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Pooling strategies for call center agent cross-training

Author

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  • Eylem Tekin
  • Wallace Hopp
  • Mark Van Oyen

Abstract

The efficiency benefits achievable via cross-training in call and service center environments where agents serve distinct customer types are investigated. This is achieved by first considering specialized agents grouped into N departments according to the customer type they serve. Then, cross-training policies that pool a set of departments into a single larger department that serves all of the pooled call types according to either a first-come-first-served or non-pre-emptive priority service discipline are examined. The impact of system parameters, such as the number of servers, mean service times and service time coefficient of variation, on the decision of which departments to pool in order to minimize the expected delay in the system are characterized by comparing the proposed queueing models via standard queueing approximations and numerical analysis. The results show that if the mean service times of the departments that will be pooled are similar, pooling the departments with the highest service time coefficient of variation reduces the expected delay the most. Sufficient conditions for the mean service times to be considered similar are also provided.[Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following supplemental resource: Appendix of proofs for all results developed in the paper]

Suggested Citation

  • Eylem Tekin & Wallace Hopp & Mark Van Oyen, 2009. "Pooling strategies for call center agent cross-training," IISE Transactions, Taylor & Francis Journals, vol. 41(6), pages 546-561.
    • Handle: RePEc:taf:uiiexx:v:41:y:2009:i:6:p:546-561
    DOI: 10.1080/07408170802512586
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    Cited by:

    1. Zhou, Liping & Geng, Na & Jiang, Zhibin & Wang, Xiuxian, 2017. "Combining revenue and equity in capacity allocation of imaging facilities," European Journal of Operational Research, Elsevier, vol. 256(2), pages 619-628.
    2. E. Morozov & B. Steyaert, 2013. "Stability analysis of a two-station cascade queueing network," Annals of Operations Research, Springer, vol. 202(1), pages 135-160, January.
    3. Tanja Mlinar & Philippe Chevalier, 2016. "Pooling heterogeneous products for manufacturing environments," 4OR, Springer, vol. 14(2), pages 173-200, June.
    4. MLINAR, Tanja B. & CHEVALIER, Philippe, 2013. "Pooling in manufacturing: do opposites attract?," LIDAM Discussion Papers CORE 2013040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Hans Corsten & Ferdinand Becker & Hagen Salewski, 2020. "Integrating truck and workforce scheduling in a cross-dock: analysis of different workforce coordination policies," Journal of Business Economics, Springer, vol. 90(2), pages 207-237, March.
    6. Dipankar Bose & A. K. Chatterjee, 2015. "Specialized versus Multi-skilled Workforce: A Newsboy Approach for Call Centre Resource Planning," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 40(3-4), pages 252-267, August.
    7. Paulo B. Goes & Noyan Ilk & Mingfeng Lin & J. Leon Zhao, 2018. "When More Is Less: Field Evidence on Unintended Consequences of Multitasking," Management Science, INFORMS, vol. 64(7), pages 3033-3054, July.
    8. Legros, Benjamin & Jouini, Oualid & Dallery, Yves, 2015. "A flexible architecture for call centers with skill-based routing," International Journal of Production Economics, Elsevier, vol. 159(C), pages 192-207.
    9. Nilay Tanık Argon & Sigrún Andradóttir, 2017. "Pooling in tandem queueing networks with non-collaborative servers," Queueing Systems: Theory and Applications, Springer, vol. 87(3), pages 345-377, December.
    10. Arie Harel, 2011. "Convexity Results for the Erlang Delay and Loss Formulae When the Server Utilization Is Held Constant," Operations Research, INFORMS, vol. 59(6), pages 1420-1426, December.
    11. Soroush Saghafian & Wallace J. Hopp & Mark P. Van Oyen & Jeffrey S. Desmond & Steven L. Kronick, 2012. "Patient Streaming as a Mechanism for Improving Responsiveness in Emergency Departments," Operations Research, INFORMS, vol. 60(5), pages 1080-1097, October.

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