Statistical Quality Control for the Service Sector

The service industry has become increasingly important in our daily lives and global economies, and improving service quality will have a significant social and economical impact. The massive amount of data readily available provides us with opportunities to integrate advanced statistical methodologies with system knowledge to better model and control the quality of service sys-tems. Monitoring and quick detection of abnormal activities have become critical in a variety of service industries that have complex operation systems and process huge amounts of data. However, most conventional statistical process control techniques cannot effectively handle the monitoring and surveillance of such a large amount of data on a real-time basis. This paper in-dicates the importance of and sheds some lights on developing statistical monitoring and control methodologies for the service sector. It focuses on three fundamental issues: (1) the monitoring of feedback data arising from customers ’ perception of service quality; (2) the monitoring and controlling metrics of operational performance in service systems; and (3) the monitoring of the functional relationship between operational determinants and the service quality perceived by end customers. In addition, we will elaborate on the first issue by reviewing some recently developed results