PLM, value or cost?

April 7, 2025 in Artificial Intelligence, Blocking change, Change, Digital Enterprise, Education, Innovation, Observations, PLM, ROI on PLM, Storytelling | Tags: , , , , , , | Leave a comment

In the last two weeks, I have had mixed discussions related to PLM, where I realized the two different ways people can look at PLM. Are implementing PLM capabilities driven by a cost-benefit analysis and a business case? Or is implementing PLM capabilities driven by strategy providing business value for a company?

Most companies I am working with focus on the first option – there needs to be a business case.

This observation is a pleasant passageway into a broader discussion started by Rob Ferrone recently with his article Money for nothing and PLM for free. He explains the PDM cost of doing business, which goes beyond the software’s cost. Often, companies consider the other expenses inescapable.

At the same time, Benedict Smith wrote some visionary posts about the potential power of an AI-driven PLM strategy, the most recent article being PLM augmentation – Panning for Gold.

It is a visionary article about what is possible in the PLM space (if there was no legacy ☹), based on Robust Reasoning and how you could even start with LLM Augmentation for PLM “Micro-Tasks.

Interestingly, the articles from both Rob and Benedict were supported by AI-generated images – I believe this is the future: Creating an AI image of the message you have in mind.

When you have digested their articles, it is time to dive deeper into the different perspectives of value and costs for PLM.

 

From a system to a strategy

The biggest obstacle I have discovered is that people relate PLM to a system or, even worse, to an engineering tool. This 20-year-old misunderstanding probably comes from the fact that in the past, implementing PLM was more an IT activity – providing the best support for engineers and their data – than a business-driven set of capabilities needed to support the product lifecycle.

 

The System approach

Traditional organizations are siloed, and initially, PLM always had the challenge of supporting product information shared throughout the whole lifecycle, where there was no conventional focus per discipline to invest in sharing – every discipline has its P&L – and sharing comes with a cost.

At the management level, the financial data coming from the ERP system drives the business. ERP systems are transactional and can provide real-time data about the company’s performance. C-level management wants to be sure they can see what is happening, so there is a massive focus on implementing the best ERP system.

In some cases, I noticed that the investment in ERP was twenty times more than the PLM investment.

Why would you invest in PLM? Although the ERP engine will slow down without proper PLM, the complexity of PLM compared to ERP is a reason for management to look at the costs, as the PLM benefits are hard to grasp and depend on so much more than just execution.

See also my old 2015 article:   How do you measure collaboration?

As I mentioned, the Cost of Non-Quality, too many iterations, time lost by searching, material scrap, manufacturing delays or customer complaints – often are considered inescapable parts of doing business (like everyone else) – it happens all the time..

The strategy approach

It is clear that when we accept the modern definition of PLM, we should be considering product lifecycle management as the management of the product lifecycle (as Patrick Hillberg says eloquently in our Share PLM podcast – see the image at the bottom of this post, too).

When you implement a strategy, it is evident that there should be a long(er) term vision behind it, which can be challenging for companies. Also, please read my previous article: The importance of a (PLM) vision.

I cannot believe that, although perhaps not fully understood, the importance of a data-driven approach will be discussed at many strategic board meetings. A data-driven approach is needed to implement a digital thread as the foundation for enhanced business models based on digital twins and to ensure data quality and governance supporting AI initiatives.

It is a process I have been preaching: From Coordinated to Coordinated and Connected.

We can be sure that at the board level, strategy discussions should be about value creation, not about reducing costs or avoiding risks as the future strategy.

 

Understanding the (PLM) value

The biggest challenge for companies is to understand how to modernize their PLM infrastructure to bring value.

* Step 1 is obvious. Stop considering PLM as a system with capabilities, but investigate how you transform your infrastructure from a collection of systems and (document)  interfaces towards a federated infrastructure of connected tools.

Note: the paradigm shift from a Single Source of Truth (in my system) towards a Nearest Source of Truth and a Single Source of Change.

 

* Step 2 is education. A data-driven approach creates new opportunities and impacts how companies should run their business. Different skills are needed, and other organizational structures are required, from disciplines working in siloes to hybrid organizations where people can work in domain-driven environments (the Systems of Record) and product-centric teams (the System of Engagement). AI tools and capabilities will likely create an effortless flow of information within the enterprise.

* Step 3 is building a compelling story to implement the vision.   Implementing new ways of working based on new technical capabilities requires also organizational change. If your organization keeps working similarly, you might gain some percentage of efficiency improvements.

The real benefits come from doing things differently, and technology allows you to do it differently. However, this requires people to work differently, too, and this is the most common mistake in transformational projects.

Companies understand the WHY and WHAT but leave the HOW to the middle management.

People are squeezed into an ideal performance without taking them on the journey. For that reason, it is essential to build a compelling story that motivates individuals to join the transformation. Assisting companies in building compelling story lines is one of the areas where I specialize.

Feel free to contact me to explore the opportunity for your business.

It is not the technology!

With the upcoming availability of AI tools, implementing a PLM strategy will no longer depend on how IT understands the technology, the systems and the interfaces needed.

As Yousef Hooshmand‘s  above image describes, a federated infrastructure of connected (SaaS) solutions will enable companies to focus on accurate data (priority #1) and people creating and using accurate data (priority #1). As you can see, people and data in modern PLM are the highest priority.

Therefore, I look forward to participating in the upcoming Share PLM Summit on 27-28 May in Jerez.

It will be a breakthrough – where traditional PLM conferences focus on technology and best practices. This conference will focus on how we can involve and motivate people. Regardless of which industry you are active in, it is a universal topic for any company that wants to transform.

 

Conclusion

Returning to this article’s introduction, modern PLM is an opportunity to transform the business and make it future-proof. It needs to be done for sure now or in the near future. Therefore PLM initiatives should be considered from the value point first instead of focusing on the costs.  How well are you connected to your management’s vision to make PLM a value discussion?

Enjoy the podcast – several topics discuss relate to this post.

 

 

The importance of a (PLM) vision

March 17, 2025 in Artificial Intelligence, Blocking change, Data centric, Knowledge Management, PLM | Tags: , , | Leave a comment

In the last two weeks, I had some interesting observations and discussions related to the need to have a (PLM) vision. I placed the word PLM between brackets, as PLM is no longer an isolated topic in an organization. A PLM strategy should align with the business strategy and vision.

To be clear, if you or your company wants to survive in the future, you need a sustainable vision and a matching strategy as the times they are a changing, again!

I love the text: “Don’t criticize what you can’t understand” – a timeless quote.

 

First, there was Rob Ferrone’s article: Multi-view. Perspectives that shape PLM – a must-read to understand who to talk to about which dimension of PLM – and it is worth browsing through the comments too – there you will find the discussions, and it helps you to understand the PLM players.

Note: it is time that AI-generated images become more creative 😉

Next, there is still the discussion started by Gareth Webb, Digital Thread and the Knowledge Graph, further stirred by Oleg Shilovitsky.

Based on the likes and comments, it is clearly a topic that creates interaction – people are thinking and talking about it – the Digital Thread as a Service.

One of the remaining points in this debate is still the HOW and WHEN companies decide to implement a Digital Thread, a Knowledge Graph and other modern data concepts.

