Intelligent Procedures for Intra-Day Updating of Call Center Agent Schedules

• 成果类型: Article
• 署名作者: Mehrotra, Vijay; Ozluk, Ozguer; Saltzman, Robert
• 署名单位: University of San Francisco; California State University System; San Francisco State University
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.3401/poms.1080.01097
• 发表日期: 2010
• 页码: 353-367
• 关键词: call center operations; doubly stochastic processes; workforce scheduling; integer programming; real-time optimization

摘要

For nearly all call centers, agent schedules are typically created several days or weeks before the time that agents report to work. After schedules are created, call center resource managers receive additional information that can affect forecasted workload and resource availability. In particular, there is significant evidence, both among practitioners and in the research literature, suggesting that actual call arrival volumes early in a scheduling period (typically an individual day or week) can provide valuable information about the call arrival pattern later in the same scheduling period. In this paper, we develop a flexible and powerful heuristic framework for managers to make intra-day resource adjustment decisions that take into account updated call forecasts, updated agent requirements, existing agent schedules, agents' schedule flexibility, and associated incremental labor costs. We demonstrate the value of this methodology in managing the trade-off between labor costs and service levels to best meet variable rates of demand for service, using data from an actual call center.