The Power of Data Automation in Financial Models and Tools for Corporate Success with Paul Medici

Nice thing about financial modeling is that there are standard finance principles. The buildup for revenue could be completely different, or the build up for cost could be completely different.

When you first started building models, what was the hardest part of getting comfortable with models in areas where you didn't feel comfortable about the business?

It's very difficult to ascribe a value to building a financial model. Reviewing models is a whole skill in and of itself. Those types of issues are very easy to solve. Dynamic arrays where you only have to build in the one formula in the one cell and not copy it across. So you're saving a lot of so dynamic arrays. They are kind of a relatively new implementation in Excel over the past few years.

Will Excel ever die?

No. We've seen tons of bad models and they all have one thing in common, and that is.

Welcome to Financial Modelers Corner where we discuss the art and science of financial modeling with your host, Paul Barnhurst. Financial Modeler's Corner is sponsored by Financial Modeling Institute.

Foreign.

Welcome to Financial Modelers Corner. I am your host Paul Barnhurst. This is a podcast where we talk all about the art and science of financial modeling with distinguished financial modelers from around the globe. The Financial Modelers Corner podcast is brought to you by the Financial Modeling Institute. FMI offers the most respected accreditations in financial modeling and that is why I completed the Advanced Financial Modeler. I'm thrilled to welcome to the show this week Paul Medici. Paul, welcome to the show.

Thank you Paul. It's a pleasure being here and I'm looking forward to our discussions.

Thrilled to have you here. Excited to get to chat with you. So Paul is the founder and CEO of his own company, Medici Financial Modeling. He has over a decade of experience building bespoke financial models and data automation tools. He's done that for corporate clients across the globe including US, Canada and Europe in a multitude of industries. He previously worked at an industry leading financial modeling training company where he gained valuable experience building a wide range of financial models for companies. He also taught financial modeling and advanced Excel courses at the country's leading investment banks. During his tenure at the firm, he played a key role in building up its financial modeling consulting practice. From inception, he's also worked at companies including capital markets and equity research. He's covered mining equities focused on a variety of commodities and he received his MBA from the University of Toronto and he holds a Master of Science in Geological Science and Geological Engineering. That's a fun background. You know we're going to start with our famous question. You probably know what's coming? Tell me about that worst financial model you've ever seen.

Yeah, no, as you can imagine, Paul, and you know, watching your podcast, I've heard some horror stories of different financial models as being the worst. And I'd say, you know, in this line of work, you know, when we're building, you know, models for corporations, they're only coming to us for one reason, and that is because they either don't have a model or their model. They have no confidence in their model. And so, as you can imagine, we've seen tons of a ton of bad models. And they all have one thing in common, and that is there's usually adhering to financial modeling standards. So the file is not user friendly, it's very difficult to use, it's very difficult to update, it's very time consuming and things of that sort. So that kind of plagues all bad models we see. But the one in particular that has three issues, that's one. The second one was, and keep in mind, this is a large public company. They were trying to, you know, they were forecasting out their internal process in terms of how much they were supposed to pay suppliers, and they asked us to review the model. They had suspicions that the numbers may not be correct. And as we looked into it, there were formulaic errors and they were actually overpaying their suppliers for a number of years. And so from a materialistic standpoint, that's the worst. But to add to that third beacon, the. The other issue was it's actually home to probably one of the worst formulas as well. And so what they were trying to do was they were trying to look up different items on different worksheets. And, and as you can imagine, you know, there's probably 40, 50. This was about 10 years ago, 40, 50 worksheets. And they were trying to look up items on these 40, 50 worksheets. And uniquely, they were using nested if statements. And so we looked at the formula bar and it was full. And then so we looked down, went to the keyboard control shift u expand the formula bar a bit. On my laptop, it expands, you know, between three to four or five lines, still full. So then we did what, you know, no financial model is supposed to do, and we picked up the mouse and then we grabbed the formula bar, brought it down, and the formula just continued. And so we looked at it. Prior to this, we had no idea how many nested ifs you could build. Apparently that number 64. And I have to say they came close. But after trying to deal with what they were trying to figure out. We actually got that formula down to a couple of lines. So, you know, everyone knows the index function. There's two different forms. There's the array form that everyone uses. The little known form, the reference form is the beautiful formula that we put in. We, you know, the different worksheets that they were alluding to, we made them all the same grid, like the same grid and we used the index reference form. And so we were able to pick out exactly what we wanted from any of those different sections or areas. And so with that said, one of the worst models, but one of my favorite models, because we were able to take just a monster of a formula and, and blend it down to just a couple lines.

So, so they covered the three bad things. No good design, correct, wrong. Like materially wrong answer and complex formulas.

Yes.

Cover it. So yeah, that's the worst. At least if they wouldn't have been wrong. You're like, okay, I can live with it, I'll fix it, we'll clean it up and make it run better. But it's worst when it's complex, it's messy and it's wrong. Which usually they go together. Right. It's just a question of how wrong.

