Michael Choe - Atomization of Private Equity Decisions at Charlesbank (EP.432)

26:23Let's look at the 10th percentile case, which we are calling our realistic disaster scenario. Translation, that was like our old downside case. So the human mind still looks for stories and scenarios. Over time, though, we're now getting a lot better than we used to be at thinking about modeled outcomes as probability distributions. And one of the ways we're doing that is rather than looking at what the median case return is or what the 90th percentile case return is, what we're asking teams to produce are KPIs such as what percent of 10 ,000 modeled outcomes results in a greater than 30 % IRR over two years?

26:57What percent of 10 ,000 modeled outcomes result in our ability to drive a 2x multiple of invested capital over two years? What percent of modeled outcomes result in impairment of our capital. And that's a profoundly different set of statistics to look at then what's your base case return? What is your upside case return? What is your downside case return? Because now you're actually describing the decision that we're tasked to make, which is what is the asymmetry between an upside scenario and a downside scenario? How do those probabilities relate to each other? And so rather than looking at things that have a high base case, what we're looking for now are companies that have a very asymmetric distribution of outcomes towards the upside with very muted downside.

27:40What are some of the ways that the modeling approach changes how you think about risk? In general, I'd say undertaking this process has made us humble to the fact that probabilities are inherently uncertain in private equity and things happen that impact investment. So if you build a regular five-year LBO model of a business that is recession exposed, for example, what you typically do is you build a base case model that doesn't involve a recession. And you say, well, this is just a base case. There's no recession. And then somebody on the IC would typically say, okay, well, what if there's a recession?

28:17And the team goes off and says, okay, well, we came back. Here's a recession model. The recession case produces a 1.3X multiple of capital. And the reason for that is that the team has the freedom to put the recession arbitrarily at any point in the five-year time period. And so they'll say, well, we'll put the recession in year two, the company's earnings went down, and then in year three, there's a bounce back and we came back. So we lost a year and it grew a little bit slowly or something. The thing we now do, if a business is severely recession exposed, we have a generic probability of a recession.

28:46It's 12 % in any given year. We could be wrong about that, but it's better than not putting a probability in. So we say, okay, well, let's just assume that once every eight years, there's a recession. So in each of the first two years, there is a 12 % probability of a recession. And if a business is severely recession exposed, that will show up in the shape of the distribution that we're building. That's an output to our process that has created, I think, a profound shift in how we differentially assess the risk of a company that might be recession exposed, whose base case investment results in a five-year-old model might look just as good as something that we are approving.

29:22But those types of hidden risks are a lot easier for us to quantify and think about. Another one would be customer concentration. So we recently looked at an investment that had two customers that were roughly 20 % of the revenue. This is a company that sold to the CIOs of large enterprises. The two largest customers were big public companies. And so obviously, if you lost these customers, it would be a pretty catastrophic event for the investment outcome. Now, the deal team's advocacy, and this was an early stage investment committee process, Their advocacy was this is an incredibly sticky service.

29:57It's very hard for these customers to leave you. And there's all this growth that's going to offset any potential loss in the near term. But we said, OK, well, what's the probability of one of these customers leaving you? And they said, well, it's pretty low. And so the investment committee dialogue was, well, what about 10 percent? The deal team's initial view was, well, that might be kind of high. But the investment committee's feedback was, well, that means one out of every 10 years, something could happen that might cause a customer to leave. Seems reasonable. CIO could move on to another job.

30:25The customer could get bought by another company. So 10 % generic probability. Well, if you do the math and you assume that these two events are independent from each other statistically, then in year one, your probability of retaining both customers is roughly 80%. It's 0.9 times 0.9. And the same thing happens in year two. So your probability of retaining both customers over the first two-year period, which is our modeling horizon, is roughly two-thirds. So one third of 10 ,000 modeled outcomes is going to have the loss of one of these customers. That's a very counterintuitive result relative to a five-year base case model where you'd probably build in zero customer attrition for the top two customers because you think they're so sticky and they haven't left in over a decade or something.

