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L. L. Bean Improves Call-Center Forecasting

Author

Listed:
  • Bruce H. Andrews
  • Shawn M. Cunningham

    (School of Business, University of Southern Maine, 96 Falmouth Street, Portland, Maine 04103)

Abstract

We developed and implemented two forecasting models for use at L. L. Bean, Inc., a widely known retailer of high-quality outdoor 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. We 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 our models is estimated to save $300,000 annually through enhanced scheduling efficiency.

Suggested Citation

  • Bruce H. Andrews & Shawn M. Cunningham, 1995. "L. L. Bean Improves Call-Center Forecasting," Interfaces, INFORMS, vol. 25(6), pages 1-13, December.
    • Handle: RePEc:inm:orinte:v:25:y:1995:i:6:p:1-13
    DOI: 10.1287/inte.25.6.1
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    Citations

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    Cited by:

    1. Vijay Mehrotra & Thomas A. Grossman, 2009. "OR Process Skills Transform an Out-of-Control Call Center into a Strategic Asset," Interfaces, INFORMS, vol. 39(4), pages 346-352, August.
    2. Theresa Maria Rausch & Tobias Albrecht & Daniel Baier, 2022. "Beyond the beaten paths of forecasting call center arrivals: on the use of dynamic harmonic regression with predictor variables," Journal of Business Economics, Springer, vol. 92(4), pages 675-706, May.
    3. Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2011. "Forecast evaluation in call centers: combined forecasts, flexible loss functions and economic criteria," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    4. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
    5. Ibrahim, Rouba & Ye, Han & L’Ecuyer, Pierre & Shen, Haipeng, 2016. "Modeling and forecasting call center arrivals: A literature survey and a case study," International Journal of Forecasting, Elsevier, vol. 32(3), pages 865-874.
    6. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Noah Gans & Ger Koole & Avishai Mandelbaum, 2003. "Telephone Call Centers: Tutorial, Review, and Research Prospects," Manufacturing & Service Operations Management, INFORMS, vol. 5(2), pages 79-141, September.
    8. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    9. Landon, Joshua & Ruggeri, Fabrizio & Soyer, Refik & Murat Tarimcilar, M., 2010. "Modeling latent sources in call center arrival data," European Journal of Operational Research, Elsevier, vol. 204(3), pages 597-603, August.
    10. Ding, S. & Koole, G. & van der Mei, R.D., 2015. "On the estimation of the true demand in call centers with redials and reconnects," European Journal of Operational Research, Elsevier, vol. 246(1), pages 250-262.
    11. Robbins, Thomas R. & Harrison, Terry P., 2010. "A stochastic programming model for scheduling call centers with global Service Level Agreements," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1608-1619, December.
    12. Rouba Ibrahim & Pierre L'Ecuyer, 2013. "Forecasting Call Center Arrivals: Fixed-Effects, Mixed-Effects, and Bivariate Models," Manufacturing & Service Operations Management, INFORMS, vol. 15(1), pages 72-85, May.
    13. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    14. Albrecht, Tobias & Rausch, Theresa Maria & Derra, Nicholas Daniel, 2021. "Call me maybe: Methods and practical implementation of artificial intelligence in call center arrivals’ forecasting," Journal of Business Research, Elsevier, vol. 123(C), pages 267-278.
    15. Barrow, Devon & Kourentzes, Nikolaos, 2018. "The impact of special days in call arrivals forecasting: A neural network approach to modelling special days," European Journal of Operational Research, Elsevier, vol. 264(3), pages 967-977.
    16. Refik Soyer & M. Murat Tarimcilar, 2008. "Modeling and Analysis of Call Center Arrival Data: A Bayesian Approach," Management Science, INFORMS, vol. 54(2), pages 266-278, February.
    17. Haipeng Shen & Jianhua Z. Huang, 2008. "Interday Forecasting and Intraday Updating of Call Center Arrivals," Manufacturing & Service Operations Management, INFORMS, vol. 10(3), pages 391-410, July.
    18. Prakash Mirchandani & G. G. Hegde & Richard E. Wendell, 2001. "Enhancing Competitiveness of the Customer Loan Center at Promistar Financial Corporation," Interfaces, INFORMS, vol. 31(3), pages 28-43, June.
    19. Nabil Channouf & Pierre L’Ecuyer & Armann Ingolfsson & Athanassios Avramidis, 2007. "The application of forecasting techniques to modeling emergency medical system calls in Calgary, Alberta," Health Care Management Science, Springer, vol. 10(1), pages 25-45, February.

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