Presents a case for the dynamic retention model to be used to affect workforce management policies.

This report discusses the dynamic retention model (DRM), “a state-of-the-art modeling capability that supports decisionmaking about workforce management policy” (p.iii). The DRM is a statistical model that has primarily been used to support military compensation decisions; however, as the authors of this report discuss, the model can be used in workforce contexts to predict various compensation and personnel policies.

The research in this report addresses the model’s previous gaps, and “extends the DRM to allow simulations of the effects of alternative policies both in the steady state and in the transition to the steady state. It also shows the effects of alternative implementation strategies and how different policies can affect how quickly the population and costs move toward the new steady state” (p.iii).

“The research should be of interest not only to the research community concerned with models to support workforce management but also to decisionmakers concerned about how to assess the short- and long-term effects of workforce management policies” (p.iii).

(Abstractor: Author and Website Staff)

Full Publication Title: A New Tool for Assessing Workforce Management Policies Over Time: Extending the Dynamic Retention Model

Major Findings & Recommendations

“The transition modeling presented in this report has major advantages over other approaches that are commonly used to assess the retention effects of different policies in the transition period. The DRM models behavior with a dynamic program, and the model is structured so all relevant information about the individual’s history is summed up in the state variables, namely, active years of service, Reserve years, total years, and status (AC, RC, civilian). Further, the model allows individuals to differ in their tastes for active and Reserve service, and the model assumes the individual is buffeted by shocks that can affect the decision. The model’s structure leads to an expression for the probability in each year that the individual will take a certain action given the current state, e.g., stay in the AC, leave and become a pure civilian, or leave and join the Reserve” (p.59). “The DRM approach is logically consistent with rational behavior over time and handles decisionmaking under uncertainty in an attractive way by allowing people to change their decisions over time as uncertainty is resolved and new information becomes available to them. By extending the DRM to the transition period, we are now able to extend the advantages of the DRM to the transition period as well. As mentioned at the outset, this allows the analysis to consider policies aimed at facilitating the transition to a new force size and shape, policies of a long-term nature such as changes to the basic pay table or the retirement benefit structure, and the total and year-by-year cost of a policy change that might involve both short- and long-term features” (p.60). (Abstractor: Author)