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In nearly twenty years of coaching PLM implementations, I’ve noticed something striking: these projects often mirror politics—not just in complexity, but in the blame game that follows when things go wrong.
When something goes wrong, people rarely see it as an opportunity to solve the issue together. They look for someone to blame instead.
That happens in politics and in Product Lifecycle Management. I wrote about it in 2019, The PLM Blame Game—and most of those observations still hold—although the emphasis has shifted.
But what if the real issue isn’t the system or the technology? What if it’s the human connections—or lack thereof—that determine success?
Political systems/ PLM approaches
In democracies, everyone debates priorities, but progress is slow. Stakeholders defend their own interests, consultants favor preferred solutions, and vendors promise the moon. Long-term plans such as digital transformation often stall.
The result is familiar: each leadership change resets ambitions, leaving users with mixed messages and less commitment – sounds familiar in PLM?.
From: Communication charts around the world
Then there are the autocracies, where a single dominant view determines the path. Usually, that view comes not from the CEO but from the CFO or CIO. These leaders often have a limited understanding of product lifecycle management and instead rely on trusted networks.
That is why some companies choose SAP because “all enterprises run on SAP” or Teamcenter because “everyone in automotive uses Teamcenter.” Strategic consultants reinforce the same pattern with their own preferred solutions.
The result: Surface-level alignment, but resistance beneath the surface—another familiar PLM scenario.
From: Communication charts around the world – 2014 China
In smaller companies, a populist version often appears. Without a strong strategic layer, the loudest voices from vendors and implementers shape the company’s view. That is the riskiest setup because vision and strategy are effectively outsourced. Early in my career, I often heard:
“You know solution XYZ, so tell us what to do.”
The result is predictable: no one in the company feels a true sense of ownership of the business outcome – the type of situations I have been mediating the most.
Of course, the analogy is imperfect. Countries usually lack competition, so citizens cannot simply switch. Still, it is a useful way to frame what happens in PLM.
They – not us – are the problem!
In the past, debates focused on who was to blame for project problems, often blaming the stakeholder who was not at the table.
Vendors and implementers blamed customers, vendors and customers blamed implementers, and implementers blamed vendors. My role in PLM mediations was to get everyone into the same room.
But one issue always remained:
Blaming the customer is difficult when the customer is assumed to be right – They are paying the bill and not always with pleasure.
Why 70 % of PLM implementations fail – or not?
For decades, we have heard horror stories about failed PLM implementations, each supposedly explained by one simple cause.
Depending on who tells the story, the culprit is the software, the company culture, poor user involvement, or unrealistic ambitions without a budget or understanding.
But the truth is more nuanced: many of these implementations did not actually fail completely.
People react strongly to the word failure because no one wants to be associated with it.
Yet, in software, ‘failing fast’ is often celebrated—it’s a way to adapt early. PLM is slowly catching on, with the rise of Minimum Viable Product (MVP) approaches. Instead of waiting for a ‘perfect’ big-bang rollout, companies now start with a working foundation and iterate as needs emerge.”
That only works if the company owns its vision and strategy. An MVP approach also demands end-to-end stakeholder involvement, because everyone contributes to the solution. At the same time, our limbic brain works against us: it pushes us to protect what we know and react strongly to change.
That reaction shows up in PLM projects too. The loudest critics get the most attention, which makes it easy to conclude a program failed—even when it is working for most people who have adapted to the change.
And now, a new trend has emerged:
PLM systems are failing!
Now, a new claim is gaining traction: PLM systems themselves are failing. With the rise of AI, traditional vendors are being blamed for failing to provide the right infrastructure or opportunities for AI-enabled capabilities.
After years of success built on legacy platforms, vendors now face growing pressure from opinion leaders calling for change.
Martin Eigner has made this point in several posts:
- Why We’re “Optimizing” Problems We Created Ourselves
- 50 % failure rate is not an accident
- My vision for the next 5 years
Oleg Shilovitsky has made similar arguments:
- Did We Solve PLM, or Just Learn How to Describe It?
- Who can replace the big three PLM and why that may be the wrong question in the Age of AI?
- Is Product Memory Just a New Name for PLM?
Prof. Dr. Jörg W. Fischer wrote:
- Will we ever solve PLM? We did, but AI has taken over.
- Digitalization has failed to deliver on its central promise! Why?
Doug Macdonald wrote about the shortcomings of Legacy PLM, which most companies imagine/practice:
- The shortcomings of Legacy PLM
- Could you manage the development of a toothbrush in a Legacy PLM system
I agree with much of this critique, for sure, if you still consider PLM a system rather than a product lifecycle management strategy implemented through a federated infrastructure of systems.
The posts I referred to highlight real problems from the past and suggest that new insights and AI might help us build better businesses. The question is whether that promise will be fulfilled.
Creating the human thread
AI could help businesses break through organizational silos by pulling together information across functions.
That would make concepts such as the digital thread and digital twin easier to implement without relying on dedicated interfaces.
This shift creates both opportunity and risk.
If AI reduces the need for siloed optimization, traditional middle-management roles will change. The key question is whether companies are willing to rethink their structures or stay constrained by Conway’s Law.
It could also make many methodology debates less important.
Today, we as consultants often promote methodologies shaped by our own experience or vendor narratives. The long-running eBOM–mBOM debate is a good example. Across industries and platforms, the answer is often more straightforward than the discussion suggests.
As AI absorbs more collective knowledge, the role of PLM experts and consultants will shift. At the Share PLM Summit in Jerez, we discussed what should come next: a stronger focus on human connection.
That is why I use the term human thread: the network of relationships that connects people across the business. Michael Finochario (Fino) touches on the same shift in his post on the changing balance between humans and technology, in his review of my session in Jerez.
Others are moving in the same direction. This week, Helene Älander shared a post that makes a similar point.
Helene’s post and the related discussion suggest a growing belief that transformation depends less on technology alone and more on human connection and motivation inside the company.
A quote from Helene’s post, and I recommend reading the full post and thread.
One lesson has stayed with me ever since:
Transformation rarely fails because of technology. It slows down when the distance between executive ambition and middle-management reality becomes too large.
For now, I call this the need for the human thread. A successful transformation starts with an end-to-end human connection across the business, with people treating that connection as a shared priority.
Because people are intrinsically motivated by a human connection.
The human thread requires a new approach, new forms of workshops and learning sessions where leaders, managers, and employees work together on the desired business flow.
Helene Älander points in this direction, and Share PLM supports it through initiatives such as Share The Nest.
Also this year at the Share PLM Summit in Jerez, Andreas Wank described how Pepperl+Fuchs made a breakthrough by bringing people together. As Fino in his review post quoted:
No one on the team wanted to make a decision because every decision affected someone else. So they put 30 people in one room for a week and forced them to make decisions. Not perfect decisions. Working hypotheses. That was a critical insight: In PLM, waiting for perfect certainty kills momentum.
The year before, at the 2025 Share PLM Summit, Andrea Järvrén already shared a similar lesson, describing how Tetra Pak used design sprints to advance its PLM work by prioritizing human interaction.
It is an unstoppable trend – the human thread popping up in more and more conversations.
Conclusion
The time for blaming systems, technology, and methodology should fade into the background. Companies need to focus on building business flow through the human thread—the human connections that drive commitment, motivation, and change.
So, here is the question: Are we ready to stop blaming systems and start building the human thread? Or will we keep repeating the same patterns, just with fancier technology?
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:
Last week I listened to a Dutch podcast that gave me an unexpected inspiration. The podcast “Zo Simpel is het Niet” (“It is not that simple “in English) is a podcast with a focus on economic topics and trends, not at all about PLM, sometimes a little about the effects of digital transformation and AI is more and more mentioned.
The episode I listened to was about the decline of literacy in the Netherlands. The conclusion is based on research discussed from the PISA test from the OECD. Learn more about the OECD and PISA test here on this Wiki page.
I asked Notebook LM to make an English slide deck from the podcast – You can download the deck HERE.
The conclusion: We are in a free fall in the Netherlands (image below) and likely in other countries too, because we are reading less, writing less, and consequently thinking less deeply.
Social media was identified as one of the root causes. Short-form content, the endless scroll, the dopamine loop of likes and shares — it is all rewiring how we process information – short-term, quick results without building deeper skills.
