The industrial gravitation towards data driven improvement methods is absent from university departmental strategies. In order to apply a systems approach to department improvement, data driven quality metrics (system outputs) and controllable system inputs must be found and correlated. This paper explores these correlations in the context of highly ranked industrial and manufacturing engineering departments. Variations in the way each department operates are discussed in terms of their correlation to both currently used quality metrics and proposed data driven metrics. The conclusion is reached that a Pareto surface exists constraining the department research expenditures and peer determined U.S. News and World Report department ranking. This balance is controlled primarily by the proportion of theoretical and practical faculty members for the respective field.