Early work in pharmacology characterized the interaction of receptors and ligands in terms of two parameters, affinity and efficacy, an approach we term the bipartite view. A precise formulation of efficacy only exists for very simple pharmacological models. Here we extend the notion of efficacy to models that incorporate receptor activation and G-protein coupling. Using the cubic ternary complex model, we show that efficacy is not purely a property of the ligand-receptor interaction; it also depends upon the distributional details of the receptor species in the native receptor ensemble. This suggests a distinction between what we call potential efficacy (a vector) and realized efficacy (a scalar). To each receptor species in the native receptor ensemble we assign a part-worth utility; taken together these utilities comprise the potential efficacy vector. Realized efficacy is the expectation of these part-worth utilities with respect to the frequency distribution of receptor species in the native receptor ensemble. In the parlance of statistical decision theory, the binding of a ligand to a receptor ensemble is a random prospect and realized efficacy is the utility of this prospect. We explore the implications that our definition of efficacy has for understanding agonism and in assessing the legitimacy of the bipartite view in pharmacology.