Structure, data, and compelling conclusions: Notes from the field

Some systems dynamics models are more effective than others in changing the thinking and actions of their audiences. In my experience, the models that prove most compelling to clients generally have two things in common: a potent stock and flow structure and a rich fabric of numerical data for calibrating that structure. Stock and flow structures focus attention on the intrinsic momentum of a situation and allow one to track movements of people and things in a clear and systematic way. Numerical data not only help to build a client's confidence in a model, but also can materially affect the final structure and key parameter values of a model. Three examples are presented that demonstrate the strong inferences one may draw when stock and flow structures are combined with sufficient numerical data. System dynamics models should be built on a foundation of straightforward core structures and the full range of available evidence.