An improvement selection methodology for key performance indicators

Andrew J. Collins (), Patrick Hester, Barry Ezell and John Horst
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Andrew J. Collins: Old Dominion University
Patrick Hester: Old Dominion University
Barry Ezell: Old Dominion University
John Horst: National Institute for Standards and Technology (NIST)

Environment Systems and Decisions, 2016, vol. 36, issue 2, 196-208

Abstract: Abstract Key performance indicators (KPIs) are critical measures for determining the health of a manufacturing plant in relationship to the plant’s goals. In today’s competitive environment, manufacturers cannot be careless about their business; in fact, they must ensure that their KPIs are effective and use them to make improvements when necessary. This paper describes a method for suggesting improvements to a manufacturer’s KPIs, based on the results achieved from a workshop to score the KPI on a number of predefined criteria. The approach uses a prospect theory approach to weight the scoring. Different problem formulations were derived that allow for both recommendations for improvements and the recommendations for disinvestments to over-performing KPIs. The authors applied the developed approach to two workshop outputs, each from independent manufacturers, and the results highlighted the significant difference between the two manufacturers in terms of improvement priorities and KPI assessment. The optimal improvement suggestions were compared to those found through a fast heuristic. It was determined that given the underlying assumptions of the approach that the heuristic solutions were just as adequate as the optimal ones.

Keywords: Key performance indicators (KPI); Manufacturing; Performance improvement; Heuristics (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10669-016-9591-8

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