Q&A With a New Type of VC, John Sharp

Venture Capitalists using data, deep learning, and AI powered insights to analyse early stage startups may seem like the impossible dream. Hatcher+ has made it a proven reality. Partner John Sharp sat down with CRIISP Media today and provided an inside – look into the inner workings of a VC that has analysed 11,000+ deals and completed 105 investments – just in the past year). With investors in his fund such as Coca – Cola Amatil, Midis Group, and Mistletoe Group it’s well worth sparing a moment to hear what he has to say!

Q1. To begin with, Hatcher+ might be a foreign concept to many, you claim to provide predictable returns in the space of early-stage investing, can you give us an overview on how that’s achieved?

Ten years from now, we expect it is traditional VC structures that will appear foreign.  Hatcher+ is based on three simple and easily-proven premises:

  1. If you diversify your risk across industries and geographies, your returns will become more predictable.
  2. In an environment in which failure rates are high and a handful of power curve effects are responsible for the bulk of the returns, you need to dramatically increase the size of your portfolio (INSEAD research recommends increasing your portfolio size to at least 500 companies)
  3. Valuations in earlier stages are much more favorable to investors, even allowing for the much higher risk of failure.

Q2. How did you come across the problem, more importantly, how did you figure out the solution?

We systematically studied the outcomes over 20 years for both individual investments and portfolios, and the results were not ambiguous in the slightest.  Only a handful of outlier small funds generate large multiples – the majority of small funds fail to deliver even Nasdaq-level returns.

We figured out the solution by building over 4 billion simulated portfolios using 600,000 venture transactions spanning 20 years and 40 countries.  The output of those simulations clearly shows that a strategy of building larger, earlier-stage portfolios creates more robust returns.  We also did a survey of investors and discovered that a majority of professional investors select and invest in deals at a rate of roughly 1 in 100, or 1%.  These two findings form the core of our strategy, which is, for every 100000 companies we analyze, we expect to invest in 1000, and have approximately 10 large-scale exits.  This 1 in 10,000 strategies is only possible is you use data science and significant levels of automation in combination with a wide deal origination network.

Q3. Seeing the volume of companies and data you are dealing with, you must have insights others would dream of, such as;

– What characteristics of a founder indicate future success?
– What characteristics of companies indicate future success?

We are continuing to compile massive amounts of data, and are forming some early opinions on what characterizes a good bet when it comes to founders and companies.  However, we don’t yet use these outputs, or our AI, to make decisions – we only use them to provide guidance to the very smart people working within our deal origination network.  We advise people using our advice to see this analysis as just “one voice at the table”, rather than THE voice at the table.

Q4. What is Hatcher+ looking at right now, what sectors excite you?

Hatcher+ is sector and geography-agnostic in large part.  What excites us is seeing a deal back by a great team of founders and accelerator partners that scores highly in a sector that isn’t yet over-bought.

Q5. Being a trailblazer in the space of predictable VC what does the future of VC look like to you?

We recently commissioned a report from Insight Group that we plan to publish in the next few weeks called The Future of Venture Capital.  Without giving too much away, we believe the future of VC will belong to those large-scale entities willing to invest a significant percentage of their annual operating expenses in data and technology.  Right now, most VCs spend less than $100,000 a year on technology, and some spend less than $10,000 a year.  Making blind bets on small portfolios without the benefit of data (and the ability to build a large portfolio) will continue to happen, but on a smaller scale than today.

Most LPs are wising up to the fact that two-thirds of the capital being invested in the venture is currently being invested by forms with over 500 companies in their portfolio.  The future lies in larger-scale, data-driven investments – and a greater reliance on sophisticated data analysis, global levels of cooperation, and business process automation.

Q6. Being a founder yourself, but also an astute investor, what insights do you believe would be of most use to a founder just beginning their journey?

I get this question all the time, and I always answer it the same way.  The only founders I’m interested in are founders that are passionately interested in solving a problem, and capable of bringing together the skills and the people needed to solve it and scale the solution.  The only founders I *invest* in are founders that can show me, over time, they are capable of reliable, honest communications.  Founders that are capable, that are solving a big problem in a unique and scalable way, that are capable of communicating well and often, will always get investment.

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