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

Michael Choe is the CEO and Co-Head of Flagship private equity strategy at Charlesbank Capital Partners, a $22B manager of middle-market private equity, credit, and technology opportunities that spun out of the Harvard Management Company in 1998. Our conversation covers Mike's path from science to finance, including an immigrant story and a draw to decision-making at a young age. We discuss Charlesbank's history and aspiration to manufacture sound decision-making as a path to investment success, applying its "fan of outcomes" thinking to talent, research, diligence, sourcing, and company operations. Learn More Follow Ted on Twitter at @tseides https://twitter.com/tseides?lang=en or LinkedIn https://www.linkedin.com/in/tedseides/ Subscribe to the mailing list https://capitalallocators.com/ Access Transcript with Premium Membership https://capitalallocators.com/signup Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com https://thepodcastconsultant.com/)

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:01Ted Seides?

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• 0:46Ted Seides?

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• 2:06Ted Seides?

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• 2:47Ted Seides?

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• 3:32Ted Seides?

  Hello, I'm Ted Seides and this is Capital Allocators. This show is an open exploration of the people and process behind capital allocation. Through conversations with leaders in the money game, we learn how these holders of the keys to the kingdom allocate their time and their capital. You can join our mailing list and access premium content at capitalallocators.com.

• 3:59Speaker 01

  All opinions expressed by Ted and podcast guests are solely their own opinions and do not reflect the opinion of Capital Allocators or their firms. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Capital Allocators or podcast guests may maintain positions in securities discussed on this podcast.

• 4:18Ted Seides?

  My guest on today's show is Michael Choe, the CEO and co-head of flagship private equity strategy at Charles Bank Capital Partners, a $22 billion manager of middle-market private equity, credit, and technology opportunities that spun out of Harvard Management Company in 1998. Our conversation covers Mike's path from science to finance, including an immigrant story and draw to decision-making at a young age. We discuss Charles Bank's history and aspiration to manufacture sound decision-making as a path to investment success, applying its fan-of-outcomes thinking to talent, research, diligence, sourcing, and company operations.

• 5:02Ted Seides?

  Before we get going, it's that time of year where it's just plain cold in the Northeast. Chilly temperatures, bitter winds, and snow and ice that stays around for weeks on end. Back when I was in college, a group celebrated "Feb Club", where they held a party every night of the week during the month of February just to find some cheer during the winter doldrums. Now, I love cold weather and especially the snow. But if you hear the gentle sounds of waves in the background, it's because I high-tailed it to Florida this week to catch some professional tennis at the Delray Open. And I'll have to admit, an 80-degree day in February feels about 20 degrees warmer than an 80-degree day in June.

• 5:47Ted Seides?

  I'm not surprised some of the tri-state area investment industry has found its way to Florida in these winter months. But regardless of whether you're stuck inside, swishing down ski mountains, or enjoying the sun and waves on a beach, you can always pop in some earphones and have a listen to, well, you guessed it, capital allocators. I, for one, am enjoying both this spot of sunshine and this week's episode. Thanks so much for spreading the word. Please enjoy my conversation with Mike Choe.

• 6:19Ted Seides?

  Mike, great to see you.

• 6:21Speaker 02

  Good to see you. Thank you for having me.

• 6:23Ted Seides?

  I'd love to start all the way back.

• 6:25Speaker 02

  Well, in many ways, it's sort of unusual. So I'm Korean, but I don't consider myself really a typical Korean American because I was born in the States, but when I was eight, my family had to suddenly move back to Seoul. It was unexpected. The reason for that was that my parents moved here for my dad to do his graduate studies. And he ended up dropping out of grad school and opening a diner. And so I was just a regular kid living in California whose parents had a small business. But because he was operating a diner on an expired student visa and hadn't managed to get a green card, my parents were technically illegal immigrants, even though they were taxpayers and they had social security numbers.

• 7:07Speaker 02

  And so one day, that whole situation caught up with them and they were deported. And deportation, even with a family like ours, otherwise law-abiding family, is a pretty violent process. So it happened overnight. At the age of eight, I suddenly moved back to Korea and found myself going to Korean public schools. And I was somewhat conversant in spoken Korean. I really didn't know how to read and write. So I had to learn a brand new language, or at least how to read and write it. But the more difficult thing was actually getting caught up with the Korean kids on math. They were approximately a couple of years ahead of where I was on math. And so I ended up growing up in Korea for the rest of my childhood and then came back to the States at age 18

• 7:49Speaker 02

  to go to college. And as a result, I'm a US citizen because I was born here, but I was mainly raised in Korea during the relevant part of my adolescence. And so I have a mixed cultural identity, I'd say.

