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

Global Journal of Business Research, v. 7 (2) pp. 9-27, 2013

20 Pages Posted: 29 Jan 2013

See all articles by Bernard Morard

Bernard Morard

HEC, University of Geneva

Alexandru Stancu

University of Geneva and IATA

Christophe Jeannette

University of Geneva

Date Written: 2013

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.

Keywords: Balanced Scorecard, Key Performance Indicators, Performance Measurement, Structural Equation Modeling (SEM), Partial Least Squares (PLS), Principal Component Analysis (PCA), Public Organization, Energy Industry, Energetic Sector

JEL Classification: G39, M19, M40, L32

Suggested Citation

Morard, Bernard and Stancu, Alexandru and Jeannette, Christophe, Time Evolution Analysis and Forecast of Key Performance Indicators in a Balanced Scorecard (2013). Global Journal of Business Research, v. 7 (2) pp. 9-27, 2013, Available at SSRN: https://ssrn.com/abstract=2147983

Bernard Morard (Contact Author)

HEC, University of Geneva ( email )

40 Boulevard du Pont d'Arve
Geneva 4, Geneva 1211
Switzerland

Alexandru Stancu

University of Geneva and IATA ( email )

33, Route de l'Aeroport
PO Box 416
Geneva, 1215
Switzerland

Christophe Jeannette

University of Geneva ( email )

102 Bd Carl-Vogt
Genève, CH - 1205
Switzerland

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