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In the last few weeks, I thought I had a writer’s block, as I usually write about PLM-related topics close to my engagements.
Where are the always popular discussions related to EBOM or MBOM? Where is the Form-Fit-Function discussion or the traditional “meaningful numbers” discussions?

These topics always create a lot of interaction and discussion, as many of us have mature opinions.

However, last month I spent most of the time discussing the connection between digital PLM strategies and sustainability. With the Russian invasion of Ukraine, leading to high energy prices, combined with several climate disasters this year, people are aware that 2022 is not a year as usual. A year full of events that force us to rethink our current ways of living.

The notion of urgency

Sustainability for the planet and its people has all the focus currently. COP27 gives you the impression that governments are really serious. Are they? Read this post from Kimberley R. Miner, Climate Scientist at NASA, Polar Explorer& Professor.

She doubts if we really grasp the urgency needed to address climate change. Or are we just playing to be on stage? I agree with her doubts.

So what to do with my favorite EBOM-MBOM discussions?

Last week I attended an event organized by Dassault Systems in the Netherlands for their Dutch/Belgium customers.

The title of the event was: Sustainable innovation for a digital future. I expected a techy event. Click on the image to see the details.

Asking my grandson, who had just started to his study Aerospace Engineering in Delft (NL), learning to work with CAD and PLM-tools, to join me – he replied:

“Too many software demos”

It turned out that my grandson was wrong. The keynote speech from Ruud Veltenaar made most of the audience feel uncomfortable. He really pointed to the fact that we are aware of climate change and our impact on the planet, but in a way, we are paralyzed. Nothing new, but confronting and unexpected when going to a customer event.

Ruud’s message: Accept that we are at the end of an existing world order, and we should prepare for a new world order with the right moral leadership. It starts within yourself. Reflect on who you really are, where you are in your life path, and finally, what you want.

It sounds simple, and I can see it helps to step aside and reflect on these points.

Otherwise, you might feel we are in a rat race as shown below (recommend to watch).

The keynote was the foundation for a day of group and panel discussions on sustainability. Learning from their customers their sustainability plans and experiences.

It showed Dassault Systems, with its 2012  purpose (click on the link to see its history), Harmonizing Products, Nature and Life is ahead of the curve (at least they were for me).

The event was energizing, and my grandson was wrong:
“No software – next time?”

 

The impact of legacies – data, processes & people

For those who haven’t read my previous post, The week after PLM Roadmap / PDT Europe 2022, I wrote about the importance of Heterogeneous and federated PLM, one of the discussions related to data-driven PLM.

Looking back, I have been writing about data-driven PLM since 2014, and few companies have made progress here. Understandable, first of all, due to legacy data, which is not in the right format or quality to support data-driven processes.

However, also here, legacy processes and legacy people are blocking the change. There is no blame here; it is difficult to change. You might have a visionary management team, but then it comes down to the execution of the strategy. The organizational structure and the existing people skills are creating more resistance than progress.

For that reason, I wrote this post in 2015: PLM and Global Warming, where I compared the progress we made within our PLM community with the lack of progress we are making in solving global warming. We know the problem, but we are unable to act due to the lack of feeling the urgency.

This blog post triggered Rich McFall to start together in 2018 the PLM Global Green Alliance.

 

In my PLM Roadmap / PDT Europe session Sustainability and Data-driven PLM – the perfect storm, I raised the awareness that we need to speed up. We have 10 perhaps 15 years to implement radical changes, according to scientists, before we reach irreversible tipping points.

 

Why PLM and Sustainability?

Sustainability starts with the business strategy. How does your company want to contribute to a more sustainable future? The strategy to follow with probably the most impact is the concept of a circular economy – image below and more info here.

The idea behind the circular economy is to minimize the need for new finite materials (the right side) and to use for energy delivery only renewables. Implementing these principles clearly requires a more holistic design of products and services. Each loop should be analyzed and considered when delivering solutions to the market.

Therefore, a logical outcome of the circular economy would be transforming from selling products to the market towards a product-as-a-service model. In this case, the product manufacturer becomes responsible for the full product lifecycle and its environmental impact.

And here comes the importance of PLM. You can measure and tune your environmental impact during production in your ERP or MES environment. However, 80 % of the environmental impact is defined during the design phase, the domain of PLM. All these analysis together are called Life Cycle Analysis or Life Cycle Assessment (LCA). A practice that starts at the moment you start to think about a product or solution – a specialized systems thinking approach.

