In today’s data driven cost estimating environment, it is critical to understand the impact of design and systems engineering decisions on cost. It is also important to leverage actual cost data in developing data-driven Cost Estimating Relationships (CERs) that relate engineering design and performance parameters to cost. Critical in today’s environment to have the ability to conduct sensitivity analysis on not only the CER, but on the entire system estimated to understand the full impact on Measures of Effectiveness and Measures of Performance. This paper discusses a methodology of how data driven cost estimating relationships (CERs) are incorporated into a parametric cost model. Using a satellite example we will discuss how to create libraries of data-driven CERs for future projects. These CERs are “white box” and auditable both in terms of the trend line equation and underlying data points. In addition to developing data-driven CERs, engineers also need the ability to visualize the sensitivity of the CERs to changes in design and performance parameters. Using new interfaces between systems engineering and cost estimating tools, this presentation will demonstrate how sensitivity analysis for custom developed CERs can easily be generated.