Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/4821
Title: Exploring Program Archetypes to Simplify Digital Transformation
Authors: Nicole Hutchison, David Long
Keywords: artificial intelligence
learning-based systems
Bayesian methods
systems engineering
model-based systems engineering
systems theory
Issue Date: 1-May-2023
Publisher: Acquisition Research Program
Citation: APA
Series/Report no.: Acquisition Management;SYM-AM-23-052
Abstract: In the U.S. Department of Defense (DoD), evidence across the Services and industry has affirmed that digital transformation is critical for successful acquisition in an environment of increasing global challenges, dynamic threats, rapidly evolving technologies, and increasing life expectancy of systems currently in operation. (Zimmerman et al., 2019) The DoD must continue to practice systems engineering efficiently and effectively to provide the best advantage for successful acquisitions and sustainment. Digital transformation will require the update of both acquisition and systems engineering practices to take full advantage of the digital power of computation, visualization, and communication throughout the lifecycle. There are a wide variety of variables that shape the profile of a program: What type of acquisition is being done? What is the risk profile of the program? What is the balance of the acquisition in terms of fidelity versus abstraction of data? The research described in this paper is intended to build a set of program archetypes that will help to template the considerations for programs that need to utilize digital acquisition approaches, whether they be existing programs transitioning to digital or new programs.
Description: Proceedings Paper
URI: https://dair.nps.edu/handle/123456789/4821
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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