So far my impression is that most companies implement their digital enhancements (treads/graphs) in a bottom-up approach, not driven by a management vision but more like band-aids or places where it fits well, without a strategy or vision.

The same week, we, Beatriz Gonzáles and I, recorded a Share PLM podcast session with Paul Kaiser from MHP Americas as a guest. Paul is the head of the Digital Core & Technology department, where he leads management and IT consulting services focused on end-to-end business transformation.

During our discussion, Paul mentioned the challenge in engagements when the company has no (PLM) vision. These companies expect external consultants to formulate and implement the vision – a recipe for failure due to wrong expectations.

The podcast can be found HERE , and the session inspired me to write this post.

“We just want to be profitable“.

I believe it is a typical characteristic of small and medium enterprises that people are busy with their day-to-day activities. In addition, these companies rarely appoint new top management, which could shake up the company in a positive direction. These companies evolve …..

You often see a stable management team with members who grew up with the company and now monitor and guide it, watching its finances and competition. They know how the current business is running.

Based on these findings, there will be classical efficiency plans, i.e., cutting costs somewhere, dropping some non-performing products, or investing in new technology that they cannot resist. Still, minor process changes and fundamental organizational changes are not expected.

Most of the time, the efficiency plans provide single-digit benefits.

Everyone is happy when the company feels stable and profitable, even if the margins are under pressure. The challenge for this type of company without a vision is that they navigate in the dark when the outside world changes – like nowadays.

 

The world is changing drastically.

Since 2014, I have advocated for digital transformation in the PLM domain and explained it simply using the statement: From Coordinated to Connected, which already implies much complexity.

Moving from document/files to datasets and models, from a linear delivery model to a DevOps model, from waterfall to agile and many other  From-To statements.

Moving From-To is a transformational journey, which means you will learn and adapt to new ways of working during the journey. Still, the journey should have a target, directed by a vision.

However, not many companies have started this journey because they just wanted to be profitable.

“Why should we go in an unknown direction?”

With the emergence of sustainability regulations, e.g., GHG and ESG reporting, carbon taxes, material reporting, and the Digital Product Passport, which goes beyond RoHS and REACH and applies to much more industries, there came the realization that there is a need to digitize the product lifecycle processes and data beyond documents. Manual analysis and validation are too expensive and unreliable.

At this stage, there is already a visible shift between companies that have proactively implemented a digitally connected infrastructure and companies that still see compliance with regulations as an additional burden. The first group brings products to the market faster and more sustainably than the second group because sustainability is embedded in their product lifecycle management.

And just when companies felt they could manage the transition from Coordinated to Coordinated and Connected, there was the fundamental disruption of embedded AI in everything, including the PLM domain.

  • Large Language Models LLMs can go through all the structured and unstructured data, providing real-time access to information, which would take experts years of learning. Suddenly, everyone can behave experienced.
  • The rigidness of traditional databases can be complemented by graph databases, which visualize knowledge that can be added and discovered on the fly without IT experts. Suddenly, an enterprise is no longer a collection of interfaced systems but a digital infrastructure where data flows – some call it Digital Thread as a Service (DTaaS)
  • Suddenly, people feel overwhelmed by complexity, leading to fear and doing nothing, a killing attitude.

2014 The Economist – the onrushing wave

I cannot predict what will happen in the next 5 to 10 years, but I am sure the current change is one we have never seen before. Be prepared and flexible to act—to be on top of the wave, you need the skills to get there.

 

Building the vision

The image below might not be new to you, but it illustrates how companies could manage a complex change.

I will focus only on the first two elements, Vision and Skills, as they are the two elements we as individuals can influence. The other elements are partly related to financial and business constraints.

Vision and Skills are closely related because you can have a fantastic vision. Still, to realize the vision, you need a strategy driven by relevant skills to define and implement the vision. With the upcoming AI, traditional knowledge-based skills will suddenly no longer be a guarantee for future jobs.

AI brings a new dimension for everyone working in a company. To remain relevant, you must develop your unique human skills that make you different from robots or libraries. The importance of human skills might not be new, but now it has become apparent with the explosion of available AI tools.

Look at this 2013 table about predicted skills for the future – You can read the details in their paper, The Future of Employment, by Carl Benedikt Frey & Michael Osborne(2013)  – click on the image to see the details.

In my 2015 PLM lectures, I joked when showing this image that my job as a PLM coach was secured, because you are a recreational therapist and firefighter combined.

It has become a reality, and many of my coaching engagements nowadays focus on explaining and helping companies formulate and understand their possible path forward. Helping them align and develop a vision of progressing in a volatile world – the technology is there, the skills and the vision are often not yet there.

Combining business strategy with in-depth PLM concepts is a relatively unique approach in our domain. Many of my peers have other primary goals, such as Rob Ferrone’s article: Multi-view. Perspectives that shape PLM explains.

And then there is …..

The Share PLM Summit 2025

Modern times need new types of information building and sharing, and therefore, I am eager to participate in the upcoming Share PLM Summit at the end of May in Jerez (Spain).

See the link to the event here: The Share PLM Summit 2025 – with the theme: Where People Take Center Stage to Drive Human-Centric Transformations in PLM and Lead the Future of Digital Innovation.

In my lecture, I will focus on how humans can participate in/anticipate this digital AI-based transformation. But even more, I look forward to the lectures and discussions with other peers, as more people-centric thought leaders and technology leaders will join us:

Quoting Oleg Shilovitsky:

PLM was built to manage data, but too often, it makes people work for the data instead of working the other way around. At Share PLM Summit 2025, I’ll discuss how PLM must evolve from rigid, siloed systems to intelligent, connected, and people-centric data architectures.

We need both, and I hope to see you at the end of May at this unique PLM conference.

Conclusion

We are at a decisive point of the digital transformation as AI will challenge people skills, knowledge and existing ways of working.  Combined with a turbulent world order, we need to prepare to be flexible and resilient. Therefore instead of focusing on current best practices we need to prepare for the future – a vision developed by skilled people. How will you or your company work on that? Join us if you have questions or ideas.

 

Model-based – the elephant in the room

March 3, 2025 in Artificial Intelligence, Digital Enterprise, digital thread, MBD, MBSE, model-based, PLM | Tags: , , , | Leave a comment

Four years ago, I wrote a series of posts with the common theme: The road to model-based and connected PLM. I discussed the various aspects of model-based and the transition from considering PLM as a system towards considering PLM as a strategy to implement a connected infrastructure.

Since then, a lot has happened. The terminology of Digital Twin and Digital Thread has become better understood. The difference between Coordinated and Connected ways of working has become more apparent. Spoiler: You need both ways. And at this moment, Artificial Intelligence (AI) has become a new hype.

Many current discussions in the PLM domain are about structures and data connectivity, Bills of Materials (BOM), or Bills of Information(BOI)  combined with the new term Digital Thread as a Service (DTaaS) introduced by Oleg Shilovitsky and Rob Ferrone. Here, we envision a digitally connected enterprise, based connected services.

 

A lot can be explored in this direction; also relevant Lionel Grealou’s article in Engineering.com: RIP SaaS, long live AI-as-a-service and follow-up discussions related tot his topic. I chimed in with Data, Processes and AI.

