E436: Nnamdi Okike on Billionaires, Founder Psychology & the Venture Capital Bubble

David Weisburd (0:00)

Most venture capitalists believe that comes down to instincts good investing.

Nnamdi Okike (0:04)

You disagree, why?

Our belief is that it's really not instinct, it's more the totality of experiences that inform how somebody invests. And so our belief, that's really science at the end of the day. There's information that's going into that. The reason that it's been hard to quantify that is one, there's a lot of data points that can be subjective. When you're thinking about a founder and a founder's ability, it's harder to say this person is great or not great. You have to go a level deeper. And so our belief is that there is real science behind it, but you need to really unpack the elements and understand the key drivers. And there's a lot of nuance too. It's not purely a ones and zeros game.

David Weisburd (0:42)

And before founding 645 Ventures, which is five vintages, and you built out this Data Insights team at Insight. Tell me about that.

Nnamdi Okike (0:51)

Insight Partners was one of the pioneering firms to build this data-driven sourcing approach. Insight was started back in the mid-90s, so a long time ago now.

And Insight was one of the first firms to say, we can use a outbound sourcing, meaning going to the founders rather than waiting for a referral or inbound deal to come in.

And we could use data to inform where we look. Now, Insight was looking at companies that were post-launch with some revenues, right? So my first job out of college, I called it a glorified telemarketer job. It's basically calling up founders every day. I'd call up 15, 20 founders every day. And I'd say, I'd pick up the phone and a founder might pick up and I'd say, hey, how many employees do you have? And how much revenue and how fast are you growing? And kind of tell me about the product. And some founders would not answer, they'd hang up the phone and not want to talk. But some would say, hey, like, let me tell you about my business. And that those data points inform the quality of the company. We had metrics we would use around customer adoption, kind of how quickly were customers buying the product? What was the ACV, the average customer contract value?

How fast was revenue growing? And those data points really informed where we looked, and it enabled us to find deals that nobody else was seeing, right? Most of Insight's best deals in their first decade were deals that were, like, far off the beaten path. I'll give you one example. So one of the first deals I worked on was a company coming out of Indiana called Exact Target. Exact Target was a founding team that had been working in traditional mail marketing, literally sending out mailers. And they found that email, which at the time was like a new medium for marketing, could be used to market more effectively. And so when we came upon Exact Target, that company I think had probably five million of revenue, it was just growing to 10, it was bootstrapped, never raised venture, never even heard about, you know, kind of what venture was. But they had a really good business, right? In Indianapolis, where nobody was looking.

And so we ended up investing in that company. And that company ended up getting acquired for almost two billion dollars by Salesforce and went public.

David Weisburd (2:53)

Back when two billion dollars was a lot of money.

Nnamdi Okike (2:54)

Now it's not as much, but at the time it was a lot of money. And that was an example of a company nobody was looking at at the time. It was in a smaller city, way off the beaten path, hadn't raised money, it was bootstrapped. But it had these early metrics to kind of qualify the business as interesting, right? So that was Insight's DNA and bread and butter for many years.

And so when we started our firm, we thought, we started thinking a lot about, okay, how could you take that model and apply it to earlier stage companies? So companies that may not have 5 million revenues, maybe they had a couple hundred K revenues, but there were early signs that there was really something there. And we learned this over time as we built the firm. They had qualities as founders that were predictive of success, which is a more complicated.

David Weisburd (3:37)

You take a quantitative approach to the very early stage. What exactly are you looking for?

Nnamdi Okike (3:42)

It's an interesting question. As our firm has grown and evolved, we've gotten a lot more precise around that. So when we started the firm, we were taking really a page from the Insight Playbook. So we were looking at things like, this is back when mobile apps were big, we were looking at things like mobile app downloads and early adoption of those apps or rate of growth of web traffic, very traction driven.