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Unlock a secret weapon for business improvement with PLM and the Digital Thread
The synergistic relationship between the digital thread and Product Lifecycle Management (PLM) platforms is recognized as essential. The digital thread ensures the traceability of digitized product structures and related artifacts, while PLM provides configuration management throughout the product lifecycle. This includes impact analysis, change management, quality control, the transfer of design data from engineering to manufacturing, the creation of digital twins, and more. However, traceability of product structures and configurations is just one strategic application of data captured in PLM-managed digital threads.
Unlocking the potential of Value Chain Analysis
The concept of Value Chain Analysis, introduced by Harvard Business School professor Michael Porter in The Competitive Advantage: Creating and Sustaining Superior Performance, focuses on the value added by each process step across the product lifecycle. This approach, widely adopted across industries, aims to drive cost reduction, eliminate inefficiencies, accelerate time to market, enhance competitive advantage, and improve customer satisfaction. It is an essential element of continuous improvement.
Modern PLM platforms leverage digital threads to capture transactional process details—referred to as workflows in PLM terminology—used in transforming product structures and configurations. Harvesting workflow performance and navigational data across all products provides invaluable insights for Value Chain Analysis, extending PLM value well beyond traditional configuration management.
There are some great examples of how companies use PLM platforms to drive Value Chain Analysis to the next level, click here to learn more.
Workflows vs. product structures
PLM-managed digital threads model workflows by recording every transaction between workflow sub-states (bullets in Figure 1). Each sub-state (dots in Figure 1) and transaction (arrows in Figure 1) carries metadata such as who performed the action, why it was initiated, when it was completed, the result, time taken for the next step, and more. These workflow models are independent of product structures, although related when relevant. Examples of PLM-managed workflows include changes, reviews, and releases.
Figure 1: Sample PLM workflow that controls the process of lifecycle state transformations
A model of specific actions to get from one lifecycle state to another
PLM of course uses digital threads for traceability of product configurations across lifecycle states (Figure 2). This supports activities such as design verification, impact analysis, and the transformation of engineering BOM (EBOM) to manufacturing BOM (MBOM). While essential, these configurations focus on product configurations rather than the processes that produce them.
Figure 2: PLM traceability of product configurations in the context of lifecycle states
The power of workflow metadata
The accumulation of workflow metadata over time enables organizations to evaluate and optimize the efficiency of their design processes. PLM-managed digital threads act as a “secret weapon” for business improvement, capturing how workflows perform under varying circumstances, such as lifecycle state transitions or specific activities. For example, metadata can reveal trends like slower reviews or bottlenecks in approvals, providing actionable insights to enhance efficiency.
This data-driven approach to Value Chain Analysis extends the digital thread‘s role from supporting engineering decisions to enabling continuous improvement of workflow processes. In essence, workflow traceability evaluates the efficiency of design processes, complementing configuration management’s focus on engineering outcomes.
Beyond 3D assemblies: Complex products and multi-domain integration
Value Chain Analysis of PLM workflows becomes even more impactful when addressing today’s complex products, which integrate mechanical, electronic, and software components. Modern PLM platforms enable workflow mapping across domains connected by Model-Based Systems Engineering (MBSE) and simulation models. While cross-domain product structure traceability remains a challenge, the related PLM workflows can capture data to analyze:
- Allocation from system models to domains to initiate design activities.
- Misalignments causing rework between mechanical and electronic designs.
- Handover times between domains.
- Partner and supply chain contributions to the process.
Achieving this requires domain-specific tools synchronized with the PLM-managed digital thread, focusing on lifecycle workflows rather than, in addition to, design data configurations.
But there’s more…
Authoritative Source of Truth
The multi-domain approach to workflow tracking does not fall victim to the never-ending discussion of how much data should be managed by PLM: copy vs. synchronizes vs. federate. This is because workflow metadata is fixed per workflow instance once the workflow is completed, and therefore, there is no risk of having different interpretations due to the actual location of the data. However, having it in PLM retains all the benefits of a centrally managed digital thread, such as local configurability of the workflow data model to reflect specific manufacturer needs.
Enterprise-wide visibility
Like ERP systems, PLM-managed workflows provide centralized reporting for comparing efficiencies across domains, teams, and locations.
AI-Generated Workflows
Workflow performance data could eventually support AI-generated workflows, optimizing existing and generating new workflows.
Closing thoughts
Value Chain Analysis focuses on optimizing the processes and activities that deliver customer value. While not traditionally associated with PLM platforms, this approach can leverage workflow data already collected by PLM to provide new strategic insights on the efficiency of engineering and other processes—without imposing additional burdens on the users.
For C-level executives, this translates complex technical concepts (e.g., digital threads, PLM architectures, semantically rich relationships) into tangible business value, emphasizing measurable results and continuous improvement strategies of the PLM workflows. This value realignment is based on PLM data-driven Value Chain Analysis initiatives. That in turn makes it easier to secure support and funding for a strategic shift toward modern PLM platforms or for increasing the footprint of the existing PLM beyond the traditional focus on lifecycle management of mechanical designs.
