Publication:
Proceedings of the Eleventh Annual Acquisition Research Symposium, Thursday Sessions Volume II. Acquisition Research: Promoting Affordability in Defense Acquisitions: A Multi-Period Portfolio Approach

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Authors
Davendralingam, Navindran
DeLaurentis, Daniel
Subjects
Advisors
Date of Issue
2014-04-30
Date
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Abstract
The implementation of Better Buying Power policies seeks to achieve affordability across the spectrum of major defense acquisition programs. However, the technical and programmatic challenges associated with sequential decision-making in the acquisition of large scale, increasingly interdependent defense systems prompts a need for quantitative frameworks that can better address the complexities of negotiating capability, schedule, and cost, while fulfilling target objectives of affordability. Our proposed research extends prior funded work and adopts innovations from financial engineering to enable quantitatively informed multistage decision-making under uncertainty. The method provides a means of assessing tradeoffs between capability, cost, and schedule risks, and the ability to objectively make sequentially dependent acquisition decisions on a “portfolio” of systems, towards some desired overarching capability. We adopt a dynamic programming approach using statistical measures and optimization techniques that balance short term decisions against long term implications on dimensions of cost, risk, and schedule. The method is demonstrated for the concept case of multi-stage acquisitions in a naval acquisition scenario.
Type
Technical Report
Description
Published April 30, 2014
The research presented in this report was supported by the Acquisition Research Program of the Graduate School of Business & Public Policy at the Naval Postgraduate School.
Department
Graduate School of Business & Public Policy
Identifiers
NPS Report Number
NPS-AM-14-C11P17R02-064
Sponsors
Naval Postgraduate School Acquisition Research Program
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Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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