Robot Uprising in Venture Capital?
Like it or not, we live in a quantitative world; and it gets more so every day. Manufacturing defects are measured with 99.99966% accuracy. Automated trading algorithms evaluate businesses, prices, alphas, betas, libraries of ratios and make trades based on picoseconds of marginal arbitrage. In 2006, an estimated 40% of trades on the London Stock exchange were done by robotic intelligence. United States estimates are closer to 80%, as anyone paying attention on May 6th got a sense for.
In this world of empiricism, data and calculation, the job of a venture investor seems an anomaly indeed. While there are some exceptions, the majority of venture investors allocate billions of dollars every year based on little more than experience and gut intuition.
This is not to, in any way, detract from successful investors; the ability to pick winners, wrestle out a deal and drive others towards a central direction can require tremendous talent and skill. Rather, the point here is merely to pose a question. Given the dollars at stake and lives in the balance, will venture investing inevitably evolve in a more empirical direction? Will there be a robot uprising?
Once upon a time marketing and advertising were a matter of visionary intuition and interpersonal sensitivity. Yet today statisticians are increasingly replacing marketing MBAs, and software developers are taking the place of bygone “Mad Men.” If you want to know what makes left-handed, Republican, blonde, female smokers buy pink purses in Nebraska, you’re increasingly better off writing a few lines of code rather than hosting a living room focus group. Downtrodden liberal arts students with a penchant for business are finding fewer and fewer places to hide.
While intuition-based venture investing works for some, most agree that it usually fails. Investors spend inordinate time screening deals, only to see around 90% fail (on a good day). Industry-wide VC returns in the US over the past 10 years are now negative. Not only is VC investing falling short of LP and GP expectations, but it – by necessity – excludes the gross majority of startups as well. Less than 1% of startups attract VC investment in any given year. Less than 95% of businesses attract any equity investment at all (either from VCs or angel investors).
A common counter-argument to empiricism is that venture investing is inherently unquantifiable. Too unpredictable. Too subtle; so as to be forever exempt from the purview of robots. Yet is venture capital really more multivariate than manufacturing, biology, chemistry or physics? Anyone who has run a semiconductor fab, high-volume manufacturing plant or pharmaceutical lab might disagree. What makes venture investors immune? Why are they so special?
The field of Psychology is perhaps a worthy analogy. Equally amorphous and intangible, psychology is divided between clinical methodologies (relying on human judgment and subjective analysis) and mechanical methodologies (relying on statistics, algorithms and other more objective tools). More than 136 different studies have tested the relative accuracy of both methods going as far back as the early 1900s, almost invariably concluding that mechanical methods are more consistent, accurate and yield higher quality results.[i] Even in Blink[ii], a book often held up in defense of intuition, author Malcolm Gladwell goes to lengths to call out the limitations of intuition, such as inaccuracy, wishful thinking, knowledge inaccessibility and the mind’s ability to play tricks on itself. Along these lines it was found that even simple checklists, the most basic of objective tools, reduced hospital surgical mortality by around half. Half![iii]
With so many lives and dollars at stake in the realm of venture investing, can empirical methodologies lend more of a hand? Should we demand more than “gut feel”? Could society benefit from a little more robot uprising in venture capital today?
[i] Grove & Meehl, Comparative Efficiency of Informal (Subjective, Impressionistic) and Formal (Mechanical, Algorithmic) Prediction Procedures: The Clinical-Statistical Controversey, Psychology, Public Policy, and Law (1996).
[ii] Gladwell, Blink: The Power of Thinking Without Thinking, Little, Brown and Company (2005)
[iii] Haynes, Weiser et al, A Surgical Safety Checklist to Reduce Morbitidy and Mortality in a Global Population, The New England Journal of Medicine, Volume 360:491-499 (January 29, 2009)
Me like post… take me to your leader… I mean investor…
Once again you raise some excellent points. If I was allowed to be as free wheeling as some of these VCs I’d probably get fired. I think a lot of VCs are feeling more pressure than ever to differentiate now, and this could be a great way if some of them were capable.
Some VCs are notably better at this than others, although I agree that the vast majority are intuitive. I’ve seen a few “quant” VC firms trying to raise money but never saw them get very far with LPs. With all those former Wall St quant people out of a job in the last few years, I wouldn’t be surprised if more of this takes root in VC.
Great way to start my day, thanks for this post! Of course, if VCs did get more quantitative us entrepreneurs would try to game the algorithm.
An intriguing thought for vc indeed. Thanks.
The classic struggle between Spock vs Kirk (logic vs intuition). Risk management (which is not the same as “no risk”) dictates logic while the occasional burst of intuition can lead to far greater rewards.
Most VCs won’t leave their comfortable positions for rigors they don’t have. It is a competency destroying move. They have it too good right now. But others will be more creative and will get out of comfort level to try new things. In time the best will rise to the top and lazy VCs will fall behind.
As a downtrodden liberal arts graduate myself, I can certainly appreciate this article. I think it’s true and going in the direction outlined, but hope there is room for us “soft” skilled thinkers out there. It’s becoming a more mathematical world, which is unfortunate for us non-mathematically inclined people.