31:07So that type of identification of risks that can get hidden in a five-year modeling scenario and making them an explicit part of our probability distribution has had, we think, a pretty beneficial effect on the curation of what types of investments we want in our portfolio. We're going to take a break in the action to tell you more about Morningstar. Data isn't just a byproduct of your business. It's the driving force. But where's it taking you? Morningstar data clears the way forward. A decisive language of insights for investment professionals to implement conviction-led strategies across both public and private markets.

31:47Visit wheredataspeaks.com to see what Morningstar data can do for you. And now, back to the show. How did using the model inform where you search for investment opportunities? The model that determines our pricing tolerance or valuation tolerance of an investment, that exercise happens at the final investment committee meeting after we've been working on something for months. What's been fascinating to see is how the change in that end modeling process has filtered upstream to influencing how people choose to spend their time. One simple thing that we've noticed, and this has been one of the most exciting changes at our firm over the last 10 years, is even way before the FAN of Outcomes model is built, when teams are out there sourcing and looking for investments, the language that they use to think about and filter investments involves the FAN of Outcomes type thinking.

32:45So we will often hear somebody say, we found this idea through our research. It's a company that does XYZ type of business. And when we build the fan, we think it's going to have a really attractive asymmetric shape. Now, that's a very interesting thing that's happening. It's a tool that we are using at a final stage of an investment process, really influencing the way somebody is thinking about potential investments at the very early stages. So as that got amplified, what we have noticed is that there's been a shift away from filtering investments using availability. There's always a part of somebody's brain when they're looking at investments around how do I make sure that I don't waste too much time?

33:24How do I look for companies that are actionable? And that's always going to be a consideration. We have to make sure we're not wasting time. But the dial has turned a little bit away from availability at the early stages of the process toward the kinds of companies that really do offer that type of asymmetric probability set where we think we can drive a very attractive set of outcomes in the first two years. And so the quality of the curation of the investment funnel has improved all the way up to the beginning stages of our research. Where have you found those types of companies that offer that asymmetric profile?

33:59One of the areas that we have found a lot of that type of profile in would be companies that have a specialized human capital services offering that is combined with a revenue model that has strong recurrence. As we all know, from 2010 to 2020, software as an asset class came into real prominence in our industry. It's really transformed the way capital has gotten allocated in private equity. And the reason for that is the software business model was simply put very misunderstood and underappreciated. In this decade, we think there are classes of companies out there that offer human capital services that are highly specialized, that have pricing power, that have the ability to generate very attractive margins, that are incredibly asset light and very capital efficient, that with the right ownership model, generate similar types of returns on capital as software and are fairly misunderstood.

34:54Oftentimes, these are companies that participate in gigantic industries where there's really relatively low private equity penetration. So a lot of opportunity for private equity to have a focused role in consolidating the industry. And so an example of that would be the US CPA industry. It's a$40 billion industry before accounting for surrounding advisory revenue that typically goes along with having an audit or a tax practice. Within that, tax accountants tend to have very, very strong revenue retention. If you've ever thought about how hard it would be for you to leave your tax accountant, and you'll know what I'm talking about.

35:31And there's really minuscule private equity penetration into the U.S. tax EPA industry. Now, why is that? Well, it's complicated to invest in one of those as a private equity firm. You have to make sure that you leave enough employee ownership such that the engine of the firm remains intact. You have to think about how do you capitalize EBITDA in a business like that, because these companies typically distribute all their earnings to the partners. And so you have to figure out what's called an income contribution model or what's called a scrape model. But if you can see through those complexities and work through them, we think that you can establish an investment in a company that has really, really strong revenue technicals, strong resilience across a bunch of different types of macro environments.

