teach you excel. So you have to learn something for the world and don't even if it's a stupid little calculation you have to do it correctly, because in all your life you will be using Excel. That was what I always told my kids. And now my youngest. I was working with quantum and I just told tell the teacher quantrix and so everything she has to calculate something or doing some little example for her math classes or something. She always uses quantrix. So she's 11 now, but she started using quantum F9 with nine not news.

[00:32:29] Host: Paul Barnhurst: I love it that's great. Thank you for sharing that. And she'll be the quanterix expert when she goes to college.

[00:32:38] Guest: Gilbert Hangartner : I hope so.

[00:32:40] Host: Paul Barnhurst: All right, so we're going to come back to Excel for a minute, because toward the end, we like to ask this question of people just for fun within Excel. Do you have a favorite shortcut you like? Is there one that you can't live without if you had to pick one?

[00:32:53] Guest: Gilbert Hangartner : I'm very old fashioned mouse guy. I grew up with Macintosh, so I'm very tied to my mouse. But the most important thing somebody once told me, control arrow down to go, especially when you have sheets of other people, which has 10,000 lines. This is great. So, I mean, instead of scrolling down ten minutes and it builds up screen after screen. So this this is really wow. That saves 50% of the time.

[00:33:21] Host: Paul Barnhurst: Yes.

[00:33:21] Host: Paul Barnhurst: Those control arrows the end the home. If you're sitting there scrolling more than a second. There's a better way to do it, and I've been guilty of it. There's times I start scrolling. It's like, okay, what's the column that doesn't have a bunch of blanks? So I can get to the end here really quick? And how do I get this where I'm not? But yeah. Control the control down arrow the right. Left. All those are fabulous.

[00:33:44] Guest: Gilbert Hangartner : I think navigation takes the most time in Excel. And if you master navigation how to get from one point to the other. How to jump to the to the sheet where the data is and come back without getting lost. I mean, if you manage that then you have really half of the.

[00:34:00] Host: Paul Barnhurst: I think that's huge.

[00:34:01] Host: Paul Barnhurst: Like I know control left bracket. If you're in a formula and you want to go where it's referencing, I think it's alt F5 to go back to where you were. There's lots of little things like that that along with those control arrows, it could just save you a ton of time not even learning any of the others of performing certain functions, but just starting with increasing your navigation speed around a spreadsheet.

[00:34:22] Guest: Gilbert Hangartner : Navigation. Yeah.

[00:34:23] Guest: Gilbert Hangartner : I think navigation, because Excel is so difficult to get the whole picture. It's so unstructured and normally it's so big. So getting navigating around and don't lose your overview. That's that's key to to working efficiently with Excel.

[00:34:37] Host: Paul Barnhurst: Yeah.

[00:34:38] Host: Paul Barnhurst: And that's that's the greatest strength and weakness. What you mentioned is unstructured right. Excel gives you pretty much unlimited flexibility in the sense you can build whatever you want. It's just a blank canvas. At the same time, you don't have the structure. You get a lot of flexibility. But with other tools you often get structure and some benefits that, when you learn them, can make a lot of things easier. But you almost always give up at least a little bit of flexibility because you have a database on the end, you're all of a sudden using structure. And that's the biggest thing I ask. I have people ask me all the time, well, I want a tool that's just as flexible as Excel. Like if all you care about is the flexibility, then just stay in the spreadsheet. You're going to trade off some of that flexibility for a lot of other things that may make your life a lot easier, depending on what you're doing. And you have to decide if those benefits make sense. That's usually kind of how I frame it with people.

[00:35:29] Guest: Gilbert Hangartner : I'm completely agree. Completely agree. I'm just not sure if flexibility is really what you want because sorry to say, it's good for people who are afraid to think about their problem. And if you have quantrix is really annoying because you have to think.

[00:35:47] Guest: Gilbert Hangartner : And it forces you to really make a clean, clear structure. But this clean, clear structure then helps you not only because you're more efficient, but also you have a better understanding of your problem and you can build anything in Excel, which doesn't make any sense.

[00:36:04] Guest: Gilbert Hangartner : And you wouldn't realize, but in Quantrix or in any other tool which is more structured, you have to think about the structure. You have to make decisions and think. Then things that are possible are not possible because you defined it this way and this really forces you. And I think that's a good thing. It forces you to be clearer clear and to have a clear structure, clear data, and you know what you're doing.

