Data-driven decision making is a critical leadership skill. This study describes how leadership at a four-year university used extant data to improve student outcomes. The University identified the high rate of first-time-in-college (FTIC) student withdrawal/failure in initial algebra courses as having a detrimental effect on other student success metrics such as student retention and completion rates. The study was initiated to determine how analysis of extant student data could enable leaders to better understand the problem, identify ways in which university policies and/or practices could be modified to increase students' pass rates in their initial math courses, and ultimately result in improved student outcomes. Data from four cohorts of first time in college students were analyzed to better understand the effects of the university placement practices on student outcomes, and potentially identify students who may be at-risk of failure to provide early intervention. The initial results indicate under-placement of female students in lower math courses at a statistically significant level, and potential use of students' high school GPA as an early-warning indicator of failure. The study highlights the importance of leaders monitoring and analyzing local data to assess the impact of current policies and practices on student outcomes.