Earlier today, I was honored to be invited by Michael Finocchiaro to participate in a webinar on the Future of PLM with analysts and panelists – George Lawrie, Jim Brown, Predrag (PJ) Jakovljevic, CIRM, Peter Bilello, Oleg Shilovitsky, Rob Ferrone, Martin Eigner, and Jos Voskuil. It was an interesting discussion that I recommend checking out. We covered a wide range of topics, including the role of PLM analysts, the future of technologies, and – of course, since it’s unavoidable these days – the role of AI.
Check the recording here.
In my blog today, I’d like to share my reflections on the conversation, along with my perspective on the current status quo and the future of PLM. This is not a transcript of the webinar, but rather my own thoughts on where we are now and where PLM technology and business are heading.
For decades, PLM software vendors have promoted the dream of a unified platform—the so-called PLM holy grail—a single system capable of managing every aspect of the product lifecycle, from design and engineering to manufacturing and service. This vision has shaped roadmaps, procurement strategies, and even entire IT architectures. Yet, the reality has consistently fallen short of the promise.
As Jim Brown noted during the webinar, the truth is that we live in a world of many systems. This is the reality practitioners face every day. The challenge, therefore, is not to keep demanding a single PLM vendor platform (or worse, a single database) to manage the entire product lifecycle, but to find a better, more sustainable way forward.
Companies are getting more distributed, global supply chains have become more interconnected, technologies more dynamic, and businesses more specialized than ever. The “one-size-fits-all” PLM vision has proven brittle in a world that thrives on flexibility and cross-company collaboration. The cracks are visible: stalled implementations, high costs, and frustrated users.
The question facing manufacturing companies now is not whether PLM matters—it clearly does—but what kind of PLM future they should prepare for. If your company is still waiting for the “one-hollistic-fits-all” PLM platform to save the day, you’re waiting for something that will never come. Instead, the next phase of PLM requires new thinking: separating strategy from technology, putting data at the center, and building ecosystems around services and intelligence.
Let’s talk about all these topics.
The Three Hard PLM Truths
The End of the Unified PLM Platform Vision
The dream of the monolithic PLM platform is over. No single vendor can realistically cover the breadth of processes, tools, and data flows modern manufacturers require.
Vendor roadmaps were designed with good intentions: deliver a seamless stack from CAD to ERP to service. But in practice, companies are too diverse. A medical device startup has entirely different needs than a global automotive OEM. Suppliers must collaborate across multiple customers and toolchains. The idea that one vendor stack could dominate all of this was a convenient narrative—but not a sustainable reality.
The collapse of large-scale PLM projects underscores this truth. Many enterprises invested years and millions into single-platform deployments only to discover that they couldn’t adapt to new technologies or integrate with partners. Some ended up running “Frankenstein systems”—patched together with customizations that defeated the purpose of buying a platform in the first place.
Global collaboration adds another nail in the coffin. In a world where design is in Germany, manufacturing is in Vietnam, and the supply chain spans five continents, no closed system can keep up. PLM must evolve beyond platform boundaries.
Data Outlives Applications
Software platforms and tools come and go, but data remains. Engineering and manufacturing data – design files, BOMs, requirements, test results, quality records – often need to be retained for decades. The lifespan of a jet engine, a medical device, or even a car model can exceed the lifespan of most PLM, CAD, or ERP software releases.
The problem is that companies still anchor their most valuable assets to specific applications. A CAD file may be locked in a proprietary format. A BOM might only exist inside an ERP database. When it comes time to migrate or upgrade, organizations face painful transitions, often losing fidelity or accessibility in the process.
Examples abound: CAD migrations that take years and drain budgets; ERP systems from the 1990s still holding manufacturing BOMs that no one dares to touch; quality systems that become orphaned after a vendor exit. The risk is not theoretical – companies literally lose their ability to reuse or even access their own product knowledge.
If applications are transient, but data is permanent, then the only sustainable approach is to treat data as the real asset. That shift is still missing in many organizations.
The Adoption Status Quo is Broken
Even when companies succeed in deploying PLM software platforms, adoption remains a stubborn challenge. After decades of investment, many organizations still struggle to achieve broad, consistent usage. Why?
- Complexity: PLM systems often overwhelm users with features they don’t need.
- Training burden: Every release requires retraining, slowing down adoption.
- Fragmented collaboration: Engineering, manufacturing, and suppliers rarely use the same system, leading to duplication and rework.
