The Problem With Analyzing Unicorns


analyzing unicorns

Early in November, Nabeel Hyatt blogged:

Aileen Lee posted a very interesting piece on TechCrunch where she lays bare some of the analysis she has done on “Unicorns” — startups that have entered the $1B club.
It’s a rarified club, to be sure.  In fact, it’s enough of a rarified club that I would call into question any conclusions one would assume by Aileen’s analysis.  The long version of why this wasn’t a good idea was the subject of my last post, but the short version is this: 39.
The starting data set is 39 companies.  Perhaps it’s a bit more than that as people expand the list, but it’s a pretty small number no matter what.  And it’s hard to reach any definitive conclusions with a number that small.

I have a different take on Aileen’s post.  There is a lot of mythmaking that goes on around Silicon Valley and the startup world — much of it based more on intuition than actual data.  Let’s face it, we make decisions and come to conclusions on a daily basis, whether insignificant or important, on nothing more than a whim.

That is especially true of venture investing and startups.  Anyone in the space will talk a good deal about data, but there are scarcely any proof points to refer to.  Did anyone think Airbnb was really going to make it when they were occupying their time making Obama cereal?  Did Facebook seem like a good bet when MySpace dominated social media?  Since we’re already Monday morning quarterbacking, how could Webvan not have been an enormous success?  How could Color or Airtime possibly fail to catch fire?  And while we’re mentioning Tumblr, did that really make a ton of sense as an investment?

Back to the post though.  It’s an interesting, albeit small, data set.  You can easily dismiss it as statistically irrelevant.  Even the number is up for debate (there was a NY Times article back in February, which speculated between 25 to over 40 startups).  However, that’s not what matters.  What the data set should open everyone’s eyes to is the fact that any company that reaches a $1 billion valuation is a total anomaly.

That is what the venture world is built upon, 40 companies (or more according to this hackpad).  The economics are such that you are damned if you are a large fund.  If a large fund doesn’t get into a couple of those billion-dollar companies, they’ll be toast.  It seems like a rather specious model by which to create an entire industry around, but LPs continue to be generous in the face of overwhelming odds and horrible track records.

Which is why I’m quite enjoying many of the reactions to this piece.  There are going to be plenty of folks that will take this data set and the accompanying results as some level of proof.  They’re going to use this as a new model or most likely as confirmation of existing biases.  And they’re all going to be crushed because you cannot predict Black Swans.

The lemmings, the social proofers, the quants and the pattern-recognition crowd are being laid to waste.  Evidence-based venture investing makes no sense when it is a grand slam contest.  The only way to be successful is to either go against the playbook or to position oneself to profit comfortably off of many smaller exits.  Even the last option is really nothing more than a hunch, based more on a review of the YC and 500 Startups’ approach of investing in diverse portfolios.

So what should you make of the unicorn analysis?  It is historically interesting.  In a sense, it goes against the grain of some of the startup lore about the “ideal startup” model, while agreeing with other beliefs.  But it’s also stuck in time.  What the billion-dollar club looks like in 5 years will be radically different.  There are more minorities and women founding companies now.  Entrepreneurs are starting younger.  New models and concepts are just starting to bear fruit (it should be noted that Bitcoin was only conceived of 5 years ago).  Even the goal of a billion dollars may not mean as much because we’re only at the being of the Internet Age.  Other industries had decades, if not centuries, to build their pillars and stalwarts.

As an entrepreneur, this discussion may sound like much ado about nothing.  Yet it’s important to understand that given the economics of the venture model, if you are not on a billion-dollar track, most VC’s are simply not interested.  If you don’t fit easily into a preconceived bucket of existing ideas (meaning you are novel or different), then you will get passed over by all but the few VC’s that actually do invest in outliers.  It’s no coincidence then that the VC’s that are doing well are also those that seem less prone to snap categorizations and are more willing to invest time into all the startups in their portfolio — not just the select few.  These are the firms willing to invest and support the mad ones, because it’s the mad ones that are truly changing the world.

This article was originally published on Strong Opinions, a blog by Birch Ventures for the NYC tech startup community.

Image credit: CC by rahuldlucca

About the author: Mark Birch

Mark is an early stage technology investor and entrepreneur based in NYC. Through Birch Ventures, he works with a portfolio of early stage B2B SaaS technology startups providing both capital and guidance in the areas of marketing, sales, strategic planning and funding.

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