Article

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

Global Journal of Business Research 7(2).

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.

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Available from: Alexandru Stancu, Jan 05, 2016
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    • "Furthermore, the relations between criteria are not clearly explained and, finally, the causal relationships are problematic (more like interdependence, rather than correlations). Lastly, Malina & Selto [11] asserts that the BSC is very difficult to put into practice. The authors underline several negative aspects of the BSC and present significant controversy between the organization and its stakeholders. "
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    ABSTRACT: This paper compares two Balanced Scorecard models, an optimal construction based on a time-managed approach to identify the evolution of the key contributors to the current organization’s strategy and a model based on Kaplan and Norton methodology. Both Balanced Scorecards are generated using financial and non-financial strategic indicators collected directly from the company. The paper proposes a process to construct an optimal structure of a Balanced Scorecard model based on the Partial Least Square equations. The optimal model is based on a modified version of bootstrap technique that seeks and chooses the most predictable cause-and-effect sequence among all possible combinations. The Kaplan’s model is grounded on the authors’ methodology as presented in their articles and books. The comparison between the two models will be analyzed and validated using a practical example from a Swiss medical establishment. It will be concluded that the Optimal Balanced Scorecard (OBSC) is superior to the Kaplan’s model in terms of statistical validation and, thus, OBSC advantage to accurately represent and study the company’s strategy
    Full-text · Article · May 2015
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    ABSTRACT: Two earlier articles (http://ssrn.com/abstract=2368919 and http://ssrn.com/abstract=2463978) have explored the benefits of applying the process perspective to explore the underlying mechanisms that cause the consequences of adopting the BSC to vary across organizations and the understanding derived from a survey of users of BSC in India. The second article had, however, only addressed the issues of 'how' and 'why' of the effectiveness of BSC. The research objective was to also explore the 'how to' aspects of improving the effectiveness of BSC. This article elaborates on these aspects by exploring in greater details the different relationships between the different Constructs (the Latent Variables) and the Measures (the Manifest Variables). These relationships are explored through the application of Multiple Regression Analysis and Structural Equation Modeling on the data set. For reasons explained in the article, the SEM approach applied is the PLS-SEM and not the CBSEM.The SEM analysis shows that significant relationships are found between the Antecedents and the Orientation, Design, Use and BSC Effectiveness. There is no significant relationship of any of the Process constructs with any of the constructs of Consequences. This tends to establish the conclusion that the perceived benefits of adopting the BSC do not seem to emanate from any of the processes involved but from the Antecedent factors, particularly Management Style and Ownership. In the MRA outcome, there is a significant relationship of only Implementation with the constructs of the Consequences. Each Construct is analyzed further to bring out the specific ‘how to’ factors which could help to improve the effectiveness of the BSC. Overall, it is felt that it is the processes leading to neglect of Motivation and Consultants, lack of attention to causality amongst the Measures used, unwillingness to incorporate inputs from BSC in Incentive Schemes and the neglect of National Culture that are some of the reasons for such an outcome. It is felt that these arise out of political behaviors of the actors involved and could be handled through better internal communication. This outcome leads to the conclusion that the adoption of BSC (in India at least) could be seen as another example of poor strategic implementation, particularly if it is accepted that the decision to adopt the BSC is a strategic decision. It is suggested that organizations need to pay proper attention to not only implementation of their strategies but also implementation of their strategic performance measurement system.
    Full-text · Article · Jan 2014 · SSRN Electronic Journal
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    ABSTRACT: Purpose ‐ The development and empirical verification of the balanced scorecard (BSC) model are key parts of the research of a case study on the performance measurement system (PMS) of the Ydria Motors LL Company (YM). The paper aims to discuss these issues. Design/methodology/approach ‐ The research was performed as a single case study of modelling the BSC for the manufacturing company and founded on complementary use of qualitative and quantitative methods. The central part of the case study is an empirically evaluated layout of the BSC with the Engle-Granger two-step method. Findings ‐ The results and findings from empirical analysis showed that the methods used are appropriate for inclusion in the methodological approach as they are complementary. Therefore, it can be asserted that the introduction of quantitative methods of continuous data analysis for the implementation of the BSC improved the established approach. In this research, an approach that represents the basis for further work in the field of research in PMSs of companies, with the use of econometric tools, was empirically tested and developed. Research limitations/implications ‐ The generalization of research findings is limited to only one manufacturing company. With the continuation of the research on other case studies, the preliminary lessons learned can be expanded to other organizations. Originality/value ‐ Following the research findings, it can be established that the methodology used provides support to organization's decision-making process in real-time and can be used with different strategies scenarios and forecast simulations and thus supports the prioritization of strategic initiatives. In addition, the developed model allows the integration and testing of various performance indicators and the identification and selection of the most appropriate KPIs.
    No preview · Article · Mar 2014 · Industrial Management & Data Systems
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