Last week, my memory was triggered by this LinkedIn post and discussion started by Oleg Shilovitsky: Rethinking the Data vs. Process Debate in the Age of Digital Transformation and AI.

me, 1989
In the past twenty years, the debate in the PLM community has changed a lot. PLM started as a central file repository, combined with processes to ensure the correct status and quality of the information.
Then, digital transformation in the PLM domain became achievable and there was a focus shift towards (meta)data. Now, we are entering the era of artificial intelligence, reshaping how we look at data.
In this technology evolution, there are lessons learned that are still valid for 2025, and I want to share some of my experiences in this post.
In addition, it was great to read Martin Eigner’s great reflection on the past 40 years of PDM/PLM. Martin shared his experiences and insights, not directly focusing on the data and processes debate, but very complementary and helping to understand the future.
It started with processes (for me 2003-2014)
In the early days when I worked with SmarTeam, one of my main missions was to develop templates on top of the flexible toolkit SmarTeam.
For those who do not know SmarTeam, it was one of the first Windows PDM/PLM systems, and thanks to its open API (COM-based), companies could easily customize and adapt it. It came with standard data elements and behaviors like Projects, Documents (CAD-specific and Generic), Items and later Products.
On top of this foundation, almost every customer implemented their business logic (current practices).
And there the problems came …..
The implementations became too much a highly customized environment, not necessarily thought-through as every customer worked differently based on their (paper) history. Thanks to learning from the discussions in the field supporting stalled implementations, I was also assigned to develop templates (e.g. SmarTeam Design Express) and standard methodology (the FDA toolkit), as the mid-market customers requested. The focus was on standard processes.
You can read my 2009 observations here: Can chaos become order through PLM?
The need for standardization?
When developing templates (the right data model and processes), it was also essential to provide template processes for releasing a product and controlling the status and product changes – from Engineering Change Request to Engineering Change Order. Many companies had their processes described in their ISO 900x manual, but were they followed correctly?
In 2010, I wrote ECR/ECO for Dummies, and it has been my second most-read post over the years. Only the 2019 post The importance of EBOM and MBOM in PLM (reprise) had more readers. These statistics show that many people are, and were, seeking education on general PLM processes and data model principles.
It was also the time when the PLM communities discussed out-of-the-box or flexible processes as Oleg referred to in his post..
You would expect companies to follow these best practices, and many small and medium enterprises that started with PLM did so. However, I discovered there was and still is the challenge with legacy (people and process), particularly in larger enterprises.
The challenge with legacy
The technology was there, the usability was not there. Many implementations of a PLM system go through a critical stage. Are companies willing to change their methodology and habits to align with common best practices, or do they still want to implement their unique ways of working (from the past)?
“The embedded process is limiting our freedom, we need to be flexible”
is an often-heard statement. When every step is micro-managed in the PLM system, you create a bureaucracy detested by the user. In general, when the processes are implemented in a way first focusing on crucial steps with the option to improve later, you will get the best results and acceptance. Nowadays, we could call it an MVP approach.
I have seen companies that created a task or issue for every single activity a person should do. Managers loved the (demo) dashboard. It never lead to success as the approach created frustration at the end user level as their To-Do list grew and grew.
Another example of the micro-management mindset is when I worked with a company that had the opposite definition of Version and Revision in their current terminology. Initially, they insisted that the new PLM system should support this, meaning everywhere in the interface where Revisions was mentioned should be Version and the reverse for Version and Revision.
Can you imagine the cost of implementing and maintaining this legacy per upgrade?
And then came data (for me 2014 – now)
