The New Face Of Venture Capital, Part 2

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A continuation of Part 1, explaining why conventional VC networks and outlier identification don't produce good results, and how augmentation or replacement with crowdsourcing/crowdfunding is the …

A continuation of Part 1, explaining why conventional VC networks and outlier identification don't produce good results, and how augmentation or replacement with crowdsourcing/crowdfunding is the future of high-return Venture Capital.

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  • 1. The New Face of Venture Capital, Part 2: Rise of Crowdfunding A road-map for LPs and startups Kevin Lawton March 31, 2010 http://www.trendcaller.com/
  • 2. Finding Outliers
    • VC is much about finding potential outliers , and then letting them morph real-time with the market.
    • Thus to produce good returns, it's absolutely essential that future VC is centered around outlier identification .
    • Given 10 years of poor returns in the VC asset class, is it a surprise that today's VC model is not?
    • Let's 1st look at how today's VC filters deals.  One doesn't need to look any further to know poor returns will often follow.
    •  
    • Their 1st-order filters are the same ones that many parts of society (mistakenly) use...
  • 3. Brand Name & Superstars
    • Nothing gets a VC whipped up more than a big brand name :  Stanford, Harvard, Wharton, MIT, ...
    •  
    • But how much does this correlate with chances of doing something really new & big?
    • It doesn't!   This was shown elegantly in the book Outliers , by Malcolm Gladwell.  Brand name affinity is a centuries-old legacy screen that hasn't worked for longer than VC has lived.
    • And then there are superstars . These are the fortunate souls who have “gone big” before.  They must be destined to make the next big thing, right?  Let's look at some really Big Thing companies and see if they were founded from repeat customers...
  • 4. Superstars
      • Microsoft (Bill Gates & Paul Allen, drop-outs)
      • Oracle (Larry Ellison, drop-out)
      • Google (Brin/Page Ph.D. drop-outs)
      • DELL (Michael Dell, drop-out)
      • Facebook (Mark Zuckerberg, drop-out)
      • Apple (Steve Jobs, drop-out)
    •  
    • Not looking too promising as a good screen for outlier identification !  Maybe VC should instead screen for only drop-outs ?
    •  
    • And hey, regarding drop-outs (besides being 4 out of 5 of America's richest people and behind many of the World's greatest inventions), here's a list of some of them that sound familiar...
  • 5. Other Notable Drop-outs
      • James Cameron & Steven Spielberg
      • Founders of:
        • Kodak & Polaroid
        • Disney
        • Ford
        • Learjet
        • Bank of America
        • Whole Foods
        • Jet Blue
        • Domino’s, Dunkin’ Donuts, Wendy’s, McDonald’s, KFC
        • NBC
        • Holiday Inn
      • People lending their images on the U.S. penny, quarter, 1/5/20/100/1000-dollar bills
  • 6. Why superstars have short shelf-lives
    • As per the book Outliers , an outlier needs the following:
      • Put in their 10,000 hours to develop domain expertise.
      • Be at the right place at the right time.
    •  
    • The chances of someone creating another amazing 10,000 hour expertise are slim, given human nature works against them after a major success.
    • The chances of that plus being at the right place at the right time again , are really slim.
    • People may be involved in a number of interesting companies, due to “brand seeking brand”, but they are highly unlikely to truly found repeat Big Things.
    • In a high rate-of-change world, chances are even worse.
  • 7. The limits of human networks
    • VCs, like most anybody, have networks and they're chocked full of brand name & superstars.  See where this is going?
    •  
    • Their networks have people who are among the least likely to know what the Next Big Thing is, and they use their networks to find and vet startups.  So:
      • They limit their scope to a small cross-section where the outliers almost certainly do not live , and
      • When they accidently find an outlier, it often gets vetoed by one of yesterday's “experts” in their networks.
    •  
    • That makes it extremely easy to predict that tomorrow's high-return VC will network drastically different than today's.
  • 8. The scalability of human networks
    • Given a huge human population, how do you select a subset of people for your network?  Human networking is not very scalable.
    • Using brand as a 1st-order screen, probably made sense some time in human history (like before most people could read proficiently and had a broad-band Internet connection).
