Model-based enterprise (MBE) has become one of the defining frameworks for digital transformation in aerospace & defense (A&D) manufacturing. Almost every major OEM and supplier is evaluating how digital product definitions, model-based definition, and connected manufacturing processes can improve quality, reduce cycle times, and increase program agility.
But after years of working with A&D manufacturers, I’ve noticed something interesting. Some organizations become so focused on advancing their MBE maturity that they lose sight of the reason they started the journey in the first place. The objective isn’t to achieve the highest possible maturity level. The objective is to solve business and manufacturing challenges.
That distinction may sound subtle, but it can make the difference between years of investment with limited returns and meaningful operational improvements delivered in months or even weeks.
When the Maturity Model Becomes the Goal
One of my recent customer experiences illustrates this point.
As part of an ambitious MBE initiative, one aerospace manufacturer set out to move process planning, quality planning, and manufacturing definition upstream into its PLM environment. The client had aligned with a particular interpretation of digital transformation maturity: centralize planning, build out bill-of-process and bill-of-characteristics structures, and push more manufacturing information into the digital thread originating in PLM.
On paper, the strategy made sense. In practice, the company spent millions of dollars over several years trying to make it work, but the effort struggled. The goal is not tool maturity, it’s process capability.
What the team eventually discovered was that they had moved critical manufacturing planning activities too far away from the people and processes responsible for execution. Process planning and quality planning were becoming increasingly disconnected from the realities of the shop floor. And barriers to continuous improvement were being introduced in the form of approval overprocessing waste. Not only that, but the new process was also only usable in a single program, where full model-based definition with semantic PMI had been introduced. They forgot about the other 99%+ of their manufacturing footprint that was not capable of this level of maturity. They forgot about the limitations of standards like PERT in process planning, which don’t account for the flexibility needed in complex discrete manufacturing processes.
After several unsuccessful attempts, the customer reconsidered their approach. Instead of continuing to force process planning into PLM, they returned final process planning and operation flow development to Solumina MES, where manufacturing engineering, execution, and quality could remain closely aligned with production.
The results were dramatic. What had proven difficult for years was reorganized and implemented in approximately three weeks. The lesson wasn’t that PLM was the wrong system. The lesson was that digital transformation doesn’t follow a universal blueprint. The right architecture depends on the problem you’re solving, the complexity of your products, and how work actually gets done across your organization. That’s where maturity models can sometimes become misleading.
Maturity Models Are Useful, But They’re Not the Mission
MBE maturity models provide a valuable framework for understanding how organizations evolve from annotated 3D models to increasingly integrated, model-driven environments. The challenge is that many organizations begin treating advancement through the framework as a goal in itself.
When that happens, discussions shift from operational outcomes to capability checklists. Teams start asking how to reach the next maturity level rather than whether a particular investment will improve quality, accelerate change management, reduce planning effort, or strengthen traceability. The real value comes in mistake-proofing the transfer of knowledge and requirements by enabling the digital thread.
Every MBE initiative should start with two questions:
- What business problem are we trying to solve?
- What level of digital capability is required to solve it?
Those answers often lead to a very different investment strategy than simply pursuing the highest possible maturity score.
Every Program Starts from a Different Place
One reason MBE can be challenging is that no two aerospace programs have identical requirements.
Programs involving advanced composites, structural simulation, material science breakthroughs, digital certification, or multidisciplinary optimization often require deeper model integration and more sophisticated digital threads. For those organizations, advancing MBE maturity may be critical to meeting customer objectives.
Other programs face different challenges. They may already have well-defined models, but struggle to implement manufacturing changes efficiently. They may experience delays caused by manual interpretation of requirements, disconnected quality processes, duplicate data entry, or limited visibility into production performance.
In those environments, the greatest value often comes from improving the flow of information rather than changing what’s working in pursuit of the next maturity milestone. The point isn’t that one approach is more advanced than the other. The point is that both organizations are making the right decision by investing in capabilities that address their most significant constraints.
Where Manufacturers See Immediate Value
The most successful MBE initiatives don’t begin with technology. They begin with operational friction.
- Engineering changes take weeks to reach the floor.
- Quality teams spend time reconciling information across multiple systems.
- Planners manually recreate information that already exists elsewhere.
- Technicians work from documents that don’t fully reflect current engineering intent.
These are the kinds of problems that directly affect outcomes and costs. When product definition data flows seamlessly into manufacturing and quality processes, those inefficiencies begin to disappear.
- Technicians can work from the same product definition authored by engineering.
- Quality plans can remain aligned with current product requirements.
- Manufacturing teams gain greater visibility into changes and their impact on execution.
- Production feedback becomes available to planners and engineers, allowing process improvements to be driven by actual manufacturing performance rather than assumptions.
Most importantly, information remains connected to the work itself rather than being replicated between disconnected systems. That’s often where manufacturers begin seeing measurable value from MBE.
Start With the Friction, Not the Framework
Organizations frequently ask where they should begin their MBE journey. Our recommendation is to start by identifying the points where information loses context as it moves through the organization.
Look for:
- Shop floor struggles with translating engineering intent or engineering changes that are slow to reach production
- Quality requirements that require manual interpretation
- Process plans that are difficult to maintain
- Duplicate data entry across systems
- Production feedback that never makes its way back into planning
- Teams relying on spreadsheets and workarounds to bridge system gaps
- 2D or iso metric view when 3D is needed
These operational symptoms often reveal opportunities more clearly than a maturity assessment alone. Most A&D manufacturers operate within complex environments that combine advanced engineering systems with legacy manufacturing processes, supplier networks, regulatory requirements, and decades of accumulated business practices.
Even organizations with sophisticated digital engineering capabilities often discover that the greatest opportunities for improvement exist in the handoffs between engineering, planning, execution, and quality. Addressing those gaps frequently produces faster returns than pursuing maturity advancement for its own sake.
Building the Right MBE Strategy for Your Organization
At iBase-t, we work with manufacturers across every stage of the MBE journey. Some organizations focus on extending the value of existing engineering models into manufacturing and quality processes. Others build the foundation for more advanced model-driven execution and digital thread initiatives. In both cases, the goal is the same: ensuring that engineering intent, manufacturing planning, execution, and quality remain connected throughout the product lifecycle.
What we have learned from working with customers is that MBE is not a one-size-fits-all journey. The organizations achieving the greatest success aren’t the ones moving through a model maturity the fastest. They’re the ones using digital capabilities to solve real manufacturing problems, improve operational performance, and create a digital thread that supports the way their business operates.
