Statistical Analysis of a Telephone Call Center

Loading...
Thumbnail Image
Penn collection
Operations, Information and Decisions Papers
Degree type
Discipline
Subject
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
queueing science
queueing theory
service time
Other Physical Sciences and Mathematics
Other Social and Behavioral Sciences
Sales and Merchandising
Theory and Algorithms
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Brown, Lawrence D
Gans, Noah
Mandelbaum, Avishai
Sakov, Anat
Shen, Haipeng
Zeltyn, Sergey
Zhao, Linda
Contributor
Abstract

A call center is a service network in which agents provide telephone-based services. Customers who seek these services are delayed in tele-queues. This article 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 techniques 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. Finally, the article surveys how the characteristics deduced from the statistical analyses form the building blocks for theoretically interesting and practically useful mathematical models for call center operations.

Advisor
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Publication date
2005-01-01
Journal title
Journal of the American Statistical Association
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Recommended citation
Collection