Please use this identifier to cite or link to this item:
https://dair.nps.edu/handle/123456789/1767
Title: | Capital Budgeting and Portfolio Optimization in the U.S. Navy and Department of Defense |
Authors: | Johnathan Mun |
Keywords: | Capital Budgeting Portfolio Optimization Risk-Based Capital Budgeting Programs Portfolios PEO-IWS NAVSEA |
Issue Date: | 13-May-2019 |
Publisher: | Acquisition Research Program |
Citation: | Published--Unlimited Distribution |
Series/Report no.: | Acquisition Management SYM-AM-19-076 |
Abstract: | This research has the explicit goal of proposing a reusable, extensible, adaptable, and comprehensive advanced analytical modeling process to help the U.S. Department of Defense (DoD) with risk-based capital budgeting and optimizing acquisitions and programs portfolios with multiple competing stakeholders while subject to budgetary, risk, schedule, and strategic constraints. The research covers topics of traditional capital budgeting methodologies used in industry, including the market, cost, and income approaches, and explains how some of these traditional methods can be applied in the DoD by using DoD-centric non-economic, logistic, readiness, capabilities, and requirements variables. Portfolio optimization for the purposes of selecting the best combination of programs and capabilities is also addressed, as are other alternative methods such as average ranking, risk metrics, lexicographic methods, PROMETHEE, ELECTRE, and others. Finally, an illustration at Program Executive Office Integrated Warfare Systems (PEO IWS) and Naval Sea Systems Command (NAVSEA) is presented to showcase how the methodologies can be applied to develop a comprehensive and analytically robust case study that senior leadership at the DOD may utilize to make optimal decisions. |
Description: | Acquisition Management / Defense Acquisition Community Contributor |
URI: | https://dair.nps.edu/handle/123456789/1767 |
Appears in Collections: | Annual Acquisition Research Symposium Proceedings & Presentations |
Files in This Item:
File | Size | Format | |
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SYM-AM-19-076.pdf | 1.02 MB | Adobe PDF | View/Open |
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