[00:36:29] Host: Paul Barnhurst: I think we're going to I'm going to contact all the multi-dimensional tools. So see if we can make you the spokesman. You definitely you have it down to what you see as the advantages. And it's clear you really appreciate those. And I like that. I love a strong opinion and coming with your reason. You know, I'd say most of the people we have and most people obviously model and excel, I'm no exception. And that's their tool of choice. And getting them to look at other tools can be difficult. I've looked at a lot of tools and there's definitely some benefits. Like I said, one of the biggest things I like, whether it's Quantrix or dozens of others I can think of, is one of the biggest benefits, is that multi-dimensional modeling. I am with you. That's a huge thing. And definitely there has to be more structure. And it's a good question. Flexibility is what you.

[00:37:17] Guest: Gilbert Hangartner : You can fool yourself to do structured modeling in Excel.

[00:37:21] Host: Paul Barnhurst: Yes. 

[00:37:21] Guest: Gilbert Hangartner : But excel doesn't force you. You have to force you yourself.

[00:37:25] Host: Paul Barnhurst: Correct. And that's why there's so many guides and so much discipline is, you know, like investment banking. One of the first things they teach is standards. And here's how you model, because they're trying to force a certain discipline. And I never learned that earlier in career. My my first few models were terrible because it's like I know what he taught me. I'm just trying to figure it out, and you're just throwing it all in the paper, and then you get done and you're like, what have I built? This makes no sense. Whereas if you start with something that forces you for structure from the beginning, there is definitely some benefit. And so everybody has to decide where is that trade off, what makes the most sense? Obviously Excel is extremely inexpensive. We can do just about anything in it. That's probably one of my favorite things about it. But you just have to recognize, like anything, it comes with trade offs. So I love how you shared that there. So I want to ask one more question. Then we're going to move into our rapid fire section, which is kind of our fun section where you have to choose a side, and then at the end you can elaborate So what is the one thing if you had to list one thing that you've learned during your career that's helped you the most? What is it?

[00:38:31] Guest: Gilbert Hangartner : I don't know.

[00:38:32] Guest: Gilbert Hangartner : Not being afraid, not being afraid, asking questions again, that's I think. And the confidence that everything that's important can be easily modeled for everything. It's a need. There is an easy answer. There is a nice little neat formula. If you understand the problem, it's always possible. Don't be afraid.

[00:38:55] Host: Paul Barnhurst: I love that, so basically, don't be afraid. Ask questions. Keep digging till you're able to get to where you can answer it in a simple way. I'm going to have to do some more digging on some things. Now, does that apply to relationships? Because I can't understand women at all. All right. We'll move into our rapid fire section. And this is going to be related to Excel. I know you use Quantrix some but we'll run through this for Excel. And this is you have to pick a side. You can't say it depends. And at the end, if you want to elaborate on 1 or 2 of your answers, you can. So kind of make it fun. It's supposed to go quick, you know. Just a quick one side or the other, ten 15 seconds at most. So in your models, should you use circular or no circular references?

[00:39:36] Guest: Gilbert Hangartner : No circular. 

[00:39:38] Host: Paul Barnhurst: VBA or no VBA?

[00:39:41] Guest: Gilbert Hangartner : Yes, but not for calculation, only for graphics user interface. This is the kind of stuff, but not you should not not never anything calculate in VBA.

[00:39:51] Host: Paul Barnhurst: Okay, I've heard that before. You're not the first to have that opinion. Do you think the model horizontal. So basically write lots of sheets or vertical where you kind of build all your schedules for the most part. On one sheet you have a preference between horizontal or vertical.

[00:40:05] Guest: Gilbert Hangartner : The question doesn't matter.

[00:40:07] Guest: Gilbert Hangartner : Structure and display something completely different. You have to separate that even in Excel. If you don't do that, you're lost. Don't build your model on the layout.

[00:40:18] Host: Paul Barnhurst: Dynamic arrays in your model. Yes or no?

[00:40:20] Guest: Gilbert Hangartner : Yes yes.