And then the connection between social media and the drop in literacy and science skills hit me. We are doing the same thing at the moment with AI!
Third Way of Thinking
In my posts, I sometimes refer to Daniel Kahneman’s book and his research: Thinking Fast and Slow, as this is for me a foundational theory for understanding human behavior.
Kahneman describes our brain as a combination of System 1, which is the fast, intuitive brain (low energy), and System 2, which is the slow, deliberative one (burns energy). As humans, we avoid using energy when thinking, although nowadays, outside our brains, we are hooked to fossil energy 😉.
Next, I read a research from Steven Shaw and Gideon Nave, from The Wharton School of the University of Pennsylvania, that indicated that AI is going to have an additional impact on our behavior as humanity.
Their paper Thinking—Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender introduces System 3 as artificial cognition. External, automated, data-driven reasoning that lives not in your brain but in the cloud.
Their central finding is something they call “cognitive surrender” – access to AI made people more confident, regardless of whether the AI was right or wrong. An enforcement of the Dunning-Kruger effect?
The most vulnerable are people with higher trust in AI, lower need for cognition, and lower fluid intelligence, who showed the greatest cognitive surrender. The least critical thinkers delegate most, and then feel most certain about the result.
Benedict Smith, my True Intelligence friend, pointed to the same pattern in his post: When the Graph talks back. Read it and think!
Both their conclusions made me even more worried, combined with the results of the Dutch literacy developments – are we all racing downhill?
I believe our brain is a muscle. Like any muscle, it needs resistance to stay strong. You do not become a better cyclist by riding an eBike everywhere — the motor does the work, and your legs lose the real strength needed when you are without your bike. The same applies to cognitive effort.
We Have Been Here Before
It is not the first time a transformative technology arrived with enormous promise and created a deeply unequal outcome. The Industrial Revolution reduced most workers to resources while a few became extraordinarily wealthy.
John D. Rockefeller (oil & railroad industries), Andrew Carnegie (steel industry), J.P. Morgan (financing the new industries) and Cornelius Vanderbilt (shipping and railroads) as examples.
These industry leaders did not care so much about humans, and it took roughly a hundred years — and the rise of labour unions — to begin correcting that imbalance.
The AI revolution is moving much faster! And if history teaches us anything, it is that working more efficiently with new tools does not automatically raise your value. The more companies invest in AI solutions, the more pressure there will be to develop your individual skills.
Efficiency without insight is a commodity.
My friend Helena Guitierrez wrote this weekend this supporting post: Preparing for AI Adoption
What does it mean for Product Lifecycle Management?
Purposefully, I wrote Product Lifecycle Management to focus on the strategy, and not an all-around capable PLM system, as PLM systems have never quite delivered on their original promise.
The PLM vendors benefited from selling the dream, the consultants benefited from its complexity and the users, initially engineers and later more stakeholders in the product lifecycle, often suffered under rigid processes and complex systems. As the systems were designed to store information. User-friendlyness was not a priority.
Will AI, being layered on top of PLM and other enterprise systems, be the solution for these underperforming systems?
Oleg Shilovitsky believes in that, as you can read in his recent post: PLM’s OpenClaw Moment: How AI Agents Will Break Closed Systems
The risk is that we repeat the same pattern. AI will be positioned as the solution to problems actually caused by poor implementation and insufficient investment in the human side of change.
There is an interesting discussion ongoing about the future of PLM infrastructures, well described recently by Rainer Mewaldt in his post: What would a 𝗣𝗟𝗠 𝘀𝘆𝘀𝘁𝗲𝗺 look like if it were 𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗱 𝗳𝗼𝗿 𝗔𝗜 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗴𝗿𝗼𝘂𝗻𝗱 𝘂𝗽?
The principles are there, like 10 years ago, before AI became hyped, when we discussed digital transformation as moving from a coordinated infrastructure to a coordinated and connected infrastructure, with a mix of Systems of Record and Systems of Engagement.
I have not seen much progress with the customers I have been working with in the past five to ten years. The change did not seriously happen due to the need for new ways of working, different people skills and organizational change.
Will it happen now with the AI-wave? A question Ilan Madjar also asked this weekend.
What should we – companies and individuals – actually do?
As an approach, the research from Wharton suggests that using rewards (incentives) and providing feedback can help people stay mentally engaged and avoid disengaging or losing motivation.
In other words, these strategies can combat the tendency to mentally “check out” or stop trying.
When participants were rewarded for accuracy and received immediate feedback, their override rates on faulty AI roughly doubled.
This observation means we should design AI-assisted workflows so that people remain accountable for outcomes and receive clear feedback when AI-assisted decisions go wrong. Work to do for startups and existing PLM vendors to develop the best combination of agents and content.
BUT: do not let the AI absorb the accountability while the human takes the credit – System 3!
Companies are in an uncomfortable situation. Before AI became the focus for improving businesses, the most heard statement was:
“Our employees are our assets – they create the value of our company,”
And this is one of the reasons that HR departments exist. Although not all HR departments are there for the employees – their role is to balance the HUMAN RESOURCES in a company – we are still talking about resources.
With AI, the new statement might be
“Our AI-supported employees are our assets, where part of the asset value comes from the AI tools used”.
This raises the question of who will remain as the AI-supported employee. We already see that entry-level jobs in any type of business get replaced by AI, creating stress on the job market. This, combined with the observed reduced mastery of deep-skills in math, reading and science, as described in the PISA research earlier shared in this post, puts a generation at risk.
Like the winners of the Industrial Revolution, the winners of the AI revolution do not care about humans – they care about profits.
As individuals, we need to keep on training our brain-muscles without AI where the muscle matters. As the Dutch podcast mentioned: write your first draft before asking Claude to improve it, think through a problem before asking ChatGPT to solve it, and read a book of 100 pages.
In PLM, judgment and contextual reasoning are the core of what people need to do. You should protect the practice of doing that work yourself. Use AI to accelerate and refine, not to replace the effort that builds competence.
Invest in yourself to remain independent. Read broadly — actually read, not skim AI summaries. The people who will remain valuable in an AI-saturated world are not the ones who prompt best, but the ones who can evaluate, challenge, and contextualise what AI produces.
And with that, I want to come back to the post from Helena Guitierrez that I mentioned before, where she focused on what we can do as individuals.
Helena is one of the founders of Share PLM, a company with the purpose: BUILDING A HUMAN-CENTERED DIGITAL FUTURE, as is written on their website. We both believe that in order to enjoy the AI revolution, we have to invest in ourselves. The above image illustrates steps to take- click on the image for the full post.
Talking about the human-centered digital future, have a look at the agenda of the upcoming Share PLM Summit on 19-20 May in Jerez de la Frontera (Spain) – our sessions and discussions will, of course, be based on PLM and AI experiences, with the focus on what it means for humans – it will not be a technology conference.
Conclusion
The Wharton researchers close with a question worth “What happens when our judgments are shaped by minds not our own?” Their answer so far: we become more confident, less accurate when the AI is wrong, and largely unaware of the difference – a big risk.
The challenge is not artificial intelligence. The challenge is whether we will remain genuinely intelligent in the presence of it – take care of yourself!
What do you think? I am looking forward to your comments and feedback.
Recently, I have been reading some interesting posts beyond all the technical discussions related to PLM and AI. Is PLM becoming obsolete? Are we heading to a new type of infrastructure based on MCP agents? Are these agents an example of new ways of collaboration?
Collaboration – it pops up everywhere!
Here is a quote from the article that triggered me:
The 𝐧𝐮𝐦𝐛𝐞𝐫 𝐨𝐧𝐞 𝐫𝐞𝐚𝐬𝐨𝐧 organizations deploy MBSE is not simulation or architecture development. It is 𝐞𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐜𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧 — at 67%. But here is the uncomfortable part.
Only 24% reported actually achieving collaboration as a business outcome. That is a 43-point gap between intent and result. Traceability is even worse — 48% deploy MBSE for it, 9% say they have realized it.
What if the problem is not that MBSE fails to deliver collaboration — but that most organizations 𝐧𝐞𝐯𝐞𝐫 𝐝𝐞𝐟𝐢𝐧𝐞 𝐰𝐡𝐚𝐭 𝐛𝐞𝐭𝐭𝐞𝐫 𝐜𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 𝐥𝐨𝐨𝐤𝐬 𝐥𝐢𝐤𝐞 in measurable terms?
