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During my summer break, I have been thinking about why companies struggle to start a digital transformation and how businesses keep going, struggling to change.
I ended up with Conway’s Law as a demonstration of the biggest inhibitor to digital transformation in companies.
But before that, I need to make two basic statements that form the basis of my plea.
1. PLM is a strategy
When we mention PLM without the word system, we should think of it as a strategy supported by connected, federated systems.
Most of the time, when I hear people talk about PLM, it sounds like they are talking about their PLM system. A core system needed to implement a Product Lifecycle Management strategy.
For me, PLM (Product Lifecycle Management) starts with the core business processes a company needs to implement to remain a long-term (sustainable) product or solutions provider. More on the solution provider dimension later.
Every company that sells products has a product lifecycle management strategy – see the image above.
When a company focuses only on product data, I am tempted to call it PDM (Product Data Management), which can still support different disciplines.
For me, PLM is the operational environment that helps companies manage their products/solutions throughout the product lifecycle, which means it is influenced by sales, R&D, engineering, manufacturing, service and, increasingly, regulations.
This broad scope makes it clear to me that no single PLM system can effectively support all these demands while providing a user-friendly interface. Even if you are SAP or one of the three major PLM vendors.
To remember:
PLM (Product Lifecycle Management) is a strategy supported by a federated infrastructure, where a PLM or PDM system/platform can be one of the main components.
2. Conway’s Law
If you have read my blog posts before, you might have come across Conway’s Law; although it is not a real law, more a description of a phenomenon, it’s largely true. Compare it to Moore’s Law or Murphy’s Law.
Let’s start with THE LAW:
Conway’s Law is an observation about how organizations design systems, formulated by computer scientist Melvin Conway in 1967:
“Any organization that designs a system… will inevitably produce a design whose structure is a copy of the organization’s communication structure.”
Conway meant that the organizational architecture of what you build tends to mirror the shape of the team that builds it. If you have a siloed organisation with Sales, R&D, Manufacturing and Service, you will build processes and install systems to support those siloes.
The reason: People can only design what they can communicate about. Coordination across team boundaries is harder than coordination within a team, so design decisions cluster along organisational boundaries.
This observation makes what I often call the COORDINATED approach, the approach companies are following and feel comfortable with – image below:
People can work in their silos, then share information in a linear, document-driven process when requested and needed. Sometimes it is not a document but a Bill of Materials. Handling the BOM is a great example of Conway’s Law that still exists.
An example: The PDM(PLM) – ERP integration
One topic that keeps our community busy is PDM-ERP integration, or, in a more advanced setting, PLM-ERP integration, especially when you consider the MBOM.
A recent debate can be found here: Turbulent times in PLM: The EBOM-MBOM chain is shaking, AI is rattling everything.
Without going into the debate, as there are many dimensions in the PLM domain, the first question to ask is: WHY DO WE PERCEIVE IT AS DIFFICULT?
Let’s have a look through Conway’s eyes.
- Two silos need to collaborate: engineering on one side and manufacturing preparation, purchasing and manufacturing on the other. Each side has its favorite system, and that’s where the problem starts.
- Instead of analyzing the preferred process, the focus shifts to how to get data into my preferred system easily and reliably. Instead of People, Processes, Data and Tools, it becomes a Tools, Data and Process discussion. People are not considered anymore.
This approach can lead to ludicrous situations, where an engineer has to request a part number when designing a new product, or, in another case, use a temporary part number until the part is mature enough to be registered in ERP, according to the ERP standard. These are real examples I encountered.
Historically, SAP drove these scenarios, as its material master message and MDM approach were built around a single connected manufacturing environment.
For SAP, the bridge to engineering is built through custom solutions at the CAD level (CIDEON) or EBOM level, e.g., ECTR (DSC).
Technology has never limited a fluent PDM-ERP interaction, as long as you start at the process level before touching the systems.
I have written many posts around this topic in the past too. Here are a few of them:
2026: The BOM revisited – what are the challenges
2023: The rise and fall of the BOM
2020: Learning from the past
For me, the discussion is closed; many companies already know the theory and best practices from the past or for their current operations. But will they work on a better future?
