Lauren Liwen
MBA 608
Dr. Turek
Cranston Coils Regression Case

Executive Summary The Cobb-Douglas cost function of Cranston Coils was found using output, capital, and labor data from their eighteen plants. The cost function, Q = (0.40692) K0.32477 L0.79466, was used to determine the short-run cost equations of total cost, average cost, average variable cost and marginal cost. Calculations using these equations gave rise to Cranston Coils cost structure, which predicts cash flow within the company. Cranston Coils’ cost function was also used to determine if a contract between Sleep Easy and Cranston Coils should be accepted. After determining marginal cost and revenue (see Appendix 5: Sleep Easy Contract Costs at Connecticut Plant), the contract should be accepted.
Problem Definition The short-run cost structure of the new Cranston Coils facility in Connecticut needs to be determined in order to predict the cash flow of the new plant. Once the cost structure is defined, the cost function can be used to evaluate whether or not certain contracts should be accepted, such as the Sleep Easy Company’s proposed contract of fifty units at $70.00 per unit.
Identification of Possible Solutions The short-run cost equations of Cranston Coils indicate that the cost structure varies between the plants because of the significant discrepancy between the marginal costs of each plant. One possible solution would be to reevaluate each plant’s marginal product of labor and marginal product of capital in order to determine where the discrepancies are occurring. After these calculations have been conducted, each plant should seek to adjust their input in order to maximize output. The optimal way to conduct this is to find where total revenue equals total cost, and set the inputs of cost (capital and labor) to the appropriate levels. For plants unable to reach profit