We have started from a number of written hypotheses and developed a model that has helped us to explore some of these hypotheses in a unified framework. This technique has a major advantage of focusing attention on policy issues from the start and also forces a continuity between the model and the way different people think about the problem. This is very helpful. One of the biggest problems in implementing model results is explaining the results in terms that the people implementing them can relate to. By continually relating a model to hypotheses, this issue is addressed from the beginning and can be less daunting in the end.
At this point a warning is in order. We have built a simple conceptual model to help us think about different issues around growth in the field of System Dynamics. While the model we developed has provided insights and allowed us to explore some of the hypotheses put forward, it is not possible to draw conclusions from it.
When you get an insight from a simple model you need to stop and look around and ask yourself "is this what is happening." In some cases the answer is yes, and the model has given you a new basis for understanding reality and acting on that understanding. In this case the answer is maybe. We have seen some plausible dynamics, but done little to establish confidence that the model represents what is really happening. Unless we go further and make use of data and Reality Checks, we could end up with a model that seems plausible, but is just plain wrong.