Chad Jackson’s article aligns with many other discussions I had with companies related to PLM (and MBSE) – itinspired me to focus this time on collaboration.
How do we measure collaboration?
My 2015 blog post has the same title: How do you measure collaboration? The post was written at a time when PLM collaboration had to compete with ERP execution stories. Often, engineering collaboration was considered an inefficient process to be fixed in the future, according to some ERP vendors.
ERP always had a strong voice at the management level—boxes on an org chart, reporting lines, clear ownership and KPIs flowing upward. You could see how the company was performing.
From the management side, accountability flows downward. The architecture of the organization mirrors the architecture of the product, and the architecture of the product mirrors the architecture of the organization.
We have known this for decades; it is Conway’s Law. Yet we are still surprised when silos emerge exactly where we designed them.
The Management Dilemma
In many of my engagements, the company’s management often struggles to understand the value of collaboration because there is no direct line between collaboration and immediate performance. Revenue can be measured. Cycle times can be measured. Defects can be measured. Even employee turnover can be measured.
But collaboration? What is the KPI?
It is a fair question. If something cannot be quantified, it becomes subjective and depends on gut feelings. And if it cannot be tied directly to quarterly results, it often becomes optional.
The problem is not that collaboration has no impact on performance – look at the introduction of email in companies. Did your company make a business case for that?
Still, it improved collaboration a lot, and sometimes it became a burden with all the CC-messages and epistles exchanged.
Collaboration has an impact, deeply and systematically. But its impact is indirect, delayed, and distributed. It reduces friction, can improve shared understanding and prevent expensive rework.
The return on investment on collaboration is real, but it does not show up as a clean, linear metric.
For a hierarchical and linearly structured organization, horizontal collaboration is often hard to “sell.”
Back to Conway’s Law
Organizational structure shapes communication patterns. Communication patterns shape systems.
If your organization is vertical, your product will be vertical. If your incentives are local, your decisions will be local. If your teams are isolated, your solutions will be fragmented.
You cannot expect horizontal behavior from a vertically optimized structure without friction.
Disconnected collaboration initiatives fail because they try to overlay horizontal tools on top of vertical incentives.
Attempts like a new collaboration platform or using shared workspace technology to incentivize collaboration are examples of this approach.
But the underlying structure remains untouched. People are still measured on local performance. Budgets are still allocated per department. Promotions still reward vertical success.
First question to ask in your company: Who is responsible for your PLM/collaboration infrastructure for non-transactional information?
Most likely, it is in the IT or Engineering silo, rarely on a higher organizational level.
And then we are surprised when collaboration stalls?
The Myth of the Tool
Whenever collaboration becomes a pain, people look for IT tools as a cure.
“We need better platforms.”
“We need integrated systems.”
and now:
“We need AI – the AI agents will do the collaboration for us.”
Tools matter, but they are amplifiers. They amplify existing behavior. They do not create it. While finalizing this article, I saw this post from Dr. Sebastian Wernicke coming in, containing this quote:
Agents are software. Maturity is culture. And culture, inconveniently, doesn’t come with an install package.
If trust is low, a collaboration platform becomes a battlefield. If incentives are misaligned, shared dashboards become weapons. If fear dominates, transparency becomes a threat.
Collaboration is not a software problem. It is a human problem. Which brings us to something that is rarely discussed in boardrooms: the intrinsic motivation of its employees.
The Limbic Brain Is Always There
Beneath the rational layer of strategy and planning sits something older: the limbic system. The part of us that cares about belonging, safety, recognition, autonomy, and purpose.
Collaboration thrives when the limbic brain’s needs are met. It collapses when they are threatened.
- If people feel unsafe, they protect information!
- If they feel undervalued, they withdraw effort!
- If they feel controlled, they resist alignment!
You cannot mandate collaboration if the emotional system of the organization is defensive.
The question is not “How do we force collaboration?”
The question is “How do we create conditions where collaboration feels natural?”
And that requires leaders to connect to the human, not just to the role or an artificial intelligence solution. They should be inspired by this iconic image from Share PLM:
Besides a difficult-to-quantify ROI, there is another reason why collaboration struggles to gain executive traction: it rarely creates immediate success.
It prevents future failure, and we humans in general do not prioritize prevention, thinking of our environmental, financial and potential even health behavior. Where prevention has the lowest cost, most of the time, fixing the damage lies in our nature.
For companies, it is easier to celebrate the hero who fixes a late-stage integration disaster than the quiet team that prevented it months earlier through cross-functional dialogue.
For me, the firefighters are the biggest challenge to successfully implementing a PLM infrastructure. The image to the left comes from a 2014 presentation when discussing potential resistance to a successful PLM implementation.
In vertical systems, firefighting is visible. Prevention is silent and therefore collaboration activities feel like a cost center rather than a strategic lever.
Where to Push, Where to Invest?
If you cannot directly measure collaboration, where should you push? Not in tools alone, slogans or one-off workshops. Invest in shared experiences.
When people meet outside their vertical silos, something subtle shifts. They see faces instead of functions. They understand constraints instead of assuming incompetence. They replace narratives with conversations.
Note: shared experiences are not the same as planned online webmeetings that became popular during and after COVID. They have a rigid regime of collaboration enforcement, back-to-back in many companies, most of the time lacking the typical “coffee machine” experiences.
Also, when looking at events where people share experiences, there is a difference between a traditional vertical PLM/CM/IT/ERP conference where specialists focus on one discipline and on the other side, a human-centric conference, where humans share their experiences in an organization.
The Share PLM Summit in May last year was an eye-opener for me. Starting from the human perspective brought a lot of energy and willingness to discuss various insights – collaboration at its best.
Events, summits, workshops—when done well—create human connection. They remind participants that behind every deliverable sits a person trying to do meaningful work.
The focus on the human perspective is not soft. It is strategic because collaboration is not primarily about information exchange. It is about relationship quality and trust.
The Real Question
The question is not whether collaboration is valuable. The question is whether we are willing to adjust our vertical incentives to make it possible.
Because collaboration is not free, it requires time. It requires emotional energy. It requires psychological safety. It sometimes requires giving up local control for global benefit.
In systems terms, it requires shifting from local optimization to whole-system optimization.
That is uncomfortable.
But if our products are complex, interconnected, and rapidly evolving—as most are today—then vertical thinking alone is no longer sufficient. The world has become horizontal, even if our org charts have not.
And perhaps the real challenge is not how to measure collaboration, but how to design organizations where collaboration is no longer something we need to sell at all. An article from McKinsey might inspire you here for this transition – for me, it did: Toward an integrated technology operating model.
Beyond AI
While everyone talks and writes about AI, I do not believe AI will solve the collaboration issue. For sure, AI collaboration with agents will increase personal and organizational effectiveness, but it never touches our limbic brain, the irreplaceable part that makes us typical humans and unique.
There will always be a need for that, unless we become numb and addicted to the AI environments. There are various studies popping up on how AI “untrains” our brain muscles, reduces patience and deep thinking. Finding a new human balance is crucial.
Conclusion
Triggered by Chad Jackson’s post about MBSE and collaboration, I took the time to deep-dive into the aspects of collaboration in the PLM domain. How do you manage collaboration?
Come and share your experiences at the upcoming Share PLM 2026 summit from 19-20 May in Jerez. The title of my keynote: Are Humans Still Resources? Agentic AI and the Future of Work and PLM.
December is the last month when daylight is getting shorter in the Netherlands, and with the end of the year approaching, this is the time to reflect on 2025.
For me, it has been an interesting year, and I hope it has been similar for you. I started 2025 with this post: My 2025 focus, sharing the topics that would drive my primary intentions—a quick walk through some of these topics and what to reflect on what I have learned.
Fewer blog posts
It was already clear that AI-generated content was going to drown the blogging space. The result: Original content became less and less visible, and a self-reinforcing amount of general messages reduced further excitement.
As I have no commercial drive to be visible, I will continue to write posts only when relevant to personal situations or ideas, with the intention of being shared and discussed with the readers of my posts – approximate 26 / year.
Therefore, if you are still interested in content that has not been generated with AI, I recommend subscribing to my blog and interacting directly with me through the comments, either on LinkedIn or via a direct message.
