On the inventory performance of demand forecasting methods of medical items in humanitarian operations

Rostami-Tabar, Bahman ORCID: https://orcid.org/0000-0002-3730-0045, Hasni, Marwa and Babai, Zied 2022. On the inventory performance of demand forecasting methods of medical items in humanitarian operations. IFAC-PapersOnLine 55 (10) , pp. 2737-2742. 10.1016/j.ifacol.2022.10.132

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Abstract

The inventory management of medical items in humanitarian operations is a challenging task due to the intermittent nature of their demand and long replenishment lead-times. While effective response to emergency results in inventory build-up which saves human lives, excess inventories could be intentionally burnt or donated which is costly for humanitarian organizations. Henceforth, linking demand forecasting to the inventory control task is shown to be a significant scope to offer a higher performance. In this vein, it is key to accurately select adequate forecasting methods. This paper investigates the effectiveness of parametric and non-parametric demand forecasting methods that are commonly considered to deal with stock keeping units (SKUs) characterized with an intermittent demand in industrial contexts. To do so, we conduct an empirical study by means of data related to 1254 SKUs managed in three warehouses of a major humanitarian organization based in Geneva, Middle-east and Africa. The investigation is carried out to compare the inventory performance of three parametric and two bootstrapping methods when used with an order-up-to-level inventory control policy. The results demonstrate the high performance of the bootstrapping methods in achieving higher service levels. The investigation enables to gain insights on the forecasting method that should be selected under particular assumptions on the demand and the lead-time value.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Business (Including Economics)
Publisher:	Elsevier
ISSN:	2405-8963
Date of First Compliant Deposit:	7 December 2022
Date of Acceptance:	26 October 2022
Last Modified:	29 Jul 2024 10:01
URI:	https://orca.cardiff.ac.uk/id/eprint/154705

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