    • Now, it's an effective way to screen against outliers.
    • In fact, the “Rolodex” value of many VC firms is diminishing with every new way of commoditized and far more scalable networking (e.g. LinkedIn).
    • Fortunately, the Internet is also the solution.
  • 9. The Collective Wisdom of the Crowd
    • As was the conclusion of the book The Wisdom of Crowds , the crowd can often make smarter decisions than its individuals.
    • This phenomena is used, for example, in prediction markets.  But crowd-sourcing is disrupting nearly every type of market:
      • Mutual funds: kaChing , Covestor
      • Film financing: Pirate My Film
      • Micro financing: Kiva
      • Patents: Peer to Patent
      • Hedge Fund: Algodeal
      • Graphic Design: crowdSPRING
      • Business Idea spotting: Springwise
      • Encyclopedia: Wikipedia
      • Language translation: Google Translator Kit
  • 10. Crowdfunded VC was inevitable
    • And we've already entered that age (e.g. GrowVC ).
    •  
    • Currently, crowdfunded VC tends to be narrowly focused on seed funding, and within disciplines (e.g. Internet/mobile).  That's because:
      • Applying it to small amounts of money is an easier 1st play.
      • Natural relationship/trust-building mechanisms are not well built-in yet . (e.g. incremental disclosure)
      • Mechanisms for intelligently & dynamically identifying the skills of the participants are immature.
      • No home-runs have stemmed from it yet (this will be kindling wood for the fire).
    •  
    • But as it matures, crowdfunding will become the norm.  And span many business disciplines & multiple rounds.
  • 11. Where crowdfunded VC needs to go
    • Replicating natural relationship/trust building:
      • Early on, startups want to disclose a small amount to a large number of participants.
      • Later on, startups want to disclose a larger amount to a small number of participants.
    •  
    • Crowdfunding can't scale well to big-value startups until it replicates this human process.
  • 12. Intelligent scalable match-making
    • Replicating natural match-making allows scalability:
      • Intelligent and crowd-sourced tagging allows for better match-making between startups and VCs.
      • Multi-faceted scoring of participants surfaces the signal above the noise and prevents group-think.
      • In fact, many of the mechanisms used on dating sites are very relevant.  Why shouldn't VCs be automatically presented with possibly interesting startups?
      • A really intelligent crowdfunding site could actually predict which startups will succeed, and provide a heat-map of the hottest trends!
    •  
    • To be scalable, a crowdfunding site has to do a lot of work for you.  Otherwise, you’ll be buried in noise.
  • 13. Crowdsourced diligence
    • Much of diligence can be crowd validated:
      • Assumptions
      • Competitive landscape
      • IP
      • ...
    •  
    • Let the experts in the crowd descend upon these too!
    • And why not make these incremental, so the crowd can continuously diligence a startup through its evolution?  This is more powerful than anything in the conventional VC realm.
    • Diligence can be profitable for the skilled participants, if they share in the returns!
  • 14. From augmentation to pure-play
    • Apart from full financing of startups with minimal capital needs, crowdfunding will evolve from an augmentation of conventional VC to a pure-play.
    • As an augmentation, it can act as an “outsourced” early stage process and/or seed fund for VC firms.
    • An intelligent system could actually tell any participant who their network should be!
  • 15. From augmentation to pure-play (cont’d)
    • Over time, it can evolve to have a complete ecosystem of participants and financing for most startups.
    •  
    • People could invest some of their money in crowdfunded VC instead of the equities market.
    •  
    • In other words, crowdfunded VC is a new asset class!!!
  • 16. Alignment of Interests
    • By rewarding participants by the value they add (e.g. finding good startups early on), a natural alignment of interests is created.
    • Any number of participant types can be added.  E.g. a “finder” who excels at identifying the most promising startups.  See The coming "Finder's Economy" for more info.
    • The system will quickly separate talented from the mediocre.
    • And transparency is a more natural outcome, while possibly providing privacy (incremental disclosure, orthogonalized crowd diligence, ...).
  • 17. For deeper thoughts, contact me
    • Kevin Lawton
    • http://www.trendcaller.com/
    • http://www.thecrowdfundingrevolution.com/