Modeling & Simulation (Systems, Agents, Discrete Events)

Much of the art of system dynamics modeling is discovering and representing the feedback processes, which, along with stock and flow structures, time delays, and nonlinearities, determine the dynamics of a system.
All systems, no matter how complex, consist of networks of positive and negative feedbacks, and all dynamics arise from the interaction of these loops with one another. Positive feedback denotes a self-reinforcing process, and negative feedback denotes a self-correcting one. Though there are only two types of feedback loop, models may easily contain thousands of loops, of both types, coupled to one another with multiple time delays, nonlinearities, and accumulations. Dynamics of all systems arise from the interactions of these networks of feedbacks.

When intuition fails (when multiple loops interact), we usually turn to computer simulation to deduce the behavior of our models. (For isolated loops, intuition or mental models will mostly work). In system dynamics, the term “mental model” includes our beliefs about the networks of causes and effects that describe how a system operates, along with the boundary of the model (which variables are included and which are excluded) and the time horizon we consider relevant-ur framing or articulation of a problem.
A central principle of system dynamics is to examine issues from multiple perspectives; to expand the boundaries of our mental models to consider the long-term con.sequences and “side effects” of our actions, including their environmental, cultural, and moral implications.

Guidelines for Systems Modeling

1) Develop a model to solve a particular problem, not to model the system
2) Modeling should be integrated into a project from the beginning
3) Be skeptical about the value of modeling and force the “why do we need it” discussion at the start of the project
4) System dynamics does not stand alone. Use other tools and methods as appropriate.
5) Focus on implementation from the start of the project
6) Modeling works best as an iterative process of joint inquiry between client and consultant
7) Avoid black box modeling
8) Validation is a continuous process of testing and building confidence in the model
9) Get a preliminary model working as soon as possible. Add detail only as necessary.
10) A broad model boundary is more important than a great deal of detail
11) Use expert modelers, not novices
12) Implementation does not end with a single project