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Capital Allocators – Inside the Institutional Investment Industry
[REPLAY] Alex Abell - Lower Middle Market Buyout Investing at RCP (EP.383)
00:56:30
Alex Abell is a Managing Partner at RCP Advisors, which at $14 billion of committed capital, is one of the largest firms focused exclusively on lower-middle market buyouts. Alex has spent twenty-three years in the business, starting on the LP side,...
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- [00:00]
Alex A. Bell
Foreign.
- [00:05]
Ted 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@capitalallocators.com 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. My guest on today's sponsored insight is Alex A. Bell, a Managing Partner at RCP advisors, which at $14 billion of committed capital is one of the largest firms focused exclus on lower middle market buyouts. Alex has spent 23 years in the business, starting on the LP side, building Atlas Diligence, a research and advisory platform focused on advanced analytics, and then merging Atlas with RCP a decade ago. Today he helps manage RCP's research efforts, its customized solutions and advisory services. Our conversation covers Alex's path and lessons learned investing in lower middle market buyout funds across, assessing managers with data benchmarking, blending quantitative and qualitative factors, and applying insights to primary and secondary investing. Alex and I just scratched the surface on what's possible with analytics in the private markets. If you'd like to learn more, reach out to alex directly@alexcpadvisors.com before we get going. Capital Allocators has entered the world of AI. We've trained a large language model on all our transcripts to help you learn anything want from seven years of conversations. We've affectionately called this model ChatGpted. It's safe to say Hank Morgan and I have no idea how to build an LLM, train data and get the outputs that ChatGPTed delivers. So a special thanks goes to our friends on the data science team at Atalaya Capital who took on the development of the minimum viable product from start to finish. What they've done for us barely scratches the surface of on how they're using AI to enhance their investment process, but I'll leave that to you to discuss with them. ChatGpted is the latest add on to our premium membership. To sign up for a premium membership and access ChatGpted to query all our transcripts, go to capitalallocators.com thanks so much for spreading the word about ChatGpted Please enjoy my conversation with Alex Abel.
- [03:07]
Alex, thanks so much for joining me.
- [03:09]
Alex A. Bell
Very happy to be here today.
- [03:10]
Ted Seides
Well, why don't you take me back to how you got into this business in the first place?
- [03:15]
Alex A. Bell
I started doing work investing in private equity as a limited partner. Going on 22 years now. So long time. My first job doing this was out of business school. I went to Stanford for business school and took a job with Hewlett Packard's pension fund. So small investment group at HP Corporate that was managing about a 6, $7 billion pension fund. And I think partly because they were located in the Valley, we had a tremendous amount of exposure to equity generally, but also venture capital more specifically. They've been investing in alternatives for probably 20 years, had a great track record, and for me, frankly, it was an amazing place to start a career doing this type of work, as I was working for some of the people that have been doing this from maybe even the beginnings of the industry, we might say. So it was a fantastic learning ground for me as I started my career out of business school.
- [04:05]
Ted Seides
And what was your path from those initial years at hp?
- [04:09]
Alex A. Bell
After Hewlett Packard, I took a job with a fund of funds platform, a firm called Quellos Group that was based out in Seattle. They originally started as a hedge fund of funds, but they decided they wanted to move into private equity as well. This was also a very unique and in some ways fortuitous opportunity for me from a professional development standpoint. The folks that they brought on to run what was a new private equity platform were folks that ran Duke University's dumac, the management company that manages the endowment assets. It was the chief investment officer who had actually founded dumac, head of private equity there, Sally Shipping Russell. And they had a track record that went back again, 20 plus years of relationships doing this in private equity, traditional buyouts, venture capital, as well as other areas like real estate and real assets. So for me, again, after hp, I got very lucky to have found myself in a group where it was a tremendous learning experience. And Quellus itself had developed a really interesting platform that would become very relevant later on in my career. It was a database, but it was a very sophisticated database. Nothing that I'd ever seen before as it related to manager research. So that database ended up sparking ideas later on in my career about building something better for other limited partners. Then eventually, Quellos was an attractive asset management platform. It was acquired by BlackRock. I became part of BlackRock's alternatives platform. And then more specifically, I started working within what was called BlackRock Private Equity Partners, which was the private equity platform. Again, great experience. I was able to do a lot of the same stuff we were doing at Quellos, then had a whole set of colleagues that were doing investing, I would say a little bit more on the bigger side of the private equity worlds. And there we started again to incorporate this database into the BlackRock platform as well, and started to really develop and try to think about unique ways of evaluating managers. Not just on the quantitative side, which ultimately became very important, but also on the qualitative side, how to grade and evaluate characteristics of managers that had the highest probability of outperformance in those early.
- [06:14]
Ted Seides
Years of the corporate pension experience and then the fund of funds experience into a large asset manager. What were the differences that you saw in how the different types of pool of capital would address this space?
- [06:25]
Alex A. Bell
I would say that the differences between sort of a more specialized entrepreneurial fund of funds platform like Quellos and the larger private equity markets type platform like BlackRock was that Quellos was very happy to have very specific strategies that they believed, whether it be on the hedge fund side or in our case the private equity side, and then finding clients that fit those strategies that said this is what we want, whether it be smaller market investment or venture capital. I think that for BlackRock, the platforms at larger asset management firms like that are trying to create solutions for everybody, or at least a mass appeal market. What that does though, is that theoretically, and I think some ways, practically changes the risk return behavior of your investing. We were doing at BlackRock, larger investments on the fund side, larger investments on the co invest side and secondary side. And that part of the market has historically generated less returns and certainly in a less risky way as well. The biggest change for me was a broadening of strategy outside of what we had been used to in a much more smaller, niche based company.
