Nine out of 10 startups will fail, at least six won’t return the money invested in them, whereas only one will return 5x or more. In addition, 70% of tech companies will go out of business within 20 months of raising money. The facts around venture capital funding can be downright discouraging. So why bother? Investors might as well blindly throw darts at a dartboard, argue the critics.

One of the myths around VC investing is that it pays off to be a specialist. If the hunt for the next unicorn (a private company valued at $1bn or more) is like looking for a needle in a haystack, it should make sense to focus your resources by dividing the haystack into distinct sub-quadrants. If the needle is in your part, fantastic! However, the needle may simply not be in your part of the haystack and your very detailed search efforts may be completely in vain. This leads directly to a second strategy: to diversify. If your search involves a larger share of the overall haystack, you have a higher chance of having the needle in your part of the haystack – but you also run the risk of not recognizing it.

Of course, real-world venture investing involves a more complex interaction of activities than in this intuitive example. Venture capital is not only about the early identification of the one-out-of-ten fund-returning startups but also about accompanying and mentoring them until their exit, the so-called “liquidity event”. With the humility of experience, no one can know upfront which of a VC’s investments is going to become a unicorn, or even if any will. Thus, the VC needs a disciplined and validated portfolio strategy.

What makes venture investing so hard?

Specialists argue that in an environment of omnipresent uncertainty, it takes enormous experience and a great network to identify and mentor promising startups. We wholeheartedly agree. Anyone who has ever made a startup investment decision knows how hard it is.

• First, there is usually a lack of history and data; it’s impossible to extrapolate or build models to predict where the firm will go.
• Second, some aspects of the venture are likely to be new – technology, product, market, or business model – so there isn’t an out-of-the-box recipe to follow.
• Third, the founder or founding team may never have built a startup previously, so their professional track record won’t tell you much about how they’ll perform in a new venture.
• Fourth, if the product isn’t yet on the market, we don’t know how users and customers will react to it.
• Fifth, there is always competition, but we can’t know a priori how they’ll react.
• Sixth, there are our biases as investors in perhaps seeing what we want to see (confirmation bias), group thinking (everyone else is investing in this field), the Lake Wobegon effect (the human tendency to over-estimate our abilities), or basing our decisions primarily on personal experience (saliency bias).