In 2015, during the pivotal PLM Roadmap/PDT conference related to Product Innovation Platforms, it brought the idea of framing digital transformation in the PLM domain in a single sentence: From Coordinated to Connected. See the original image from Marc Halpern here below and those who have read my posts over the years have seen this terminology’s evolution. Now I would say (till 2024): From Coordinated to Coordinated and Connected.
A data-driven approach was not new at that time. Roughly speaking, around 2006 – close to the introduction of the Smartphone – there was already a trend spurred by better global data connectivity at lower cost. Easy connectivity allowed PLM to expand into industries that were not closely connected to 3D CAD systems(CATIA, CREO or NX). Agile PLM, Aras, and SAP PLM became visible – PLM is no longer for design management but also for go-to-market governance in the CPG and apparel industry.
However, a data-driven approach was still rare in mainstream manufacturing companies, where drawings, office documents, email and Excel were the main information carriers next to the dominant ERP system.
A data-driven approach was a consultant’s dream, and when looking at the impact of digital transformation in other parts of the business, why not for PLM, too? My favorite and still valid 2014 image is the one below from Accenture describing Digital PLM. Here business and PLM come together – the WHY!
Again, the challenge with legacy
At that time, I saw a few companies linking their digital transformation to implementing a new PLM system. Those were the days the PLM vendors were battling for the big enterprise deals, sometimes motivated by an IT mindset that unifying the existing PDM/PLM systems would fulfill the digital dream. Science was not winning, but emotion. Read the PLM blame game – still actual.
One of my key observations is that companies struggle when they approach PLM transformation with a migration mindset. Moving from Coordinated to Connected isn’t just about technology—it’s about fundamentally changing how we work. Instead of a document-driven approach, organizations must embrace a data-driven, connected way of working.
The PLM community increasingly agrees that PLM isn’t a single system; it’s a strategy that requires a federated approach—whether through SaaS or even beyond it.
Before AI became a hype, we discussed the digital thread, digital twins, graph databases, ontologies, and data meshes. Legacy – people (skills), processes(rigid) and data(not reliable) – are the elephant in the room. Yet, the biggest challenge remains: many companies see PLM transformation as just buying new tools.
A fundamental transformation requires a hybrid approach—maintaining traditional operations while enabling multidisciplinary, data-driven teams. However, this shift demands new skills and creates the need to learn and adapt, and many organizations hesitate to take that risk.
In his Product Data Plumber Perspective on 2025. Rob Ferrone addressed the challenge to move forward too, and I liked one of his responses in the underlying discussion that says it all – it is hard to get out of your day to day comfort (and data):
Rob Ferrone’s quote:
Transformations are announced, followed by training, then communication fades. Plans shift, initiatives are replaced, and improvements are delayed for the next “fix-all” solution. Meanwhile, employees feel stuck, their future dictated by a distant, ever-changing strategy team.
And then there is Artificial Intelligence (2024 ……)
In the past two years, I have been reading and digesting much news related to AI, particularly generative AI.
Initially, I was a little skeptical because of all the hallucinations and hype; however, the progress in this domain is enormous.
I believe that AI has the potential to change our digital thread and digital twin concepts dramatically where the focus was on digital continuity of data.
Now this digital continuity might not be required, reading articles like The End of SaaS (a more and more louder voice), usage of the Fusion Strategy (the importance of AI) and an (academic) example, on a smaller scale, I about learned last year the Swedish Arrowhead™ fPVN project.
I hope that five years from now, there will not be a paragraph with the title Pity there was again legacy.
We should have learned from the past that there is always the first wave of tools – they come with a big hype and promise – think about the Startgate Project but also Deepseek.
Still remember, the change comes from doing things differently, not from efficiency gains. To do things differently you need an educated, visionary management with the power and skills to take a company in a new direction. If not, legacy will win (again)
Conclusion
In my 25 years of working in the data management domain, now known as PLM, I have seen several impressive new developments – from 2D to 3D, from documents to data, from physical prototypes to models and more. All these developments took decades to become mainstream. Whilst the technology was there, the legacy kept us back. Will this ever change? Your thoughts?

