Accession Number:

AD1168975

Title:

Early Predictive Indicators of Contractor Performance: A Data-Analytic Approach

Descriptive Note:

[Technical Report, Research Report]

Corporate Author:

RAND CORP SANTA MONICA CA

Personal Author(s):

• Anton, Philip S.
• Shelton, William
• Ryseff, James
• Cohen, Samantha
• Johnson, Grant
• Joplin, Stephen B.
• Kravitz, David
• McKernan, Megan
• Camargo, Alejandro V.

Report Date:

2022-01-01

Pagination or Media Count:

109

Abstract:

In this report, the authors describe a new way to apply data science to a variety of disparate and disjointed government and external data sources to highlight the relative contractor performance risks and provide earlier indicators of performance issues in DAF acquisition contracts and programs than would normally be achieved in traditional formal reporting. Although the authors cannot definitively state this is the optimal approach, this method seeks to produce risk and performance indicators earlier than current information sources and metrics do. This is the final report for Phase II of an effort to test the approach outlined here by building a prototype that uses actual data to calculate contractor risk measures and performance metric values relative to those of their peers, the available contractor base, or fixed thresholds, presenting outliers to prototype users for further human investigation and assessment.

Descriptors:

• information science
• air force
• information systems
• business administration
• computational science
• machine learning
• management personnel
• computer programming
• organizational structure
• systems engineering
• program management
• risk analysis
• test and evaluation
• data science
• employment
• statistical analysis
• supply chain

Subject Categories:

• Administration and Management
• Personnel Management and Labor Relations

Distribution Statement:

[A, Approved For Public Release]