In this age of exponential growth in science, engineering, and technology, the capability to evaluate the performance, reliability, and safety of complex systems presents new challenges. Today's methodology must respond to the ever increasing demands for such evaluations to provide key information for decision and policy makers at all levels of government and industry on problems ranging from national security to space exploration. Scientific progress in integrated reliability assessment requires the development of processes, methods, and tools that combine diverse information types (e.g., experiments, computer simulations, expert knowledge) from diverse sources (e.g., scientists, engineers, business developers, technology integrators, decision-makers) to assess quantitative performance metrics that can aid decision-making under uncertainty. These are highly interdisciplinary problems. The principle role of the statistician is to bring statistical sciences thinking and application to these problems. By the nature of our training, statisticians frequently assume the role of scientific integrator, and are thus well poised to lead the development of integrated reliability assessments. However, this puts the statistician closer to policy pressures and politics. This talk will focus on the growing challenges facing statistical sciences in the domain of integrated system assessment and how we, as statisticians, must separate the scientific method from the politics of the scientific process to develop assessment methodology that will facilitate the decision making processes.