So how to define and select the right options for future products?

 

Virtual products / Digital Twins

This is where sustainability is pushing for digitization of the product lifecycle. Building and analyzing products in the virtual world is much cheaper than working with physical prototypes.

The importance of a model-based approach here allows companies efficiently deal with trade-off studies for each solution.

In addition, the choice and the behavior of materials also have an impact. These material properties will come from various databases, some based on hazardous substances, others on environmental parameters. Connecting these databases to the virtual model is crucial to remain efficient.

Imagine you need manually collect and process in these properties whenever studying an alternative. The manual process will be too costly (fewer trade-offs and not finding the optimum) and too slow (time-to-market impact).

That’s why I am greatly interested in all the developments related to a federated PLM infrastructure. A monolithic system cannot be the solution for such a model-based environment. In my terminology, here we need an architecture with systems of engagement combined with system(s) of record.

I will publish more on this topic in the future.

In the previous paragraphs, I wrote about the virtual product environment, which some companies call the virtual twin. However, besides the virtual twin, we also need several digital twins. These digital models allow us to monitor and optimize the production process, which can lead to design changes.

Also, monitoring the product in operation using a digital twin allows us to optimize the performance and execution of the solutions in the field.

The feedback from these digital twins will then help the company to improve the design and calibrate their simulation models. It should be a closed loop. You can find a more recent discussion related to the above image here.

 

Our mission

At this moment, sustainability is at the top of my personal agenda, and I hope for many of you. However, besides the choices we can make in our personal lives, there is also an area where we, as PLM interested parties, should contribute: The digitization of the product lifecycle as an enabler for a sustainable business.

Without mature concepts for a connected enterprise, implementing sustainable products and business processes will be a wish, not a strategy. So add digitization to your skillset and use it in the context of sustainability.

Conclusion

It might look like this PLM blog has become an environmental blog. This might be right, as the environmental impact of products and solutions is directly related to product lifecycle management. However, do not worry. In the upcoming time, I will focus on the aspects and experiences of a connected enterprise. I will leave the easier discussions (EBOM/MBOM/FFF/Smart Numbers) from a coordinated enterprise as they are. There is work to do shortly. Your thoughts?

 

 

 

 

 

 

 

With great pleasure, I am writing this post, part of a tradition that started for me in 2014. Posts starting with “The weekend after …. “describing what happened during a PDT conference, later the event merged with CIMdata becoming THE PLM event for discussions beyond marketing.

For many of us, this conference was the first time after COVID-19 in 2020. It was a 3D (In person) conference instead of a 2D (digital) conference. With approximately 160 participants, this conference showed that we wanted to meet and network in person and the enthusiasm and interaction were great.

The conference’s theme, Digital Transformation and PLM – a call for PLM Professionals to redefine and re-position the benefits and value of PLM, was quite open.

There are many areas where digitization affects the way to implement a modern PLM Strategy.

Now some of my highlights from day one. I needed to filter to remain around max 1500 words. As all the other sessions, including the sponsor vignettes, were informative, they increased the value of this conference.


Digital Skills Transformation -Often Forgotten Critical Element of Digital Transformation

Day 1 started traditionally with the keynote from Peter Bilello, CIMdata’s president and CEO. In previous conferences, Peter has recently focused on explaining the CIMdata’s critical dozen (image below). If you are unfamiliar with them, there is a webinar on November 10 where you can learn more about them.

All twelve are equally important; it is not a sequence of priorities. This time Peter spent more time on Organisational Change management (OCM), number 12 of the critical dozen – or, as stated, the Digital Transformation’s Achilles heel. Although we always mention people are important, in our implementation projects, they often seem to be the topic that gets the less focus.

We all agree on the statement: People, Process, Tools & Data. Often the reality is that we start with the tools, try to build the processes and push the people in these processes. Is it a coincidence that even CIMdata puts Digital Skills transformation as number 12? An unconscious bias?

This time, the people’s focus got full attention. Peter explained the need for a digital skills transformation framework to educate, guide and support people during a transformation. The concluding slide below says it all.


