Another year passed, and as usual, I took the time to look back. I always feel that things are going so much slower than expected. But that’s reality – there is always friction, and in particular, in the PLM domain, there is so much legacy we cannot leave behind.
It is better to plan what we can do in 2024 to be prepared for the next steps or, if lucky, even implement the next steps in progress.
In this post, I will discuss four significant areas of attention (AI – DATA – PEOPLE – SUSTAINABILITY) in an alphabetic order, not prioritized.
Here are some initial thoughts. In the upcoming weeks I will elaborate further on them and look forward to your input.

AI (Artificial Intelligence)
Where would I be without talking about AI?
When you look at the image below, the Gartner Hype Cycle for AI in 2023, you see the potential coming on the left, with Generative AI at the peak.
Part of the hype comes from the availability of generative AI tools in the public domain, allowing everyone to play with them or use them. Some barriers are gone, but what does it mean? Many AI tools can make our lives easier, and there is for sure no threat if our job does not depend on standard practices.
AI and People
When I was teaching physics in high school, it was during the introduction of the pocket calculator, which replaced the slide rule.You need to be skilled to uyse the slide rule, now there was a device that gave immediate answers. Was this bad for the pupils?
If you do not know a slide rule, it was en example of new technology replacing old tools, providing more time for other details. Click on the image or read more about the slide rule here on Wiki.
Or today you would ask the question about the slide rule to ChatGPT? Does generative AI mean the end of Wikipedia? Or does generative AI need the common knowledge of sites like Wikipedia?
AI can empower people in legacy environments, when working with disconnected systems. AI will be a threat for to people and companies that rely on people and processes to bring information together without adding value. These activities will disappear soon and you must consider using this innovative approach.
During the recent holiday period, there was an interesting discussion about why companies are reluctant to change and implement better solution concepts. Initially launched by Alex Bruskin here on LinkedIn , the debate spilled over into the topic of TECHNICAL DEBT , well addressed here by Lionel Grealou.
Both articles and the related discussion in the comments are recommended to follow and learn.
AI and Sustainability
Similar to the introduction of Bitcoin using blockchain technology, some people are warning about the vast energy consumption required for training and interaction with Large Language Models (LLM), as Sasha Luccioni explains in her interesting TED talk when addressing sustainability.
She proposes that tech companies should be more transparent on this topic, the size and the type of the LLM matters, as the indicative picture below illustrates.

Carbon Emissions of LLMs compared
In addition, I found an interesting article discussing the pros and cons of AI related to Sustainability. The image below from the article Risks and Benefits of Large Language Models for the Environment illustrates nicely that we must start discussing and balancing these topics.
To conclude, in discussing AI related to sustainability, I see the significant advantage of using generative AI for ESG reporting.
ESG reporting is currently a very fragmented activity for organizations, based on (marketing) people’s goodwill and currently these reports are not always be evidence-based.
Data
The transformation from a coordinated, document-driven enterprise towards a hybrid coordinated/connected enterprise using a data-driven approach became increasingly visible in 2023. I expect this transformation to grow faster in 2024 – the momentum is here.
We saw last year that the discussions related to Federated PLM nicely converged at the PLM Roadmap / PDT Europe conference in Paris. I shared most of the topics in this post: The week after PLM Roadmap / PDT Europe 2023. In addition, there is now the Heliple Federated PLM LinkedIn group with regular discussions planned.
In addition, if you read here Jan Bosch’s reflection on 2023, he mentions (quote):
… 2023 was the year where many of the companies in the center became serious about the use of data. Whether it is historical analysis, high-frequency data collection during R&D, A/B testing or data pipelines, I notice a remarkable shift from a focus on software to a focus on data. The notion of data as a product, for now predominantly for internal use, is increasingly strong in the companies we work with
I am a big fan of Jan’s posting; coming from the software world, he describes the same issues that we have in the PLM world, except he does not carry the hardware legacy that much and, therefore, acts faster than us in the PLM world.
An interesting illustration of the slow pace to a data-driven environment is the revival of the PLM and ERP integration discussion. Prof. Jörg Fischer and Martin Eigner contributed to the broader debate of a modern enterprise infrastructure, not based on systems (PLM, ERP, MES, ….) but more on the flow of data through the lifecycle and an organization.
It is a great restart of the debate, showing we should care more about data semantics and the flow of information.
The articles: The Future of PLM & ERP: Bridging the Gap. An Epic Battle of Opinions! and Is part master in PLM and ERP equal or not) combined with the comments to these posts, are a must read to follow this change towards a more connected flow of information.
While writing this post, Andreas Lindenthal expanded the discussion with his post: PLM and Configuration Management Best Practices: Part Traceability and Revisions. Again thanks to data-driven approaches, there is an extending support for the entire product lifecycle. Product Lifecycle Management, Configuration Management and AIM (Asset Information Management) have come together.
PLM and CM are more and more overlapping as I discussed some time ago with Martijn Dullaart, Maxime Gravel and Lisa Fenwick in the The future of Configuration Management. This topic will be “hot”in 2024.
People
From the people’s perspective towards AI, DATA and SUSTAINABILITY, there is a noticeable divide between generations. Of course, for the sake of the article, I am generalizing, assuming most people do not like to change their habits or want to reprogram themselves.
Unfortunate, we have to adapt our skills as our environment is changing. Most of my generation was brought up with the single source of truth idea, documented and supported by science papers.
In my terminology, information processing takes place in our head by combining all the information we learned or collected through documents/books/newspapers – the coordinated approach.
For people living in this mindset, AI can become a significant threat, as their brain is no longer needed to make a judgment, and they are not used to differentiate between facts and fake news as they were never trained to do so
The same is valid for practices like the model-based approach, working data-centric, or considering sustainability. It is not in the DNA of the older generations and, therefore, hard to change.
The older generation is mostly part of an organization’s higher management, so we are returning to the technical debt discussion.

