Improving Navy MPTE Studies with Model-Driven Big Data
Lucas, Thomas W.
Sanchez, Susan M.
MetadataShow full item record
The goal of this research was to improve upon the ability of OPNAV N1 analysts to quickly and efficiently obtain experiment-based information from their computational models. The enhanced information will enable N1’s analysts to better support Navy leadership in resource and policy decisions that shape the future Navy and help it retain and develop its most talented Sailors. This project built on previous collaborations with N1 using data farming to enhance the information gleaned from their Navy talent management models, such as the Officer Strategic Analysis Model (OSAM) model, the Production Resource Optimization (PRO) model, and the Navy Total Force Strength Model (NTFSM). During this research period, (1) Ensign William Desousa (2015) investigated the behavior of economic inputs in NTFSM; (2) Lieutenant Peter Bazalaki (2016) used the new data farming capabilities we developed in OSAM to investigate Surface Warfare Officer (SWO) inventory across a breadth of possibilities; and (3) Lieutenant Allison Hogarth (2016) built, tested, and demonstrated a user interface in Excel that enables users of the PRO model to automatically execute a sophisticated design of experiments—the tool that enables this new capability is known as Production Resource Optimization Model With Experimental Design (PROMWED). In addition to working with the student-officers, the faculty supporting this project performed an empirical study of statistical software packages that may provide better understanding of the high-dimensional behavior of manpower models in the future (Erickson, Ankenman, & Sanchez 2016).
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
NPS Report NumberNPS-N16-N154-A