REPLACEMENT PARTS MANAGEMENT: THE VALUE OF INFORMATION
研究了指数平滑和加权移动平均两种简单预测方法在替换零件需求预测中的适用性，提出一种判断更复杂预测方法是否值得采用的方法，帮助管理者平衡预测精度与数据收集成本。
Exponential smoothing (ES) and weighted moving average (WMA) are the predominant methods used to predict future demand for replacement parts. They require simple calculations and make use of information readily available. By gathering more information and doing additional calculations, more accurate forecasts can be developed. However, the cost of collecting the additional data could exceed the inventory cost savings from the better demand forecast. This paper presents a straightforward method for determining when the benefits of a more complex forecasting method outweigh the total costs required to use the method.