There are a lot of reasons to create system simulation models. Many efforts start by simply wanting to understand what is causing some situation to develop; or, just the desire to understand how things work. In these cases a simulation model becomes a rich and transparent cause-and-effect hypothesis. Now, let me observe that having a solid understanding of how your business (or whatever you are exploring) works, its driving structure, and the baseline values of its parameters is a basic and broadly useful result in and of itself. One that is surprisingly rare.
However, in this "what have you done for me lately" world, inevitably, the "so what?" question comes up. As in, "So you have a simulation model . . . so what?" Because, as soon as a basis for system understanding has been established, we want to improve, control, change, the system. We want to make insightful resource allocation decisions. So, as I've discussed many times in this blog, it's usually not enough to build a system model simply to know how things work -- we need to think about how to harness it to do useful work.
This is trickier than it might first appear. Commonly, the initial approach runs along the classical scientific reductionist line: "Now that we have a model that predicts the future we simply act in accordance with that insight." This is so common it has a name: The predict-and-act decision framework.
In a very real sense, however, system models don't predict the future. They describe the cause-and-effect physics that connect our actions with assumptions about the future that lie outside our control. They describe the rules that allow us to "shape" but not dictate the future.
As the saying goes, this is not a bug, it's a feature. Because, shocking as it might appear, good decision making does not require that we predict the future. Good decision making requires that we understand the implications of our actions. System modeling is a practical way to differentiate the implications of our decisions from uncertain factors that are out of the sphere of our influence. And by doing so we gain deep insight into both.
Working with my clients I've created a visualization that helps them put their system model to use in a decision making environment. I call it an "Outcome Map". I've drawn heavily on work from "Real Options" and "Robust Decision Making" and married it to system simulation. Take a look at this Prezi to learn more.
Some Prezi Hints: After you fire up the Prezi, use the "more" menu to switch to full screen mode. Advance the presentation using the "next" arrow at the bottom. After seeing the presentation explore the canvas using the pan (left click and drag) and zoom (scroll wheel).