Building Program Archetypes for Digital Engineering

11.1.4: MBSE lightning round

David Long
Nicole Hutchison

INCOSE Content: 421
When: Thu 20, Jul 11:00-11:20 HST
Topics: MBSE Lightning round

In the US Department of Defense (DoD), evidence across the Services and industry affirms digital transformation is critical for program success 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 is not alone in this experience. Whether engaged in aerospace or transport, energy or medical devices, organizations recognize that they must harness the potential of digital transformation not only in the practice of systems engineering but across the greater engineering and product lifecycle. We as systems engineers must update our concepts, methods, and workflows taking full advantage of the digital power of computation, visualization, and communication as we develop, deploy, and sustain capabilities.
While the desire and drive to digitally transform are real, so are the challenges programs and organizations face in this journey. For some, this is the challenge of starting a program in a digital way. For many others, it is a challenge of taking the approaches and processes currently being used and updating them and their staff to take advantage of digital approaches. Though many organizations are working to create reference models and best practices, digital transformation is often hindered by the workforce’s understanding of how to tailor it to fit the program’s needs.
There is no one-size-fits-all answer to this challenge. While the theoretical ideal would have every organization and program custom develop a fit-for-purpose environment and ecosystem, such an approach is not practical. In reality, by focusing on a select set of considerations, we can quickly reduce the solution space to a limited number of archetypes. A few considerations include the type of acquisition (e.g. a major capability, a prototyping approach, software-intensive, etc.); the risk profile of the program; the novelty of the technology in play; and the balance of the acquisition in terms of fidelity versus abstraction of data. These archetypes provide a solid starting point that can then be further tailored, as desired. We will discuss the most frequent archetypes and the different “flavors” of digital engineering that are most commonly required based on archetype, including common templates, considerations for environment, etc.