A systemic methodology for the reduction of complexity of the balanced scorecard in the manufacturing environment

Abstract

The main objective of this paper is to develop and validate a methodology to select the most important key performance indicators from the balanced scorecard. The methodology uses and validates the implicit systemic hypothesis in the balanced scorecard model, together with a qualitative and statistical analysis. It helps to determine a small set of indicators that summarizes the company’s performance. The method was tested using actual data of 3 complete years of a multinational manufacturing company’s balanced scorecard. The results showed that the scorecard can be summarized in six metrics, one for each dimension, from an initial scorecard composed of 90 indicators. In addition to reducing complexity, the method tackles the hitherto unresolved issues of the analysis of the trade-offs between different dimensions and the lagged effects between metrics.

Keywords

• balanced scorecard (bsc)
• strategy/policy deployment
• lagged time series
• key performance indicators (kpis)
• operating system (os)
• dynamic principal component analysis (dipca)
• correlation analysis