Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/5255
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dc.contributor.authorRaymond Jones-
dc.date.accessioned2024-08-27T22:36:20Z-
dc.date.available2024-08-27T22:36:20Z-
dc.date.issued2024-08-27-
dc.identifier.citationAPAen_US
dc.identifier.urihttps://dair.nps.edu/handle/123456789/5255-
dc.descriptionSYM Presentationen_US
dc.description.abstractThis 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 tren_US
dc.description.sponsorshipAcquisition Research Programen_US
dc.language.isoen_USen_US
dc.publisherAcquisition Research Programen_US
dc.relation.ispartofseriesAcquisition Management;SYM-AM-24-161-
dc.subjectDigital Twinen_US
dc.subjectValue Theoryen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectInnovationen_US
dc.titleEfficiency Based Forecasting of Defense Acquisition Programs for Improved Decision Making(Enhanced Earned Value Management (E2VM))en_US
dc.typePresentationen_US
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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