Moneyball for Private Equity — Driving Alpha Through Portfolio Management
Drew Pearson, Biospring's Chief Operating Officer, recently led a discussion for Limited Partners on best practices in Portfolio Management. We're pleased to share a recap of the discussion below.
"When I think about private equity as an industry, it's at the highest level, an incredibly simple business. It's really all about making one or two dozen great decisions every year. It's a handful of investment decisions, and it's a handful of liquidity decisions. If a firm can do that correctly, returns are going to be excellent." — Drew Pearson
How are decisions made at PE/VC firms?
Most firms follow a similar investment decision-making process. If you were blindfolded and dropped on a Monday morning into any private equity firm in the world, I think you'll find most of the meetings work similarly. It tends to be a highly centralized process, and it tends to be very collaborative. Usually, decisions are made when the majority of folks agree, some firms are unanimous, some firms are a majority, but usually, there needs to be consensus to make a decision.
Decisions are usually data-driven. Usually, millions of dollars are spent on diligence before arriving at a final decision. And decisions usually aren't made at a single point. They're usually evolutionary and through multiple discussions.
What's amazing to me is that the same level of rigor and analytics doesn't really apply to liquidity decisions. It's usually a decentralized process that's delegated to an individual deal team to decide when and how to sell. It's usually based on anecdotes, rather than hard analysis. And what's terrifying is a lot of times the decisions are governed by non-financial metrics.
We're raising a new fund, we need to take liquidity now
We've been in it for five years, it's probably time to sell
The lead partner is on five boards and needs to get off a board in order to do a new deal
These are the wrong metrics upon which to base a liquidity decision. Almost all firms buy into the concept of collaborative decision-making on investments but rarely do firms hold themselves to that same level of rigor when they're making liquidity decisions.
Improving Investment Performance with Portfolio Data
There should be an underpinning of data that firms gather to drive analytics to make better decisions. Using data, you can determine what metrics are correlated with investment success.
You can look for trends underlying company performance, which informs your buy, sell, hold decisions, when you see trends across the portfolio.
One of the things I'm most passionate about is how can you identify biases that individuals are making in their decision making and help them get better help them realize their bias at an individual level and help them remedy that. At a firm level, you're looking for trends and biases in your decision-making and remedy that.
In general, I think private equity firms aren't great at doing forecasting of performance or liquidity. Using data, there's lots of room for improvement there.
The concept of risk management is pretty nascent in most private equity firms. Before you can really think about managing risk, you really need to get a bit better sense of: What is your portfolio? What are the dynamics? How can you assess the performance of it?
The valuation process is obviously more of an art than a science that a lot of firms. When you get better at analyzing data, you can have a more rigorous valuation process.
There's also a lot of value to be gained by linking insights from how your portfolio performs to your investment committee decision-making.
Resource allocation. At most private equity firms, time is probably the most valuable resource in terms of: Are you spending it on the right portfolio companies? Are you spending it on the right prospects? I believe there's a lot more of a science that you can have in terms of where your time should be spent on what companies which companies have the most upside, which prospects have the most upside. If you can get that, right, there's massive value to be had.
I think the biggest lever to drive is using analytics to decide the right time to sell. There are hundreds and hundreds of basis points of returns at the fund level that can be generated from being more intelligent about making buy, sell, hold decisions.
Finally, I found that when we do when you do it, right, when you do all these things right, it makes your LPs happy, which is obviously incredibly important in the long term if you're trying to build a private equity firm that's going to sustain through multiple funds.
Moneyball for PE/VC
One of the analogies I like to make is to Moneyball. Historically, baseball had been driven by scouts, who I would draw an analogy to, are very similar to a lot of traditional investment managers, who can look at a player and determine if he is a great player or a dud. Non-traditional metrics, such as on-base percentage and slugging percentage, started being analyzed and a whole new area of statistics (sabermetrics) arose to evaluate players.
This is a discipline that can be applied to private equity, the concept of using analytics to challenge a lot of traditional non-analytical tools and methods that are used by investment professionals is something that is long overdue in the industry.
One of the things that I'm a big fan of is looking at metrics that are correlated with investment success. So it's linking individual company performance data with investment data. The linkage of the two is where you see the improved returns. We have different correlations that we are constantly running by geography, by sector, by investment professional.
Some observations over multiple firms and multiple funds include:
Revenue size: There's no correlation between revenue size in returns.
Revenue Growth is moderately correlated to faster-growing companies, in general, there is some statistical correlation with better returns.
Rate of Change of Revenue Growth is highly correlated with positive investment outcomes.
On the bottom line, there's no real correlation with Margin, some correlation with EBITDA Growth, but a real strong correlation between the Rate of Change of Margin.
Entry Multiples aren't strongly correlated with investment returns.
Exit Multiples have some correlation. If we are able to realize an above-average Exit Multiple, that was moderately correlated with good returns.
Vintage Year, as you would expect has some correlation because of their cycles. If you are buying on the downturn in a cycle, it tends to be a much stronger year.
Sector and Geography do not have much correlation.
Performance versus Plan. Hitting your numbers is unsurprisingly correlated with investment success. This is one of the lessons I really try to drive home to investment professionals. Private equity is a pretty simple business, all you have to do is derive a plan and hit the plan. When you do that, usually good things happen.
Using Portfolio Data to Make Better Decisions
What questions can LPs ask GPs to evaluate their portfolio management systems?
Portfolio Management Best Practices & Red Flags
Returns can be improved through better decision-making.
A key factor in any portfolio management system is the combination of analytics (to identify biases and trends) and strong governance (to impact change).
LPs should consider a more rigorous evaluation of each manager's portfolio management capabilities.