"But why are other VCs not investing?"
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“But why are other VCs not investing?”

On October 24 nuTonomy, which builds self-driving car technology, announced it was being acquired for $450 million. I had been part of the seed round in November 2015 and the Series A in April 2016, and have watched the company’s progress closely over the last two years. It is a fantastic story with a huge cast and the nuTonomy team undoubtedly as protagonists.

When I first met nuTonomy, no other institutional investor had yet made a bet on the company. I remember very well hearing the question “But why are other VCs not investing?” from many different parties, including my teammates.

This is a common challenge for both entrepreneurs and investors at the very cutting edge. VCs are supposed to spot an emerging technology or trend before everyone else sees it and then nurture it through capital, advice, introductions, and governance. Even the best of us succeed only sporadically, but as a class VCs have identified and backed many companies that have changed the world.

So how do you get backing for taking a risk? Below are three counterintuitive lessons I’ve learned from this journey, as well as observing investments my colleagues and other investors have made.

1) Don’t (Just) Listen To Your Gut

When I first discovered nuTonomy I was absolutely intrigued — but instincts aside, I had at best a superficial understanding of the space they operated in. To have conviction in making an investment I decided first to learn more, which involved months of debating with professors, talking to industry experts, reading analysis and research papers, and understanding the competitive landscape. Our thesis around autonomous vehicles allowed me to convince my partnership to take the bet, not just a gut feeling around the team or the space. I have seen this repeatedly in a variety of frontier technologies, whether it be AR / VR, big data, or blockchain, where there just is not enough data and traditional metrics can actually blindside you.

2) Embrace The Unconventional

While the whole world is looking at machine learning with the perspective of “more data with less explainability,” I saw in nuTonomy the unconventional approach of “less data with more explainability.” Self-driving cars are very different from social apps — there is really no room for errors when you play with people’s lives — and therefore I saw nuTonomy’s emphasis on more explainability with less data as better way of going to market. This conclusion was driven not by pattern recognition but by a fundamental principles-first analysis, which I would argue is true for many of the most disruptive investments. I was not expecting universal consensus, but just enough to get backing for an unconventional bet that the majority might not have made.

3) Let Your Cons Be Your Pros

Financial VCs are often competing against each other on their speed of decision-making, their personal brands, and the networks they can leverage. Corporate VCs have a different value proposition, which is usually the platform they can provide, and are not as beholden to other factors. Knowing that my decision-making would be slower also gave me the opportunity to be thoughtful in my diligence, which I might not have had the luxury of in a fund that has to move faster.

Having seen this consistently with colleagues on my team and in other corporate VCs, it makes me wonder if it also makes corporate VCs more grounded — i.e., less likely to invest just because someone else is investing. Being willing to be the first institutional money in means bucking many cognitive biases around social proof, and having consistent conviction is the key to getting there.

“Why are other VCs not investing?” may be a valid question, but the line between misguided conviction and rational precognition is very fine indeed. nuTonomy went on to get a huge amount of interest from VCs. My lessons are arguably most relevant for other investors but hopefully can be an insight to entrepreneurs also on how VCs think.

Thanks to Ajay Singh for inspiring this article and to him, Raymond Liao and Ryan Lawler for feedback. These are purposely short articles focused on practical insights (I call it gl;dr — good length; did read). I would be stoked if they get people interested enough in a topic to explore in further depth.

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