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Forecasting sales in the supply chain: Consumer analytics in the big data era

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  • Boone, Tonya
  • Ganeshan, Ram
  • Jain, Aditya
  • Sanders, Nada R.

Abstract

Forecasts have traditionally served as the basis for planning and executing supply chain activities. Forecasts drive supply chain decisions, and they have become critically important due to increasing customer expectations, shortening lead times, and the need to manage scarce resources. Over the last ten years, advances in technology and data collection systems have resulted in the generation of huge volumes of data on a wide variety of topics and at great speed. This paper reviews the impact that this explosion of data is having on product forecasting and how it is improving it. While much of this review will focus on time series data, we will also explore how such data can be used to obtain insights into consumer behavior, and the impact of such data on organizational forecasting.

Suggested Citation

  • Boone, Tonya & Ganeshan, Ram & Jain, Aditya & Sanders, Nada R., 2019. "Forecasting sales in the supply chain: Consumer analytics in the big data era," International Journal of Forecasting, Elsevier, vol. 35(1), pages 170-180.
    • Handle: RePEc:eee:intfor:v:35:y:2019:i:1:p:170-180
    DOI: 10.1016/j.ijforecast.2018.09.003
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