Podcast

Episode: 68 |
Neil Booth:
Financial Models:
Episode
68

HOW TO THRIVE AS AN
INDEPENDENT PROFESSIONAL

Neil Booth

Financial Models

Show Notes

Our guest today is Neil Booth.

In our discussion, Neil shares how he became a deep expert in how to build a really well designed model – he followed what could be termed the Benjamin Franklin method. Neil then turned that skill into a career.

Neil also shares some modeling best practices – such as splitting up your formulas – do one step at a time – cells are cheap. We also geek out on cell styles, how to define constants, and whether you should include macros in your model.

Neil is currently working at the investment bank Houlihan Lokey where he established the firms’ Financial Modeling as a Service group.

His group offers corporate training in financial modeling best practices, and will also build the financial model for you.

If you’d like to follow up with Neil you can reach him at NBooth@HL.com.

One weekly email with bonus materials and summaries of each new episode:

Will Bachman: Hey, Neil. It is great to have you on the show.
Neil Booth: Hey, Will. Thanks so much for having me. I’m really excited.
Will Bachman: Awesome. So, we were chatting recently, and you were telling me about some of the work you’re doing helping smart folks improve their modeling skills. I just found that topic fascinating. Thanks for coming on the show to talk a little bit about it more.
Before we dive in, in this show to Excel tips and tricks, and modeling tips and tricks beyond just Excel, could you give us … Rewind a little bit … Give us a bit of your quick bio, and how you got to this stage in life, where this is what you’re doing professionally, helping people improve these things?
Neil Booth: Yeah, sure. I think it’s a valid place to start. It’s sort of a weird thing, to be an expert in such a specialized topic like financial modeling within this weird program called Excel.
Backing up, I was a banker since 2004. I worked for the city of New York, and then I worked on an infrastructure [inaudible 00:01:09] at a very large bank. And you can sort of guess by the timeline, 2006, 2007, what happened next. The financial crisis changed everything for pretty much everyone who was working at that point, including myself. And having gotten cut by the same bank the day before Leiman went bust, did make me take a reflective pause, to think through why am I doing what I’m doing. What is it about this job that really excites me.
And a few things came to mind. I really did enjoy working with smart people. I really did enjoy working in a high pressure environment. And I really liked quantitative analysis. And so, with that as a guide, the thing that everyone uses to accomplish getting answers to questions on those three topics, was the financial modeling.
And I’d also always sort of been an Excel Jockey. And went about trying to gain more knowledge, and gain more skills. And somewhere around 2013, 2014, I joined a firm called Corality. And Corality is a financial modeling consulting firm. I’d never heard of that before. So, a firm that specializes exclusively in building financial models seemed like heaven to me.
So I spent a lot of time learning the Corality methodology, and became the global head of training there. We trained over 400, 500 analysts in the [inaudible 00:02:51] banks, development companies, in the methodology of how we attack financial models. And again, to step a little bit further back, the way you attack a financial model is not all that different from the way you attack really, any problem. It’s about structure, it’s about thinking clearly.
Again, it really is sort of a neuro biological problem, as much as it is a technical issue, involving Excel. It’s an exciting thing, have to get a little existential about it to continue being excited at some points. But by and large, I love what I do. I wouldn’t be doing anything else.
Will Bachman: How did you get connected at Corality?
Neil Booth: It’s really funny, I saw their website, and was just absolutely blown away by, there’s this thing that does this. So I sent them an email, and said, “I know you’re not actually doing business in the United States yet, but if at any point you decide to do that, please give me a ring at some point.” And sure enough, I eventually became the very first employee for the firm in the US.
Will Bachman: I think that is so cool, Neil, how you didn’t apply to a job the way it posted. But you just found a company that you were passionate about, and you reached out to them and said, “Hey, if you open up an office, let me do something for you.” That was very cool.
Neil Booth: Yeah, I had to get a little … So, at the time, I was … I had a job at the time, and I was distinctly unhappy with it for a variety of reasons. But I was in heavy job search mode. I was an English and Philosophy major in undergrad, so I’ve always thought of myself as a little bit of a writer. I’d bring that skill to my intro emails, and I made some racy comparisons to fast cars and financial models in the email that I sent. And I think the guy that eventually hired me said, “Yeah, that email pretty much got you the job right there.”
