 |
|
|
|
|
Transforming Conditions
Anticipating Change
Previous |
Next
Instead of concentrating exclusively on what is most likely to happen (the probable future), which is the goal in most types of forecasting, system dynamics (SD) modeling supports a pragmatic, navigational view: one based on moving consciously among the larger set of trajectories that could plausibly unfold.40 This shift from the probable to the plausible is subtle, but significant. “Most organizations plan around what is most likely,” observed Clement Bezold and Trevor Hancock in an overview of the health futures field. “In so doing, they reinforce what is, even though they want something very different” (Bezold and Hancock, 1993). Furthermore, considering that Hancock is one of those most responsible for launching the worldwide Healthy Cities/Healthy Communities movement (Hancock, 1993; International Healthy Cities Foundation, 2002; Norris and Pittman, 2000), he speaks from experience when he describes the power that is often unleashed when we plan around plausible futures.
Too often our image of the future is the scenario we think will most likely happen. If we don’t like the way we think things are going, this may bring with it an awful sense that the light at the end of the tunnel is a train bearing down upon us. The probable future is something that seems to be done to us, something over which we have little or no control, and often something we don’t like very much. If health futures (as a field) focuses too much upon the probable, which it has a tendency to do (planners, be they politicians, civil servants, or private business persons, like to know what to plan for, as do ordinary people), then it runs the risk, perhaps inadvertently, of disempowering people and denying them choice....The energy and creativity released in a “preferable future” process can be quite astonishing.
(Hancock and Bezold, 1994:25).
Just as architects learn their craft by studying prototype designs in a studio before introducing (or imposing) them on the real world, so can SD modeling help us to reflect with one another on our most important values, anticipate plausible futures, and choose among them in more open and ethical way. The methods offer a rare avenue for learning and experimenting in a simulated world before rushing into the high stakes enterprise of acting in the real one. Considering how useful SD modeling can be, the next section goes into more depth about its core principles and then illustrates the technique through two examples: (1) a causal map of factors affecting outside assistance in a divided neighborhood that is challenged by multiple afflictions; and (2) a simulation model designed to explore plausible futures for diabetes prevalence in the wake of rising obesity.
40. System dynamics is one particular methodology within the larger class of simulation modeling techniques (Forrester, 1961, 1989; Sterman, 2000).
Previous |
Next Back to top
Page last reviewed: January 30, 2008
Page last modified: January 30, 2008
Content source: Division of Adult
and Community Health,
National Center for Chronic Disease Prevention and Health Promotion
|
|
