Why Manufacturers Need More Than a PLM to Achieve Digital Thread Outcomes

Digital thread is one of the most commonly used terms in manufacturing, cited in the context of enterprise digitalization, digital twins, data management, and Product Lifecycle Management (PLM). In itself, a digital thread is the continuous flow of data that links all stages of a product lifecycle, offering complete traceability and a single source of truth for products. PLMs are advertised as the backbone of digital threads, collecting and organizing product data within and across lifecycles, especially as the Bill of Materials (BOM) becomes central to design, engineering, procurement, production, and service.

The crucial role of a PLM in a digital thread is undeniable, and surging PLM adoption reflects the growing recognition of its importance in enabling continuity and collaboration throughout the product lifecycle. Despite high PLM adoption, though, customers are falling short of achieving digital thread results. For example, only 14% of brownfield and 22% of greenfield sites report having integrated Information Technology (IT) and Operational Technology (OT) environments (see ABI Research’s Industrial and Manufacturing Survey 2H 2024/1Q 2025: State of Play for Digital Transformation (PT-3657)). Many mistakenly treat a PLM and digital thread as interchangeable, leading to expectations that a PLM alone can deliver outcomes it cannot.

While a PLM is essential for a digital thread, it does not automatically mean closed-loop traceability and data feedback. Most manufacturers still struggle with data continuity across domains, particularly bridging design, manufacturing, and service. In fact, more than 2/3 of manufacturers can collect and normalize data, but the data reside in single applications—isolated and non-continuous.

The problem is not investment: the PLM market is expected to grow at a Compound Annual Growth Rate (CAGR) of 11.8% from 2025 to 2035, which is high for an established software market (see ABI Research’s Product Lifecycle Management Software market data (MD-PLM-103)). While several factors influence the high growth in PLM software, the push by suppliers such as Aras, Autodesk, Dassault Systèmes, Infor, PTC, and Siemens to underline PLM as the key to a digital thread is central to the marketing narrative. Manufacturers are adopting PLM software expecting to produce a digital thread, but failing to develop consistent data governance standards and a robust ownership framework for mapping data reinforces the lack of digital thread continuity.

The lack of digital thread achievement among manufacturers investing in PLMs can be rectified by actively governing a semantic data layer, assigning clear ownership of data changes across domains, and developing a single digital pathway that can be expanded over time.

• The manufacturing industry correctly emphasizes the importance of a data foundation and data contextualization tools but often fails to recognize the action needed to maintain a contextualized data layer over time. It is not a one-time creation or one-off investment. Manufacturers must start treating data and data contextualization like any other asset: monitoring its health and continuously maintaining it.
• Manufacturers must assign explicit governance ownership to data that cross domains. PLM deployments skip this step—defining who is accountable across domains for the semantic model, who is accountable when tool changes propagate, and who has the authority to force naming standards across PLM, Enterprise Resource Planning (ERP), Manufacturing Execution System (MES), and Quality Management System (QMS) solutions. Human-created naming inconsistencies are where digital threads continue to break even after PLM deployments.
• Start narrow—focus on a decision or question to track throughout a lifecycle, rather than an abstract complete digitalization that is not intentional about traceability of decisions. By following a precise decision or question, users can progressively form the pieces of a digital thread, rather than expecting immediate returns from a broad digitalization initiative that overlooks the small hiccups that break data transfers.