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Many would-be entrepreneurs think that people who invest in early-stage companies have a complex and sophisticated decision-making process, akin to what happens on Wall Street. But, unlike the world of high finance where investors gather copious amounts of information and use complex computer modeling to make decisions, investors in early-stage companies spend very little time and gather very little information when making choices.

Perhaps perversely, this approach makes perfect sense.

Before I get into why it makes sense, let me explain how most early-stage investors make decisions. Venture capital firms and angel groups typically screen the business opportunities they receive on the basis of a couple of simple criteria. First, did someone they know and trust refer the deal? If the answer is “no,” the opportunity is almost always ignored or deleted without even being opened or read.

When investors do look at an opportunity, they tend to make a first cut by scanning the executive summary of the entrepreneur’s business plan or the entrepreneur’s pitch deck – the PowerPoint slides the entrepreneur prepares about his or her venture.

This initial screen is very fast. South African venture capitalist Keet Van Zyl explains in one of his posts on the topic that the average venture capitalist spends less than 30 seconds evaluating a business plan.

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If the venture makes it past this hurdle, investors still don’t spend much time on it. They simply give the founding team a little time to make a pitch. A study I did a few years ago showed that the typical angel group allows the few entrepreneurs who make it through the initial screen 20 minutes of presentation time and 15 minutes of Q&A before deciding whether or not to proceed to due diligence. Venture capitalists generally allot similar amounts of time to presentations.

Only after this part of the screening process is over do investors spend much time at all evaluating investment opportunities. By then we are down to perhaps 1-in-200 ventures.

As perverse as it may sound, this approach makes a lot of sense for two reasons. First, early-stage investors will put money in a tiny fraction of ventures they see. Virtually every business they consider will be a “no.”

There are many paths to get to “no.” The opportunity doesn’t fit the investor’s expertise or her fund’s mandate. The team is wrong. The IP is too weak. The market is too small. The venture will take too much money to develop. IPOs never occur in the startup’s industry. The supply chain is too complex. The forecasts are unrealistic. The list goes on and on. A 30-second scan of an executive summary will identify a reason not to invest in 99 out of 100 ventures presented to an investor.

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Second, the prospects of new ventures are uncertain. Not risky, but uncertain. As economist Frank Knight explained brilliantly back in 1921 in his classic book Risk, Uncertainty and Profit, something is risky when we don’t know what will happen in the future, but we know the probability distribution of outcomes. Something is uncertain when we don’t know what will happen in the future and we don’t know the odds of different results occurring.

Early stage investors live in a world of uncertainty. No one knows whether an entrepreneur will be able to build the product, or customers will buy it. No one knows if competitors will crush the startup or it will win; if the team will fall apart under crisis or come together; or if later investors come in and crush down the early backers of the company of those early financiers will escape unscathed. And no one knows the answer to a hundred other questions that matter for startup success or the probability distribution of their outcomes. Moreover, the probability distribution of all of these outcomes is unknowable.

If things are uncertain – that is, the probability of outcomes is unknowable – then spending a lot of time trying to gather information is unproductive. There is no information that you can find to know the unknowable.

Experienced startup investors realize this and don’t waste their time trying to know the unknowable. Instead of trying to calculate the probability that a string of unknowable outcomes will occur, they instead look at the upside. If that which is unknowable worked out in a positive way, they ask, is the investment worth it?

For example, they ask, “If I invested in this company, is it possible that it will be a unicorn that will go public in a Facebook-sized IPO?” Then they spend their time on looking more carefully at the handful of ventures where the answer is “yes.”

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