36:13So it's not really recession exposed or exposed to shocks the way other companies might be. And a company that participates in a giant industry where there's plenty of opportunity to generate organic and inorganic growth by being a focused investor. And so that would be an example of the kind of opportunity that this type of fan of outcomes thinking where we're looking for that type of upside downside asymmetry has generated an interesting idea. What were some of the other success factors that you found from your historical investing? We regressed earnings growth against returns. Unsurprisingly, it's very correlated.

36:48We were curious about whether organic versus inorganic growth would make a big difference. And startlingly, the R squared on total earnings growth is almost as strong as organic growth only. And I think the reason for that is that when a company is approving acquisitions and we're obviously in control of that decision, we're typically doing it with a lot of strategic advantages. We're doing it carefully. And it's pretty rare that we've seen a systematic acquisition program with the proper discipline be dilutive. And so that was one surprising finding. Another one would be that we used to think that management stability would be very correlated with investment success.

37:32And we looked at changes in C-suite management and there was really not a ton of correlation there. So I'd say that's been an insight that has caused us to be perhaps a little bit less fearful of making management changes when necessary or strengthening management teams. Another interesting one was looking at the correlation between entry multiple and investment success. And in our case, and we really had the data just to look at the hundred or so transactions in our history as a private equity firm, there was really no correlation. If there was one, it was a very weak negative correlation. So lower multiple investments tended to have weaker results.

38:08And so that was another interesting insight that came out of that. Once you make an investment, how do you apply that thinking towards the toolkit that you're going to use to help improve the operations as an owner? That's one important and profound improvement that we're looking to make is to really use the modeling tool as a cognitive motivator for high urgency, higher quality portfolio management. Because we have focused our model on a two-year period, because our rallying cry now is, unless we're winning out of the gates, we're losing, because that's just a simple way to articulate the outcome of all this regression analysis we've done.

38:53Because the underwriting process of generating this fan of outcomes model involves such specific inputs around what we intend to do to improve the business. The other thing I would say is we consider ourselves producers of decisions. We're professional decision makers. It's not just a final investment decision. It's really every decision that we're making that we think of as part of that process. And so in portfolio management, we are using probabilistic thinking to try and improve the quality of our decisions. Should we invest in a new branch office? Well, what does the fan of outcomes look like in terms of upside EBITDA contribution relative to risks of that decision?

39:35We don't have to build a model to think about that, but we can use that framework to discuss that decision more intelligently with our management partners. What does the fan of outcomes look like on making two or three critical hires in the go-to-market organization? Well, the downside, if it doesn't work, it's probably a pretty finite amount of downside. the upside might be pretty attractive relative to that finite downside. So that's one of the things that we've seen, even down to the hiring of individuals, either into our portfolio companies or into our own firm. We are trying to use fan of outcomes thinking.

40:04So in our own firm, we have adopted simple personality profile testing, and we're back testing different personality profiles against performance tiers in our firm to see what profiles are predictive of high performance. One of the factors that is very dominantly correlated with being a high performer at Charles Bank is something called action orientation or action bias in the personality tool that we use. And so really using this probabilistic thinking around understanding that every decision is something we should be humble about because the future is unknowable by anybody, but then trying to use analysis and data as much as possible to make decisions that are more predictive of success is something that's happening all across the supply chain of decisions.

40:45What are some of the challenges that you've run into either internally or with portfolio companies of trying to inculcate this thinking? Seth Klarman talked about this on your podcast. Andy Duke talks about it, is that you could make the right decision and tail events can happen. And so one of the important things for us is when something happens that's unexpected, think about whether it's bad luck or good luck in spite of the decision-making or whether something about our decision-making was flawed. We've been working on this particular type of thinking for the better part of a decade where we now believe we have enough data points to start backtesting and refining the model.

41:27But sometimes we end up in tail scenarios relative to our distribution and just being clinical and then giving our teams permission to say, gosh, something about the way we did the inputs was wrong or this was a tail event and just being really intentional about that. That's one generic challenge. The other one is just logistical. It's just hard to move an investment operation, even of our scale. and I don't consider ourselves a huge firm, to go from one mode of modeling to another mode of modeling. And in the beginning, it was just taking up so much time in these processes. A final one, I'd say, is our initial inclination when we built this kind of different way of probabilistic thinking into our process was to overcomplicate it.

