Journal
INTERNATIONAL JOURNAL OF FORECASTING
Volume 21, Issue 2, Pages 303-314Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ijforecast.2004.10.001
Keywords
demand forecasting; intermittent demand; accuracy measures; Croston's method; exponential smoothing; forecasting competition
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Intermittent demand appears sporadically, with some time periods showing no demand at all. In this paper, four forecasting methods, Simple Moving Average (SMA, 13 periods), Single Exponential Smoothing (SES), Croston's method, and a new method (based on Croston's approach) recently developed by the authors, are compared on 3000 real intermittent demand data series from the automotive industry. The mean signed and relative geometric root-mean-square errors are shown to meet the theoretical and practical requirements of intermittent demand, as do the Percentage Better and Percentage Best summary statistics based on these measures. These measures are subsequently applied in a simulation experiment. The out-of-sample comparison results indicate superior performance of the new method. In addition, the results show that the mean signed error is not strongly scale dependent and the relative geometric root-mean-square error is a well-behaved accuracy measure for intermittent demand. (c) 2004 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
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