Dissolving Silos: Unlocking the Real Value of MBSE

Connecting people and data into a living innovation hub

Eric Alexander, Director of MBSE Services 

Engineering programs have long struggled with functional silos. Systems engineers model requirements. Software teams track code. Safety, reliability and test specialists manage their own datasets. Cybersecurity often shows up last, when design changes are most expensive. Each discipline is vital, but too often their work only converges late in the lifecycle, when integration issues surface at the worst possible time. 

MBSE: CONNECTING PEOPLE, NOT JUST DATA

Model-based systems engineering (MBSE) is often described as a way to “connect data.” While that’s true, the real power of MBSE is that it connects people and disciplines. Done right, MBSE becomes an integrated product team (IPT) enabler, giving systems, software, safety, reliability, test and cyber engineers a shared innovation environment to make faster, better-informed decisions. 

True integration means more than connecting datasets – it’s about aligning processes, toolchains, and execution frameworks so that software, test and systems engineers can collaborate in real time. When MBSE connects technical teams to program management,  supporting agile delivery rhythms, the model becomes the living heartbeat of execution rather than a static artifact. 

THE TRAP: THE MODEL AS ANOTHER SILO

Unfortunately, many MBSE initiatives miss this point. They treat the system model as another silo, a deliverable owned by a handful of trained “model jockeys”, instead of as an environment where subject matter expert (SME) knowledge flows freely. The steep learning curve of SysML and MBSE tools, plus limited training budgets, makes it tempting to centralize modeling and lock others out. That approach may produce artifacts, but it doesn’t unlock MBSE’s true value. 

THE KEY: INTEGRATING SPECIALTY DISCIPLINES

The real payoff comes when MBSE integrates specialty views and data into the system model: 

• Safety → Hazards, fault trees, and, failure modes and effects analyses (FMEA) are linked to architecture so risks are mitigated earlier 

• Reliability → Failure rates are tied into structure so design trade-offs balance performance, maintainability and cost 

• Test → Verification is mapped to model elements, making the test architecture living and traceable 

• Software → Interfaces and architecture are aligned with system-level intent instead of deciphered from static PDFs 

• Cyber → Attack surfaces and mitigations are baked into design decisions, not bolted on later 

• Electrical and firmware → Design schematics, configuration constraints and PCB development data linked to system requirements 

• Mechanical → CAD representations and dimensional constraints tied to interfaces and performance parameters 

• Sustainment → Maintenance tasks, reliability analyses and support equipment needs captured alongside design data to ensure life cycle continuity 

When this integration happens, the model becomes more than a documentation tool. It becomes a decision engine. 

MAKING IT WORK: GETTING SME KNOWLEDGE INTO THE MODEL

Integration isn’t just a technical challenge – it’s a program management one. Each engineering discipline must remain active contributors throughout the life cycle rather than just until relevant static milestones are met. That requires leadership alignment, iterative planning and continuous connection between systems engineers, developers and mechanical designers. 

The challenge is to enable this integration without requiring every SME to become a SysML expert. There are three practical approaches emerging: 

1. TRANSLATOR SYSTEMS ENGINEERS A systems engineer collects SME inputs and enters them into the model. This ensures data makes it in, but it’s inefficient and risks turning engineers into high-paid data clerks 

   
   

2. STRUCTURED INPUT TEMPLATES SMEs contribute through standardized forms, spreadsheets, or lightweight tools in their native workflow. These inputs can then be automatically imported into the system model, reducing friction while keeping the model fresh 

   
   

3. AI-ENABLED CAPTURE AI technologies can ingest SME artifacts—requirements documents, hazard analyses, reliability spreadsheets, even verbal notes— and transform them into structured model content. This approach eliminates training burden and allows SMEs to stay focused on engineering, not modeling syntax 

Each of these mechanisms lowers the barrier to participation. The goal isn’t to force every discipline to “speak SysML,” but to ensure their expertise is captured, connected and consumable in the model. That’s how MBSE dissolves silos in practice, not just in theory. 

ANSWERING THE QUESTION: “WHEN IS THE MODEL DONE?” 

Here’s where the concrete truck metaphor helps. A concrete truck’s job isn’t to be admired as the final product. Its job is to keep turning, mixing and pouring out what’s needed to build the foundation. In the same way, the system model isn’t the end product—it’s the innovation engine that produces the end products. 

From the model flows the concrete: 

• Technical review criteria and artifacts 

• Requirement specifications 

• System and software architectures 

• Interface control documentation 

• Functional analyses 

• Hazard tracking data 

• FMEA 

• Test plans and verification matrices 

These are the foundations of a solid technical baseline. But if the truck stops turning—if you treat the model as a “deliverable” that ends before the program does—it will dry up. When you return to it later, it will be unusable. 

THE MODEL AS A LIVING, BREATHING ENVIRONMENT

The model must remain living and breathing, continuously evolving as the design matures, the system learns and the enterprise adapts. That’s how MBSE dissolves silos, unlocks integration across specialties, and delivers not just better diagrams, but better systems. 

The question for leaders isn’t whether to adopt MBSE, but whether they’ll use it as a static deliverable or a living innovation hub. In our experience, the organizations that treat the model like a concrete truck (always turning, always pouring) are the ones that stay adaptable in the face of complexity. 

Because in the end, MBSE isn’t about the model. It’s about keeping innovation in motion. 

Eric Alexander serves as a senior director of MBSE services for STC, where he leads initiatives in MBSE, digital transformation and AI-enabled engineering. With a background spanning complex defense and aerospace programs, he’s passionate about empowering teams to deliver clarity, speed and innovation through integrated digital ecosystems.