Despite our best efforts as evaluators, program implementation failures abound. A wide variety of
valuablemethodologies have been adopted to explain and evaluate the why of these failures. Yet, typically
these methodologies have been employed concurrently (e.g., project monitoring) or to the post-hoc
assessment of program activities. What we believe to be missing are methods that will lead to the
successful prediction of programimplementation failures in advance,methods that will lead us directly to
the ‘‘how’’ and, especially, the ‘‘how likely’’ of program implementation failure. Tothat endwe propose,
discuss, and illustrate three such methods that seemingly hold promise – marker analysis, the wisdomof
crowds, and ‘‘Big Data.’’ Additionally, we call for an expanded role for evaluation – explanation, but also
prediction without a total embrace of the need to understand why a prediction works.