Optimal Talent Management of the Acquisition Workforce in Response to COVID-19: Dynamic Programming Approach

Abstract

As the economic impact of the COVID-19 pandemic lingers, with the speed of recovery still uncertain, the state of the civilian labor market will impact the public sector. Specifically, the relatively stable and insulated jobs in the Department of Defense (DoD) are expected to be perceived as more attractive for the near future. This implies changes in DoD worker quit behavior that present both a challenge and an opportunity for the DoD leadership in retaining high-quality, experienced talent. The authors use a unique panel dataset of DoD civilian acquisition workers and a dynamic programming approach to simulate the impact of the pandemic on employee retention rates under a variety of recovery scenarios. Their findings posit that workers will choose not to leave the DoD while the civilian sector suffers from the impact of the pandemic. This allows leadership to more easily retain experienced workers. However, once the civilian sector has recovered enough, these same workers quit at an accelerated rate, making gains in talent only temporary. These results imply that while the DoD can take short-run advantage of negative shocks to the civilian sector to retain and attract high-quality employees, long-run retention will be achieved through more fundamental reforms to personnel policy that make DoD jobs more attractive, no matter the state of the civilian labor market.