- [07:33]
Ted Seides
So when you were looking at the breadth of different strategies, all different types of managers, you sort of mentioned a research process and data aggregation. What did you want to do with it?
- [07:44]
Alex A. Bell
Yeah, I mean, one of the things that Quellos had done was created a proprietary database that was really amazing. And unfortunately for them, they did it before things like Salesforce existed. And so they spent a lot of money to develop something that was unbelievably useful. We used to have a philosophy at the firm that if it wasn't in the database, then it didn't happen or it didn't exist. And what was great about it was it created an institutional market intelligence. So we had meeting notes that went back 10 years in some cases. For us, it was a way of keeping track of managers to keeping track of data as well track record data, historical and current, as well as keeping track of what I'll call more qualitative market intelligence about their strategy, about their team, about what they said they were good at. So that when you meet with managers, when their next fundraise, maybe after you turn them down in the first fundraise, you can see what they said three or four years ago and then compare it to how they're pitching themselves today. So all that sort of institutionalized knowledge wasn't sitting in people's notebooks and it was sitting inside of an electrical database that all of us could access, regardless of whether the people that had had those meetings were still with the firm or not. And that was a really significant difference from a lot of the other organizations I'd ever worked for. And as Quellus started to grow and Also again, as BlackRock acquired it, one of the things that I found lacking in it was that we were still stuck analyzing track record in the way that the private equity professionals on the limited partner side have been doing for probably decades, mainly on vintage year benchmarking. Vintage year benchmarking was the best useful tool given the data that most people were collecting and had. So fund level returns, how do we compare that to in most cases? Historically, Cambridge's big consultants fund level aggregated returns across multiple managers. And how did a manager that started a fund in a specific vintage year due to all the other funds that started at the same time. And that was in some ways the best we could do on the private equity side to benchmark the public equity markets. And even fixed income had many more ways to do it in a much more sophisticated way, including incorporating things like risk into that equation, which on the private side, all private equity limited partners, I think, think about risk. There weren't the types of metrics that had been developed on the public equity side. So things like a Sharpe ratio doesn't exist in private equity. And so we do it through other means. But it was all relatively unsophisticated at that point. And we're talking about now over 10 years ago. Still, I felt like there was interesting different ways that we could use to do a better job of trying to figure out whether a manager has outperformed their peers in deals that were done at similar times. But to do that, you had to have a lot of data, and that was the key.
- [10:38]
Ted Seides
So you had the data inside of blackrock what did you do with that when you went to create what became Atlas Diligence?
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Alex A. Bell
I couldn't take that data with me, so we had to recreate it right. So more importantly we had to make sure that we were collecting the right data. So there was tons of data that we would collect on managers that we were doing deep level due diligence on at blackrock. So we would track their operating performance of the underlying companies and how well those managers had done at increasing performance in the operational level, not just the mark or their performance at a cash on cash level, for example, of each deal. But we weren't tracking that kind of data systematically for all the other managers that we didn't invest in, which was the vast majority of the universe that was out there. So Atlas Diligence, the idea and the goal was to create a platform where we could create a similar type of database. The idea behind it at least that was a sophisticated, extensive database that would be a tool in blackrock and Quellos. This was a tool that we used as investment professionals to do a better job of tracking the market evaluating managers. The problem is that for most limited partner organizations, even sometimes a very large institutional platforms, they don't have a huge staff like a private equity fund of funds does. They might have two or three people working on investing $10 billion and that's usually across multiple markets. So usually different types of strategies that are included in their illiquid alternatives allocations. So the idea that I had when I founded Atlas and left BlackRock was to create a similar type of tool that could be used not just by the Blackrock's of the world, but could be used by a $3 billion endowment who was trying to do better alternative investing and had one person who was the head of alternatives covering hedge funds and private equity and venture capital and provide them with a that would allow them to screen the market much more effectively and then have advanced ways to analyze those managers at their fingertips, even if they didn't have a large staff to go ahead and do that for them. That was the sort of thesis behind Atlas Diligence. And when I found that it maybe the most important component of it was what I was going to focus on. So my grand vision was, oh, I might do the whole private capital world, but there's big parts of the private capital world, especially big market buyout for example, where this type of tool isn't as useful, there's less firms to cover. And if you're doing very large checks into some of the larger players like a KKR or a Blackstone, you probably don't need this type of tool to cover that part of the market. And so that was why I decided to focus our energies at Atlas Diligence originally on small market buyout. That made a ton of sense. And frankly, historically it is the most attractive part of the private equity markets from a returns perspective. And so when we created Atlas, we were focused on trying to create a value add tool in the most value add part of the market to help provide market intel. And information was the smaller part of the market.
- [13:43]
Ted Seides
So as you built that up, what was the scale of what you had in the database at Atlas?
- [13:50]
Alex A. Bell
At first it was small. The good news is we had some institutions that I knew that were early clients of ours that we could use their name as a way of saying to managers, hey, we have people who are going to subscribe to this tool and this is going to give you a way to reach those potential LPs in your fun. Now what we didn't do was we made sure that all the analysis was objective. And so for a couple years we started building up that market intelligence and data. We were trying to cover at that time, over a thousand managers, but over time we were able to create a platform that had a nice login for our clients where they could come in and essentially get a library of investment members demos that frankly was just a huge time saver. And our clients were sophisticated LPs. They were folks that knew how to do a lot of the analysis, but they were very resource constrained. So how do we provide leverage for folks that want to do it themselves but don't have the resources to do this on 500, 700, 1000 managers? So that was the biggest, I think, value that we had created at Atlas was allowing a overworked LP to help them better cover a part of the market that they valued.
