Abstract
The paper investigates temporal relationships between leading drivers of success, non-financial outputs, and financial outcomes as suggested by the Balanced Scorecard. Based on a sample of 42 companies with a four-year survey data, we find partial confirmation of temporal causality between selected actions and performance. The effects of the leading variables on the non-financial outputs are the strongest in the same year. Also, the influence of innovation and HR policies via the number of patented innovations and new products (services) on profit growth is the strongest within one year. These findings have important implications for the design of cause-and-effect relationships schemes (strategy maps) and the development of contemporary performance measurement systems.
Highlights
After about two decades of their presentation in the literature, the effectiveness of contemporary multidimensional models of performance measurement such as the Balanced Scorecard still hasn’t been conclusively established
One of the most compelling research questions is related to the identification of temporal relationships between actions and performance implicitly suggested by these models
To what extent can organizations be confident that investments in learning and growth, for example, will impact innovations in internal processes and product development which will, in turn, attract new customers or lead to customer loyalty and, further, to financial performance? The multidimensionality of PMS suggests that there is a sequence of drivers that lead to results in a certain period of time
Summary
After about two decades of their presentation in the literature, the effectiveness of contemporary multidimensional models of performance measurement such as the Balanced Scorecard still hasn’t been conclusively established. One of the most compelling research questions is related to the identification of temporal relationships between actions and performance implicitly suggested by these models. To what extent can organizations be confident that investments in learning and growth, for example, will impact innovations in internal processes and product development which will, in turn, attract new customers or lead to customer loyalty and, further, to financial performance? The multidimensionality of PMS suggests that there is a sequence of drivers that lead to results in a certain period of time. The cause-and-effect relationships between leading and lagging performance measures are dependent upon time. There has been little research that would incorporate time dimension into the investigation of the effectiveness of multidimensional performance measurement.
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