No, exactly. I would agree. The materialistic standpoint is absolutely the worst. But, and it all depends on, on the scope as well. You know, most models, you know, all models have a variability in error, but obviously we try to minimize that. But when it's blatant and it's extremely material, that's obviously a big issue.

So yeah, it's like, if you've ever heard the quote by George Box is one I really like. He says all models are wrong, some are useful.

I like that. I might, I might have to steal that from you, Paul.

Oh, I use it all the time. I, he came up with it. I saw it online one time and like, this is great, this is going in some material because I think it, it sums it up. Well, the goal is to be useful. Odds are you're going to be wrong somewhere. So you started your career as an exploration geologist and now you're doing financial modeling. You worked in several different mining companies. How did that switch happen?

Yeah, no, also it's, that's a great question. And you know, I get this all the time because they are not related at all. And so, you know, working in exploration geology, especially mining, you tend to be in remote areas and you know, you'll fly out for three, four weeks, work in a remote area and then fly back home for one or two weeks. And so, you know, I worked a lot in northern Canada and specifically the one project I was on, it was, it was a gold project. And the company I worked for had delineated a resource or reserve to the point where a larger company was interested. And so they actually made a bid, they acquired us and, you know, management flew out to our, to the little village we were in and did a speech and talked to us about how things would change. And I think it was that moment where I was just enthralled with what had happened. I had so many questions. My direct supervisor couldn't answer any of it because I was in a geology role. And most of my questions were finance related. Mainly how did they come up with a value for this project and how did the deal work and what's going to happen with the human resources in each company and things of that sort. Why would they purchase us? Things like that strategy as well. And so I quickly realized that I was probably in the wrong discipline. And so next logical step was to work on the finance side of the mining industry. And so I networked my way into the capital markets and I worked in equity research where I was covering, you know, mining stocks or mining equities and various commodities. And that was kind of my first foray into financial modeling itself because I would never had to use it before. And so I learned a lot on the job there. You know, having done that for a couple of years, I wanted to go back to school, get a formal business degree. And it was there that I met a training firm. They came in and they would teach financial modeling courses. I would say after the, the first course was in an Excel course. And I learned so much in that eight hours that had I known that in my prior equity research role, I would have saved so much time. I wouldn't have been up till 2, 3 in the morning, you know, updating models. I would have been able to apply those skills immediately. And rather than fidgeting with my model all the time, I would have had more time to kind of digest what the model was saying and, you know, provide more recommendations and things like that. Focus more on the business rather than the model. The famous saying. And so since that first Excel course, I just, I fell in love with Excel. You know, as nerdy as that sounds, maybe that's a little bit of the computer science that, you know, is interesting as well. But Excel, you know, very similar to that. And so since then I took all the courses that were offered as, you know, you know, most business schools don't offer financial modeling courses. So to bridge that gap, typically private companies come in and teach. So I took them up on all their offerings. If I could think of something I needed, I built it in Excel during those two years in the mba, and then I liked it so much, I interned with them and then upon graduation, worked with them as well. And that's kind of how the whole financial modeling aspect started. And I would say that the first and foremost, getting to that region, probably there were two takeaways. One was just to keep an open mind of what you want to do, because like I said, they're complete opposite ends of the spectrum. And two, to take risks. You know, go back to school. If you want to try a different industry, ask those questions that are. You're thinking about, don't hold it in, things like that.

I love how you said, take risk, do new things, go back to school. I know you went from the mining to doing equity research to really focusing on the modeling and the training and Excel. And along the way, in addition to, you know, doing that MBA and that master's, you started the CFA program and then you decided, hey, maybe this isn't for me. I'm going to guess because you did level one but didn't finish the others. I did similar. I did level one and never did level two or three. So I'm curious, was it just as you realized, hey, I want to do more modeling, not equity, so this doesn't apply, or how did that kind of happen?

Yeah, no, that's. That's a great question. While you hit the nail on the head. So I started the c. The. The CFA program prior to getting in equity research. That was kind of the. The intermediary to get me to the interview stage because as you can imagine, I had no finance background. And so, so taking the cfa, it made logical sense. And then while I was in equity research, just given the situation I was in and where I thought my career was headed, and it's definitely not a. Or decision, but for me, I thought, you know what? I'll go do the MBA rather than continue the cfa. And then I did the mba and I just never really looked back. And so not to say that I would never do it, because it's very, very useful designation, but I just wanted more of a broader sense of business studies. I specialized in finance, of course, which. The CFA specialty, but perhaps it's on the bucket list. But. Or perhaps not. But, but there's a lot. There are a lot of people in, in our situation as well. And for you know, a myriad of reasons and things of that sort, so.

Totally agree. And I'm at the point now where I would be surprised if I ever did it. So I totally 100 get where you're coming from. I enjoyed level one, but there's only so much time in the day, and we all got to figure out, you know, what programs and what certifications make the most sense because there's more out there than we could ever do.

