This paper explores the trade-offs inherent in the pursuit and fulfillment of multiple performance goals in complex organizations. We examine two related research questions: (1) What are the organizational implications of pursuing multiple performance goals? (2) Are local and myopic (as opposed to global) goal prioritization strategies effective in dealing with multiple goals? We employ a series of computational experiments to examine these questions. Our results from these experiments both formalize the intuition behind existing wisdom and provide new insights. We show that imposing a multitude of weakly correlated performance measures on even simple organizations (i.e., an organization comprised of independent employees) leads to a performance freeze in that actors are not able to identify choices that enhance organizational performance across the full array of goals. This problem increases as the degree of interdependence of organizational action increases. We also find that goal myopia, spatial differentiation of performance goals, and temporal differentiation of performance goals help rescue organizations from this status quo trap. In addition to highlighting a new class of organizational problems, we argue that in a world of boundedly rational actors, incomplete guides to action in the sense of providing only a subset of underlying goals prove more effective at directing and coordinating behavior than more complete representations of underlying objectives. Management, in the form of the articulation of a subset of goals, provides a degree of clarity and focus in a complex world.