Optimal skill diversity in teams

We investigate how optimal team skill/expertise diversity depends on the nature of production and the team’s objective. Akin to horizontal differentiation, an agent’s contribution is decreasing in the distance from their expertise to the required task, while diversity is captured by the distance between the expertise of the agents. Optimal skill diversity weakly increases when team output relies more on the best performing agent under a Bayesian (expected-value) objective. In contrast, with a robust (worst-case) objective, which captures the preferences of a public service provider, a regulated firm, or a very risk averse manager, optimal skill diversity might decrease when the team output is more dependent on the best performer. Furthermore, we show that optimal skill diversity is weakly higher under the robust objective than under the Bayesian objective; this suggests that greater skill diversity in teams can be achieved by imposing a minimal satisfactory service (performance) requirement, rather than micromanaging diversity directly.