Thinking well in the social sciences and about public policy
System dynamics differs in two important ways from common practice in the social sciences and government. Other approaches assume that the major difficulty in understanding systems lies in shortage of information and data. Once data is collected, people have felt confident in interpreting the implications. I differ on both of these attitudes. The problem is not shortage of data but rather inability to perceive the consequences of information we already possess. The system dynamics approach starts with concepts and information on which people are already acting. Generally, available information about system structure and decision-making policies is sufficient. Available information is assembled into a computer model that can show behavioral consequences of well-known parts of a system. Generally, behavior is different from what people have assumed. (p. 6)
How Small System Dynamics Models Can Help the Policy Process, a relatively new article by Navid Ghaffarzadegan, John Lyneis, and George Richardson, seems to offer ways to get feedback thinking usefully into deliberations on important issues. It builds on his earlier Concept Models. If you'd like to see how these ideas fit into the longer history of social science, read his excellent Feedback Thought in Social Science and Systems Theory,
Often we feel obligated to persuade others of our processes before showing results. While that may be important sometimes, I think just diving in, if done well, can sometimes be more productive. For a public example, see Making musical sense by email: the table of contents.
What has your experience been?