42:09And we would put too many input distributions in and we'd get an output distribution that we couldn't look at and easily intuitively understand why it was looking that way because too many things went into it. So curtailing our impulse to be overly nerdy and trying to really simplify the number of things that we put in to drive the 10 ,000 case simulations, that's been another challenge that we've been working on. How about with a portfolio company management team that's completely unaccustomed to this way of thinking and you're just talking to them about it for the first time? That's an area where we're trying to tread very lightly.

42:46In any given portfolio company, there's usually three to five levers we're really trying to pull to create true fundamental enterprise value growth. And that focus is super helpful. And what we don't want to do is overly complicate the agenda. Now, with certain of our CEOs, especially those who are in business lines where this is relevant, we have started to introduce this concept of asymmetric decisions versus decisions where the upside and downside is more symmetric. As you've increasingly applied this to your decision making, how do you get a sense of whether it's working? Great question. Well, the number one report card for us is the performance of our portfolio and portfolio construction.

43:29And we've been in business for over 25 years as Charles Bank. I think we've generated a very consistent track record in North American private equity. And so if we look at our portfolio construction, one of the things we're seeing is that over the last, I'd say, six or so vintage years, we are starting to see a higher concentration of investments that have real breakout potential. We don't think that's accidental. We think it's because we're being much more focused on all the things I talked about by integrating our value creation planning into the underwriting by going to work with a maniacal level of focus even before we close the investment on accomplishing that two-year enterprise value growth.

44:11So this non-accidental concentration of more breakout performance into our portfolio is something we're seeing. We've been working on this tool for just under a decade now. Private equity is, it's a little bit like watching paint dry. Things don't happen very quickly. And so we're now just starting to be able to look at the different vintages of investments and see this type of effect. How do you use that decision process to consider your business strategy at Charles Bank? think we've just simplified our thinking around what do we do to which decisions offer the most asymmetric upside to our firm and muted downside.

44:47When we do that, unsurprisingly, it's back to the basics, making sure that we are being best in class human capital managers. At the end of the day, we're just like every other professional services business that we like investing in, our greatest asset is our people. And so just thinking through the upside of being a great human capital manager relative to the downside of having attrition of star performers. So that leads to a whole set of investments that we've made in terms of just being much more disciplined human capital managers. We have a in-house talent management function, which is quite robust to help us with that.

45:21Really thinking through not getting attracted to shiny new objects. If you think about expansion into new territories, expansion into new business lines, those all have risks that can be understated if you're just simply making decisions because you're growth oriented, but just being really judicious about assessing risk. Anything new has to, by definition, have a high level of generic risk. So I think it's just made us generally more prudent decision makers. And I'd say the main effect of it has been for us to really stick to our basic knitting around just being great people managers, sticking to industries and companies we know really well, where we can, in fact, generate asymmetric conviction relative to what the market understands and therefore find assets that are misunderstood and likely mispriced relative to their two-year forward trajectory that we can unlock.

46:09So from that long history of middle market buyouts, how did you decide to extend into the adjacencies in credit and technology opportunities? We wanted to check a few boxes that were critical. First and most important was, were these expansions that would really deepen and enhance our fundamental research toolkit in the middle market and therefore be highly strategic and complementary to our core business of middle market buyouts? Our entire model is premised on doing superior research. It was our belief that the more we could extend the depth of that research with teams that were looking at the same industries and the same types of companies with slightly different lenses, the more of a competitive moat we could create.

46:57The second was, do we have entitlement based on our pattern recognition and the talent that we can bring to bear to generate excellent track records in those industries? And we really wanted to satisfy both of those boxes with a high degree of conviction before we entered them. This is why in nearly 30 years of being a private equity firm, we've only done that twice. I'd love to hear your thoughts on the landscape and maybe how you might be thinking about it either similarly or differently than others. It's very interesting to think about the fact that private equity, in the format that we know it, it's really been around for roughly 40 years.

