Forecasting Accuracy and Learning: The Key to Measuring Simulation Performance

Authors

  • Richard Teach

Abstract

"This paper looks at forecasting errors made by student participants of the CAPSTONE simulation. CAPSTONE is a total enterprise simulation in which participants make individual product decisions as well as firm-wide management decisions. Over the eight rounds of the simulations, the student learned how to more accurately forecast outcomes. Each participant was essentially a “brand manager” for a single product and each student was held responsible for the contribution margin of their product. After the decisions for each round were made, each student was required to forecast the following four items: 1) the unit gross margin of their product; 2) the unit sale of their product; 3) their product’s market share; and 4) their product’s ending inventory levels in terms of the number of units on hand and the number of days of sales the inventory represented at the end of the round. The accuracy of these forecasts was then related to the student product’s contribution to overhead and profit. After the product level forecasts were made, the team acting as a committee of the whole forecast three firm-wide outcomes: 1) the cash–on-hand at the end of the period; 2) the return on sales (ROS) for the period and 3) the earnings per share (EPS) for the period. The study found a strong positive relationship between the product-level forecast accuracy and the product’s contribution margin and the firm-wide forecast accuracies and the firm’s profitability. A rather strange anomaly was found. If a firm went into a chapter 11 Condition (it needed an emergency loa), it became more profitable. Implications of these findings are discussed. "

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Published

2014-02-24