Searches that include both feasible and infeasible solutions have proved to be ef cient algorithms for solving some scheduling problems. Researchers conjecture that these algorithms yield two primary benefits: 1) they tend to focus on solutions close to the boundary between feasible and infeasible solutions, where active constraints are likely to yield optimal values, and 2) moves that include infeasible solutions may uncover short-cuts in a search space. Researchers have published empirical studies that confirm the value of searching along the feasible-infeasible boundary, but until now there has been little direct evidence that infeasible search yields short-cuts. We present empirical results in two oversubscribed scheduling domains for which boundary region search in infeasible space appears to offer advantages over search in strictly feasible space. Our results confirm that infeasible search finds shortcuts that may improve search efficiency more than boundary region search alone. However, our results also reveal that ineffi- cient infeasible paths which we call detours may degrade search performance, potentially offsetting efficiency shortcuts may provide.