In my recent blog about the CIMdata Industry and Market Forum in Ann Arbor, I highlighted a recurring theme that caught my attention. Despite decades of evolution and the rise of buzzwords like “digital thread” and “digital twin,” Product Lifecycle Management remains predominantly an engineering tool. Vendors talk about futuristic PLM solutions and PLM software to support enterprise transformation, connected ecosystems, supply chain management, and strategic value. Yet, in practice, PLM software continues to sit in the engineering department, often isolated from the broader business it is meant to serve. While the PLM vision, PLM business strategy and product lifecycle management software capabilities were designed for an entire organization, PLM vendors didn’t deliver PLM process, PLM capabilities and most importantly broad adoption of PLM beyond engineering team.
This isn’t just an academic observation. It highlights a fundamental question that many manufacturing companies struggle with today: What is desired PLM ownership? Who should own PLM strategy, system, and software? Should it combined with enterprise resource planning? Belong to IT? Become an addition to inventory management, combined with product quality? Who should be responsible for PLM implementation, how to ensure real time data is available to everyone, how to connect computer aided design (CAD) with engineering change management (ECO) and rest of business processes. How to ensure PLM enables people, analyze engineering data.
I wanted from to learn from market trends an other industries and tools. Let’s learn from someone success or mistakes is aways a good idea… Let’s check some success stories…
What We Learn from CRM Systems
Take CRM systems like Salesforce as an example. At first glance, CRM appears to be a sales tool. After all, it’s about leads, opportunities, pipeline management, and closing deals. Naturally, sales teams were the first owners. The initial software product was targeting sales people.
But over time, companies realized that a CRM is only as powerful as its integration into the entire customer journey. Marketing uses CRM for campaign management and lead qualification. Customer service integrates support cases and issue resolution workflows. IT manages integration with ERP, data governance, and security. Executives track company-wide customer metrics and strategic goals.
When CRM is owned only by IT, it becomes a technical infrastructure project with limited business impact. When owned only by sales, it remains disconnected from marketing and service, leading to fragmented customer experiences. The only way CRM delivers true value is through shared ownership – where sales, marketing, service, IT, and executive leadership jointly shape, adopt, and sustain the system as a strategic customer platform.
Collaboration Platforms: From Chat Tools to Digital Nervous Systems
I can see a similar story with collaboration platforms like Slack or Microsoft Teams. These tools started by individuals or small teams. They were seen as simple chat or notification tools to reduce email clutter.
However, their real transformative power emerged only when ownership expanded beyond IT or a single team. As HR and communications integrated onboarding, training, and company-wide announcements, Slack and Teams became cultural infrastructure. Business units embedded approvals, task management, and workflows to streamline operations. IT ensured security, integration with business systems, and governance policies. Executives promoted these platforms as vehicles for cultural change, productivity, and innovation.
When Slack remains owned only by IT, it becomes another tool installed on employee laptops. When owned by one department, it risks becoming fragmented shadow IT. Shared ownership transformed these platforms into the nervous system of modern organizations, connecting everyone and everything in real-time.
The Engineering Cage and “Give Up PLM” Argument
This brings us back to PLM. The roots of successful PLM software implementations goes back to a very complex process helping engineering team to deliver from initial concept to production planning, but mostly focused on the development phase. PLM vendors pushed the ideas of accelerate innovation (remember “innovation platforms”), regulatory compliance (remember PLM+QMS), meet market demands (remember “ideation” and requirements), as well as pure technological approaches (remember “cloud native plm system”, “cloud based solutions”), software as a service (remember “SaaS PLM”). While all these days were good, the change didn’t happen.
Recently, Andreas Lindenthal wrote a provocative article urging engineers to “give up PLM.” His argument was simple: engineering’s tight control and departmental mindset keep PLM trapped as a tactical tool rather than allowing it to evolve into an enterprise-wide strategic solution. According to him, IT and business executives should take over ownership to drive broader adoption and impact. This approach will allow to IT to ensure that PLM integrates and effectively manage product data connecting a PLM platform to other key components of IT and providing ongoing support to key processes and teams outside of engineering eliminating data errors, analyze data and helping to deliver a competitive advantage.