 

However, we also need to focus on the term model-based or model-driven. When we talk about models currently, Large Language Models (LMM) are the hype, and when you are working in the design space, 3D CAD models might be your first association.

There is still confusion in the PLM domain: what do we mean by model-based, and where are we progressing with working model-based?

A topic I want to explore in this post.

 

It is not only Model-Based Definition (MBD)

Before I started The Road to Model-Based series, there was already the misunderstanding that model-based means 3D CAD model-based. See my post from that time: Model-Based – the confusion.

Model-Based Definition (MBD) is an excellent first step in understanding information continuity, in this case primarily between engineering and manufacturing, where the annotated model is used as the source for manufacturing.

In this way, there is no need for separate 2D drawings with manufacturing details, reducing the extra need to keep the engineering and manufacturing information in sync and, in addition, reducing the chance of misinterpretations.

MBD is a common practice in aerospace and particularly in the automotive industry. Other industries are struggling to introduce MBD, either because the OEM is not ready or willing to share information in a different format than 3D + 2D drawings, or their supplier consider MBD too complex for them compared to their current document-driven approach.

In its current practice, we must remember that MBD is part of a coordinated approach.

Companies exchange technical data packages based on potential MBD standards (ASME Y14.47 /ISO 16792 but also JT and 3D PDF). It is not yet part of the connected enterprise, but it connects engineering and manufacturing using the 3D Model as the core information carrier.

As I wrote, learning to work with MBD is a stepping stone in understanding a modern model-based and data-driven enterprise. See my 2022 post: Why Model-based Definition is important for us all.

To conclude on MBD, Model-based definition is a crucial practice to improve collaboration between engineering, manufacturing, and suppliers, and it might be parallel to collaborative BOM structures.

And it is transformational as the following benefits are reported through ChatGPT:

  • Up to 30% faster in product development cycles due to reduced need for 2D drawings and fewer design iterations. Boeing reported a 50% reduction in engineering change requests by using MBD.

  • Companies using MBD see a 20–50% reduction in manufacturing errors caused by misinterpretations of 2D drawings. Caterpillar reported a 30% improvement in first-pass yield due to better communication between design and manufacturing teams.
  • MBD can reduce product launch time by 20–50% by eliminating bottlenecks related to traditional drawings and manual data entry.
  • 20–30% reduction in documentation costs by eliminating or reducing 2D drawings. Up to 60% savings on rework and scrap costs by reducing errors and inconsistencies.

Over five years, Lockheed Martin achieved a $300 million cost savings by implementing MBD across parts of its supply chain.

 

MBSE is not a silo.

The MBSE playground

For many people, Model-Based Systems Engineering(MBSE) seems to be something not relevant to their business, or it is a discipline for a small group of specialists that are conducting system engineering practices, not in the traditional document-driven V-shape approach but in an iterative process following the V-shape, meanwhile using models to predict and verify assumptions.

And what is the value connected in a PLM environment?

A quick heads up – what is a model

A  model is a simplified representation of a system, process, or concept used to understand, predict, or optimize real-world phenomena. Models can be mathematical, computational, or conceptual. 

We need models to: 

  • Simplify Complexity – Break down intricate systems into manageable components and focus on the main components.
  • Make Predictions – Forecast outcomes in science, engineering, and economics by simulating behavior – Large Language Models, Machine Learning. 
  • Optimize Decisions – Improve efficiency in various fields like AI, finance, and logistics by running simulations and find the best virtual solution to apply.
  • Test Hypotheses – Evaluate scenarios without real-world risks or costs for example a virtual crash test..

It is important to realize models are as accurate as the data elements they are running on – every modeling practices has a certain need for base data, be it measurements, formulas, statistics.

I watched and listened to the interesting podcast below, where Jonathan Scott and Pat Coulehan discuss this topic: Bridging MBSE and PLM: Overcoming Challenges in Digital Engineering. If you have time – watch it to grasp the challenges.

The challenge in an MBSE environment is that it is not a single tool with a single version of the truth; it is merely a federated environment of shared datasets that are interpreted by modeling applications to understand and define the behavior of a product.

In addition, an interesting article from Nicolas Figay might help you understand the value for a broader audience. Read his article:  MBSE: Beyond Diagrams – Unlocking Model Intelligence for Computer-Aided Engineering.

Ultimately, and this is the agreement I found on many PLM conferences, we agree that MBSE practices are the foundation for downstream processes and operations.

We need a data-driven modeling environment to implement Digital Twins, which can span multiple systems and diagrams.

In this context, I like the Boeing diamond presented by Don Farr at the 2018 PLM Roadmap EMEA conference. It is a model view of a system, where between the virtual and the physical flow, we will have data flowing through a digital thread.

Where this image describes a model-based, data-driven infrastructure to deliver a solution, we can, in addition, apply the DevOp approach to the bigger picture for solutions in operation, as depicted by the PTC image below.

 

Model-based the foundation of the digital twins

To conclude on MBSE, I hope that it is clear why I am promoting considering MBSE not only as the environment to conceptualize a solution but also as the foundation for a digital enterprise where information is connected through digital threads and AI models (**new**)

The data borders between traditional system domains will disappear – the single source of change and the nearest source of truth – paradigm, and this post, The Big  Blocks of Future Lifecycle Management, from Prof. Dr. Jörg Fischer, are all about data domains.

However, having accessible data using all kinds of modern data sources and tools are necessary to build digital twins – either to simulate and predict a physical solution or to analyze a physical solution and, based on the analysis, either adjust the solutions or improve your virtual simulations.

Digital Twins at any stage of the product life cycle are crucial to developing and maintaining sustainable solutions, as I discussed in previous lectures. See the image below:

Conclusion

Data quality and architecture are the future of a modern digital enterprise – the building blocks. And there is a lot of discussion related to Artificial Intelligence. This will only work when we master the methodology and practices related to a data-driven and sustainable approach using models. MBD is not new, MBSE perhaps still new, building blocks for a model-based approach. Where are you in your lifecycle?

 

 

 

Modularity – a need for the business and the future

February 18, 2025 in Change, Circulair Economy, Data centric, Green Development, Modularity, PLM, Sustainability | Tags: , , , , | Leave a comment

In my business ecosystem, I have seen a lot of discussions about technical and architectural topics since last year that are closely connected to the topic of artificial intelligence. We are discussing architectures and solutions that will make our business extremely effective. The discussion is mostly software vendor-driven as vendors usually do not have to deal with the legacy, and they can imagine focusing on the ultimate result.

Legacy (people, skills, processes and data) is the mean inhibitor for fast forward in such situations, as I wrote in my previous post: Data, Processes and AI.

However, there are also less visible discussions about business efficiency – methodology and business models – and future sustainability.

These discussions are more challenging to follow as you need a broader and long-term vision, as implementing solutions/changes takes much longer than buying tools.

This time, I want to revisit the discussion on modularity and the need for business efficiency and sustainability.

 

Modularity – what is it?

Modularity is a design principle that breaks a system into smaller, independent, and interchangeable components, or modules, that function together as a whole. Each module performs a specific task and can be developed, tested, and maintained separately, improving flexibility and scalability.

Modularity is a best practice in software development. Although modular thinking takes a higher initial effort, the advantages are enormous for reuse, flexibility, optimization, or adding new functionality. And as software code has no material cost or scrap, modular software solutions excel in delivery and maintenance.

In the hardware world, this is different. Often, companies have a history of delivering a specific (hardware) solution, and the product has been improved by adding features and options where the top products remain the company’s flagships.

Modularity enables easy upgrades and replacements in hardware and engineering, reducing costs and complexity. As I work mainly with manufacturing companies in my network, I will focus on modularity in the hardware world.

 

Modularity – the business goal

How often have you heard that a business aims to transition from Engineering to Order (ETO) to Configure/Build to Order (BTO) or Assemble to Order (ATO)? Companies often believe that the starting point of implementing a PLM system is enough, as it will help identify commonalities in product variations, therefore leading to more modular products.

The primary targeted business benefits often include reduced R&D time and cost but also reduced risk due to component reuse and reuse of experience. However, the ultimate goal for CTO/ATO companies is to minimize R&D involvement in their sales and delivery process.

More options can be offered to potential customers without spending more time on engineering.

Four years ago, I discussed modularity with Björn Eriksson and Daniel Strandhammar, who wrote “The Modular Way” during the COVID-19 pandemic. I liked the book because it is excellent for understanding the broader scope of modularity along with marketing, sales, and long-term strategy. Each business type has its modularity benefits.

I had a follow-up discussion with panelists active in modularization and later with Daniel Strandhammar about the book’s content in this blog post: PLM and Modularity.

 

Next, I got involved with the North European Modularity Network (NEM) group, a group of Scandinavian companies that share modularization experiences and build common knowledge.

Historically, modularization has been a popular topic in North Europe, and meanwhile, the group is expanding beyond Scandinavia. Participants in the group focus on education-sharing strategies rather than tools.

The 2023 biannual meeting  I attended hosted by Vestas in Ringkobing was an eye-opener for me.

We should work more integrated, not only on the topic of Modularity and PLM but also on a third important topic: Sustainability in the context of the Circular Economy.

You can review my impression of the event and presentation in my post: “The week after North European Modularity (NEM)“

That post concludes that Modularity, like PLM, is a strategy rather than an R&D mission. Integrating modularity topics into PLM conferences or Circular Economy events would facilitate mutual learning and collaboration.

 

Modularity and Sustainability

The PLM Green Global Alliance started in 2020 initially had few members. However, after significant natural disasters and the announcement of regulations related to the European Green Deal, sustainability became a management priority. Greenwashing was no longer sufficient.

One key topic discussed in the PLM Green Global Alliance is the circular economy moderated by CIMPA PLM services. The circular economy is crucial as our current consumption of Earth’s resources is unsustainable.

The well-known butterfly diagram from the Ellen MacArthur Foundation below, illustrates the higher complexity of a circular economy, both for the renewables (left) and the hardware (right)

In a circular economy, modularity is essential. The SHARE loop focuses on a Product Service Model, where companies provide services based on products used by different  users. This approach requires a new business model, customer experience, and durable hardware. After Black Friday last year, I wrote about this transition: The Product Service System and a Circular Economy.

Modularity is vital in the MAINTAIN/PROLONG loop. Modular products can be upgraded without replacing the entire product, and modules are easier to repair. An example is Fairphone from the Netherlands, where users can repair and upgrade their smartphones, contributing to sustainability.

In the REUSE/REMANUFACTURE loop, modularity allows for reusing hardware parts when electronics or software components are upgraded. This approach reduces waste and supports sustainability.

The REFURBISH/REMANUFACTURE loop also benefits from modularity, though to a lesser extent. This loop helps preserve scarce materials, such as batteries, reducing the need for resource extraction from places like the moon, Mars, or Greenland.

A call for action

If you reached this point of the article, my question is now to reflect on your business or company. Modularity is, for many companies, a dream (or vision) and will become, for most companies, a must to provide a sustainable business.

Modularity does not depend on PLM technology, as famous companies like Scania, Electrolux and Vestas have shown (in my reference network).

Where is your company and its business offerings?

IMPORTANT:

If you aim to implement modularity to support the concepts of the Circular Economy, make sure you do it in a data-driven, model-based environment – here, technology counts.

 

Conclusion

Don’t miss the focus on the potential relevance of modularity for your company. Modularity improves business and sustainability, AND it touches all enterprise stakeholders. Technology alone will not save the business. Your thoughts?

Do you want to learn more about implementing PLM at an ETO space company?
Listen to our latest podcast: OHB’s Digital Evolution: Transforming Aerospace PLM with Lucía Núñez Núñez

Data, Processes and AI

February 4, 2025 in Artificial Intelligence, Data centric, digital thread, Digital Twin, Minimum Viable Product, PLM | Tags: , , , , , | Leave a comment

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

PLM and Sustainability in 2025

January 23, 2025 in Artificial Intelligence, Blocking change, Climate Change, Green Development, Innovation, PLM, Sustainability | Tags: , | Leave a comment

In my general 2025 outlook for PLM,  My 2025 focus, I mentioned Sustainability at the end, as I believe it is a topic on its own, worth an entire blog post.

After our 2025 PLM Global Green Alliance core team kick-off last week, I felt the importance of sharing our thoughts, observations, and personal thoughts/focus.

The PGGA core team consists of Rich McFall – Climate Change, Klaus Brettschneider Life Cycle Assessment, Mark Reisig Sustainability and Green Energy, Evgeniya Burimskaya Circular Economy, Erik Reiger Design for Sustainability and me Talking about Sustainability.

 

Some interesting observations:

  • Evgenia mentioned that in job interviews for CIMPA, it is motivating to see that new employees want to contribute to sustainability activities and the education of companies. Sustainability is part of their WHY (I will come back to that later)
  • We have more and more PGGA members from Asia, while percentage of US members is declining. Where the US has the loudest voice against human-caused climate change and Sustainability, there are a lot of hidden and positive success stories from Asia, and we are looking for spokespeople from that region.

Regulations

In many lectures, I explained that digitization in PLM was going slow because this is a complex topic for many companies, and current business performance might be challenging but not too bad. So why would we go on an unknown and potentially risky transformation journey?

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.

Therefore, it is interesting to read Oleg Shilovitsky’ s blog, Reimagining PLM for 2025: Key Strategic Trends, in which he also sees the importance of Sustainability and the Circular Economy.

Quoting Oleg:

Sustainability cannot be ignored and, therefore I expect more interest to environmental considerations in PLM strategies. Companies are incorporating sustainability metrics into product design and lifecycle assessment, aligning with Industry 5.0 and Engineering 5.0 principles. It is impossible without digital thread and data connectivity and, therefore will continue to support business strategies.

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 Kafkaesque society. Whereas if you are alone in the world or are the only important person in the world, you do not need regulations as you do not care.

Now the challenge comes of how we deal with regulations.

 

The WHY!

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?

There is the difference between the long-term WHY (strategy) and the short-term WHY(emotion). For most individuals the short-term WHY prevails, for companies and governments the long term WHY should lead their decisions.

Unfortunately short term decisions (money, food, comfort, legacy habits) get a higher priority by humans instead of long term goals (transformations and transitions).

