Venture capitalists and investors are often regarded as wise and discerning in determining which new startups are ripe for growth and which should be avoided.
No industry titan is exempt from this one potential fatal flaw — the human mind. Cognitive bias makes everyone, not just investors, tend to make stupid choices or bad judgments based on certain feelings or beliefs. As an investor, I have seen far too many cases where brilliant VCs made terrible investments due to the conventions of their unconscious thinking.
In an industry where one wrong decision costs millions of dollars, there’s no room for illogical reasoning to sabotage sound strategy and decisions.
Understanding Cognitive Bias
This is the concept which Amos Tversky and Daniel Kahneman introduced in 1972: cognitive bias, a pattern of deviation in judgment that occurs in particular situations. These mental shortcuts from our brains are an implicit way our past experiences shape the future; no person is immune to cognitive bias and heuristics.
Most cognitive biases arise from System 1 thinking. This type of thinking tends to make mistakes when it is not balanced by the more analytical System 2.
Behavioral economics has adopted and expanded this idea, demonstrating that cognitive biases aren’t limited to venture capital but influence decisions across finance, healthcare, hiring, policy-making, and more.
For example, studies show that hiring managers struggle with confirmation and similarity biases during recruitment, which can result in overlooking more qualified candidates.
Retail investors often follow trends driven by herd mentality or overconfidence, as evidenced by the wild GameStop trading of 2021. Using helpful examples and real-world instances, my goal is to help you understand just how damaging biases can be when money, people, and outcomes are involved.
While there are numerous types of cognitive bias and examples of how they play out in daily life, these are the kinds you’ll commonly see in the venture capital industry:
- Confirmation bias
- Overconfidence bias
- Anchoring bias
- Availability bias
- Herding bias
Common Cognitive Biases in Venture Capital
Let’s quickly review the most common cognitive biases you will encounter, along with simple examples of how they might show up in the investment world.
Confirmation Bias: This bias is one of the more frequently heard about. This is something known as confirmation bias, where people tend to notice information or data that supports their original beliefs and either overlook or outright dismiss contradictory information. An investor may already hold certain assumptions about a specific startup and, thus, will only absorb advice or proof that supports the conclusion they initially formed.
Example: An investor with their heart set on a particular startup will only listen to advice or evidence confirming what they want to believe about that company. At the same time, they ignore warnings that it’s likely to fail because it’s burning through cash at an unsustainable rate.
We saw this during Theranos’s rise and fall. Investors ignored red flags in favor of data that supported their optimism, leading to a historic downfall. Despite multiple media reports questioning the company’s technology and internal processes, investors blindly followed founder Elizabeth Holmes’ vision. They wanted to believe in this revolutionary breakthrough in healthcare diagnostics so severely that it overshadowed the need for objective scrutiny.
Overconfidence Bias: This type of bias receives significant attention. Confirmation bias occurs when people selectively notice data or information that supports their existing beliefs and disregard all other information. One example is a tech startup that an investor already has in mind, but they will only consider advice or evidence that supports their opinion of the startup’s potential.
Example: A venture capitalist who had a remarkable record of selecting risky, outcast high-growth startups that went on to make him a fortune. This creates a false sense of security that she can do no wrong, leading to even riskier decisions based on that thinking.
A real-world example of overconfidence bias is the collapse of Quibi. Much-hyped Quibi, a mobile, quick-to-watch video platform that had never been tried before, landed massive funding of $2 billion and support from media mogul luminary names like Jeffrey Katzenberg and Meg Whitman. The leadership team had a track record of success and a compelling vision, so many people thought they would win. But they overestimated the market and mispriced consumer willingness to pay for short-form, mobile-only programming, which is why it has come so undone. This resulted in one of the most notable startup failures in recent years.
Warren Buffett captured overconfidence perfectly when he said, “What the human being is best at doing is interpreting all new information so that their prior conclusions remain intact.
Anchoring Bias: First impressions can be powerful. Anchoring bias is proof of this, as investors make decisions based on the first piece of information they receive, even if it’s irrelevant or misleading. They rely heavily on the initial “anchor” when making subsequent decisions.
Example: Founders tell a prospective venture capitalist that the valuation estimate is $10 million. Even if that estimate differs, the VC may use that initial information as an anchor point. Any further negotiations or assessments of the startup will be influenced by that first piece of information, leading them to overvalue or undervalue the company’s true worth.
Investors ignored such low valuations from earlier funding stages in Facebook’s private rounds. This led to a significant underestimation of the company’s actual growth potential, subsequently keeping them away from many valuable opportunities. Later investors, however, paid too much because they focused only on inflated valuations during the pre-IPO excitement. They believed those numbers represented intrinsic value.
Availability Bias: By focusing on personal examples that we recall quickly, we might give undue weight to the probability of a similar episode occurring again.