• 8:00Ted Seides?

  What did you take away from this kind of movement at age eight?

• 8:05Speaker 02

  If I had to pick one profound influence, I would say it's the fact that frameworks are something that I consider to be relative. So I think if you grow up in one culture, The educational system that you grow up in, the language that you use, the customs with which you interact with people, it becomes a given and you don't question those things. But because I was displaced from one system at a pretty young age and had to learn a pretty different system, I mean, Korea was somewhat westernized at the time, but in many ways it was not. And the way they teach math is very different. The way they teach history is very different. The way they teach language is very different. There's a lot

• 8:46Speaker 02

  more rote input of information. And so, understanding that the way an entire society does things doesn't necessarily mean it's the only way to do things. That sense of relativism where there may be a bunch of different ways to systematically approach something, I think I started to learn that at a pretty early age.

• 9:03Ted Seides?

  Even though you were young when that happened, I'm curious about what you took away from your father's decision making?

• 9:12Speaker 02

  I've thought a lot about this. What influences did I get from my parents growing up? What influences did I get from the particular experiences I've had? And I'd say as a starting point, I'm pretty surprised that I have the career that I have now. I was not one of these kids who thought about economics or finance. I went to college and I studied science. One of the first classes I took as a freshman in college was a seminar on decision making. And that class was populated by people who wanted to go into economics and finance. And then there was me. And so, when we had to have our final project for the end of the term, many of the kids were writing papers on how to invest, or how to think about different options, or stocks, or bonds, or different structured financial

• 9:57Speaker 02

  instruments. And I wrote my paper on human experimentation in medicine. And so, I studied the Nuremberg Trials and explored the morality of that. But I remember listening to these kids who were in my class who were bound for finance and thinking, oh my gosh, I have no aptitude in terms of the kinds of problems that they like thinking about. I had no personal interest in understanding finance. I was much more interested in questions that were unanswered in science. And so, I find myself really surprised that I've ended up with a career that I've had. But I'd say- Maybe one of the influences was my dad was an incredibly logical person. He studied math as an undergrad. He taught me most of the math that I know when I was a kid. But he was also a somewhat indecisive person.

• 10:42Speaker 02

  So he struggled to make even routine day to day decisions. And my mom, on the other hand, is an incredibly decisive person. But sometimes not the most logical. And I remember at an early age thinking, gosh, it'd be great if I didn't struggle with decisions the way my dad did. But if I could figure out a way to use logic to construct decisions versus some other instinct. So I think that has been a lifelong idea that I've pursued. How can I get better at making decisions? And if you really think about it, you can reduce one's life to really a series of decisions you're making every day.

• 11:18Ted Seides?

  So from going to college, everyone else is talking about finance and you weren't interested in it, to in relatively short order, you found yourself in finance. So what was that decision process?

• 11:29Speaker 02

  Well, I'd say it was a series of accidental events that led me there. Around my junior year, I started to question whether a lifelong career in science or medicine was right for my personality. I like interacting with people. I like learning things interpersonally by interacting with people, kind of the way we are now. And I've loved listening to your podcast as a way to learn. And so I started to question what alternatives might exist. And at around the same time, one of my lab partners of all people got a job at McKinsey and Company, which is a strategy consulting firm. And he said, look, they think about questions that are in many ways as complicated as scientific questions, but they apply them to business problems. And so I was attracted to that. And so I ended up getting a job at McKinsey out of college.

• 12:13Speaker 02

  And then after my analyst stint at McKinsey, I wanted to move back to Boston. I was in the Los Angeles office and I followed a guy who was my best friend in the analyst class at McKinsey to this job that he was talking about. He said, it's private equity. I had no idea what that meant. But I followed him to this job mainly because it was a job back in Boston and it seemed like it was going to use similar skill sets is what I developed at McKinsey. And that's the job I still have now, 27 and a half years later. And that person is my partner, Brendan White, and we've worked together pretty much every day of our entire professional lives.

• 12:47Ted Seides?

  So take me back, you're moving over to Boston to Charles Bank. What's the history of the firm?

• 12:53Speaker 02

  Our firm was started inside Harvard Management Company, which is the umbrella organization that managed the Harvard endowment. At the time when it was formed, Harvard was basically an in-house investment model for its endowment. So in contrast with Yale, where David Swensen pioneered the use of third-party managers to generate performance and manager selection, and then also overweighting into alternatives, Harvard decided to construct their portfolio with in-house investors. And so the team that started Charles Bank was really the direct private equity investment team of Harvard. I joined the Harvard team one year before we spun it out to create Charles Bank.

