Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/4392
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dc.contributor.authorThomas J. Housel, Johnathan Mun-
dc.contributor.authorRaymond D. Jones, Timothy R. Shives-
dc.contributor.authorBenjamin Carlton-
dc.date.accessioned2021-05-18T20:05:43Z-
dc.date.available2021-05-18T20:05:43Z-
dc.date.issued2021-05-10-
dc.identifier.citationPublished--Unlimited Distributionen_US
dc.identifier.urihttps://dair.nps.edu/handle/123456789/4392-
dc.descriptionAcquisition Management / Defense Acquisition Community Contributoren_US
dc.description.abstractThis study examines five advanced decision support methodologies—Lean Six Sigma (LSS), Balanced Score Card (BSC), Integrated Risk Management (IRM), Knowledge Value Added (KVA), and Earned Value Management (EVM)—in terms of how each can support the information technology (IT) acquisition process. In addition, the study provides guidance on when each methodology should be applied during the acquisition life cycle of IT projects. This research includes an in-depth review of each methodology in the context of the acquisition life cycle. All acquisition projects within the Department of Defense must go through the acquisition life cycle. While each acquisition project is unique, all must pass a series of common hurdles to succeed. Understanding how and when the methodologies can be applied to an IT acquisition is fundamental to its success. The study concludes with a set of recommendations for the use of each methodology in the acquisition life cycle of IT projects.en_US
dc.description.sponsorshipAcquisition Research Programen_US
dc.language.isoen_USen_US
dc.publisherAcquisition Research Programen_US
dc.relation.ispartofseriesAcquisition Management;SYM-AM-21-085-
dc.subjectInformation Technologyen_US
dc.subjectOptimal Risk Mitigationen_US
dc.subjectDecision Support Systemsen_US
dc.subjectSchedule Overrunsen_US
dc.titleA Comparative Analysis of Advanced Methodologies to Improve the Acquisition of Information Technology in the Department of Defense for Optimal Risk Mitigation and Decision Support Systems to Avoid Cost and Schedule Overrunsen_US
dc.typeBook chapteren_US
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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