Transformation Journey and PLM & PDM Modernization to the Digital Future

The second keynote of the day was from Josef Schiöler, Head of Core Platform Area PLM/PDM from the Volvo Group. Josef and his team have a huge challenge as they are working on a foundation for the future of the Volvo Group.

The challenge is that it will provide the foundation for new business processes and the various group members, as the image shows below:


As Josef said, it is really the heart of the heart, crucial for the future. Peter Bilello referred to this project as open-heart surgery while the person is still active, as the current business must go on too.

The picture below gives an impression of the size of the operation.

And like any big transformation project also, the Volvo Group has many questions to explore as there is no existing blueprint to use.

To give you an impression:

  • How to manage complex documentation with existing and new technology and solution co-existing?
    (My take: the hybrid approach)
  • How to realize benefits and user adoption with user experience principles in mind?
    (My take: Understand the difference between a system of engagement and a system of record)
  • How to avoid seeing modernization as pure an IT initiative and secure that end-user value creation is visible while still keeping a focus on finalizing the technology transformation?
    (My take: think hybrid and focus first on the new systems of engagement that can grow)
  • How to efficiently partner with software vendors to ensure vendor solutions fit well in the overall PLM/PDM enterprise landscape without heavy customization?
    (My take: push for standards and collaboration with other similar companies – they can influence a vendor)

Note: My takes are just a starting point of the conversation. There is a discussion in the PLM domain, which I described in my blog post: A new PLM paradigm.

 

The day before the conference, we had a ½ day workshop initiated by SAAB and Eurostep where we discussed the various angles of the so-called Federated PLM.

I will return to that topic soon after some consolidation with the key members of that workshop.


Steering future Engineering Processes with System Lifecycle Management

Patrick Schäfer‘s presentation was different than the title would expect. Patrick is the IT Architect Engineering IT from ThyssenKrupp Presta AG. The company provides steering systems for the automotive industry, which is transforming from mechanical to autonomous driving, e-mobility, car-to-car connectivity, stricter safety, and environmental requirements.

The steering system becomes a system depending on hardware and software. And as current users of Agile PLM, the old Eigner PLM software, you can feel Martin Eigner’s spirit in the project.

I briefly discussed Martin’s latest book on System Lifecycle Management in my blog post, The road to model-based and connected PLM (part 5).

Martin has always been fighting for a new term for modern PLM, and you can see how conservative we are – for sometimes good reasons.

Still, ThyssenKrupp Presta has the vision to implement a new environment to support systems instead of hardware products. And in addition, they had to work fast to upgrade their current almost obsolete PLM environment to a new supported environment.

The wise path they chose was first focusing on a traditional upgrade, meaning making sure their PLM legacy data became part of a modern (Teamcenter) PLM backbone. Meanwhile, they started exploring the connection between requirements management for products and software, as shown below.

From my perspective, I would characterize this implementation as the coordinated approach creating a future option for the connected approach when the organization and future processes are more mature and known.

A good example of a pragmatic approach.


Digital Transformation in the Domain of Products and Plants at Siemens Energy

Per Soderberg, Head of Digital PLM at Siemens Energy, talked about their digital transformation project that started 6 – 7 years ago. Knowing the world of gas- and steam turbines, it is a domain where a lot of design and manufacturing information is managed in drawings.

The ultimate vision from Siemens Energy is to create an Industrial Metaverse for its solutions as the benefits are significant.

Is this target too ambitious, like GE’s 2014 Industrial Transformation with Predix? Time will tell. And I am sure you will soon hear more from Siemens Energy; therefore, I will keep it short. An interesting and ambitious program to follow. Sure you will read about them in the near future. 


Accelerating Digitalization at Stora Enso

Stora Enso is a Finish company, a leading global provider of renewable solutions in packaging, biomaterials, wooden construction and paper. Their director of Innovation Services, Kaisa Suutari, shared Stora Enso’s digital transformation program that started six years ago with a 10 million/year budget (some people started dreaming too). Great to have a budget but then where to start?

In a very systematic manner using an ideas funnel and always starting from the business need, they spend the budget in two paths, shown in the image below.

Their interesting approach was in the upper path, which Kaisa focused on. Instead of starting with an analysis of how the problem could be addressed, they start by doing and then analyze the outcome and improve.

I am a great fan of this approach as it will significantly reduce the time to maturity. However, how much time is often wasted in conducting the perfect analysis?