- [15:00]
Ted Seides
What were some of those different analytical tools that you used to make those assessments?
- [15:07]
Alex A. Bell
What we started doing was thinking about evaluating a manager's performance, not just simply on the fund level returns, which of course are important. So don't want to make it seem like that's not something we look at. But at the end of the day, a fund is a collection of deals and the deal level performance allows you to have a much more specific way to compare that manager to other private equity deals that were going on at the same time. Let's say you're evaluating a private equity manager in the healthcare space and they did a healthcare services deal and you could look into your database and say, I want to find all the healthcare services deals that are done within a six month period or even a year period of this particular deal that were of a similar size. So let's say it's an $80 million enterprise value, small company, family owned business that was acquired. We want to match the size, we want to match the sector, we want to match the timing. Let's say the performance of that deal is a 3X. Now on the surface that looks like a great deal. They tripled money on that deal. That's usually what most private equity firms are trying to underwrite too. But if we were to look at the benchmark, let's say we find 35 deals in our database that look very similar, done around the same time. And let's say the median was 3.2. Well, all of a sudden that 3x, when you put it into context, tells you that over 50% of the deals done at the time actually did much better than that. And you can be more specific than just looking at median. So the idea was, as it relates to things like track record, was to say, look, a vintager benchmark has some significant flaws in it. First off, it puts against managers that have started their funds at similar times. These are managers that of course are investing over a two to five year period, depending on how quick or how slow they invest. And it doesn't really match timing. And the whole point of a benchmark frankly is to match timing of when investment dollars are going to investment. And how would they do if you had just invested in the market or other deals? So timing is an issue. The other issue is the number of observations. So even the best benchmarks that are doing fund level, vintage or benchmarking data have a limited number of observations. And more importantly, you can make it more specific and break it down by size of fund or break it down by strategy of fund. If you're not doing that and you're comparing a health care fund that you're evaluating to an index that might have seven consumer oriented funds, three tech funds, seven generalists, you're not really comparing strategy wise because the investment dollars that go into a deal in the tech side on any given time might be very different than what's going on in industrials. So when you look at the deal level, you can match up the timing in a more specific way. You can match up the size of the companies that are being targeted and you can match up sector. And you can say with more certainty that this manager compared to all the other private equity firms that are doing deals that look like this at the same time, did better or did worse or did average. And that helps us evaluate the performance in a very unique way.
- [18:18]
Ted Seides
When you create that as a service business, so there's a thousand different funds, you're doing this analytics that's the same analytics off of objective measures across the funds, it's not hard to think a certain small subset of those managers will be deemed the best ones. How do you then deliver that in such a way that you're not saying, well, you really only want to invest in these 50, forget about the other 950.
- [18:44]
Alex A. Bell
In some ways, we do end up saying that. But what I would say is that we're talking a lot about data and benchmarking, track record and things like that. But our evaluation, whether it be what I do today or what we did at Atlas, probably half or more, is actually qualitative. And so the assessments that we do is a mixture of taking information about the team, their backgrounds, their experience, their strategy, and deciding do we like these things? And then using references in a significant way to evaluate these people and sort of confirm a lot of the things they tell us as it relates to what they've done historically and how they've added value to companies. And so for us, I think that the biggest point we always like to make with our clients is that we think that the data stuff we do has a significant differentiation, but it's only part of what we do. What the data does and evaluating these unique ways does is it helps us do a better job of putting into context sometimes all the qualitative things that we are also evaluating. And so when we were in Atlas diligence, we wouldn't put out a top 10 list. We wouldn't put out groups that these are the 50 best. And part of that is because the evaluation of managers has components of preference for different organizations and even different individuals. There might be an limited partner who I respect tremendously, who looks at a firm, looks at the strengths of that firm and the opportunity, and looks at the weaknesses, and can come away with a very different answer than I will. And that's okay. There's certain types of risks that some organizations and some individuals just don't want to take that another organization might be very happy to take. The closest we came to that was we did create somewhat of an objective grading system, both on qualitative measures as well as quantitative measures, which, of course, isn't perfect. There's no way to create any kind of perfect grading system that would be informative to help compare managers against each other on these various criteria. And we had probably 20 major qualitative criterias and a ton of quantitative stuff. And the other thing we did was we created what we call a focus list. The idea of the focus list was to be able to provide guidance to our clients as to where to look for, let's say, the generally best managers. And the way I would think about that is the A managers and maybe the B managers of the world. The A managers are ones that have many strengths and very few weaknesses. The B managers have maybe a more balanced of both, but are still some of the better opportunities. The strengths outweigh those weaknesses on the whole. So those are the types of groups that we were trying to focus our clients towards. And then they can make their own assessments based on the information we lay out in the platform of this is a good fit for us or this isn't, based on those different kinds of risks and criteria.
- [21:35]
Ted Seides
How did you go from having a set of clients as an analytical service business to back to the investing side?
