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

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Presentation transcript:

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

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

Forecast accuracy versus skill Skill Accuracy

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

“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

“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

“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

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

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

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

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

Skill Accuracy Forecast accuracy versus skill

Skill Accuracy Forecast accuracy versus skill

Model You observe a noisy signal:

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

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

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

Model Task: Make a Forecast

Model Task: Make a Forecast Forecast = b*S

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

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

If m = 0, distribution of forecasts Forecast

If m = 0, distribution of forecasts Bayesian Forecast

If m = 0, distribution of forecasts Bayesian Overreactor Forecast

If m = 3, distribution of forecasts

Bayesian Forecast

If m = 3, distribution of forecasts Bayesian Overreactor Forecast

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

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

Forecast

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

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

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

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

Experiment Artist Test Actual …….

Experiment Artist Test Actual ……. Test i = m i + error (mean of m i =50) Actual i = m i + error

Suppose the actual outcome is between 40 and 60

Suppose the actual outcome is above 60

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?