Building Process Improvement Business Cases Using Bayesian Belief Networks and Monte Carlo Simulation

Abstract

Many organizations require quality improvement initiatives to be based on quantified business cases. This leads some organizations to start measurement programs to collect data about current performance-a lengthy and expensive process that requires a strong commitment from management. This report describes a collaboration between the Software Engineering Institute and Ericsson Research and Development, The Netherlands, to build a business case using high maturity measurement approaches that require limited measurement effort. For this project, a Bayesian belief network (BBN) and Monte Carlo simulation were combined to build a business case for quality improvement. Using a BBN gave quick insight into potential areas of improvement based on relevant quality factors and the current performance level of the organization. Monte Carlo simulation enabled a detailed calculation of the likely business results in the areas of potential improvement. This approach led to the decision to implement agile methods to improve the quality of requirements.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2009
Accession Number
ADA512345

Entities

People

  • Ben Linders

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Agile Software Development
  • Bayesian Networks
  • Business Administration
  • Commerce
  • Computational Science
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Delphi Method
  • Engineering
  • Measurement
  • Monte Carlo Method
  • Organizational Structure
  • Project Management
  • Simulations
  • Software Development
  • Software Metrics

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Organizational Process Management (OPM).

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy