Ford was tasked with determining the best sourcing footprint for its $1.5 billion Automotive Components Holdings, LLC Interiors business. This extensive undertaking required a complete re-engineering of the supply footprint of 42 high-volume product lines over 26 major manufacturing processes and more than 50 potential supplier sites. We propose an approximation of the large-scale Mixed Integer Nonlinear Program (MINLP) that accurately accommodates the nonlinear nature of facility cost as a function of utilization and present an iterative Mixed Integer Program (MIP) approach to solve the underlying MINLP. We demonstrate that the resulting solution to the iterative algorithm provides an equivalent solution to the approximated MINLP. The recommendations from this work have been implemented in practice and have resulted in savings of approximately $40 million in upfront investment over the previously preferred alternative.