Accession Number:

AD1122258

Title:

A New Military Retention Prediction Model: Machine Learning for High-Fidelity Forecasting

Descriptive Note:

[Technical Report, Final Report]

Corporate Author:

INSTITUTE FOR DEFENSE ANALYSES ALEXANDRIA VA

Personal Author(s):

• Pechacek, Julie
• Gelder, Alan
• Roberts, Cullen
• King, Joe
• Bishop, James
• Guggisberg, Michael
• Kirpichevsky, Yev
• ,
• ,
• ,
• ,
• ,
• ,

Report Date:

2019-06-01

Pagination or Media Count:

26

Abstract:

Using machine learning algorithms and 18 years of data, we predict individual-level attrition among active duty personnel in all military Services, with hold-out sample prediction accuracies typically exceeding 70. Importantly, our methodology accommodates both right and left-censoring of observed career paths, and significantly outperforms traditional survival analysis. Using these individual-level predictions, we generate aggregate predicted force profiles which closely align with historical actuals. This and other features offer a rich slate of observations for further empirical analysis, and suggest new policy levers for managing attrition.

Descriptors:

Subject Categories:

• Personnel Management and Labor Relations
• Information Science
• Military Forces and Organizations

Distribution Statement:

[A, Approved For Public Release]