More podcast recordings
Together with the Share PLM podcast team, Beatriz Gonzales and Maria Morris, we enjoyed talking with a large variety of people active in PLM, all having their personal stories related to PLM to share—each episode ending with an experience to share and a desired takeaway for the listeners. We did it with great pleasure and learned from each episode.
You can find all the recordings from 2025 (Season 3) here.
In Season 4, we want to add the C-level perspective to our PLM and People podcast discussions.
#DataCentric or #PeopleCentric ?
It was PeopleCentric first at the beginning of the year, with the Share PLM Summit in Jerez and DataCentric in the second half of the year, with activities connected to the PLM Roadmap/PDT Europe conference in Paris.
In case you missed the excitement and lessons learned, here they are:
- The weekend after the Share PLM Summit 2025
- A week after Shaping the Future of PLM – No time to lose!
- A very long week after PLM Roadmap / PDT Europe 2025
Both topics will become even more critical due to the impact of AI tools on our day-to-day work.
Sustainability?
Already an uncomfortable term for some of us at the beginning of 2025, it has become one of the best-kept secrets of 2025. Where traditional countries and companies revert to their short-term bad habits – optimize shareholders value, there are also forward-looking enterprises that are actively rephrasing their sustainable strategies as risk mitigation strategies with the awareness that adaptation is inevitable. Better start early than too late – not a typical human strategy.
In case you are interested, I recommend you read and listen to:
And now it is time to discuss AI.
With all the investments and marketing related to AI, it is unavoidable to neglect it. For sure, it is a hype, but I believe that we are into something revolutionary for society, like the impact of the industrial revolution on our society 150 years ago.
However, there are also the same symptoms of the .com-hype 25 years ago.
Who are going to be the winners? Currently, the hardware, datacenter and energy providers, not the AI-solution providers. But this can change.
Let’s look into some of the potential benefits.
Individual efficiency?
Many of the current AI tools allow individuals to perform better at first sight. Suddenly, someone who could not write understandable (email) messages, draw images or create structured presentations now has a better connection with others—the question to ask is whether these improved efficiencies will also result in business benefits for an organization.
Looking back at the introduction of email with Lotus Notes, for example, email repositories became information siloes and did not really improve the intellectual behavior of people.
Later, Microsoft took over the dominant role as the office software provider with enhanced search and storage capabilities, but still, most of the individual knowledge remained hidden or inaccurate as it missed the proper context.
As a result of this, some companies tried to reduce the usage of individual emails and work more and more in communities with a specific context. Also, due to COVID and improved connectivity, this led to the success of Teams. And now with Copilot embedded in the Microsoft suite, I am curious to learn what companies perceive as measurable business benefits.
The chatbot?
For many companies, the chatbot is a way to reduce the number of people active in customer relations, either sales or services. I believe that, combined with the usage of LLMs, an improvement in customer service can be achieved. Or at least the perception, as so far I do not recall any interaction with a chatbot to be specific enough to solve my problem.
The risks with AI?
Now I may sound like a boomer who started focusing on knowledge management 25 years ago – exploring tacit knowledge.
Tacit knowledge is the knowledge a real expert has by combining different areas of expertise and understanding what makes sense.
Could tacit knowledge be replaced by an external model that gives you all the (correct?) answers?
In verifiable situations, we know when the model is hallucinating – but what if the scope is beyond our understanding? Would we still rely on AI, and could AI be manipulated in ways that we lose touch with the real facts?
Already, the first research papers are coming out warning of reduced human cognitive performance, e.g., this paper: Beware of Metacognitive Laziness: Effects of Generative Artificial Intelligence on Learning, Motivation, Processes, and Performance.
Combined with laziness (a typical human behavior – system 1), these results made me think of a statement made by Sean Illing:
“People love the truth, but they hate facts.”
A statement highly relevant to what we see happening now with social media – we do not think or research deep enough anymore, we select the facts that we like and consider them our truth.
What happens in our PLM domain?
In the PLM domain, companies are indeed reluctant to use LLMs directly, where some of them use RAG (Retrieval-Augmented Generation) to feed the LLM with a relevant context.
Still, the answers require human interpretation, as you cannot avoid hallucinations in your product lifecycle management processes.
As long as the results are based on inconsistent data sources that lack the relevant context, the answers are of low quality.
Meanwhile, every vendor in the PLM space is now offering AI-agents, most of the time within their own portfolio space. The ultimate dream is polygot agents (who are buying them / who are developing them) that can work together and create a new type of agility beyond traditional workflows. An interesting article in this context comes from Oleg Shilovitsky: Why Does PLM Need Task Re-Engineering Before It Can Have AI?
Still, these potential “quick” fixes create a risk for companies in the long term. Buying AI tools does not fix the foundation that is based on legacy.
In particular, related to the Shape the Future of PLM – Together workshop in Paris on Nov 4th, the consensus was that companies need to invest in understanding and implementing domain-specific ontologies and semantic models to provide a data-driven infrastructure that allows AI to make accurate decisions or valid recommendations.
You can read the summary of the event and recommendations here: Accelerating the Future of PLM & ALM on the ArrowHead’s website.
You can also read this post from Ole Olesen-Bagneux: Why will 2026 be the year of the ontologist?
Although the topics in the workshop might look “too advanced” for your company, they are crucial to transform into a long-term, sustainable, data-driven, model-based, and AI-supported enterprise.
Somewhere, you have to cross the chasm from documents to data in context.
Being busy is not an excuse, as you can also read in Thomas Nys’s LinkedIn post: Your Engineers spend 40 % of their time maintaining yesterday’s shortcuts. And you’re wondering why your AI initiative isn’t moving faster. I loved the image.
Human Resources?
The AI revolution will have an impact on society, and it is up to us individuals how well we adapt.
Remember, the first 50 – 100 years of the Industrial Revolution made only a few people extremely rich. James Watt, the Rothschild family, Andrew Carnegie, John D. Rockefeller, Cornelius Vanderbilt, J.P. Morgan, Alfred Krupp and the Schneider family became so rich due to ownership of factories and machinery, the control of raw materials (coal, iron, oil), the use of new technology (steam power, mechanization) combined with access to cheap labor and weak labor laws and limited competition early on.
Most humans moved into urbanized areas to become nothing but cheap resources, even children. And remember, many of us are still human resources!
A new conspiracy?
In 2016, Ida Auken’s lecture at the WEF created traction during COVID among people who believed in conspiracies. Her story focused on a more circular economy with respect for the Earth’s resources. The story was framed into the message:
“In the future, you will own nothing and be happy.”
The conspiracy theorist believed all their possessions would be taken away by the elite in the long term.
I want to conclude with a new message for these conspiracy theorists active on X or other discussion fora:
“In the future, you will know nothing, and you won’t be aware enough to care.”
Conclusion
2026 is going to be an interesting year, where we cannot allow ourselves to sit still and watch what is happening. Active participation is more challenging but also more rewarding than being a consumer. In May 2026, I hope to meet some of you at the Share PLM Summit in Jerez and share the human side, followed by the PDM Roadmap/PDT Europe conference in Q4 in Gothenburg, where we will catch up on the technical and data side.
I am wishing you all a wise and happy/healthy 2026
Last week, I wrote about the first day of the crowded PLM Roadmap/PDT Europe conference.
You can still read my post here in case you missed it: A very long week after PLM Roadmap / PDT Europe 2025
My conclusion from that post was that day 1 was a challenging day if you are a newbie in the domain of PLM and data-driven practices. We discussed and learned about relevant standards that support a digital enterprise, as well as the need for ontologies and semantic models to give data meaning and serve as a foundation for potential AI tools and use cases.
This post will focus on the other aspects of product lifecycle management – the evolving methodologies and the human side.
Note: I try to avoid the abbreviation PLM, as many of us in the field associate PLM with a system, where, for me, the system is more of an IT solution, where the strategy and practices are best named as product lifecycle management.
And as a reminder, I used the image above in other conversations. Every company does product lifecycle management; only the number of people, their processes, or their tools might differ. As Peter Billelo mentioned in his opening speech, the products are why the company exists.
Unlocking Efficiency with Model-Based Definition
Day 2 started energetically with Dennys Gomes‘ keynote, which introduced model-based definition (MBD) at Vestas, a world-leading OEM for wind turbines.