The future and Conway’s Law
In my network, many PLM experts, like Prof. Jörg Fischer or Martin Eigner, can describe an ideal future approach to product lifecycle management. But Oleg Shilovitsky, Benedict Smith, Doug Macdonald and many other voices also describe a potential future, often inspired by an additional graph database layer, sometimes better supported by an ontology. The whole idea is that such an environment is a needed foundation for agent AI.
For example, I like the concept Martin Eigner expresses in the technical architecture. On paper (or slide), the concept looks explainable, though the details are missing.
And of course all the PLM software vendors have similar offerings related to the concept above – the only question to ask yourself as an enterprise is:
“Who owns the data and who owns the knowledge – be aware of a lock-in”
At the upcoming PLM Roadmap & PDT Europe conference in Gothenburg on November 4th & 5th, we will learn about and discuss interesting future concepts, including the application of agentic AI.
Here, I am curious about the following sessions I saw in the agenda:
- Key Findings in the Arrowhead fPVN Project – A Knowledge Graph-Based Digital Twin for Semantic Lifecycle Interoperability
- AI in PLM – Balancing Innovation with Stable Enterprise Architecture
- Digital Threads for Digital Agents & Collaboration: Connecting ALM, Mechanics, E/E, Software and Production
- Ontology-based Data Governance and Enterprise Data Modelling: Standards, AI Readiness and Governance Processes for PLM Data Management, a “Data Town Plan” Approach
- Practical AI Transformation in Enterprise PLM
Of course, there are more interesting presentations to watch and discussions to have, so if you are interested in a potential technical future, join us in Gothenburg; there are still places left; last year the conference sold out.
How to escape from Conway?
The digital thread is one of those topics that appeared even before AI and has now become a theme companies should implement, supported by their software vendors and system integrators. In many boardrooms, the term “Digital Thread” is mentioned to address the lack of end-to-end visibility in the company, finally enabling full traceability.
However, more important, I believe, is the horizontal business thread, where disciplines work together in real time. Technology and, for sure, AI agents can facilitate this approach; however, as long as every silo in the organisation is optimized for its own performance (Conway’s Law again), no horizontal business thread will emerge.
I wrote about this topic in June, addressing the mood in the field at the time: The Human Thread, breaking the (PLM) blame game, where I look into the alerting messages that PLM is failing, already with Conway behind the scenes.
I don’t believe Product Lifecycle Management is failing; businesses are failing to transform their organisations, which will lead to new, better operating models.
Too many future strategies are built on an existing siloed organisation, blocking the potential change needed.
A great book to read in this context is Reshuffle by Sangeet Paul Choudary; he describes the fundamental business changes required to break Conway’s trap.
The challenge is that you cannot delegate this job to middle management; top management needs to understand and execute it once they have mastered the potential strategy.
I consider this one of my major topics for the coming years: educating and coaching organisations to escape Conway’s Law and fully benefit from an AI-supported digital transformation.
Conclusion
This time, a short conclusion – Conway is the elephant in the room – what do you think?
Back on track after a side step (see: I am back), I restarted my PLM activities, and WOW, was I lucky with the first conference on my list: CONTACT Open World 2026 in Bonn.
Melanie Stadtler invited me as a guest (thanks, Melanie 🙏), and for the first time I connected in depth with CONTACT Software, their partners and customers.
I knew CONTACT Software from a few brief interactions, but now I could experience their full ecosystem. As CONTACT Software has historically been active in the DACH region, our paths rarely crossed – most of my activities were elsewhere in Europe.
So my key question was: Who is CONTACT Software, and where would I position them in an SAP/Teamcenter-dominated market?
Around 650 people attended this year’s biannual event. The World Conference Center Bonn, along the Rhine, was a great venue for sessions, networking and evening entertainment.
The conference theme was Industrial AI – from top floor to shop floor.
Before the event, there was a great warm-up party with dinner and a variety show. Beyond the impressive show, it was a great first chance to network and catch up with peers. And then the event started.
Industrial AI — from Top Floor to Shop Floor
Maximilian Zachries, Chief Operating Officer (COO) at CONTACT software, kicked off day 1 sharing CONTACT’s ambition and strategy to grow, with a repackaging of their solution – the CONTACT elements as the image below shows.
In the domain of PLM, I would position CONTACT software as a platform with a few foundational layers and op top of that customers can implement Elements, functional, pre-configured blocks on the platform or connect to other systems in the enterprise architecture.
