Time Evolution Analysis and Forecast of Key Performance Indicators in a Balanced Scorecard

ABSTRACT This paper offers a generic and rational construction of Balanced Scorecard. The construction involves implementing a time-managed approach to identify the evolution of the main contributors to the current company’s strategy as well as their behavior in the future organizational performance. After the optimal structure of the model is generated employing financial and non-financial strategic indicators collected from the organization, the study puts forward a realistic analysis of the evolution in time of the performance metrics. This analysis is based on the Partial Least Square equations behind the Balanced Scorecard proposed methodology, statistically comparable to the Structural Equation Modeling. Using historical data in the final model, an accurate prediction of the performance indicators can be achieved in the Balanced Scorecard tool as the approach establishes a stable cause-and-effect sequence. Under certain statistical assumptions, this allows forecasting the effects of future strategic decisions. Although the paper proposes a generic methodology, applicable to any organization, both public or private, commercial or non-profit, this technique is applied, reinforced and validated with a practical example from a public-owned Swiss electricity company.