Relevance Assumed: A Case Study of Balanced Scorecard Development Using System Dynamics

Abstract

The balanced scorecard (BSC) has become a popular concept for performance measurement. It focuses attention of management on only a few performance measures and bridges different functional areas as it includes both financial and non-financial measures. However, doubts frequently arise regarding the quality of the BSCs developed as well as the quality of the process in which this development takes place. This article describes a case study in which system dynamics (SD) modelling and simulation was used to overcome both kinds of problems. In a two-stage modelling process (qualitative causal loop diagramming followed by quantitative simulation), a BSC was developed for management of one organizational unit of a leading Dutch insurer. This research illustrates how, through their involvement in this development process, management came to understand that seemingly contradictory goals such as customer satisfaction, employee satisfaction and employee productivity were, in fact, better seen as mutually reinforcing. Also, analysis of the SD model showed how, contrary to ex ante management intuition, performance would first have to drop further before significant improvements could be realized. Finally, the quantitative modelling process also helped to evaluate several improvement initiatives that were under consideration at the time, proving some of them to have unclear benefits, others to be very promising indeed.

A dynamic sustainability Balanced Scorecard methodology as a navigator for exploring the dynamics and complexity of corporate sustainability strategy

“…What is more, Neely, Gregory, and Platts (2005) point out that managers can easily identify performance measures but impediments arise when they are asked to choose the most suitable ones, which accurately illustrate the corporate performance. Although this problem is usual during the planning phase of BSC, when managers have to translate a firm's strategy into a limited Kaplan and Norton 1996), the BSC literature does not provide an explicit guideline for indicator selection and mechanisms to test their relevance and validity over time (Akkermans and van Oorschot 2005;Bianchi and Montemaggiore 2008;Hudson, Smart, and Bourne 2001). Third, there is an insufficient description of cause and effect relationships.…”

“…Third, there is an insufficient description of cause and effect relationships. Particularly, BSC presents the cause and effect relationships as a unidirectional causality instead of multidirectional relationships among different BSC's perspectives (Akkermans and van Oorschot 2005;Norreklit 2000). In addition, the causality relationships are built in an open-loop logic totally ignoring possible feedback loops (Bianchi and Montemaggiore 2008).…”

“…Steramn (2000) pointed out that SD separates the causes and effects in time which is a successful way to solve the time dimension problem. Using the SD modelling approach, all time lags that exist in causality relationships of BSC are identified and their effects can be calculated over time (Akkermans and van Oorschot 2005;Nielsen and Nielsen 2008).…”

“…Thereby cause and effect relationships, measures, and time delays are continuously tested for their congruency. As a result, managers can be more confident that they have selected the most appropriate measures, which concisely capture the corporate performance (Akkermans and van Oorschot 2005;Barnabè 2011;Schoeneborn 2003).…”

“…Such shortcomings basically refer to the inability of BSC to take into account the dynamic and complex aspects of the firms' environments that influence the execution of their strategies (Barnabè 2011; Bianchi and Montemaggiore 2008;Capelo and Dias 2009;Norreklit 2000). To deal with these limitations, many authors propose system dynamics (SD) as an appropriate methodology that overcomes BSC deficiencies (Akkermans and van Oorschot 2005;Nielsen and Nielsen 2008;Wolstenholme 1998). Particularly, they believe that a dynamic BSC approach is an effective method that facilitates the decision-making process and the assessment of strategic actions by offering managers and decision-makers the ability to test their different strategic hypothesis and scenarios (Barnabè 2011;Bianchi and Montemaggiore 2008;Nielsen and Nielsen 2008;Schoeneborn 2003).…”