Webit, Istanbul, 10 October 201214 Primary Lessonsfor Black Swans(Decision Theory for Startups)                           ...
About Jochen                     Business                                Complexity  Coder                                ...
InfluencersKarl Popper   Nassim Taleb, Rolf Dobelli    Daniel Kahneman                                      Jochen Wegner ...
14 Primary Lessonsfor Black Swans
>6 million businesses   are created every year in the   United States alone** Kauffman Foundation, US Census Bureau
1 out of 1.000-10.000 will be big.** >500 employees after 10 years,estimate based on Kauffman Index, US Census Bureau
What if big success was random?What if it would be impossible to predictif you will be the next Black Swan?
What if big success was random?What if it would be impossible to predictif you will be the next Black Swan?
What if big success was random?Some reliable sources suggest exactly that:suggest exactly that:„The majority of funds — 62...
Successful startups are„Black Swans“ according to Taleb:‣rare‣extreme impact‣only retrospective predictability
Lesson 1Big startups successshows many properties of arandom process.
Lesson 2Startup entrepreneurs showthe typical cognitive biasesconnected with randomness.
There are 156 cognitive biases.*Let us pick 12 of them.* assembled by Wikipedia
Your startup will almost certainlybe a White Swan (and no big hit)...
Lesson 3Your startup will almost certainly be a White Swan......even if everyone else aroundyou is so successful.** Select...
Lesson 4Your startup will almost certainly be a White Swan......even if you got big funding.** smart investors „farm black...
Lesson 5Your startup will almost certainly be a White Swan......even if you got funded by avery successful investor.** Sel...
Lesson 6Your startup will almost certainly be a White Swan......even if you were successfulbefore.** Randomness, Selection...
Lesson 6(...even if your name is Loic,Niklas or Chad.)
Lesson 7Your startup will almost certainly be a White Swan......even if you find a lot ofevidence that your model willwork...
Lesson 8Please follow your idea - even ifit seems not big enough for biginvestors.** They are solely in the Black Swan Far...
Lesson 9Please follow your idea - even ifit seems a little insane (butcould be really big).** „If a good idea were obvious...
Lesson 10It may be rational not to takemoney from big investors.
Lesson 11It may be rational not to takemoney from small investors.** Reciprocity
Lesson 12Please follow your idea - butnot because you worked sohard on it in the past.* Onlybecause of future prospects.* ...
Lesson 13Don‘t listen to success storiestoo much.** Availability Bias
(Read „Techcrunch“ like youread „TMZ“ or „People“Magazine.)
Lesson 14Be very careful if you takeadvice from successfulentrepreneurs.** Overconfidence, Hindsight, Illusion of Control
ResourcesBooksJudgement under Uncertainty: Heuristics and BiasesFooled By RandomnessThe Black SwanArticles / BlogsWhy Ange...
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14 Primary Lessons for Black Swans

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14 Primary Lessons for Black Swans

  1. 1. Webit, Istanbul, 10 October 201214 Primary Lessonsfor Black Swans(Decision Theory for Startups) Jochen Wegner . jochen@wegner.io . http://wegner.io . 10/2012
  2. 2. About Jochen Business Complexity Coder Physicist Journalist Researcher Consultant ‣publishers ‣industry & Angel - see http://wegner.io ‣startups Science Editor Startup Managing Science Editor-in-ChiefEntrepreneur Director Writer
  3. 3. InfluencersKarl Popper Nassim Taleb, Rolf Dobelli Daniel Kahneman Jochen Wegner . jochen@wegner.io . http://wegner.io . 10/2012
  4. 4. 14 Primary Lessonsfor Black Swans
  5. 5. >6 million businesses are created every year in the United States alone** Kauffman Foundation, US Census Bureau
  6. 6. 1 out of 1.000-10.000 will be big.** >500 employees after 10 years,estimate based on Kauffman Index, US Census Bureau
  7. 7. What if big success was random?What if it would be impossible to predictif you will be the next Black Swan?
  8. 8. What if big success was random?What if it would be impossible to predictif you will be the next Black Swan?
  9. 9. What if big success was random?Some reliable sources suggest exactly that:suggest exactly that:„The majority of funds — 62 out of 100 —failed to exceed returns available from thepublic markets, after fees and carry werepaid.“ (Kauffman Foundation)
  10. 10. Successful startups are„Black Swans“ according to Taleb:‣rare‣extreme impact‣only retrospective predictability
  11. 11. Lesson 1Big startups successshows many properties of arandom process.
  12. 12. Lesson 2Startup entrepreneurs showthe typical cognitive biasesconnected with randomness.
  13. 13. There are 156 cognitive biases.*Let us pick 12 of them.* assembled by Wikipedia
  14. 14. Your startup will almost certainlybe a White Swan (and no big hit)...
  15. 15. Lesson 3Your startup will almost certainly be a White Swan......even if everyone else aroundyou is so successful.** Selection Bias / Survivorship Bias / Representativeness /„Law of small numbers“
  16. 16. Lesson 4Your startup will almost certainly be a White Swan......even if you got big funding.** smart investors „farm black swans“- © Paul Graham
  17. 17. Lesson 5Your startup will almost certainly be a White Swan......even if you got funded by avery successful investor.** Selection Bias, „Swimmer‘s Body Illusion“
  18. 18. Lesson 6Your startup will almost certainly be a White Swan......even if you were successfulbefore.** Randomness, Selection Bias, Overconfidence
  19. 19. Lesson 6(...even if your name is Loic,Niklas or Chad.)
  20. 20. Lesson 7Your startup will almost certainly be a White Swan......even if you find a lot ofevidence that your model willwork.** Confirmation Bias
  21. 21. Lesson 8Please follow your idea - even ifit seems not big enough for biginvestors.** They are solely in the Black Swan Farming Business -see Paul Graham
  22. 22. Lesson 9Please follow your idea - even ifit seems a little insane (butcould be really big).** „If a good idea were obviously good, someone else would already have done it. So the most successful founders tend towork on ideas that few beside them realize are good. Which is not that far from a description of insanity, till you reachthe point where you see results.“ (Paul Graham)
  23. 23. Lesson 10It may be rational not to takemoney from big investors.
  24. 24. Lesson 11It may be rational not to takemoney from small investors.** Reciprocity
  25. 25. Lesson 12Please follow your idea - butnot because you worked sohard on it in the past.* Onlybecause of future prospects.* Sunk Cost Fallacy
  26. 26. Lesson 13Don‘t listen to success storiestoo much.** Availability Bias
  27. 27. (Read „Techcrunch“ like youread „TMZ“ or „People“Magazine.)
  28. 28. Lesson 14Be very careful if you takeadvice from successfulentrepreneurs.** Overconfidence, Hindsight, Illusion of Control
  29. 29. ResourcesBooksJudgement under Uncertainty: Heuristics and BiasesFooled By RandomnessThe Black SwanArticles / BlogsWhy Angel Investors don‘t make moneyBlack Swan FarmingWe have met the enemy - and he is us (PDF, Kauffman)Cognitive biases, risk perception, and venture formation: How individuals decide to start companiesResources on EntrepreneurshipUS Census BureauKauffman FoundationWikipedia: List of Cognitive Biases

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