When Success Is Rare and Competitive: Learning from Others’ Success and My Failure at the Speed of Formula One

Abstract

Organizations can learn from prior successes and failures to improve organizational performance. Few learning-curve studies have investigated this phenomenon at the individual level. A notable exception found that surgeons learn from their own success and others’ failure. Success in surgery is common and individually independent from other surgeries. We study learning from success and failure in a context where success is rare and competitive: Formula One (F1) racing. Only one driver will win a race, preventing the other competitors from winning. Even severe failures causing drivers to abandon the race are common. We investigate two types of abandonments: car failures and driver failures. Our data set covers F1 from the start of F1 in 1950 through 2017, yielding 21,487 driver-race observations. We find that win probability follows an inverted U-shaped function of racing experience. We also find that drivers learn from their own success, teammates’ success, as well as own car failures. However, drivers do not learn from their own driver failures. A teammate’s win increases the probability of winning the next race by 1.8%. An own car failure increases the probability of winning the next race by 1.9%. We use two characteristics of success, frequency and competitiveness, to define a spectrum of organizational settings. Placement of our F1 findings and the surgery findings on this spectrum reveals when managers can expect benefits from their own versus others’ success and failure. This paper was accepted by Charles Corbett, operations management. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4324 .