The nature of information and overconfidence on venture capitalists' decision making

Abstract Venture capitalists (VCs) are considered experts in identifying high potential new ventures—gazelles. Thus, the VC decision process has received tremendous attention within the entrepreneurship literature. Yet, most studies on VC decision-making focus on which decision criteria are central to selecting gazelles. Although informative, the majority of these studies has neglected cognitive differences in how VCs make decisions. This is surprising considering the influence cognitive differences are likely to have on the exploitation of an opportunity as well as its influence on likely success. The current study investigates whether VCs are overconfident, as well as the factors surrounding the decision that lead to overconfidence. Overconfidence describes the tendency to overestimate the likely occurrence of a set of events. Overconfident people make probability judgments that are more extreme than they should, given the evidence and their knowledge. In the case of the new venture investment decision, overconfident VCs may overestimate the likelihood that a funded company will succeed. The results of the current study indicate that VCs are indeed overconfident (96% of the 51 participating VCs exhibited significant overconfidence) and that overconfidence negatively affects VC decision accuracy (the correlation between overconfidence and accuracy was 0.70). The level of overconfidence depended upon the amount of information, the type of information, and whether the VC strongly believes the venture will succeed or fail. As more information becomes available, people tend to believe they will make better decisions; they are making a “more informed decision.” More information ideally should enable the VCs to assess any potential pitfalls. However, additional information makes the decision more complex. Information factors may contradict and relate to other information in unexpected ways. Even if more information is available, people usually don't analyze all of it (even though they believe they do). Thus, more information creates greater confidence, but it also leads to lower decision accuracy. The type of information that is available also impacts overconfidence and decision accuracy. VCs are intuitive decision makers. When people are familiar with a decision and the structure of the information surrounding that decision, they resort to automatic information processing. On the other hand, if information surrounding the decision is structured in an unfamiliar way, people need to decipher what each piece of information means and how that impacts their overall accuracy. In the case of expert VCs, that means they must deviate from their intuitive style. It seems that forcing them outside their “comfort zone” has a negative effect on their confidence and has an even greater effect (negative) on their accuracy. There is evidence of an “availability bias” in VC decision-making; VCs rely on how well the current decision matches past successful or failed investments. VCs are overconfident in their prediction of venture success when they predict a very high level of success. VCs are also overconfident in their prediction of venture failure when they predict a very low likelihood of success. This high level of overconfidence in success predictions (or failure predictions) may encourage the VC to limit information search and fund a lower potential investment (or prematurely reject a stronger potential investment). Although overconfidence in itself does not necessarily lead to a wrong decision, the bias is likely to inhibit learning and improving the decision process. Overconfident VCs may not fully consider all relevant information, nor search for additional information to improve their decision. Moreover, the natural tendency for people to recall past successes rather than failures may mean that VCs will make the same mistakes again. VCs can take simple steps to reduce the effect of overconfidence, including counterfactual thinking (i.e., imaging scenarios where current assumptions might not hold), formally recording how past decisions were made at the time of the decision (versus trying to recall how that decision was made from memory), and using actuarial decision aids that decompose decisions into core components. Reducing overconfidence may lead to stronger decisions. It is hoped that this study illustrates the power of cognitive theories for understanding VC decision-making.