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The secret is out that startup investing is binary, with the majority of VC industry returns concentrated on a few winners. And while Angel investors have addressed this power law via diversification, top tier US VCs have been more proactive, trying to predict breakout successes early and betting big.

In other words, if we knew ahead of time which companies will be successful, the ultimate outcome for any fund would be to invest 100% of it’s capital in one mega unicorn in its very first round. This new modus operandi, termed “Fundraising Acceleration”, leads to the obvious question: is it possible for VCs to accurately identify upcoming winners in a way that avoids price wars?

Learning from hedge funds

In the crowded and efficient public markets, the only way to consistently profit over time from trading stocks is by getting an “edge” aka proprietary information. The recent New Yorker article titled “The Empire of Edge” provides some examples of the lengths hedge funds go to for an information edge, including:

…in order to evaluate a technology stock, hedge funds sent “people to China to sit in front of a factory and see whether it was doing one shift or two.”…At their disposal was a boutique firm full of former C.I.A. officers who could monitor the public statements of corporate executives and evaluate whether they were hiding something

Hedge funds are focused on finding growth in stocks that others don’t yet see, and with the increasing digitization of startup investing, VCs will need to consider how to give their investment teams a similar “edge”.

Data networks

Similar to hedge funds, VCs will need access to tools that collect proprietary data and turn it into insights.

In terms of collecting the data, there has been a rise in software solutions aimed at making startup investing more efficient. Examples include cap table management, tracking of startup metrics, and generation of dynamic “one pagers”. These companies grow their data bases each time you use them, gathering proprietary startup data points around valuation, engagement, churn, and revenue that are impossible to gain at scale today.