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.

Background:The Gautrain was created with the sole purpose of availing efficient transportation between the three metropolitan municipalities, namely the City of Tshwane, the City of Johannesburg and the City of Ekurhuleni. The Gautrain has been transporting more than five million passengers annually. However, ridership decreased drastically because of COVID-19. Poor ridership has resulted in less revenue income and the halting of expansion. In prior years, the Gautrain Management Agency (GMA) measured customer satisfaction levels; however, it has not undertaken such a study since the start of COVID-19 pandemic.Objectives: The study measured service quality experienced by Gautrain users amidst the COVID-19 pandemic through the service quality (SERVQUAL) model. Unknown customer satisfaction levels with the Gautrain services during the COVID-19 pandemic posed a problem for the agency.Method: This study followed a descriptive and quantitative path. A cross-sectional survey via online platforms was used to collect the data. The study had a sample size of 84 Gautrain commuters. Results:The findings revealed that users experienced a negative service quality in terms of SERVQUAL dimensions, namely assurance, tangibles, empathy and responsiveness. Conclusion:The study concluded that COVID-19 had a negative impact on some of the Gautrain service factors; however, users were still satisfied with some of the service factors. It is recommended that the Gautrain can improve services by understanding what customers expect in terms of service factors during the pandemic.