Analytics and Simulation for Decision Support: Good Results Achieved by Teaming the Two

In this article, a new adaptable mission analysis and decisions system (AMADS) that couples data analytics with DES to support decision making for multiple, broad mission areas is presented. This article also introduces a new approach for deriving the probability of success for courses of action taken within these mission areas that extends analytics into the time domain by applying Bayesian statistics within DES. This approach allows for random sampling of the input probability distributions and, through iterative computation, provides Monte Carlo analysis with which to derive confidence intervals for probabilities.