Quality management performance modelling for the South African contact centre industry.
MetadataShow full item record
Against the background of an extreme youth unemployment problem, South Africa seeks to identify and support industries that may offer substantial solutions. The employment potential of the contact centre industry was recognised by the South African government as far back as 2004. By capitalising on comparative advantages such as lower costs, South Africa has successfully claimed a place amongst the preferred international customer service destinations. While lower costs remain a key driver behind the outsourcing of services to offshore destinations like South Africa, a shift in focus towards the ‘quality of service’ is increasingly featured in outsourcing decisions. It follows that, in order to maintain the competitive momentum amidst intense international rivalry, it is imperative that contact centre managers understand the relationship between quality practices and business performance. While these relationships have been investigated across various industry sectors and in various locations globally from as far back as the early 90s, such relationships have not been empirically investigated in the contact centre environment and specifically not in the South African context. The primary objective of this study is to address this gap by developing a model that reveals the nature of the quality practice / performance relationships together with the moderating impact of contingency factors. This should serve as a valuable, context-specific, industry reference while academically contributing towards the development of quality management theory. Based on extensive academic and practice literature, a new industry-specific measurement instrument was developed that demonstrated very good reliability and validity. By initially exploring the extent and manner in which quality practices are deployed it was found that the South African contact centre industry are generally ‘high users’ of quality practices that are normally deployed as part of a more holistic quality program. The proposed quality practice / performance model was based on features of prominent models found in the literature where Path Analysis techniques were employed to test the relationships among variables. Regression analyses confirmed the importance of ‘Top Management Support’ where Leadership quality practices showed a strong, positive and significant impact on the deployment of ‘Core quality practices’ such as Customer, Human Resource, Operational, Infrastructure and Relationship practices. When the impact of each core group of quality practices was measured in isolation i.e. via directly related performance metrics, the results show that all groups have a strong, positive and significant impact on performance. Similar results were obtained when performance was measured at an organisational level for both operational and business performance. Further, synergistic value was found in the deployment of quality practices thus confirming the interdependent nature of such practices. The key implication is that although there are variations in the impact among the various quality practices, all contribute significantly to operational and business performance – thus supporting the deployment of full-blown quality programs. The results may however be used for piecemeal program implementations that focus on the practices that offer the highest impact on performance i.e. customer and human resource-related practices. Finally, the contingency factors that demonstrated the highest moderating impact on the practice / performance relationships included ‘Management Knowledge’, External Demand for Compliance’ and ‘Culture’ while demographic factors had no significant impact. The result partially supports both the universal and context driven approaches to quality management. Path analyses revealed a good fit of the model to the data.