Method Investing: Bringing Science to the Early Stage


Over the past five years, our team at Social Starts has developed a unique and powerful approach to early stage investing. We call it The Method. I get questions about The Method regularly, so it seemed appropriate to go over the fundamentals in one time and place.

Considering the early stage as an investment class. We view early stage investment in as close to a Wall-Street-way as possible. The early stage in an asset class, like stocks or bonds. Like any asset class, early stage startups have unique characteristics. Our task is to understand those characteristics and build an approach to the startup asset class that can produce strong returns, day-in, day-out.

 Gaining investment advantage: An information edge or an analysis edge. Years ago, when I worked with Sir John Templeton on his autobiography, I learned a lot about Graham investing, which is the approach Sir John used to win on Wall Street and that drives the investment philosophy of Warren Buffet, among others. Graham preaches that the key to investment success comes from gaining an information or analysis edge on the rest of the market. If I have information you don’t have or can develop insights you can’t see, I win. The  Method is designed to bring this philosophy to early stage startups.

Information edge in early-stage startups: Tough but not impossible. There were, by one estimate, 1.78M new tech companies created in the world last year. They spanned a dizzying array of technologies, use cases, countries, and stages. It would appear on the surface to be a nest of writhing variables, impossible to parse and gain an information advantage. In truth, getting an edge on startup information is daunting, but it isn’t impossible. At Social Starts, we’ve learned that the two keys to gaining an information edge are focusing the target set and acceptance of high volume.

In stocks, all the information on all investable shares is gathered together and available to every investor. But in startups, that information is disparate and occult. Is it possible to get all data on all startups? Not really. There are too many variables in play. However, what if, instead, the question was: Is it possible to get all data on a small, defined subset of startups? That is much more achievable. So at Social Starts, every six months we define a tight set of startup targets and work to gather tons of data in those limited spaces. We seek a local, not universal, information advantage.

But even with limited sets, the startup world today is so huge that building an information advantage requires enormous effort. For our method to work, we essentially have to be aware of every new company in our focus areas and personally meet with a significant set of them to build up the context that gives us an information advantage. We identify up to 4,000-5,000 companies across five to six focus areas in a typical year, and formally evaluate 1,500 or so. Only this level of speed and effort can generate the data we need to clearly see where opportunity lies.

Analytic advantage in early-stage startups: It’s all about the data. Beyond an information edge, if a fund can analyze the available data effectively, advantage can compound. We work to evaluate companies in a consistent, deep and dispassionate way. Our basic question is: Are there any patterns that the most successful startups share? If there are, does this particular team, tech and company, at this moment in time, display those attributes? At this point, analysis focuses on the psychology of the founder and the temperament of the team. Many of
the impulsions of becoming an entrepreneur are negative in source; they derive from overweaning pride or deep insecurity. We have found a rather specific and narrow psychology that correlates most strongly with trust, confidence and resilience in startup teams. When we find a company with potential, we test these “inner person” characteristics strongly as our final jumping hedge before investment commitment.

So, to review quickly, the fundamentals of the Social Starts method are:

  • Establish boundaries; define tight focus areas; limit the set; test the segment fundamentals. You can’t eat the whole pie. Go for rich slices.
  • Fill in the data points. The card counter wins a long night of poker.
  • Evaluate consistently, by patterns. Are the fundamentals for success present in this opportunity?
  • Establish a set with the characteristics for next-step success. We don’t believe it’s possible to know which companies will be big winners. But it is possible to identify a set of companies with the greatest possible prospect for success.
  • Recursion, recursion, recursion. Constantly look for patterns. Follow the data, wherever it goes.
  • Stay focused outward; do a total teardown at least once a year. Success, for us, isn’t about emotion or how we feel. It is about data and market realities. So we do a complete teardown of the fund every six months, compelling us to look outward to see what is happening, and driving us to respond to the market as it is, not as it was or as we with it to be.

This is just a start. We're proud of The Method and believe it has set our funds up for success. However, we see much more we can do. In this era of nearly universal analytics, we feel our ability to gather information and use it to predict startup success will only grow. We are determined to continue innovating on ways to bring science to the early stage.