The previous work related to eigenvalue analysis in the system dynamics field, focused on linking the 
model structure to the modes of behavior -- i.e. the eigenvalues.  While the system eigenvalues define 
the characteristics of the system’s behavior modes (e.g., exponential growth, expanding oscillations), 
these behavior modes are not equally represented in all model variables, making it difficult to link the 
behavior of the reference mode to the behavior of a particular variable.  In this study we propose an 
alternative perspective and explicitly explore the significance that each behavior mode has on the 
system state variables.  We achieve this by decomposing the behavior of a variable into a sum of the 
weighted reference modes in the system (represented by the eigenvalues).  We argue that focusing on 
the weights, rather than on the eigenvalues, is a more efficient way to develop policy recommendations 
and compute the elasticity of the weights to the gain on any link the model allowing for a more efficient 
and discriminate way to identify policies.  A routine to estimate the weights of any linear model and 
compute the elasticity of those weights to model links is developed and made available at http://
iops.tamu.edu/faculty/roliva/research/sd/.