Will Bachman: Wow.
Neil Booth: I patted myself on the back a little bit.
Will Bachman: That’s one to frame, then.
What does it mean to have a firm that builds financial models? You go to a typical bank, or you go to a consulting firm, and they have analysts that are doing that as part of one of a range of jobs. What does a firm like that do, who would they serve?
Neil Booth: Sort of fast forwarding to today, what I do now, is I work at a firm called Houlihan Lokey. And they’re asking themselves that same question. And I’m sort of the answer to that question. So the spot that I’m in right now is called … Houlihan Lokey’s financial modeling is a service for a business line. And we sit within the financial advisory services, or consulting, side of the bank. We do have a lot of different ways in which people attack Excel every day. And the thing that I tell folks internally, and externally, is you can write a letter, or you can send a Twitter or you can send an email. You can send a communication in pretty much any way, shape, or form possible, right. You don’t need an author to create you an email all the time, right. But if you’re talking to a very specialized audience, about a very specialized high priority, high complexity situation, it might make sense to get somebody to help you craft that in a way that attracts the most attention, or accomplishes your goals in the most efficient way possible. And that’s really what we do. Is we help people structure analyses in a very specific way to achieve a goal.
And so, we can do that for infrastructure, we can do that for corporate finance, we can do that for deal making, credit funds. A whole wide variety of folks.
Will Bachman: Awesome. So your group will both do the models for someone … I think that you also provide training.
Neil Booth: Yeah, we talk with folks about how best to structure their own analysis. And that’s one of my favorite parts of the job, is meeting people, and talking with them about their problems. We like to help people do this for themselves, because the absolute best result that I can imagine, is training somebody, and then almost losing a little bit of track of them over the course of 24, 36 months. And then finding a model in the market that has our fingerprints all over it, built by somebody else.
That is, that does happen every once in a while, one of the more gratifying parts of our job. Is to see that the process itself speaks for itself, and can be communicated efficiently through different organizations over time.
We love when that happens.
Will Bachman: So, talk to me, and talk to our listeners about … For someone who knows how to use Excel, right. Knows the basics, knows how to do pivot tables, knows how to use most of the functions and so forth, and how to do formatting. What’s the next level that you would help people get to? Talk to us about some of the tips and tricks and practices that distinguish a really well designed model from kind of a hacked together, something from someone who hasn’t been formally trained and just sort of figured out how to use Excel. And doing a decent job, but isn’t truly sort of professionalized.
Neil Booth: Sure. And again, doing this in an anonymous way, and not talking about any specific analysis helps take some of the sting out of this. But you can tell very quickly when you open up a model, how hackneyed, or how difficult it’s going to analyze, pretty quickly.
So if you open up a model, and the very first note you get is, there are external links to other data sources. Big red flag. Ding, ding, ding, ding. The next one is, once you get through that, you’ll probably get … Especially with bankers, some sort of circular reference warning. And we’ll talk through what those do, in a few minutes.
But those are two big red flags. Ideally, you never want to have your analysis in a model refer to someplace outside of it. Everything should be self-[inaudible 00:09:57]. And certainly, circular references … Excel is a uni directional software tool. Once you’ve embedded a circularity, everything that depends on the calculation within that circularity is itself broken. We want to strive as much as possible to avoid circular references.
Those are a couple really quick ways to identify bad analyses. And then, to your question about, what is a good analysis. That’s a little bit more of a nebulous question, because good analysis comes in a lot of different forms. The point of any good financial model is to have one page, where every stakeholder in the process that you’re running, be that an M&A process, be that a corporate development process, every stakeholder can get answers to all the possible questions around that deal, off of one piece of paper. That’s usually an outputs tab that’s printed up at the front of the model.
So, if example, again during an M&A process, the bank can see that the debt service [inaudible 00:11:11] ratio increases over time, on a graph, great. And the equity guys in the same room with the debt guys can see that their IRR increases over time, right. And that’s usually a good thing. When the development company sees that they’re getting their development fee paid right after financial close. Good.
