Date of this Version
Journal of the American Statistical Association
A call center is a service network in which agents provide telephone-based services. Customers that seek these services are delayed in tele-queues.
This paper summarizes an analysis of a unique record of call center operations. The data comprise a complete operational history of a small banking call center, call by call, over a full year. Taking the perspective of queueing theory, we decompose the service process into three fundamental components: arrivals, customer patience, and service durations. Each component involves different basic mathematical structures and requires a different style of statistical analysis. Some of the key empirical results are sketched, along with descriptions of the varied techniques required.
Several statistical techniques are developed for analysis of the basic components. One of these is a test that a point process is a Poisson process. Another involves estimation of the mean function in a nonparametric regression with lognormal errors. A new graphical technique is introduced for nonparametric hazard rate estimation with censored data. Models are developed and implemented for forecasting of Poisson arrival rates.
We then survey how the characteristics deduced from the statistical analyses form the building blocks for theoretically interesting and practically useful mathematical models for call center operations.
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the American Statistical Association on 31 Dec 2011, available online: http://wwww.tandfonline.com/10.1198/016214504000001808.
abandonment, arrivals, call center, censored data, Erlang-A, Erlang-C, human patience, inhomogeneous poisson process, Khintchine-Pollaczek formula, lognormal distribution, multiserver queue, prediction of poisson rates, queuing science, queuing theory, service time
Brown, L. D., Gans, N., Mandelbaum, A., Sakov, A., Shen, H., Zeltyn, S., & Zhao, L. (2005). Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective. Journal of the American Statistical Association, 100 (469), 36-50. http://dx.doi.org/10.1198/016214504000001808
Date Posted: 27 November 2017