The Unicorn Paradox

Success is a probability, with extreme success founded on extreme probability. This breaks the math.

Many ventures have achieved enormous success, (e.g. 1205 global unicorns) due to startup accelerators and venture funds providing funding and network support to new startups. Our research tracked “the Big Three” accelerator programs, Y Combinator, Techstars, and 500 Startups. These accelerators retain a 1.5% rate of unicorn contributing 139 of the 1205 or 11.4% of all global unicorns.

However, the success of funding programs, through its high number of alumni unicorns, is cause for the oversaturation of unicorns in the market. Natural progression of a successful startup typically follows into an exit, either by acquisition or initial public offering (IPO).

The high number of unicorns appears paradoxical to the fundamental basis of a startup lifecycle. Within the past 10 years, only 200 software companies have gone public, compared to the emergence of over 1000 global unicorns in the past 10 years.

So why are there so many unicorns?

A 1.5% rate of unicorns shows the statistical improbability of a company’s chances, only made possible through a compelling product, driven founder(s), and outstanding teams. 

It is without doubt that such an anomaly would garner significant interest and quickly get acquired or eventually go public. 

Surprisingly, a large reason behind the prominent lack of unicorn exits falls directly upon that of the VC itself. Specifically, the economics and mathematics that drive long-term strategy and investment. Many firms expect a 4-5% rate of constant return, with mathematically derived exit requirements and acquisition criteria.

However, the math only considers the range of companies that are labeled as “normal.” Those that follow natural tendencies and see steady linear growth are considered normal, in this case. The mathematical models and machine learning algorithms that VC’s employ are consistent and effective with ‘normal’ data and companies. This is a testament to successful portfolios and profitable returns for many VC firms. 

The anomalies that are unicorns (characterized by exponential growth, enormous market share, and domineering products) do not conform to traditional standards. The fact that 1000 of the total 1200 unicorns have appeared in just the last 10 years shows the irregularity that characterizes unicorns.

VCs dictate exit requirements, acquisition metrics, IPO criteria, etc., which are reasonably achievable by “normal” standards. Unfortunately, the math for these metrics ends up serving as an impossible barrier for unicorns. Thus, many unicorns end up stuck and unable to exit, causing a perceived oversaturation of unicorns in the market. This leads to bubbles.

We’ve previously discussed the success rates and outcomes of the ‘Big Three’ accelerators. Statistically, accelerator alumni break out along the following groups:

• Unicorn status: 1.5%
• $100M or more valuation: 3.8%
• Sustainable success: 10.8%
• Walking dead or dead: 83.9%

The ‘Big Three’ are notorious for their ‘shotgun approach’ to investing: Chasing a variety of startups without regard to funding round, category, and growth stage, hoping that a couple of shots land on target.

This allows for a relatively comprehensive overview in how accelerated and VC funded companies fare over time. Even with the shotgun approach the Big Three only sees a 1.5% rate of unicorn. This is indicative of the obvious statistical rarity of such successes.

Unicorns are considered outliers. Statistically, they may not be factored into any established mathematical or machine learning model when projecting expectation within normal means.

This outlier status causes our Unicorn Paradox: where the improbable success of unicorns serves as its own barrier to exit. Irregularities, especially for unicorns, are not confined within the statistical bounds of normality. Success should not serve as its own hindrance for further growth. 

The typical barriers to exit for unicorns may include:

• Structural friction for IPO (lawyers, legal, SEC reviews, etc.), however the lack of funds within unicorns is a rare occurrence
• VCs won’t surrender their positions due to the potential for continued growth
• Too expensive to acquire 
• Founders face undesirable scrutiny and loss of control through the IPO
• By definition, Unicorns don’t follow patterns

So now what?

The Unicorn Paradox is the disconnect between VC math and unicorn founders. Using mathematical and economic models derived from statistical methods, VCs have attempted to standardize “normality or expected returns” to company growth and revenue. This has rejected their greatest asset, the unicorns, from achieving the standards set in place by the math itself. 

For the vast majority of founders who have taken VC money, the formulae set in place by VCs are achievable. However for the 1.5% of unicorn founders attempting to build the next Stripe or SpaceX, the greater your success, the greater the risk to break the math.