Oh, absolutely. Absolutely. You said, you said it perfectly.

So I, I'm curious, when you first started building models, when you really got into models, especially for sectors outside mining, you started doing more sectors you weren't familiar with, what was the hardest part of getting comfortable with models in areas where you didn't feel comfortable about the business?

Yeah, no. Thinking back, you know, the nice thing about financial modeling is that there's. There are standard finance principles. And so, you know, for, say we're building a three financial statement model, well, it all hooks up the same way, and it all hooks into supporting schedules that for the most part are. Are similar. So if you think of capex and depreciation, there's principles, you know, income tax, various pieces of debt, standardization in terms of how we build that, you know, equity schedules, similar thing as well. Really where I find even now, the difference in building those types of models between different industries is the revenue buildup and the cost buildup. And so that's really what sets the models apart. And it's, it's amazing because even you could have two competitors in the same region in the same industry, in the same country, and the buildup for revenue could be completely different or the buildup for cost could be completely different. And so starting off, you know, kind of getting outside of the shell of mining, that was my first. My first challenge was the revenue and cost buildup. The nice thing about financial modeling, and probably something that I find is typically not mentioned a lot, is that when we think about financial modeling, especially when I used to, you know, going out and teaching, the first thing everyone wants to do is get on the laptop, open Excel, and start building the model or using a template and building the model. And, you know, after years of doing this and a lot of great mentors along the way, you realize that the first, you know, if you do that, you'll be doing that multiple times because you'll build it wrong the first time, the second time, and the third time. And so, you know, the initial part of the process is you have a meeting and you take notes, you open up word, you you know, write down on pen and paper, which, you know, I haven't done that for ages, but you open up word and you, you, you, you make some notes and, and you really learn sometimes along with management of how to build up revenue and costs. Because a lot of times we're rebuilding models for corporations. It's, it's kind of a reset. They, you know, in a typical corporation you're not always thinking about the model. It's a time to actually sit down, set aside time within the day and reflect on how do we actually want to build this up. So while I was learning how to build it up, they were also kind of relearning how to build it as well. You know, they obviously come with much more knowledge but you know, after doing that a few times you become a lot more comfortable, you know, going into new situations with new industries and things of that sort. But yeah, revenue and costs, where a lot of differentiation happens for sure.

Yeah. And I really like something you said there. One realizing it, it starts with opening up the pen and paper and kind of discovery with them versus if I just jump into the model because like I said, revenue and costs are going to be different. Depreciation, taxes, capex, they're going to be very similar, different industry, maybe a little bit of a different instrument, you know, variable fix, whatever. But they're pretty standard where when you get into revenue, particularly cost, I think there's a little more standardization. But revenue models, everyone can be so different, especially in planning and budgeting that side of it. It's amazing how different those models be from company to company.

No, absolutely. And, and even, not even just the buildup, but even the level of detail as well. And, and you know, as, as humans, our first, our, our first reaction is to model out in as much detail as possible. I find, especially with, especially with clients and, and you know, I, I do the same thing when I model things out. I, I, I tend to start with as much detail as possible. But that's not, not always the best approach. It's, it's, you need to balance the detail with, in moderation with realistically, how much more accurate are you getting with that detail? Is it relevant and things like that. So I find it, you know, initially as you go down the financial modeling path, you're very detail oriented, very, very detailed. As detailed as we can be, revenue can be, you know, 5,000 rows. And then as you move along the obstacles in your career, you realize it's just not necessary. And so, you know, now revenue can't be four Lines, you know, it's not just going to be price times volume equals revenue. There has to be some form of detail in there as well. But just need to do a nice balance. And I find when speaking about that with clients, that's where we spend a lot of time, is on the revenue buildup for many reasons, but that's typically what we do.

Makes complete sense. And I'm with you on that. Is finding that right level of balance. Four lines isn't enough. If you got 5,000, you might want to rethink your model. It's probably somewhere in between that and I would hope a little closer to four than 5,000, but couple hundred. Yeah. And it does a little bit depend on the industry, but they, it can get complex for sure. As I've, I heard one person say, keep it as simple as you can because your business partners will make it more complex. You don't need to, you know, because like, can you add this? Can you add that? Well, we'd like to understand this piece. And before you know it, you went from the hundred lines you put in to 400 or whatever.

Oh yeah, yeah. And then, and it's, it's, it's interesting you bring that up because that's, that's typically how models break. Because you have one person that built the model, they leave, someone takes over the model. Doesn't necessarily like something changes it up and then management asks for something else. And again, you know, completely respectable. Because, you know, when you're working for a corporation, your job is not to make the most efficient and user friendly model. Your job is to get an answer and an answer as quick as possible. And so, you know, these things just evolve over time. And after 10, 15 years, I kind of call them, you know, Frankenstein models because they have a little bit of everything from everywhere. And then that's usually when we get a knock or a knock on the door or a phone call saying, hey, look, you know, we don't trust our models at all anymore. It used to be a beautiful piece of work 15 years ago and now, you know, there's 40 tabs, 40 worksheets. We only use two or we only use five. You know, we don't know what's going on. Do we renovate the model or do we just rebuild from scratch? And, and I would say probably nine times out of ten it ends up being a rebuild from scratch type of operation.

