Retention Analysis Modeling for the Acquisition Workforce II

Abstract

To support the modern warfighters tasked with increasing demands in a constantly changing global environment, it is imperative that the defense acquisition system continue to evolve to maintain its capability and flexibility. In this effort, growing a talented, experienced, and well-qualified civilian workforce will be vital. As part of this broad effort, the Section 809 Panel has recommended change to the DoD’s career management framework to grow and augment the workforce, and the DoD AWF Strategic Plan — FY 2016 – FY 2021 has emphasized efforts since 2010 to restore and restructure the AWF after a period of twenty years of shrinkage. This technical research report is the second in a proposed series of three linked studies to provide a cutting-edge modeling and simulation tool that leverages the increase in availability of AWF data and the large increases in computing power in the last decades. Building on the proof-of-concept model created as part of the first-year effort, we continue our development of a “Dynamic Retention Model (DRM)” designed from the ground-up for the AWF. Using a large personnel dataset of the acquisition workforce as well as a representative dataset of the civilian population from the Bureau of Labor Statistics, we estimate our DRM. DRM is a leading-edge technique that uses a powerful mathematical/econometric technique called dynamic programming. It takes a complex, multi-period problem (such as the lifetime labor market decisions of an acquisition worker) and breaks it down into simpler, one-period sub-problems in a recursive manner. Solving a single-period problem “nests” the future decisions that the worker will make, allowing the estimation and prediction of complex behavior in a surprisingly manageable framework. With estimates from the model, we simulate how various modifications in personnel policies, such as changes in salary structure and bonuses, would have affected the labor market decisions of the workforce. In particular, our model takes into account civilian positions the AWF may move into upon the decision to separate from DoD, allowing a more accurate prediction of the impact of monetary personnel policies, which must be evaluated in relation to what the worker could realistically earn in the civilian sector. In doing so, the model can help the AWF leadership in achieving the desired workforce size and structure. We conclude this report by expanding on possible extensions to enrich the model to provide yet more accurate estimation and richer simulations, including evaluating the potential impact of COVID-19 on the long-run career trajectory of the workforce.