[00:40:22] Host: Paul Barnhurst: External workbook links. Yes or no?

[00:40:24] Guest: Gilbert Hangartner : No no no.

[00:40:26] Host: Paul Barnhurst: Oh, I usually get multiple no's on that one named ranges. Yes or no?

[00:40:31] Guest: Gilbert Hangartner : Yes, absolutely. That's the key to make an Excel model work.

[00:40:36] Host: Paul Barnhurst: I like it. Formal standards. Do you follow them for your modeling? Do you like fast or smart or any of those others?

[00:40:44] Guest: Gilbert Hangartner : No.

[00:40:44] Host: Paul Barnhurst: And that's fine. You're not alone on that. Do you think Excel will ever die? Do you think it's with us forever?

[00:40:50] Guest: Gilbert Hangartner : It will die. Absolutely. And that's what I want to elaborate on afterwards, please.

[00:40:56] Host: Paul Barnhurst: All right.

[00:40:56] Host: Paul Barnhurst: Great. We'll look forward to that. Will AI build models for us in the future?

[00:41:01] Guest: Gilbert Hangartner : No, it will help. But it will not. It will not. Definitely not.

[00:41:06] Host: Paul Barnhurst: All right.

[00:41:07] Guest: Gilbert Hangartner : I mean, if it's the last thing that will be replaced by AI. If I can do that, then everything else is replaced before.

[00:41:14] Host: Paul Barnhurst: We're in trouble. If it's doing that is what you're saying. Do you think you should use sheet cell sell protection in your models?

[00:41:22] Guest: Gilbert Hangartner : No.

[00:41:23] Host: Paul Barnhurst: All right. Do you believe financial models are the number one corporate decision making tool?

[00:41:30] Guest: Gilbert Hangartner : I'm sorry. No.

[00:41:31] Host: Paul Barnhurst: What is.

[00:41:33] Guest: Gilbert Hangartner : How do you call this? I think in English you say, napkin. In German we say the thing, the carton thing under the beer glass. The corporate decisions are taken by gut or by very stupid calculation on a napkin. And people are afraid of models, so they don't use them.

[00:41:52] Host: Paul Barnhurst: So you think back of the napkin gut feel. You don't think most decisions are really made with data and a model?

[00:42:01] Guest: Gilbert Hangartner : People are afraid, even for a lot of clients. They always have a tendency. They make the decision. They tell me what the decision is, and then they tell me, can you please make a model that confirms that my decision is right?

[00:42:13] Host: Paul Barnhurst: I'm laughing because I know what you're talking about.

[00:42:17] Guest: Gilbert Hangartner : Then there is the process. The education starts and the successful processes end with a company which, two years after they do it the other way around. They model first and take the decision afterwards, and projects end with the company wants to take the decision like they always took. And then I say, well then it's not worth that. I'm wasting my time.

[00:42:39] Host: Paul Barnhurst: If they're just looking for the model to confirm what they've already decided, then they're just playing kind of corporate politics in a sense, versus really trying to make good decisions. And we've all seen it.

[00:42:52] Guest: Gilbert Hangartner : An open mind and the research attitude. I don't know what the good decision is and I want to find it out. And then it's worth to build a model.

[00:43:00] Host: Paul Barnhurst: I'm fully with you. You really have to you need to question and you need to be open. Got a problem? You need to be open to figure out what the answer is, what the right answer is, or the best answer, or at least the risks around the different options. Sometimes there may not. Often there's not a best, but at least having an idea of the risk being open minded, because there will clearly be times that it will show you whatever you think is a good idea is a bad idea.

[00:43:25] Guest: Gilbert Hangartner : I mean, you can still take the decision you want, but take please, an informed decision. Seeing all options, seeing the advantages and disadvantages of the options and understand what your decision is about. And then you can still I mean, you're still the boss. It's not the model that will take the decision for you, but the model makes you understand and it makes the decision transparent. The problem is, not everyone wants a transparent decision.

[00:43:53] Host: Paul Barnhurst: Yep. Good point. And I have one more question. Then we'll go back to the Excel every day. Because I know you wanted to elaborate on that one. Do you have a favorite lookup function you like to use in Excel like Vlookup index match Xlookup choose something else. Is there one you tend to tend to use some ifs? Okay, yeah, there's definitely some that use that one. That's a good one.