Maximilian Zachries showed the unification of CIM database, Office, Project and IoT into a single collaboration platform based on Elements – coordinated PLM in my terminology.
Openness is a key driver for CONTACT software, so connectivity is crucial.
The image also shows the intelligence layer, named Fourier, which CONTACT has released and includes Elements related to its AI capabilities.
Initially focused on enhancing functionality within the platform and, in upcoming releases, also adding support for MCP connectivity, agentic AI, AI coding and even the option to bring your own model (BYOM)
The mood of the session was much more down-to-earth and factual than at other conferences I used to go to. The understated German culture was evident in this session and in other sessions too, which was a relief for me as a VirtualDutchman.
CONTACT’s intention to grow is also visible in its recent acquisitions and partnerships, including a significant investment in team neusta SE.
You snooze, you lose.
Markus Dietrich (CEO, team neusta) then illustrated the complementary value they bring: modern front-end development, data-driven capabilities and dashboards on top of the CONTACT platform – the modern connected PLM in my terminology.
The trend, as Markus stated, is from components to systems, and in the long run from selling products to delivering products as a service.
Driven by economic survival, it is crucial for a sustainable, circular economy.
Companies should start exploring data-driven capabilities now – AI only performs reliably when the underlying data is correct and in the right context.
Hence the title: you snooze, you lose.
From Product Truth to Possible Futures – AI and the future of lifecycle management
Frank Patz-Brockmann, Chief Product Officer at CONTACT Software, gave an interesting presentation, discussing AI’s impact on PLM—particularly in engineering.
We already see what AI does in software development. And as the image below illustrates, the real human value is in dealing with the intent—the WHY behind what we do.
Of course, we should not forget that software changes are relatively cheap. A code change typically doesn’t affect the stock in the warehouse or your selected and approved suppliers, as it would in a mechanical world—one reason manufacturers push as many product features as possible into software.
Still, as Frank mentioned, creating engineering artifacts today is expensive and requires specific skills. As AI advances, authoring tools will likely become capabilities of the engineering system, while humans will still be needed to decide intent—the broader context AI cannot address through its trained models.
His ultimate conclusion: in the long run, traditional PLM systems built as the “Single Source of Truth” will be replaced or superseded by a collection of federated data sources, accessed and managed by AI agents. A statement that is supported by many of my forward-looking peers in the PLM community.
From systems to platforms to knowledge infrastructures.
After the guided tours—an excellent way to get a quick impression of sponsors grouped around a theme—it was time for the afternoon sessions.
From Connected R&D to Intelligent R&D: Apollo Tyres’ Digital Transformation Journey
I listened with great interest to Hizmy Hassen, Chief Digital Officer at Apollo Tyres. Having worked with tyre companies before, and having a soft Dutch spot for their Vredestein brand, much of his story felt familiar.
What caught my attention even more was their “New House strategy” as shown below:
Too often, I have seen companies start their transformation from their pains and wishes, wrapped in a project based on the known As-Is situation. External consultants like this approach too—it lets them sell interviews and reporting while getting paid to learn the company. It is the traditional business model, and I understand it.
However, I believe in a different approach: define the desired To-Be status from the company’s business strategy for the coming years, then derive the enterprise processes and the underlying data model needed to get there.
From there, you define the journey.
Instead of looking back and fixing what went wrong—an inherently negative mindset—the company looks forward, fostering a positive, aligned attitude when everyone is informed and on board.
Of course, Organizational Change Management becomes crucial here, as systems, the organization, and even business models can and must change.
I saw exactly this mindset in Hizmy’s New House strategy.
One of his best examples: introducing AI/automation as the natural way of working with data in a context where data is available. And as his concluding slide showed, this forward-looking approach is already delivering its first wins.
Success Under Extreme Conditions – What Enables Innovation Under Pressure
During the afternoon sessions, attendees chose from various tracks, and we concluded the day with an inspiring keynote from Jutta Kleinschmidt, a famous race car driver (Dakar), physicist and author, who shared how to succeed in an unpredictable environment.
After a great networking evening on board the Ocean Diva, sailing on the Rhine, we started Day 2 with an interesting opening session: the CONTACT software product management team shared their plans and roadmap.
Roadmap CONTACT Elements: opening the next chapter
What surprised me first was the roadmap’s level of detail. Most vendors talk about roadmaps but rarely share specifics or commit to capabilities before a release is actually available. Here, I saw the opposite.
