What Makes Groups Successful?

The influence of network structure and social learning strategies

A study by the Max Planck Institute for Human Development and the Santa Fe Institute identifies conditions that can both promote and inhibit successful group decision making. The results have been published in the journal Nature Communications.

The problem-solving capacity of a group depends on how its individual members connect and communicate with each other. But results from previous studies were inconsistent: Some found groups that were well-connected to be more successful in finding the best solution, whereas others found poorly connected groups to be more successful. In the latter case, so the argument goes, group members need to invest more effort into searching for solutions and hence increase their chances of finding a better solution.

Using computer simulations, researchers from the Max Planck Institute for Human Development and the Santa Fe Institute have now found that these results are not contradictory but can instead be seen as two sides of the same coin. Successful group decision making ultimately depends on how groups trade off exploration (searching for novel, superior solutions) and exploitation (using existing solutions that work well). This trade-off, the study finds, is affected both by how individual group members learn from other group members—that is, their social learning strategies—and by the network structure in which group members are embedded. Good performance results from the right match between social learning strategy and network structure. Well-connected (efficient) networks are superior when members follow the solution most frequently proposed by other members. Less efficient networks, by contrast, are better when individuals copy the group member with the best solution.  

The network structure determines the success of the strategies and vice versa. “If you copy the best solution your collaborators have found so far, you soon pick up on a promising solution and start exploiting it, and thus engage in less exploration. This has the benefit of spreading solutions quickly in a network but also the danger of zooming in on inferior solutions. It’s a fast strategy that works well in less connected, slower networks, where it strikes the right balance between exploration and exploitation,” says Daniel Barkoczi, lead author and post-doctoral researcher at the Max Planck Institute for Human Development. “On the other hand, if you choose the solution most frequently used by your collaborators, it slows down the learning process because you need to wait for the solution to be adopted by several others before accepting it. This slow strategy is best able to trade off exploration and exploitation when combined with a more tightly connected, efficient network structure.”

The study has implications for organizational learning, as well as for technological and cultural innovation. The researchers identified conditions that can both promote and hinder innovation. "Many studies dealing with innovation in organizations limit themselves to investigating how to shape the external environment in order to improve group performance," says Daniel Barkoczi. But the social learning strategies used by individual group members are also critical. The interaction of these strategies and the external environment jointly determines the outcome. Organizations focusing only on the structure of communication networks might therefore fail to achieve the desired effects.”

Original Publication
Barkoczi, D., & Galesic, M. (2016). Social learning strategies modify the effect of network structure on group performance. Nature Communications, 7, 13109. doi:10.1038/ncomms13109

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