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This paper presents a case study of data-forward, system-level learning at a regional comprehensive university to better understand and support student success. Using disaggregated institutional data as an example of sensemaking (Kezar, 2013), the project challenged dominant assumptions about major selection. Students who changed majors graduated at significantly higher rates than those who did not. An emergent data story served as a boundary object for cross-functional organizational sensemaking, catalyzing collaboration across academic advising, career services, and institutional research. These efforts led to new policies, tools, and practices that support purposeful major exploration. The case illustrates how IR can foster shared inquiry and how middle leaders align data interpretation with practice and policy to advance equity through institutional change.