Orphan Page (editing practice)
The First Industrial Revolution in the late 18th and early 20th centuries was marked by a transition from production by hand to machine production through the use of steam or water power. The Second Industrial Revolution from the late 19th to the early 20th centuries built upon the progress generated by the increased use of electricity as well as the railroad and telegraph networks that allowed people and concepts to move quickly. The Third Industrial Revolution of the late 20th century was a shift from mechanical and analogue electronics to digital electronics and was characterized by sweeping changes resulting from digital computing and digital communication technologies. During WWI and WWII, the U.S. Department of Defense (DoD) was a leader in technological innovation and use. Famously, a program in the Defense Research Projects Agency (DARPA) paved the way for the modern internet, which has dramatically transformed society.
Throughout the digital revolution, the DoD has moved from being a technological leader during WWII to a slower adopter of digital and computational technologies today. Defense programs that currently utilize digital acquisition and engineering approaches often have to extract technical and programmatic information from their modeling environments to “print out” deliverables in paper form, given the current constraints in the acquisition system.
Digital transformation in the DoD requires an overhaul of two primary elements: engineering and acquisition. In 2018, the Office of the Under Secretary of Defense for Research and Engineering (OUSD(R&E)) published a Digital Engineering Strategy. This outlines the vision for digital engineering (DE) and five goals of the transition to a digitally based engineering and acquisition approach (DoD 2018). The DoD defines DE as “an integrated digital approach that uses authoritative sources of system data and models a continuum across disciplines to support lifecycle activities from concept through disposal” (DoD 2018). The primary goals of the Digital Engineering Strategy are illustrated at left.
Digital transformation is fundamentally changing the way acquisition and engineering are per-formed across a wide range of government agencies, industries, and academia. It is characterized by the integration of digital technology into all areas of a business, changing fundamental operations and how results are delivered in terms of new value to customers. It includes cultural change centered on alignment across leadership, strategy, customers, operations, and workforce evolution.
In the DoD, digital transformation involves transition from traditional acquisition and engineering approaches, which are heavily document- and event-driven, to a model-based approach that improves transparency and integration and allows improvements in existing processes. Full digital transformation requires both digitization and digitalization. Digitization – the simple transfer of existing processes into a digital environment – is generally the easier of the two to tackle. The example of programs having to “print out” expected documents from models is an example of digitization. Digitalization does not require that existing processes and artifacts be translated into an electronic environment, but that these be reviewed to determine where they can and should be updated to improve effectiveness, efficiency, and transparency in a digital environment. It is only with thoughtful consideration of both aspects that any organization can achieve true digital transformation. The distinction is important because digitization is the easier of the two and can result in some initial quick wins; however digitization in itself is not enough. Without continuing to push for digitalization and making improvements to harness the power of digital approaches and workflows, the Department will not achieve its objectives for digital transformation.
As the DoD transitions to digital engineering, there is a need to develop and maintain an acquisition workforce that is literate in model-based approaches, competent in digital models, methods, and tools, and understands digital artifacts across the acquisition lifecycle. Recently, the Systems Engineering Research Center (SERC) developed a competency framework to support this workforce.
DIGITAL ENGINEERING COMPETENCY FRAMEWORK (DECF)
A capable workforce is key to realize the intent of the digital engineering strategy. In 2019, the DoD tasked the SERC with defining the critical knowledge, skills, abilities, and behaviors (competencies) required to implement digital engineering approaches; highlighting the competencies that are most critical for the DoD acquisition workforce; and providing the basis for ensuring the acquisition workforce has the appropriate competencies to work within the envisioned digital environment.
In 2021, the SERC published the Digital Engineering Competency Framework (DECF) version 1.1.[1] The DECF conceptualizes digital engineering as being built on a foundation of digital data. Data is used to create models and those models are used to support the processes associated with digital engineering and the other acquisition functions. From the digital engineering activities, artifacts are generated – some focused on the system and some at the program level and higher. All of these are supported by modeling and simulation suites and require an integrated digital environment.
The DECF competency groups (below) align with the major activities in this context. Competencies around the creation and use of digital and PM artifacts (e.g.,digital twin, digital thread, etc.) are interwoven throughout the competency groups, as they touch on each area. The DECF framework also assumes a foundation of basic digital competencies, shown in the table (below right).
Though they were created for different purposes, the DECF framework also aligns well with the Skills Framework for the Information Age (SFIA), which is a multi-national effort that outlines a “global skills and competency framework for the digital world.”[1] This indicates that the DECF, created for a DoD context, is likely to have a wider applicability.
The final dimension for any competency model is that of proficiency: the level of attainment for a particular competency. The DECF utilizes typical strata for proficiency: awareness, basic, intermediate, advanced, and expert. For those familiar with Bloom’s taxonomy, an “awareness” proficiency equates to “knowledge” – the ability to, for example, recite a specific definition. “Basic” equates to “understanding” – not just knowing a definition, for example, but being able to explain that definition using different terminology to different stakeholders. The “expert” proficiency is the equivalent of “synthesis” and “evaluation” – meaning having enough skill and depth of knowledge to be able to generate new concepts or appropriately assess when certain approaches and techniques are most appropriate.