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.

中文翻译：

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销售点数据对南非服装零售业需求计划的影响

背景：在当今充满活力的消费市场中，供应链需要以价值为导向且以消费者为导向。需求计划使供应链成员可以专注于消费者并创造最佳价值。在需求计划中，销售点（POS）数据是其过程的必要输入。然而，文献表明，基于POS的需求计划在实践中经常被需求计划者所忽视。目的：本研究的主要目的是确定南非服装零售商在需求计划中使用POS数据的程度。方法：本研究遵循基于定性数据收集的扎根理论方法。在扎实的理论分析之后，使用代码对收集到的数据进行了分析，得出了各种类别的代码，这些代码随后发展成为主题。发现：研究结果表明，服装零售行业中的公司大量使用POS数据，并且是需求计划过程中的基本输入因素。但是，这项研究还发现，不能将POS数据应用于所有类型的服装产品的计划中，并且除POS数据以外，还有其他一些变量构成需求计划过程的关键部分。结论：POS数据在需求计划过程中起着根本性的作用，应准确收集并与其他定性和定量因素一起用作需求计划过程的输入因素。随着客户对客户服务水平的要求越来越高，预计POS数据在需求计划中的作用将会增强。