Scheduling of agents in inbound multilingual call centers

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DOI:

https://doi.org/10.14488/BJOPM.2017.v14.n2.a11

Keywords:

Planning, Allocation, Call Centers, Scheduling, Skill-Based Routing, Integer Programming.

Abstract

This paper presents an Integer Linear Programming model, which enables the scheduling of agents in call centers according to segmentation by skills, as well as the inclusion of labor law restrictions. The results from the experimental application of this method to situations involving real-time problems are presented, wherein the necessary shifts to meet forecasted demand are provided, in addition to an economically optimum combination of agents and skills, generating a solution, which is sufficient to maintain the desired level of service at the lowest cost possible. The approach proposed in this study presents an alternative worthy of consideration, since it is able to successfully incorporate the flexibility of call centers with skills-based routing in an easy-to-implement model that has proven to be effective in experiments conducted in on-the-job settings. Advances in information technology and telecommunications in recent years have increasingly heightened the presence of call centers in the day-to-day of companies and their customers. Call center management should endeavor to achieve a balance between technical performance and economic performance (labour costs, equipment, trunks and rates). It is estimated that 70% of the operating costs of call centers are currently related to labor costs. This paper provides research on how to significantly reduce personnel-related operational costs without negatively affecting the quality of the service.

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Author Biographies

Luiz Henrique Santanna Barbosa

Universidade Federal Fluminense

Maria Cecilia C. Chaves

Universidade Federal do Rio de Janeiro

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Published

2017-07-23

How to Cite

Barbosa, L. H. S., Gomes, C. F. S., & Chaves, M. C. C. (2017). Scheduling of agents in inbound multilingual call centers. Brazilian Journal of Operations & Production Management, 14(2), 228–238. https://doi.org/10.14488/BJOPM.2017.v14.n2.a11

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