Their Digi Fund process is a fast process to quickly go from idea to concept, to POC and to pilot, the left side of the funnel. After a successful pilot, an implementation process starts small and scales up.

There were so many positive takeaways from this session. Start with an MVP (Minimal Viable Product) to create value from the start. Next, celebrate failure when it happens, as this is the moment you learn. Finally, continue to create measurable value created by people – the picture below says it all.

It was the second time I was impressed by Stora Enso’s innovative approach. During the PI PLMX 2020 London, Samuli Savo, Chief Digital Officer at Stora Enso, gave us insights into their innovation process. At that time, the focus was a little bit more on open innovation with startups. See my post:  The weekend after PI PLMx London 2020. An interesting approach for other businesses to make their digital transformation business-driven and fun for the people


 A day-one summary

There was Kyle Hall, who talked about MoSSEC and the importance of this standard in a connected enterprise. MoSSEC (Modelling and Simulation information in a collaborative Systems Engineering Context) is the published ISO standard (ISO 10303-243) for improving the decision-making process for complex products. Standards are a regular topic for this conference, more about MoSSEC here.

There was Robert Rencher, Sr. Systems Engineer, Associate Technical Fellow at Boeing, talking about the progress that the A&D action group is making related to Digital Thread, Digital Twins. Sometimes asking more questions than answers as they try to make sense of the marketing definition and what it means for their businesses. You can find their latest report here.

There was Samrat Chatterjee, Business Process Manager PLM at the ABB Process Automation division. Their businesses are already quite data-driven; however, by embedding PLM into the organization’s fabric, they aim to improve effectiveness, manage a broad portfolio, and be more modular and efficient.

The day was closed with a CEO Spotlight, Peter Bilello. This time the CEOs were not coming from the big PLM vendors but from complementary companies with their unique value in the PLM domain. Henrik Reif Andersen, co-founder of Configit; Dr. Mattias Johansson, CEO of Eurostep; Helena Gutierrez, co-founder of Share PLM; Javier Garcia, CEO of The Reuse Company and  Karl Wachtel, CEO, XPLM discussed their various perspectives on the PLM domain.

 

Conclusion

Already so much to say; sorry, I reached the 1500 words target; you should have been there. Combined with the networking dinner after day one, it was a great start to the conference. Are you curious about day 2 – stay tuned, and your curiosity will be rewarded.

 

Thanks to Ewa Hutmacher, Sumanth Madala and Ashish Kulkarni, who shared their pictures of the event on LinkedIn. Clicking on their names will lead you to the relevant posts.

 

As human beings, we believe in the truth. We claim the truth. During my holiday in Greece, the question was, did the Greek Prime Minister tell the truth about the internal spy scandal?

In general, we can say, politicians never speak the real truth, and some countries are trying to make sure there is only one single source of truth – their truth. The concept of a Single Source Of Truth (SSOT) is difficult to maintain in politics.

On social media, Twitter and Facebook, people are claiming their truth. But unfortunately, without any scientific background, people know better than professionals by cherry-picking messages, statistics or even claiming non-existing facts.

Nicely described in The Dunning-Kruger effect. Unfortunately, this trend will not disappear.

If you want to learn more about the impact of social media, read this long article from The Atlantic:  Why the Past 10 Years of American Life Have Been Uniquely Stupid. Although the article is about the US, the content is valid for all countries where social media are still allowed.

The PLM and CM domain is the only place where people still rely on the truth defined by professionals. Manufacturing companies depend on reliable information to design, validate, manufacture and support their products. Compliance and safe products require an accurate and stable product definition based on approved information. Therefore, the concept of SSOT is crucial along the product lifecycle.

The importance may vary depending on the product type. The difference in complexity between an airplane and a plastic toy, for example. It is all about the risk and impact of a failure caused by the product.

During my holiday, the SSOT discussion was sparked on LinkedIn by Adam Keating, and the article starts with:

The “Single Source of Truth (SSOT)” wasn’t built for you. It was built for software vendors to get rich. Not a single company in the world has a proper SSOT.

A bit provocative, as there is nothing wrong with software vendors being profitable. Profitability guarantees the long-time support of the software solution. Remember the PLM consolidation around 2006, when SmarTeam, Matrix One (Dassault), Agile and Eigner & Partner (Oracle) were acquired, disappeared or switched to maintenance mode.

