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

Matthew P. Manary, S. Willems
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引用次数: 4

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.
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数据集:187周的客户预测和英特尔公司的微处理器订单
问题定义:该数据集包含了Intel在其五个销售区域之一的所有五个配送中心的连续187周的微处理器需求信息。对于每个地点的每个库存单位(SKU),提供每周预测需求和实际客户订单以及SKU的平均销售价格类别。这些数据按周、按配送中心提供,共产生26114条记录。学术/实践相关性:数据集中的86个sku跨越了5代产品。它提供了跨越世代和价格点的多年产品演变。方法:作为一篇数据集论文,其目的是为研究人员开发预测、库存、定价和产品分类模型提供有趣和丰富的真实世界数据。结果:数据集显示存在显著的预测偏差,分布中心之间的预测误差异质性,代际差异,产品生命周期和定价动态。管理含义:该数据集提供了对大型公司丰富的定价和销售设置的访问,这是以前无法获得的。
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