Evaluating the Productive Efficiency of Dynamical Systems

Engineering managers are typically concerned with the assessment and improvement of system performance. In the literature, analytical approaches have been proposed not only for the purpose of computing and estimating performance measures, but also for linking these performance measures to performance improvement strategies. In reality, organizational and/or system efficiency performance is dynamic, nonlinear in its relationship to key production drivers, and a function of multiple/complex interactions and feedback mechanisms. This paper introduces a methodological approach that combines the system dynamics (SDs) modeling paradigm with the concepts taken from the measurement of productive efficiency so as to evaluate dynamical systems. In this research, the SD paradigm is coupled with the fundamental assumptions of production theory in order to evaluate productive efficiency performance. As a result, a structure within the SD model is introduced that computes efficiency performance scores based on a hill-climbing optimization procedure. The structure is illustrated using an electric utility example described by Kopp, 1981, where constrained optimization results are not only replicated but also the path to achieve optimal dynamic system performance is found. An example is provided as to how this structure can be used to facilitate policy decisions within a technology management environment where investments are made in new technologies.