Lessons Learned from a Company Dealing with Big Data
D. Antony Tarvin (),
Levente Sipeki (),
Alexandra M. Newman () and
Amanda S. Hering ()
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D. Antony Tarvin: Operations Research with Engineering PhD Program, Colorado School of Mines, Golden, Colorado 80401
Levente Sipeki: Department of Mechanical Engineering, Colorado School of Mines, Golden, Colorado 80401
Alexandra M. Newman: Department of Mechanical Engineering, Colorado School of Mines, Golden, Colorado 80401
Amanda S. Hering: Department of Statistical Science, Baylor University, Waco, Texas 76712
Interfaces, 2018, vol. 48, issue 2, 147-155
Abstract:
The concept of big data has caught the attention of business leaders. However, there is still widespread confusion in industry as to how to treat such data. We describe one such encounter with big data from an industrial parts supplier who was concerned with unexpected variability in its prices. Unable to discern trends in the data, a point of contact for the supplier worked with us to explore this concern. Analysis showed that customers at different branches of the company were experiencing significantly different levels of price variation, and that some customers within a specific branch were being offered products at widely varying prices, which were apparently uncorrelated with the quantity of products purchased. Such behaviors are unacceptable to end customers, and rectification of these behaviors has led to increased customer satisfaction for this company. Furthermore, we were able to demonstrate general methodologies to help the company with future analyses.
Keywords: big data; analytics; industry; computer programming (search for similar items in EconPapers)
Date: 2018
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https://doi.org/10.1287/inte.2017.0890 (application/pdf)
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:48:y:2018:i:2:p:147-155
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