Daniel Kahneman, Nobel prize winner writing about this in his book Thinking Fast and Slow. We see this dilemma, fast based on gut-feeling or slow based on a real analysis in companies, we see it in our society .

  • How many companies have a 10-years sustainable strategy and consistent roadmap?
  • How many countries have a 10-years sustainable strategy and consistent roadmap?

Jan Bosch also mentioned the importance of the WHY in his Digital Reflection #15: Why do you get out of bed in the morning? Did you ask yourself this question?

Sustainability, like digitization in PLM, requires a behavioral change. From traditional linear coordinated ways of working we need to learn to work in a more complex and advanced environment with real-time data. Luckily if the data is accurate AI will help us to manage the complexity.

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 (from Expert to T-shape) and new skills are needed. Are you able to acquire those new skills or do you give up and complain about the future?

The same challenges happen related to sustainability. Our current (western) habits are draining the planet and only behavioral changes can stop or reduce the damage. Most of us are aware that the planet is limited in resources and we need an energy transition in the long term. But are you able to learn those new behaviors or do you give up and hold on to the good old past?

Note: It’s important to understand that individual actions are not the primary cause of the climate crisis, nor can they alone resolve it. This idea is often promoted by industries. The bigger question is whether our societies can change—consider where financial resources are being allocated.

 

Sustainability and Systems Thinking

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.

I wrote two posts in 2022 about Systems Thinking t: SYSTEMS THINKING – a must-have skill in the 21st century and as a follow-up based on interactions Systems Thinking: a second thought. The challenge with Systems Thinking is that the solution is not black or white and requires brain power.

 

Sustainability and Political Leadership

With what is happening currently in our societies you can see that sustainability is strongly connected to its country’s political system. The bad news for long term issues democracy is probably the worst. Let me share some observations.

Europe

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.

There are so many Dunning-Kruger experts roaring down the common sense debates – mainly in democratic countries. It would be great if people started from the WHY. WHY is someone acting – is it a short-term gain/fear to loose or is there a long-term strategy.

As long as Europe can maintain its consensus culture there is hope for the long-term.

US

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 his 2022 interview he shares his vision that the future is in solar energy and batteries with nuclear needed for the transition. Also he is no fan of longevity – quote from the video (5:30)

Most people don’t change their mind, they just die. And if they don’t die we will be stuck with old ideas and society won’t advance.

It is a great example of “If you cannot beat them – join them” and then use them to fund your missions. A narcistic president becomes your helper to achieve your long-term strategy.

 

Saudi Arabia

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.

 

China

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.

However their energy transition towards solar, water, wind and even nuclear goes so much faster than committed in the Paris agreements, as China has a long-term strategy to be energy independent and to be the major supplier in the energy transition. The long-term WHY is clear.

 

Russia

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.

 

 

Conclusion

PLM and Sustainability are important for the long-term, despite the throw-back you might see on the short term due to politics and lobbies. In addition we need courage to keep on focusing on the long-term as our journey has just started.

Feel free to share your thoughts with compassion and respect for other opinions.

 

My 2025 focus

January 8, 2025 in Artificial Intelligence, Change, Data centric, PLM | Tags: , , , , | 2 comments

First, I wish you all a prosperous 2025 and hope you will take the time to digest information beyond headlines.

Taking time to digest information is my number one principle now, which means you will see fewer blog posts from my side and potentially more podcast recordings.

My theme for 2025 : “It is all about people, data,
a sustainable business and a smooth digital transformation”.

 

Fewer blog posts

Fewer blog posts, as although AI might be a blessing for content writers, it becomes as exciting as Wikipedia pages. Here, I think differently than Oleg Shilovitsky, whose posts brought innovative thoughts to our PLM community – “Just my thoughts”.

Now Oleg endorses AI, as you can read in his post: PLM in 2025: A new chapter of blogging transformation.  I asked ChatGPT to summarize my post in 50 words, and this is the answer I got – it saves you reading the rest:

The author’s 2025 focus emphasizes digesting information deeply, reducing blog posts, and increasing podcast recordings exploring real-life PLM applications. They stress balancing people and data-centric strategies, sustainable digital transformation, AI’s transformative role, and forward-looking concepts like Fusion Strategy. Success requires prioritizing business needs, people, and accurate data to harness AI’s potential.

Summarizing blog posts with AI saves you time. Thinking about AI-generated content, I understand that when you work in marketing, you want to create visibility for your brand or offer.

Do we need a blogging transformation? I am used to browsing through marketing content and then looking for the reality beyond it – facts and figures. Now it will be harder to discover innovative thoughts in this AI-generated domain.

Am I old fashioned? Time will tell.

 

More podcast recordings

As I wrote in a recent post, “PLM in real life and Gen AI“, I believe we can learn much from exploring real-life examples. You can always find the theory somewhere and many of the articles make sense and address common points. Some random examples:

Similar recommendations exist for topics like ERP, MES, CRM or Digital Transformation (one of the most hyped terms).

They all describe WHAT to do or not to do. The challenge however is:  HOW to apply this knowledge in your unique environment, considering people, skills, politics and culture.

With the focus on the HOW, I worked with Helena Gutierrez last year on the Share PLM podcast series 2. In this series, we interviewed successful individuals from various organizations to explore HOW they approached PLM within their companies. Our goal was to gain insights from their experiences, particularly those moments when things didn’t go as planned, as these are often the most valuable learning opportunities.

I am excited to announce that the podcast will continue this year with Series 3! Joining me this season will be Beatriz Gonzales, Share PLM’s co-founder and new CEO. For Series 3, we’ve decided to broaden the scope of our interviews. In addition to featuring professionals working within companies, we’ll also speak with external experts, such as coaches and implementation partners, who support organizations in their PLM journey.

Our goal is to uncover not only best practices from these experts but also insights into emerging “next practices.”

Stay tuned for series 3!

 

#datacentric or #peoplecentric ?

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: Driving Transformation: Data or People First?

We all agree here that it is not either one or the other, and as the discussion related to the post further clarifies, it is about a business strategy that leads to both of these aspects.

This is the challenge with strategies. A strategy can be excellent – on paper – the success comes from the execution.

This discussion reminds me of the lecture Yousef Hooshmand gave at the PLM platform in the Netherlands last year – two of his images that could cover the whole debate:

Whatever you implement starts from the user experience, giving the data-centric approach the highest priority and designing the solution for change, meaning avoiding embedded hard-coded ways of working.

While companies strive to standardize processes to provide efficiency and traceability, the processes should be reconfigurable or adaptable when needed, reconfigured on reliable data sources.

Jan Bosch shared this last thought too in his Digital Reflection #5: Cog in the Machine. My favorite quote from this refection

“However, in a world where change is accelerating, we need to organize ourselves in ways that make it easy to incorporate change and not ulcer-inducing hard. How do we get there?”

Of course, before we reach tools and technology, the other image Yousef Hooshmand shared below gives a guiding principle that I believe everyone should follow in their context.

It starts with having a C-level long-term commitment when you want to perform a business transformation, and then, in an MVP approach, you start from the business, which will ultimately lead you to the tools and technologies.

