Scalable Analysis for Customer Contact Centers

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This grant provides funding for the development of tools that help analyze the performance of customer contact centers. Customer Contact Centers are organizations or entities providing service to customers via chat-box, e-mail, phone, or other communication channels. Such centers play an increasingly dominant role in society. Customer contact centers can be of any size and appear in a variety of places. Most US companies employ moderate- or small-size call centers. For multiserver systems that model customer contact centers, the PIs propose to develop universal, scalable approximations for various performance measures such as the fraction of customers that encounter a delay. These approximations will be computationally efficient for both small and large systems, and for systems that may not necessarily be critically loaded (think of call centers for emergencies). The PIs will pay special attention to realistic model features like general service time distribution and customer abandonment, leading to the challenge of developing algorithms for high dimensional diffusion processes. The proposed research will involve a wide range of techniques like numerical solution of partial differential equations, diffusion processes, extreme value theory, large deviations and analytic techniques; many of which are new in this area.If successful, this research will result in single universal method for call center staffing that is applicable in a variety of settings. The algorithm will be implemented. The proposed software implementation provides a practical tool to allow one to study the impact of service time variability and patience time distribution on system performance. The PIs intend to make the software available to academic researchers, practitioners from industry, and university students.