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How Data Driven Strategies Help to overcome Cognitive Biases

12 most common biases and how data driven strategies can overcome cognitive biases

Wall-E

The human brain is an amazingly energy-efficient device. In computing terms, scientists estimate the brain can process vast amounts of information simultaneously to be 1 - 100 exaflops — with just 20 watts of power, similar to the energy consumption of a dim light bulb. To get a sense of what an exaflop is, imagine a billion people, each holding a billion calculators and pressing the equal button at the same time.

In comparison, one of the most powerful supercomputers in the world has recently demonstrated exaflop computing. But it needs about 13 megawatts, which is enough to power thousands of homes!

However, the human brain is not without limitations as it often uses shortcuts to make quick decisions due to a combination of evolutionary, psychological and social factors. As a result, humans inherently develop cognitive biases.

This impacts all aspects of life including the esteemed venture capitalist when it comes to deal sourcing, due diligence, decision making and etc. Traditional approaches to venture capital deal sourcing often suffer from cognitive biases that can skew investment decisions. Incorporating a data driven approach may offer a way to help mitigate these biases by providing objective information and improving decision-making processes.

12 most common biases in Venture Capital

Anchoring Bias

Anchoring bias occurs when investors rely too heavily on the first piece of information they encounter (“the anchor”) and can exert a disproportionate influence on subsequent decisions.

How Anchoring Bias Impacts Venture Capital Sourcing

Investors may have a first impression of a startup’s team, product, or pitch, which can disproportionately influence their investment decisions. By focusing too much on initial information, investors might overlook subsequent information that could indicate a startup’s true potential or risks.

Availability Bias

Availability bias occurs when investors rely on readily available information rather than comprehensive data, often leading to skewed perceptions.

How Availability Bias Impacts Venture Capital Sourcing

Investors may place weight on the latest market trends or highly publicised success stories, leading to a skewed perception of the founder and the problems they are trying to solve with their startup. Additionally, recent experiences with previous founders/startups may disproportionately influence decision-making causing investors to shy away from similar companies or favor them.

Confirmation Bias

Confirmation bias is the tendency to research for, interpret and remember information that confirms one’s perception or views, while giving disproportionately less consideration of contradictory evidence.

How Confirmation Bias Impacts Venture Capital Sourcing

Investors may be selective during due diligence and research that focuses on data that supports their initial positive impression of a startup while disregarding negative information. The initial assessments of a startup’s potential can become self-reinforced, leading to overconfidence in investing or passing on a company.

Herd Mentality

Herd mentality bias occurs when individuals make decisions based on the actions, and signals of others rather than on their own analysis and reasoning.

How Herd Mentality Bias Impacts Venture Capital Sourcing

Investors may overlook promising startups because they are focused on what others are investing in. This can lead to excessive investments into trendy sectors or companies leading to overvaluation and investment bubbles. Clear examples can be seen during the dotcom bubble, crypto bubble and recent 2021 tech bubble.

Conservatism Bias

This bias involves a tendency to stick with prior beliefs and opinions, even when new information suggests otherwise.

How Conservatism Bias Impacts Venture Capital Sourcing

Investors may be slow to adapt to new market trends, technologies or business models due to market timing, previously failures, lack of conviction resulting in missed opportunities. Emerging startups or sectors that did not work previously may be operating in a completely new environment and business models for it to succeed or fail.

Hindsight Bias

This bias involves seeing events as having been predictable after they have already occurred. This bias leads people to believe that they knew the outcome of an event all along, despite having had no way to predict it accurately.

How Hindsight Bias Impacts Venture Capital Sourcing

Investors may overemphasize the predictability of a startup’s success or failure, affecting their willingness to invest in similar opportunities. Investors may incorrectly attribute success or failure to specific factors, leading to overconfidence or undue risk aversion to the startup they’ve sourced.

Loss Aversion

Loss aversion bias refers to the psychological tendency to prefer avoiding losses rather than acquiring equivalent gains. This bias suggests that the pain of losing is psychologically twice as powerful as the pleasure of gaining.