The pivotal 2015 PLM Roadmap / PDT conference









Due to sustainability regulations, digital transformation has gotten a push in the right direction. GHG (Greenhouse Gas) reporting, ESG (Environmental Social Governance) reporting, CSRD (Corporate Sustainability Reporting Directive), and the DPP (Digital Product Passport) have all created the need for companies to create digital threads for information that historically did not exist or was locked in documents.
The challenge of regulations is that they limit someone’s freedom. Regulations are there to create an equal playing field for all and ensure society makes progress. Be it traffic regulations, business regulations or environmental regulations. The challenge is not to over-regulate and create a
I have learned to always look at the WHY. Why are companies doing business in a certain manner, why are people behaving in a certain manner even against common logic?
Still it is a transformational change in the way you work and this is a challenge for an existing workforce. They reached their status by being an expert in a certain discipline, by mastering specific skills. Now the needed expertise is changing (
We cannot just produce product or consume like crazy if we care about future generations. It is not longer only about the money, it is about next generations and the environment – if you care. This complexity pushes us toward Systems Thinking – many topics are connected – addressing a single topic does not solve the rest.
Historically Europe has been a stable democracy since the second world war and the European Union has been able to establish quite a unified voice step by step. Of course the European Union was heavily influenced by the Automotive and Agricultural lobby. Still the European Green Deal was established with great consensus in the middle instead of focusing on the extremes. A multi-party parliament guarantees a balanced outcome. However type of democracy is still very sensitive for influences from lobbyist and external forces.
The US has been leading the world in polarization. With two major parties fighting always for the 51 % majority vote, there is no place for consensus. The winner takes it all. And although we call it a democracy, you need to have a lot of money to be elected and money is the driving power behind the elections. The WHY in most cases in the US is about short term money making, although I found an interesting point related to Elon Musk.
In
Here we are not talking about a democracy anymore and they might seem the biggest enemy for the climate. However they have a long-term strategy. While keeping the world addicted to fossil fuels, they invest heavily in solar and hydrogen and once the western world understands the energy transition is needed, they are far ahead in experience and remain a main energy supplier.
With 1.4 billion inhabitants and not a democracy either, China has a different mission. Initially as the manufacturing hub for the planet they needed huge amount of energy and therefore they are listed as the most polluting country in the world.
It is a pity to mention Russia as with their war-economy and reliance on fossil fuels, they are on a path towards oblivion. Even if they would win a few other wars, innovation is gone and fossil is ending. It will be a blessing for humanity. I hope they will find a new long-term strategy.

As I wrote in a recent post, “

The title of the paragraph covers topics from the previous paragraphs and it was also the theme from a recent post shared through LinkedIn from Lionel Grealou: 

The challenge seen in this discussion is that:
A potential interesting trend als related to AI I want to clarify further is the modern enterprise architecture . Over the past two years, we have seen a growing understanding that we should not think in systems connected through interfaces but towards a digitally connected infrastructure where APIs, low-code platforms or standardized interfaces will be responsible for real-time collaboration.











The second post, more recent, summarized the experiences I had with several customer engagements. The title says it all: “

I also follow
Of course, Oleg Shilovitsky’s impressive and continuous flow of posts related to modern PLM concepts is amazing—just browse through his 


Congratulations if you have shown you can resist the psychological and emotional pressure and did not purchase anything in the context of Black Friday. However, we must not forget that another big part of the world cannot afford this behavior, as they do not have the means to do so – ultimate Black Friday might be their dream and a fast track to more enormous challenges.
Or we need more planets, and I understand a brilliant guy is already working on it. Let’s go to Mars and enjoy life there.

It is important to note that the recycle loop is the most overestimated loop, where we might contribute to recycling (glass, paper, plastic) in our daily lives; however, other materials, like composites often with embedded electronics, have a much more significant impact.

My presentation focused on three steps that manufacturing companies need to consider now and in the future when moving to a Product Service System.

As an upcoming bonus and a must, companies need to use AI to run their Product Service System as it will improve customer knowledge and trends. 
Step 2: From product to experience can already significantly impact organizations. The traditional salesperson’s role will disappear and be replaced by excellence in marketing, services and product management.
When scaling up slowly, the company might be able to finance this transition themselves. Another option, already happening, is for a third party to finance the Product Service System – think about car leasing, power by the hour, or some industrial equipment vendors.
But we must abandon the old business models and habits – there will be a lot of resistance to change before people are forced to change. This change can take generations as the outside world will not change without a reason, and the established ones will fight for their privileges.
Recently, I noticed I reduced my blogging activities as many topics have already been discussed and repeatably published without new content.
Most companies are not frontrunners in using extremely modern PLM concepts, so you can type risk-free questions and get common-sense answers.
It was interesting to see the order proposed by ChatGPT. Fist the tools (technology), then the processes (domain knowledge / analytical thinking), and last the people and business (strategy and interpersonal and management skills) It is hard to find individuals with all these skills in a single person.

This question cannot be answered by external PLM vendors, consultants or system integrators. Forget the Out-of-the-Box templates or the industry best practices (from the past), but start from your company’s culture and vision, introducing step-by-step new technologies, ways of working and business models to move towards the company’s vision target.










Due to other activities, I could not immediately share the second part of the review related to the PLM Roadmap / PDT Europe conference, held on 23-24 October in Gothenburg. You can read my first post, mainly about Day 1, here: 
Christina’s 
I believe that in our PLM domain, this resonates with actual discussions you will find on LinkedIn, too. @










An interesting point in the discussion was the statement from Diane Goenage, who repeatedly warned that using LLM-based solutions has an environmental impact due to the amount of energy they consume.


As usual, the conference started with 













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