1. Business Strategy, Luck, and Poor Judgment Jerker Denrell, Stanford Christina Fang, NYU

5. Strategizing and forecasting Accurate forecasting of the value of resources is the only systematic way to earn above normal returns Barney, 1986, 1990

6. Forecast accuracy versus skill Skill Accuracy

7. “I think there is a world market for about five computers.” Thomas J. Watson, Chairman of IBM, 1943 Accurate vs Good Forecasts

8. “I think there is a world market for about five computers.” Thomas J. Watson, Chairman of IBM, 1943 “I think there is a world market for about five billion computers.” Thomas Crank, Chairman of Wild Ideas, 1943 Accurate vs Good Forecasts

9. “I think there is a world market for about five computers.” Thomas J. Watson, Chairman of IBM, 1943 Accuracy: bad Judgment: good “I think there is a world market for about five billion computers.” Thomas Crank, Chairman of Wild Ideas, 1943 Accurate vs Good Forecasts

10. “I think there is a world market for about five computers.” Thomas J. Watson, Chairman of IBM, 1943 Accuracy: bad Judgment: good “I think there is a world market for about five billion computers.” Thomas Crank, Chairman of Wild Ideas, 1943 Accuracy: good Judgment: bad Accurate vs Good Forecasts

11. If someone predicts that an activity will be very successful Accurate vs Good Forecasts

12. If someone predicts that an activity will be very successful and the prediction turns out to be correct Accurate vs Good Forecasts

13. If someone predicts that an activity will be very successful and the prediction turns out to be correct the individual is probably a poor forecaster Accurate vs Good Forecasts

14. If someone predicts that an activity will be very successful and the prediction turns out to be correct the individual is probably a poor forecaster Accurate foresight about the next big thing signals bad judgment Accurate vs Good Forecasts

15. Skill Accuracy Forecast accuracy versus skill

16. Skill Accuracy Forecast accuracy versus skill

17. Model You observe a noisy signal:

18. Model You observe a noisy signal: S = m + error

19. Model You observe a noisy signal: S = m + error

20. Model You observe a noisy signal: S = m + error

21. Model Task: Make a Forecast

22. Model Task: Make a Forecast Forecast = b*S

23. Model Task: Make a Forecast Forecast = b*S Bayesian b = 0.5

24. Model Task: Make a Forecast Forecast = b*S Bayesian b = 0.5 Overreactor b = 1

25. If m = 0, distribution of forecasts Forecast

26. If m = 0, distribution of forecasts Bayesian Forecast

27. If m = 0, distribution of forecasts Bayesian Overreactor Forecast

28. If m = 3, distribution of forecasts

29. Bayesian Forecast

30. If m = 3, distribution of forecasts Bayesian Overreactor Forecast

31. Accuracy vs Expected Accuracy Mean Square Error (MSE) E[ ( forecast– actual) 2 ]

32. If m = 3, what is the expected MSE given the forecast?

33. Forecast

34. If m = 3, what is the expected MSE given the forecast? Forecast

35. Experiment You observe a noisy signal: S = m + error Task: Make a Forecast

36. Experiment You observe Test Sales Task: Make a Forecast of the Actual Sales

37. Experiment You observe Test Sales Task: Make a Forecast of the Actual Sales Can observe 50 previous test sales and actual sales

38. Experiment Artist Test Actual 100158.6275.33 100227.6816.17 100363.8170.79 100447.8646.46 100543.9464.67 100648.0544.31 100771.0452.03 100854.651.37 …….

39. Experiment Artist Test Actual 100158.6275.33 100227.6816.17 100363.8170.79 100447.8646.46 100543.9464.67 100648.0544.31 100771.0452.03 100854.651.37 ……. Test i = m i + error (mean of m i =50) Actual i = m i + error

40. Suppose the actual outcome is between 40 and 60

42. Suppose the actual outcome is above 60

44. Conclusion Accurate Foresight about the Next Big Thing Signals Bad Judgment Are entrepreneurs who made money by betting on a vision that turned out to be correct worse forecasters?