Personally, I consider MBD as one of the stepping stones to learning and mastering a model-based enterprise, although do not be confused by the term “model”. In MBD, we use the 3D CAD model as the source to manage and support a data-driven connection among engineering, manufacturing, and suppliers. The business benefits are clear, as reported by companies that follow this approach.
However, it also involves changes in technology, methodology, skills, and even contractual relations.
Dennys started sharing the analysis they conducted on the amount of information in current manufacturing drawings. The image below shows that only the green marker information was used, so the time and effort spent creating the drawings were wasted.
It was an opportunity to explore model-based definition, and the team ran several pilots to learn how to handle MBD, improve their skills, methodologies, and tool usage. As mentioned before, it is a profound change to move from coordinated to connected ways of working; it does not happen by simply installing a new tool.
The image above shows the learning phases and the ultimate benefits accomplished. Besides moving to a model-based definition of the information, Dennys mentioned they used the opportunity to simplify and automate the generation of the information.
Vestas is on a clear path, and it is interesting to see their ambition in the MBD roadmap below.
An inspirational story, hopefully motivating other companies to make this first step to a model-based enterprise. Perhaps difficult at the beginning from the people’s perspective, but as a business, it is a profitable and required direction.
Bridging The Gap Between IT and Business
It was a great pleasure to listen again to Peter Vind from Siemens Energy, who first explained to the audience how to position the role of an enterprise architect in a company compared to society. He mentioned he has to deal with the unicorns at the C-level, who, like politicians in a city, sometimes have the most “innovative” ideas – can they be realized?
To answer these questions, Peter is referring to the Business Capability Model (BCM) he uses as an Enterprise Architect.
Business Capabilities define ‘what’ a company needs to do to execute its strategy, are structured into logical clusters, and should be the foundation for the enterprise, on which both IT and business can come to a common approach.
The detailed image above is worth studying if you are interested in the levels and the mappings of the capabilities. The BCM approach was beneficial when the company became disconnected from Siemens AG, enabling it to rationalize its application portfolio.
Next, Peter zoomed in on some of the examples of how a BCM and structured application portfolio management can help to rationalize the AI hype/demand – where is it applicable, where does AI have impact – and as he illustrated, it is not that simple. With the BCM, you have a base for further analysis.
Other future-relevant topics he shared included how to address the introduction of the digital product passport and how the BCM methodology supports the shift in business models toward a modern “Power-as-a-Service” model.
He concludes that having a Business Capability Model gives you a stable foundation for managing your enterprise architecture now and into the future. The BCM complements other methodologies that connect business strategy to (IT) execution. See also my 2024 post: Don’t use the P** word! – 5 lessons learned.
Holistic PLM in Action.
or companies struggling with their digital transformation in the PLM domain, Andreas Wank, Head of Smart Innovation at Pepperl+Fuchs SE, shared his journey so far. All the essential aspects of such a transformation were mentioned. Pepperl+Fuchs has a portfolio of approximately 15,000 products that combine hardware and software.
It started with the WHY. With such a massive portfolio, business innovation is under pressure without a PLM infrastructure. Too many changes, fragmented data, no single source of truth, and siloed ways of working lead to much rework, errors, and iterations that keep the company busy while missing the global value drivers.
Next, the journey!
The above image is an excellent way to communicate the why, what, and how to a broader audience. All the main messages are in the image, which helps people align with them.
The first phase of the project, creating digital continuity, is also an excellent example of digital transformation in traditional document-driven enterprises. From files to data align with the From Coordinated To Connected theme.
Next, the focus was to describe these new ways of working with all stakeholders involved before starting the selection and implementation of PLM tools. This approach is so crucial, as one of my big lessons learned from the past is: “Never start a PLM implementation in R&D.”
If you start in R&D, the priority shifts away from the easy flow of data between all stakeholders; it becomes an R&D System that others will have to live with.
You never get a second, first impression!
Pepperl+Fuchs spends a long time validating its PLM selection – something you might only see in privately owned companies that are not driven by shareholder demands, but take the time to prepare and understand their next move.
As Andreas also explained, it is not only about the functional processes. As the image shows, migration (often the elephant in the room) and integration with the other enterprise systems also need to be considered. And all of this is combined with managing the transition and the necessary organizational change.
Andreas shared some best practices illustrating the focus on the transition and human aspects. They have implemented a regular survey to measure the PLM mood in the company. And when the mood went radical down on Sept 24, from 4.1 to 2.8 on a scale of 1 to 5, it was time to act.
They used one week at a separate location, where 30 of his colleagues worked on the reported issues in one room, leading to 70 decisions that week. And the result was measurable, as shown in the image below.
Andreas’s story was such a perfect fit for the discussions we have in the Share PLM podcast series that we asked him to tell it in more detail, also for those who have missed it. Subscribe and stay tuned for the podcast, coming soon.
Trust, Small Changes, and Transformation.
Ashwath Sooriyanarayanan and Sofia Lindgren, both active at the corporate level in the PLM domain at Assa Abloy, came with an interesting story about their PLM lessons learned.
To understand their story, it is essential to comprehend Assa Abloy as a special company, as the image below explains. With over 1000 sites, 200 production facilities, and, last year, on average every two weeks, a new acquisition, it is hard to standardize the company, driven by a corporate organization.
However, this was precisely what Assa Abloy has been trying to do over the past few years. Working towards a single PLM system, with generic processes for all, spending a lot of time integrating and migrating data from the different entities became a mission impossible.
To increase user acceptance, they fell into the trap of customizing the system ever more to meet many user demands. A dead end, as many other companies have probably experienced similarly.
And then they came with a strategic shift. Instead of holding on to the past and the money invested in technology, they shifted to the human side.
The PLM group became a trusted organisation supporting the individual entities. Instead of telling them what to do (Top-Down), they talked with the local business and provided standardized PLM knowledge and capabilities where needed (Bottom-Up).
This “modular” approach made the PLM group the trusted partner of the individual business. A unique approach, making us realize that the human aspect remains part of implementing PLM
Humans cannot be transformed
Given the length of this blog post, I will not spend too much text on my closing presentation at the conference. After a technical start on DAY 1, we gradually moved to broader, human-related topics in the latter part.
You can find my presentation here on SlideShare as usual, and perhaps the best summary from my session was given in this post from Paul Comis. Enjoy his conclusion.
Conclusion
Two and a half intensive days in Paris again at the PLM Roadmap / PDT Europe conference, where some of the crucial aspects of PLM were shared in detail. The value of the conference lies in the stories and discussions with the participants. Only slides do not provide enough education. You need to be curious and active to discover the best perspective.
For those celebrating: Wishing you a wonderful Thanksgiving!
This week is busy for me as I am finalizing several essential activities related to my favorite hobby, product lifecycle management or is it PLM😉?
And most of these activities will result in lengthy blog posts, starting with:
“The week(end) after <<fill in the event>>”.
Here are the upcoming actions:
Click on each image if you want to see the details:
In this Future of PLM Podcast series, moderated by Michael Finocciaro, we will continue the debate on how to position PLM (as a system or a strategy) and move away from an engineering framing. Personally, I never saw PLM as a system and started talking more and more about product lifecycle management (the strategy) versus PLM/PDM (the systems).
Note: the intention is to be interactive with the audience, so feel free to post questions/remarks in the comments, either upfront or during the event.
You might have seen in the past two weeks some posts and discussions I had with the Share PLM team about a unique offering we are preparing: the PLM Awareness program. From our field experience, PLM is too often treated as a technical issue, handled by a (too) small team.
We believe every PLM program should start by fostering awareness of what people can expect nowadays, given the technology, experiences, and possibilities available. If you want to work with motivated people, you have to involve them and give them all the proper understanding to start with.
Join us for the online event to understand the value and ask your questions. We are looking forward to your participation.
This is another event related to the future of PLM; however, this time it is an in-person workshop, where, inspired by four PLM thought leaders, we will discuss and work on a common understanding of what is required for a modern PLM framework. The workshop, sponsored by the Arrowhead fPVN project, will be held in Paris on November 4th, preceding the PLM Roadmap/PDT Europe conference.
We will not discuss the term PLM; we will discuss business drivers, supporting technologies and more. My role as a moderator of this event is to assist with the workshop, and I will share its findings with a broader audience that wasn’t able to attend.
Be ready to learn more in the near future!
