An efficient ranking and selection approach to boost the effectiveness of innovation contests

Breakthrough innovation has two key prerequisites: idea generation, collection of a large number of competing designs, and idea screening, efficient evaluation, and ranking of these designs to identify the best one(s). Open innovation has recently been modeled and analyzed as innovation contests, where many individuals or teams submit designs or prototypes to an innovating firm. Innovation tournaments increase the capacity of idea generation by enabling access to a broad pool of solvers while avoiding exorbitant costs. To deliver on their promise, however, such tournaments must be designed to enable effective screening of proposed ideas. In particular, given the large number of designs to be evaluated, tournaments must be efficient, favoring quick judgments based on imperfect information over extensive data collection. Through a simulation study, this article shows that contests may not necessarily be the best process for ranking innovation opportunities and selecting the best ones in an efficient way. Instead, we propose a ranking and selection approach that is based on ordinal optimization, which provides both efficiency and accuracy by dynamically allocating evaluation effort away from inferior designs onto promising ones. A numerical example quantifies the benefits. The proposed approach should therefore complement innovation tournaments’ ability of idea generation with efficient idea screening.