Some random thoughts I noted down:
- CONTACT Elements is primarily a platform of connected capabilities. It provides a foundation through its Elements, and customization remains possible. I did not hear any Out-Of-The-Box messaging.
- The focus on delivering 3D Search capabilities surprised me somewhat, as I have seen this capability in typical PLM systems before. I also assumed there would be vendor-independent solutions in the market to connect to. Apparently not.
- The roadmap suggests the current mindset is still to deliver more and more standard, traditional PLM capabilities. This makes it harder to distinguish between being a platform and being a PLM system.
- Combining ALM and MBSE into a single Element suggests that the full complexity of managing systems—hardware and software—through a model-based approach is not yet fully developed. Both ALM and MBSE could be domains on their own, with many elements.
Of course, these are first impressions, and as I am not a CONTACT software insider, I am eager to learn more.
In the afternoon, there were more thematic sessions. I want to highlight one close to my heart:
Circular by Design – Anchoring Sustainability in Product Strategy
Comparing the agendas of the 2022 and 2024 editions with this year’s, I noticed sustainability has become less prominent — less hype, fewer dedicated topics. Understandable, as we’re overwhelmed by other immediate global challenges, despite the extreme climate warnings we’re facing.
That’s why I was glad to attend this session. In Europe, we see fewer specialized sustainability discussions; however, more and more companies are being forced to anchor sustainability in their product strategy—mainly due to regulations and, hopefully soon, genuine business benefits and customer demands.
Sebastian Weber gave a great overview of the industry’s current state and CONTACT Software’s approach, where other speakers shared their detailed sustainability experiences (this blog space is too short to mention everything. 🙄 I had much more to tell and digest, but I already passed my 1500-word deadline.)
As a core team member of the PLM Green Global Alliance (PGGA), I am happy to announce we’ll publish a dedicated interview with Sebastian on our PGGA channel in mid-October. There, we will definitely dive deeper into CONTACT software’s contribution to sustainability.
Conclusion
The CONTACT Open World conference was an eye-opener for me for several reasons. First, it was a warm, open community where I could discuss the typical challenges a medium-sized enterprise faces. Next, the clarity of the presentations and discussions helped me better understand where to position and recommend CONTACT software in the PLM domain as an exploration every potential customer should do.
CONTACT software is currently a niche player, but an interesting company that’s willing to expand. Keep them on your radar.
Next big event to meet
Those who follow my blog know that whenever I visit an event, I push myself to write a review the weekend after to share the experience. However, this time after the conference, I have been exploring further the Andalusian culture, making me realize that this is exactly what makes the conference different and stand out.
Where traditional conferences are often in cold high-tech places, efficiently to reach, making it for attendees an event in their comfort zone, the Share PLM Summit is held in a grand bodega in the unhurried scenery of Jerez de la Frontera.
An experience best described by Helena Alander in her recent post: “I have never taken the time to invest in myself.” – Read the post, she shares a great reflection.
As the focus of Share PLM is to focus on human-centric transformations, there is much more focus on the human experiences of people implementing transformations in their companies.
The human focus translates into a diverse audience and one big common theme for all, instead of a traditional industry or technology focus.
With more than a hundred attendees, the conference felt like a big family gathering where you can easily connect and learn from everyone. I believe this type of conference will be the future in the age of AI.
The many sponsors that joined the conference were also a part of the success. Without their support and human-centric messages, it would be hard to make this event sustainable 😉
If you want to read an impression of each session, Michael Finocchareo made a great effort to share the highlights of each session – you can find all his excellent reviews here: Share PLM Summit – Fino Summary Post Index.
And now some of my personal highlights from the conference!
The Role of People in Transformation Programs: Experience LEAN
An interesting learning experience was the session from Javier Sánchez, who is a plant manager at Kerry in Spain, about the implementation of LEAN at several plants in Spain.
Where initially we might think that PLM and plant operations are two different worlds, Javier was able to take us on the journey of implementing a LEAN program for the Spanish plants. There was so much communality to PLM implementations when dealing with behavioural change and the uncertainty of people.
Change can only happen when people in the organisation understand and trust what is going to happen and that they are part of a change for their benefit.
