Identifying temporal relationships within multidimensional performance measurement

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.

Keywords

• performance measurement
• multidimensional models
• leading and lagging variables
• temporal causality
• strategy maps
• structural equation modelling