These are all incentives that folks have when they come to the deal table, to ameliorate their concerns about receiving the benefit from doing the work. Helps everyone calm down a little bit, and really talk about what it is that brought them to the table in the first place. And that’s what a model is supposed to do, is generate a conversation. A pleasant conversation, not an aggrieved one, certainly. And hopefully we’re doing that through structuring an efficient one page output summary.
Now, all the stuff that goes behind that one page output summary, is the working guts of a model. And how you structure that, well, you think through first off … This is sort of a rhetorical question for you, Will. Do you know how many decisions a human brain can make in one day?
Will Bachman: I’m sorry, Neil, I’ve already made my quota.
Neil Booth: Well, you know, it’s interesting. That, there is actually a quota every day. Neuro biologists have figured out that the human brain can … With a average diet, average caloric intake, can make roughly 72,000 decisions every day.
Will Bachman: 72,000.
Neil Booth: 72,000 decisions every day. And, chances are fairly good, you’re about two thirds of the way through that right now. I know it’s probably about 2:30pm in the afternoon. Because you think about, what are decisions? Well, do I take cream with my coffee, or sugar. Do I wear the red tie, or the blue tie? Do I wear the white shirt with the red tie, or … You can sort of do the math how those decisions sort of accrue over a day.
So, if you’re wasting caloric intake, or if you’re wasting decisions in your brain, trying to decide whether or not the hard code embedded in this formula, or the three line long view look up with a twos and an index and a match is working properly, chances are good your brain is not going to be able to process that. And that’s not something that you want. So what you want, is simple formulas, right. The idea would be, two items and a formula. You got the beginning of the formula, and the end of a formula.
This, times that. This plus that. This minus that. That’s really what a simplified well-constructed financial model brings to there.
Simple financial formula structure, the format of the model is laid out [inaudible 00:14:10]. So our inputs tab is the aggregate place where everything that can be changed during the course of a model exists. And it’s organized in a way that tells the story. So if your tabs across are … You start with the construction of a plant, then you go to the operations of a plant. Then you have debt that is used to finance the plant. Your inputs tab is organized down, by those very categories. And we use cell styles in order to limit the amount of formatting issues. So, it’s really about formatting, it’s about presentation. And about organizing your formulas, and your analysis in order to tell a really good story.
Will Bachman: So let me ask you a few questions there. So the simple formulas, so take away is, don’t try to do one cell, one formula that tries to take the … Figure out where the space is, cut off the left, cut off the left, get first name and then divide that up, do a bunch of things. Just say, do each of those things, break it apart, show your work. Each sort of interaction should just be a separate row, separate cell. Just show your work.
Neil Booth: Yes. 100 percent. So we have a slide that we have during our training session. We’ve actually extracted a formula from our model audit practice, where we review people’s model sometimes, bad ones. And we’ve got a formula that’s about 15 lines long.
Will Bachman: Oh, my god.
Neil Booth: It’s a real formula. Poor guy, the story that I tel behind this formula was, his boss came … And I don’t know if this is true or not, but based off the formula, i can sort of infer a few things. The boss came on a Friday afternoon, about 5:00pm in the day. And said, “This annual model that you’ve made for me is great. Maybe you can make it monthly, and semi annual at the same time. And I’d love for you to be able to do that before Monday morning. So I’ll look forward to your analysis.” And walks out the door. Boss. Right.
And the analyst jockey cracks open a red bull, starts coding a few name [inaudible 00:16:33]. Adds a couple F’s. Roughly seven red bulls later, hits enter on the last parenthesis. The thing works, falls over on his desk, comes back on Monday morning. His boss says, “This looks great, except …” And he points about two thirds of the way through this 15 line long formula. “… How do you do this? Why did you do it this way?” And the analyst looks back and says, “I have no idea.” That’s the thing that you want to avoid, right. Everyone’s got to be able to speak the same language.
Will Bachman: Okay, so split it up. So, one step at a time, so you can audit it more easily. And then, I love this idea of really thinking about the organization to tell a story. So, not just as you randomly thought about the next step. What are the different formatting and cell styles. Talk to me about what do you mean by that.
