Teaching Smart People How to Fail

Twenty five years ago Chris Argyris summarized a long-term study of management consultants, typically recent MBA graduates from a handful of top business schools, as they struggled to learn how to improve their work.

Published in Harvard Business Review in 1991, “Teaching Smart People How to Learn” has lessons for improvement in health care, where there are lots of smart people, too. https://hbr.org/1991/05/teaching-smart-people-how-to-learn , also available https://www.ncsu.edu/park_scholarships/pdf/chris_argyris_learning.pdf accessed 20 July 2016. Page numbers reference this pdf.)

What does Argyris mean by learning? How could academically accomplished MBAs not know how to learn? After all, they had great grade point averages and superior standardized test scores.

Argyris invented the distinction between single-loop learning and double-loop learning. He found the MBAs often were not capable of double-loop learning. 

“First, most people define learning too narrowly as mere ‘problem solving,’ so they focus on identifying and correcting errors in the external environment. Solving problems is important. But if learning is to persist, managers and employees must also look inward. They need to reflect critically on their own behavior, identify the ways they often inadvertently contribute to the organization’s problems, and then change how they act. In particular, they must learn how the very way they go about defining and solving problems can be a source of problems in its own right.” 

“I have coined the terms ‘single loop’ and ‘double loop’ learning to capture this crucial distinction. To give a simple analogy: a thermostat that automatically turns on the heat whenever the temperature in a room drops below 68 degrees is a good example of single-loop learning. A thermostat that could ask, ‘Why am I set at 68 degrees?’ and then explore whether or not some other temperature might more economically achieve the goal of heating the room would be engaging in double-loop learning.”(p.4) 

In other words, double-loop learning builds on the simple feedback and adjustment of behavior in a defined environment that characterizes single-loop learning. In double-loop learning, we’re open to using information from the environment to change our mental model and decision-making rules. (See the clear explanation and picture in the Wikipedia article on double-loop learning here. 

Argyris’s subjects all appreciated this distinction and were committed to continuous improvement in performance. What prevented their embrace of double-loop learning? 

When the MBAs found themselves in situations where single-loop learning failed to produce good results, the failure provoked defensiveness and anxiety--psychological states unlikely to promote effective learning. 

Argyris concluded that a major reason for this reaction was predictable: the elite management consultants had succeeded spectacularly in school and seldom, if ever, experienced failure. They didn’t know how to learn from failure. When confronted with evidence of failure to achieve expected performance, their defensiveness and anxiety overwhelmed effective analysis. 

This brings me back to the advice on testing developed by my colleagues at API summarized in table 7.1 in The Improvement Guide, 2nd edition. They give three factors to guide choice on scale of test, including Failure Cost. 

Argyris has helped me reinterpret failure cost. Failure cost certainly relates to costs like harm to patients, loss of revenue or reputation. However, Argyris convinces me that failure costs should include psychological costs: defensiveness and anxiety that prevent effective learning by smart people unused to failure. 

With that interpretation, the cost of failure may loom large for professionals and generate behavior that appears as “resistance to change”.

API’s table points us to very small-scale tests when cost of failure is large. 

Very small scale tests, with modest or negligible consequences of failure, appear to give smart people a way to gain experience with less than perfect performance. 

Gradual exposure and mastery of very small failures, in a quest to inquire about how people actually work and a willingness to modify mental models, looks like a way to reduce anxiety and fear. 

In testing, people can “…begin to identify the inconsistencies between their espoused and actual theories of action. They can face up to the fact that they unconsciously design and implement actions that they do not intend.” (p. 11) 

Note on problem-solving

Argyris’s single and double loop learning are cousins of the first and second order problem-solving I discussed here. Second order problem solving involves reflection and study to prevent recurrence of problems, not just immediate fixes that permits work to continue.