TRUST is the word that I noted down, and to build trust, you can see how Javier shared the org chart of the Kerry Sevilla plant – upside down – people at the top and the manager at the bottom to support everyone.
This image above really illustrates that you have a people-first approach.
Javier further elaborated on the difference of such an approach and how an organization can be fully engaged, as the picture below illustrates.
And after a successful implementation, Javier also warned about the rebound effect.
Where initially the excitement and energy come from the new situation, companies might slowly fall back into the traditional, as over time people have and bring their habits, the pyramid falls over as the image to the left illustrates and Javier shared several potential causes for such a rebound.
Important to see C-level change as #1 point, a point I have seen popping up in many PLM implementations too. After starting with a great vision, new people at the C-level come in questioning the vision (and strategy).
Note: GENBA is a term coming from LEAN, and is also relevant to PLM. It refers to the location where value is created—such as a factory floor, construction site, sales floor, or any workplace where the core work happens.
The concept emphasizes the importance of direct observation and engagement at the source of the action, rather than relying on reports or second-hand information.
It is a key principle in lean manufacturing and continuous improvement methodologies, encouraging leaders to “go to the GENBA” to understand problems and opportunities firsthand.
Combined with his great storytelling skills, Javier took us on an interesting story, very relevant for a human-centric approach and showing that we can learn from other disciplines.
Adapting PLM implementation strategy in evolving organizational realities
Susanna Mäentausta, also a guest in our Share PLM season 2 podcast with that time the title The ROI of Digitalization: A Deep Dive into Business Value gave an interesting lecture about her experiences with the PLM implementation at her current company, Novartis.
She excels in keeping her focus on both PLM business value and strategies to achieve this.
I knew Susanna from her earlier presentation at the Product Innovation 2019 conference in London. Here she stood out because of her strategic and tactical approach to implementing PLM – at that time at Kemira – where she was able to get PLM business benefits to be discussed at the C-level – it was more than a technical story.
You can read my observations from that time here: The weekend after PI PLMx London 2019
In her session this time, she explained all the challenges that she had to address at her current employer. It was not such a nice, linear step-by-step approach as presented by Andreas Wank earlier that day, talking about his implementation challenges at Pepperl & Fuchs.
Susanna’s tactics were all about securing the progress of the PLM project – design for change and awareness in the organisation. Javier Sanchez mentioned that the change at the C-level had a serious impact on the roadmap, as did both Susanna and Andreas. It remains a continuous point of attention when you want to guarantee a long-term outcome.
The image below says it all:
Susanne ended with some tactics:
- Design for non-removable anchor points that keep the PLM vision connected even when priorities shift.
- Define the non-negotiable cornerstone for the future: process & design frameworks and necessary authorities.
Her final recommendation was also interesting – the core team should have a clear long-term understanding of the future and work in an entrepreneurial mindset, meanwhile shielding execution from organizational politics.
Don’t get involved in politics – a recommendation that I also often shared, as politics is so much about emotions and subjective arguments, it’s better to work around it in silence.
The Human Advantage: Working and Leading in the Age of AI
Helena Gutierrez, well known as one of the founders of Share PLM and her AI-related newsletter, shared her positive view on how AI, in one way, destroyed Share PLM’s actual business practices, as a lot of material development now could be done with the help of AI in hours, compared to days of actual design work.
Companies won’t pay anymore for weeks of development of specific materials, she also pointed to the need for human skills in the future.
I think we agree on the fact that with AI, we will need people who can bridge and work with agentic AI to achieve unmet benefits for organisations. These people will have a special role; they are there for their human skills, combining emotion and logic, potentially a highly rewarding job, however, in smaller quantities than current knowledge workers in companies.
In my session Are Humans Still Resources?, I shared a pessimistic viewpoint and an optimistic end.
The pessimistic part is based on the fact that we humans run on our old biological hardware, the limbic brain, which urges us to save energy (think fast) and may lead to cognitive surrender. This situation might push companies to invest even more in AI and consider humans as a difficult resource to handle – are we back in the early days of the industrial revolution?
The optimistic side, which was also mentioned by others, and we see it happen, is that thanks to AI, the entrepreneur has a much easier life. A lot of the supporting activities for an entrepreneur can now be done using AI agents – the image below from this post by Dr.Sam Zolfagharian says it all:
For sure, the discussion will go on between the optimists and the realists (pessimists in disguise)
Scaling human capabilities
I am closing this impression with a train of thought that I can’t get out of my head. We can scale tools and resources with AI, leaving only a space for people with a combination of specific human skills – not only deep thinking, but also emotional and empathic roles, like healthcare providers, coaches and entertainers.
