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IMA Journal of Management Mathematics Advance Access published online on February 27, 2008
IMA Journal of Management Mathematics, doi:10.1093/imaman/dpn001
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© The authors 2008. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Forecasting aggregate time series with intermittent subaggregate components: top-down versus bottom-up forecasting

S Viswanathan{dagger} and Handik Widiarta

Nanyang Business School, Nanyang Technological University, Singapore 639798, Republic of Singapore

Rajesh Piplani

School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore

{dagger}Corresponding author. Email: vish{at}pmail.ntu.edu.sg

Received on 12 January 2007. Accepted on 10 January 2008.

In this paper, we evaluate the performance of top-down (TD) and bottom-up (BU) forecasting strategies in estimating the aggregate data series when the subaggregate time series components are intermittent. The findings of our simulation-based study are as follows. When the variability of the inter-order intervals of the subaggregate time series is low, BU forecasting that is carried out using Croston's method outperformed TD for estimating the aggregate data series. However, when the inter-order intervals and the demand sizes of the subaggregate components are highly variable and the aggregate data series is composed of many subaggregate components, TD forecasting outperformed BU. Finally, for forecasting the aggregate demand using TD forecasting, the simple exponential smoothing technique outperformed Croston's method in a majority of the cases.

Keywords: forecasting; intermittent time series; top-down forecasting; bottom-up forecasting; Croston's method; inventory management


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