Systems engineering practices, thought to provide cost or schedule savings to an organization, and the correlations between these identified practices and such improvements, have been historically ill quantified. The research problem addressed in this study is that these specific best practices (independent variable) remain ill defined and poorly linked to successfulness of a program (dependent variable). In answering the research questions this study identified systems engineering best practices, based on Capability Maturity Model Integrated^® (CMMI^®) guidelines, which produced statistically significant correlation values to program improvements (cost, schedule, and overall program performance), and identified those numeric correlations. Phase 1 used Kendall’s τ, and Phase 2 used Spearman rank correlation coefficient analysis techniques. The identification of such specific highly correlated best practices, provided by this research, is important to the social sciences and positive social change. For in the social sciences, such practices are vital to the effective design of programs, the efficient utilization of resources, and the resultant improvement of lives of those who live within society in general.