The idea of program evaluation is both simple and appealing. Program outcomes are measured and compared to some minimum performance standard or threshold. In practice, however, evaluation is difficult. Two fundamental problems of outcome measurement must be addressed. The first, which we call the problem of auxiliary outcomes, is that we do not observe outcome of interest. The second, which we call the problem of counterfactual outcomes, is that we do not observe the threshold standard. This article examines how performance standard should be set and applied in the face of these problems in measuring outcomes. The central message is that the proper way to implement standards varies with the prior information an evaluator can credibly bring to bear to compensate for incomplete outcome data. By combining available data with credible assumptions on treatments and outcomes, the performance of a program may be deemed acceptable, unacceptable, or indeterminate.