The challenge seen in this discussion is that:

most manufacturing companies are still too focused on investing in what they are good at now and do not explore the future enough.

This behavior is why Industry 4.0 is still far from being implemented, and the current German manufacturing industry is in a crisis.

It requires an organization that understands the big picture and has a (fusion) strategy.

 

Fusion Strategy ?

Is the Fusion Strategy the next step, as Steef Klein often mentions in our PLM discussions?  The Fusion Strategy, introduced by world-renowned innovation guru Vijay Govindarajan  (The Three Box Solution) and digital strategy expert Venkat Venkatraman (Fusion Strategy), offers a roadmap that will help industrial companies combine what they do best – creating physical products – with what digital technology companies do best – capturing and analyzing data through algorithms and AI.

 

It is a topic I want to explore this year and see how to connect it to companies in my ecosystem. It is an unknown phenomenon as most of them struggle with a data-driven foundation and skills and focus on the right AI applications.

 

The End of SaaS?

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.

I wrote about these concepts in my PLM Roadmap / PDT Europe review. Look at the section: R-evolutionizing PLM and ERP and Heliple. At that time, I shared the picture below, which illustrates the digital enterprise.

The five depicted platforms in the image ( IIoT, CRM, PLM, ERP, MES) are not necessarily a single system. They can be an ecosystem of applications and services providing capabilities in that domain. In modern ways of thinking, each platform could be built upon a SaaS portfolio, ensuring optimal and scalable collaboration based on the company’s needs.

Implementing such an enterprise based on a combination of SaaS offerings might be a strategy for companies to eliminate IT overhead.

However, known forward-thinking experts like Vijay Govindarajan and Venkat Venkatraman with their Fusion Strategy. Also, Satya Nadella, CEO of Microsoft, imagines instead of connected platforms a future with an AI layer taking care of the context of the information – the Microsoft Copilot message. Some of his statements:

This transformation is poised to disrupt traditional tools and workflows, paving the way for a new generation of applications.

The business logic is all going to these AI agents. They’re not going to discriminate between what the backend is — they’ll update multiple databases, and all the logic will be in the AI tier.  

Software as a Business Weapon?

Interesting thoughts to follow and to combine with this Forbes article, The End Of The SaaS Era: Rethinking Software’s Role In Business by Josipa Majic Predin.  She introduces the New Paradigm: Software as a Business Weapon.

Quote:

Instead of focusing solely on selling software subscriptions, innovative companies are using software to enhance and transform existing businesses. The goal is to leverage technology to make certain businesses significantly more valuable, efficient, and competitive.

This approach involves developing software that can improve the operations of “real world” businesses by 20-30% or more. By creating such powerful tools, technology companies can position themselves to acquire or partner with the businesses they’ve enhanced, thereby capturing a larger share of the value they’ve created.

 

It is interesting to see these thoughts popping up, usually 10 to 20 years ahead before companies adopt them. However, I believe with AI’s unleashed power, this is where we should be active and learn. It is an exciting area where terms like eBOM or mBOM sound hackneyed.

 

Sustainability?

As a PLM Green Global Alliance member, I will continue to explore topics related to PLM and how they can serve Sustainability. They are connected as the image from the 2022 PLM Roadmap/PDT Europe indicates:

I will keep on focusing on separate areas within my PGGA network.

 

Conclusion

I believe 2025 will be the year to focus on understanding the practical applications of AI. Amid the hype and noise, there lies significant potential to re-imagine our PLM landscape and vision. However, success begins with prioritizing the business, empowering people, and ensuring accurate data.

 

 

 

 

PLM and Sustainability: talking with CIMPA

January 6, 2025 in Circulair Economy, Data centric, Digital Enterprise, Digital Twin, Life Cycle Analysis, Life Cycle Assessment, PLM, Sustainability | Tags: , , , | Leave a comment

Most times in this PLM and Sustainability series, Klaus Brettschneider and Jos Voskuil from the PLM Green Global Alliance core team speak with PLM related vendors or service partners.

This year we have been speaking with Transition Technologies PSC, Configit, aPriori, Makersite and the PLM Vendors PTC, Siemens and  SAP.

Where the first group of companies provided complementary software offerings to support sustainability – “the fourth dimension”–  the PLM vendors focused more on the solutions within their portfolio.

This time we spoke with , CIMPA PLM services,  a company supporting their customers with PLM and Sustainability challenges, offering an end-to-end support.

What makes them special is that they are also core partner of the PLM Global Green Alliance, where they moderate the Circular Economy theme – read their introduction here: PLM and Circular Economy.

 

CIMPA PLM services

We spoke with Pierre DAVID and Mahdi BESBES from CIMPA PLM services. Pierre is an environmental engineer and Mahdi is a consulting manager focusing on parts/components traceability in the context of sustainability and a circular economy. Many of the activities described by Pierre and Mahdi were related to the aerospace industry.

We had an enjoyable and in-depth discussion of sustainability, as the aerospace industry is well-advanced in traceability during the upstream design processes. Good digital traceability is an excellent foundation to extend for sustainability purposes.

 

CSRD, LCA, DPP, AI and more

A bunch of abbreviations you will have to learn. We went through the need for a data-driven PLM infrastructure to support sustainability initiatives, like Life Cycle Assessments and more. We zoomed in on the current Corporate Sustainability Reporting Directive(CSRD) highlighting the challenges with the CSRD guidelines and how to connect the strategy (why we do the CSRD) to its execution (providing reports and KPIs that make sense to individuals).

In addition, we discussed the importance of using the proper methodology and databases for lifecycle assessments. Looking forward, we discussed the potential of AI and the value of the Digital Product Passport for products in service.

Enjoy the 37 minutes discussion and you are always welcome to comment or start a discussion with us.

 

What we learned

  • Sustainability initiatives are quite mature in the aerospace industry and thanks to its nature of traceability, this industry is leading in methodology and best practices.
  • The various challenges with the CSRD directive – standardization, strategy and execution.
  • The importance of the right databases when performing lifecycle analysis.
  • CIMPA is working on how AI can be used for assessing environmental impacts and the value of the Digital Product Passport for products in service to extend its traceability

Want to learn more?

Here are some links related to the topics discussed in our meeting:

 

Conclusion
The discussion was insightful, given the advanced environment in which CIMPA consultants operate compared to other manufacturing industries. Our dialogue offered valuable lessons in the aerospace industry, that others can draw on to advance and better understand their sustainability initiatives

 

 

 

2024 PLM reflections

December 19, 2024 in Artificial Intelligence, Change, Data centric, Innovation, PLM, Sustainability | Tags: , , , , | Leave a comment

This year, I will celebrate 25 years since I started my company, TacIT, to focus on knowledge management. However, quickly, I was back in the domain of engineering data management, which became a broader topic, which we now call PLM.

Looking back, there have been significant changes in these 25 years, from systems to strategy, for documents to data, from linear to iterative. However, in this post, I want to look at my 2024 observations to see where we can progress. This brings me to the first observation.

 

PLM is human

Despite many academic and marketing arguments describing WHAT and WHY companies need specific business or software capabilities, there is, above all, the need for people to be personally inspired and connected. We want to belong to a successful group of people, teams and companies because we are humans, not resources.

