The classic model in angel investing goes something like this: You look at a large number of potential companies and winnow them down to a handful of the best companies and invest a relatively large amount in each of them.
Will the model give you great returns? I don’t think so.
The success of this model depends on your ability to pick winners. You probably can’t. I don’t mean that there is something wrong with your selection skills. But that when outcomes are truly uncertain, human beings can’t pick winners and losers. The information they need to make these choices doesn’t exist.
Being human, we make two big errors in the process of selecting. We think we can know the unknowable and we underestimate the value of diversification when outcomes are unknowable.
Seed Stage Angel Investments Model
Let’s start with the idea of picking winners when outcomes are unknowable. We think that finding winners is easy because at the top of the funnel, it’s not so hard. It’s easy to cull a list of 400 potential companies down to 100. Some basic criteria differentiate startups that have a decent chance of growing large from those that have essentially zero chance. A small number of industries account for a high fraction of companies that go public or get acquired by public companies at high prices. Few high potential companies succeed without a team of founders that have both marketing and technical skills. Few companies go anywhere with a team that has no experience in the industry they are targeting. And failure to identify a true customer problem or a valuable solution to it usually means the company isn’t going anywhere.
But that’s the first cut. We can identify probable “losers” easily.
After that, the selection process becomes very difficult. It’s very hard to figure out which of the startups in the “right” industries, with a team of founders that have the necessary set of marketing and technical skills, experience in the industry and a good solution to a customer problem will succeed in the end.
There’s just too much uncertainty. Much of the information we need to know to identify winners and losers doesn’t exist yet. We don’t know what the products will look like before they have been built. We can’t foresee how customers will react to products they have never seen. We have no idea how competitors will respond to a company that is not yet challenging them. We can’t judge the value of a company’s business model or go-to-market strategy before it has been formulated.
This makes investigation and due diligence very ineffective. No amount of searching will help you find answers that do not yet exist. But because human beings don’t like uncertainty, we look for patterns which don’t exist, and then choose between alternatives based those false patterns.
The second problem is under diversification. Given the distribution of returns from seed stage angel investments, investors need more than 50 investments in their portfolios to generate good returns with a low probability of loss of capital. But most investors spend too much time looking for “winners” in which to put relatively large sums of money. As a result, they make too few investments.
Most angel investors would generate a higher rate of return and experience a lower probability of loss if they took their pool of investment funds and made small investments in all of the companies that stand a plausible chance of success than if they made large investments in the few companies they believe will be the big “winners.”
Other asset classes use this approach to investing; it’s the principle behind indexing. In a space where even less information exists to pick winners than the stock market, investors might consider this alternative.
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