- [21:43]
Alex A. Bell
RCP Advisors, where I am today. A number of the partners there were good friends of mine. We had been investors in some of the same funds. They focus on small market funds, again, focus a lot on smaller market funds. We were on advisory boards together. So I knew them very well. When I started Atlas, I actually went out to rcp. I raised some capital from all limited partner, either institutions or individuals. And I said, hey, would you like to invest in this idea? I have. And RCP itself had been known to have a very good database. And the initial answer was, well, we see you as sort of competitive, Alex, because you're basically providing all these great tools to people to do investing in these part of the markets themselves. When that's essentially what we're trying to do, is provide a platform for us to do it for. Though what they found out over time and what I found out over time is that there wasn't a lot of gray area. There were people that wanted to outsource it or needed to outsource it to someone like rcp. And there are people that were always going to do it themselves. And when they started looking at the clients that I was picking up, they were all folks that they had tried to sell fund to funds to, but who always wanted to do it themselves. And now all of a sudden there was a great platform to help them do it better. And the other thing that started happening was I would start sharing some of my ideas of how to analyze managers to RC and my friend there. And one of my Partners had a backdoor login to my system and we would compare notes and I would get feedback from them, I would share with them, let's say a nuke way. We were benchmarking at a deal level performance. And then six months later I would be in Chicago and I'd visit the offices and my partner John would say, oh, we did what you told us about. And they would pull up on their computer the exact analysis we had talked about that we were building. And the reason was that RCP had been collecting this data for 20 years. And so all the data that we were trying to collect at Atlas and we were think doing a good job, we were starting from scratch. And this was a firm that had been investing in this part of the market for probably about 12 years at that point and had been systematically collecting this data for years. And so that's when we started talking about things like a joint venture, how can we work together? Because all of a sudden what I was building was not competitive but complementary and I could bring these platform. They brought the data and market, intel and a much larger team and eventually it became an acquisition. I was able to join RCP. We brought this platform in house. We call it GBSCout Navigator. GBSCout itself is our internal database here. And we brought a lot of these more unique ways of analyzing managers into our normal due diligence process as it relates to primary fund investing as well as secondary and co investing that we do at rcp.
- [24:21]
Ted Seides
So as you looked at all the analytical tools that you had, all the data that they had, the data that you had, and you bring it into an investment strategy that they had started, where did you decide to focus?
- [24:32]
Alex A. Bell
Yeah, I mean for us the initial focus was, I would say, in two big places. One was primary fund investing because that was the market and that was the product that I was really building. And then the other thing that became very clear was that a lot of the deal level stuff that we were working on was very relevant to co investing. And so there was a convest platform that had been created not too many years before I ended up joining and the performance was great. But the ability to use some of the data in a more efficient way for evaluating deals was very apparent early on.
- [25:04]
Ted Seides
When this comes to assessing managers for investment, what are the characteristics that you've seen through all this data that are indicators of future success?
- [25:15]
Alex A. Bell
What we see is managers that have generally stuck to their strategy over time have produced the most repeatable returns. That seems like a simple answer, but in our part of the market, especially the best managers, tend to grow and they tend to raise more capital. There have been many examples of managers that have continued to perform at extremely high levels, even with larger fund sizes and targeting larger companies. But there's just a fundamental difference between five to $15 million companies and 50 to $100 million companies. And I think one of the things that we have also seen is that there's no magical algorithm. So in some ways it's really the reverse. And let's say a manager tells me in a meeting, well, we bought this company at 10 times EBITDA. That might seem expensive, but everybody else was buying companies at 12 times EBITDA. You might say, well, buying cheap is better, but when you look at the actual data, you do a regression analysis and so maybe you would expect to see the cheaper you bought, the return would be up and to the right. And what we really see is that one, there's almost no relationship and the R squared is close to zero, usually de minimis. And there's a reason for that one is that sometimes cheap deals are cheap for a very good reason. There's a lot of risk in those deals. Main learning from our data is that you have to put the data that we have in the context of what you're seeing in the rest of your due diligence. And so there isn't a magic button you can push that says if you do X and we see X in the data, then there's a very good chance you're going to have good returns in this next fund. But what the data does do is help us provide context and validation, I would say so. For example, there was a manager that we were looking to invest in that was an industrial manager, one that we had invested in over a long period of time. Their valuations that they were paying for deals were starting to go up pretty significantly over time compared to the market. So they were going up in an absolute way, but they were also going up compared to what their peers were paying for deals and what they told us, which I think was a very valid reason, which was they've been industrials for a long time, they've seen cycles, they know that if they don't buy the best assets in the market at any given time, there's increased risk and they believe they could generate better returns by buying higher quality companies, which again, generally will have a higher valuation. And we asked them, what are the characteristics of these higher quality companies? And of course there were qualitative ones like better management team, et cetera, but one of the key metrics they focused on was EBITDA margin. And they said, look, we're buying companies with better EBITDA margin. And we said, okay, let's go back to our data and see that. Because if we look at their data, what we should see is that for every company that they are buying, those companies have higher EBITDA margins than all the other companies that are being bought in the market in the same time period. And what we found was that, yes, the average EBITDA margin increase for these industrial companies was like 900 basis points above the market. Now, 900 basis points is not that much if you're looking at software. But for these industrial companies, that's a big difference. And so what's important is that our data was able to validate that what the GP was telling us about what their strategy was was true. But this is the most important distinction I want to make is it wasn't telling us whether that was a good strategy or not. All we learned was that they believe buying higher EBITDA margin companies, as well as other characteristics at higher prices, was a great way to reduce risk and ultimately generate better returns. But that's only half the question. So we were able to validate that's true. And then the question is, is that actually something we want to do? Do we believe that's true? And then we can sometimes use data to sort of validate or invalidate those ideas as well, which you actually did in this case.