Almost always it's the easier way. Rarely do you want to salvage something, especially when you just don't know the logic. They usually don't follow good design principles. Like when you said Frankenstein, I often use the term Franken models.

Okay, I like that. I like that too.

That's what I'll call them a lot. I'm like, I built my share of Franken models because they're just together and a little bit of Frankenstein, a little bit of everything else. And you're just like, what, what do I have on my hands here?

I was just saying you just got to go back to basics and, and start from scratch.

Very true. Sometimes. So I'm curious, do you have a favorite industry you like to model? Is there an industry, if you could pick to model any industry tomorrow, is there one that you really enjoy or you would choose?

So I, I a little bit biased, but I, I do like when the mining mandates come in just because it takes me back to my youth a little bit. And you know, very, very used to modeling those, those, those models out and, and you know, different projects. There's a lot of variability in the mining industry as well because you have commodity, different commodity, different type of mining, is it exploration, is it development, is it production? And so there's a lot of variability there. To be honest. I like modeling. I also like the challenge of modeling new industries and things of that sort. But what I really like is in terms of what type of financial model, if we were to go that route as well. I really enjoy building the, you know, the typical corporate model, the model that says and does everything. So the three financial statements, the supporting schedules, you know, adding in some modules, obviously a, a wonderful summary output that dynamically updates with a click of a button, but adding some modules as well, you know, tracking, you know, forecasts versus actuals over a time period and seeing, you know, for management's perspective, how is, how is cash doing, how you know, versus what we forecast last quarter or last year and then selfishly for my purposes, how well is the model actually forecasting? It's a nice, it's a nice benchmark to say how is the model telling the story? Is it accurate? And it's funny, in equity research it's always forward looking. Very rarely do you ever go back and say how close was I on my eps, my earnings per share, you know, cash flow per share and things like that. So I like the budgeted hose. They are not cookie cutter. They are, they are company specific and software, you know, software that will solve the problem for you. It's usually fairly expensive and you know, could be difficult to update and things of that sort. And then traditionally people's go to method is to build it in Excel, but because it's not a traditional financial model, there's usually a skill set gap of, you know, how do we actually build this so that it looks and feels like Excel or it feels like Excel but looks like custom software. And so I love those builds as well because they're just outside of the box. There's a lot more planning, there's a lot more due diligence in terms of, you know, discussion with management. What do you actually need in those projects? They're never identical, they're always different.

So sure, anytime you're building something bespoke, so sounds like, you know, mining is kind of brings you back to your youth. The restatement, you just love that, love being able to see the full operational but really enjoy within that when you get those bespoke where you're really doing something custom.

Oh yeah.

Because it creates more of a challenge of how to figure it out, how to do it versus just a very standard. I want to use the term vanilla, but we'll use that vanilla three statement model, so to speak.

Yeah. And you can really, you really see the data automation tools, you actually, you really see the value that it provides for the most part. Because, you know, it's very difficult to ascribe a value to building a financial model. Right. If a company doesn't have one, they need it. But if they have one that's, you know, not optimal, how do you provide, how do you ascribe a value to rebuild it? Right. It's the lifelong question that, you know, that we've been trying to tackle. But with these data automation tools, you know, they're usually processes that occur over and over and over. And so, you know, the one that is top of mind, that was just phenomenal. You know, again, a large public corporation and they had, they had to perform this task about a thousand times, like import data, manipulate the data and then have an engine that was calculating it automatically and then outputting it and then transporting that into a PDF. First of all, the tool wasn't built as efficient as it could be. So to do that it would take, you know, six, seven, eight hours to do one of those. So you can ascribe that times a thousand times, that's 8,000 hours, right. You get someone to rebuild the model and it only takes a couple minutes per. Then you can kind of ascribe a value in terms, okay, we saved 7,500 hours or whatnot. And so it's a lot easier to ascribe values to those types of models and I find it very rewarding as well because you physically see how you help the client in a very short term perspective as well.

FP and a guy here. And as you know, I am very passionate about financial modeling and, 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.

You start to think, you kind of go back to basics and you think okay, actually why am I doing this? Because I have a feeling that I'm likely going to be asked that question. And so you kind of start putting, you can take yourself out of your shoes and put yourselves in the shoes or the perspective of the participants of the course and you know, what kind of questions should could they ask. And so then you're kind of boiling everything down to basics and you're kind of relearning everything from scratch again, but just from a different perspective. And so I, I found that as I taught, I started asking myself 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's program. Earning the accreditation will demonstrate maybe the key takeaway from, from teaching that how did it help you in your career?

