Dow Chemical Co.: Big Data in Manufacturing
In 2012, a pilot study undertaken by the data services team of the Dow Chemical Company in the polymer division of the multinational company’s Midland, Michigan, plant had revealed an uncanny trend on the company’s shop floor. Plant engineers were working for the data; the data was not working for them. The data services director saw an opportunity to reverse the trend through the deployment of big data capabilities and, more specifically, enterprise manufacturing intelligence (EMI), a subset of big data. How should he gain user acceptance of the proposed EMI?
Collection: Ivey Business School (Canada)
Ref: IVEY-9B17E014-E
Format: PDF
Number of pages: 12
Publication Date: Nov 17, 2017
Language: English
Review date: Nov 17, 2017
What material is included in this case:
Description
In 2012, a pilot study undertaken by the data services team of the Dow Chemical Company in the polymer division of the multinational company’s Midland, Michigan, plant had revealed an uncanny trend on the company’s shop floor. Plant engineers were working for the data; the data was not working for them. The data services director saw an opportunity to reverse the trend through the deployment of big data capabilities and, more specifically, enterprise manufacturing intelligence (EMI), a subset of big data. How should he gain user acceptance of the proposed EMI?
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Year: 2012
Geographic Setting: United States
Industry Setting: Manufacturing;
Learning Objective
The case can be used in undergraduate, graduate, and executive education programs focused on information systems. The case gives students the opportunity to do the following: ·Describe the main characteristics of big data. ·Explain how big data analytics can add value to a firm’s manufacturing operations. ·Discuss the challenges faced by an in-house data analytics division in fulfilling its strategic mission.
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"Dow Chemical Co.: Big Data in Manufacturing"
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