Later generations that grew up as digital natives are used to almost real-time interaction, and when applied consistently in a digital enterprise, people will benefit from the information available to them in a rich context – in my terminology – the connected approach.
AI is a blessing for people living in this mindset as they do not need to use old-fashioned methods to acquire information.
“Let ChatGPT write my essay.”
However, their challenge could be what I would call “processing time”. Because data is available, it does not necessarily mean it is the correct information. For that reason it remains important to spend time digesting the impact of information you are reading – don’t click “Like”based on the tittle, read the full article and then decide.
Experience is what you get, when you don’t get what you expect.
meaning you only become experienced if you learn from failures.
Sustainability
Unfortunately, sustainability is not only the last topic in alphabetic order, as when you look at the image below, you see that discussions related to sustainability are in a slight decline at C-level at the moment.
I share this observation in my engagements when discussing sustainability with the companies I interact with.
The PLM software and services providers are all on a trajectory of providing tools and an infrastructure to support a transition to a more circular economy and better traceability of materials and carbon emissions.
In the PLM Global Green Alliance, we talked with Aras, Autodesk, Dassault Systems, PTC, SAP, Sustaira, TTPSC(Green PLM) and more to come in 2024. The solution offerings in the PLM domain are available to start, now the people and processes.
For sure, AI tools will help companies to get a better understanding of their sustainability efforts. As mentioned before AI could help companies in understanding their environmental impact and build more accurate ESG reports.
Next, being DATA-driven will be crucial. As discussed during the latest PLM Roadmap/PDT Europe conference: The Need for a Governance Digital Thread.
And regarding PEOPLE, the good news is that younger generations want to take care of their future. They are in a position to choose the company to work for or influence companies by their consumer behavior. Unfortunately, climate disasters will remind us continuously in the upcoming decades that we are in a critical phase.
With the PLM Global Green Alliance, we strive to bring people together with a PLM mindset, sharing news and information on how to move forward to a sustainable future.
Mark Reisig (CIMdata – moderator for Sustainability & Energy) and Patrice Quencez (CIMPA – moderator for the Circular Economy) joined the PGGA last year and you will experience their inputs this year.
Conclusion
As you can see from this long post, there is so much to learn. The topics described are all actual, and each topic requires education, experience (success & failures) combined with understanding of the technology concepts. Make sure you consider all of them, as focusing on a single topic will not make move faster forward – they are all related. Please share your experiences this year—Happy New Year of Learning.








New people in the organization need to learn the meaning of the numbering scheme. This learning process reduces the flexibility of an organization and increases the risk of making errors.