In a couple ways. You know, there's that old adage that says, you know, you don't truly, truly know anything unless you teach it. Part of that is true. You think you know, you know all there is to know about a certain subject. But then when you start teaching it, you start to think, you kind of go back to basics and you think, okay, actually why am I doing this? Because I have a feeling that I'm likely going to be asked that question. And so you kind of start putting, you can take yourself out of your shoes and put yourselves in the shoes or the perspective of the participants of the course and you know, what kind of questions should they could they ask? And so then you're kind of boiling everything down to basics and you're kind of relearning everything from scratch again, but just from a different perspective. And so I found that as I taught, I started asking myself more detailed questions. Why am I doing this? Mainly because I thought I would probably get asked that. Right. And things that we kind of take for granted the longer our careers are. And so I enjoyed that aspect in terms of, I think it made me a better financial modeler in terms of just thinking of why. But also, you know, it also brought me back to the days of equity research where, you know, honestly, that, that first day of equity research may have been the first time I opened Excel, because I never had to prior to that. And so I was learning, you know, the capital markets, you know, the role and Excel at the same time. And I just remember thinking, wow, like I, I, it would have been great to have been taught that. And, and so that's kind of my way of, you know, helping out people, not kind of have to go down that road as well. Because if you can save a couple hours a day and put out more meaningful work, you know, that does wonders to the mind.

Yeah. I wish I knew when I started my career what I know today about Excel. I'm like, I saved myself so much time. I think a lot of us are that way. Especially if you didn't come from a background where you started in investment banking and you were trained now kind of from day one. I know you did a lot of investment banking training. And I was always a little jealous when I come in and see all the skills and shortcuts and everything. And here I am just hacking away at Excel.

Yeah. And that kind of goes back to what we were mentioning before that, that disconnect between, you know, what, what we learn in, in university and, or college and, you know, what the demands are on the job. And, you know, we're starting to see more financial modeling courses in house universities. But a big role still is, or still is that those external private corporations that are coming in to kind of fill, bridge the gap between education and kind of industry.

It's like if you've ever seen that curve, and I know if you're listening to this, this is a bad radio, but if you're watching the video, you'll see there's the curve, there's little comic that's kind of funny and it has a kind of bell curve. And it starts with elementary school math, you know, fractions, algebra, you get calculus, differential calculus, whatever, all the different things. And then the curve goes all the way down to the other side and shows workplace. You see Excel and it's back there at level one, you know, kind of like you learned all these different mathings in school, but all you really needed was Excel at that, you know, third grade level, so to speak. And sometimes that's how it feels when you talk about that disconnect.

Oh yeah, well, you know, it's, it's, it's amazing because, you know, I would say, you know, the majority of, of or not the majority, but you know, a lot of people that use Excel, first of all, you just don't know what you don't know. That's the big thing, right? And so, yeah, you know, with Excel, there's, there are so many functions and tools, especially now, you know, they're new, they're rolling out new items all the time, it seems. New functions, powerful functions that, you know, if you only know how to do something one way, you'll figure out how to do it that one way. But yep, once you have the toolbox and you, you have like five or six different methods, you can kind of choose the most efficient way. But kind of before all that, you know, a lot of, and I think we were all, we all fell suspect to this at some point, likely within our first time we opened Excel thinking and using Excel kind of as like a advanced calculator, that, that's kind of what it appears to be. But then you kind of get under the hood and you realize that this, this is a powerful machine. And that's just at the Excel level. You could go down to the, you know, the VBA level and it becomes, you know, a whole computer program. And so, but again, you don't know what you don't know. And you know, if the majority of your time is just spending in Excel filling out forms or doing simple calculations, that's all, you know what Excel is. And that kind of ties in with the education part where, you know, you go to an Excel course and you kind of, you just realize how much there is. And even, you know, a typical Excel course, in eight hours you'll learn, you know, maybe the top 10 functions or formulas that can go a long way.

Yeah, it's amazing how much you can do with just 10, 10 formulas. In Excel, most models don't require a whole lot more than probably 10 formulas. And so one of the things you did, you know, in addition to the training is I know you worked for fmi, the Financial Modeling Institute. You graded some of those exams. People building their three statement models talk a little bit about what that was like.