It is all about people, which was also the title of my session during the March 2024 3DEXPERIENCE User Conference in Eindhoven (NL). I led a panel discussion on the importance of people with Dr. Cara Antoine, Daniel Schöpf, and Florens Wolters, each of whom actively led transformational initiatives within their companies.

Through Dr. Cara Antoine, e at Capgemini and a key voice for women in tech, I learned about her book Make It Personal. The book inspired me and motivated me to continue using a human-centric approach. Give this book to your leadership and read it yourself. It is practical, easy to read, and encouraging

Recently, in my post “PLM in real life and Gen AI“, I shared insights related to PLM blogs and Gen AI – original content is becoming increasingly the same, and the human touch is disappearing, while generating more and longer blogs.

I propose keeping Gen AI-generated text for the boring part of PLM and exploring the human side of PLM engagements in blogs. What does this mean? In the post, I also shared the highlights of the Series 2 podcast I did together with Helena Gutierrez from Share PLM. Every recording had its unique human touch and knowledge.

We are now in full preparation for Series 3—let us know who your hero is and who should be our guest in 2025!

 

PLM is business

One of the most significant changes I noticed in my PLM-related projects was that many of the activities connected the PLM activities to the company’s business objectives. Not surprisingly, it was mostly a bottom-up activity, explaining to the upper management that a modern, data-driven PLM strategy is crucial to achieving business or sustainability goals.

I wrote two long posts about these experiences. The first one,” PLM – business first,” zooms in on the changing mindset that PLM is not an engineering system anymore but part of a digital infrastructure that supports companies in achieving their business goals. The image below from Dr. Yousef Hooshmand is one of my favorites in this context. The 5 + 1 steps, where the extra step is crucial: Long Executive Commitment.

So, to get an executive commitment, you need to explain and address business challenges.

Executive commitment and participation can be achieved through a Benefits Dependency Network approach, as illustrated in this webinar I did with the Heliple-2 team, where we were justifying the business needs for Federated PLM. More about the Federated PLM part in the next paragraph.

Another point to consider is that when the PLM team is part of the IT organization (the costs side), they have a big challenge in leading or even participating in business discussions. In this context, read (again) Jan Bosch’s post: Structure Eats Strategy.

The second post, more recent, summarized the experiences I had with several customer engagements. The title says it all: “Don’t use the P**-word! – 5 lessons learned“, with an overlap in content with the first post.

Conclusion:  A successful PLM strategy starts with the business and needs storytelling to align all stakeholders with a shared vision or goal.

 

PLM is technology

This year has seen the maturation of PLM technology concepts. We are moving away from a monolithic PLM system and exploring federated and connected infrastructures, preferably a mix of Systems of Record (the old PLMs/ERPs) and Systems of Engagement (the new ways of domain collaboration). The Heliple project manifests such an approach, where the vertical layers are Systems of Record, and the horizontal modules could be Systems of Engagement.

 

I had several discussions with typical System of Engagement vendors, like Colab (“Where traditional PLM fails”) and Partful (“Connected Digital Thread for Lower and Mid-market OEMs“), but I also had broader discussions during the PLM Roadmap PDT Europe conference – see: R-evolutionizing PLM and ERP and Heliple.

I also follow Dr. Jorg Fischer, who lectures about digital transformation concepts in the manufacturing business domain. Unfortunately, for a broader audience, Jörg published a lot in German, and typically, his references for PLM and ERP are based on SAP and Teamcenter. His blog posts are always interesting to follow – have a look at his recent blog in English: 7 keys to solve PLM & ERP.

Of course, Oleg Shilovitsky’s impressive and continuous flow of posts related to modern PLM concepts is amazing—just browse through his Beyond PLM home page to read about the actual topics happening in his PLM ecosystem or for example, read about modern technology concepts in this recent OpenBOM article.

Conceptually, we are making progress. As a commonality, all future concepts focus on data, not so much on managing documents—and here comes the focus on data.

 

PLM needs accurate data

In a data-driven environment, apps or systems will use a collection of datasets to provide a user with a working environment, either a dashboard or an interactive real-time environment. Below is my AI (Artist Impression) of a digital enterprise.

Of course, it seems logical; the data must be accurate as you no longer have control over access to the data in a data-driven environment. You can be accountable for the data; others can consume the data you created without checking its accuracy by your guidance.

Therefore, data governance and an excellent enterprise architecture are crucial to support the new paradigm:

The nearest source of truth supported by a single source of change
Quote: Yousef Hoohmand

Forget the Single Source of Truth idea, a previous century paradigm.

With data comes Artificial intelligence and algorithms that can play an essential role in your business, providing solutions or insights that support decision-making.

In 2024, most of us have been exploring the benefits of ChatGPT and Generative AI. You can describe examples of where AI could assist in every aspect of the product lifecycle. I saw great examples from Eaton, Ocado, and others at the PLM Roadmap/PDT Europe conference.

See my review here: A long week after the PLM Roadmap / PDT Europe conference.

Still, before benefiting from AI in your organization, it remains essential that the AI runs on top of accurate data.

Sustainability needs (digital) PLM

This paragraph is the only reverse dependency towards PLM and probably the one that is less in people’s minds, perhaps because PLM is already complex enough. In 2024, with the PLM Green Global Alliance, we had good conversations with PLM-related software vendors or service partners (aPriori, Configit, Makersite, PTC, SAP, Siemens and Transition Technologies PSC) where we discussed their solutions and how they are used in the field by companies.

We discovered here that most activities are driven by regulations, like ESG reporting, the new CSRD directive for Europe and the implementation of the Digital Product Passport. What is clear from all these activities is that companies need to have a data-driven PLM infrastructure to connect product data to environmental impacts, like carbon emissions equivalents.

Besides complying with regulations, I have been discussing the topic of Product-As-A-Service, or the Product Service System, this year, with excellent feedback from Dave Duncan. You can find a link to his speech: Improving Product Sustainability – PTC with PGGA.

Also, during the PLM Roadmap / PDT Europe conference, I discussed this topic, explaining that achieving a circular economy is a long-term vision, and the starting point is to establish a connected infrastructure within your organizations and with your customers/users in the field.

Sustainability should be on everyone’s agenda. From the interactions on LinkedIn, you can see that we prefer to discuss terms like PDM/PLM or eBOM/mBOM in the PLM domain. Very few connect PLM to sustainability.

Sustainability is a long-term mission; however, as we have seen from long-term missions, they can be overwhelmed by the day’s madness and short-term needs.

 

PLM is Politics

You might not expect this paragraph in my log,  as most PLM discussions are about the WHAT and the WHY of a PLM solution or infrastructure. However, the most challenging part of PLM is the HOW, and this is the area that I am still focused on.

In the early days of mediating mainly in SmarTeam implementations, it became clear that the technology was not the issue. A crisis was often due to a lack of (technical) skills or methodology and misplaced expectations.

Unicorns & HIPPOs in an enterprise (Peter Vind)

When the way out became clear, politics often started. Sometimes, there was the HIPPO (HIghest Paid Person’s Opinion) in the company, as Peter Vind explained, or there was the blame game, which I described in my 2019 “The PLM blame game post”.