Therefore it makes sense to have a profitable business model or perhaps a real open source business model.

Still, the rest of the discussion was interesting, particularly in the LinkedIn comments. Adam mentioned the Authoritative Source of Truth (ASOT) as the new future. And although this concept becomes more and more visible in the PLM domain, I believe we need both. So, let’s have a look at these concepts.

 

Truth 1.0 – SSOT

Historically, manufacturing companies stored the truth in documents, first paper-based, later in electronic file formats and databases.

The truth consists of drawings, part lists, specifications, and other types of information.

Moreover, the information is labeled with revisions and versions to identify the information.

By keeping track of the related information through documents or part lists with significant numbers, a person in the company could find the correct corresponding information at any stage of the lifecycle.

Later, by storing all the information in a central (PLM) system, the impression might be created that this system is the Single Source Of Truth. The system Adam Keating agitated against in his LinkedIn post.

Although for many companies, the ERP has been the SSOT  (and still is). All relevant engineering information was copied into the ERP system as attached files. Documents are the authoritative, legal pieces of information that a company shares with suppliers, authorities, or customers. They can reside in PLM but also in ERP. Therefore, you need an infrastructure to manage the “truth.”

Note: The Truth 1.0 story is very much a hardware story.

Even for hardware, ensuring a consistent single version of the truth for each product remains difficult. In theory, its design specifications should match the manufacturing definition. The reality, however, shows that often this is not the case. Issues discovered during the manufacturing process are fixed in the plant – redlining the drawing  – is not always processed by engineering.

As a result, Engineering and Manufacturing might have a different version of what they consider the truth.

The challenge for a service engineer in the field is often to discover the real truth. So the “truth” might not always be in the expected place – no guaranteed Single Source Of Truth.

Configuration Management is a discipline connected to PLM to ensure that the truth is managed so that as-specified, as-manufactured, and as-delivered information has been labeled and documented unambiguously. In other words, you could say Configuration Management(CM) is aiming for the Single Source Of Truth for a product.

If you want to read more about the relation between PLM and CM  – read this post: PLM and Configuration Management (CM), where I speak with Martijn Dullaart about the association between PLM and CM.

Martijn has his blog mdux.net and is the Lead Architect for Enterprise Configuration Management at our Dutch pride ASML. Martijn is also Chairperson I4.0 Committee IPX Congress.

Summarizing: The Single Source Of Truth 1.0 concept is document-based and should rely on CM practices, which require skilled people and the right methodology. In addition, some industries require Truth 1.0.

Others take the risk of working without solid CM practices, and the PLM system might create the impression of the SSOT; it will not be the case, even for only hardware.

 Truth 2.0 – ASOT

Products have become more complex, mainly due to the combination of electronics and software. Their different lifecycles and the speed of change are hard to maintain using the traditional PLM approach of SSOT.

It will be impossible to maintain an SSOT, particularly if it is based on documents.

As CM is the discipline to ensure data consistency, it is important to look into the future of CM. At the end of last year, I discussed this topic with 3 CM thought leaders. Martijn Dullaart, Maxime Gravel and Lisa Fenwick discussed with me what they believe the change would be. Read and listen here: The future of Configuration Management.


From the discussion, it became clear that managing all the details is impossible; still, you need an overreaching baseline to identify the severity and impact of a change along the product lifecycle.

New methodologies can be developed for this, as reliable data can be used in algorithms to analyze a change impact. This brings us to the digital thread. According to the CIMdata definition used in the A&D digital twin phase 2 position paper:

The digital thread provides the ability for a business to have an Authoritative Source of Truth(ASOT), which is information available and connected in a core set of the enterprise systems across the lifecycle and supplier networks

The definition implies that, in the end, a decision is made on data from the most reliable, connected source. There might be different data in other locations. However, this information is less reliable. Updating or fixing this information does not make sense as the effort and cost of fixing will be too expensive and give no benefit.

Obviously, we need reliable data to implement the various types of digital twins.

As I am intrigued by the power of the brain – its strengths and weaknesses – the concept of ASOT can also be found in our brains. Daniel Kahneman’s book, Thinking Fast and Slow talks about the two systems/modes our brain uses. The Fast one (System 1 – low energy usage) could be the imaginary SSOT, whereas the Slow one (System 2 – high energy required) is the ASOT. The brain needs both, and I believe this is the same in our PLM domain.