• 13:33Ted Seides?

  So under Jack Meyer, what was that dynamic like when these internal asset managers all started spinning out at the same time?

• 13:41Speaker 02

  It was fascinating. I mean, it was great to have a front row seat to that evolution of Harvard's endowment. From a timing standpoint, we were right at the leading edge of a part of Harvard's endowment operation balkanizing into private investment operations. So when I joined, Jack was the boss of every investment team. He would show up at our weekly staff meetings. He was an exceptional investor and had this amazing ability to just see through the risk-adjusted return that people were debating across a very wide range of asset classes. So it was an amazing learning experience. And then when we started to spin out, it was our private equity team. There were some public equity teams that spun out. There were some private credit teams that spun out. And so there was a lot of news about why it was happening,

• 14:26Speaker 02

  whether it was better for the university, not better for the university, but it was an amazing time to be part of that transition.

• 14:32Ted Seides?

  That was a long time ago. You said 27 years under the same umbrella. I'd love you to bring me current by talking about key reflection points along the way.

• 14:43Speaker 02

  If I were to give you the most important plot points of our firm's evolution over this period of time, Harvard was a deep believer in finding value in investments through superior research. So in terms of where they wanted their investment edge to come from, it wasn't about having a better sourcing model or a better operating toolkit. It really was around doing superior research and therefore having differentiated conviction and using that conviction to uncover investments that are misunderstood and therefore mispriced. Now, in the early days of Charles Bank's history, and while we were part of Harvard,

• 15:25Speaker 02

  sometimes that inclination to find misunderstood and therefore mispriced assets would get arithmetically translated into, let's look for things that are in a certain multiple range. The problem with that type of simple heuristic where you go for certain multiples is that especially given the dynamic evolution of the private equity industry over this last couple decade period, it's often the case that it's not dynamic or nuanced enough as a way to really think about value. And so we tend to think about our firm as a manufacturing process where the atomic unit of production is a decision. Now, some of those decisions are our final investment decisions, but really everything we do leading

• 16:07Speaker 02

  up to a final investment decision is the production of a decision. Which industry should we think about today? Within those industries, which themes are attractive? Within those themes, which companies should we focus on? How should we staff ourselves with industry expertise to really develop differentiated conviction? The atomic output of all of those workloads is a decision. So the question for us is, how do we make that manufacturing process of producing decisions as high quality and as efficient as possible?

• 16:38Speaker 02

  And I'd say perhaps the number one area of evolution and continuous improvement that we will indefinitely work on is how do we define getting value or identifying mispriced investments in a dynamic and nuanced enough way such that we can sustain a competitive advantage?

• 16:57Ted Seides?

  How did that evolve from the simple heuristic of cheap to how you look at value today?

• 17:03Speaker 02

  First of all, I'd say we always were engaged in a set of very complex activities to get beyond just understanding the entry multiple of an investment. Now, having said that, the entire private equity industry, for the most part, tends to think about one single metric to at least have a headline sense of what the value of an investment is. And that metric is total enterprise value divided by EBITDA. The reason why that came into place in the first place is that it's supposed to be a proxy for the inverse of the cash yield of owning an asset. So if we were to pause it for a second, for simplicity, that EBITDA is equal to cash flow. It's not, and that you could, in fact, dividend all of the EBITDA

• 17:48Speaker 02

  or cash flow of a business to yourself every year. You can't. Then total enterprise value divided by EBITDA would basically be the inverse of the free cash flow yield of owning that asset. Now, because private equity has evolved so much from the early days where that actually was true to today where private equity portfolio companies are by and large exited to other buyers. So they're not really being sold on free cash flow yield. There's been a huge evolution in the valuation ranges that are applicable to private equity transactions. And so what we decided to do was to expand our view of what the underlying value of an asset was from the simple snapshot of how much free cash flow is generating at a point in time

• 18:32Speaker 02

  to a point of view around, within the first two years of our ownership, what is the probability distribution of earnings that we might be able to generate using our toolkit?

• 18:44Ted Seides?

  I'd love to walk through the lens of that manufacturing of decision making. And at the highest level, how have you thought about the optimal decision making unit?

• 18:57Speaker 02

  We have a phrase at Charles Bank. It's called mission atomization. We regress our investment results against all these different metrics. Going in multiple, exit multiple, inorganic growth, organic growth. One of the things we analyzed was, gee, you know, what percent of our human workloads go into what type of activity? And as we analyzed it, one of the things we observed is that there's just a lot of workload creep. Five people get into a meeting. There may be a stated mission for that meeting, but the meeting will evolve into something else. We'll start talking about things that weren't really related to that initial mission. And so atomizing workloads where we say, look, X number of people are going to do some amount of work,

• 19:39Speaker 02

  but the goal of that activity is a tangible thing that we're going to try to accomplish. We now sit down in meetings and we say, okay, what's the prize available in this meeting? We try to be super explicit about it. And as we zoom out to how we try to systematize that, we operate in sector teams at Charles Bank. And within each sector team, there are stage gates of work, after which people have to check back in. So a stage one workload is one where a couple of people can spend a certain number of hours exploring an idea. But after those certain number of hours are done, they have to come back to a group and say, gee, you know, we did this work. Here was the outcome of it. Should we continue working? So creating incremental checkpoints so that we don't have workload creep without clear missions is one of the things we're working on.

• 20:22Ted Seides?

  What are those different stages as it relates to deciding when to dive into a company or an idea?

• 20:29Speaker 02

  Within our origination and sourcing process, there's typically three stages. There's no real genius to how we staged gated them. It's really something pretty speculative. Anybody can work on, but it's a pretty small number of hours that will authorize for that. And then in order for it to become something where we're spending more than 20 person hours, we want a certain number of checklist items to be reviewed. So is it a viable theme? Do we actually have a shot at generating something within the next year or so? Once that stage gate is done, then we really want a lot of conviction that there's something where it's worth really are focusing a bunch of energy.

• 21:09Ted Seides?

  When you've run the regression analysis over all the different aspects that go into your investments and investment success, how did that translate into how you started to focus the firm?

• 21:22Speaker 02

  If you go back a decade or so, our primary modeling tool for assessing the attractiveness of an investment was a five-year LBO model. Now, even back then, we recognized that the five-year LBO model is highly flawed. Let's just say that you and I could review every five-year LBO model that got approved at an ICE five years ago. Let's just say we could look at that today for all North American buyouts. And let's say we could compare the dispersion of the outcome of those models with the actual outcome of those companies that received the investment. I am pretty sure what we would find is that the actual outcome dispersion would be way greater than the five-year LBO models that got those investments approved.

• 22:07Speaker 02

  I'm also fairly certain that we would find that the base case outcome of those five-year LBO models would be something like two and a half to three times multiple of invested capital. And then there would be some scenarios for all these firms that approve these models. And some of the scenarios would be conservative cases, and there would be some upside cases. But we know that the actual dispersion would be way wider. So the question for us is, well, we're using a highly flawed tool that actually promotes all kinds of predictable human biases. There's anchoring bias, there's familiarity bias, to make a decision that is inherently very difficult to make. Because what we're really doing is we are underwriters of a very uncertain future probability distribution.

• 22:49Speaker 02

  And so the decision manufacturing process is actually not a high-quality decision manufacturing process. And so we tried to develop a tool or a modeling regime that would be closer to the task we're actually trying to accomplish, which is to describe an uncertain future probability distribution of outcomes with as much asymmetric knowledge that we can bring to bear. This is where our research and our value creation plans come into play. And then use a differentiated perspective on favorable probability distributions that might exist in certain companies to curate a better portfolio. We have, as a result, shifted all of our modeling to a homegrown proprietary tool that we call our two-year Fan of Outcomes.

• 23:33Speaker 02

  It's basically a fairly simplified Monte Carlo analysis. It runs 10,000 simulations of the two-year forward future of any given investment. We inform it as much as possible with what we intend to accomplish with that investment. And I'd say that's been a pretty big unlock in terms of our ability to curate better investments into our portfolio.

• 23:53Ted Seides?

  How has the Fan of Outcomes impacted your investment decisions?

• 23:57Speaker 02

  The model is just a tool for us to think better and work better together. The model doesn't give us any answers that we can't generate as human beings. We just think it makes that process more efficient. And so if we were to just crack apart the different benefits of this approach, the first one is talking about two years versus five years. When we ran our regression analysis, our ability to grow the pre-tax earnings of a company within the first two years of our ownership was highly correlated and very predictive of ultimate investment success, no matter how long the hold period was. Now, that's a useful insight as opposed to some less useful insights such as, gosh, our investment success is really correlated with management quality.

