In this paper, we examine how empirical production frontiers may contribute to the incentives of production units. We consider a series of Data Envelopment Analysis (DEA) frontiers, and we show when these may be incentive efficient in the sense that they contain all the information that are relevant for optimal incentive provision. The frontiers considered include the so-called constant, decreasing and varying return to scale models, the free disposability and the free replicability models, as well as the increasing and decreasing return to scale models based on a relaxed set of assumptions. Also, we illustrate how to design optimal incentive schemes based on such frontiers.