Super Founders: What Data Reveals About Billion-Dollar Startups

Super Founders: What Data Reveals About Billion-Dollar Startups

by Ali Tamaseb

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Tamaseb, a DCVC partner, hand-collected 30,000 data points on every US billion-dollar startup founded since 2005 and compared them to a control group of random startups to test common myths. He finds that most unicorn founders had no industry experience, solo founders do fine, first-mover advantage is largely a myth, and the single strongest predictor is a founder's prior track record of starting things - overturning much received VC wisdom.

Published:
Pages:
384
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In the Conversation

In this collection, Super Founders: What Data Reveals About Billion-Dollar Startups references 4 other books.

It draws on Zero to One, The Lean Startup and The Innovator's Dilemma.

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What This Book Draws On

4

The books Tamaseb references and why each one mattered to the argument.

Tests Thiel's Zero to One claims about monopoly, market size, and being first empirically against the unicorn dataset, finding first-mover advantage far weaker than Thiel implies while confirming his points about secrets and market structure

Zero to One

References

Zero to One

by Peter Thiel

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Evaluates Ries's Lean Startup methodology against the data, finding that pivots and MVPs correlate with unicorn outcomes but that many billion-dollar companies skipped the classic lean playbook entirely

The Lean Startup

References

The Lean Startup

by Eric Ries

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References Christensen's Innovator's Dilemma when analyzing whether unicorns disrupt incumbents from below or attack established markets head-on, finding more direct competition than the disruption frame predicts

The Innovator's Dilemma

References

The Innovator's Dilemma

by Clayton Christensen

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Engages Gladwell's Outliers 10,000-hour thesis by testing whether domain expertise predicts unicorn founding - and finds, surprisingly, that most super founders lacked industry experience

Outliers

References

Outliers

by Malcolm Gladwell

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