A new PLM Paradigm

In this context, there is a vivid discussion about the System of Record and Systems of Engagement. I wrote about it in June (post: A new PLM paradigm); other authors name it differently, but all express a similar concept. Have a look at these recent articles and statements from:

Author Link to content

Authentise

 

The challenge of cross-discipline collaboration …….

Beyond PLM

 

When is the right time to change your PLM system + discussion

Colab

 

The Single Source Of Truth wasn’t built for you …….

Fraunhofer institute

 

Killing the PLM Monolith – the Emergence of cloud-native System Lifecycle Management (SysLM)

SAAB Group

 

Don’t mix the tenses. Managing the Present and the Future in an MBSE context

Yousef Hooshmand

 

From a Monolithic PLM Landscape to a Federated Domain and Data Mesh

If you want to learn more about these concepts and discuss them with some of the experts in this domain, come to the upcoming PLM Roadmap PTD Europe conference on 18-19 October in Gothenburg, Sweden. Have a look at the final agenda here

Register before September 12 to benefit from a 15 % Early Bird discount, which you can spend for the dinner after day 1. I look forward to discussing the SSOT/ASOT topics there.


Conclusion

The Single Source Of Truth (SSOT) and the Authoritative Source of Truth (ASOT) are terms that illustrate the traditional PLM paradigm is changing thanks to digitization and connected stakeholders. The change is in the air. Now, the experience has to come. So be part of the change and discuss with us.

 

In the last weeks, I had several discussions related to sustainability. What can companies do to become sustainable and prove it? But, unfortunately, there is so much greenwashing at this moment.

Look at this post: 10 Companies and Corporations Called Out For Greenwashing.

Therefore I thought about which practical steps a company should take to prepare for a sustainable future, as the change will not happen overnight. It reminds me of the path towards a digital, model-based enterprise (my other passion). In my post Why Model-Based definition is important for all, I mentioned that MBD (Model-Based Definition) could be considered the first stepping-stone toward a Model-Based enterprise.

The analogy for Material Compliance came after an Aras seminar I watched a month ago. The webinar How PLM Paves the Way for Sustainability with  Insensia (an Aras implementer) demonstrates how material compliance is the first step toward sustainable product development.

Let’s understand why

The first steps

Companies that currently deliver solutions mostly only focus on economic gains. The projects or products they sell need to be profitable and competitive, which makes sense if you want a future.

And this would not have changed if the awareness of climate impact has not become apparent.

First, CFKs and hazardous materials lead to new regulations. Next global agreements to fight climate change – the Paris agreement and more to come – have led and will lead to regulations that will change how products will be developed. All companies will have to change their product development and delivery models when it becomes a global mandate.

A required change is likely going to happen. In Europe, the Green Deal is making stable progress. However, what will happen in the US will be a mystery as even their supreme court becomes a political entity against sustainability (money first).

Still, compliance with regulations will be required if a company wants to operate in a global market.

What is Material Compliance?

In 2002, the European Union published a directive to restrict hazardous substances in materials. The directive, known as RoHS (Restriction of Hazardous Substances), was mainly related to electronic components. In the first directive, six hazardous materials were restricted.

The most infamous are Cadmium(Cd), Lead(Pb), and Mercury (Hg). In 2006 all products on the EU market must pass RoHS compliance, and in 2011 was now connected the CE marking of products sold in the European market was.

In 2015 four additional chemical substances were added, most softening PVC but also affecting the immune system. Meanwhile, other countries have introduced similar RoHS regulations; therefore, we can see it as a global restricting. Read more here: The RoHS guide.

Consumers buying RoHS-compliant products now can be assured that none of the threshold values of the substances is reached in the product. The challenge for the manufacturer is to go through each of the components of the MBOM. To understand if it contains one of the ten restricted substances and, if yes, in which quantity.

Therefore, they need to get that information from each relevant supplier a RoHS declaration.

Besides RoHS, additional regulations protect the environment and the consumer. For example, REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) compliance deals with the regulations created to improve the environment and protect human health. In addition, REACH addresses the risks associated with chemicals and promotes alternative methods for the hazard assessment of substances.