Neil Booth: Yeah, so a cell style is, again, using the analogy of telling a story. If the inputs tab is your table of contents, each tab then, is a chapter. Within each tab, you’ve got calculation blocks. And those calculation blocks are comprised of formulas. And those are sort of the paragraphs of your story.
Well, the actual cells are the words. And the words generally can be, words can be bolded in a letter. It can be capitalized. They can be italicized, underlined. There’s a whole different ways of formatting, that we’ve all come to understand have different meanings. And cell styles are a very easy way in Excel to standardize all those meanings. So you can view mnemonically, very quickly extract meaning from a visual cell style without needing to parse what the author of that cell was trying to say.
Will Bachman: Walk me through some of the common ones that you recommend.
Neil Booth: Yeah, so when you sum everything across a row, one that we use is line summary style. Summary style is a gray box. And that gray instantly tells you, yup, this is a cell that everything to the right is being summed. Similarly, if you sum everything going up, you’d use like … You’d line subtotal style, and that’s just a solid line at the top of the box of the cell. And that says that everything again, directly above has been summed.
Which, ironically, those are some of the biggest mistakes that we see in financial models, are some rows not being run all the way across a range. And that is one of the things that can kill a deal very quickly, surprisingly. It’s the easiest thing ever, right. Make sure your sum alt equal, right. And then, quick shortcut, and you should be able to sum everything up pretty quickly. Add, subtract, move things around, and all of a sudden, your sum ranges don’t add up.
Will Bachman: Okay. What are some other ones? I’d imagine for hard coding a constant, or for a formula, or for other kind of cell styles that you suggest?
Neil Booth: Yeah, so cell styles … A lot of people spend a lot of time fiddling around with, let’s say everything from the number of decimals past the decimal point, to whether things are being represented in dollars. Maybe they’re being represented just with regular decimals style, like an accounting style. Set all that up upfront. We like two decimal places for percentages, right. And if something requires decimal places … I’m going to say, for example, you’re dealing with a number of dollars that are in the billions of dollars. Chances are good you don’t need to see two or three decimal places on billions of dollars. So use some common sense, and take those out. Because it’s just wasting space.
And then likewise, if you’re dealing with, let’s say, some sort of chemical relationship, where decimal places are very important. We’ll have some standardized thinking on how many decimal places are important to look at. Is it two? Is it three? Whatever it is, standardize it. And also, call out your units. This is really, really important, especially in project finance. If you’re trying to convert between capacity, which is given in megawatts, and output, which is given in megawatt hours. The abbreviation for megawatts is MW. The abbreviation for megawatt hours is MWH. One letter, if you’re not very careful about how you’ve labeled your line items, it’s a big difference, and can make or break a deal based on that one letter.
Everyone’s got to be singing the same song, as it comes to unit descriptions as well.
Will Bachman: You’re bringing me back to 11th grade, and dimensional analysis.
Neil Booth: Yes, yes indeed.
Will Bachman: Keep track of your units. That’s cool. So, cell styles. And I imagine you do like … I think I was taught at one point, constants that you put in there should be a certain color, and bolded perhaps. So you can know where that’s hard coded in there. Don’t put any constants in a formula, maybe.
Neil Booth: Yeah, exactly. And one best practice for constants is, we put them all in one page, called either a names page, or a constants page. So, or tech page. So tech, T-E-C-H, refers to silly stuff that everyone knows is constant. There are 365 days a year, except in a leap year in four years, right. There are 24 hours in a day, seven days a week. If you change those underlying assumptions, chances are good you’re not going to get the right answer.
So instead of taking a risk that someone’s going to enter [inaudible 00:22:49] instead of 365, you put it on the tech page, and you name the range days a year. And so, any time that it is referred to in a formula, it’s very clear to everyone who’s reading that formula, oh, okay, I get it. We’re taking number of hours, and multiplying it through by this in order to divide then by days a year. Okay, that makes sense to me.
And again, keeping your formula simple, and structured, and not hard coded as well, makes everyone much more ready to trust the model. Which at the end of the day, is the thing you’re seeking to engender across a deal.
Will Bachman: Got it, cool. Any other best practices that you see often, maybe people failing to observe?