47:37But within those 40 years, I would say really the last 25 years of evolution has created this industry that we now think of as the global private equity industry. 25 years, in some sense, I guess, is a long period of time, but it's also a pretty short period of time if you think about the number of fun vintages that have been invested during that period of time. And so one of the things that I think is pretty clear is that for a certain type of companies, and we would put certainly North American middle market companies in this category, focused private equity ownership is just a really advantaged form of ownership.

48:20Take any industry that now has meaningful private equity penetration, the optical retail industry, for example, we were one of the early investors in that industry. Going back 20 years ago, your neighborhood optical retail shop didn't think of themselves as having terminal enterprise value. But in fact, they do. They actually have a fairly recurring base of earnings in the form of their patient file. I've been going to the same eye doctor for the last 20 years, and I'm unlikely to switch unless there's some affirmative reason for me to switch. And so industries getting recognized for their true underlying value by private equity, and then for the focused ownership of private equity to create advantage forms of being in that type of industry as a consolidator or as somebody who provides superior customer service or whatever.

49:04We think that's a long-term trend. we think that's likely to continue. We still think that private equity generally is underpenetrated into middle market companies. We think there is plenty of company formation in the U.S. such that there's a good runway. The other thing that we think has happened is that EBITDA multiples have gotten over the last 10 to 15 years pretty divorced from free cash flow yield. The average free cash flow yield of a North American buyout is in the low single digits now. And so it's no longer really supposed to be a metric for free cash flow. There's been a emergence of a new way of thinking about private equity, which is which companies are likely to be valued highly by a successive private equity owner.

49:46That's something that's likely to continue. We think right now where multiples are, probably there's a little bit of a plateau because if you're paying the type of prevailing average multiples that are going on in the industry today, if you pay any more than that, you start to erode your ability to generate real private equity type returns, even if you can create enterprise value growth, because there's just too many turns of equity going into the buyout. Certainly we're not, and we don't think most people are modeling in a continued linear multiple expansion, which the industry has benefited from over the last 15 years.

50:19But at this new level of where multiples are being capitalized in middle market private equity, we think there's almost a liquidity profile of these companies because of the ability of the private equity industry to create successive generations of ownership among different firms. And so we think that's an interesting thing that we're thinking about in terms of how do we think about multiple discipline? We always have to think about valuation mean reversion risk. We do think there is a little bit of a floor or a cushion to valuation mean reversion risk because of the fact that there's just trillions of dollars of global capital that wants to get allocated to private equity that will create a bit of a technical floor to that.

50:55What concerns you about the industry going forward? Because of the way the leverage markets work, and certainly now an enormous amount of capital is getting allocated to private credit, and a lot of it is going into the hands of a few very large players. Those types of excesses, just because of the organic sequencing of psychology in our industry, can create valuation bubbles. And so I think that's a generic risk. We certainly saw one in the 21 timeframe. As a firm, because of our long history, we've lived through many of these bubbles. And a lot of them don't end well. We think a lot of the leverage excesses of 21 are likely to result in first liability management exercises, LMEs that will then involve some amount of restructuring over the next few years.

51:40So those are generic risks to our industry. Because of our fundamental research driven model, we tend to look to find opportunity in that type of chaos. So we're getting ready for that. What are you most excited about? At our firm level, Bringing a level of analytical rigor to talent is a pretty new endeavor, but I mentioned earlier, we're using some personality profile testing to backtest certain personality profile features around how to recruit better. Recruiting higher caliber human capital into our companies and into our firm is obviously a major unlock for us. And so just continuing to get deeper into that, there's an enormous amount of science out there that's now getting generated around how can people get a little bit more predictive around human talent.

