This study determines the required number of call center agents to meet service level agreements in an Allianz customer service center. A review of call center literature is presented and the respective optimization problem is formulated. Stochastic processes for call volumes, service times and customers' patience behavior are estimated from real-world data. Within the M/M/n+G model, heavy-traffic approximations in the quality-and-efficiency driven regime are used to solve the optimization problem for different service levels and to determine the agent staffing. A simulation study is performed using both random variables and real-world data in order to compare the results to the analytically obtained solutions. For the special case of bank holidays, the resulting variations in staff numbers on the following days are studied and managerial conclusions are presented.
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This study determines the required number of call center agents to meet service level agreements in an Allianz customer service center. A review of call center literature is presented and the respective optimization problem is formulated. Stochastic processes for call volumes, service times and customers' patience behavior are estimated from real-world data. Within the M/M/n+G model, heavy-traffic approximations in the quality-and-efficiency driven regime are used to solve the optimization probl...
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