A new approach to forecasting intermittent demand for service parts inventories

A new approach to forecasting intermittent demand for service parts inventories

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Article ID: iaor2005428
Country: Netherlands
Volume: 20
Issue: 3
Start Page Number: 375
End Page Number: 387
Publication Date: Jul 2004
Journal: International Journal of Forecasting
Authors: , ,
Keywords: inventory
Abstract:

A fundamental aspect of supply chain management is accurate demand forecasting. We address the problem of forecasting intermittent (or irregular) demand, i.e. random demand with a large proportion of zero values. This pattern is characteristic of demand for service parts inventories and capital goods and is difficult to predict. We forecast the cumulative distribution of demand over a fixed lead time using a new type of time series bootstrap. To assess accuracy in forecasting an entire distribution, we adapt the probability integral transformation to intermittent demand. Using nine large industrial datasets, we show that the bootstrapping method produces more accurate forecasts of the distribution of demand over a fixed lead time than do exponential smoothing and Croston's method.

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