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OBEY THE POWER LAW
The importance of hit-‐driven thinking in venture capital and technology
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Babe Ruth: Home runs define success.
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In VC, a fund’s best investment returns more $ than all other investments combined.
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As expected, great venture capital funds have more “home run” investments.
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And great funds’ home runs are of greater magnitude.
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But great funds also lose money more oOen than good ones do.
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To be hit-‐driven, need to trade-‐off probability of success with magnitude of impact.
100%
0%
High Low
Probability of success
Magnitude of impact
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Consensus
Non-‐ consensus
Right Wrong
Nature of belief
Outcome
In VC, this translates to being “non-‐consensus right.”
“Vulture” Money already in, race to remaining profit opportunity
“Thunderlizard” Big breakthroughs not obvious at :me
of investment
“Lemming” Lowest-‐risk failure
via safety in numbers
“Babe Ruth” Big swing and a
miss
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How valuable is “consensus”? Expert predicUons oOen have liVle predicUve value.
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Most of us think of the world as Normally Distributed.
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But power laws govern most of what happens in technology.
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Here are some reasons why.
Zero marginal cost of so=ware reproduc@on makes hit products dispropor@onately profitable Consumer demand for new technologies is usually very difficult to predict Mutually reinforcing, mul@-‐step, posi@ve feedback loop between plaIorms and applica@ons
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“Companies spend more than $2 trillion on acquisi@ons every year.
Study a=er study puts the failure rate of mergers and acquisi@ons somewhere between 70% and 90%.”
Example #1: Most tech M&A transacUons are complete failures.
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But the few that succeed can be completely transformaUve.
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Example #2: Winner-‐take-‐most markets (applicaUons)
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Example #2: Winner-‐take-‐most markets (infrastructure)
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Example #2: Winner-‐take-‐most markets (search)
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Example #3: “10x engineers”
Task Best engineer Worst engineer
Coding @me 1 20
Debugging @me 1 25
Program size 1 5
Program execu@on speed
10 1
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Example #4: InsUtuUonalised Hit-‐Making.
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Example #5: Technology Udal waves and incumbent failure.
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Embrace power curve thinking in your organisaUon.
Incen@vise outcome value, not frequency of success Make dispropor@onately big investments in a few products designed to appeal to large audiences Make failure allowable (not desirable): Quan@ty + Learning = Quality Find secrets (“non-‐consensus rights”) Don’t overweight expert predic@ons