The conventional and very traditional rational decision model posits a sequence like this:
Science (or information) => Process (or politics) => Decision
As anyone who works with community decision making knows, the world doesn’t really work that way (even when the legal structure, say a NEPA process, tries to make it do so). A more enlightened model might posit a bit more back-and-forth:
Science => Process => Science => Process => Science => Process => Decision
The next incremental step towards building a model that actually reflects how these processes unfold might acknowledge that politics typically (always?) actually comes before the science. The science or information gathering isn’t abstracted from the real world in which it operates; while it might respond to politics in complex ways, the science/information gathering/analysis element always responds to politics. One simple representation might be just to add “politics” before the science in our model.
Politics => Science => Process => Science => Process => Science => Process => Decision
But none of these models really work all that well because they presume that these processes are fundamentally linear (even when they repeat sequences). The problem is that decision processes aren’t really linear even when we pretend they are. As such, they aren’t really mappable in any simple way, especially – in our view – because of the way politics shapes, frames, intercedes, reacts, and otherwise influences how any decision process unfolds. Our representational challenge, then, is to figure out how to convey the complexity of a typical decision process, and the importance of politics within that process, without drawing something that’s just indecipherable.