- [28:57]
Ted Seides
One of the questions that's coming up in my head as you're talking about this is about market efficiency. So you mentioned, for example, smaller funds that do well get bigger. Well, that implies that even people that don't have your data have recognized those are good returns. I'm curious what you've seen about your ability to invest in, let's say, inefficient parts of the market, or things where your data is telling you something that other people who don't have access to the data aren't getting because the market's just correct. In assessing both quality of deals and.
- [29:29]
Alex A. Bell
Managers, I would say that comes into play the most with smaller funds in smaller parts of the market, where the number of observations they have in their track record that they have of realized deals where they can say, I actually generated this return tends to be smaller. So if we're looking at a fund and we're evaluating a manager, the most relevant deals that that manager has ever done is the last fund they invested. And when we're looking at that fundraise, they generally have 80 to 90% of that fund still unrealized. That creates a really difficult problem because even if you're doing vintager benchmarking, the vintager benchmarking on the fund that's two years old doesn't tell you anything. So where I think we have advantages in that kind of situation is the operational data that we collect. So we can also say the manager is touting the fact that this particular company is growing at a 14% revenue CAGRADE and EBITDA has increased at a 8% EBITDA CAGR. I don't know. 14%? That sounds good, I guess. I don't know. Is that good or not? I have no idea. Let's say it's a healthcare services company and he's telling it 14%. He's saying that's amazing. Without the data that we have, it's hard to understand if that is actually good or not. Have they actually been doing a good job of creating value? So in our part of the market and the smaller part of the market, we don't use financial leverage to generate most of our returns. Most of the returns are generated through growth. They're generated through taking smaller, less sophisticated companies that have a lot of levers to pull operationally to improve them and making them grow and scaling them to a place that they can be sold in a much more efficient market. So the operational improvement that we see is a really critical part of most of our thesises. So when a manager tells us they're growing their companies at certain rates and it's in their data room, what we can do is look and see is that actually good or not? And that gives us an advantage. We think in terms of our evaluation of trying to decide good versus bad and whether or not in situations where there's limited track record of realized deals. How do you get comfortable with those managers? As you mentioned, at some point some of our managers get very big and it's because they've done really well and everybody recognizes that's true. But the problem is that when you're investing, when they're fund two or fund three and they're not at that stage yet, you need to figure out how to do an evaluation with more limited information that gets you to conviction. And that's what we spend a lot of time on. The only other area I'll say that we end up having advantages on emerging managers and somewhat for similar reasons. But what's different about emerging managers is that one thing for sure is that on the data side, you don't have Vintage or benchmarking to use on an emerging manager, even though the most basic tool that most LPs are using is not something that is applicable. Because in most cases an emerging manager has a collection of attributed track record from their previous organization. So maybe there's 10 deals over 10 years that that person or team has done. And so again, like going back, our deal level data allows us to evaluate these types of managers in these types of ways in we think a much better way than if we were just taking big leaps of faith alone.
- [32:51]
Ted Seides
So as you look at that whole middle market, you have to still pick your spots. What are the type of managers based on? Maybe the metrics and qualitative metrics that you've decided to add to your portfolios?
- [33:03]
Alex A. Bell
For us, the best managers are ones that present a team, a strategy, a process that we believe has the ability to create repeatable returns. That seems like a very obvious statement. What we're dealing with, as with any investment team or professional of a manager, is there are oftentimes managers that have really good track records. And when you dig into how they were able to execute to develop those track records, you find out that it might be a track record based on one really amazing deal where there was no consistency or even a couple deals that were good, but that the reason that they ended up being good, there's no common thread and there's no way to sort of guarantee that those reasons will ever occur again. So for us, the way we think about it is we're obviously trying to back teams that are exceptional, but maybe the most important part of that is teams that are exceptional that based on their background and experience, have the ability and have a stated process and strategy for how they do deals that we think gives them the best probability of out producing other managers on the return front. And I say probability because if anybody tells you they can pick the top decile manager of any given vintage year, they're completely wrong and lying. But what it does mean is that we can look for characteristics in each of those sort of big buckets and say we think that there's something about this that puts them in a position for every deal they do to have and achieve outsized returns. So on the process side, that could be something like sourcing, something unique about their sourcing strategy. How do they find deals? How do they create proprietary deal situations where their valuations are, let's say, moderate and less than the market? How do they win deals when it's a very big competitive process and there's 10 other private equity firms, how do they win deals for less than the top bid, which we hear often from private equity firms. So that's one interesting idea. Some people have sourcing strategies that we would consider, fine, but that's not their superpower. And there's some managers where that is their superpower. That's their magic fairy dust that makes them differentiated. Another example would be really value creation. Right. And we mentioned this a little bit before, the ability to create value in these smaller companies is where you generate most of your returns. And most teams today have some form of operational capabilities that they have either as part of their existing team in house or as a very close outsource resource. These operational teams are critical. We've seen a development over time of how private equity uses these operational folks and the models have changed over the years. But no matter what the model is that you're using, we have to see something about the way they attack the issues within these companies that we have faith that they can do over and over again.
- [35:56]
Ted Seides
How do you then construct your portfolios.