These roles are hard to scale – you become a coach by learning from experiences, and AI will not have an “experience transfer function.” How will business scale in the future, as we also see that junior roles in an organisation disappear due to AI?
The topic was also discussed in the interesting AI panel discussion – image above – with a mix of participants. It was a balanced discussion between tech, vision and reality and one of the highlights was the response from Susanna to a question from the audience:
“I don’t know.”
Have you ever seen someone honestly say this in a panel discussion? And what would AI respond? Great to see the human presence.
Where will humans build their experience and skills to think? I wrote about this already in March and have not yet answered: PLM, AI, and the Risk of Cognitive Surrender: A Call to Stay Sharp!
How to stay sharp in an AI-dominated world?
Conclusion
The Share PLM summit demonstrated again that a human-centric approach related to product lifecycle management has many benefits, as these shared experiences and outcomes from the discussions are directly applicable. Big kudos to the Share PLM team that dared to invest in such an event last year and exceeded expectations this year.
For those who want to learn more, join us at the upcoming event, Putting People in PLM: A Share PLM Summit Recap! and get excited.
For those who are interested in a lifetime, full-time job, watch this excellent short movie below:
Let me start with a confession: as a kid, I was a classic nerd, drawn to soccer and exact sciences. Math and physics weren’t just subjects—they were my playground.
During my education to become a teacher in Physics and Mathematics, I discovered something even more captivating: programming. It started with my first Apple IIe, where I tackled the challenge of programming with limited memory using machine language, analogue/digital interfaces, Pascal, and C.
Later, I turned to Visual Basic and C++, writing programs to simulate math scenarios, automate AutoCAD tasks, and later develop solutions on top of SmarTeam.
It was not just work—it was how I relaxed – structuring my thinking – would we call it now Vibe coding?
The upside of this experience? Technical and physical concepts never intimidated me – they helped me to see the bigger picture. I was wired to think deeply, patiently, and persistently—skills that have stayed with me ever since.
The switch to human
But then I got involved in training and mediating in PLM implementations, where I discovered that technical skills were needed; however, more important were understanding human behavior (not software), communication and PLM methodology skills.
Many implementations at that time stalled because everyone started with great enthusiasm until the results failed to materialize. The solution was not as expected, too unstable or not possible. And from the point of view of the users, it is too complex and frustrating for them. You can read one of my experiences from that time: Where is my ROI. Mister Voskuil
One of those many interesting discussions
But the budget was often finished, and the enthusiasm was gone. One of my favorite quotes at that time was:
“You never get a second first impression.”
indicating that from the start, you need to anticipate user acceptance, don’t think of a big bang approach and start with understanding and agreeing on the big picture before diving into the details.
How many of you have been in this situation?
Although the majority of people in the PLM community agree that human behavior can make or break a PLM implementation, the majority of discussions and focus are most of the time targeting tools and technologies.
#12 – digital skills related to the transformation
Organizational Change Management is often considered too soft to address, particularly in so-called result-driven organizations. Shut up and do the work!
Recently, some PLM software vendors mentioned OCM as an important activity, sometimes even provided by them. Their business model is to sell as many software licenses as possible, and therefore, they promise best-case scenarios and coverage of business scenarios.
Would you buy your PLM software from a company that says:
“Our software is great; however, you also need to address a business change program.”
Or would you buy from“We are a market leader in your business, and thousands of users are currently working happily with our software.”
I believe, with the experience as a PLM coach, that every PLM implementation should be a people and business discussion first – preferably sponsored at C-level – before jumping on the solutions.
The challenge of this approach is that a human-centric approach depends on people, often hard to scale, as it is a people business, not a software tools business.
Digital Transformation is failing
While preparing for the upcoming Share PLM summit in Jerez on May 19-20, I was looking back at why real digital transformation in the PLM domain is still failing – we keep on working mostly in a linear document-driven operating model.
My opinion at this moment: For existing organizations, the move from coordinated to coordinated and connected is too complex for humans.
Despite a great white paper from McKinsey on how organisations could move away from a linear, often document-driven organisation to an organisation working in multidisciplinary product teams, there is no real progress in most organisations.
