Higher-education retention efforts are being urged to move from reactive detection to proactive identification of dropout signals, as the reasons students leave often surface long before formal withdrawal appears. A new analysis centered on Noodle and Genio’s “Churning Point” reporting cites costly attrition patterns, including higher first-year loss shares and large per-dropout tuition and fee impacts. The reporting argues that early-alert systems still skew toward academic triggers, even though many “Potential Completers” stop out for non-academic reasons and re-enroll at much higher rates—suggesting institutions need administrative and behavioral indicators earlier, not just GPA and missed-assignment flags.