Data quality is a multi-dimensional concept and this research will explore its impact in performance measurement systems (PMSs). Despite the large numbers of publications on the design of PMSs and the definition of critical success factors to develop Performance Measures (PMs), from the data user perspective there are possibilities of finding data quality problems, that may have a negative impact in decision making. This work identifies and classifies uncertainty components of PMSs, and proposes a qualitative method for PMs' quality assessment. Fuzzy PMs are used to represent uncertainty that is present in any physical system. A method is also proposed to calculate an indicator of the compliance between a fuzzy PM and its target value, that can serve as a risk indicator for the decision-maker. © 2013 Springer Science+Business Media Dordrecht.
CITATION STYLE
De Sousa, S. D. T., Nunes, E. M. P., & Da Silva Lopes, I. (2013). Uncertainty components in performance measures. In Lecture Notes in Electrical Engineering (Vol. 229 LNEE, pp. 753–765). Springer Verlag. https://doi.org/10.1007/978-94-007-6190-2_57
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