- [35:59]
Alex A. Bell
At rcp on the primary fund side, which is what we're mostly talking about right now, the way we think about it is a fund for all seasons, to use a phrase that my partner likes to use. Really the idea is when you're investing in private equity, it's an illiquid investment that is on at least the surface a 10 year marriage that you can get out of at least in the secondary market. But it's not something you're planning to do. For us we're looking for managers that have the experience to invest through cycles. And so as part of that when we construct our portfolio, we're looking for managers that create a diversified portfolio across a little bit across size. Although again for us everything we're doing is under essentially a billion dollars in fund size with some very few exceptions sector we don't have sectors that we feel like we have to have. We do want to make sure we're not over concentrated in any sector. And even within sectors the strategies themselves can be very different. So in one fund of ours we might have a technology oriented buyout manager that focuses on very high growth companies. And then in the same fund we might have a technology oriented manager that's focused on complex special situations doing carve outs of orphaned software products from a larger company. And those are both technology, but they're very different technology. So for us we look at that as well to make sure that we have not an over concentration in any style, any sector and certainly diversification by Size, from a geography standpoint, we're pretty boring. So it's U.S. and Canada with 90% or more, usually in any given fund being from the United States. But our main goal is to understand that different strategies will operate through cycles differently and to make sure we have managers within each of these types of funds that have experience and track record that can go through those cycles.
- [37:44]
Ted Seides
How do you think about secondaries both as a mechanism for your primary funds and then as a separate vehicle where you're investing and buying?
- [37:52]
Alex A. Bell
Yeah, so we have a separate secondary program. I'll actually touch on what you mentioned first, which is how do we think about our own funds? One of the things that funda funds are notoriously, I think, bad at is they end up having really long, long fund lives where they can go well beyond the 10 years that a normal underlying GP commitment is. And part of that's just because oftentimes if you have a portfolio of 10 or 12 underlying managers, there might be one or two that have some leftover positions, there's escrows, they're still doing audits, which of course starts to degradate returns for everybody. And most investors don't want a 14 year K1. We try to aggressively, really starting in years 8, 9 and 10, start to look at opportunities in the secondary market just like we would as a buyer of secondaries. We look for places where we can package funds where we believe there's more value in selling than what we can get in the lift of the return in the remaining hold period that could be unknown. So we start evaluating them over time. We have someone internally here who that's part of their job to do on a regular basis. And when we find their situations where we think it is in the best interest of our investors to exit an opportunity, we do so. We've been very successful at doing that and wrapping up older funds in our secondary investing. That's in some ways a little bit of a reverse. We're obviously looking for great deals, but the market in secondaries has changed a lot over the years. Traditionally, when we talked about secondaries, we would talk about limited partner secondaries that used to be 95% of the market and now it's probably more like 50% of the market. The other 50% has been GP LED secondaries or CVS continuation vehicles. Now we see tons of these things and many of them have significant conflict problems. They have significant issues around structure and alignments. But for the ones that don't, the ones that are structured correctly have good alignment with your underlying manager. They can be really good investment opportunities as part of the overall secondary world. And then the other way to think about secondaries is not just GP versus LP, but single asset versus multi asset. Many of these GP LEDs can also be multiple companies in a portfolio that they're selling. And those behave much more similar to a traditional limited partner secondary than the single asset deals, which in many ways behave a little bit more like a traditional co investment.
- [40:18]
Ted Seides
There's a lot of noise in private equity about the challenging exit environment with rates going up. What are you seeing both in your portfolio and then across all the information you have of all these different funds?
- [40:30]
Alex A. Bell
So last year was probably one of the worst years for proceeds and realizations that we've had in our data. And not surprising anybody who's been touching either the bigger part of the market or the lower part of the market. We've seen overall activity decrease. Luckily, in the smaller part of the market it hasn't been as extreme. There's a variety of reasons for that. Usually our part of the market is more immune to whatever macro effects are going on. I think the biggest reason is that we just one, use much less leverage in our part of the market, where the credit markets at the top part of the market create huge difficulties. I think for getting deals done in our part of the market, we're using maybe three turns of leverage on ebitda. That's probably less than half than most of the bigger part of the market is. And the other dynamic in our part of the market that's a little bit different on leverage is that vast majority of leverage in our part of the market is not from traditional money banks and it's certainly not syndicated loans. It's a lot of private debt. And the private debt funds have been raising capital very consistently for the last 10 years, and they have in some cases a higher risk appetite. So even through the uncertainty of the last 12 months, 18 months, they have been willing to lend now sometimes at higher spreads, higher pricing, maybe less leverage than they traditionally have historically, especially on the entry of a deal. But that has maintained activity in our part of the market in a way that I think has been a little bit more robust than what we've seen in the bigger part of the market. Now that said, it's still been lower. And so what we've been hearing over the last, I would say, three to six months has been a much more positive attitude by many of our managers about the potential for exits. And so many of our managers have a set of companies that they've been essentially waiting to take out to the market that they now feel some confidence that they can get the valuations that they hope and look for. Now, what I'll say is that anecdotally, most recently we have heard some amazing success stories related to that where people have brought those companies out and have gotten the valuation they want and been very happy and good realizations. And we've heard some anecdotal stories where people have brought it out to market and not getting the bidding that they want and they're stopping the process. They're just figuring they're going to wait longer. I think the jury is out as to whether or not the market has recovered. I certainly think activity wise we are seeing a little bit more pickup on the investing side for sure. It's the exit side that's from the gps who again are going to be very picky about exiting their companies when their carried interest is relying on that cash on cash multiple that they're going to generate. They're okay waiting for another year if they need to six months a year. There's a variety of other tools that exist in the market today that didn't exist 10 years ago. They have the ability to do recaps and takes away maybe some of the uncertainty that the market still has on some of these sectors that are having.
