Management control and the Balanced Scorecard: An empirical test of causal relations

This dissertation tests the descriptive validity of the Balanced Scorecard (BSC) as a causal model of leading and lagging indicators of non-financial and financial performance. A review of prior studies investigating this implied causal relation finds mixed empirical support. These findings contrast with the professional literature that gives the implied relation nearly unqualified support. This project examines the causal relations among measures of a BSC at a large, international manufacturing company with interview and archival data obtained from designers, administrators, and North American managers whose divisions are objects of the BSC. A causal model is constructed to statistically test the BSC using the same firm's BSC measures, which reflect non-financial and financial performance for 31 business units over twelve consecutive quarters.; Contributions of this study include the use of structural equation modeling to reflect the company's beliefs about causal relations among the chosen BSC measures, the use of time series data to capture the impact of delays between a change in a lead indicator and the subsequent effect on the lagging indicator, and the use of “real, live” BSC data instead of researcher picked publicly available BSC proxies. While statistical validity may not be required for strategic purposes, without empirical support the BSC may not be a reliable management control device.; The results of this study provide partial support for the claim that the BSC model reflects cause and effect relations underlying the company's business model. Contrary to BSC theory, this study supports heavy reliance on traditional financial measures of performance. Only one of the non-financial performance measures on the company's BSC (whole goods inventory turns) is a significant leading indicator of performance.