Manage Toward Success - Utilization of Analytics in Acquisition Decision Making

Abstract

Large information technology (IT) projects such as Defense Business System (DBS) acquisitions have been experiencing an alarming rate of large cost overruns, long schedule delays, and under-delivery of specified capabilities. There are strict defense acquisition laws/regulations/policies/guidance with an abundance of review and oversights, generating a plethora of data and evidence for project progress. However, with the size and complexity of these large IT projects and sheer amount of project data they produce, there are challenges in collectively discerning these data and making successful decisions based on them. This research article develops an analytic model with Bayesian networks to orient the vast number of acquisition data and evidence to support decision making, known as the DBS Acquisition Probability of Success (DAPS) model.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2015
Accession Number
ADA622598

Entities

People

  • Kai-Chi Chang
  • Sean Tzeng

Organizations

  • Defense Acquisition University

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Bayesian Networks
  • Computer Programs
  • Cost Estimates
  • Data Science
  • Department Of Defense
  • Engineering
  • Failure Mode And Effect Analysis
  • Governments
  • Military Acquisition
  • Operations Research
  • Probability
  • Procurement
  • Project Management
  • Reasoning
  • Systems Engineering
  • Test And Evaluation

Readers

  • Defense Acquisition Program Management
  • Distributed Systems and Data Platform Development
  • Strategic Security Studies

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy