What are Your Thoughts on Yale's Recent Study?

As probably the most well-known search investor to graduate from Yale School of Management###-###-#### and the lead investor in the first Yale School of Management graduate who searched, operated, and exited (Kalil Diaz, CCD), I was interested and excited to see SOM's continued leadership in the search fund space with the publication of How are Search Fund Investors Really Faring? I heartily agree with what I take to be the goal of AJ and the other authors here, even if I want to point out some ways in which the study falls short. Search is going through major growing pains. $1 billion invested in the space every three years is hardly the pass-the-hat amongst a few friends approach that Irv envisioned at the start, and made so many of the first search funds feel like one big happy family. We currently have a Stockdale Paradox for both new investors and searchers—how to maintain unwavering faith in a positive future outcome while simultaneously confronting the most brutal facts of your current reality. Much of the growth in search is based on the Stanford Study’s rosy picture of returns, a picture that has many complicating factors, such as not weighting the data by capital deployed, not giving us the ability to measure how returns have changed over time, and not providing hard return data from investors. The truth is that many searchers entering the ecosystem today will not achieve the Stanford returns, nor would a virgin investor without a lot of sophistication and deal flow come close to those returns. There is froth in our market, and if AJ has successfully corrected that to some extent, I applaud him. We all need some brutal reality, new entrants most of all. I have no doubt that all the data used and the math done are correct. My issues have to do with framing and what I see as important and special about search, most of which I assume AJ and his team would agree with, and in some sense take for granted that the reader already understands. I am just going to repeat all that here to make sure that the cold hard data is taken in the context of an investment class that is still uniquely great, even if it is going through a fundamental coming of age crisis. *** Before going through my analysis below, I wanted to share a few observations from friends who read an early draft of my response to the Yale study. One who did have a greater than 10x return on his deal pointed out, “Search is among the hardest things anybody will ever do. The 25% carry granted to a single searcher who has zero capital and (probably) zero CEO experience is the most generous deal out there > but they earn every penny of it.” Another friend who exited around 4x, slightly under the Stanford average, who reflected on a long hard struggle with his search and company as “still worth it and it was still an amazing experience and I'm super grateful for.” He went to say, “I wouldn’t want the [Yale Paper] to dissuade an aspiring entrepreneur from doing one of the most meaningful things they'll do.” And an experienced investor in the space who reflected on the importance of tying the empirical data back to the human element: “The original roots of the model — mentorship, alignment, humility, and hands-on collaboration — are under strain. If those foundations erode, so will returns.” *** To review what AJ and the folks at Yale did: The study uses 1,192 investment observations—over $700 million in investment dollars—to take a deep dive into actual investment returns, uncovering surprising results that deviate substantially from the Stanford Study. The Stanford study is designed to capture all returns, not just a sample, but it has the weaknesses outlined above. The new Yale study approach is to use a large sample (14% of the Stanford Study) to examine returns from a different perspective. While, again, I understand and at a fundamental level agree with the motivation of this piece of academic work, I have some fundamental disagreements with some of its conclusions and certainly with the overall impression it leaves out of this context. My criticisms of the study's method are three: no time horizon to locate the data in history, no data on how long each investment was held, and, from my own personal experience and knowledge of other significant search investors, the results of this sample do not feel truly representative. Here are my brief thoughts on each of these points. No time horizon. At a time of massive explosion in the asset class, I am most interested in the impact of that expansion on returns. The data here are untethered by time and place so to me that is not that helpful. I most want to understand the impact of the boom on results. No hold periods. I understand you work with the data you are given, and I am obviously a huge MOIC fan, as per my attempt to reformulate the Matlack Formula. It remains a significant weakness in the Yale data, as retrospective IRRs are important, if not in compensation, for measuring returns. I am also somewhat troubled that authors are using companies that have not yet exited at whatever marks the investor puts on them, which, depending on how many of these younger investments are included in the study, could significantly skew returns downward. Sniff Test on the Result. The paper reports a fully weighted average MOIC of 2.5x across all dollars invested in the sample. If I look at my own experience and that of many other search investors whom I know well enough to trust what they tell me, this is a lower return than any of them. I believe the data here is true, I just don’t believe it is representative retrospectively over any chunk of time. Again, going forward is a different story. *** The fundamental issue at hand for all of us is that the search ecosystem has undergone a dramatic change in the last ten and even five years (which the authors point out at the top, noting the vast capital inflows), but do not try to examine in the study. The Stanford Study, and attractive returns in the ecosystem in general, have attracted huge amounts of capital, and caused potential entrepreneurs to flock to the space around the globe (international returns, an area where I have done a lot of work, would be another area that would be interesting to examine as in my experience they have been higher because of lack of competition). The result of which has been a dramatic dilution of talent of searchers, much higher failure rate of search funds, and presumably a drop in expected search IRRs and MOICs going forward which is the warning shot that presumably AJ is trying to fire here. This is a maturing in our space like venture capital, private equity, or any other asset class where manager selection is crucial to capture alpha. You must reliably be able to recognize patterns across many reps to tell who a top-decile searcher is and who simply is not, and then have the value-add to get into those top-decile deals. I joked with several partners of a noted search fund of funds that maybe they had underwritten this study (they obviously did not) because the conclusion is that if you don’t truly know what you are doing, you should be getting exposure to the search ecosystem via them, not directly. The study very much underscores their value proposition, especially now if you believe what I have just said about the recent change in environment. *** I have three further areas that I want to reinforce the obvious which doesn’t necessarily contradict the Yale study but simply put it in context: I do not believe that search is fundamentally a “hits” asset class; in the end, especially now, I believe search is about idiosyncratic rather than market risk; and search success is heavily impacted by the team mentoring the new CEO. I will take them in order. This is not a hits business. I came to search after two prior careers: as CFO of a large media company and as a venture capitalist. Both prior experiences influenced why I went all in on search fund investing, serving on boards, thinking deeply about compensation, etc. As we all know, running a business is really hard work (IMO, the hardest). I have my own scars to prove it from my time as CFO of The Providence Journal, despite taking the company public and selling it. I had one giant grand slam homerun VC investment, a company called Art Technology Group, which I take as beginner’s luck, in the late 90s, before raising VC funds in 1999 and 2000, perhaps the worst vintage years ever, as we started a couple of dozen companies right into the teeth of the market collapse. This is the source of my scars from having to build real companies from the ground up, with no get-out-of-jail card—no stupidly high valuations —in the VC world. And the devastating process of going to the founders and all their employees, again and again, to shut down 70% of the portfolio companies that didn't work. I learned a ton, but it cost me a decade of my life to produce modest returns for my investors. In 2010, I began investing in search at the suggestion of perhaps my closest business friend and mentor, Will Thorndike, because I felt I could apply my learnings in operating a business and starting a bunch more, while playing just not to lose rather than having to swing for the fences all the time. And in my personal sample of perhaps twenty total search investments, that has in fact been the case. The whole attractiveness of the model, to me anyhow, is that you find a smart, energetic, high character young person with a top business education to help them find an unbreakable boring recurring revenue business that she is able to convince the founder to sell to her at a low multiple of EBITDA, you coach her up to build her team and the business, you double EBITDA and sell at a much higher multiple six or seven years later. Sure, maybe there are a handful of Asurions in the ecosystem, but that is not what makes it go and are fundamentally not what this is about. If this works it’s because it is very hard to lose your money, and as an investor you pick the right searchers and support them to be able to generate 3-5x your money most of the time. I fundamentally disagree with the concept that you have to capture 10x deals to make an attractive return in search. Even in the Yale data itself, the highest average return investor had no 10x deals. This has, in fact, been my personal experience. I haven’t ever made 10x on a search investment but am extremely happy with my returns. Search is about idiosyncratic rather than market risk. I very much appreciate all the academic math in the study. As I have noted elsewhere, math is my native tongue and in many ways my biggest advantage in business, for which I have my time at Yale SOM to thank. But sometimes the deep statistical analysis doesn’t tell the story of what is happening on the ground. The reality, in terms of my own process in the search ecosystem —and, in fact, running a VC for a decade before that —and even as an operator who had to hire tons of people, is that the risk here is 99% idiosyncratic—by which I mean is a unique judgement call not correlated to anything else, subject to market forces or Yale analytics. The bet is always on a person. I have always worked with people, invested in people, and judged them in face-to-face interactions seeking out those that I intuitive sense are talented, trustworthy, and high potential. As with any asset class, Alpha means generating returns far in excess of what market risk, or Beta, would imply. Search is an intensely human encounter. In most of my deals anyhow, the actual company we bought was far worse when we got inside than we thought it was. And our CEO knew even less about how to lead our company than we hoped. But success was generated over time because we picked the right athlete who was brilliant and trainable. A crucial part of search success is the team mentoring the new CEO. To me search investing is fundamentally a bet on yourself. And a commitment to being a mentor who loves the search CEO so fiercely you will not allow them to fail. If you are not going to roll up your sleeves and do everything humanly possible to make this person a success, then please invest in Amplify SG or Paltus Capital, both firms I work with and have deep expertise and deal flow to generate top decile returns, or for that matter you can invest in market leaders like Pacific Lake and Anacapa to get even broader exposure to the asset class. To me the special—even sacred—part of search which distinguishes it from any other investment or business ecosystem is the extent to which people go out of their way to help each other. Searchers help searchers, and search investors invest in developing people for the reward of watching a young person blossom into a great leader as much as the MOIC. This is altruistic, and it’s also a way to control your own destiny as an investor. The issue isn’t how the stock market, or even the search fund market, is doing. It’s how well can I mentor this specific searcher in this situation to find a good company, to buy it well, and then teach them over months and years on how to become a great CEO. This process is about far more than making money, though that is a happy byproduct. It’s about sitting at the closing dinner when the CEO is ugly crying because he has overcome the certain death of his company more than once to get to the big exit he never really thought was going to be possible. *** AJ and the authors of the Yale Study know all the above and probably agree with me on most of it. AJ has devoted his life to teaching aspiring searchers for goodness' sake. And, again, I am all about confronting the most brutal facts of your current reality, especially if it clears the field a bit of people who should not be searching and investors who should not be directly investing. But I also want to make sure we don’t throw out the baby with the bathwater. In the end, search is about unconditional, and often very tough, love of young people who are exceptionally talented but know next to nothing about buying and running a business. Our job is to teach them, correct them, and love them fiercely with the understanding that if you do all those things well, your returns will follow, even in an ecosystem that is growing and changing rapidly.