Jun 11, 2021
Venture Capital

GoingVC Research: How to Make Better Venture Decisions

Executive Summary

Success in the Venture Capital industry is predicated on distilling down piles of information into a single decision: invest or not invest. As the industry adopts more technology and a data-driven approach, often overlooked are the hidden biases that lead to suboptimal decisions.

In the world of investments, the study of these biases are collectively referred to as Behavioral Finance. In this paper we detail these biases that affect decision making and adopt a framework for thinking smarter for the Venture Capital industry.

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Behavioral Biases Explained

How does the way information is framed, past personal experiences, or lack of statistical mindset affect decision making? These are the questions that are asked and attempt to be answered by Behavioral Finance studies.

For the past several years, the financial industry, particularly financial advisors and investment managers, have adopted Behavioral Finance as a means to improve client communication and portfolio management. This means incorporating the learnings into the entire process, from client sourcing through security selection.

How is this relevant to the Venture industry? We believe that VCs can improve how they source and diligence opportunities and manage portfolios. Throughout the remainder of this paper we will show how these principles can be applied to VCs and Angel investors.

The fathers of Behavioral Finance are Nobel Prize winners Daniel Kahneman and Amos Tversky (cite the paper/book). At the core of their research is the hypothesis that human beings suffer from cognitive biases that impair their decision making process.

Kahneman and Tversky post that there are two ‘systems’ in which we, as humans, use to think: System 1 (Fast) and System 2 (Slow). System 1 is characterized by one that is based on intuition and perception and operates quickly and almost automatically. This system uses heuristics (i.e. mental shortcuts) and is most vulnerable to the types of biases the research identified and for which it attempts to derive solutions.

System 2, on the other hand, is based in logic and is more thoughtful, effortful, systematic and flexible. This is the ideal system for decision making and is less vulnerable to these biases.

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