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Published in: Information Systems and e-Business Management 2/2012

01-06-2012 | Original Article

MetricM: a modeling method in support of the reflective design and use of performance measurement systems

Authors: Stefan Strecker, Ulrich Frank, David Heise, Heiko Kattenstroth

Published in: Information Systems and e-Business Management | Issue 2/2012

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Abstract

Performance indicators play a key role in management practice. The existence of a coherent and consistent set of performance indicators is widely regarded as a prerequisite to making informed decisions in line with set objectives of the firm. Designing such a system of performance indicators requires a profound understanding of the relations between financial and non-financial metrics, organizational goals, aspired decision scenarios, and the relevant organizational context—including subtleties resulting from implicit assumptions and hidden agendas potentially leading to dysfunctional consequences connected with the ill-informed use of performance indicators. In this paper, we investigate whether a domain-specific modeling method can address requirements essential to the reflective design of performance measurement systems, and which structural and procedural features such a method entails. The research follows a design research process in which we describe a research artifact, and evaluate it to assess whether it meets intended goals and domain requirements. In the paper, we specify design goals, requirements and assumptions underlying the method construction, discuss the structural specification of the method and its design rationale, and provide an initial method evaluation. The results indicate that the modeling method satisfies the requirements of the performance measurement domain, and that such a method contributes to the reflective definition and interpretation of performance measurement systems.

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Footnotes
1
In line with Lebas and Euske (2007, 128), “[w]e prefer the word ‘indicator’ to the more traditional one of ‘measure’. A measure often implies precision; it is usually well-defined, and in similar circumstances its numerical value should be the same. An indicator may be less precise, but meaningful; indicators tend to allow for more timely and sensitive signals”. The term “measure” rather than “indicator” is common in performance measurement literature (Kaplan and Norton 1992; Neely et al. 1997; Bourne et al. 2005). The latter underlines that a numerical representation is deliberately chosen—according to some rule—to indicate the state of some entity that is being evaluated (Nagel 1931; Smith Stevens 1959). Managers often refer to “Key Performance Indicators” (KPI) suggesting a deliberate selection from among a wide range of conceivable performance indicators for a specific scope (Hope 2007). Also note the different connotations of the term “measure” when used as a verb or noun. “Measure” as a noun has a meaning of “an official action that is done in order to achieve a particular aim” (Oxford Advanced Learner’s Dictionary, 7th edition) which complicates interpretation in the context of our study. Hence, for the sake of terminological clarity, we prefer to strictly distinguish between actions leading to some outcome and indicators designed to measure some feature of an outcome. Thus, performance indicator system and performance measurement system will be used interchangeably.
 
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Metadata
Title
MetricM: a modeling method in support of the reflective design and use of performance measurement systems
Authors
Stefan Strecker
Ulrich Frank
David Heise
Heiko Kattenstroth
Publication date
01-06-2012
Publisher
Springer-Verlag
Published in
Information Systems and e-Business Management / Issue 2/2012
Print ISSN: 1617-9846
Electronic ISSN: 1617-9854
DOI
https://doi.org/10.1007/s10257-011-0172-6

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