Facilitating Decision Choices with Cascading Consequences in Interdependent Program Networks
Abstract
Acquisition research has recently laid emphasis on the study of the cascading effects of interdependencies in the joint space of Major Defense Acquisition Programs (MDAPs). We are interested in proactively modeling the nonlinear cascading effects of interdependencies in highly dependent networks. Specifically, in this report we examine DoD acquisition in the context of MDAPs exchanging and sharing resources for the purpose of establishing joint capabilities. We hypothesize that examining the interdependent regions among MDAPs from multiple perspectives using nonlinear methods will allow for "what-if" analyses, and will help decision makers gain insight on the cascading effects of perturbations and take appropriate measures to handle them. Additionally, we also ascertain whether a popular decision-theoretic model for decision making and planning for cascading effects in the face of uncertainty is appropriate for studying the cascading effects among MDAPs. We use a case study to determine whether the data required to build an effective decision-theoretic model is available. We also examine the data investigation process and identify the challenges that were encountered. Our results show that it is possible to recast the study of cascading effects in MDAPs as a sequential decision problem. We describe the informational value in the existing data and challenges inherent in the data collection process.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 07, 2013
- Accession Number
- ADA586205
Entities
People
- Anita Raja
- Mohammad R. Hasan
Organizations
- University of North Carolina at Charlotte