Yeah, FMI being, you know, the, the industry standard in terms of financial modeling certifications. I, I worked with Them from day one when, when it was just a local accreditation program here, here in Canada and, and, you know, was able to help out from content creation, kind of, kind of the entire pipeline. Content creation, content reviewing, content testing, you know, proctoring of exams, things of that sort. And then grading. Of course, each task in that pipeline was, was unique in and of itself, but the grading was fun in terms of. You really get an idea of. Because we all, we all have our own. All of us sometimes have trouble balancing the balance sheet. Right. More often than not, earlier on in our careers. But there's always something comes up, but usually it's the. It's a similar issue. Right. Maybe you mislink to a different row or you have a negative sign instead of a positive. They're easy to figure out when you're grading someone else's exam. It's a different thought process of who built the exam. So there are errors that you may not have made, that you may not be looking for. And so you develop a skill set in terms of solving how and why balance sheets aren't balancing. And so, you know, back. If you, if you asked me back in my, you know, mining days if I would find that interesting, I, I probably would have asked you, what is that off the top of my head. But, you know, for people like us, that's, that's a great skill set to have. You know, I remember in equity research, you know, there's tight deadlines. You're update, you're updating a quarterly model because earnings just came out and you need to forecast out next year's earnings. Well, if you kind of did some surgery on the model and now you're not balanced, you really only have until midnight, maybe 1am, 2am to get that solved and write the report so that the editorial team can put out the release at 7am Right. So there's that tight deadline. And so you really learn different, all kinds of different mistakes that can be had trying to balance models, but more importantly, how to fix it in a very quick and efficient manner.

Yes, I remember taking that test and when I got done, my model didn't balance. And how do I fix this in short, short time frame? Fortunately, I figured out the mistake I made and got it all to balance. But I could totally see grading them. That would be a really good learning on balance because that's a very common issue, right. You get all done and you're like, all right, where did I mess up? Why does this not equal that? And the last thing you do is plug it, right?

Yeah. The Famous spot always used to be I retained earnings used to be the famous spot or.

Yes.

Even in some models people would just hide rows and just add like a 1.37528 and then it would magically balance or they would put. Or the best would be. There's always new ways of figuring out. Some, some would put the cell out, you know, and sell CD 45,000 and you know, link to it there. And you know, reviewing models is a whole skill in and of itself and those, those types of issues are very easy to spot.

One of my favorites, someone told me one time is he reviewed a model in the balance sheet. You know, the, the check said the balance sheet balance. They had written the formula to say if you know, assets equals liabilities plus owner's equity, okay. If it does not equal assets plus liability or equity, okay. So no matter what, it always registered to oa.

Okay.

And the guy was telling me the balance sheet had, I think it was a two billion dollar out of balance when he, he dug through it just.

A little bit material there. But again, you know, creative and unique ways of doing things that it takes a, a career to see them, you know, but when you're grading exams all the time, you get to see them all the time, which is unique from that perspective.

I bet any advice you'd offer if we have someone listening and they're thinking of taking the fmi.

Yeah. So if I think back, you know, if you're taking level one, the AFM and you're building that, you know, three statement financial model, first firstly would be, you know, going through doing a lot of. The FMI has a lot of great, you know, practice material and things of that sort to kind of prep you for the exam. So the first, first thing would be understand, just understanding how the financial statements link from a theoretical perspective and a build perspective and then how the supporting schedules all link up to those financial statements. And I would say that that has to be the hardest part. That's, that's a secret sauce of trying to figure this out. And then once you're able to do that, the next step is timing. Because if you can build that in eight hours, that's amazing, but you need to build it in four. So you just, you just have to increase your speed a little bit. And with that a lot of people are looking for, you know, the, the quick and dirty answer, the quick and seamless answer of how to get there the fastest as possible. But like many things, um, it's just try, like just practice, practice, practice and, and you know, a part of that is the infamous keyboard shortcuts. That saves a lot of time. You know, like anything, there's an upfront investment, and it can be overwhelming. But really thinking about it, there's probably 10, 15, 20 keyboard shortcuts. And so if you're learning one or two a week, you know, that's not bad at all. And to be honest, it's not a hassle to learn because if you're doing the same thing 80 times in the day, it's just a Google search away of what the shortcut is. And so you just kind of get that in, and that becomes part of your routine and part of your muscle memory. That saves a lot of time. Right. So not only, you know, building quickly and, you know, from a, you know, efficiency standpoint, but also a mechanical standpoint in terms of how you're actually building. So it would just be for.

Visit www.fminstitute.com backslash podcast and use code podcast to save 15% when you enroll in an accreditation today. Yeah, got it. Makes a lot of sense. You get the kind of the reward of being able to calculate the value prescribed. You see the difference it makes. It's always rewarding whatever the project is. Anytime you take something and reduce it by 50, 60, 30, 90, whatever the number is. But when you see a material difference, where somebody's like, oh, wow, you mean I can press a button now versus spending my whole day doing this?

Exactly. Yeah. No, it's. It's. It's nice to have those every once in a while.

So you did a lot of teaching. You taught Excel, you taught modeling.

Well, and. And to be honest, it's not a hassle to learn because if you're doing the same thing 80 times in the day, it's just a Google search away of what the shortcut is. And so you just kind of get that in and. And that becomes part of your routine and part of your muscle memory. That saves a lot of time. Right. So not only. Not only, you know, building quickly and, you know, from a, you know, efficiency standpoint, but also a mechanical standpoint in terms of how you're actually building. So it would just be practice, practice, practice. But it's kind of two things. One, the material, understanding the material, and there's a lot of resources for that. The second one is the timing, and that's really on just practice, practice, practice.

