Investigating Organizational Factors, Training Needs, and Role Allocation to Aid the Aerospace Workforce in the Transition to Model-Based Systems Engineering

Abstract

The increasing complexity of modern systems is driving the aerospace engineering community to update its legacy systems engineering (SE) approaches to embrace more modernized digital engineering (DE) methods. A key component of DE is Model-Based Systems Engineering (MBSE), where interconnected models support all aspects of the system lifecycle and enable focus on collaboration, integration, and responsiveness to changing requirements. The transition to MBSE has proven difficult for the industry to conceptualize and plan, and the aerospace industry needs to better understand the steps to make this change and the challenges involved. Successful transition results from a combination of technology and organizational factors. The technical and process aspects of digital transformation have been the subjects of research and development, but fewer conclusions are available on the required training for the current workforce to make this transition successful, or on how organizational factors such as composition, roles, size, and culture affect it. Culture includes habits like processes or specific ways of thinking, which can be partly influenced by effective training. The Department of Defense (DoD) and organizational bodies like the International Council on Systems Engineering (INCOSE) have developed competency frameworks to provide input on the required skills for DE. Still, more refinement and alignment with industry needs are necessary to make these useful to all types of organizations and to train all roles involved in executing SE projects involving MBSE. This research examines artifacts and survey results from industry and government SE projects to identify which roles and associated tasks are involved in a set of projects that use MBSE and how those roles are allocated to personnel. To understand the influence of team sizes, information was solicited from a panel of DE and SE experts to define project roles, allocating tasks to roles and roles to personnel for their current projects and for ideal teams ranging from 10 to 100 personnel. The findings suggest that these experts would prefer that projects define more specialized roles to perform MBSE and SE activities. Their ideal teams allow technical engineers to focus more on core technical tasks and less on cross-functional responsibilities, and the experts’ responses represent a desire for clear role distinctions to optimize team effectiveness, particularly in small teams. The results and associated discussion demonstrate both the reinforcement of and some challenges to existing literature on the organizational structures of effective MBSE projects. Following the task and role allocation, this research develops a comprehensive list of the competencies and level of proficiency required for each role when executing an example project that uses MBSE, leveraging the Digital Engineering Competency Framework (DECF) v1.1. Findings from this research indicate a variety of lessons that can inform workforce development and digital transformation in the aerospace industry. For example, this research finds that engineering roles spanning both program management and technical tasks require higher DE proficiency in management-focused activities than in technical execution. The Systems Engineer role also demonstrated broader competency needs, extending beyond modeling and analysis to digital enterprise environments and data engineering. Results highlight that most roles that execute technical tasks share a common competency baseline, suggesting that training programs can emphasize universal foundations while tailoring DE workforce development to select roles. The resulting mapping between SE projects that use MBSE, workforce needs, and competencies is a novel contribution to our field’s understanding of the DE transition and demonstrates how DECF v1.1 competencies can be applied across roles in MBSE-enabled projects and inform training program design.