Martin Eigner’s recent post, 40 Years of PDM/PLM: The Status Quo and the Future (LinkedIn post), caught my attention earlier this week. Reflecting on four decades of Product Lifecycle Management and Product Data Management (PLM/PDM) evolution, Martin presents a compelling perspective on where the industry stands today, how PDM and PLM is used for product development process and what the future might hold for holistic product lifecycle management (PLM).
His insights prompted me to think about the trajectory of PLM—what momentum exists, the opportunities ahead, and the challenges that engineering software developers will need to navigate. In this post, I’d like to share my thoughts on the key takeaways and the broader implications for the next phase of PLM development.
The Ongoing PLM Disconnect
For my last 25 years in the business of development PDM/PLM software as well as consulting engineering teams and manufacturing companies, I found an persistent tension between its original vision product lifecycle management and real-world implementations of document management, product data manegement (PDM) computer aided design (CAD), enterprise resource planning, and supply chain management software.
Here are six conflicts I observe in the process of building a holistic PLM solutions, managing product related data (many of them are mentioned in Martin Eigner’s article).
PLM Philosophy vs. PLM Software
The vision of PLM was conceived as a philosophy for seamlessly managing product data and processes across the entire lifecycle. In the reality CAD, PDM, and PLM vendors turned the vision into an IT solution with the business model that prevents holistic integrations. The reality of every PDM/PLM business as of today is to lock data in the RDBS and benefit from CRUD applications. It was best articulated in the video about PLM standards – check this article Empty promises for PLM openness. Because customers cannot quit and the video inside.
Holistic Integration vs. Fragmentation
The vision of PLM was to have a unified system enabling smooth collaboration and agility. In the reality most of PLM software solutions today are monolithic, built on outdated software architectures that struggle to deliver the holistic integration they promise. Some of my recent thoughts about this topic are here – Data Evolution from Scattered Systems to Seamless Intelligence.
Functionality vs. Integration
The vision was to combine best-in-class functionality and best-in-integration (PLM suites). The reality was more ugly – specific standalone tools usually excel in specific areas, but then integrated monolithic PLM software platform from a single vendor were development and they often underdeliver on both usability and depth of function. The platformization lead to a selection of a solution from a single vendor.
PLM Systems vs. Other Enterprise Systems
The vision was to position PLM as the single source of truth for product data. In a real life, product data is distributed across CRM, CPQ, ALM, MES, SCM, ERP, making the single-source ideal difficult to achieve (which lead to a new concept of single source of change. Navigate to my article – Navigating the Evolution of Single Source of Truth: From Files and Folders to Digital Twin/Threads and Product Knowledge Graphs). From an integration perspective (especially PLM-ERP), there is no universal model, with companies forced to navigate a complex web of integrations.
Current Use vs. Future Vision
The vision is that PLM should drive AI, IoT, and knowledge graph capabilities for intelligent product management. And in the reality, 70-80% of PLM customers still use it as a glorified PDM/TDM system, far from the AI-driven future often promised.
Standalone PLM vs. Integrated Digital Thread
In the vision, PLM could evolve into an overarching digital thread/knowledge graph, integrating legacy systems rather than existing as a standalone solution. The reality is ugly and traditional PLM vendors are still selling monolithic, standalone systems. Although everyone speaks about changes, vendors (because of the reason mentioned earlier) resisting this shift toward an open, federated architecture.
PLM Vision Key Challenges
Here are top three challenges I can see in the realization PLM visions. In my view, these challenges are real and we need to speak about them if we are looking how to transform the industry.
- Data Fragmentation: Product data is spread across multiple systems, contradicting the “single source of truth” claim of many PLM vendors. Although, a “single source of change” is a very promising approach, the implementation of this approach requires solving next two challenges.
- Legacy Technologies: Many PLM systems are built on outdated, monolithic software architectures from the 1990s. While most of companies understand the challenge, practical solutions are not coming from the vendors developed these systems (it is an inherent conflict of incapable to kill their own solutions, which is easy to understand).
- Integration Issues: The “best in function vs. best in integration” dilemma has led to suboptimal solutions and isolated data silos. Many organizations were burned by complex integrations in the past and got sick of integrating silos.
Crossing The Chasm
The primary chasm that PLM needs to cross is the disconnect between its original holistic vision and the fragmented reality of its current implementation. Martin Eigner points out that while PLM was conceived as a comprehensive philosophy for managing product data and processes throughout the entire lifecycle, it has largely been reduced to isolated IT systems that fail to deliver on this promise.
Here is how I can see customers can be equipped to cross this chasm: :
- Embrace Modern Software Technologies:
- Adopt cloud-native, microservices, and multitenant architectures
- Implement low-code engines to reduce customization costs and increase flexibility
- Incorporate MBSE, IoT, AI, Digital Twin, and Knowledge Graphs into PLM strategies
- Implement an Overarching Digital Thread:
- Create a knowledge graph that spans all relevant legacy systems
- Develop seamless integration with other enterprise systems (ERP, MES, SCM, CRM)
- Use open and documented interfaces, following initiatives like ProSTEP Code for Openness
- Use new technologies to provide real-time insights and predictive analytics:
- Use graph databases to realize this concept, abstracting from individual application
- Develop new applications for real time collaboration and decision support
- Integrate product data from multiple applications into holistic process support
The Path Forward – Digital Thread Using Knowledge Graph
The most promising approach Martin Eigner proposes is the implementation of an overarching digital thread using a knowledge graph. This approach aligns closely with the original PLM vision, allowing for true integration of product data and processes across the entire lifecycle, while still leveraging existing systems.
By abstracting from legacy systems and extending the digital thread concept, companies can create a unified view of their product data without the need for massive, disruptive overhauls of existing infrastructure. This approach also provides a foundation for leveraging AI and other advanced technologies to drive innovation and efficiency.
What is my conclusion?
PLM remains caught between its lofty ambitions and the practical realities of legacy systems, vendor-driven marketing, and fragmented enterprise environments.
The question remains: Will PLM evolve into a connected digital ecosystem, or remain a constrained IT system rooted in past architectures?
As I reflect on 40 years of PLM evolution, I think that crossing the chasm will require a paradigm shift in how we approach product lifecycle management.
The opportunity is now to embracing modern technologies, focusing on integration, and implementing an overarching digital thread. By doing so, “new PLM” can finally deliver on its promise of holistic, agile, and integrated product management.
The next few years will be crucial in determining whether PLM can make this leap and truly transform product development and management for the digital age.
Just my thoughts…
Best, Oleg
Disclaimer: I’m the co-founder and CEO of OpenBOM, a digital-thread platform providing cloud-native collaborative services including PDM, PLM, and ERP capabilities. With extensive experience in federated CAD-PDM and PLM architecture, I’m advocates for agile, open product models and cloud technologies in manufacturing. My opinion can be unintentionally biased
