The work presented in this paper investigates behaviorally plausible rules for making decisions in complex situations. A rule is plausible if it iss consistent with assumptions concerning limits on a decision maker’s information processing capacity. The structure and relationship between decision environment, manager and decision strategies is modeled in stochastic terms and resulting performance is studied using Monte Carlo simulation. The basic analytical framework, initially developed by Radner and Rothschild considers a manager who is responsible for n activities. At the beginning of each time period the manager must decide how to allocate his time among competing activities. If at time t the manager devotes all effort to activity i, its performance will improve or remain unchanged according to a stochastic rule. Likewise, if no time is allocated to an activity, its performance deteriorates or remains unchanged. Different decisions strategies are investigated including putting out fires, adaptive random selection and constant proportions. The goal is to gain insights which are useful in both describing and prescribing managerial behavior in organizations. Limitations of the model and future work are discussed.