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The Effects of Customer Misclassification on Cross-Training in Call Centers

In: Operations Research Proceedings 2013

Author

Listed:
  • Andreas Schwab

    (Julius-Maximilians-Universität Würzburg)

  • Burak Büke

    (The University of Edinburgh)

Abstract

The benefits of cross-training in terms of increasing responsiveness to demand fluctuations have been studied extensively in the literature. In this work, we study another important advantage of cross-training due to customer misclassification, i.e. a caller declares to face a certain problem (e.g. a hardware problem) where in fact another problem persists (e.g. a software problem). In call centers that apply no cross-training, misclassified calls need to be rerouted to agents who are able to serve the true problem, whereas cross-training enables agents to serve different problem types which reduces cycle times. We introduce two-type queueing models to study the effects of customer misclassification on cross-training in call centers. We observe that, if only a third of the agents is cross-trained, high increases in model performance can be confirmed, whereas little benefit is added by higher amounts of cross-training. We also study the effects of routing policies on cycle times.

Suggested Citation

  • Andreas Schwab & Burak Büke, 2014. "The Effects of Customer Misclassification on Cross-Training in Call Centers," Operations Research Proceedings, in: Dennis Huisman & Ilse Louwerse & Albert P.M. Wagelmans (ed.), Operations Research Proceedings 2013, edition 127, pages 429-435, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-07001-8_58
    DOI: 10.1007/978-3-319-07001-8_58
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