Suppose you have followed my blog posts for the past 10 years. In that case, you know this conference is always a place to get inspired, whether by leading companies across industries or by innovative and engaging new developments. This conference has always inspired and helped me gain a better understanding of digital transformation in the PLM domain and how larger enterprises are addressing their challenges.
This time, I will conclude the conference with a lecture focusing on the challenging side of digital transformation and AI: we humans cannot transform ourselves, so we need help.
At the end of this year, we will “celebrate” our fifth anniversary of the PLM Green Global Alliance. When we started the PGGA in 2020, there was an initial focus on the impact of carbon emissions on the climate, and in the years that followed, climate disasters around the world caused serious damage to countries and people.
How could we, as a PLM community, support each other in developing and sharing best practices for innovative, lower-carbon products and processes?
In parallel, driven by regulations, there was also a need to improve current PLM practices to efficiently support ESG reporting, lifecycle analysis, and, soon, the Digital Product Passport. Regulations that push for a modern data-driven infrastructure, and we discussed this with the major PLM vendors and related software or solution partners. See our YouTube channel @PLM_Green_Global_Alliance
In this online Zoom event, we invite you to join us to discuss the topics mentioned in the announcement. Join us in this event and help us celebrate!
I am closing that week at the PTC/User Benelux event in Eindhoven, the Netherlands, with a keynote speech about digital transformation in the PLM domain. Eindhoven is the city where I grew up, completed my amateur soccer career, ran my first and only marathon, and started my career in PLM with SmarTeam. The city and location feel like home. I am looking forward to discussing and meeting with the PTC user community to learn how they experience product lifecycle management, or is it PLM😉?
With all these upcoming events, I did not have the time to focus on a new blog post; however, luckily, in the 10x PLM discussion started by Oleg Shilovitsky there was an interesting comment from Rob Ferrone related to that triggered my mind. Quote:
The big breakthrough will come from 1. advances in human-machine interface and 2. less % of work executed by human in the loop. Copy/paste, typing, voice recognition are all significant limits right now. It’s like trying to empty a bucket of water through a drinking straw. When tech becomes more intelligent and proactive then we will see at least 10x.
This remark reminded me of one of my first blog posts in 2008, when I was trying to predict what PLM would look like in 2050. I thought it is a nice moment to read it (again). Enjoy!
PLM in 2050
As the year ends, I decided to take my crystal ball to see what would happen with PLM in the future. It felt like a virtual experience, and this is what I saw:
- Data is no longer replicated – every piece of information will have a Universal Unique ID, also known as a UUID. In 2020, this initiative became mature, thanks to the merger of some big PLM and ERP vendors, who brought this initiative to reality. This initiative dramatically reduced exchange costs in supply chains and led to bankruptcy for many companies that provided translation and exchange software.
- Companies store their data in ‘the cloud’ based on the concept outlined above. Only some old-fashioned companies still handle their own data storage and exchange, as they fear someone will access their data. Analysts compare this behavior with the situation in the year 1950, when people kept their money under a mattress, not trusting banks (and they were not always wrong)
- After 3D, a complete virtual world based on holography became the next step in product development and understanding. Thanks to the revolutionary quantum-3D technology, this concept could even be applied to life sciences. Before ordering a product, customers could first experience and describe their needs in a virtual environment.
- Finally, the cumbersome keyboard and mouse were replaced by voice and eye recognition. Initially, voice recognition
and eye tracking were cumbersome. Information was captured by talking to the system and by recording eye movements during hologram analysis. This made the life of engineers so much easier, as while researching and talking, their knowledge was stored and tagged for reuse. No need for designers to send old-fashioned emails or type their design decisions for future reuse - Due to the hologram technology, the world became greener. People did not need to travel around the world, and the standard became virtual meetings with global teams(airlines discontinued business class). Even holidays can be experienced in the virtual world thanks to a Dutch initiative inspired by coffee. The whole IT infrastructure was powered by efficient solar energy, drastically reducing the amount of carbon dioxide.
- Then, with a shock, I noticed PLM no longer existed. Companies were focusing on their core business processes. Systems/terms like PLM, ERP, and CRM no longer existed. Some older people still remembered the battle between those systems over data ownership and the political discomfort this caused within companies.
- As people were working so efficiently, there was no need to work all week. There were community time slots when everyone was active, but 50 per cent of the time, people had time to recreate (to re-create or recreate was the question). Some older French and German designers remembered the days when they had only 10 weeks holiday per year, unimaginable nowadays.
As we still have more than 40 years to reach this future, I wish you all a successful and excellent 2009.
I am looking forward to being part of the green future next year.
In recent months, I’ve noticed a decline in momentum around sustainability discussions, both in my professional network and personal life. With current global crises—like the Middle East conflict and the erosion of democratic institutions—dominating our attention, long-term topics like sustainability seem to have taken a back seat.
But don’t stop reading yet—there is good news, though we’ll start with the bad.
The Convenient Truth
Human behavior is primarily emotional. A lesson valuable in the PLM domain and discussed during the Share PLM summit. As SharePLM notes in their change management approach, we rely on our “gator brain”—our limbic system – call it System 1 and System 2 or Thinking Fast and Slow. Faced with uncomfortable truths, we often seek out comforting alternatives.
The film Don’t Look Up humorously captures this tendency. It mirrors real-life responses to climate change: “CO₂ levels were high before, so it’s nothing new.” Yet the data tells a different story. For 800,000 years, CO₂ ranged between 170–300 ppm. Today’s level is ~420 ppm—an unprecedented spike in just 150 years as illustrated below.
Frustratingly, some of this scientific data is no longer prominently published. The narrative has become inconvenient, particularly for the fossil fuel industry.
Persistent Myths
Then there is the pseudo-scientific claim that fossil fuels are infinite because the Earth’s core continually generates them. The Abiogenic Petroleum Origin theory is a fringe theory, sometimes revived from old Soviet science, and lacks credible evidence. See image below
Oil remains a finite, biologically sourced resource. Yet such myths persist, often supported by overly complex jargon designed to impress rather than inform.
The Dissonance of Daily Life
A young couple casually mentioned flying to the Canary Islands for a weekend at a recent birthday party. When someone objected on climate grounds, they simply replied, “But the climate is so nice there!”
“Great climate on the Canary Islands”
This reflects a common divide among young people—some are deeply concerned about the climate, while many prioritize enjoying life now. And that’s understandable. The sustainability transition is hard because it challenges our comfort, habits, and current economic models.
The Cost of Transition
Companies now face regulatory pressure such as CSRD (Corporate Sustainability Reporting Directive), DPP (Digital Product Passport), ESG, and more, especially when selling in or to the European market. These shifts aren’t usually driven by passion but by obligation. Transitioning to sustainable business models comes at a cost—learning curves and overheads that don’t align with most corporations’ short-term, profit-driven strategies.
However, we have also seen how long-term visions can be crushed by shareholder demands:
- Xerox (1970s–1980s) pioneered GUI, the mouse, and Ethernet, but failed to commercialize them. Apple and Microsoft reaped the benefits instead.
- General Electric under Jeff Immelt tried to pivot to renewables and tech-driven industries. Shareholders, frustrated by slow returns, dismantled many initiatives.
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My presentation at the 2019 PLM Roadmap / PDT Europe conference – click on the image to get access through SlideShare.
- Despite ambitious sustainability goals, Siemens faced similar investor pressure, leading to spin-offs like Siemens Energy and Gamesa.
The lesson?
Transforming a business sustainably requires vision, compelling leadership, and patience—qualities often at odds with quarterly profit expectations. I explored these tensions again in my presentation at the PLM Roadmap/PDT Europe 2024 conference, read more here: Model-Based: The Digital Twin.
I noticed discomfort in smaller, closed-company sessions, some attendees said, “We’re far from that vision. ”
My response: “That’s okay. Sustainability is a generational journey, but it must start now”.
Signs of Hope
Now for the good news. In our recent PGGA (PLM Green Global Alliance) meeting, we asked: “Are we tired?” Surprisingly, the mood was optimistic.
Our PGGA core team meeting on June 20th
Yes, some companies are downscaling their green initiatives or engaging in superficial greenwashing. But other developments give hope:
- China is now the global leader in clean energy investments, responsible for ~37% of the world’s total. In 2023 alone, it installed over 216 GW of solar PV—more than the rest of the world combined—and leads in wind power too. With over 1,400 GW of renewable capacity, China demonstrates that a centralized strategy can overcome investor hesitation.