[00:44:14] Guest: Gilbert Hangartner : I mean, normally I separate the model in two parts calculating. 

[00:44:19] Guest: Gilbert Hangartner : Pushing everything in a flat database, you know, value and attributes, and then making the analysis section, which is a dashboard that just uses some ifs and grabs the right results out of the database. So, I mean, you can build a database in Excel if you're structured enough.

[00:44:35] Host: Paul Barnhurst: Oh yeah. No question. You can. I agree with that.

[00:44:38] Guest: Gilbert Hangartner : And then some ifs works nicely.

[00:44:41] Host: Paul Barnhurst: Yeah. So this is a fabulous formula especially for, financial modeling. It's a it's a favorite. So back to Excel because you know we got to start and end there. What's elaborate on, when it's going to die or why you think it's going to die?

[00:44:56] Guest: Gilbert Hangartner : My, year of birth is 70. Okay, so my father was a carpenter, and he had a little business, two people, and he had this famous big paper book where he wrote everything down. Okay? Every transaction you wrote in this book the pencil and made little notes to it. And in the end of the year, there was the bookkeeping to be made for the taxes. So he gave the book to me and said, when I was six years old, seven years old, Gilbert, can you please do the, the, the, the profit and loss statement for me? So I took the calculator and calculated it everything and wrote it down and calculate it again. And the trouble was, you know, each time you type the thing, the numbers are gone. So this was a stupid way. And then some years later, I went to school and I went to first Apple Computers, Macintosh with Multiplan, which is like a little bit more stupid. And I discovered this and it was, wow, a new world, because you can write it down and you see the numbers and you have the formula. And for the first month and the second month, you can use the same formula. You can copy paste. It's so nice. It's so clean.

[00:46:06] Guest: Gilbert Hangartner : It's not the same thing with another tool. It it opens a different world. And I think if you never did the profit and loss statement of an entire company by hand and then move to to multiplan. You don't understand this step. And for me, going from Excel to real modeling tool, it's the same step. It's another world. It's other possibilities. You can do the same thing. You can do it in Excel, like you can do it by hand, but it opens up. So more other questions and other possibilities. And I think the times where you have just, you know, to add up numbers to get the sum of these numbers, there are gone. We are living in a much more complex world. We have data analytics. We have scenarios. We have data we want to cross with. We have risks. And this is another world and it needs another world of tools. And I mean, I always say Excel is good for writing a shopping list and everything that's more complicated than a shopping list. You shouldn't do with Excel. You can, but you really you really wasting your time and you're passing about A side of a new universe, you could open your mind much more, in going to other tools.

[00:47:20] Host: Paul Barnhurst: Love it. I love that we get a contrarian view. Most our guests love Excel. I would definitely say I go beyond the shopping list, but I love getting to hear different people's opinions and it will be fun to watch because we're definitely in a changing world where technology continues to evolve and we'll we'll watch it unfold. It's exciting. So I appreciate you taking the time to join me, and we'll go ahead. And I think this is a good spot to end and wrap up. So just one last question for you. If our audience wants to learn more about you, get in touch with you. What's the best way for them to learn more about you?

[00:47:56] Guest: Gilbert Hangartner : Drop me a note on LinkedIn or email and let's chat. Ten, ten minutes chat. It's it's worth much more than private face to face chat. It's what I prefer. Perfect.

[00:48:10] Host: Paul Barnhurst: All right, well, we'll put your LinkedIn information in the show notes and I'll have to reach out at you sometime, and maybe we can do some kind of little demo on Monte Carlo. That'd be fun. But thank you so much for joining me. I've really enjoyed it. Have fun on the island this weekend and happy boating.

[00:48:27] Guest: Gilbert Hangartner : Thank you very much, Paul. Very interesting question. I really like to be on the show. Thank you. All the best. Bye bye.

[00:48:34] Host: Paul Barnhurst: Financial Modelers Corner was brought to you by the Financial Modeling Institute. This year. I completed the Advanced Financial Modeler certification and it made me a better financial modeling. What are you waiting for? Visit FMI at www.fminstitute.com/podcast and use Code podcast to save 15% when you enroll in one of the accreditations today.