ON THE EFFICIENCY OF COST-BASED DECISION RULES FOR CAPACITY PLANNING

The quality of capacity planning significantly affects firm profitabil ity, particularly for firms in service industries. In practice, firms use product cost data to infer the expected cost of under-and over-sto cking capacity and to determine installed capacity. Theory shows that this is not optimal practice. In light of the informational and comput ational complexities associated with the optimal theoretical formulati on, the use of product cost may be justified as a heuristic. For a mul ti-product, multi-resource firm, we use simulations to investigate the efficiency of four cost-based decision rules in determining the expec ted cost of under-and over-stocking capacity. Results indicate surpris ingly high performance levels, relative to a benchmark solution, The p erformance of the product-based planning rule deteriorates as products increasingly share capacity resources, The opposite is true for resou rce-focused rules. There appears to be significant value from identify ing mechanisms to balance installed capacity across resources.