Neil Booth: Yeah, we spend a lot of time helping folks with macros. So, it’s a topic that I get a lot of questions on. Is, I want to do this really funky thing in VBA, maybe you can help me write this really, really awesome code for a thing that does a thing. You know, as soon as people ask me that, I have to first chuckle a little bit, and then step back and go, “Okay, great. So, you want me to help you with the … ” Let’s say it’s John. John’s asking me this. “You want me to help you with the John [inaudible 00:24:15] employment plan.” Is pretty much what you’re asking me.
Because no one knows how to audit macros, right. Let’s be just completely honest. Except for a very small slice of what is already a very small slice of the American population. It’s the real tech at investment banks know how to do macros. And [inaudible 00:24:36] to them, right. I’m sure there are some really cool stuff that you can do. And I’ve seen some really cool stuff be done with macros.
End of the day, you want to keep your macros, and your code in macros as simple as possible. I’m not saying don’t use them. But they do have a very specific purpose, macros. And those are, to at least in my mind, resolve circular references. So there are, inherent in any deal model, certain things that are just crazy. Like, banks are saying, “I want you to size my fee off of two months forward debt service.” Let me think about that for a second. The debt service is a result of the revenues, which I don’t know. And you’re saying, in six months time, you want me to size your fee today, off of this unknown thing. Okay, that’s going to result in circular reference. How am I going to avoid that, Neil?
Well, again, you create a very simple macro. And all it does, is copy and paste values until such time as a delta between two values is a result of zero. And that code is three lines long, right. So it’s like, do this, copy and paste, until this delta between the two values equals zero. That’s it. There’s no reason to get any more complicated than that. You can stack those copy paste macros on top of each other using some form of optimized macro, and make them run in unison in a very seamless way.
So, we help people think through that type of stuff. And yeah, of course if you want to do fancy stuff in macros, we can help you do that. But we try to counsel folks to keep it as simple as possible.
Will Bachman: Cool. Let’s kind of go up, higher altitude, and talk about the different categories of financial models. So, that’s a pretty broad term. You mention … What are the different sub categories within that?
Neil Booth: Yeah, so if you think about what financial models were originally intended to do, they come from data tables. Lotus 1-2-3, back in the day. And a data table is, how do I review the output of one formula across changes in multiple different inputs. So, if I change my ratio and my interest rate, what’s the output, or what’s the net result in IRR? That was really the reason for Excel to have gained the dominance that it did over Lotus 1-2-3, was it had a better solution to data tables than anybody else really did. And that was back in the mid-1980s, early 1990s when that sort of took off.
So, if you can structure analysis from the lowest level possible … It’s a housewife balancing her checkbook. The types of analysis, and the types of formal structure that you’re dealing with in that instance, fairly straightforward, fairly … Let’s be honest, lower level of sophistication. The type of formula structure you’re dealing with is sums, products, this plus that. A little bit more fancy than that.
But when you step up a little bit more, and you start to get to banking level, right. Or, M&A banker, you’re dealing with maybe LOOKUP. You’re dealing with SUMIFs. You’re dealing with array formulas. And those can be volatile, add lots of size to your analysis. And that can lend itself to complicated situations. When you multiply that times, let’s say multiple different assets. So I’m not just trying to evaluate a buy-sell decision on one asset. But let’s say I want to decide between buying and selling 55 different assets, all at once, right. Let’s say that I’ve got a global conglomerate that has gotten too big and unwieldy. And I’m the CEO, or CFO, and I need to communicate to my M&A bankers, sell these 10 or however many, underperforming business lines. Because we want to move on with the more profitable ones.
Well, that analysis starts to get really complicated. And you can start to multiply out the levels of complexity. So it starts from very, very simple, up to okay, this is a base level of financial modeling requirement, M&A banking et cetera. And then, just taking that complexity, and multiplying it through by multiple different asset categories. And that’s generally how we see the modeling world line up.
Will Bachman: What are some of the different maybe categories of use cases, that you see people using it for. So I guess, one is to your point of trying to sell off an asset, and seeing if it makes sense to sell it, and at what price. You mentioned project finance. I’ll reveal my ignorance here. I only have the vaguest idea of what that means. I suppose it’s finance related to some kind of project.
