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Using data to disrupt your brain

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This talk helps you uncover the dark forces at work on your team and in your own decision making as a result of cognitive bias. Discover how data can help you make better decisions for team and product development. This talk was delivered at the Refresh PDX event at New Relic on September 21, 2016.

Published in: Leadership & Management

Using data to disrupt your brain

  1. 1. DISRUPT YOUR BRAIN WITH DATA
  2. 2. LinkedIn, Medium & Twitter: @laurex LAURE PARSONS SENIOR PRODUCT MANAGER
  3. 3. 1. WHAT’S WRONG WITH OUR THINKING? 2. FOUR PRODUCT PROBLEMS & SOLUTIONS • ALIGNMENT • ESTIMATION • VANITY • OPPORTUNITY
  4. 4. @laurex SYSTEM 1 & SYSTEM 2
  5. 5. Acquiescence bias Adaptive bias Affect heuristic Ambiguity effect Anchoring Anthropic bias Apophenia Attentional bias Attitude polarization Attribute substitution Attributional bias Availability heuristic Bandwagon effect Base rate fallacy Bias blind spot Bias of an estimator Closed world assumption Clustering illusion Cognitive bias mitigation Cognitive closure Confirmation bias Conjunction fallacy Contrast effect Cultural bias Default standard unit bias Deindividualisation Delay discounting Disconfirmation bias Dr. Fox Effect Dunning–Kruger effect Egocentric bias Emotional forecasting Empathy gap Endowment effect Error management theory Exaggeration Experimenter effect False-consensus effect False-consensus effect False memory syndrome Familiarity heuristic Forer effect Framing effects Functional fixedness Fundamental attribution error Gambler's fallacy Generation effect Group attribution error Group-serving bias Groupthink Halo effect Hindsight bias Hostile media effect Illusion of asymmetric insight Illusion of control Illusion of transparency Illusory correlations Illusory superiority Illusion of control Illusion of transparency Illusory correlations Illusory superiority Impact bias Implicit cognition Ingroup bias Inductive bias Introspection illusion Isolation effect Just-world hypothesis Lake Wobegon effect Loss aversion Magical thinking Mere-exposure effect Mindset Minimization Misinformation effect Name–letter effect Negativity bias Negativity effect Neglect of probability Notational bias Oedipus effect Optimism bias Pareidolia Partisan effect Pessimism bias Physical attractiveness stereotype Picture superiority effect Planning fallacy Positive illusions Positivity effect Primacy effect Projection Publication bias Recency effect Regression fallacy Repetition bias Response bias Rosy retrospection Selective perception Self-deception Self-serving bias Serial position effect Social comparison bias Spacing effect Status quo bias Subject-expectancy effect Subjective validation Sunk cost fallacy Trait ascription bias True-believer syndrome Univariate bias Valence effect Wishful thinking Worse-than-average effect Zeigarnik effect COGNITIVE BIASES
  6. 6. Acquiescence bias Adaptive bias Affect heuristic Ambiguity effect Anchoring Anthropic bias Apophenia Attentional bias Attitude polarization Attribute substitution Attributional bias Availability heuristic Bandwagon effect Base rate fallacy Bias blind spot Bias of an estimator Closed world assumption Clustering illusion Cognitive bias mitigation Cognitive closure Confirmation bias Conjunction fallacy Contrast effect Cultural bias Default standard unit bias Deindividualisation Delay discounting Disconfirmation bias Dr. Fox Effect Dunning–Kruger effect Egocentric bias Emotional forecasting Empathy gap Endowment effect Error management theory Exaggeration Experimenter