Harlan, LydiaBuxton, KristinHayden, Gabrielle2025-02-172025-02-172024https://hdl.handle.net/1794/3040110 pages, Appendix A - 8 pagesA trio of personnel at University of Oregon Libraries explored options for automating a pathway to ingest, store, and visualize cost per use data for continuing resources. This paper presents a pipeline for using Alma, SUSHI, COUNTER5, Python, and Power BI to create a tool for data-driven decision making. By establishing this pipeline, we shift the time investment from manually harvesting usage statistics to interpreting the data and sharing it with stakeholders. The resulting visualizations and collected data will assist in making informed, collaborative decisions.en-USCreative Commons BY-NC-ND 4.0-USPower BIAlma AnalyticsPythonOther0000-0001-6957-19420000-0002-1693-70390000-0003-4740-4187