Improving Navy recruiting with the new Planned Resource Optimization Model with Experimental Design (PROM-WED)
Hogarth, Allison R.
MetadataShow full item record
The Navy spends over $300 million per year to recruit approximately 35,000 new active duty enlisted Sailors. The Navy has historically used a non-linear optimization model, the Planned Resource Optimization (PRO) model, to help inform decisions on the allocation of those recruiting resources. Input variables to the PRO model include economic influences and policy factors. The result is a recommended allocation of resources for advertisements, recruiters, enlistment bonuses, and education incentives. The PRO model's primary limitations are (1) potential deviations of input variables are not taken into consideration, and (2) extensive experimentation is not feasible. Realistically, input variables to the PRO model fluctuate, are unpredictable, and can interact with other variables to influence the recruiting environment and affect the optimal allocation of recruiting resources. This paper describes the Planned Resource Optimization Model with Experimental Design (PROM-WED), a tool that alleviates the limitations and enhances the analytic utility of the legacy PRO model. PROM-WED embeds the legacy PRO model within a data farming environment. PROM-WED's graphical user interface and decision support capability provide decision makers with robust insights into variable interactions and uncertainties to better inform their recruiting resourcing decisions.
Approved for public release; distribution is unlimited
Showing items related by title, author, creator and subject.
Lewis, James M. (1987-09);This thesis studies the influence of environmental factors on recruiting Category I-IIIA males for the United States Army. Econometric modeling using regression analysis is used to estimate the determinants of the supply ...
Arima, James K. (Monterey, California. Naval Postgraduate School, 1978-12); NPS-54-78-009A selective review of the literature on advertising effectiveness revealed no generalizable results for setting advertising budget decisions. The primary problem is a lack of knowledge as to how advertising, as input, ...
Peterson, Jeffery M. (Monterey, California: Naval Postgraduate School, 1990-06);Estimation of regional distributions of qualified military available (QMA) population is essential for determining an efficient allocation of recruiting resources. Estimates of regional mental ability distribution are ...