Working Paper
Organizations often rely on deliberative groups -committees, taskforces, boards- to make decisions, yet deliberation's effectiveness remains contested. When can deliberation help a group outperform the average or even the best individual in the group? We propose that the value of deliberation depends on how the network structure of the group shapes informational influence (which promotes updating beliefs based on perceived expertise) and normative influence (which drives conformity to gain social approval). Using an agent-based model, we show that deliberation can help groups achieve strong synergy effects (i.e. outperform the best individual in the group) if members typically recognize each other’s relative expertise at better than chance levels, and when the network structure neither isolates any members nor allows for clustering and cliques. Moreover, introducing a few actors into the network who are impervious to conformity (such as AI agents) can improve group decision quality even if these actors are no better than random chance at recognizing expertise. We draw implications for how to compose and structure group deliberation processes to improve the chances of obtaining effective decisions.
Faculty
Professor of Strategy
