Title: Identifying a catalyst for demand uncertainty within inventory management forecasting

Authors: Ndivhuwo Nemtajela; A.S. Tolmay

Addresses: Department of Production and Operations Management, School of Public and Operations Management, University of South Africa (UNISA), P.O. Box 392, Unisa, 0003, South Africa ' Department of Production and Operations Management, School of Public and Operations Management, University of South Africa (UNISA), P.O. Box 392, Unisa, 0003, South Africa

Abstract: The problem addressed by the research reported in this paper is that the fast moving consumer goods (FMCG) sector is faced by high levels of demand uncertainty that, in turn, leads to high levels of out-of-stock (OOS) events. A lack of research on this topic still prevails, especially in developing countries. This study investigated which qualitative and quantitative techniques acts as a possible catalyst towards demand uncertainty. This research was conducted through a survey within the South African FMCG sector. The unit of analysis was the perceptions of employees regarding their understanding of the following concepts: 'qualitative forecasting', 'quantitative forecasting' and 'catalyst for demand uncertainty'. It was found, using path analysis that qualitative rather than quantitative forecasting techniques act as a possible catalyst towards demand uncertainty. This paper contributes towards conceptualising the management of demand through qualitative versus quantitative forecasting as a possible catalyst for demand uncertainty to prevent OOS.

Keywords: inventory management; demand uncertainty; qualitative forecasting; quantitative forecasting; forecasting catalysts.

DOI: 10.1504/IJLSM.2022.125659

International Journal of Logistics Systems and Management, 2022 Vol.43 No.1, pp.66 - 85

Received: 21 Nov 2019
Accepted: 20 Feb 2020
Published online: 26 Sep 2022 *

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