• 24:41Speaker 02

  You don't really know management quality when you first come to an investment. You actually develop your view of their quality depending on how that investment's going. So that's sort of a spurious correlation. The fact that two-year EBITDA performance is actually predictive of ultimate investment success is a very useful insight because we can think about two years way better than we can think about five years, especially if we force our teams to crack the first two years into year one and year two. And one of the things that we witnessed happening was that there is a much higher degree of accountability to the team's modeling. So if you were my investment committee, Ted, and you said, okay, build me a five-year LDO model. I would almost come at that exercise with a resignation that there's not going to be

• 25:26Speaker 02

  a lot of precision embedded in it. There's probably a lot of straight lining going on. But if you ask me to build you a two-year LBO model on an investment that might get done in the next month, I'm now thinking, gosh, in three months, I'm going to be defending a pretty high percentage of what I'm putting in front of Ted. And so that increase in accountability was very noticeable. People started to think very hard about what inputs were going into the model, just because of that dynamic. The second thing is, we always have, for our entire history, thought about what are we going to do differently with an investment? The planning exercise of what we were going to do with investment was largely divorced from the five-year LBO model, because in a five-year model, you're straight lining a bunch of things. But now, we're actually inputting very, very specific probability

• 26:10Speaker 02

  distributions of improvements we intend to make. And so, when we separate the different beneficial impacts of it, the greater accountability, our ability to be much more specific around elegantly unifying our value creation plan with a modeling exercise, those things were immediate unlocks. The thing that took a little bit longer was getting our teams to think probabilistically. So when we first did this, what did we do? We went back to old habits and we said, well, let's look at the 50th percentile case. Translation, old B's case. Let'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

• 26:55Speaker 02

  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 result in a greater than 30% IRR over two years? What 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?

• 27:36Speaker 02

  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.

• 28:00Ted Seides?

  What are some of the ways that the modeling approach changes how you think about risk?

• 28:05Speaker 02

  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? And 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

• 28:47Speaker 02

  to put the recession arbitrarily at any point in the five-year time period. And so they'll say, well, we 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. It'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's 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,

• 29:30Speaker 02

  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 LBO model might look Just as good as something that we are approving. But 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.

• 30:14Speaker 02

  Their advocacy was this is an incredibly sticky service. It'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, okay, 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%? 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. It seems reasonable. CIO could move on to another job. The 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,

• 30:54Speaker 02

  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 2/3. So 1/3 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. So 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

• 31:37Speaker 02

  has had, we think, a pretty beneficial effect on the curation of what types of investments we want in our portfolio.

• 31:45Ted Seides?

  We're going to take a quick break in the action to tell you about Brookfield. Brookfield invests in the thing behind the thing behind the next big thing. Their focus across infrastructure, energy, real estate, private equity and credit is helping to build the backbone of the global economy. Brookfield combines deep operational expertise with disciplined, long-term investing, uncovering value and partnering alongside clients to shape tomorrow's economy today. Invest in the businesses that shape tomorrow. Learn how you can own what's next at Brookfield.com/own.

• 32:22Speaker 02

  This is not an offer to sell or investment advice. Investing involves risk, including the loss of capital.

• 32:28Ted Seides?

  And now, back to the show. How did using the model inform where you search for investment opportunities?

• 32:37Speaker 02

  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.

• 33:20Speaker 02

  So, 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? How 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.

• 34:06Speaker 02

  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.

• 34:28Ted Seides?

  Where have you found those types of companies that offer that asymmetric profile?

• 34:34Speaker 02

  One 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

• 35:17Speaker 02

  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. Oftentimes, 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 USCPA 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

• 35:59Speaker 02

  retention. If you've ever thought about how hard it would be for you to leave your tax accountant, you'll know what I'm talking about. And There's really minuscule private equity penetration into the US 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

• 36:42Speaker 02

  revenue technicals, strong resilience across a bunch of different types of macro environments. So 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.

• 37:12Ted Seides?

  What were some of the other success factors that you found from your historical investing?

• 37:17Speaker 02

  We regressed earnings growth against returns. Unsurprisingly, it's very correlated. We 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.

• 37:59Speaker 02

  Another one would be that we used to think that management stability. Would be very correlated with investment success. And 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.

• 38:43Speaker 02

  And so that was another interesting insight that came out of that.

• 38:46Ted Seides?

  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?

• 38:56Speaker 02

  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. Because the underwriting process of generating this fan of outcomes model involves such specific inputs around what we intend to do to improve the business.

