Analyzing Cost, Schedule, and Engineering Variances on Acquisition Programs

Report Number: NPS-AM-11-175

Series: Acquisition Management

Category: Major Defense Acquisition Programs (MDAPs)

Report Series: Sponsored Report

Authors: William E. Griffin, Michael R. Schilling

Title: Analyzing Cost, Schedule, and Engineering Variances on Acquisition Programs

Published: 2011-12-01

Sponsored By: Acquisition Research Program

Status: Published--Unlimited Distribution

Research Type: Graduate Student

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Keywords: cost, engineering variance, schedule, Selected Acquisition Report (SARs), statistics, program management, contract management


This study of cost, schedule, and engineering variance (CV, SV, and EV) data identified in the Selected Acquisition Reports (SARs) of acquisition programs indicates that early program variances are significantly associated with future program variances. An enhanced understanding of CV, SV, and EV interrelationships and the connection between these program variances and the cost and schedule Earned Value contract variances will allow program managers to better understand the full programmatic impact of a variance problem. This understanding could also aid future researchers in identifying best practices in recovering from the identification of such a problem. In addition, the identification of CV, SV, and EV differences across Major Defense Acquisition Program (MDAP) types highlights the connection between segments of the defense industry and the development of best program management practices.
This research first examines the data using traditional descriptive statistics in order to determine whether identifiable patterns exist among MDAPs and their associated contracts.
A primary objective of the analysis is to develop empirical models that employ cross-sectional, time-series data contained in the SARs. These models help explain the full effect of fixed-price incentive R&D contracts within MDAPs on cost and schedule variance during both engineering and manufacturing development (EMD) and production and deployment.
It is anticipated that this analysis will also help close any existing gaps in the understanding of program versus contract management data.