Several comments related to the Smart Numbering discussion mentioned that changing the numbering system is too costly and risky to implement and that no business case exists to support it. This statement only makes sense if you want your business to become obsolete slowly. Modern best practices based on digitization should be introduced as fast as possible, allowing companies to learn and adapt. There is no need for a big bang.
Start with mapping, prioritizing, and mapping value streams in your company. Where do we see the most significant business benefits related to cost of handling, speed, and quality?
Note: It is not necessary to start with engineering as they might be creators of data – start, for example, with the xBOM flow, where the xBOM can be a concept BOM, the engineering BOM, the Manufacturing BOM, and more. Building this connected data flow is an investment for every department; do not start from the systems.
Make sure these objects have, besides the part number, the right properties, the right status, and the right connections. In other words, create a connected digital thread – first internally in your company and next with your ecosystem (OEMs, suppliers, vendors)
I just read Oleg Shilovitsky’s post 






By creating a connected digital thread between these sources, reporting becomes a push on the button, and the continuous availability of information will help companies assess and improve their products to reduce environmental and social risks.
One of the areas where the connected digital thread will become important is the implementation of the 


Although sustainability is mentioned in their vision statement, the main business drivers are increased efficiency, improved competitiveness, and cost reduction by removing the overhead and latency of such a network.





Ultimately, to have a business-sustainable PLM infrastructure, you need to structure your company internally and connect to the outside world with a focus on standards to avoid a vendor lock-in or a dead end.

Another benefit Cyril demonstrated was the integration of RoHS compliance to the BOM as an integrated environment. In my session, I also addressed integrated RoHS compliance as a stepping stone to efficiency in future compliance needs.








A great follow-up on Yousef’s session was 


Topics to share in the next post are related to my contribution at the conference The Need for a Governance Digital Thread, where I addressed the need for federated PLM capabilities with the upcoming regulations and practices related to sustainability, which require a connected Digital.
I want to combine this post with the findings that
And there was the introduction of AI at the conference, with some experts’ talks and thoughts. Perhaps at this stage, it is too high on Gartner’s hype cycle to go into details. It will surely be THE topic of discussion or interest you must have noticed.

The conference was sold out this time, and during the breaks, you had to navigate through the people to find your network opportunities. Also, the participation of the main PLM players as sponsors illustrated that everyone wanted to benefit from this opportunity to meet and learn from their industry peers.

The second keynote was from 
In the Q&A there to Christine’s sessions there was an interesting question related to the involvement of Human Resources (HR) in this project. There was a laugh that said it all – like in most companies HR is not focusing on organizational change, they focus more on operational issues – the Human is considered a Resource.














During this two-day conference, there were approximately 80 attendees from around 15 companies, all with a serious interest and experience in modularity. The conference reminded me of the
When talking about modularity, many people will have Lego in mind, as with the Lego bricks, you can build all kinds of products without the need for special building blocks. In general, this is the concept of modularity.
From
PLM and Modularity suffer from the framing that it is about R&D and their tools, whereas in reality, PLM and Modularity are strategies concerning all departments in an enterprise, from sales & marketing, engineering, and manufacturing to customer service.
The exciting part of the conference was that all the significant modularity players were present. Hosted by Vestas and with a keynote speech from 
















The book, with the additional chapter, will be available later this year. I want to share with you in this post the topics I addressed in this chapter. Perhaps relevant for your organization or personal interests. Also, I am looking forward to learning if I missed any topics.








This section describes the importance of implementing a digital twin for the design phase, allowing companies to develop, test and analyze their products and services first virtually. Trade-off studies on virtual products are much cheaper, and when they are done in a data-driven, model-based environment, it will be the most efficient environment. In my terminology, setting up such a collaboration environment might be considered a System of Engagement.

During my summer holiday in my “remote” office, I had the chance to digest what I recently read, heard, saw and discussed related to the future of PLM.
The most significant change I noticed in my discussions is the growing awareness that PLM is no longer covered by a single system.
The main question is: “Every PLM Vendor has a rich portfolio on PowerPoint mentioning all phases of the product lifecycle.
I have discussed several observed changes related to the effects of digitization in my recent blog posts, referencing others who have studied these topics in their organizations.




If you look at the messaging of the current PLM Vendors, none of them is talking about this federated concept.
Plug-and-play systems of engagement require interface standards, and PLM Vendors will only move in this direction if customers are pushing for that, and this is the chicken-and-egg discussion. And probably, their initiatives are too fragmented at the moment to come to a standard. However, don’t give up; keep building MVPs to learn and share.
I plan to come back with a more dedicated discussion at some point with Martijn soon. Meanwhile, start reading the book. Get your free chapter if needed by 
Last week I had the opportunity to discuss the topic of Systems of Engagement in the context of the more extensive PLM landscape.



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