L.L. Bean improves call-center forecasting

The authors developed and implemented two forecasting models for use at L.L. Bean, Inc., a widely known retailer of high-quality out-door goods and apparel. The models forecast calls incoming to L.L. Bean’s call center so that efficient staffing schedules for telephone agents can be produced two weeks in advance. The authors used the ARIMA/transfer function methodology to model these time series data since they exhibit seasonal patterns but are strongly influenced by independent variables, including holiday and advertising interventions. The improved precision of the present models is estimated to save $300,000 annually through enhanced scheduling efficiency.