Optimizing fixed targets in organizations through simulation

This paper examines how setting targets in organizations affects decision making. We assume a division acts to maximize the probability of meeting its given target. We use a simulation-based model to quantify the value gap that results from this target-based behavior in relation to utility maximizing behavior. We define an optimal target as one that minimizes the value gap. We investigate the effects of the organization´s risk aversion, the number of potential decision alternatives, and the distribution of the alternatives on both the value gap and the optimal target. The distribution of the alternatives is modeled with a copula based method. The results show that the optimal target (i) decreases as the risk aversion increases; (ii) increases as the number of available alternatives increase; and (iii) decreases as the alternatives approach some efficient frontier. We discuss the rationale and implications for the simulation results.