What is project finance, and what kind of modeling gets done there?
Neil Booth: Yeah, so project finance is a really fun thing. I don’t know where you’re situated now, but I’m looking out the window in midtown Manhattan. And I see roads, and bridges, and I see office buildings. These are very large capitally intensive assets. And they’re prime candidates for project financing.
So, for example, the Tapan Zee bridge is a great example of project financing. It cost I think between 14 and 16 billion dollars to build. And if you think about it, who really owns the Tapan Zee Bridge, would the Tapan Zee bridge have been built wherefore without some sort of government intervention? Probably not, because realizing revenue from that is really difficult.
So what ends up happening, is a state entity or a government entity with a [inaudible 00:31:11] will go out and say, we own the old Tapan Zee bridge. We don’t like this asset anymore. We want to fix it, or completely renovate it. We could do it on our own, and it would be really expensive. Or, we could contract with the private sector, and lease the right to an asset to them, technically finance it. And let them officially allocate the capital in the way that they see fit.
So if you’re optimal capital structure in a corporate finance environment is 60-40, or whatever it happens to be, in a private financing, that optimal capital structure can exceed 90-10.
Will Bachman: That’s equity, and debt and equity I guess?
Neil Booth: Yeah, so debt and equity. So 90 percent debt, 10 percent equity. And the reason is, because it’s non-recourse lending. So if everything goes belly up, there’s no recourse, certainly not to the government. And certainly not to anyone other than an SPV constructed exclusively, Special Purpose Vehicle, constructed exclusively for the purpose of financing this project. So you’ve got the assets on the ground, and that’s it.
That’s project finance in a nutshell. So, when you’ve got this risk of, am I really going to get paid on a quarter by quarter, or month by month basis, the model used to describe project financings are really, really detailed. That’s the certainty equivalent that the banks and the equity guys require in order to get comfortable with these types of financings. You can’t just do annual cash flows, you can’t just do 10 lines on a page, and sort of assume that, well, if I get it wrong, someone else will come by and fix it. That’s not really how it works. So, there’s a lot of sophistication and a lot of detail in these big models.
Will Bachman: Okay. So project finances, that would be one category of modeling that you teach. What are some of the other main use cases that people who take your courses, or who engage with Houlihan Lokey, would be wanting to do?
Neil Booth: So, M&A would certainly be another use case. We have guys who are doing what’s called FP&A, or financial planning and analysis on the corporate side. And that’s everything from how do I organize my business in such a way to create a result? So, what are my key product indicators, or [inaudible 00:34:00] indicators, KPIs that drive my business, and how do I calculate those, given a data rich environment, to update a larger group.
So, we’ll help people … I also deal with the oil and gas base. What are some of the fundamentals that drive pricing in the oil and gas base. And so, we’ve got all this data in the power markets, in the oil space, and we help people think clearly, given lots and lots of data, about how to make buy-sell decisions in those markets, as well as to structure their companies, and structure their thoughts around business areas in a way to attract attention, or to get a job done.
Generally, it’s the higher complexity and shorter time, the more chances of engaging directly with Houlihan Lokey. So if you’ve got 55 … I keep coming back to that number, 55, but it’s come up a couple times in recent client engagements. But if you’ve got a portfolio of natural gas fire power plants, which themselves are pretty funky things, and I want to acquire, or I want to sell some natural gas fire power plants. And I want to do it by the end of the month, chances are pretty good you’re not going to want to [inaudible 00:35:29] all that yourself, you’re going to hire a specialist to come in and do that.
Those are some of the real best applications of where financial [inaudible 00:35:39] and service shines.
Will Bachman: Would you then maintain a library of template models that are already set up for something like that? So you can just pull your natural gas model off the shelf? Or does it always make more sense just to build it from scratch?
Neil Booth: You know, we do get clients who will come to us every once in a while, and say, “I’ve got this analysis, and all I need you to do is this very simple tweak.” To this otherwise large analysis that I’ve spent lots and lots of time on. And, I try to counsel those clients as best I can, that models are like balls of yarn. Once you start pulling at them a little bit, the whole thing is going to unravel.
