In The General Theory of Employment, Interest and Money, Keynes wrote about investment through the metaphor of a newspaper contest to select the six best looking people from a group of photos, with the prize being awarded to the contestant whose choice most closely corresponded to the average of all contestants.
Keynes’ point was that, despite the clear and simple instruction, contestants are actually not inclined to consider which of the photographed people are the best looking. Rather, they now consider a third-degree perspective of ‘what would the average person imagine that the average opinion is?’
We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. And there are some, I believe, who practise the fourth, fifth and higher degrees.John Maynard Keynes, Economist
In A Simple Model of Herd Behavior, Abhijit V. Banerjee examined the inefficiencies created when decision making becomes reliant on signals from others. We become inclined to abandon our own data, in favor of prioritizing signals which themselves may also be based on nothing more than another prior signal.
If decreasing returns (average payoffs decline as the number of people who choose it increases) tends to reduce herding, one would expect increasing returns, which rewards doing what a lot of others are doing, to increase the tendency to herd. This is indeed what we find.Abhijit V. Banerjee, Ford Foundation International Professor of Economics at Massachusetts Institute of Technology
There are a number of social psychological drivers of this behavior, but the most obvious are our desire to associate with popular choices, and the greater dispersion of responsibility if that choice proves wrong.
Consensus threatens innovation
Generally, herd behavior is problematic in how it undermines sound judgment and rational choice, though by nature it tends to be low-stakes and risk-controlled. For venture capital, this innately human behavior should be viewed as an existential threat, running contrary to the needs of effectively identifying and funding innovation.
If no great book or symphony was ever written by committee, no great portfolio has ever been selected by one, either.Peter Lynch, former manager of the Magellan Fund at Fidelity Investments
The root of the name venture capital, as Evan Armstrong reminds us in Venture Capital is Ripe for Disruption, is adventure capital. It’s only really an adventure if you’re not sure of the destination, and backing innovation is exactly that: you are straying into the unknown; high risk, large potential reward.
The classic archetype of a venture capitalist, fitting with this concept, is a highly perceptive and analytical individual who can evaluate all kinds of oddball, out-of-the-box startups and identify the ones with potential. Someone who sees opportunities where others do not, who does not care about (or actively avoids) pattern-matching with past successes, and who ignores the noise of signals from their peers.
There is an old saying in enterprise software, “No one is fired for buying IBM”—people mitigate risk for their decisions by choosing the consensus option.Evan Armstrong, ‘Reformed’ Venture Capitalist
This occurs even in the supposedly risky world of venture capital.
Hunger drives herd behavior
In recent years, as the appetite for cheap capital grew to unsustainable heights, venture capitalists became preoccupied with following external signals to ascertain whether the market would agree to provide capital to their portfolio. Would their peers validate their investment choices? Would prospective LPs recognise the value of earlier investments if they weren’t shared with other respected names? Herd behavior crept in with pernicious effect; the seductive comfort of piling into seemingly safe deals with other investors. Manufacturing winners.
As long as the peer-group of venture capitalists agreed on valuation growth in future rounds (and why wouldn’t they) it was still a good model, right?
As long as the (paper) returns were good, it was still venture capital, right?
We know how that ended. We also broadly know why it ended (crude valuation practices, interest rates making capital more expensive, slow public markets backing up exits… etc). The question we should ask now is what can be done to stop it happening again?
Learning from mistakes
Anyone involved in investment of any kind should be aware of the way signals should be handled (with oven gloves). It is valuable input that can shape an investment decision but shouldn’t drive it. For venture capital, that might mean reevaluating everything from deal flow management to valuation practices.
- Are the majority of your deals sourced through referrals from other investors?
- When evaluating potential investments, how quickly do you reference recent similar deals?
- How much analytical rigor are you applying to the individual nature of each opportunity?
- When setting valuation, how much do you rely on crude ARR multiples?
- How much does the VC Twitter echo-chamber shape your approach to early stage investment, generally?
These might seem like basic questions, but there is clear cause to begin a first-principles reevaluation of how capital is allocated to ideas and founders. The responsibility is to effectively fund technological progress, not to exploit an uncertain market for short-term gains.
A new approach, with a more analytical focus on individual businesses, may seem unrealistic: too much time involved, too much uncertainty. To that, I’ll close on three points:
- Startups in 2023 are running leaner. The great hunger for capital is over, for now. That opens the opportunity to strike out and make fund returning deals without needing to drag other investors along with you. Your ability to identify winners (not simply agree on them) matters more than ever.
- There are tools and frameworks which make analysing startups in detail much more practical (Equidam is an obvious example). Build a process which lets you collect data about opportunities and decisions, allowing you to develop and codify your experience.
- Reconsider industry dogma about practices and perceptions (for example: about financial projections at early stage). More data = better decisions, you just need to pick the right lens to derive the right value.
As many have said, the 2023 vintage has great promise. Particularly for investors who best adapt to the new conditions.
[EDIT 26/03/2022: Adding a link to Chamath Palihapitiya’s fantastic article about herd behavior in venture funds and the risks involved. It’s a much more analytical perspective, which you can read here.]