Patterns of Success in Systems Engineering: Acquisition of IT-Intensive Government Systems

Abstract

The objective of this effort was to discover patterns of success in the systems engineering of information technology (IT)-intensive systems in a government acquisition environment using the method of positive deviance. Thirty government programs were identified, each with some notable success in the acquisition of IT-intensive capabilities. Twelve were selected for extensive follow-up and analysis, including detailed interviews with front-line practitioners who cope with the demands of the government acquisition system and are in a position to influence or observe positive deviance in their environment. This report describes two large-scale success patterns that were observed, each with several recurring sub-patterns. "Balancing the Supply Web" addresses "social" interdependencies among enterprise stakeholders who have different equities in the capability being developed. "Harnessing Technical Complexity" addresses the technical interdependencies among system components that together deliver an operational capability for the enterprise. The large-scale patterns are two sides of the same coin. The programs studied achieved success because of the way they each navigated through these dual interdependencies.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2011
Accession Number
ADA552395

Entities

People

  • George Rebovich Jr.
  • Joseph K. Derosa

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Commerce
  • Complex Systems
  • Contractors
  • Engineering
  • Governments
  • Information Exchange
  • Information Systems
  • Logistics
  • Network Protocols
  • Procurement
  • Software Development
  • Spiral Development
  • Supply Chain
  • Systems Engineering
  • Teamwork
  • World Wide Web

Fields of Study

  • Computer science

Readers

  • Organizational Process Management (OPM).
  • Regression Analysis.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.