How Loss Bias Impacts Venture Capital Sourcing

Investors may naturally shy away from high-risk, high reward opportunities due to the fear of potential losses, which is counterintuitive from venture capital investing strategies. By focusing too much on the negative or the unknown factors associated with a startup, investors may miss out on promising opportunities.

Overconfidence Bias

Overconfidence bias, the tendency to overestimate one's abilities or knowledge, can significantly impact behaviour.

How Overconfidence Bias Impacts Venture Capital Sourcing

Investors tend to be confident individuals. However, overconfident investors may take on excessive risk, believing they possess a superior ability to select or predict market movements. VCs who have previously selected previous winners in their portfolio may be overconfident in their ability to select winners again - especially before a successful exit and validating their success from near-term mark ups.

Recency Bias

Recency bias is the cognitive tendency to give more weight to recent events and experiences compared to those that occurred in the past.

How Recency Bias Impacts Venture Capital Sourcing

Investors may adopt reactionary strategies based on the latest news or market movements, resulting in the avoidance of potential new opportunities that might have longer term potential.

Regret Aversion

Avoiding decisions that could lead to feelings of regret in the future. This bias can cause individuals to be overly cautious, avoid decisions or invest into companies that could potentially result in negative outcomes.

How Regret Bias Impacts Venture Capital Sourcing

Investors may regret not investing in a company with limited indication of its long-term business fundamentals leading to making riskier bets without supporting information. Focusing on potential regrets can also lead to missed opportunities in similar companies or industries that have been previously invested.

Representativeness Heuristic

The representativeness heuristic is a cognitive bias where individuals judge the probability of an event by how much it resembles existing stereotypes or past experiences, rather than relying on objective data.

How Representativeness Heuristics Impacts Venture Capital Sourcing

This may be a misjudgement of a startup or founder based on similarities to other successful or failed ventures leading to missed opportunities. This can be otherwise referred to as pattern recognition or gut feeling that investors get based on their previous VC investment experience.

Survivorship Bias

Survivorship bias occurs when analyses or decisions are based only on entities that have survived a particular process, while overlooking those that did not. This bias can lead to an overly optimistic view of the likelihood of success by focusing on the successful startups (survivors) while ignoring the numerous failures that did not make it.

How Survivorship Bias Venture Capital Sourcing

Learning only from successful startups can result in incomplete insights as lessons from failures are not considered. Ignoring the failures can result in an underestimation of the risk associated with investing in startups.

Data-Driven Strategies to Overcome Cognitive Bias

Investors recognize the impact that cognitive biases can have on their decisions and may seek ways to mitigate these biases. Post-mortem analysis of previous investment decisions is an example of how some firms determine why companies were invested, passed or missed. By leveraging comprehensive data and AI to collect and analyze vast amounts of information can help investors make a more informed and objective decision. This data-driven approach can help counteract common cognitive biases by providing a more thorough and impartial view of a founder, markets, team, and trends that may have otherwise been missed.

Data platforms such as Landscape collects and analyze a wide array of information about startups providing a holistic view and widening the net for opportunities beyond traditional methods. This comprehensive approach ensures that investors do not miss out on promising startups due to cognitive biases like availability or confirmation bias.

AI significantly impacts the venture capital industry by offering more accurate and data-driven investment insights, reducing the influence of human biases. This enables less biased investment decisions, leading to more diverse and profitable portfolios. By adopting these data-driven strategies, venture capitalists can enhance their decision-making processes and achieve better investment results.

Combining Data and Human-Centric Approach

Venture capital is inherently a people-based service business, with many aspects not being able to be captured without human intervention. However, a data-driven approach presents an opportunity to identify investment opportunities and enrich information to provide a holistic perspective. Combining this approach with traditional methods, such as meetings and diligence calls, can offer objectivity and help counteract cognitive biases in investor decision-making.

While venture capital heavily relies on personal interactions and real-life meetings to collect crucial data points, investors can rectify the limitations of data-driven strategies. By integrating data insights with human information gathering, the deal sourcing & decision-making process becomes more robust.