Call Center Arrivals: When to Jointly Forecast Multiple Streams?

Han Ye, James Luedtke, Haipeng Shen

Research output: Contribution to journalArticlepeer-review

Abstract

We consider call centers that have multiple (potentially inter-dependent) demand arrival streams. Workforce management of such labor intensive service systems starts with forecasting future arrival demand. We investigate the question of whether and when to jointly forecast future arrivals of the multiple streams. We first develop a general statistical model to simultaneously forecast multi-stream arrival rates. The model takes into account three types of inter-stream dependence. We then show with analytical and simulation studies how the forecasting benefits of the multi-stream forecasting model vary by the type, direction, and strength of inter-stream dependence. In particular, we find that it is beneficial to simultaneously forecast multi-stream arrivals (instead of separately forecasting each stream), when there exists inter-stream lag dependence among daily arrival rates. Empirical studies, using two real call center datasets further demonstrate our findings, and provide operational insights into how one chooses forecasting models for multi-stream arrivals.

Original languageEnglish (US)
Pages (from-to)27-42
Number of pages16
JournalProduction and Operations Management
Volume28
Issue number1
DOIs
StatePublished - Jan 2019

Keywords

  • arrival process
  • lag dependence
  • vector time series
  • workforce management

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Management of Technology and Innovation

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