Example: If an investor recently succeeded with a series of technology startups, these wins will be easy to recall. They might overvalue their chances of success in the tech sector. They may invest more money in these startups, easily overlooking promising ventures in other industries and skewing their portfolio to be more technology-heavy.
This was easy to see during the dot-com bubble, when investors, overconfident from a string of early wins in internet-related companies, rushed to pour money into nearly any startup with a “.com” attached to it.
Herding Bias: When venture capitalists start following the decisions of other investors, rather than objectively evaluating the information for themselves, they are going along with the “herd” and not their analysis.
Example: A trendy new mobile app startup is getting much attention, especially from recent investors. Even without proper due diligence, more and more investors follow along, believing there must be something worth jumping into. As more firms follow, it’s mainly based on what others are doing rather than the company’s objective merit.
Do you remember WeWork? They fell into the hype, false endorsements, and FOMO, too. The writing was on the wall regarding practices and governance issues. Still, as in most cases, the firm followed rather than doing its research, which conferred a shade of respectability and legitimacy. This resulted in a multi-billion-dollar debacle that could have been easily prevented if more time had been allowed, discipline had been maintained, and proper analysis had been conducted. This, of course, tends to be terrible for investors with their firms unchecked.
Mitigating Cognitive Biases in Decision-Making
These biases can infiltrate investment analyses, potentially leading to negative impacts on investments and reputations.
Conduct Thorough Due Diligence
We need to put systems in place so these cognitive biases do not define a multi-million-dollar $ deal.
VCs are known for meticulous research, so this shouldn’t be challenging. When conducting research, questions should also address any preconceived notions or subjective ideas about the startup. Take into account any known or foreseeable biases, and add this alibi to the due diligence.
The research phase should encompass founder interviews, third-party market validation, customer reference calls, and competitive analysis. Verify facts and actively seek evidence that contradicts your initial ideas, not just to assess, but to make the jump willingly if corroboration supports it. It might seem counterintuitive to do individual research.
However, by allowing different groups to examine the data and form their own conclusions, you ultimately secure a more unbiased perspective, as emphasized in many other cases.
Implement a Structured Decision-Making Process
By establishing a standard structure that everyone in commerce knows and follows, it helps mitigate knee-jerk choices based on cognitive biases. Data-based analysis should be at the core of this structure. Reliable numbers should support every conclusion about a startup or investment opportunity. Data can help confirm the validity of theories.
Incentive investments are another essential aspect, as you should identify what the goals of your grant are before offering any grants (Metro). A singular investment thesis and strategy keep everyone on the same page with the goals you want to achieve and how you plan to do it.
Make the risk tolerance clear and define the expected returns in detail. Every investor should understand the expectations.
Utilize tools such as investment memos, internal scorecards, or machine learning platforms to establish a standard process.
With peer reviews and feedback mechanisms in place, the framework should ask the right questions and challenge assumptions. It’s no secret that investors can have egos, but these must be checked at the door to make the best, most profitable decisions.
Team Dynamics and Diversity
Focusing on diverse teams is one of the most significant contributors to reducing cognitive bias in VC firms. Whatever those norms might be, when you have people around the table from different backgrounds and cultures, they bring a set of new perspectives that can challenge many assumptions.
Groupthink can be dangerous as an investment style. Face-to-face interactions among individuals from diverse backgrounds and cultures will always offer a range of perspectives that can challenge assumptions about undiplomatic views.
And in investing as well, groupthink can be hazardous. People often overlook things when they come from the same place, attend the same schools, or share similar experiences. More diversity means more chances of someone piping up and saying “uhhm, are we missing something?
Whilst the fulfilment of such a requirement is crucial, the greater significance lies in perspectives — we realize that hiring experts from alternative industries and undoubtedly extraordinary individuals is vital due to diverse viewpoints, enhancing decision-making.
Moving Past Cognitive Biases to Successful Decisions
There’s no getting past cognitive biases sneaking into how investors think and feel about a startup. These are simply part of human nature.
Yet, the power of building solid and knowledgeable teams lies in the fact that these biases can be quickly identified and addressed through the proper settings and frameworks. Do savvy investors have a gut-level feeling about an investment, or a VC’s intuition, if you will? Of course, and in some cases, exceptions can be made when this happens.
However, a group of rational individuals working toward the same goals can prevent one person’s biases from leading to expensive and harmful choices. Behavioral finance will continue to shape the growth of new venture capital strategies. Investors who understand their biases usually make better choices, invest in proper processes, and build strong, successful portfolios.
Our industry is all about risk and chance. There are no guarantees. However, the investors who do everything they can to increase the odds of success are the ones who find their portfolios flourishing with sound investment choices that pay dividends in the end.
Featured Image Credit: Photo by Mikhail Nilov; Pexels
