When working with communities to build entrepreneurial ecosystems, I’m often asked for the “secret sauce” to identifying successful entrepreneurs in advance. I wish I had this power, but it’s sadly not that easy. A large chunk of the entrepreneurship literature is focused on this question of what factors contribute to a business’ long-term success. If, for example, you take a look at the excellent Startup Cartography Project, you’ll find lots of interesting correlations. For example, a new venture has a massively higher prospect of success if it takes out a patent in the first year, is headquartered in Delaware, and is organized as a corporation (as opposed to a partnership or LLC). Another interesting stream of research assesses how personality traits affect business success.
All of this excellent research still doesn’t translate well into the real world, in the sense of providing clear directions to winnow out good ideas and good businesses from bad. Another recent research piece from the World Bank as offered further confirmation on this front. This study, “Man vs. Machine in Predicting Successful Entrepreneurs,” looked at Nigerian business plan competitions and tested a number of ways—from expert judges to economic modeling to the use of machine learning to predict business success–to assess the quality of business pitches and ideas. The results? None of the methods proved to be very effective in predicting success, leading to this “dog bites man” conclusion from the authors: “Business success is really hard to predict.” Well, we knew that already but it’s always useful to be reminded of the dangers of hubris and excessive confidence. Even when we’re armed with the best research and analysis, a good entrepreneur can surprise us!