effect False-consensus effect False memory syndrome Familiarity heuristic Forer effect Framing effects Functional fixedness Fundamental attribution error Gambler's fallacy Generation effect Group attribution error Group-serving bias Groupthink Halo effect Hindsight bias Hostile media effect Illusion of asymmetric insight Illusion of control Illusion of transparency Illusory correlations Illusory superiority Impact bias Implicit cognition Ingroup bias Inductive bias Introspection illusion Isolation effect Just-world hypothesis Lake Wobegon effect Loss aversion Magical thinking Mere-exposure effect Mindset Minimization Misinformation effect Name–letter effect Negativity bias Negativity effect Neglect of probability Notational bias Oedipus effect Optimism bias Pareidolia Partisan effect Pessimism bias Physical attractiveness stereotype Picture superiority effect Planning fallacy Positive illusions Positivity effect Primacy effect Projection Publication bias Recency effect Regression fallacy Repetition bias Rosy retrospection Selective perception Self-deception Self-serving bias Serial position effect Social comparison bias Spacing effect Status quo bias Subject-expectancy effect Subjective validation Sunk cost fallacy Trait ascription bias True-believer syndrome Univariate bias Valence effect Wishful thinking Worse-than-average effect Zeigarnik effect
  7. 7. DATA DATA DATA @laurex
  8. 8. SOLUTION @laurex
  9. 9. -Ronald Coase, Economist TRUTH If you torture the data long enough, it will confess. @laurex
  10. 10. PROBLEM 1: ALIGNMENT @laurex
  11. 11. ULTIMATE ATTRIBUTION ERROR @laurex
  12. 12. STATUS QUO BIAS @laurex
  13. 13. CONFIRMATION BIAS @laurex
  14. 14. BANDWAGON EFFECT + The False Consensus Effect @laurex
  15. 15. SHARED INFORMATION BIAS @laurex
  16. 16. SOLUTION @laurex
  17. 17. OKRS @laurex
  18. 18. DRE = (Total defects found in development [A]/ (Total defects found in development[A] + Defects found in production [B] )) x 100
  19. 19. TEAM POLLING
  20. 20. CUSTOMER DATA
  21. 21. PROBLEM 2: ESTIMATION @laurex
  22. 22. OVERCONFIDENCE @laurex
  23. 23. PLANNING FALLACY @laurex
  24. 24. TIME-SAVING BIAS @laurex
  25. 25. SOLUTION @laurex
  26. 26. @laurex VELOCITY
  27. 27. @laurex THROUGHPUT
  28. 28. @laurex CYCLE TIMES
  29. 29. PROBLEM 3: VANITY @laurex
  30. 30. CONFIRMATION BIAS @laurex
  31. 31. ILLUSION OF CONTROL @laurex
  32. 32. INFORMATION BIAS @laurex
  33. 33. @laurex ILLUSORY CORRELATION
  34. 34. SOLUTION @laurex
  35. 35. NO VANITY METRICS @laurex
  36. 36. COUNTER-METRICS@laurex
  37. 37. PROBLEM 4: OPPORTUNITY @laurex
  38. 38. IKEA EFFECT @laurex
  39. 39. LOSS AVERSION + The Sunk Cost Fallacy @laurex
  40. 40. NARROW FRAMING @laurex
  41. 41. CONFIRMATION BIAS @laurex
  42. 42. SOLUTION @laurex
  43. 43. USER RESEARCH Resist Confirmation Bias by asking open-ended questions Combat Narrow Framing by using “and” instead of “or” Test Reality by finding out what users are doing now and A/B test to see if your hypotheses are correct @laurex
  44. 44. Teresa Torres- http://producttalk.com OPPORTUNITY DECISION TREE
  45. 45. A/B TESTING
  46. 46. @laurex MVP
  47. 47. RESOURCES Thinking Fast & Slow - Daniel Kahneman Decisive, Made to Stick- Chip & Dan Heath Mental Models I Find Repeatedly Useful - Gabriel Weinberg OKRs: Getting Started Guide for Teams The Four Villains of Product Management Four steps to more Decisive product decisions Gib Biddle on Netflix Product Strategy Why This Opportunity Solution Tree is Changing the Way Product Teams Work -Teresa Torres Spurious Correlations @laurex
  48. 48. YOUR THOUGHTS?

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