Generally I find that building from scratch is the best way forward. That’s just from a time, and clarity and an efficiency perspective. Starting with a blank slate makes a lot of sense. Because you can control all the numbers that go in to your new analysis, and validate, and vet all the relationships new. And you don’t have to worry about all the relationships that were embedded by anybody else. That said, there are ways to take short cuts. So if you know for example, we’re always going to have an income statement balance sheet and a cash flow statement, well, while the form of those things may change from industrials to consumer products, generally you know that an income statement’s going to start with revenue. And we can format the revenue section. And balance sheet’s going to start with cash, and we can generally format that financial statement in a way to save ourselves some time down the road.
So, we do look for efficiencies, but every model is completely unique, and completely different from the one that came before.
Will Bachman: Have you come across any stories of models where a mistake in the model caused a deal to not go through? Or maybe a mistake in the model, a deal went through, but then they realized later that holy smokes, our calculations were way off.
Neil Booth: Yeah, we have quite a few of those. But I think one of the best ones was a … So, there’s an engineering firm who shall remain nameless. They wanted to get a power plant built. And that power plant was predicated on a government program that changed over time. So the incentives promised during the government program, went from being allocated as cash, to being allocated as a tax credit, right.
So you think to yourself, it’s okay, who cares. It’s the same benefit. True. We’ll get to that in a second, but … So, they published this report for a client who asked them, build us … Will you help us think through the engineering on building this power plant for us. And embedded in that, is a working calculation, which is based off of proforma analysis.
Well, roll forward eight months time, after the government program that was embedded in that proforma analysis, had changed from cash to tax credit. Client comes back and says, “Yes, I’d like to do this because the IRR on that proforma is over 25 percent. I’m losing money not doing this. So I’m going to engage directly with your engineering firm, and we’re going to build this thing together.”
So, engineering firm comes to us, and says, “You’re going to help us finance it. Here’s the proforma.” And I’m the model jockey, who’s responsible for analyzing this. And look at the model and go, yeah, this deal ain’t going to work. And there’s silence. There’s big board meeting, big board meeting. And, what do you mean it’s not going to work? More than 40 percent of your cash flows have come from this cash item. That’s not a cash item anymore, that’s a tax credit. Which means that, you’ve got to be able to monetize that tax benefit, and we really can’t do that right now. So, that 25 percent IRR is less than three.
And again, compete silence around the room as people start to digest this. And it ended up being sort of a big stink. And actually, I don’t think the deal ever got done.
So, yeah, models are living, breathing things. You have to constantly update them, and keep them fresh. And if you’re not, it can lead to some pretty dire consequences.
Will Bachman: Yeah, so, I bet that made you popular that day. Better than finding out after the deal was already done.
Neil Booth: Yeah, exactly, yeah.
Will Bachman: Awesome.
Neil, for someone who … Probably the best thing, I would imagine, would be able to go through one of your trainings. But for someone who doesn’t have that opportunity, what are some self-study tools that you suggest to people to kind of take their level of modeling skill to the next level?
Neil Booth: Yeah, that’s a good question, I get it quite a bit. In everyone’s universe, they’ll probably have someone that knows modeling … And certainly feel free to reach out to me. I’ll leave my contact information if you like. I’d be happy to share some of these tools. But I would suggest that if people are truly interested in this, they go out, and find a good model. And go find some form of a good analysis that represents what they feel is adequate to, or surpasses the level of sophistication they would need in order to do their thing. Generally speaking, you can ask around and find something that suits well enough.
And then, once you’ve found that good model, break it. Break it, destroy it, and rebuild it from scratch, five times. And once you’ve rebuilt it from scratch, and learned all the formulas, all the structure, all of that, chances are good that you will understand that analysis better than the person who built it just that one time. And that will really truly help you understand how to make it better for others.
And chances are similar between the second and fifth time, you’ll be able to build a better version of that simple thing.
So, there really are no shortcuts. There’s no way I can magically make you an amazing financial model. Over time, it really just takes an investment of time and actual energy on the part of a student to get up the hill.
