Drill sergeant selection model

This research aims to strengthen the current utility of the Warrior Attributes Inventory (WAI), formerly known as the Non Commissioned Officer Leadership Skills Inventory (NLSI). The end state of the research is to create a model that will accurately predict potential drill sergeant performance based upon WAI scores and biographical data. The research leverages statistical learning methods and the United States Military Academy Department of Systems Engineering’s Systems Decision Process (SDP). The use of the SDP created a drill sergeant performance measurement, since none previously existed. Statistical learning determined the best function approximation that relates the WAI and biographical data to drill sergeant performance. Statistical learning methods include: Multiple Linear Regression, Neural Networks, Regression Trees, and Classification Methods. In previous research, the WAI was mapped only with recruiter effectiveness. Because of the inherent negative perceptions of serving as a recruiter, soldiers intentionally skewed the results of their WAI testing in order to avoid duty as a recruiter. By adding a pairing to drill sergeant service, which soldiers view as a positive career move, both models will become more effective. The implementation of this model will allow the United States Army Human Resource Command (HRC) to place the right soldiers in the position which best accommodates their inherent skill set. This will both increase job satisfaction for the soldier and effectiveness within the Army as a whole.