PurposeThe purpose of this paper is to investigate whether first level measures in the Balanced Scorecard (BSC) declaring a cause-effect relationship by design are composite indices of lower measures, and if they converge into a single factor as is traditionally accepted in the BSC literature.Design/methodology/approachThis study reports results of a quantitative case study that focusses on an Ontario (Canada) community hospital that has been using the BSC.FindingsThe results of this study challenge the cause-effect assumption of the BSC, particularly in a cascading context, and suggest that a lack of attention of how composite indices of lower measures converge into a single higher level measure may be the reason for ineffective use of the BSC.Research limitations/implicationsThe BSC is a dynamic tool; as such there are several measures that have a very short history, thus limiting the observations available to be used in statistical models.Practical implicationsA key recommendation for practice that emerges from this study is the need to test if lower level metrics do merge naturally in the upper level measure of the BSC; if not, the upper level measure might not be linked to other measures rendering the BSC ineffective in the context of causality.Originality/valueAlthough several studies have argued in favour of the cause-effect relationship of the BSC, none of those found in the literature have paid attention to the way in which first level measures are constructed. This may explain why certain measures are linked, while others are not, to those that are calculated as composite indices of several lower level indicators.
international Journal of Productivity and Performance Management – Emerald Publishing
Published: Mar 6, 2017
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