|Faculty member Scott Page discusses problem-solving techniques using a diagram of the Chicago mass transportation system. Photo by Martin Vloet, U-M Photo Services|
But according to a U-M researcher, a collection of the best and brightest problem solvers is not as effective as a randomly selected group of problem solverswhich is more likely to contain a diversity of approaches, enabling it to find better solutions.
In a new study on diversity and optimality, Scott Page, associate professor of political science, complex systems and economics, and colleague Lu Hong of Loyola University in Chicago found that diversity can resolve the apparent contradiction between the limited ability of humans to solve problems (humans as boundedly rational problem solvers) and optimal decision making.
By using both computational and mathematical models, Page and Hong found that on average, groups of 10, 20 and even 40 randomly selected problem solvers outperform the best problem solvers in corresponding groups because of differences in perspectives and heuristics (variations in how people encode and search for solutions to problems) found in the random groups.
This rather surprising result has an intuitive explanation, Page says. If several thousand bounded problem solvers with diverse problem-solving approaches are ranked by their individual abilities, the best problem solvers tend to take similar approaches.
Being bounded rationally only stifles good decisions if we are boundedly rational in the same way. If the best problem solvers tend to think about a problem similarly, then it stands to reason that as a group, they may not be very effective. Random groups may be better, owing to their diversity.
By diversity, Page means differences in problem solvers perspectives and heuristics, differences that could result from disparate identities or ideologies stemming from an individuals race, culture, gender, educational background or life experiences.
To illustrate his point, Page uses the example of a well-known American company that appeals to a diversity of tastesBen & Jerrys Ice Cream.
According to their irreverent biography, when Ben and Jerry were developing New York Super Fudge Chunk Ice Cream, they covered a large table with pints made with different recipes, Page says. Along one edge of the table, the pints had more and more chunks. Along the other edge, the size of the chunks increased. Using this encoding, the pint in one corner of the table had only a few small chunks, while the pint in the other corner had an abundance of enormous chunks. In our model, this would be their perspective. Ben and Jerrys heuristic was to eat locallywhile thinking globally, of coursefrom a starting point. When they found a point with no tastier neighbors, they stoppedand thats the ice cream we eat today.
So how does diversity enter? Imagine a consultant who thought that calories matter. Her perspective would then be to arrange the pints from least to most caloric. Her heuristic, like Ben and Jerrys, could be to search neighboring pints, but her neighbors differ from their neighbors. And its possible that she could find an improvement on the pint they found. Does this mean shes smarter or at least better at developing new ice creams? Probably not. After all, Ben and Jerry are the experts. They probably have a better perspective on this problem than the consultant. Nevertheless, she can still help them by bringing a new way, even an inferior one in some sense, to look at the problem.
Page says that a collection of problem solvers does not necessarily mean a group of people sitting in a room together making a joint decision. The problem solvers also might operate within a hierarchy, where each person works on a problem and passes his/her solution on to the next person.
We can even interpret the collective performance to be that which would occur in a market, where problem-solving activities are not explicitly coordinated, he says. The ultimate product, whether it be an automobile, a microwave oven, a movie or a piece of software, embodies the efforts of many individuals. Though it is likely that teams, firms and markets differ in how they encourage people to locate solutions to problems, we emphasize here that all else equal, firms, teams and markets perform better when they consist of diverse problem solvers.
While much of Pages research focuses on the need for a diversity of perspectives and heuristics in the world of business or policy-making, he says his problem-solving models are equally applicable to the college classroom.
For example, he says, seminar discussions can be thought of as a sequential search for answers and understanding, and without students with diverse perspectives and heuristics, all students might agree with an initial classroom solution proposed for a problem.
In addition to reaching deeper understandings, Page says that such discussion enables students to learn the perspectives and heuristics of their classmates, and according to the Hong-Page framework, learning a new perspective or heuristic makes an individual a better problem solver.
Likewise, many college courses involve team project assignments and the sharing of ideas among students in both formal and informal study groups with diverse viewpoints, says Page, who is currently teaching the undergraduate seminar Theories of Diversity.
Were training students who will ultimately be involved in many organizations and teamsfrom churches to families to firms to volunteer organizations to political organizations, he says. If one of our missions as a university is to help those institutions perform better, then we should be concerned with creating intelligent, engaged, diverse people.