Digital Thread

Business Problem

On large, complex systems engineering projects, configuration-controlled data products—including design specifications, test results, and engineering artifacts—are generated across multiple specialized tools. Each of these systems serves as the authoritative source of truth for its respective data products, yet they operate in isolation without interoperability. These disparate systems produce data in fundamentally different structures and formats, creating silos that prevent cross-system analysis and integration.

This fragmentation makes it impossible to answer critical business and engineering questions that require insights spanning multiple data sources. Without a unified approach to connect and harmonize these diverse data products, organizations cannot achieve the visibility and traceability needed to manage complex systems effectively.

The Challenge

From the outset, the project encountered significant difficulties. The initial scope was so vast that it required multiple reductions to become manageable. Executive leadership struggled to reach consensus on what the system should encompass, creating uncertainty and conflicting priorities that complicated early planning and decision-making.

The system's dual-stakeholder nature—serving both the contractor and the customer—introduced additional complexity. Achieving alignment between these two parties on functional requirements, feature priorities, and system capabilities proved challenging, as each stakeholder brought distinct needs and expectations to the table.

As the project scope gradually became clearer, the team expanded significantly to meet growing demands. While this growth enabled broader coverage of the system's requirements, it also resulted in a loss of cohesion and communication breakdowns between sub-teams. Maintaining consistent standards, shared understanding, and effective collaboration across an increasingly distributed team structure became an ongoing challenge.

The Solution

The complexity of this system far exceeded that of the Facility Digital Twin project due to the massive volume of program data that needed to be aggregated and harmonized. As the lead Use Case Developer for the project, I made it my mission to reduce the complexity of the business problems the system needed to address, translating technical requirements into clear, actionable objectives that could be understood by every team member and stakeholder—from developers to executives.

To ground the solution in concrete business value, I identified a high-impact system review event that would require the full capabilities of a Digital Thread. This event served as a focal point that demonstrated the system's value proposition and provided a tangible use case around which the team could align.

I developed a comprehensive ontological model that captured the relationships between data sources, the data products that flowed from them, and how these data products together wove a complete picture of system readiness and status. This model provided the conceptual framework needed to understand how disparate data could be unified into a coherent view of program health and progress.

To ensure the accuracy and completeness of this model, I conducted detailed interviews with subject matter experts across different domains and disciplines. Their insights validated the model's structure and identified critical relationships that might otherwise have been overlooked. This rigorously validated ontological model served as the foundation for the Digital Thread's governing model, establishing the unified schema that would enable cross-system data integration and analysis.

The Result

The project is ongoing and remains in early development stages, but we have successfully released a prototype dashboard that demonstrates the core value proposition of the Digital Thread. This prototype visualizes the relationships and data products between two major authoritative sources of truth for the program, providing stakeholders with their first glimpse of how previously siloed data can be unified and analyzed together.

This initial release validates the ontological model and governing schema, proving that disparate data sources can be successfully integrated to provide meaningful insights across system boundaries. The prototype serves as a foundation for continued development and expansion to additional data sources as the Digital Thread matures.