Creating and sharing knowledge for telecommunications

On Predicting a Call Center's Workload: A Discretization-based Approach

Matias, L. ; Nunes, RN ; Ferreira, M. ; João Mendes-Moreira, JMM ; Gama, J.G.

On Predicting a Call Center's Workload: A Discretization-based Approach, Proc International Symposium on Methodologies for Intelligent Systems - ISMIS, Roskilde, Denmark, Vol. 1, pp. 548 - 553, July, 2014.

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Abstract
Agent scheduling in call centers is a major management
problem as the optimal ratio between service quality and costs is hardly
achieved. In the literature, regression and time series analysis methods
have been used to address this problem by predicting the future arrival
counts. In this paper, we propose to discretize these target variables into
finite intervals. By reducing its domain length, the goal is to accurately
mine the demand peaks as these are the main cause for abandoned calls.
This was done by employing multi-class classification. This approach
was tested on a real-world dataset acquired through a taxi dispatching
call center. The results demonstrate that this framework can accurately
reduce the number of abandoned calls, while maintaining a reasonable
staff-based cost.