Random groups solve problems better than select groups

March 8, 2001
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ANN ARBOR—When it comes to solving problems, making good decisions or thinking of new ideas, a group of the best individual people may not be the best collective group of people for the task, says a University of Michigan researcher.

In a testament to the value of diversity, a new study by U-M researcher Scott E. Page and colleague Lu Hong of Loyola University found that a group of people selected at random is more effective than a collection of the best and brightest individuals at problem-solving, decision-making and original thinking in such realms as business, policy-making and college classrooms.

This is because the random group is more likely to contain a diversity of approaches to these tasks, Page and Hong say.

In their study, “Diversity and Optimality,” the researchers say that diversity can resolve the apparent contradiction between the limited ability of people to solve problems (humans as “boundedly rational problem solvers”) and optimal, or best, decision-making.

By using computational and mathematical models, Page and Hong found that, on average, groups of randomly selected “problem solvers” outperform groups consisting of the best individual problem solvers because of differences in perspectives and heuristics (variations in how people search for solutions to problems) found in the random groups.

“This rather surprising result has an intuitive explanation,” says Page, U-M associate professor of political science, complex systems and economics. “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 and Hong mean differences in problem solvers’ perspectives and how they search for solutions (heuristics)—differences that could result from disparate identities or ideologies stemming from an individual’s race, culture, gender, educational background or life experiences.

The researchers say 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 might also 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,” Page 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.”

Scott E. PageDiversity and Optimalitypolitical science