Statistics and big data took over baseball scouting some years ago, with the rise of Moneyball. More recently, those tactics have spread to the political world, with presidential candidates using big data to maximize their vote, and Nate Silver using algorithms to correctly predict outcomes in all 50 states.
Now we’re doing it, too. Instead of relying on the gut instincts, punditry and armchair quarterbacking that VCs are notorious for, our firm is pattern replicating to decide which entrepreneurs to fund.
Here are the components of a secret algorithm I developed that we use to score and rate potential investments with entrepreneurs.1. We look at (and score) what you read
What content has been uploaded into your cerebral cortex via apps, websites, PDFs, books and other miscellaneous educational all matter to your eventual success outcome.What books have your founder team read and what have you posted in your social media feeds? If they’ve spent time reading Technology Ventures, Gear Up, Four Steps to an Epiphany and tweeting knowledge nuggets – quoting chapter and verse – that could lift their entrepreneurial success score via our proprietary algorithm. Posting to Twitter your snowboarding pictures from Lake Tahoe might say something else.
Chris Sacca has been quoted as saying he goes right to Twitter and reads the last 50 tweets before he even considers taking a meeting. In our new VC algorithm, you can scrape and evaluate multiple social media streams for what founders have read, uploaded, integrated, and executed. Quality is great, but we are really looking for the quantity of entrepreneurial material comprehended.2. Age of cellphone number and time of first daily phone call
The age of an entrepreneur’s cellphone number reveals so much: their relative stability, how old they are, whether their number was a jettisoned friends-and-family program or an imported landline number. We get the age of cellphone number through a process called cellphone underwriting, which reveals all of the above and more, and which is perfectly legal but secretive enough that I won’t reveal how it works. At the end of the day, we’re looking for entrepreneurs who are young, stable, middle class, and who have the support of family and friends networks — and the age of the cellphone number tells us all those things.
So, I take the approximate age of a founder’s cellphone number and then during due diligence, I get a stat: The average time of their first phone call in the day. If you and your entrepreneur team are making and taking calls at 6:30 a.m PT, you’re probably talking with people back East and there’s a 50-50 shot you’re making north of a million in revenues.
So revealing data like this, that we used to W.A.G. (wild ass guess), we can now find out by using our firm’s make-shift cellphone underwriting API, which hooks in with Verizon and AT&T – the two main carriers of the iPhone. (And by “makeshift API,” I mean have our associate do it manually.)3. How Othman Laraki are they?
Othman Laraki is a tale that is told inside of the VC community. He sold something big to Twitter. He has degrees from both MIT and Stanford, but also has a ton of street smarts. As an example of his street smarts, he squatted in 2,000 square feet of office space at Stanford’s Engineering building. That duality of street smarts coupled with academic smarts is a critical component of my firm’s algorithm.
A fund that is now underwater used to troll for deals in the basement of the CS lab at Stanford without taking into consideration the street-smart component. They failed to realize that you can’t just replicate what other people already did super long ago — you have to innovate a quarter step. That team of VCs is now begging for LP money in the pay-for-play conference known as “Venture Alpha.” (Spoiler alert: They will not make it to their next fund.)
We don’t talk about the data inputs for this street-smart metric but as a hint: Augie Garrido once said, “Question authority but follow the rules.” We are looking for entrepreneurs who question the status quo and tip-toe the fine line, but still firmly understand rules and existing hierarchies.4. Stanford University founder team formula
If you reverse engineer the biggest exits, you can see that the whales in every fund’s portfolio had two or three founders from Stanford, with an odd-ball founder from some other school tossed into the mix. YouNoodle released public data on this observation. Our algorithm does not say “just Stanford.” It does say two or three founders from a good school with at least one in the litter that is not exactly like the others – think Cal, NYU, CMU, Illinois or MIT in a pinch.
Recently, Mark Suster, blogged about the phenomenon of overly homogenous founder teams. He argues that if teams are too similar where “all founders even have the same phone,” the founders will likely follow versus lead.
Remmy Oxley is the pseudonym of a Silicon Valley VC. Follow him on Twitter @RemmyOxley.
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