- Long-term-focused companies like Iberdrola (Spain), Ørsted (Denmark), Tesla (US), BYD, and CATL (China) continue to invest heavily in EVs and batteries—critical to our shared future.
A Call to Engineers: Design for Sustainability
We may be small at the PLM Green Global Alliance, but we’re committed to educating and supporting the Product Lifecycle Management (PLM) community on sustainability.
That’s why I’m excited to announce the launch of our Design for Sustainability initiative on June 25th.
Led by Eric Rieger and Matthew Sullivan, this initiative will bring together engineers to collaborate and explore sustainable design practices. Whether or not you can attend live, we encourage everyone to engage with the recording afterward.
Conclusion
Sustainability might not dominate headlines today. In fact, there’s a rising tide of misinformation, offering people a “convenient truth” that avoids hard choices. But our work remains urgent. Building a livable planet for future generations requires long-term vision and commitment, even when it is difficult or unpopular.
So, are you tired—or ready to shape the future?
Wow, what a tremendous amount of impressions to digest when traveling back from Jerez de la Frontera, where Share PLM held its first PLM conference. You might have seen the energy from the messages on LinkedIn, as this conference had a new and unique daring starting point: Starting from human-led transformations.
Look what Jens Chemnitz, Linda Kangastie, Martin Eigner, Jakob Äsell or Oleg Shilovitsky had to say.
For over twenty years, I have attended all kinds of PLM events, either vendor-neutral or from specific vendors. None of these conferences created so many connections between the attendees and the human side of PLM implementation.
We can present perfect PLM concepts, architectures and methodologies, but the crucial success factor is the people—they can make or break a transformative project.
Here are some of the first highlights for those who missed the event and feel sorry they missed the vibe. I might follow up in a second post with more details. And sorry for the reduced quality—I am still enjoying Spain and refuse to use AI to generate this human-centric content.
The scenery
Approximately 75 people have been attending the event in a historic bodega, Bodegas Fundador, in the historic center of Jerez. It is not a typical place for PLM experts, but an excellent place for humans with an Andalusian atmosphere. It was great to see companies like Razorleaf, Technia, Aras, XPLM and QCM sponsor the event, confirming their commitment. You cannot start a conference from scratch alone.
The next great differentiator was the diversity of the audience. Almost 50 % of the attendees were women, all working on the human side of PLM.
Another brilliant idea was to have the summit breakfast in the back of the stage area, so before the conference days started, you could mingle and mix with the people instead of having a lonely breakfast in your hotel.
Now, let’s go into some of the highlights; there were more.
A warm welcome from Share PLM
Beatriz Gonzalez, CEO and co-founder of Share PLM, kicked off the conference, explaining the importance of human-led transformations and organizational change management and sharing some of their best practices that have led to success for their customers.
You might have seen this famous image in the past, explaining why you must address people’s emotions.
Working with Design Sprints?
Have you ever heard of design sprints as a methodology for problem-solving within your company? If not, you should read the book by Jake Knapp- Creator of Design Sprint.
Andrea Järvén, program manager at Tetra Pak and closely working with the PLM team, recommended this to us. She explained how Tetra Pak successfully used design sprints to implement changes. You would use design sprints when development cycles run too looong, Teams lose enthusiasm and focus, work is fragmented, and the challenges are too complex.
Instead of a big waterfall project, you run many small design sprints with the relevant stakeholders per sprint, coming step by step closer to the desired outcome.
The sprints are short – five days of the full commitment of a team targeting a business challenge, where every day has a dedicated goal, as you can see from the image above.
It was an eye-opener, and I am eager to learn where this methodology can be used in the PLM projects I contribute.
Unlocking Success: Building a Resilient Team for Your PLM Journey
Johan Mikkelä from FLSmidth shared a great story about the skills, capacities, and mindset needed for a PLM transformational project.
Johan brought up several topics to consider when implementing a PLM project based on his experiences.
One statement that resonated well with the audience of this conference was:
The more diversified your team is, the faster you can adapt to changes.
He mentioned that PLM projects feel like a marathon, and I believe it is true when you talk about a single project.
However, instead of a marathon, we should approach PLM activities as a never-ending project, but a pleasant journey that is not about reaching a finish but about step-by-step enjoying, observing, and changing a little direction when needed.
Strategic Shift of Focus – a human-centric perspective
Besides great storytelling, Antonio Casaschi‘s PLM learning journey at Assa Abloy was a perfect example of why PLM theory and reality often do not match. With much energy and experience, he came to Assa Abloy to work on the PLM strategy.
He started his PLM strategies top-down, trying to rationalize the PLM infrastructure within Assa Abloy with a historically bad perception of a big Teamcenter implementation from the past. Antonio and his team were the enemies disrupting the day-to-day life of the 200+ companies under the umbrella of Assa Abloy.
A logical lesson learned here is that aiming top-down for a common PLM strategy is impossible in a company that acquires another six new companies per quarter.
His final strategy is a bottom-up strategy, where he and the team listen to and work with the end-users in the native environments. They have become trusted advisors now as they have broad PLM experience but focus on current user pains. With the proper interaction, his team of trusted advisors can help each of the individual companies move towards a more efficient and future-focused infrastructure at their own pace.
The great lessons I learned from Antonio are:
- If your plan does not work out, be open to failure. Learn from your failures and aim for the next success.
- Human relations—I trust you, understand you, and know what to do—are crucial in such a complex company landscape.
Navigating Change: Lessons from My First Year as a Program Manager
Linda Kangastie from Valmet Technologies Oy in Finland shared her experiences within the company, from being a PLM key user to now being a PLM program manager for the PAP Digi Roadmap, containing PLM, sales tools, installed base, digitalization, process harmonization and change management, business transformation—a considerable scope.
The recommendations she gave should be a checklist for most PLM projects – if you are missing one of them, ask yourself what you are missing:
- THE ROADMAP and THE BIG PICTURE – is your project supported by a vision and a related roadmap of milestones to achieve?
- Biggest Buy-in comes with money! – The importance of a proper business case describing the value of the PLM activities and working with use cases demonstrating the value.
- Identify the correct people in the organization – the people that help you win, find sparring partners in your organization and make sure you have a common language.
- Repetition – taking time to educate, learn new concepts and have informal discussions with people –is a continuous process.
As you can see, there is no discussion about technology– it is about business and people.
To conclude, other speakers mentioned this topic too; it is about being honest and increasing trust.
The Future Is Human: Leading with Soul in a World of AI
Helena Guitierez‘s keynote on day two was the one that touched me the most as she shared her optimistic vision of the future where AI will allow us to be so more efficient in using our time, combined, of course, with new ways of working and behaviors.
As an example, she demonstrated she had taken an academic paper from Martin Eigner, and by using an AI tool, the German paper was transformed into an English learning course, including quizzes. And all of this with ½ day compared to the 3 to 4 days it would take the Share PLM team for that.
With the time we save for non-value-added work, we should not remain addicted to passive entertainment behind a flat screen. There is the opportunity to restore human and social interactions in person in areas and places where we want to satisfy our human curiosity.
I agree with her optimism. During Corona and the introduction of teams and Zoom sessions, I saw people become resources who popped up at designated times behind a flat screen.
The real human world was gone, with people talking in the corridors at the coffee machine. These are places where social interactions and innovation happen. Coffee stimulates our human brain; we are social beings, not resources.
Death on the Shop Floor: A PLM Murder Mystery
Rob Ferrone‘s theatre play was an original way of explaining and showing that everyone in the company does their best. The product was found dead, and Andrea Järvén alias Angie Neering, Oleg Shilovitsky alias Per Chasing, Patrick Willemsen alias Manny Facturing, Linda Kangastie alias Gannt Chartman and Antonio Casaschi alias Archie Tect were either pleaded guilty by the public jury or not guilty, mainly on the audience’s prejudices.
You can watch the play here, thanks to Michael Finocchiaro :
According to Rob, the absolute need to solve these problems that allow products to die is the missing discipline of product data people, who care for the flow, speed, and quality of product data. Rob gave some examples of his experience with Quick Release project he had worked with.
My learnings from this presentation are that you can make PLM stories fun, but even more important, instead of focusing on data quality by pushing each individual to be more accurate—it seems easy to push, but we know the quality; you should implement a workforce with this responsibility. The ROI for these people is clear.