As a result, companies fall back on “Excel glue.” Engineers export BOMs into spreadsheets, share them over email or shared drives, and manage change informally. This work-around persists even in companies that have spent millions on enterprise PLM.
The advanced technology development in file storage and search provoked companies to pull the data outside of the systems and manage it using various IT solutions.
The status quo is unsustainable. PLM adoption is not just a technical issue – it’s a failure to align systems with how people and organizations actually work.
Three Critical Steps Forward
Separate PLM as a Business Strategy from PLM as a Technology
One of the most fundamental shifts companies need to make is to stop conflating PLM strategy with PLM technology.
PLM as a business discipline is about how your company organizes processes, people, and decisions across the lifecycle. It’s the framework for how design transitions to manufacturing, how change is controlled, and how product knowledge is retained.
PLM as a technology is a toolbox of services and applications that support that discipline. These tools should be modular, flexible, and replaceable—not a monolithic vendor stack.
Companies that confuse the two end up chasing features instead of building capabilities. They buy tools before clarifying what business problems they are solving. The result is technology driving strategy, when it should be the other way around.
👉 Question for readers: Does your PLM strategy drive your technology choices, or are you letting tools dictate strategy?
Adopt a Data-First Vision
The second step is to make data – not applications – the centerpiece of your PLM approach.
If you accept that data outlives applications, then the logical conclusion is to invest in data models, not platforms. That means developing scalable, open, and connected data representations that can survive software changes and vendor transitions.
A data-first PLM vision treats applications as services that interact with data – not as fortresses that control it. In practice, this means adopting standards where possible, leveraging cloud technologies for accessibility, and designing for reusability across functions.
This also connects directly to the digital thread: a continuous flow of data across the lifecycle. But the digital thread cannot exist if every piece of data is locked inside a different system. Openness is the precondition for connectivity.
👉 Question for readers: If your PLM vendor disappeared tomorrow, would your product data survive intact?
Develop the Triad: Data, Product Data Services, Intelligence
The third step is to build a balanced triad that transforms PLM from an isolated IT system into a digital backbone:
- Data: Structured, connected, and persistent. Data models must support multiple lifecycle views—engineering, manufacturing, service—without duplication.
- Product Data Services: Modular capabilities for managing design data, handling change, coordinating manufacturing, and supporting supply chains. These services should plug into the data foundation rather than dictate it.
- Intelligence & Decision Support: Analytics, AI, and knowledge systems that turn product data into actionable insights. From cost analysis to predictive maintenance, intelligence closes the loop between raw information and real decisions.
A warning here: AI without a solid data foundation is just noise. “Garbage in, garbage out” applies more than ever. Companies eager to jump into AI-driven PLM need to ensure their data is clean, connected, and trustworthy.
👉 Question for readers: Where does your company stand in building this triad?
Looking Ahead
The digital backbone of tomorrow’s manufacturing enterprise will not be a single platform. It will be a data-centric ecosystem, supported by modular services and enhanced by intelligence.
This future aligns with broader technology trends:
- Cloud-native architectures that enable scalability and resilience.
- Multi-tenant models that deliver economies of scale and continuous updates.
- Graph-based approaches that represent complex relationships more naturally than tables locked in legacy databases.
Companies that embrace these trends will be positioned to outpace competitors still tied to platform thinking. The transition won’t be easy, but it is necessary.
What Is My Conclusion?
The status quo of PLM is ending. The vision of a unified platform has collapsed, applications will continue to rise and fall, and adoption cannot succeed without a shift in mindset.
The way forward is clear:
- Separate PLM strategy from technology.
- Adopt a data-first vision.
- Build the triad of data, services, and intelligence.
PLM is not about buying another platform. It’s about building an adaptive, data-driven ecosystem that can survive vendor shifts and technological change.
Now the question is:
- What does “PLM beyond the platform” look like in your organization?
Which of the three truths resonates most with your current challenges?
Those are just my thoughts… I’d love to hear your perspectives – share them in the comments or join the discussion on LinkedIn.
Best, Oleg
Disclaimer: I’m the co-founder and CEO of OpenBOM, a digital-thread platform providing cloud-native collaborative and integration services between engineering tools including PDM, PLM, and ERP capabilities. With extensive experience in federated CAD-PDM and PLM architecture, I advocate for agile, open product models and cloud technologies in manufacturing. My opinion can be unintentionally biased.