Makes a lot of sense. Understanding theory, being able to really build up those schedules, and then just learning to get quicker.

Absolutely.

Speaking of quicker, we all know shortcuts like you said, help a lot. You have a favorite Excel shortcut.

Oh, I love this question. So, you know, watching your podcast, I, I have to say it a lot. Practice, practice, practice. But it's kind of two things. One, the material, understanding the material, and there's a lot of resources for that. The second one is the timing, and that's really on just practice, practice, practice.

Makes a lot of sense. Understanding theory, being able to really build up those schedules, and then just learning to get quicker.

Absolutely.

Speaking of quicker, we all know shortcuts, like you said, help a lot. You have a favorite Excel shortcut.

All the questions. This has to be the most difficult question in terms of how to answer it, because how do you answer this? There's, there's a couple ways you can answer that. What, what is your shortcut based on frequency of use? Or what is your favorite shortcut based on, you know, uniqueness? For me, I go off of time saving. Time saving is a big one. And so for me, I would go with control backslash. I think it's an underrated, underrated shortcut. And of course that is, you know, if you have your typical model build, you know, say five years, but it's all quarterly, okay, you have 20, 20 columns. How do you review the model? And so a lot of times there are individual reviews of each cell, which, you know, could take a while. But of course, as we all know, control backslash, you just have to check the first cell to the left, highlight the, the row. Control backslash lets you know if all the formulas are consistent. If they're not consistent, lets you know where the issue is and so can save a lot of time. So much like with dynamic arrays, where, you know, you only have to build in the one formula in the one cell and not copy it across. So you're saving a lot of time in this aspect because again, you know, dynamic arrays are great, but a lot of the model, almost entirely all the models I receive from clients do not exhibit dynamic arrays. It's the traditional, traditional Excel formulas where you're building an Excel and so the utilization of, you know, formula checking on that, you have to use control backslash. And so it saves a lot of time. And probably second to that would be control shift backslash, where you want to make sure formulas or formulas are consistent, you know, from top to bottom. And so typically what I'll do is I'll just highlight the entire grid if the formulas are supposed to be consistent and well built. Control backslash. Control shift backslash. And then we just you know, reviewed 40 cells, 50 cells, 80 cells and things like that. So from a time saving perspective, that would be my favorite.

I can tell someone's reviewed a few models.

Yeah, no, it's, you know, not only just reviewing your own, but reviewing. The hardest thing is reviewing someone else. Different process of how it's built and especially if you know there's a different set of financial modeling standards that are being used or not used, that. That makes it a little bit challenging as well.

For sure. All right, we're coming up on one of my favorite sections, the rapid Fire, how this works. I'm sure you've listened. So you know it. You don't get to say it depends. You have to pick a side at the end. If there's one or two you're passionate about, you're welcome to elaborate on why you pick the site because, you know, we all know these are ones where people have strong opinions. So usually you can go either way on most of these. And so you get to pick a yes or no. And then at the end we'll let you elaborate on one or two. So we're going to just quickly go through these circular or no circular references.

I'll go with yes on circularity.

Okay. VBA or no? Vba?

No. Vba.

Horizontal or vertical model? Vertical dynamic arrays in your model. Yes or no?

No.

External workbook links? Yes or no?

Absolutely not.

That's a pretty common answer. Ranges yes or no?

No. No.

Do you follow a formal standards board like Smart or Fast or some of those when building a model?

Yes.

Will Excel ever die?

No.

Will AI build the models for us?

Yes.

Use of sheet cell protection in your models? Yes or no?

Yes.

Do you believe financial models are the number one corporate decision making?

Yes.

And then what's your favorite lookup function? Choose Vlookup Index match, xlookup or something else.

Index match.

All right, that's pretty common. Index match or index X match.

Now I'd still go with index match. Still go with index match.

It works in most situations.

Oh yeah, for sure.

All right, which one would you like to elaborate on? You can pick one or two there to share a little more context since I realize these are all nuanced.

So dynamic arrays, they are phenomenal, obviously a kind of a relatively new implementation in Excel over the past few years and quite powerful. Wonderful to use. I use them all the time in my personal. Personal models, personal tools. They saved me a lot of time because prior to the dynamic arrays, I was building things without. With the traditional Excel model, the Excel functions that were doing the same thing. But you would need a lot of supporting columns or supporting areas or combining a lot of functions together to basically do exactly what dynamic arrays can do. But when it comes to client models, it's a little different because one, it all depends on the level of comfort that the client has with Excel formulas. So that's, that's hurdle number one. And then hurdle number two is also, you know, because clients will typically be updating their model, what version of Excel they're using. And so like anything as a technology kind of rolls out, it just takes a little bit of time to implement. So, you know, if we were to have this discussion in, you know, five years, by that time, I think, you know, the tide could possibly turn and maybe more people in a corporate setting are using the dynamic arrays a lot more. And so that no could turn into a yes.

