Grounded in the concept of organizational demography, the authors investigate various demographic, precollege, and socioeconomic student-level attributes that universities readily house, and use them to create customized early warning tools to advance students' academic success. Upon a review of prior studies of sociodemographic influences in higher education, the authors examine two facets of academic success--student performance and retention--and create a decision support model for each. Such data-driven early warning tools are immediately useful in undergraduate business education and can help university staff, administrators, and faculty make customized decisions regarding data-driven support strategies for improving key student outcomes.