Note: I believe that once companies become more mature in working with data-driven tools and processes, AI will slowly take over the role of these product data people.
Conclusion
I greatly respect Helena Guitierez and the Share PLM team. I appreciate how they demonstrated that organizing a human-centric PLM summit brings much more excitement than traditional technology—or industry-focused PLM conferences. Starting from the human side of the transformation, the audience was much more diverse and connected.
Closing the conference with a fantastic flamenco performance was perhaps another excellent demonstration of the human-centric approach. The raw performance, a combination of dance, music, and passion, went straight into the heart of the audience – this is how PLM should be (not every day)
There is so much more to share. Meanwhile, you can read more highlights through Michal Finocchiaro’s overview channel here.
As human beings, we believe in the truth. We claim the truth. During my holiday in Greece, the question was, did the Greek Prime Minister tell the truth about the internal spy scandal?
In general, we can say, politicians never speak the real truth, and some countries are trying to make sure there is only one single source of truth – their truth. The concept of a Single Source Of Truth (SSOT) is difficult to maintain in politics.
On social media, Twitter and Facebook, people are claiming their truth. But unfortunately, without any scientific background, people know better than professionals by cherry-picking messages, statistics or even claiming non-existing facts.
Nicely described in The Dunning-Kruger effect. Unfortunately, this trend will not disappear.
If you want to learn more about the impact of social media, read this long article from The Atlantic: Why the Past 10 Years of American Life Have Been Uniquely Stupid. Although the article is about the US, the content is valid for all countries where social media are still allowed.
The PLM and CM domain is the only place where people still rely on the truth defined by professionals. Manufacturing companies depend on reliable information to design, validate, manufacture and support their products. Compliance and safe products require an accurate and stable product definition based on approved information. Therefore, the concept of SSOT is crucial along the product lifecycle.
The importance may vary depending on the product type. The difference in complexity between an airplane and a plastic toy, for example. It is all about the risk and impact of a failure caused by the product.
During my holiday, the SSOT discussion was sparked on LinkedIn by Adam Keating, and the article starts with:
The “Single Source of Truth (SSOT)” wasn’t built for you. It was built for software vendors to get rich. Not a single company in the world has a proper SSOT.
A bit provocative, as there is nothing wrong with software vendors being profitable. Profitability guarantees the long-time support of the software solution. Remember the PLM consolidation around 2006, when SmarTeam, Matrix One (Dassault), Agile and Eigner & Partner (Oracle) were acquired, disappeared or switched to maintenance mode.
Therefore it makes sense to have a profitable business model or perhaps a real open source business model.
Still, the rest of the discussion was interesting, particularly in the LinkedIn comments. Adam mentioned the Authoritative Source of Truth (ASOT) as the new future. And although this concept becomes more and more visible in the PLM domain, I believe we need both. So, let’s have a look at these concepts.
Truth 1.0 – SSOT
Historically, manufacturing companies stored the truth in documents, first paper-based, later in electronic file formats and databases.
The truth consists of drawings, part lists, specifications, and other types of information.
Moreover, the information is labeled with revisions and versions to identify the information.
By keeping track of the related information through documents or part lists with significant numbers, a person in the company could find the correct corresponding information at any stage of the lifecycle.
Later, by storing all the information in a central (PLM) system, the impression might be created that this system is the Single Source Of Truth. The system Adam Keating agitated against in his LinkedIn post.
Although for many companies, the ERP has been the SSOT (and still is). All relevant engineering information was copied into the ERP system as attached files. Documents are the authoritative, legal pieces of information that a company shares with suppliers, authorities, or customers. They can reside in PLM but also in ERP. Therefore, you need an infrastructure to manage the “truth.”
Note: The Truth 1.0 story is very much a hardware story.
Even for hardware, ensuring a consistent single version of the truth for each product remains difficult. In theory, its design specifications should match the manufacturing definition. The reality, however, shows that often this is not the case. Issues discovered during the manufacturing process are fixed in the plant – redlining the drawing – is not always processed by engineering.
As a result, Engineering and Manufacturing might have a different version of what they consider the truth.
The challenge for a service engineer in the field is often to discover the real truth. So the “truth” might not always be in the expected place – no guaranteed Single Source Of Truth.
Configuration Management is a discipline connected to PLM to ensure that the truth is managed so that as-specified, as-manufactured, and as-delivered information has been labeled and documented unambiguously. In other words, you could say Configuration Management(CM) is aiming for the Single Source Of Truth for a product.
If you want to read more about the relation between PLM and CM – read this post: PLM and Configuration Management (CM), where I speak with Martijn Dullaart about the association between PLM and CM.
Martijn has his blog mdux.net and is the Lead Architect for Enterprise Configuration Management at our Dutch pride ASML. Martijn is also Chairperson I4.0 Committee IPX Congress.
Summarizing: The Single Source Of Truth 1.0 concept is document-based and should rely on CM practices, which require skilled people and the right methodology. In addition, some industries require Truth 1.0.
Others take the risk of working without solid CM practices, and the PLM system might create the impression of the SSOT; it will not be the case, even for only hardware.
Truth 2.0 – ASOT
Products have become more complex, mainly due to the combination of electronics and software. Their different lifecycles and the speed of change are hard to maintain using the traditional PLM approach of SSOT.
It will be impossible to maintain an SSOT, particularly if it is based on documents.
As CM is the discipline to ensure data consistency, it is important to look into the future of CM. At the end of last year, I discussed this topic with 3 CM thought leaders. Martijn Dullaart, Maxime Gravel and Lisa Fenwick discussed with me what they believe the change would be. Read and listen here: The future of Configuration Management.
From the discussion, it became clear that managing all the details is impossible; still, you need an overreaching baseline to identify the severity and impact of a change along the product lifecycle.
New methodologies can be developed for this, as reliable data can be used in algorithms to analyze a change impact. This brings us to the digital thread. According to the CIMdata definition used in the A&D digital twin phase 2 position paper:
The digital thread provides the ability for a business to have an Authoritative Source of Truth(ASOT), which is information available and connected in a core set of the enterprise systems across the lifecycle and supplier networks
The definition implies that, in the end, a decision is made on data from the most reliable, connected source. There might be different data in other locations. However, this information is less reliable. Updating or fixing this information does not make sense as the effort and cost of fixing will be too expensive and give no benefit.
Obviously, we need reliable data to implement the various types of digital twins.
As I am intrigued by the power of the brain – its strengths and weaknesses – the concept of ASOT can also be found in our brains. Daniel Kahneman’s book, Thinking Fast and Slow talks about the two systems/modes our brain uses. The Fast one (System 1 – low energy usage) could be the imaginary SSOT, whereas the Slow one (System 2 – high energy required) is the ASOT. The brain needs both, and I believe this is the same in our PLM domain.
A new PLM Paradigm
In this context, there is a vivid discussion about the System of Record and Systems of Engagement. I wrote about it in June (post: A new PLM paradigm); other authors name it differently, but all express a similar concept. Have a look at these recent articles and statements from:
| Author | Link to content |
|
Authentise
|
The challenge of cross-discipline collaboration ……. |
|
Beyond PLM
|
When is the right time to change your PLM system + discussion |
|
Colab
|
The Single Source Of Truth wasn’t built for you ……. |
|
Fraunhofer institute
|
Killing the PLM Monolith – the Emergence of cloud-native System Lifecycle Management (SysLM) |
|
SAAB Group
|
Don’t mix the tenses. Managing the Present and the Future in an MBSE context |
|
Yousef Hooshmand
|
From a Monolithic PLM Landscape to a Federated Domain and Data Mesh |
If you want to learn more about these concepts and discuss them with some of the experts in this domain, come to the upcoming PLM Roadmap PTD Europe conference on 18-19 October in Gothenburg, Sweden. Have a look at the final agenda here
Register before September 12 to benefit from a 15 % Early Bird discount, which you can spend for the dinner after day 1. I look forward to discussing the SSOT/ASOT topics there.
Conclusion
The Single Source Of Truth (SSOT) and the Authoritative Source of Truth (ASOT) are terms that illustrate the traditional PLM paradigm is changing thanks to digitization and connected stakeholders. The change is in the air. Now, the experience has to come. So be part of the change and discuss with us.
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