Data blindness: why leaders with plenty of data don't act


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Most people assume we lack access to data and, once given the data, we will act rationally. This research assembles examples why this may not be the case. Leaders with data often ignore the findings. As data increases in volume, so too will the level of distortion and false positives. Those who succeed will not be those with the most data, but those who act most on the data they have.

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Data blindness: why leaders with plenty of data don't act

  1. 1. Data blindness: why leaders with data fail to act OnCorps 2014. All Rights Reserved 1 Research and diagnostic series Bob Suh, Founder and CEO July 4, 2014
  2. 2. Private and confidential. OnCorps © 2014. 2 Why do people with plenty of data make big mistakes? ©
  3. 3. OnCorps 2014. All Rights Reserved 3 Alan Greenspan couldn’t see the meltdown coming Americans might benefit if lenders provided greater mortgage product alternatives… 2/04 I was aware that the loosening of mortgage credit terms for subprime borrowers increased financial risk. But I believed then, as now, that the benefits of broadened home ownership are worth the risk. 9/07 That’s precisely the reason I was shocked because I’d been going for 40 years with considerable evidence that it was working exceptionally well 10/08 Mortgage Default Rate
  4. 4. OnCorps 2014. All Rights Reserved 4 Quantitative funds can’t beat the market HFRI Hedge Fund Index Performance as of June 2014 Same period returns for S&P 500 Index 22.7%
  5. 5. Private and confidential. OnCorps © 2014. 5 Conviction trumps correctness ©
  6. 6. OnCorps 2014. All Rights Reserved 6 Extroverts are heeded more but are not always right Shy people are viewed as less intelligent whenever “they are evaluated during limited intervals.” Paulhus and Morgan But the rise of the Culture of Personality intensified such biases, and applied them not only to political and religious leaders, but also to regular people. Susan Cain Consider the idea that charisma can be as much a liability as an asset. Your strength of personality can sow the seeds of problems, when people filter the brutal facts from you. Jim Collins
  7. 7. OnCorps 2014. All Rights Reserved 7 Jim Cramer is popular even though he is wrong "the United States is likely to face a once-in-a-lifetime housing bust, an oil shock, sharply declining consumer confidence, and, ultimately, a deep recession“ Nouriel Roubini to IMF “buy Bear Stearns“ Jim Cramer Source: Google Trends Source: Barron’s 2008
  8. 8. Private and confidential. OnCorps © 2014. 8 Trend magnification syndrome ©
  9. 9. OnCorps 2014. All Rights Reserved 9 Gun deaths down but perception is opposite “actual gun deaths down” “perception of gun deaths up” The rule: Rare events trend in social and media channels, inflating their perceived probability to the general population Source: Economist 9-21-2013 mass-shootings-are-up-gun-murders-down
  10. 10. OnCorps 2014. All Rights Reserved 10 Plane crash coverage outweighs actual odds “CNN plane crash” “CNN car accident” Google Trends interest over time (2005-2013) DOT comparison of accidental death risk (1999-2003) 5 year average deaths per year General US population risk per year 36,676 1 in 8K 138 1 in 2,067K
  11. 11. Private and confidential. OnCorps © 2014. 11 Myside Bias ©
  12. 12. OnCorps 2014. All Rights Reserved 12 People are often blinded by major change “Nothing has come along that can beat the horse and buggy.” US businessman Chauncey Depew advises his nephew not to invest $5000 in the Ford Motor Company in 1906 “The hypothesis of human-caused global warming comes up short“ The Nongovernmental International Panel on Climate Change “There is no reason for any individual to have a computer in their home“ Ken Olson president of Digital Equipment Corporation in 1977
  13. 13. Top leader surveys reinforce their biases 13OnCorps 2014. All Rights Reserved Use data to support the war Monitor data to execute the plan Stay alive
  14. 14. OnCorps 2014. All Rights Reserved 14 Some people believe only what they have seen Homer, Hesiod, Anaximander view of earth Bear Stearns share price in red
  15. 15. Private and confidential. OnCorps © 2014. 15 Falling into the false positive trap ©
  16. 16. OnCorps 2014. All Rights Reserved Target detection software alerts were ignored Possible explanation: too many false positive alerts numb response
  17. 17. TSA misses 90% by screening everyone Private and confidential. All rights reserved. 17 Bayes theorem suggests finding a rare event in a large data set results in extremely high false positives. Official Red Teams slip gun and bomb dummies in TSA screens. 90% are undetected.
  18. 18. Private and confidential. OnCorps © 2014. 18 Data distortions, rigged games and errors ©
  19. 19. OnCorps 2014. All Rights Reserved 19 Airlines are on-time because schedules are padded Source: Wall Street Journal Sand Bagging Syndrome
  20. 20. OnCorps 2014. All Rights Reserved 20 Why most companies meet analyst expectations Source: Cotter, Tuna, Wysocki: The Expectations Management Game: Do Analysts Act Independently of Explicit Management Earnings Guidance? • Management tends to be overly pessimistic relative to actual earnings outcomes • Analysts react quickly to management guidance • Analysts tend to shift from optimism to pessimism in response to the “bad news”
  21. 21. Everyone reaches the same conclusion, negating the conclusion Private and confidential. All rights reserved. 21 Fear of Olympic traffic gridlock means no gridlock Crowd Contradiction Syndrome1. Source: Bob Suh 2014, OnCorps
  22. 22. Data is created without regard to provenance or validation 22OnCorps 2014. All Rights Reserved Click Distortion Syndrome
  23. 23. What you rate and what you do are different 23OnCorps 2014. All Rights Reserved Rated highly… …but highly watched Source: Wired Magazine, The Science Behind The Netflix Algorithms That Decide What You’ll Watch
  24. 24. Private and confidential. OnCorps © 2014. 24 How to assess data blindness ©
  25. 25. Measure and calibrate perceptions and outcomes Private and confidential. All rights reserved. 25 De-Average Profile Reciprocate Pulse • Develop hypotheses • Track analytic profiles • Calibrate perceptions to actions • Seek smaller, targeted groups • Identify adoption leaders • Measure variances • Provide performance data to users • Make users want to come back • Respect user anonymity • Create a schedule of analytic sprints • Monitor changes in what people do • Update hypotheses and build a database
  26. 26. 26Private and confidential. OnCorps © 2014. © Cambridge, Massachusetts | Bristol, United Kingdom