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Data Set: 187 Weeks of Customer Forecasts and Orders for Microprocessors from Intel Corporation

Author

Listed:
  • Matthew P. Manary

    (Data Center Group, Intel Corporation, Hillsboro, Oregon 97124)

  • Sean P. Willems

    (Haslam College of Business, University of Tennessee, Knoxville, Tennessee 37996)

Abstract

Problem definition : This data set contains 187 consecutive weeks of Intel microprocessor demand information for all five distribution centers in one of its five sales geographies. For every stock keeping unit (SKU) at every location, the weekly forecasted demand and actual customer orders are provided as well as the SKU’s average selling price category. These data are provided by week and by distribution center, producing 26,114 records in total. Academic/practical relevance : The 86 SKUs in the data set span five product generations. It provides years of product evolution across generations and price points. Methodology : As a data set paper, its purpose is to provide interesting and rich real-world data for researchers developing forecasting, inventory, pricing, and product assortment models. Results : The data set demonstrates the presence of significant forecast bias, heterogeneity of forecast errors between distribution centers, generational differences, product life cycles, and pricing dynamics. Managerial implications : This data set provides access to a rich pricing and sales setting from a major corporation that has not been made available before.

Suggested Citation

  • Matthew P. Manary & Sean P. Willems, 2022. "Data Set: 187 Weeks of Customer Forecasts and Orders for Microprocessors from Intel Corporation," Manufacturing & Service Operations Management, INFORMS, vol. 24(1), pages 682-689, January.
  • Handle: RePEc:inm:ormsom:v:24:y:2022:i:1:p:682-689
    DOI: 10.1287/msom.2020.0933
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    References listed on IDEAS

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    1. Matthew P. Manary & Sean P. Willems & Alison F. Shihata, 2009. "Correcting Heterogeneous and Biased Forecast Error at Intel for Supply Chain Optimization," Interfaces, INFORMS, vol. 39(5), pages 415-427, October.
    2. Matthew P. Manary & Brian Wieland & Sean P. Willems & Karl G. Kempf, 2019. "Analytics Makes Inventory Planning a Lights-Out Activity at Intel Corporation," Interfaces, INFORMS, vol. 49(1), pages 52-63, January.
    3. Jason Acimovic & Francisco Erize & Kejia Hu & Douglas J. Thomas & Jan A. Van Mieghem, 2019. "Product Life Cycle Data Set: Raw and Cleaned Data of Weekly Orders for Personal Computers," Service Science, INFORMS, vol. 21(1), pages 171-176, January.
    4. Matthew P. Manary & Sean P. Willems, 2008. "Setting Safety-Stock Targets at Intel in the Presence of Forecast Bias," Interfaces, INFORMS, vol. 38(2), pages 112-122, April.
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    Cited by:

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