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February 18, 2019

The Importance Of Heuristics In Startup Investing

What is Heuristics?


Simply put, heuristics is a practical and creative approach – as opposed to a strictly logical and proven method – to learning or problem solving that is nevertheless effective in reaching a goal.


Humans use heuristics all the time when the other commonly used methods are impossible or impractical to use. This type of analysis may not be rational or logical, but it is sufficient to reach an immediate solution, based on prior similar experiences.


If you’re beginning to think this sort of decision-making process often applies to early-stage investing you are 100% correct: It’s hard to make a purely fact-based investment decision based on past financials and data when there is no such evidence.


Heuristics may simply be called an educated guess or the use of common sense, rather than using real data for real analysis. It often functions by working backward or by making intelligent assumptions.


The most significant advantage of heuristics is that it is flexible. It is the best alternative for making quick and informed decisions when real data is not available or is too limited to use in complex models.


Significance of Heuristics in Early Stage Investing


Heuristics forms a part of behavioral finance. Investors need to make decisions on a day-to-day basis and their decisions that cannot always be based on complex models and concrete numbers – especially with startups. In these types of situations using available information and coming up with the best decision possible is the way to go.


Early stage investing involves believing, or not, in the ideas, products/services, and their future potential. The startups almost always are in an early stage and have limited or no operating history. There are no balance sheets to review, no revenues to extrapolate and no performances to measure. It is here that common-sense heuristics is useful.


Investors can look at the available data, ideas, team, product or service, market strength, competition level and form a mental picture of the company’s future potential. Based on previous experiences with similar companies, a similar market, and related products, an educated guess is possible.


Therefore, despite the lack of real data, the commercial success or failure of the startup can be forecasted as accurately as the situation permits.


Heuristics is most applicable to uncertain situations. Early-stage investing has considerable uncertainty! Who could have valued Uber or Instagram in the very beginning! Neither the founders nor the investors are sure of the outcomes, market acceptance, or the profitability of the venture.


Therefore, to make the best of the available information, many investors employ heuristics instead of, or along with, real data analysis.


Drawbacks of Heuristics


Despite its advantages, heuristics suffers from obvious drawbacks. It is not a strictly logical or evidence-based approach and is, therefore, subject to many cognitive biases. Most often, you hear that VCs will look for similarities in a founders characteristics (e.g., this guy reminds me of Mark Zuckerberg or Steve Jobs, this could be huge).


While being able to identify promising founder characteristics is highly valuable, because much of what you invest in during the early days of a company is the founders, investors can be affected by stereotyping and judge one founder based on the performance of another similar one. However, even if two founders strongly resemble each other, their statistical business facts and other detailed nuances may be completely different. Heuristics often ignores this.


Similarly, investors can be affected by anchoring bias and base their decision on just one strong piece of information (e.g., this founder comes from the same accelerator as Airbnb).


They could also be influenced by availability bias, by judging the startup based on the ease with which similar instances can be recalled (e.g., we just won huge with Uber, thus this peer-to-peer marketplace will likely also be huge) .


Bottom line: Heuristics is often subject to confirmation bias, where investors tend to interpret information based on their preconceived notions. Careful steps must be made to guard against this risk.


What You Should Take Away


Heuristics do not always produce accurate results and can lead to a deviation from the optimal solution. There is also considerable skepticism about how effective these “common sense” decisions are since they can be affected by various biases.


However, in the case of early-stage investing, where only limited information is available, and there is not always hard data to work with, heuristics tend to offer a significant value add to decision making.


It is a critical thinking tool that is valuable to conducting due diligence on startups. Instead of seeing black and white, heuristics help to create an informed investment thesis based on a well rounded thought process, rather than one that overweights any one data point or lack thereof.


Regardless, be sure to have a due diligence methodology that involves several key inputs (e.g., market size, founder experience, terms) to reduce the chance of heuristics overruling general sensibility.  


And of course as we always stress, build a diversified investment portfolio. With a lack of data and track record in the early days, all the heuristics and data in the world will still not always yield positive results and thus it is important to place many small bets instead of a few big ones.


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About: Chris lustrino

A Boston College Eagle for life, on a mission to democratize startup investing for all people at KingsCrowd, with a passion for Fintech, investing, social impact, doing well and doing good, and an avid runner, cyclist and writer.

View Chris lustrino's articles

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