Don't get the cart before the horse: There are no shortcuts to prescriptive analytics

Jeremy Glassman, Benjamin Shao, Robert St Louis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Davenport [5] argues that the most important component for putting big data into action within an organization is talent management, and this opinion is widely shared among academics. We interviewed the chief purchasing officers (CPOs) of 15 major corporations and found that they did not feel it was problematic to find the right people for data analytics teams, and did not feel it was difficult to get resources to support data analytics efforts. Instead, they were frustrated by data issues such as granularity, accuracy, and integration. They also were intimidated by what they perceived to be the requirements for prescriptive analytics, and generally had not progressed beyond descriptive analytics. This article summarizes the roadblocks that the CPOs encountered as they attempted to move from descriptive to predictive to prescriptive analytics, and presents a set of steps which must be followed if organizations are to move up the analytics hierarchy.

Original languageEnglish (US)
Title of host publicationProceedings of the 52nd Annual Hawaii International Conference on System Sciences, HICSS 2019
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages1055-1064
Number of pages10
ISBN (Electronic)9780998133126
StatePublished - 2019
Event52nd Annual Hawaii International Conference on System Sciences, HICSS 2019 - Maui, United States
Duration: Jan 8 2019Jan 11 2019

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2019-January
ISSN (Print)1530-1605

Conference

Conference52nd Annual Hawaii International Conference on System Sciences, HICSS 2019
Country/TerritoryUnited States
CityMaui
Period1/8/191/11/19

ASJC Scopus subject areas

  • Engineering(all)

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