Balance Scorecard: Beyond The Causality Principle

The present paper builds on an Action Research that combines Balance Scorecard (BSC) with the scenario simulation method (CIA-ISM) in actual context. The research is carried out with direct engagement and involvement of the organization’s management team, and its main purpose is to of find an explanation of all interdependencies related to the targets and objectives of BSC from organizations. Even if this is the main purpose of the research, we can assume two different sub-targets resulting from it and the increase of knowledge that entails. First goal aims to ensure that BSC+CIA-ISM is useful in decision-making, and the second goal intends to show that improving knowledge of the objectives decrease the uncertainty amongst them and thus, reduce its risk level. Since its birth in 1992 by Robert Kaplan and David Norton, Balanced Scorecard (BSC) has been a widely accepted and used tool in business environments in order to support assistance to management, and the achievement of the targets, by using information that goes further than a purely financial vision. Moreover, the combination of Cross-Impact Analysis and Interpretative Structure Modeling (CIA-ISM), has been successfully used to generate and to provide an accounting with regard to dynamic scenarios in high uncertainty contexts, such as emergency scenarios, risk analysis and assessment of business projects. BSC+CIA-ISM combination enables us to understand and model the existing interdependencies between the different variables that make up BSC inside the organization, and indeed to simulate the effects of partial or complete achievement of one or various variables in a dynamic way, which may also involve an improvement of the tools currently used by organizations for decision-making. Furthermore, it comprises an improvement added and the implementation of temporal biases, which provides more information to the organization. In summary, the main contributions of this paper are providing an improvement of the BSC traditional usage by combining it with the scenario-based methodology of CIA-ISM. Thus, explaining the Principle of Causality between the objectives/targets on BSC, but it also includes the improvement of decision-making, by providing a combination of different methodologies, that allows to understand and model BSC. In addition, it will also help organizations to reduce the risk situations related to strategic decisions, by using CIA-ISM to simulate different adverse situations, or the relationships between the changes and target achievements, that allow also the training of the management teams. In conclusion, the combination BSC+CIA-ISM enables us to know the internal performance of the organization and the interdependencies between its targets/objectives. Graphic representations (ISM) and simulations (CIA) have been contrasted with the same direction and thus, allowing to conclude that this BSC extent provides more and better information than the traditional method. All things considered, it supports and improves decision-making progress by minimizing the level of uncertainty and hence the risk level too.