MB on VC: The Risk of Relying on Cognitive Bias in Venture Capital Investing

In the venture capital space, successful fund managers must do three things consistently well to drive top-quartile returns. They must identify emerging excellence before other investors do, recognize underdeveloped value in their portfolio and nurture it to attractive outcomes, and avoid investing in “money traps.” The best VC investors do this over and over again. Average and sub-par fund managers consistently come up short in all these areas.

When I study what successful fund managers do that their less successful peers don’t, I find that most of the delta originates from how they make decisions. Successful decision-makers are keenly aware of cognitive biases that influence their decisions. Sub-par managers seem unaware of their cognitive biases, making them prone to repeating the same flawed decisions time and again.

The Common Biases That Impact Investment Decisions in Venture Capital  

The human brain is a complex instrument. It is mighty, but it is also subject to limitations. The brain attempts to preserve energy by simplifying information processing, which is why it is so easy to slip into using cognitive biases. Biases work as decision shortcuts (heuristics) that allow people to quickly make sense of the world around them. The problem is that these shortcuts can lead to sub-optimal, even disastrous, decision-making with respect to investments.  

As I mentioned in my post about identifying expert money managers, there are few truly skilled capital allocators who can identify outlier professional investors before it becomes obvious to everybody else. Most capital allocators resort to cognitive biases when evaluating money managers. And money managers are influenced by the same cognitive biases when making investment decisions.

These are the five most common cognitive biases that impact investment decisions:  

1. Story Bias
2. Functional Fixedness
3. The Bandwagon Effect
4. Recency Bias
5. Neglect of Probability Bias

Story Bias:   This is the tendency to rely on anecdotes, stories, and unproven strategies instead of facts and data when making decisions. As a venture capitalist, I hear a lot of stories. Many pitches we hear start with “what if” and “imagine this.” There is nothing wrong with that. I love good stories. Being a successful founder requires salesmanship, and the best salespeople sell stories. They do a great job of painting a picture of how a market could be improved. That said, good investors in startups, especially VCs that are committing considerable sums of money, must be able to determine if the story they are hearing is a complete fiction or a future non-fiction story.

Functional Fixedness:   Humans have the tendency to think of objects or concepts as functioning only in one fixed way. Thinking this way limits the ability to consider how the object or service could work in other, more creative, or better ways. People who suffer from Functional Fixedness bias are prone to miss investing in incredible opportunities. I see forms of functional fixedness bias all the time when people are evaluating new, more creative ways to address problems. Business model innovations almost always accompany technological innovations that change markets. For example, the ability to geo-locate people, car drivers, and destinations is the technological innovation that enabled Uber. But it was the business model innovation – the ability to create a digital network – that empowered Uber to become so successful. It was the company's ability to create a responsive, large digital network of riders and drivers that made Uber work. The business model innovation was perhaps more important than the technological innovation.    

Bandwagon Effect:   The bandwagon effect is the tendency to adopt philosophies, attitudes, or behaviors simply because other people have or do these things. Following others' actions or beliefs can occur because of conformism or deriving information from others. Much of the influence of the bandwagon effect comes from the desire to 'fit in' with peers. Particularly with investing, the risks of this cognitive bias are falling prey to groupthink or manipulation and missing out on exceptional opportunities that are not obvious to the masses.

As a side note, I must admit that my iconoclastic tendencies cause me to eschew even the best of trends. That characteristic makes me susceptible to missing great opportunities, but it also helps me avoid the bandwagon effect. I see examples of the bandwagon effect all the time in startup pitch decks. When the crypto currency wave was sweeping the market, we saw countless investment pitches that tried to tie a business solution to use of the blockchain and the launch of a digital coin to support it. Now that AI is all the rage, we have seen countless firms change their names to ‘Whatever-AI’. Their pitch decks talk about how they are using AI in their technology stacks. The truth is that most of these companies are developing simple technology that relies on simple rules engines at best. They dress it up with the AI moniker in the hopes that people will buy into the hype. These founders are trying to benefit from the bandwagon effect.  

I would love to say that most of our peer VCs and institutional investors don’t fall for this deception, but there is way too much evidence to the contrary. The bandwagon is a powerful lure for those who don’t understand or aren’t watchful of the cognitive biases that impact their decision-making.    

Recency Bias:   One of the better-known cognitive biases, recency bias is the tendency to favor recent events or data over historical events or data when making decisions. This bias is particularly risky in VC because it can prompt (sometimes impulsive) investments in companies based on their recent performance instead of their long-term potential. Investing in overvalued startups or growing at an unsustainable rate rather than evaluating businesses on their long-term competitiveness is a recipe for loss.  

In recent years, particularly after the massive economic stimulus that took place in the wake of the Covid outbreak, I met countless VCs who believed that writing $50M checks with limited or no diligence into businesses with little to no revenue (market validation) was a form of natural selection that would lead to long-term success. In fact, the strategy led to near extinction. Many of those funds – the types that funded WeWork and similar failed business models – have now retreated from most of their venture activities.    

Neglect of Probability Bias:   Neglect of Probability is a type of availability bias, the human tendency to base judgments on readily available information. It causes people to disregard probability when making decisions 'under uncertainty.' Instead, we pull from the most salient, anecdotal, or memorable information we have, which is often also the most recent or emotional. It's easy to see how Neglect of Probability bias can lead investors to make decisions based on emotion instead of data and analysis, which is a fast track to poor outcomes.

The Difference Between Success and Mediocrity  

In VC, the quality of decision-making is one of the most potent forces that distinguish excellent fund managers from average professionals. That's not to say that successful fund managers occasionally don't rely on cognitive biases. They do. We all do. But they also maintain a critical awareness of heuristics and their risks. Capturing exceptional outcomes demands objectivity, discipline, clear-headedness, and the courage to mitigate cognitive biases – often with data. Those efforts involve rigorous due diligence, continuous learning, and an openness to innovative ideas and models that might exist on the periphery of everyone else's viewpoint.  

The point is this: in VC, return performance suffers greatly for anyone who makes sub-par investment decisions based on cognitive biases. The best fund managers consistently apply a disciplined, data-centric approach to decision-making to avoid the risks that come with relying on heuristics. These are the professionals who will be able to help you distinguish between a compelling narrative and a viable investment opportunity.  But cycle after cycle, the pedestrian, impulsive managers reinvent themselves and start a new beginning on the road to wealth destruction.

The Rebirth Enigma

The funds that are linked to bandwagon effect, story bias, recency bias and other cognitive biases are clearly identifiable. Their results are well-known to be pedestrian at best. The irony of the situation leads to questions – how do these funds continue to raise massive sums of capital from institutional investors?  What is going on with institutional investors who would entrust these money managers? Is the fear of missing out so powerful that people who should know better still cannot overcome their cognitive biases?  Why are the boards of these institutional investors not speaking or acting against these behaviors? Why do smaller funds continue to co-invest with these funds when the odds of losing money clearly increase when they are involved with a startup?  

These questions are as old as the cognitive biases that inspire them. And those biases are as old as humanity itself. We won’t answer them now, but what we can do is work to spot them, avoid those who fall victim to them, and decide to think and behave in a way that’s clear-eyed, informed, and attuned to the actual value of a startup and needs of individual investors.