- [43:25]
Ted Seides
Trouble as private credit has exploded. How have you thought about investment opportunities on the credit side?
- [43:30]
Alex A. Bell
We have an affiliate of ours that does small market buyout credit called Five Points Capital. They are a fund that utilizes the SBA's SBIC program to invest in small businesses. They've done extremely well and believe there's a huge market for the leverage that exists in the smaller part of the market. And so what we've seen generally is that the private credit markets have become way more sophisticated. They become larger, there's many more players and that creates some competition which helps the equity holders when they're going out and raising capital for these.
- [44:06]
Ted Seides
As you look out over the next couple of years, what risks are you most concerned about in the strategy?
- [44:11]
Alex A. Bell
One question I often get, which I think is certainly somewhat of a concern, is part of our thesis of what we do and what their managers are doing is they're taking these smaller companies that bigger private equity firms can't and don't want to invest in. They're buying them for two or three turns lower than what those folks want to buy companies or can buy companies for because they're in a much less efficient part of the market. There are also companies that are worth two or three turns lower because of where they are in their own maturity and life cycle. The goal of our private equity firms is to grow them, to diversify their products and services, to make sure they have professionalized management teams, to make sure they have a diversified customer base. And all of a sudden they have a shiny asset that they can then sell up to the bigger private equity firms at the next layer of the market. The big question I sometimes get is what if people stop investing in the next layer of the market? There's two really real reasons that they can pay bigger valuation multiples for the companies on the sale from our managers. One is the companies are just better, higher quality, so that gives them the ability to do it. The other is they have the ability to finance them at much higher leverage levels that helps drive higher valuations. And then really the final way is that they have a lot of capital and frankly, their cost of capital is really different than the managers at the 4 or $500 million fund size. Right. And so the question is, if that dynamic changes where capital becomes more scarce above us, does that crush our thesis? And the quick answer is, yes, it certainly could. The other big buyer of companies from our portfolios are strategic companies. Other companies that are buying add ons, either as a portfolio company of a bigger private equity firm or as an independent company. Most of those companies don't want to buy a $7 million EBITDA company. It just doesn't move the needle for them. But if a company can grow to 20 or 30 million or more, it all of a sudden can be an important add on. Those folks have been active for more than 20 years. They've been active forever. And we don't see any stopping of them and frankly don't see much stopping of the private equity markets at the level above us. Mainly because I will certainly tout that the returns in our part of the market have historically been consistently better. The returns of all private equity have been generally very good. And most institutional platforms recognize the need to have allocation to it. And while in times like this everybody starts asking questions because LPs have slowed down on their commitments and fundraising has become more difficult, the pendulum will swing back. Because long term returns that most private equity firms can generate tend to be better than the public equity and other alternatives. So people want them as part of their portfolio.
- [46:47]
Ted Seides
If we circle back to so much of how you spent your time on the analytics of these funds, what are the things that you're working on today or hoping to work on in the near Future, that's the next wave of innovation and understanding performance.
- [47:00]
Alex A. Bell
One of the things that I talked about earlier on is that private equity investors, we haven't done a really good job of figuring how to quantify risk as part of this equation. So I can tell you whether a private equity manager has outperformed and outperformed against their peers on a variety of different metrics. One of the things that I'm spending a lot of time on is trying to think about ways to both analyze the deals and the managers themselves, but also things like sectors and sort of areas of investment. Yes, technology investing has done extremely well in the buyout space over the last 10 years. How do we judge how much risk is associated with that as well? Because we're only thinking about this generate great returns. And the question is, is there a distribution of outcome across a histogram that looks very different. So places we have seen this very explicitly is things like consumer. So consumer investing, it's been a rocky number of years depending on your strategy. Some strategies during COVID did really well. Some had companies that did poorly, some had companies that did both depending on what they were doing. But even beyond that, what we've seen in consumer is that there are some managers that have been able to do really amazing returns doing things like consumer branded product goods and things like that. And then we've seen some managers have huge volatility in those portfolios where even though maybe the overall returns are going to look good, there is certainly a lot of risk on a variety of levels in getting to those returns. Most of us in the LP world use a variety of measures like loss ratio. But I think there's some better ways that we can start thinking about how to measure inter portfolio risk that is not being taken into account today. So I'll give you an example of something. One of the things that we recognize is that not every deal in a portfolio, even the ones that do well, are straight up into the right. When we're evaluating a manager, we're seeing the outcome of a deal that might have happened, say three, five years ago, and let's say they got a 3X. But if you look at the underlying company and the historical marks and their historical operating performance, there was two years it went through which was horrible, and there was a lot of risk in that company that the manager was able to save and get to a great return. Well, the problem is if we have a way of measuring that kind of risk systematically through their portfolios, then the end number itself is not the only thing we need to look at, we need to look at the journey because there's going to be lots of examples of that where they aren't able to save it. And just because they were able to save that company does not mean that if they're buying companies that inherently have certain types of binary risk and we've just been lucky that they haven't come to play in a negative way yet, well, that could lead us to bad decisions. What I would say is all this analytics that we're talking about and the way we think about evaluating managers is certainly important in finding the best investment opportunities. That's our goal. Right. But maybe as important or more important is avoiding the mistakes. Because any portfolio we do, whether it be co investing that we do or secondaries or primary fund investing, if you can avoid the mistakes, you can give yourself the highest probability of having the best high performing managers, knowing that not everyone will be there. And create an asymmetrical return profile where you have a greater probability of outsized returns, very low probability of what I'll call bad returns or even mediocre returns.
