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

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

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Forecast accuracy versus skill Skill Accuracy

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

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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

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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

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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

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

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

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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

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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

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Skill Accuracy Forecast accuracy versus skill

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Skill Accuracy Forecast accuracy versus skill

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Model You observe a noisy signal:

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

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

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

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Model Task: Make a Forecast

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Model Task: Make a Forecast Forecast = b*S

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

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

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If m = 0, distribution of forecasts Forecast

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If m = 0, distribution of forecasts Bayesian Forecast

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If m = 0, distribution of forecasts Bayesian Overreactor Forecast

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If m = 3, distribution of forecasts

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Bayesian Forecast

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If m = 3, distribution of forecasts Bayesian Overreactor Forecast

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

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

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Forecast

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

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

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

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

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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 .

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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

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Suppose the actual outcome is between 40 and 60

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Suppose the actual outcome is above 60

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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?