Got it. Now it makes a lot of sense and I've had a lot of people share that thought. You know, you have the others of, yes, let's just all use it, we'll figure out the consequences later. And obviously that's not going to work in every situation. So I think there's, I love dynamic arrays. Do I think most of us are ready to fully model with them? No, because there are some limitations. You got to use lambda or some other things to truly do fully dynamic. So I'd say most people are, Aren't there? I'm not there. But I've seen some models that have been fully dynamic and it's, it is exciting, no question.

Oh yeah, no, I remember one of the first projects, one of the first client mandates. So early on in my career, we were building out, we were building out an M and a model and we were looking at different time frames. And so the entire model was built using, we're going back 10 years now using traditional Excel formulas to the point where all the timing periodicity changed, so quarterly to monthly, combined with, you know, instead of looking out seven years, it was looking out five years, you know, when the acquisition would be occurring. And so the entire model was not just the one worship, the entire model was dynamic. And now, of course, you could use sequence for that and then a whole bunch of dynamic arrays and in a fifth of the time. Absolutely. So it's quite interesting. When I saw that, you know, when, when I saw all this new technology coming out, it brought me back to that very first model that I built and how much easier it would be to do it with that.

I bet you're like, where was this 10 years ago, we do that. Like I use unique all the time now. And it's like, how did I do it without this? Or sort some of these functions that are so nice, not even necessarily care whether they're dynamic or not. Just using them.

Yeah, no, yeah. Like I said, you need, you need the helper columns. And then, you know, how do you make it a big best practice model with helper columns and things like that and you're embedding formulas within formulas and then trying to audit. That can be a little hairy sometimes. And so no, they're, they're very powerful. It's just, I think without those, it's just a matter of time. Like anything matter of time. Eventually the technology will come around to most people and, and it'll become a standardized thing.

I agree. At some point it'll be the standard for modeling. It's going to be interesting to watch it develop. So if you could offer one piece of advice to our listeners to be better at financial modeling, what would be the one piece of advice you offer?

I would recommend how, how I did it would be. And it was a lot easier 10 years ago because, you know, kind of going back to something we said, practice, practice, practice. You know, it's one thing building a financial model and then you get used to it and it kind of, you kind of go on autopilot. But when you start modeling out pretty much anything and everything you can think of in Excel, like your timetable or your task scheduler or your investment portfolio or your bank account, you know, budgeting linked up to your bank account and feeding in data. When you start to think about those problems and how you would like to see that in Excel and you model it for yourself, you just get better at it. And so back in my first year of the mba, kind of when I was introduced to all this wonderful world of Excel, I started building anything and everything I could think of in Excel. Had I not done that, my financial modeling career wouldn't be where it is today. But I just did that extra in terms of I'd be home at night. I want to forecast out my personal budget. In order to do that, I need to bring in some data from my, my bank. Right. What's the best way to do that? And as you do this, you know, it's not about solving that specific problem. It's. It's more the thought process of, okay, now I'm tackling a real client, client problem. Oh, I can go back to how I did that on my personal, from, from my personal experience and things like that so, you know, 10 years ago, much easier to do because there were less apps that did that for you. In today's world, it's so, so simple to just say, okay, I have my phone. I'll go to Google Play or the Apple Store, I'll download my personal budget spreadsheet or I'll, or my personal budget app or I'll download my task scheduler on here or pay $15 a month for it. Right. But if you just sit back and say, you know what, avoid the temptation and build it in Excel, that gives you the practice. But it actually doesn't feel like practice if you enjoy it and you're learning a lot from it as well and developing your, you know, Excel critical thinking skills.

I like it.

Definitely.

Just experimenting is a great way to learn and trying new things and building them out. I've heard a few people say that, you know, do your budget or whatever it might be on your personal side and you'll learn a lot about modeling. Last question I have for you. If our audience wants to learn more about you or maybe get in touch with you, what's the best way for them to do that?

I would say probably the best way would be LinkedIn. You can just search my name, Paul Medici, and I'm probably the first person you'll see. Secondly, you know, through my, through my website as well, the corporate website medicifinancialmodeling.com read up, you can read up all about the firm, what we do, as well as contact us as well through the contact form.

Thank you, Paul. We'll definitely make sure we put your website, the Medici Financial Modeling in the show notes and really enjoyed you taking some time to chat with us and you know, enjoy the rest your evening there in Toronto. I think as we've been talking, I've seen it get. Start to get a little darker. So I know night is coming for you, but thanks for carving out some time.

Absolutely, Paul. And, and thanks for, thanks for having me. It's, it's been a pleasure and I, I thoroughly enjoyed our discussion.

Well, thank you. Appreciate it. Financial Modeler's Corner was brought to you by the Financial Modeling Institute. This year I completed the Advanced Financial Modeler certification and it made me a better financial modeler. What are you waiting for? Visit fmi@www.fminstitute.com podcast and use code podcast to save 15% when you enroll in one of the accreditations today.