Original Research
The impact of point-of-sale data in demand planning in the South African clothing retail industry
Submitted: 30 March 2017 | Published: 28 August 2017
About the author(s)
Douglas N. Raza, Department of Transport and Supply Chain Management, University of Johannesburg, South AfricaPeter J. Kilbourn, Department of Transport and Supply Chain Management, University of Johannesburg, South Africa
Abstract
Background: In modern days’ dynamic consumer markets, supply chains need to be value driven and consumer oriented. Demand planning allows supply chain members to focus on the consumer and create optimal value. In demand planning, Point-of-Sale (POS) data are an essential input to the process thereof; however, literature suggests that POS-based demand planning is often overlooked by demand planners in practice.
Objective: The main purpose of this study was to determine the extent to which South African clothing retailers use POS data in demand planning.
Method: This study followed the grounded theory approach based on the collection of qualitative data. The data collected was analysed following the grounded theory analysis using codes that resulted in various categories which then developed into themes.
Findings: Findings suggest that companies within the clothing retail industry make considerable use of POS data and is a fundamental input factor in the demand planning process. However, this study also found that POS data cannot be applied in the planning for all types of clothing products, and that there are variables other than POS data that form a critical part of the demand planning process.
Conclusion: POS data plays a fundamental role is the demand planning process and should be accurately collected and used with other qualitative and quantitative factors as an input factor to the demand planning process. The role of POS data in demand planning is expected to grow as customers are becoming increasingly demanding concerning customer service levels.
Keywords
Metrics
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Crossref Citations
1. Anniversary 2007–2017
Stephen Kruger, Noleen Pisa
Journal of Transport and Supply Chain Management vol: 11 year: 2017
doi: 10.4102/jtscm.v11i0.340