Leveraging U.S. Army Administrative Data for Individual and Team Performance

Abstract

The Army possesses vast amounts of administrative (archival) data about Soldiers. These data sources include screening tests, personnel action codes, training scores, global assessments,  physical fitness scores, and more. However, the Army has yet to integrate these data to create a holistic operating picture. Our research focuses on repurposing Army administrative data to (1) operationalize social constructs of interest to the Army (e.g., Army Values, Warrior Ethos) and (2) model the predictive relationship between these constructs and individual (i.e., Soldier) and team (i.e., unit) performance and readiness. The goal of the project is to provide people analytics models to Army leadership for the purposes of optimizing human capital management decisions.

Our talk will describe the theoretical underpinnings of our human performance model, drawing on disciplines such as social and industrial/organizational psychology, as well as our experience gaining access to and working with Army administrative data sources. Access to the archival administrative data is provided through the Army Analytics Group (AAG), Person-event Data Environment (PDE). The PDE is a business intelligence platform that has two central functions: (1) to provide a secure repository for data sources on U.S. military personnel; and (2) to provide a secure collaborative work environment where researchers can access unclassified but sensitive military data.

While the nFORM administrative data system is used to collect operations and performance data from HHS funded Healthy Marriage and Responsible Fatherhood (HMRF) grantees to evaluate program performance using top line measures like enrollment and attendance of workshops, the rich data collected through the system provides an unparalleled window into the workings of the HMRF programs and the population they serve. This paper describes how raw data exported from the nFORM system have been used to develop econometric models to understand the relationship of demographic and socio-economic characteristics on program enrollment and attendance, the effectiveness of incentives and behavioral nudges on program participation, as well as changes in behaviors and attitudes due to the intervention. Moreover, the paper discusses how patterns revealed through mining the raw nFORM data combined with other administrative data has provided insights into deficiencies in outreach and recruitment efforts, and highlights how the relative effectiveness of steps taken to remedy the deficiencies can also be tracked using the data. Lastly, the paper presents recommendations and best practices in using nFORM and other similar administrative data to inform continuous quality improvement of HMRF programs without stretching the budget.