Academic libraries lend their materials to users at borrowing institutions via Interlibrary Loan (ILL), which is based on a complex network of institutions connected via a lending string. These networks may be regionally, geographically, or academic-conference based, but are they the most efficient networks for getting materials to users? How might the information gleaned via GIS be harnessed to improve ILL networks of academic institutions by reducing time and waste? With users needing their materials as soon as possible and with institutions facing ever-rising shipping costs, could a reconsideration of ILL through the lens of GIS provide more efficiency? / This presentation explores the lending outputs within the state for a period of 5 years to discover trends across this period to better understand and anticipate lending activities. By visually demonstrating the 5-year lending trends to other institutions within the state, the academic library in this presentation demonstrates the lending trends that helped form their revisions to ILL-lending within the state. Following the lead of this presentation, other academic libraries might use GIS to better understand their ILL lending within the state, region, or nation to increase their ability to make data-driven decisions about their ILL lending practices to decrease wait time for the user and save money and library employees’ time.