Product life cycle data set: Raw and cleaned data of weekly orders for personal computers

Jason Acimovic, Francisco Erize, Kejia Hu, Douglas J. Thomas, Jan A. Van Mieghem

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


We provide and describe a data set of N 8,935 weekly, normalized customer orders over the entire product life cycle for 170 Dell computer products sold in North America over a three and a half year period, from 2013–2016. Total orders for these products exceeded four million units and well over one billion dollars in revenue. While Dell is historically known for fulfilling customer demand with a build-to-order approach, the products in this data set were designated as build-to-stock products. There are three elements in the data that, depending on the research application, researchers may want to identify or mitigate. First, some products have seemingly anomalous orders representing one-time purchases from large customers. Second, there are negative values for some products representing order cancellations. Third, end-of-life sales may be significantly influenced by management action. We present approaches for cleaning the data to address these issues.

Original languageEnglish (US)
Pages (from-to)171-176
Number of pages6
JournalManufacturing and Service Operations Management
Issue number1
StatePublished - 2019

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research


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