Stochastic Models for the Design and Management of Customer Contact Centers: Some Research Directions

A (customer) contact center is a collection of resources providing an interface between a service provider and its customers. The classical contact center is a call center, containing a collection of service representatives (reps) who talk to customers over the telephone. In a call center, the service reps are supported by quite elaborate information-and-communication-technology (ICT) equipment, such as a private branch exchange (PBX), an interactive voice response (IVR) unit, an automatic call distributor (ACD), a personal computer (PC) and assorted databases. With the rapid growth of e-commerce, contact between the service provider and its customers if often made via e-mail or the Internet instead of by telephone. Thus the general interface between a service provider and its customers is now often called a contact center. The design and management of contact centers is important, and worthy of research, because contact centers comprise a large, growing part of the economy and because they are quite complicated. Classic call centers are complicated because there are often many types of calls, requiring different service skills, such as knowledge of different languages and knowledge of different special promotions. The ACD is able to respond through skill-based routing, but there remains an opportunity to determine better routing algorithms and more effective methods for staffing. The difficulties are largely due to uncertainty about future arrivals of service requests of various kinds and the time and resources that will be required to respond to those requests. Given that contact with customers no longer need be by telephone, it is necessary to consider the other media, e.g., e-mail, fax, Internet, etc. When service reps perform several different kinds of work, there is a need to allocate effort to the different tasks, which presents opportunities for improved efficiency if some of the work can be postponed. Multimedia also lead to more complicated contact experiences. For example, customers might alternate between periods of interaction with service reps and periods of browsing on the Internet. Thus, the full contact experience might take place over several disjoint subintervals of time. Consequently, service reps might effectively be serving several different customers at once. This paper describes some research directions related to stochastic models of contact centers, aiming to respond to these challenges. The goal is to uncover fundamental principles and develop performance analysis tools that will make it possible to improve the design and management of contact centers. We should seek conditions for resource pooling in contact centers, where the efficiency of a large single-skill center is achieved in a multi-skilled center with minimal flexibility. Staffing should be studied in each of three important time scales: real-time, shortterm and long-term. Effort should be made to understand the contribution of different sources of uncertainty: model uncertainty, parameter uncertainty and process uncertainty. Simulation should be used as a tool and should be the subject of study: Effort should be made to determine the required simulation runlengths for call-center simulations. Effort should be made to investigate operational realtime simulations by conducting simulations with nested simulations. Finally, an effort should be made to integrate research and education by making contact centers a context focus in courses on stochastic models and simulation.