What makes it even more difficult is that people’s opinions in PLM discussions are often influenced by their friendly relations or history with a particular vendor or implementer from the past, which troubles a proper solution path.

These aspects are challenging to discuss, and nobody wants to discuss them openly. A company (and a country) must promote curiosity instead of adhering to mainstream thinking and working methods. In our latest Share PLM podcast, Brian Berger, a VP at Metso, mentions the importance of diversity within an organization.

“It is a constant element of working in a global business, and the importance cannot be overstated.”

This observation should make us think again when we want to simplify everything and dim the colors.

 

Conclusion

Initially, I thought this would be a shorter post, but again, it became a long read – therefore, perhaps ideal when closing 2024 and looking forward to activities and focus for 2025. Use this time to read books and educate yourself beyond the social media posts (even my blogs are limited 😉)

In addition, I noticed the build-up of this post was unconsciously influenced by Martijn Dullaart‘s series of messages titled “Configuration Management is ……”. Thanks, Martijn, for your continuous contributions to our joint passion – a digital enterprise where PLM and CM flawlessly interact based on methodology and accurate data.

The Product Service System and a Circular Economy

December 2, 2024 in Artificial Intelligence, Change, Circulair Economy, digital thread, Digital Twin, PLM, Sustainability | Tags: , , , | Leave a comment

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.

The difference between our societies, all living on the same planet, is illustrated in the image below, illustrating the unfairness of this situation

What the image also shows is a warning that we all have to act, as step by step, we will reach planet boundaries for resources.

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.

For those generations staying on this planet, there is only one option: we need to change our economy of unlimited growth and reconsider how we use our natural resources.

 

The circular economy?

You are probably familiar with the butterfly diagram from the Ellen MacArthur Foundation, where we see the linear process: Take-Make-Use-Waste in the middle.

This approach should be replaced by more advanced regeneration loops on the left side and the five R’s on the right: Reduce, Repair, Reuse, Refurbish and Recycle as the ultimate goal is the minimum leakage of Earth resources.

Closely related to the Circular Economy concept is the complementary Cradle-To-Cradle design approach. In this case, while designing our products, we also consider the end of life of a product as the start for other products to be created based on the materials used.

The CE butterfly diagram’s right side is where product design plays a significant role and where we, as a PLM community, should be active. Each loop has its own characteristics, and the SHARE loop is the one I focused on during the recent PLM Roadmap / PDT Europe conference in Gothenburg.

As you can see, the Maintain, Reuse, Refurbish and Recycle loops depend on product design strategies, in particular, modularity and, of course, depending on material choices.

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.

Watch the funny meme in this post: “We did everything  we could– we brought our own bags.”

The title of my presentation was: Products as a Service – The Ultimate Sustainable Economy?
You can find my presentation on SlideShare here.

Let’s focus on the remainder of the presentation’s topic: Product As A Service.

 

The Product Service System

Where Product As A Service might be the ultimate dream for an almost wasteless society, Ida Auken, a Danish member of the parliament, gave a thought-provoking lecture in that context at the 2016 World Economic Forum.  Her lecture was summarized afterward as

“In the future, you will own nothing and be happy.”

A theme also picked up by conspiracy thinkers during the COVID pandemic, claiming “they” are making us economic slaves and consumers. With Black Friday in mind, I do not think there is a conspiracy; it is the opposite.

Closer to implementing everywhere Product as a Service for our whole economy, we might be going into Product Service Systems.

As the image shows, a product service system is a combination of providing a product with related services to create value for the customer.

In the ultimate format, the manufacturer owns the products and provides the services, keeping full control of the performance and materials during the product lifecycle. The benefits for the customer are that they pay only for the usage of the product and, therefore, do not need to invest upfront in the solution (CAPEX), but they only pay when using the solution (OPEX).

A great example of this concept is Spotify or other streaming services. You do not pay for the disc/box anymore; you pay for the usage, and the model is a win-win for consumers (many titles) and producers (massive reach).

Although the Product Service System will probably reach consumers later, the most significant potential is currently in the B2B business model, e.g., transportation as a service and special equipment usage as a service. Examples are popping up in various industries.

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

 

Step 1: Get (digital) connected to your Product and customer

A foundational step companies must take is to create a digital infrastructure to support all stakeholders in the product service offering. Currently, many companies have a siloed approach where each discipline Marketing/Sales, R&D, Engineering, Manufacturing and Sales will have their own systems.

Digital Transformation in the PLM domain is needed here – where are you on this level?

But it is not only the technical silos that impede the end-to-end visibility of information. If there are no business targets to create and maintain the end-to-end information sharing, you can not expect it to happen.

Therefore, companies should invest in the digitalization of their ways of working, implementing an end-to-end digital thread AND changing their linear New Product Development process into a customer-driven DevOp approach. The PTC image below shows the way to imagine a end-to-end connected environment

In a Product Service System, the customer is the solution user, and the solution provider is responsible for the uptime and improvement of the solution over time.

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. Don’t forget that AI (and Digital Twins) runs best on reliable data.

 

Step 2 From Product to Experience

A Product Service System is not business as usual by providing products with some additional services. Besides concepts such as Digital Thread and Digital Twins of the solution, there is also the need to change the company’s business model.

In the old way, customers buy the product; in the Product Service System, the customer becomes a user. We should align the company and business to become user-centric and keep the user inspired by the experience of the Product Service System.

In this context, there are two interesting articles to read:

The change in business model means that companies should think about a circular customer journey.

As the company will remain the product owner, it is crucial to understand what happens when the customers stop using the service or how to ensure maintenance and upgrades.

In addition, to keep the customer satisfied, it remains vital to discover the customer KPIs and how additional services could potentially improve the relationship. Again, AI can help find relationships that are not yet digitally established.

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.

This will not happen quickly as, besides the vision, there needs to be an evolutionary path to the new business model.

Therefore, companies must analyze their portfolio and start experimenting with a small product, converting it into a product service system. Starting simple allows companies to learn and be prepared for scaling up.

A Product Service System also influences a company’s cash flow as revenue streams will change.

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.

 

Step 3 Towards a doughnut economy?

The last step is probably a giant step or even a journey. An economic mindset shift is needed from the ever-growing linear economy towards an economy flourishing for everyone within economic, environmental and social boundaries.

Unlimited growth is the biggest misconception on a planet reaching its borders. Either we need more planets, or we need to adjust our society.

In that context, I read the book “The Doughnut Economy” by Kate Raworth, a recognized thought leader who explains how a future economic model can flourish, including a circular economy, and you will be happy.

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.

It is a logical process where people and boundaries will learn to find a new balance. Will it be in a Doughnut Economy, or did we overlook some bright other concepts?

 

Conclusion

The week after Black Friday and hopefully the month after all the Christmas presents, it is time to formulate your good intentions for 2025. As humans, we should consume less; as companies, we should direct our future to a sustainable future by exploring the potential of the Product Service System and beyond.

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  2. Unknown's avatar
  3. Håkan Kårdén's avatar

    Jos, all interesting and relevant. There are additional elements to be mentioned and Ontologies seem to be one of the…

  4. Lewis Kennebrew's avatar

    Jos, as usual, you've provided a buffet of "food for thought". Where do you see AI being trained by a…

  5. Håkan Kårdén's avatar