52:28So that's something we're pretty excited about. All right, Mike, I want to make sure I get a chance to ask you a couple of fun closing questions. What is your favorite hobby or activity outside of work and family? Well, this is a little bit related to family, but I really love cooking. I got into it 20 years ago, just watching random shows on Food Network, and it's become a bit of an obsession. Given a choice, I'll spend a Saturday or Sunday afternoon shopping for ingredients and thinking about something to cook and putting together dinner for the family. What was your first paid job? My first paid job was being an English tutor for little kids in Seoul, Korea, for families that wanted their kids to be able to speak conversational English.

53:07So I would go to their homes, tutor these kids for roughly$10 an hour. What'd you take out of it? Well, I actually love teaching people stuff. So simplifying complicated concepts, the English language, you don't recognize this if you're a native speaker, but there's so many irregular rules in English. It's very hard to teach. So simplifying complicated things to teach little kids English. I think I learned a lot from that, but the other was that making money is hard. I usually had to go to these kids' homes and I took public transport, so it would take me usually an hour to get there and more than that to get back.

53:42So I tend not to take that for granted. What's your biggest pet peeve? I'd say it's the state of wireless coverage in the U.S. There is an intersection of two highways outside of Boston that I drive through regularly where I pretty much 100 % of the time lose my cell connection. And I won't say which carrier I'm with, but it doesn't matter because my wife is with the other carrier and she loses her connection there too. And it's something about the 4G to 5G network upgrade, but it's been that way for a few years. And I just think it's kind of embarrassing that as a country, we have areas in major metropolitan cities where wireless coverage gets dropped.

54:22How's your life turned out differently from how you expected it to? I grew up wondering if I would have any skill in decision making. I was always a pretty good student, but just because of the way my father struggled with day-to-day decisions, I remember being a little bit nervous or worried that I wouldn't grow up to be a good decision maker. And it's something that I've worked on my entire life. And I guess I find it somewhat surprising that I've become a professional decision maker. What's a mystery you wonder about? So I recently read this book, In My Time of Dying, by Sebastian Junger. It's fascinating.

55:02In it, he describes a near-death experience that he had. And near-death experiences, or NDEs, as they're called, are very closely related to another type of experience where people will receive visits from folks who have passed on. Now, I was a science major in college. I'm not particularly religious. But the idea that there might be life that survives after physical death and that the fabric of the physical universe as we understand it may actually contain some mysteries that are consistent with that. So in Sebastian Junger's book, he actually explores quantum physics and things like delayed choice quantum eraser, which are phenomena that are very hard for mere mortals like me to understand, but that are really inconsistent with classical physics.

55:53And so the idea that the fabric of the universe as we know it, using classical physics, may actually hide some mysteries that are consistent with life after death. This is something that I'm quite fascinated with. All right, Mike, last one. If the next five years are a chapter in your life, what's that chapter about? I think it's much easier to have a firm that is a great investment firm because it has one or two great investors. Now, I'm not saying we are that, but just take any famous investment firm out there, Hedge Fund or Berkshire Hathaway. Really, the persona of the firm and its investment excellence is very closely associated with the skill of one or two people.

56:37I think it's much harder to create an investment firm where the excellence is a result of a systematic process. And I feel like we are well on our way on that journey at Charles Bank of combining a bunch of great ingredients. 25 plus years operating in the middle market, all of the deep research and pattern recognition that we have as a result of that. We have an incredible network of executives that help us. And then we have obviously our investment team, which is a phenomenal team of folks who are selected for their problem solving ability, their intellectual curiosity, their action bias. But taking all of those great ingredients and creating a system that we can look at and say, boy, that system has a reasonably high probability of generating great results across a wide range of uncertain environments, no matter who's at the top.

57:32That seems like a really worthy goal and something we're super focused on working on. Mike, thanks so much for sharing this interesting framework for thinking about investing. Thank you for having me. Thanks for listening to the show. To learn more, hop on our website at capitalallocators.com, where you can join our mailing list, access past shows, learn about our gatherings, and sign up for premium content, including podcast transcripts, my investment portfolio, and a lot more. Have a good one, and see you next time.