The following steps provide a high-level view of the model-building process, from determining the model's goals to distributing the finished model. If you're new to model building, use this procedure as a guide for organizing your thoughts and getting started with model building.
Tip: For detailed information on most of these steps look at the "Learning to Write" chapters in An Introduction to Systems Thinking by Barry Richmond.
Define the purpose of your model, the problem you're trying to solve, or the story you're trying to tell.
Write your purpose statement down on paper and check back during the model building process to make sure that your model addresses your initial purpose.
Determine the model boundary.
Decide what needs to be in the model, what can or should be left out, and how detailed your model needs to be. Specify what the units of time for the model should be (Years, Months, Days, Second) when it should start and when it should finish. Look back at your model goal(s) in step 1, and make sure that your plan includes the variables and features that support your goals.
Map the model.
Identify the key variables in your model. You can think of this as determining the "main chain", a sequence of stocks connected by flows that provides the "backbone" of the model. Another way to start is to identify the stock you consider to be the closest to the heart of the issue you're modeling, and then add an inflow and an outflow to that stock. Then you can build on to those flows and stocks. In the end, you want to account for all the stocks, flows, and converters required to model your original goal(s), and make sure all feedback loops are closed.
Place the key variables in your model. In Model view, assign equations and numerical values to the variables.
Test the model.
Run the model and look for errors, anomalous values, strange or implausible behavior, etc. Fix problems you identify, then re-run the model. Continue testing and fixing until you're satisfied that your model is running correctly.
Add text, images, graphs, or tables.
Add elements to help explain your model and make it easier to understand.
Let other people use the model and learn with it. The more you can engage people in thinking about the model and the modeling process, the more impact you'll be able to have on their behavior, and on solving the problem you started with.