Original Research

Forecast accuracy in demand planning: A fast-moving consumer goods case study

Lisa M. Basson, Peter J. Kilbourn, Jackie Walters
Journal of Transport and Supply Chain Management | Vol 13 | a427 | DOI: https://doi.org/10.4102/jtscm.v13i0.427 | © 2019 Lisa Michelle Basson, Peter J. Kilbourn, Jacobus Walters | This work is licensed under CC Attribution 4.0
Submitted: 21 October 2018 | Published: 19 June 2019

About the author(s)

Lisa M. Basson, Department of Transport and Supply Chain Management, University of Johannesburg, Johannesburg, South Africa
Peter J. Kilbourn, Department of Transport and Supply Chain Management, University of Johannesburg, Johannesburg, South Africa
Jackie Walters, Department of Transport and Supply Chain Management, University of Johannesburg, Johannesburg, South Africa


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Abstract

Background: An established South African fast-moving consumer goods (FMCG) manufacturer, Company A, sought to address an underperforming supply chain through an attempt to improve demand planning accuracy. A need arose within the organisation for an assessment of the impact of this intervention. A literature gap was also identified, taking into account the limited number of relevant case studies that exist in academic literature.

Objectives: The primary objective of this study was to establish whether or not the demand planning interventions of Company A had a positive impact on the performance of the supply chain under investigation. In support of this primary objective, the secondary objectives were to determine and compare the pre- and post-intervention demand planning activities and performance of Company A.

Method: A case study research design was used focusing on Company A. The researcher sourced evidence through a secondary quantitative data analysis and primary data collection through interviews with personnel directly involved in the demand planning process at Company A.

Results: From mean absolute percentage error calculations, it was found that the focal company’s demand planning process intervention had reduced the errors in demand forecasting for all classifications of stock keeping units analysed.

Conclusion: The demand planning interventions applied by Company A had a positive impact on the overall supply chain performance. A positive relationship was found between a well-informed, team-based and technology-assisted approach to demand planning and improved forecasting accuracy within an FMCG company.


Keywords

demand planning; forecasting; fast-moving consumer goods; forecast accuracy; mean absolute percentage error

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