Inspired by the 2017 Big Ten Academic Alliance Collective Collection Conference, the presenters undertook a research study to better understand the consortium’s resource sharing needs for Spanish and Portuguese materials published in Latin America and to develop data-informed models for cooperative collection development of these publications. Using ILLiad custom request searches, Access queries, Python scripts, Google’s Language Detection Library, and WorldCat API, the presenters gathered and analyzed interlibrary loan and collections holdings data from the 15 members of the Big Ten Academic Alliance’s Library Initiatives. Given these libraries’ high volume of ILL requests and large collection sizes, it was imperative to employ various technologies to expedite analysis and reconcile data from different sources, making this project an excellent case study for exploring how to work with consortial data. In addition to presenting the study’s methodology and key findings, we hope this presentation encourages deeper analysis of consortial resource sharing, inspires greater cooperation in collecting for area studies, and helps libraries build distinctive collections to support consortial and national resource sharing.