The quality of capacity planning significantly affects firm profitability, particularly for firms in service industries. In practice, firms use product cost data to infer the expected cost of under- and over-stocking capacity and to determine installed capacity. Theory shows that this is not optimal practice. In light of the informational and computational complexities associated with the optimal theoretical formulation, the use of product cost may be justified as a heuristic. For a multi-product, multi-resource firm, we use simulations to investigate the efficiency of four cost-based decision rules in determining the expected cost of under- and over-stocking capacity. Results indicate surprisingly high performance levels, relative to a benchmark solution. The performance of the product-based planning rule deteriorates as products increasingly share capacity resources. The opposite is true for resource-focused rules. There appears to be significant value from identifying mechanisms to balance installed capacity across resources.

This paper studies information system design in a model of double moral hazard in which there is both a decision problem and a control problem. If either problem is considered in isolation, an information system that provides more public information is preferred. However, an information system that provides less public information can, in fact, be desirable because of an interaction between the two problems. The benefit of choosing an information system that provides less information is that it serves as a substitute for commitment for the principal. The cost is that neither the principal's decision (act) nor the agent's payments can be conditioned on the information. We provide sufficient conditions under which less information and more information are each optimal.