1 Department of Economics and Business Economics, Aarhus BSS, Aarhus University2 Pressalit A/S Denmark3 Siemens Wind Power A/S Denmark4 Department of Economics and Business Economics, Aarhus BSS, Aarhus University
This paper focuses on how system dynamics modelling can contribute to an increased understanding of business, which is necessarily to identify those variables that are strongest in relation to supporting the company's strategy execution through the use of the Balanced Scorecard. Strategic planning, operational execution, feedback and learning are some of the most important key features of any performance measurement model (Argyris, 1976; Kaplan and Norton, 1996; Otley, 1999; Warren, 2005). By combining BSC with systems thinking as developed by Forrester in 1958, the present paper aims to address not only the conceptual domain concept of “comprehensiveness” related to BSC, i.e. the scope’ (learning) and ‘differentiation’ (system dynamics causality and feedback), but also the methodological domain concept of ‘precision’ (solution by differential equations). By using the "soft" parts of the system dynamics (SD) when setting themes, objectives and key performance indicators, a company can - at a very early stage in the process - begin to improve and develop its business acumen and understanding of how the company's balanced scorecard must be designed according to the strategy to be executed through the tool. SD-modelling tools in this phase are: the subsystem diagram, boundary chart and CLD (closed loop diagram). The output is CLD, containing the key performance indicators and variables that are central to the company's strategy. The next step is then to use the stock & flow idea, ending up with a CLD. The final step is then to move on to the quantitative phase, using dynamics and formulas to design the BSC. The results from our case company show that a company may achieve great business sense and value of the qualitative phase alone, because using SDM application in practice demands a lot of time with the quantitative phase.
System dynamics, case, close sloop diagram, performance, and simulation