Technical Report
WRT-1006 Technical Report: Developing the Digital Engineering Competency Framework (DECF) – Phase 2
-
Human Capital Development
Report Number: SERC-2021-TR-005
Publication Date: 2021-03-23
Project:
Digital Engineering Competency Framework
Principal Investigators:
Dr. Nicole Hutchison
Co-Principal Investigators:
Dr. Dinesh Verma
This document describes the updated Digital Engineering Competency Framework (DECF) version 1.1 (DECF v. 1.1). This document also summarizes the findings of the comparison between the DECF competencies and the training resources from the US Department of Defense (DoD), and provide recommendations on how to build a competent DoD digital engineering workforce.
Digital engineering (DE) is “an integrated digital approach that uses authoritative sources of systems’ data and models as a continuum across disciplines to support lifecycle activities from concept through disposal. A DE ecosystem is an interconnected infrastructure, environment, and methodology that enables the exchange of digital artifacts from an authoritative source of truth.” DE is a critical practice necessary to support acquisition in an environment of increasing global challenges, dynamic threats, rapidly evolving technologies, and increasing life expectancy of our systems currently in operation.
Digital transformation is fundamentally changing the way acquisition and engineering are performed across a wide range of government agencies, industries, and academia and 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.
On 23 July 2020, the Systems Engineering Research Center (SERC) developed the DECF to support the DoD by providing clear guidance for the DoD acquisition workforce, in particular the engineering (ENG) acquisition workforce (Phase 1) (SERC, 2020). The guidance comprised of well-defined competencies with the associated knowledge, skills, abilities, and behaviors (KSABs) that are required for the DE workforce.
Phase 2 of this research task focused on mapping existing DoD DE training resources against the DECF to identify gaps and provide recommendations on how to build the digital engineering competency of the DoD workforce. The current Defense Acquisition University (DAU) ENG curriculum was analyzed against the DECF to:
- Identify which competencies are already covered within the existing curriculum;
- Identify clear gaps between the existing curriculum and the DECF; and
- Create specific recommendations for training that could help address DECF competencies that are not currently covered in the curriculum.
The updated DECF v. 1.1 includes new competencies that were discovered from the gaps identified when comparing the DECF with the DoD training resources. The DECF competency groups were also updated to reflect a cohesive categorization of the competencies. In DECF v. 1.1, there are five (5) competency groups, nine (9) competency subgroups, and 31 competencies (including six (6) foundational digital competencies) identified as shown in Figure 1 of the report.
The competency hierarchy provides a logical structure for the individual competencies:
- G1 Data Engineering includes data governance and data management which incorporates model-based processes to ensure the formal management of data assets within a digital enterprise.
- G2 Modeling and Simulation in the digital enterprise environment is the process of creating and analyzing a digital prototype of a physical model to predict its performance in the real world. Modeling and simulation are used to help system designers and engineers understand whether, under what conditions, and in which ways a system component could fail and what loads it can withstand through analysis. Data analytics and data visualization play an important role to improve the decision-making process in the system lifecycle. Artificial intelligence and machine learning (AI/ML) are critical tools to enable systems that continuously evolve to behave differently based both on input data and statistical, logical, and knowledge-based inference. AI/ML skills must be applied in a digital environment.
- G3 Digital Engineering and Analysis includes systems engineering and engineering management which constitute how digital engineering takes full advantage of the digital power of computation and communication to take better, faster actions throughout the defense system lifecycle. Configuration management refers to the development of strategies, policies, standards, and guidelines for configuration management of DE related artifacts in accordance with model-based systems engineering methods.
- G4 Systems Software is the systemic application of DE approaches to the development of software.
- G5 Digital Enterprise Environment addresses development of the DE environment including hardware and software aspects. Digital Enterprise Environment Management is for management, communications and planning related to enabling the workforce to manage the adoption of appropriate model-based tools and approaches, techniques and processes for the operation of digital enterprise environment systems that ensure transformational processes in enterprises occur with pace, high-quality and security. Digital Enterprise Environment Operations and Support within a digital enterprise environment include abilities to operate and support the digital enterprise environment across the enterprise and lifecycle. Digital Enterprise Environment Security involves developing policies, standards, processes, and guidelines to ensure the physical and electronic security of digital environments and automated systems.