Data analysis is already on the way to helping to identify ‘entrepreneur-founder’ types in the United States. Such advance information, if reliable, would be a real boon to venture capital providers and investment funds.

Can Big Data Help to Spot Future Entrepreneurs?
A free online course launched recently by high-profile US-based incubator Y Combinator, in partnership with Stanford University, serves to underline the growing enthusiasm for entrepreneurship in the United States and elsewhere. Proof of the pudding: MatterMark, a young startup which specialises in data collection and quantitative analysis, and Bloomberg Beta, the venture capital wing of New York-based financial software, data and media group Bloomberg, have pooled their knowhow to produce a cutting-edge study on likely entrepreneur profiles. This joint effort – focusing on people’s LinkedIn connections, educational background and the business sector they are currently working in –has spotted several hundred people who, according to the algorithm applied, will be among the most likely people to launch an entrepreneurial venture in the next four or five years. On the basis of these results, Bloomberg emailed a hundred-plus people to alert them to their business potential and invite them to networking events on the US East and West coasts.

Unexpected profile for ‘entrepreneurs-in-the-making’

As part of this ground-breaking study, MatterMark co-founder Danielle Morrill examined the major growth factors in existing startups. She and her team followed what has now become popular methodology, gathering data from the rather ‘traditional’ social network LinkedIn plus specialised networks AngelList and CrunchBase from the world of new technologies. They also inserted a strong geographical bias, focusing on the San Francisco Bay Area and New York City. The data gathered threw up surprising and perhaps counter-intuitive statistics on existing venture-backed startup founders which enabled MatterMarkt to draw up a profile for potential business innovators. For instance, in contrast to the modern tendency to equate innovation with youth, Mattermark noticed that 38% of all venture-backed founders are over 40 years old. Also highly significant was the type of work done by a company founder before s/he launches the new firm. For example, management consultants are more than twice as likely to become venture-backed founders as engineers. Meanwhile, contrary to conventional wisdom, being ‘stuck’ in the same company or position for a long time does not seem to diminish the likelihood that you will found a successful business. However, unsurprisingly half of all venture-backed founders were working at a venture-backed company immediately before setting up on their own. Nevertheless, the portrait drawn so far is far from complete, since MatterMark stresses the importance of social connections in the tech world.

A self-fulfilling prophecy?

Obviously it is in the interests of venture capital investors to spot people destined to create a startup before they actually get around to launching the new business. The lively competition between capital providers in the US, particularly in the Bay Area, to find promising firms to back provides an incentive for investors to find new ways to spot potential. The basic business model is that the returns from one highly successful startup pay for all the others that fail early. Neither MatterMark nor Bloomberg Beta has talked publicly about the fact that ‘early stage’ investors were among the organisers of the networking events held in New York and San Francisco to bring together those who top the list. The MatterMark team are quick to admit that their algorithm, based on sifting Big Data, does not take into account one crucial factor – free will.  Which leaves us deep in the Big Data debate: how far will the flattering Bloomberg/ MatterMark email actually prove to be a ‘self-fulfilling prophecy’, encouraging people to try their hand in the startup world? However, Danielle Morrill recognises that the MatterMark approach is simply a useful analytical method that points up identifiable patterns and she admits that at the end of the day entrepreneurs actually tend to be people who ‘break the pattern’.
By Simon Guigue