Approximations for the Lead Time Variance:a Forecasting and Inventory Evaluation

Saoud, Patrick and Kourentzes, Nikolaos and Boylan, John E. (2022) Approximations for the Lead Time Variance:a Forecasting and Inventory Evaluation. Omega, 110. ISSN 0305-0483

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Abstract

Safety stock is necessary for firms in order to manage the uncertainty of demand. A key component in its determination is the estimation of the variance of the forecast error over lead time. Given the multitude of demand processes that lack analytical expressions of the variance of forecast error, an approximation is needed. It is common to resort to finding the one-step ahead forecast errors variance and scaling it by the lead time. However, this approximation is flawed for many processes as it overlooks the autocorrelations that arise between forecasts made at different lead times. This research addresses the issue of these correlations first by demonstrating their existence for some fundamental demand processes, and second by showing through an inventory simulation the inadequacy of the approximation. We propose to monitor the empirical variance of the lead time errors, instead of estimating the point forecast error variance and extending it over the lead time interval. The simulation findings indicate that this approach provides superior results to other approximations in terms of cycle-service level. Given its lack of assumptions and computational simplicity, it can be easily implemented in any software, making it appealing to both practitioners and academics.

Item Type:
Journal Article
Journal or Publication Title:
Omega
Additional Information:
This is the author’s version of a work that was accepted for publication in Omega. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Omega, 110, 2022 DOI: 10.1016/j.omega.2022.102614
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1800/1802
Subjects:
ID Code:
169200
Deposited By:
Deposited On:
27 Apr 2022 14:05
Refereed?:
Yes
Published?:
Published
Last Modified:
04 May 2022 02:45