Will Bachman: You know, that is so interesting to hear you say that. What you’ve described is the Benjamin Franklin method.
Neil Booth: Yup.
Will Bachman: Ben Franklin, who taught himself to become a compelling writer by taking notes on journal articles that he really admired, right. He would mix up all the notes, and he would attempt to rewrite the article from those notes. And sometimes he felt that it came out better than the original. So, I love that approach. I hadn’t thought of it.
Neil Booth: Yeah, you know, and unfortunately it’s got the lowest uptake of any of the approaches I’ve seen …
Will Bachman: It’s the most work.
Neil Booth: … Seen taken. Yeah, exactly. People walk out of the classes that I take, and they go, “Neil, this is great. Thank you very much. How do I make sure I really learn this?” I tell them exactly what I just told you. Break it, and rebuild this model that I just showed you how to build four or five times, and it’ll become second nature. I’m not doing that.
Okay, well, you asked. There it is. THat’s all I got for you.
Will Bachman: But really putting in the work, and building it yourself. The interesting thing that, from what I hear, doing it five times, where you’re maybe trying to do it a different way, it’s almost like writing multiple drafts of a story.
Neil Booth: Yeah, it’s 100 percent right. And again, it’s hard to do, because it’s rote and boring stuff. So, the people who end up succeeding are the ones how can somehow, like I said, get a little existential about it. Why am I doing this silly thing? I’m establishing relationships, and building on calculation blocks, and financial statements, and what is this all really doing.
If you can find something that you like, in the midst of that morass of abstruse concepts, that will help you stick with it, and stay true to the Benjamin Franklin method.
Will Bachman: Yeah. Are there any areas that you’re currently trying to work on rebuilding your skills, whether it’s using Excel or some other kind of analytical tool. What’s sort of on your development agenda?
Neil Booth: Yeah, so Houlihan Lokey has a business intelligence team, that is comprised of really complicated accounting guys who know accounting like the back of their hand. I know [inaudible 00:45:31] to be dangerous in accounts and accounting. But that’s really somewhere I’d love to get specialized. But also, data visualization is a really interesting thing to me. There’s this program out there, called Spotfire, and it allow you to …
Will Bachman: Spotfire, okay.
Neil Booth: Spotfire, yeah. It’s the excel of data geeks across the world. And it can do some really, really powerful things. I’m just floored by how quickly you can get results, given even a modicum of understanding of how the program works. So I’m probably going to be spending the next couple of months learning and applying that Benjamin Franklin method to some Spotfire applications, and trying to get smart there.
Will Bachman: Is it sort of an alternative to Tableau, for example?
Neil Booth: Yeah, so Tableau would become the front end of a Spotfire analysis. The Spotfire, from what I understand, I’m certainly no expert. But Tableau is a data visualization tool that sits at the front end. So you’re really just making pretty charts and graphs with Tableau. Spotfire allows you to link relationships between the data set, and slice it and dice it in some really sexy ways. And then you can use something like Tableau at the front. But Spotfire’s got some built-in visualizations that they prefer as well. That are pretty good, too.
Will Bachman: Fantastic. Well, Neil, what is the best way for people to find you online? You can share a website, your contact info, whatever you like.
Neil Booth: Yeah, so Houlihan Lokey, the website there is HL.com. People can reach out to me by email. My first initial and my last name at HL.com. So it’s NBooth at HL.com. And certainly feel free to give me a call. My office number is 212-497-4168. Really looking forward to engaging folks about problems that they see in their financial models. I don’t like to go out and sell people on my ability to do anything more than talk about their problems, right. When people have problems in Excel, that generally means that they’re engaged in a way to try to find solutions to their problems. Your solution may not be working with my group. Solution may be, maybe it’s a really quick fix, and all we need to do is just guide you with a couple formulas. And if that’s the answer, awesome. And if I can be helpful in that way, awesome. I want to.
But, look again, if you’ve got a little time, and you’re working in a really complicated field, and we can work together in some meaningful way, love to explore that, too.
Will Bachman: That is fantastic. Neil, thank you so much for joining today.
Neil Booth: Hey, Will, I really appreciate this. This is great.

Related Episodes

jay-altizer-bain-alum-dallas-tx

Episode
440

Food Industry 101

Jay Altizer

Episode
439

Craig Beal on the Travel Business

Craig Beal

Episode
438

Rob Ristagno on Customer Segmentation

Rob Ristagno

Episode
437

Equity Research

Neeraj Monga