Most organizations that implement Model-Based Systems Engineering (MBSE) don’t fail because they choose the wrong tools. They fail because they implement MBSE as a software purchase instead of a complete reimagining of engineering work. What separates organizations that see real benefit from an MBSE implementation from those that do not often comes down to the structure of the program from the onset.
The Repeating Pattern
Here’s how it usually goes, an organization purchases a few licenses for software, send a handful of engineers to courses and expects everything to fall into place. A year later, models are inconsistent, teams are complaining and leadership is left to wonder if their investment was worth it. The problem is not that MBSE doesn’t work; the problem is that organizations underestimate the effort it takes to truly institute collaboration across teams and projects.
The organizations with the best outcomes actively put together a structured program around their mbse software. They don’t just purchase software and hope for the best; they create frameworks where continued support, standards, and ways to assess whether teams are using models proactively exist. This is not a one-size-fits-all approach.
What a Structure Program Looks Like
When organizations restructure how they approach MBSE, it usually begins from an awareness that different teams need different levels of support. A team working on spacecraft subsystems has different modeling requirements than those designing ground systems or ground/software interfaces. However, at the end of the day, each need to link their work to other models across the organization, meaning someone needs to develop criteria for linking models together across the company.
The best programs involve dedicated resources who are there to help engineers apply what they learn in a relevant manner instead of just getting their feet wet with MBSE principles. These may include internal subject matter experts who have delved into analysis projects or external consultants who can bring similar ideas from similar industries. Either way, having a go-to point of contact when a roadblock hit makes for better adoption rates.
Training also differs in such programs where one-time attendance becomes a thing of the past. Instead, organizations are building learning paths where initial courses teach basics; then, engineers apply them in meaningful projects before reconvening for interim topics, thus bridging the gap between theoretical learning and applicable experience. Companies doing this effectively realize that MBSE capability is not developed overnight; it’s a sustained process over months or years.
Why the Old Way Stops Working
The “old way” is perfectly fine for little pilot projects run by the most motivated engineers on staff. However, it falls apart when millions of dollars and hundreds of engineers across geographic regions are involved; inconsistency is everyone’s greatest enemy.
One team decides to build out their model one way while someone else does it differently. Suddenly, nobody knows what the other meant in their works. Requirements are modeled at different resolutions; interface definitions do not align; it takes three weeks for someone to assess another’s model’s tree structure because there was no universal approach. These are not hypothetical situations, but things that kill MBSE programs in large organizations.
The Move Toward Continued Support
More and more organizations realize that this is not a one-and-done moment with MBSE. It needs continued assessment and evaluation. Models need governance; standards need to be adjusted while teams learn practicality; new engineers need training; tools need debugging and connections with other software applications. All of this takes time and investment.
Some organizations are creating internal MBSE centers of excellence with a few people who oversee standards, guidance, and solutions to modeling concerns; others create long-standing relationships with external parties who can provide information when internal employees cannot. Regardless of how it’s done, this continued connection after implementation is no longer seen as a secondary addition but rather a first step of many.
What Success Really Means
Getting MBSE right through organizational implementation means that teams must understand it’s not merely about technical capability, yes, engineers need an idea about SysML and modeling principles, but they also need clear pathways toward how models will fit into preexisting processes, standards of what good-looking models will be required, and pathways to include outside opinions if concerns arise.
Organizations restructuring their programming are contemplating issues most organizations gloss over: How do we maintain quality of models as projects dissipate? What happens if an engineer on a team quits and no one knows what their models meant? How can we assess that MBSE works? These are not glamorous topics but rather ones deciding whether or not MBSE proves valuable or merely becomes expensive overhead.
Moving Forward Intelligently
Those companies looking to rethink their MBSE structure do so but do not abandon the approach, instead, they double down in smarter fashions. They recognize that sustainable acquisition occurs through more than licensing software and training sessions, it comes from learning how modeling will fit into the greater engineering effort and building systems around them over time.
This represents an organizational maturation regarding how to approach MBSE. No longer is it thought of as a tool to be implemented; it’s a capability that needs to be cultivated and sustained over time. Such a mindset shift, places organizations receiving lasting value out of MBSE into a different category than those relegating it to a footnote down the line.