Changing the organizational structure appears to be so difficult, and this relates to Conway’s Law, which states that systems reflect the organizational structure, presenting a challenge in determining where to start.
Not starting means not failing. And failing is the worst thing you can do at the C-level.
And now there is “product memory.”
Is the “product memory” based on an agentic AI layer and an underlying ontology, the next big thing after the connected digital enterprise? Initially formulated by Benedict Smith and later translated to a more PLM-specific scope by Martin Eigner and Oleg Shilovitsky, we are trying to combine the (boring) systems of record data with all the reasoning and decision-making – that’s where the knowledge is sitting.
You can follow the thought experiments when reading the True Intelligence newsletters from the start.
A theme that came up also in other “the future of PLM” discussions was that traditional PLM only stores the results of a development and delivery process, but the reasoning is missing.
In my opinion, Colab Software was one of the first complementary to PLM startups, with a focus on capturing the discussions and decisions during a design review, as the older image below shows – also, Colab Software is now much more advanced with an AI-supported infrastructure.
Still, the image shows the value; the reasoning that was captured from the communication between different stakeholders in the product development process during design reviews.
More in the traditional PLM domain, Martin and Oleg started developing the tconcept of an agentic AI enterprise driven by a graph-based layer on top of existing enterprise systems as Martin’s image illustrates below.
Where Oleg stays (for me) more in the traditional PLM enterprise world:
e.g., his post Product Memory Architecture: How PLM Loses Engineering Knowledge and What Comes Next,
Martin zoomed in on his day-to-day customer base in Germany when writing
this post: The Actual Concept of Product Memory based on a Digital Thread with a vision for the upcoming 5 years.
In addition, less PLM-focused but very data-driven, Jan Bosch wrote a complementary post on his blog related to
the agentic AI approach: From Copilot to Colleague – the rise of agentic AI.
An interesting quote from this post, valid for us all:
Agent systems require investment in data architecture, workflow mapping, governance frameworks and operational monitoring. Those investments compound. The organization that has deployed agents across its revenue cycle, supply chain and finance operations simultaneously develops deep operational expertise in running agentic systems, which is itself a form of competitive advantage.
And while finalizing this post, there was an interesting discussion related to product memory at The Future of PLM: Introducing Product Memory organized by Fino, also known as Michael Finocchiaro
As a “techie,” I was able to enjoy and follow the discussion about a future infrastructure related to product knowledge. The term “product memory” seems a little overhyped, as if information that is not directly accessible through agents is a cause of failure. The big elephant in the room is where and how to start.
Enjoy the dialogue here:
What about a product memory trauma?
In the past, when discussing knowledge graphs, I already posed the question:
“How can knowledge graphs unlearn?”
In the techie world, there was always a hypothetical response for this question, but will it happen in a product memory environment where not everything is 100 percent exact and correct? Patrick Hillberg, one of the few PLM teachers, can educate you all about seemingly small mistakes with a big impact.
During the product memory discussion, I heard a statement that only validated data is allowed to be part of the memory.
Has anyone thought about the utopia of this statement?
The ambitious statement that product memory would lead to a single source of truth is, for me, also a utopia. 100 percent correct data does not exist, nor will 100 percent accurate decisions exist. It will be the most likely truth for the moment.
Now compare this with the human brain; when a serious accident happens, the person involved might have trauma from that. Then you need a psychiatrist to fix the trauma, meaning create other memory constructs – rewiring the brain.
While seeing this interesting dialogue with Rob Ferrone (the original Product Data PLuMber) about how Quick Release became a significant consultancy firm with the pragmatic focus on making the data flow (old image below), I had a new thought.
With Rob’s entrepreneurial skills, he might be able to start a new company soon, fixing product memory traumas – as data-governance becomes a commodity.
Will the product data plumber become the first product memory shrink?
Conclusion
We are experiencing a fast-moving convergence on future PLM concepts, where the image from Martin Eigner nicely represents such a possible architecture based on “product memory”. The challenge I see is whether we would be able to implement such an architecture to be reliable and supported by humans. Because humans still have their old hardware, the limbic brain, that will try to escape from the perfect world with a single source of truth – they like their truth
This was 2025 – this year, same atmosphere, more experienced & bigger and more to discuss.
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