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Optimal call center forecasting and staffing

Published online by Cambridge University Press:  16 February 2022

Sihan Ding  and
Ger Koole Open the ORCID record for Ger Koole [Opens in a new window]
Sihan Ding
Affiliation:
CWI, Amsterdam, Netherlands. E-mail: [email protected]
Ger Koole
Affiliation:
Vrije Universiteit Amsterdam & CCmath, Amsterdam, Netherlands. E-mail: [email protected]
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Abstract

In this paper, we consider a two-stage call center staffing model. In the first stage, the interval staffing levels are set under arrival rate uncertainty. In the second stage, these initial staffing levels are corrected to the right value based on more precise arrival rate information. We show that this problem is of newsvendor type, where the costs are the initial staffing costs plus the second stage adaptation costs. We show that we should initially staff according to a quantile of the distributional forecast, rather than the mean. It is also shown that the errors in staffing are approximately linear in the forecasting errors. This leads to the conclusion that the weighted sum of errors should be the error measurement in call center forecasting, since minimizing, it minimizes the total staffing costs. In special cases where the costs are symmetric for over- and understaffing, this is equivalent to minimizing the weighted absolute percentage error.

Keywords

applied probabilitycall centerserror measurementsforecastingstaffing
Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 36 , Issue 2 , April 2022 , pp. 254 - 263
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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