Are Great Teams Less Productive?

From HBS Working Knowledge - Q&A by Amy Edmonson and Sarah Jane Gilbert. Amy Edmondson is a Professor in the Technology and Operations Management unit at Harvard Business School.

Learning promotes performance — is there any argument? Without learning, organizations, teams, and managers are stuck in yesterday's world.

In fact, says Harvard Business School professor Amy Edmondson, there are built-in tensions between learning and performance, which smart organizations must learn to recognize and deal with. For example, an organization that has just completed a learning initiative may see a drop in productivity, at least in the short term.

Edmondson and doctoral student Sara Singer explore the problematic relationship between learning and performance in a recent working paper, "When Learning and Performance are at Odds: Confronting the Tension." In this interview, Edmondson discusses her work and practical considerations for organizations looking to sharpen their learning skills, i.e., any business hoping to be successful in today's quickly changing world.

Sarah Jane Gilbert: What led you to pursue this research?

Amy Edmondson: This research, rather than being a single project, is part of a fifteen-year program of a half dozen or so projects in different settings, all focused on learning in and by organizations. The paper, written with Sara Singer, on the tension between learning and performance, was an attempt to pull together a subset of insights from this longer journey about the challenges for managers who wish to promote learning without sacrificing performance in the short term.

The longer journey that I refer to was motivated by a desire to help organizations better access, integrate, and leverage the talents and insights of their employees. An earlier career as an organizational change consultant led me to realize how many thoughtful, caring individuals were stymied in their genuine desires to make a difference at work — that is, their desires to help make their organizations more effective and responsive. I met many individuals with great ideas and insights working in large organizations that seemed to be enacting policies or producing products that didn't reflect this insight. As a result, I became fascinated by the notion of the learning organization: organizations with the capacity to sense and act upon opportunities for positive change. Around this time, I thought I'd better go to graduate school to learn and explore these ideas more carefully.

Early on, I stumbled into one of the perverse aspects of the relationship between learning and performance. My first research project in graduate school explored the relationship between teamwork and errors (in hospitals), because errors are a critical input to organizational learning, especially in that setting. I assumed I'd find a negative relationship between teamwork and error rate.

Instead, I stumbled into quite a different discovery. The statistical results I obtained were the opposite of what I'd predicted. Well-led teams with good relationships were apparently making more mistakes; there was a significant correlation between teamwork and error rates — in what I initially considered "the wrong direction."

This presented a puzzle. Did better-led teams really make more mistakes? I simply did not think that could be accurate. Why else might better teams have higher error rates?

One possibility was that they were more experienced and thus given tougher patients. To test this, I controlled for the severity of patient illness. The unexpected result not only did not change, the relationship got slightly stronger. Then, I suddenly glimpsed what these results might mean. In well-led teams, a climate of openness could make it easier to report and discuss errors — compared to teams with poor relationships or with punitive leaders. The good teams, according to this interpretation, don't make more mistakes, they report more. When I suggested this to physicians involved in the study, they were skeptical. Their response was understandable: With a research grant for the purpose of identifying the error rate, this idea was decidedly unwelcome. My interpretation of the data suggested that we might not be finding the definitive error rate — and further errors might be systematically underreported in certain units but not others. Their skepticism forced me to work hard to develop ways to support my proposition, which ultimately they came to see as reasonable, if not obvious in retrospect."

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