• 39:39Speaker 02

  The other thing I would say is we consider ourselves producers of decisions. We're professional decision makers. It's not just the 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 a fan of outcomes look like in terms of upside EBITDA contribution relative to risks of that decision? We 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 a fan of outcomes look like on making two or three critical hires in the go-to-market organization?

• 40:22Speaker 02

  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. So 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

• 41:07Speaker 02

  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.

• 41:21Ted Seides?

  What are some of the challenges that you've run into either internally or with portfolio companies of trying to inculcate this thinking?

• 41:29Speaker 02

  Seth Klarman talked about this on your podcast, Annie 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 back testing and refining the model, but sometimes we end up in tail scenarios relative To our distribution and just being clinical and then giving our teams permission to say,

• 42:12Speaker 02

  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. And 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.

• 42:55Speaker 02

  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 K simulations, that's been another challenge that we've been working on.

• 43:08Ted Seides?

  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.

• 43:18Speaker 02

  That's an area where we're trying to tread very lightly. In 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.

• 43:49Ted Seides?

  As you've increasingly applied this to your decision making, how do you get a sense of whether it's working?

• 43:57Speaker 02

  Great question. Well, the number one report card for us is the performance of our portfolio and portfolio construction. And we've been in business for over 25 years as Charles Bank. I think we've generated 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

• 44:41Speaker 02

  focus, even before we close the investment on accomplishing that two-year enterprise value growth. So 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.

• 45:06Ted Seides?

  How do you use that decision process to consider your business strategy at Charles Bank?

• 45:12Speaker 02

  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. When 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. Really thinking

• 45:56Speaker 02

  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

• 46:40Speaker 02

  mispriced relative to their two-year forward trajectory that we can unlock.

• 46:44Ted Seides?

  So from that long history of middle market buyouts, how did you decide to extend into the adjacencies in credit and technology opportunities?

• 46:52Speaker 02

  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.

• 47:32Speaker 02

  The 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.

• 47:56Ted Seides?

  I'd love to hear your thoughts on the landscape and maybe how you might be thinking about it either somewhere earlier differently than others.

• 48:04Speaker 02

  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. But 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 fund 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

• 48:47Speaker 02

  companies in this category, focused private equity ownership is just a really advantaged form of ownership. Take 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

• 49:30Speaker 02

  and then for the focused ownership of private equity to create advantaged forms of being in that type of industry as a consolidator or as somebody who provides superior customer service or whatever. We 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 US such that there's a good runway. The other thing that we think has happened is that even though multiples have gotten over the last 10 to 15 years pretty divorced from free cash flow, 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.

• 50:12Speaker 02

  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. That'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, but at this new level of where multiples are being capitalized in the middle

• 50:57Speaker 02

  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.

• 51:30Ted Seides?

  What concerns you about the industry going forward?

• 51:33Speaker 02

  Because of the way the leverage markets work, and certainly now 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. So those are generic risks

• 52:16Speaker 02

  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.

• 52:25Ted Seides?

  What are you most excited about?

• 52:27Speaker 02

  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 back test 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. So that's something we're pretty excited about.

• 53:04Ted Seides?

  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?

• 53:12Speaker 02

  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.

• 53:30Ted Seides?

  What was your first paid job?

• 53:33Speaker 02

  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. So I would go to their homes, tutor these kids for roughly $10 an hour.

• 53:48Ted Seides?

  What'd you take out of it?

• 53:49Speaker 02

  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. So I tend not to take that for granted.

• 54:20Ted Seides?

  What's your biggest pet peeve?

• 54:22Speaker 02

  I'd say it's the state of wireless coverage in the US. 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.

• 54:57Ted Seides?

  How's your life turned out differently from how you expected it to?

• 55:01Speaker 02

  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.

• 55:27Ted Seides?

  What's a mystery you wonder about?

• 55:30Speaker 02

  So I recently read this book, In My Time of Dying by Sebastian Junger. It's fascinating. In 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.

• 56:12Speaker 02

  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. And 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.

• 56:41Ted Seides?

  All right, Mike, last one. If the next five years are a chapter in your life, what's that chapter about?

• 56:47Speaker 02

  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. I 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,

• 57:32Speaker 02

  all of the deep research and pattern recognition that we have as a result of that. We have an incredible network of executives. 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. That seems like a really worthy goal and something we're super focused on working on.

• 58:11Ted Seides?

  Mike, thanks so much for sharing this interesting framework for thinking about investing.

• 58:15Speaker 02

  Thank you for having me.

• 58:17Ted Seides?

  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.