Using population matrix modeling to predict AEGIS Fire Controlmen community structure

Abstract

As the USN transitions through its personnel draw down, the need for enlisted communities to manage their manpower resources effectively will increase. The clicheÌ , "do more with less," can be applied to the USN requirement to continue to fulfill its mission obligations with fewer personnel. One community in particular has received Navy leadership's interest; the AEGIS FC community is currently experiencing problems in meeting their sea duty requirements. Part of effective manpower resource management is predicting the future manpower structure. A Population Matrix with Markov properties was used to develop the AEGIS FC aging model. The goal of this model was to provide an accurate predication of the future AEGIS FC community structure based upon variables. The thesis demonstrates that there are several problems inherent in the AEGIS FC aging model. The model was accurate when predicting in the aggregate but failed to predict the AEGIS FC community structure based on years of service.