Why Leaders Don’t Learn from Success

by Francesca Gino and Gary P. Pisano

The annals of business history are full of tales of companies that once dominated their industries but fell into decline. The usual reasons offered—staying too close to existing customers, a myopic focus on short-term financial performance, and an inability to adapt business models to disruptive innovation—don’t fully explain how the leaders who had steered these firms to greatness lost their touch.

In this article we argue that success can breed failure by hindering learning at both the individual and the organizational level. We all know that learning from failure is one of the most important capacities for people and companies to develop. Yet surprisingly, learning from success can present even greater challenges. To illuminate those challenges—and identify approaches for overcoming them—we will draw from our research and from the work of other scholars in the field of behavioral decision making, and focus on three interrelated impediments to learning.

The first is the inclination to make what psychologists call fundamental attribution errors. When we succeed, we’re likely to conclude that our talents and our current model or strategy are the reasons. We also give short shrift to the part that environmental factors and random events may have played.

The second impediment is overconfidence bias: Success increases our self-assurance. Faith in ourselves is a good thing, of course, but too much of it can make us believe we don’t need to change anything.

The third impediment is the failure-to-ask-why syndrome—the tendency not to investigate the causes of good performance systematically. When executives and their teams suffer from this syndrome, they don’t ask the tough questions that would help them expand their knowledge or alter their assumptions about how the world works.


Lessons from Ducati
We began to examine the challenges of learning from success in 2004, when we did a case study of an organization with a long history of winning: the Ducati Corse motorcycle racing team. Motorcycle racing may seem a long way from the world of business, but in fact it provides a perfect laboratory for research on learning. Performance is unambiguously measurable by lap times and race results. You know with brutal precision whether you’re getting better or worse. Racing is also unforgiving. The race is Sunday, and it won’t wait if you’re late. Finally, the racing circuit is intensely competitive: During a season a dozen world-class teams battle each week for the top spot. For an organization like Italy’s Ducati, wins have a huge impact on brand equity and commercial bike sales.

In 2003, Bologna-based Ducati entered the Grand Prix motorcycle racing circuit (or “MotoGP”) for the first time. Being a newcomer, it approached 2003 as “a learning season,” its team director told us. The goal was to acquire knowledge that would help it develop a better bike for future seasons. To that end, the team fitted its bikes with sensors that captured data on 28 performance parameters (such as temperature and horsepower). Riders were debriefed after every race to get input on subjective characteristics like handling and responsiveness. The team looked like a model learning organization.

Then something unexpected happened: The rookie team finished among the top three in nine races and was second overall for the season, and its bike was the fastest in the field. But with each success the team focused more on winning and less on learning, and it ended up analyzing little of the data it collected. As one team member commented, “You look at the data when you want to understand what’s going wrong. You do not look at the data because you want to understand why you’re performing well.”

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