- [50:20]
Ted Seides
All right, Alex, I want to make sure I get a chance to ask you a couple closing questions.
- [50:24]
Alex A. Bell
Yeah, sure.
- [50:25]
Ted Seides
What is your favorite hobby or activity outside of work and family?
- [50:28]
Alex A. Bell
My favorite hobby or activity is actually sailboat racing. Sailing. So I grew up sailing on Lake Michigan here in Chicago. I started racing when I was 12 or 13. I raced in high school, went to high school nationals, raced in college, raced on tons of other people's boats. Just recently I bought my own. So I have a small 29 foot racing sailboat called the J88. I race here in Chicago and whenever I can during the very short summer we have here, I'm trying to be on that boat in regattas, racing it and have a lot of fun doing it.
- [50:59]
Ted Seides
What's one fact that you find interesting that most people don't know about you?
- [51:04]
Alex A. Bell
All three of my children are named after professional sports stars. So my wife is from Pittsburgh, I'm from Chicago. The first names are all Chicago famous sports stars. Jordan, Peyton with an A, P, a Y, T, O, N and Maddox for Greg Maddox, who I grew up watching on the Cubs. And then their middle names are all Pittsburgh Steelers. For my wife's love of the Pittsburgh Steelers. She grew up going to games even as a little kid. So my first son's name is Jordan Bradshaw. My second is Peyton Harris and my third is Maddox Green for Mean Joe Green.
- [51:39]
Ted Seides
That's awesome. What's your biggest pet peeve?
- [51:43]
Alex A. Bell
My biggest pet peeve which happened to us pretty recently, is renting a car, especially for a family trip where I have three kids, need a big car, showing up and having them tell me that they don't have the car I reserved six months ago and having to figure out how to deal with that problem in the beginning, usually of a family trip of some sort, that drives me nuts.
- [52:08]
Ted Seides
Which two people have had the biggest impact on your professional life?
- [52:12]
Alex A. Bell
The first, Sally Shipping Russell, who was one of our partner heads at Quellos Group. She was just really influential for me in a time period where I was just getting started doing this type of work. She had a wealth of knowledge herself and experience. I was at the beginning stages of my career trying to move from being what I'll call a task executor to someone who's actually taking a lead role and doing due diligence and things like that. And she just had a significant impact on, I think, my career development, both from a technical perspective but also relationship wise. Meaning one of the most important things in private equity investing as a limited partner are relationships. Relationships with the gps, but also with other limited partners. We share information, we talk to each other, we learn a ton of stuff from each other. And I think she was a huge proponent of that and was very good at it herself and taught me, I think, how to be good at it in this profession.
- [53:04]
Ted Seides
How about a second?
- [53:05]
Alex A. Bell
I would give credit to a guy named Andy Berman. My first job before business school was actually not doing this at all. I was at a highly technical and quantitative consulting firm called Cornerstone Research, and I was a history major. So I came out of Penn. I was always a very quantitative person, but never really interested in being a math major or engineer. And all my roommates were Wharton undergrads who always made fun of me for being a history major. But he took a chance on me. I interviewed for that job and they described as really highly quantitative. And he saw past my major and hopefully what my skill set was. And I think it gave me a lot of conviction. And that job itself before business school, I think led to in some ways a lot of the quantitative thinking that we've been talking about and really being focused on thinking through things in that manner. And I think a lot of that was based in that first job I had out of college. And I'm very grateful that I was able to get it, even though I probably didn't fit the profile. What they normally hired.
- [54:00]
Ted Seides
What's the best advice you've ever received?
- [54:03]
Alex A. Bell
It was done by a manager of mine, long Long ago when I was young. And I think it was stolen actually from a line in Pulp Fiction. So I'll give some credit to Pulp Fiction. But the idea was that he said was that when someone else is talking in a conversation, he told me to stop simply waiting to talk and actually focus on listening to what they're saying. For me, it was important because that's what I do. Even today, it's something I try to fight. I like to talk and I like to give my opinion. And I've tried to learn to do a better job of listening before I just start speaking.
- [54:33]
Ted Seides
All right, Alex, last one. What life lesson have you learned that you wish you knew a lot earlier in life?
- [54:38]
Alex A. Bell
I think that early impressions that you give people of yourself and not just first impressions, not meaning when you first meet people, but let's say the first three months you're working with a new job is of outsized importance to anything you'll do after that three to six months. And what I mean by that is that if you create an impression of competence and high quality work, then every mistake you make after that is seen as an exception. If you begin your career in a company or a job and you don't take it seriously, you're not responsive to people, you're making mistakes, you're sloppy work, it takes years for people to unwind that from their mind and their impression of who you are. So no matter what you do, that's good. After that first three or six months, it's always put in the context of, yeah, it's good. But in general, Alex isn't very good at X. Luckily I didn't have any significant extreme examples of that. But there's certainly been times in my career where I have given people the impression in certain ways of things that I should be doing better. And it's taken a long time to convince them that that wasn't really me. I think that's a really good learning lesson. I teach my kids that all the time.
- [55:47]
Ted Seides
Alex, thanks so much for sharing this very data driven exploration of the middle markets and private capital.
- [55:54]
Alex A. Bell
Thank you. Really appreciate the conversation. Really enjoyed it.
- [55:58]
Ted Seides
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