Efficient extraction and processing of large datasets can enable meta-analyses that reveal hidden patterns and trends. Recognizing that Organic Letters is committed to delivering high-quality Supporting Information, we initiated an analysis of over 3,000 SI PDFs from the journal. To foster a discussion on how to further improve data quality, Table summarizes a screening of all SI PDFs from 2023 and 2024 (issues 1-36), comprising 3,028 files and totaling 26.3 GB of data. All calculations were performed on a personal computer, with no need for any data to leave the device. On a laptop computer (EliteBook 840 G8, Intel i5 @ 2.4 GHz), scanning a single SI PDF takes less than a second and checking a whole volume of Organic Letters SI PDFs takes about 15 min. The script demonstrated a high accuracy rate (>99%), successfully identifying HRMS data in over 95% of the analyzed files. The remaining <5% largely comprised files that lacked HRMS data altogether (e.g., those related to computational studies).