Please use this identifier to cite or link to this item:
https://dair.nps.edu/handle/123456789/5255
Title: | Efficiency Based Forecasting of Defense Acquisition Programs for Improved Decision Making(Enhanced Earned Value Management (E2VM)) |
Authors: | Raymond Jones |
Keywords: | Digital Twin Value Theory Artificial Intelligence Innovation |
Issue Date: | 27-Aug-2024 |
Publisher: | Acquisition Research Program |
Citation: | APA |
Series/Report no.: | Acquisition Management;SYM-AM-24-161 |
Abstract: | This paper represents a new approach to defense acquisition program forecasting during the development phase of the program life cycle. It will be the first of three research papers that will attempt to improve insight into how a program performs and will offer a method by which future programs offices will be able to simulate their program before beginning in order to develop an optimal acquisition strategy. Specifically, the purpose of this research is to explore if a digital twin of the defense acquisition development phase of an acquisition program of record can enhance a program manager's decision-making ability by revealing unforeseen patterns in program behavior. Additionally, this research will demonstrate a new way of measuring value and return on investment of a defense program of record, to provide decision-makers with an alternative to tr |
Description: | SYM Presentation |
URI: | https://dair.nps.edu/handle/123456789/5255 |
Appears in Collections: | Annual Acquisition Research Symposium Proceedings & Presentations |
Files in This Item:
File | Description | Size | Format | |
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SYM-AM-24-161.pdf | Presentation | 1.16 MB | Adobe PDF | View/Open |
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