Using fuzzy logic to characterize uncertainty during the design and use stages of performance measurement

Abstract

The process of performance measurement encompasses the activities required for data collection (use stage), which was previously designed (design stage) and contribute to decision-making after data analysis (analysis stage). The lack of quality of performance measures (PMs) may influence decision-making. Since the process of performance measurement involves generally several actors, the decisionmaker may not be aware of the level of uncertainty associated with performance measures. In this paper, fuzzy sets are used to represent the uncertainty generated in performance measures during its design, use and analysis stages. The uncertainty sources are arranged on three cause–and-effect diagrams representing controllable factors that can lead to imperfect design, use and analysis, impacting on PMs uncertainty. This degree of imperfection will be labelled deficiency (at a given stage) and a methodology is presented to infer its effect on the PM uncertainty. The identification of uncertainty sources and the determination of an Uncertainty Index support actions to improve performance measures’ quality. An application example is provided to show the usefulness of the proposed methodology.