Initially, in the information-gathering ‘reconnaissance’ stage of the game, the more connected groups performed well: the ability to pass leads on to all the other members meant that the team quickly gathered lots of potential clues about the attack. But they soon lost that advantage when they had to piece that information together to form a coherent theory about the way the terrorist plot would take place. Although you might expect that these teams would struggle to come to an agreement, like a hung jury, the major problem was conformity: the team members quickly converged on a consensus without really exploring the other possibilities. “People aren’t brainstorming effectively – they’re not going off in their own direction,” explains Shore.
The less well-connected groups, in contrast, suffered a bit with the information gathering, but they were also less likely to reach a consensus too quickly. Without the immediate updates from all teammates, each member was instead more likely to build their own theories, meaning that there was a greater diversity of ideas available before the team as a whole settled on the best solution.
Alone time
This finding, by itself, would suggest that teams might consider limiting the communication among members. A bit of chit chat is good, but you don’t necessarily want to know what everyone else is doing during the more creative parts of the problem solving that require the generation and testing of lots of ideas.
Inspired by this result, Shore and his colleagues next examined how the rhythm of our communication can also influence our problem solving. Even if you are working in a small group, you have the option to receive constant updates, or limit your communication to a few regular catch-ups – but which is best?
To find out, the researchers asked participants to find solutions to a classic puzzle known as the “travelling salesman” problem, in which they were given a map of 25 different cities and needed to work out the shortest journey passing through them all. It’s best solved iteratively, as you play with different options – and often retracing your previous steps – to find the optimal path.
