  The link between structure and behavior is central to System Dynamics, but
effective tools for understanding that relationship still elude us. The current
state of the art in the field of loop dominance analysis relies on either
practitioner intuition and experience or complex algorithmic manipulation in
the form of eigenvalue analysis or pathway participation metrics. This paper
presents a new and distinct method to find the 'loops that matter' in
generating model behavior. This is a numeric method capable of determining the
impact for every loop in a model and identifying which dominate behavior at
each point in time. The method was inspired by observations on variable value
changes during simulations and has been refined using empirical evaluation on a
variety of different models. In addition to explaining behavior, the method
shows promise for improving visualization and aggregation of simulation
results.