I find Andreas’s view insightful but also incomplete. He is right about one thing: engineering alone cannot transform PLM into an enterprise platform. But if engineers were to give up PLM entirely, the outcome would likely be catastrophic for design and technical workflows.
Here’s why. Engineering owns the core processes that create and define product data – CAD designs, part structures, BOMs, configurations, and specifications. Their expertise ensures that PLM supports real-world design, compliance, and technical decision-making. If PLM software ownership shifts entirely to IT or business executives without engineering involvement, the system risks becoming disconnected from its foundational purpose.
So, if PLM remains fully controlled by engineering, it will continue to be seen as “their system” – used for CAD file management and revision control, but ignored by manufacturing, procurement, supply chain, quality, and service teams who need access to structured product information to do their jobs effectively.
How to Achieve “True” Enterprise PLM
To break free from this “engineering cage”, the PLM paradigm itself must change. For decades, PLM systems were designed with a controlling mindset. Their primary purpose was to enforce strict workflows, lock down data, and manage approvals under tight revision control. This command-and-control approach ensured compliance, but it also created friction, resistance, and limited adoption outside engineering.
If we want PLM to become a true enterprise system, it must transform from a controlling tool to a knowledge-sharing platform.
Think about what is happening in enterprise software today. AI is bringing a new dimension to data management. Companies are starting to build product knowledge graphs that connect design data, BOMs, requirements, manufacturing processes, suppliers, field data, and customer feedback into a single semantic model. This is what I call building “product memory.”
A product knowledge graph, powered by graph database and AI, can:
- Provide engineers instant insights about past design decisions, failures, and trade-offs.
- Give manufacturing teams real-time visibility into design changes and their impact on production.
- Enable procurement to identify alternative suppliers and cost risks dynamically.
- Help service teams understand configurations and maintenance history for better support.
- Empower executives with cross-functional analytics for strategic decisions.
Such an approach turns PLM from a data vault into an intelligent knowledge-sharing network, accessible by everyone involved in the product lifecycle. It becomes a living memory of products, processes, and decisions that compounds in value over time.
Technology Is Not Enough – Business Models Must Change Too
However, even the best AI-powered knowledge graph won’t deliver its full potential if the underlying business model remains unchanged. Traditional PLM is still sold using seat-based licensing models, which create artificial barriers to collaboration and data access. Only those with a paid seat can view or contribute data, fragmenting knowledge and limiting adoption.
To truly unlock PLM’s enterprise potential, business models must evolve beyond seat-based licensing. Access to product data should be democratized, just like CRM and collaboration platforms evolved towards usage-based and value-based models to drive company-wide adoption.
But that is a discussion I will elaborate on in a separate upcoming article – “Killing the Seat-Based Model” (stay tuned).
Towards Shared Ownership in PLM
So, who should own PLM? My answer – everyone who is part of the product entire lifecycle.
PLM needs engineering leadership to ensure it supports technical workflows and design integrity. It needs IT teams to deliver scalability, integration, security, and data governance. It needs business leadership – whether COO, CDO, or even the CEO – to sponsor PLM as a strategic initiative and not just an engineering tool. Finally, it requires product data management, product development process, manufacturing engineering, procurement, production process, quality, business operations, and service teams to co-own processes, workflows, and data to ensure the system reflects the full lifecycle of the company’s products.
But, PLM business model need to be transformed too (let’s talk about it in the next blog- this one is too long already)
What is my conclusion?
As I observed at CIMdata event, PLM remains predominantly engineering-centric despite all the strategic narratives we hear. Andreas is right: engineering must give up exclusive ownership of PLM. But he is wrong to suggest that engineers should abandon PLM altogether. Their expertise is essential for grounding the system in real product design and manufacturing realities.
The real solution is shared ownership, supported by a paradigm shift. PLM must transform from a controlling, locked-down system into an open, AI-powered knowledge-sharing platform, underpinned by modern business models that democratize data access and collaboration.
Only then will PLM fulfill its promise – not as an isolated engineering tool, but as a strategic enabler that connects helps people to get to market faster, management product data, provide data analysis, streamline processes, and share knowledge and PLM data across the entire product lifecycle.
Just my thoughts…
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’m advocates for agile, open product models and cloud technologies in manufacturing. My opinion can be unintentionally biased
