Models for incoming calls forecasting in a customer attention center

Abstract

Telephone customers attention centers (CAC) are complex systems. In order to provide the best service to clients with minimum costs a careful scheduling of human resources (agents) is needed.

Call centers often receive thousands of incoming calls. A large data base of services is in many cases available for modelling. Such data has been used in different ways to improve the quality of service. In this particular case, the schedule of attention staff a week in advance.

In this paper the number of incoming calls in the hour is modelled using autoregressive models, both linear and nonlinear (neural networks). As it turns out, the most important part of the modelling procedure is the selection of appropriate input variables.