The development of a hierarchical forecasting method for predicting spare parts demand in the South Korean Navy—A case study

In the South Korean Navy the demand for many spare parts is infrequent and the volume of items required is irregular. This pattern, known as non-normal demand, makes forecasting difficult. This paper presents a case study using data obtained from the South Korean Navy to compare the performance of various forecasting methods that use hierarchical and direct forecasting strategies for predicting the demand for spare parts. A simple combination of exponential smoothing models was found to minimise forecasting errors. A simulation experiment verified that this approach also minimised inventory costs.