The compliance process in four steps

Material compliance is most of all the job of engineers. Therefore around 2005, some of my customers started to add RoHS support to their PLM environment.

 

Step 1

The image below shows the simple implementation – the PDF-from from the supplier was linked to the (M)BOM part.

An employee had to manually add the substances into a table and ensure the threshold values were not reached. But, of course, there was already a selection of preferred manufacturer parts during the engineering phase. Therefore RoHS compliance was almost guaranteed when releasing the EBOM.

But this process could be done more cleverly.

 

Step 2

So the next step was that manufacturers started to extend their PLM data model with the additional attributes for RoHS compliance. Again, this could be done cleverly or extremely generic, adding the attributes to all parts.

So now, when receiving the material declaration, a person just has to add the substance values to the part attributes. Then, through either standard functionality or customization, a compliance report could be generated for the (M)BOM. So this already saves some work.

 

Step 3

The next step was to provide direct access to these attributes to the supplier and push the supplier to do the work.

Now the overhead for the manufacturer has been reduced again. This is because only the supplier needs to do the job for his customer.

 

Step 4

In step 4, we see a real connected environment, where information is stored only once, referenced by manufacturers, and kept actual by the part suppliers.

Who will host the RoHS databank? From some of my customer projects, I recall IHS as a data provider – it seems they are into this business when you look at their website HERE.

 

Where is your company at this moment?

Having seen the four stepping-stones leading towards efficient RoHS compliance, you see the challenge of moving from a document-driven approach to a data-driven approach.

Now let’s look into the future. Concepts like Life Cycle Assessment (LCA) or a Digital Product Passport (DPP) will require a fully connected approach.

Where is your company at this moment – have you reached RoHS compliance step 3 or 4? A first step to learn and work connected and data-driven.

 

Life Cycle Assessment – the ultimate target

A lifecycle assessment, or lifecycle analysis (two times LCA again), is a methodology to assess the environmental impact of a product (or solution) through its whole lifecycle. From materials sourcing, manufacturing, transportation, usage, service, and decommissioning. And by assessing, we mean a clear, verifiable, and shareable manner, not just guessing.

Traditional engineering education is not bringing these skills, although LCA is not new, as this 10-years old YouTube movie from Autodesk illustrates:

What is new is that due to global understanding, we are reaching the limits of what our planet can endure; we must act now. Upcoming international regulations will enforce life cycle analysis reporting for manufacturers or service providers. This will happen gradually.

Meanwhile, we all should work on a circular economy, the major framework for a sustainable planet- click on the image on the left.

In my post, I wrote about these combined topics: SYSTEMS THINKING – a must-have skill in the 21st century.

 

Life Cycle Analysis – Digital Twin – Digitization

The big elephant in the room is that when we talk about introducing LCA in your company, it has a lot to do with the digitization of your company. Assessment data in a document can require too much human effort to maintain the data at the right quality. The costs are not affordable if your competitor is more efficient.

When coming to the Analysis part, here, a model-based, data-driven infrastructure is the most efficient way to run virtual analysis, using digital twin concepts at each stage of the product lifecycle.

Virtual models for design, manufacturing and operations allow your company to make trade-off studies with low cost before committing to the physical world. 80 % of the environmental impact of a product comes from decisions in the virtual world.

Once you have your digital twins for each phase of the product lifecycle, you can benchmark your models with data reported from the physical world. All these interactions can be found in the beautiful Boeing diamond below, which I discussed before – Read A digital twin for everybody.

 

Conclusion

Efficient and sustainable life cycle assessment and analysis will come from connected information sources. The old document-driven paradigm is too costly and too slow to maintain. In particular, when the scope is not only a subset of your product, it is your full product and its full lifecycle with LCA. Another stepping stone towards the near future. Where are you?

 

Stepping-stone 1:            From Model-Based Definition to an efficient Model-Based, Data-driven Enterprise

Stepping-stone 2:            For RoHS compliance to an efficient and sustainable Model-Based, data-driven enterprise.

A month ago, I wrote: It is time for BLM – PLM is not dead, which created an anticipated discussion. It is practically impossible to change a framed acronym. Like CRM and ERP, the term PLM is there to stay.

However, it was also interesting to see that people acknowledge that PLM should have a business scope and deserves a place at the board level.

The importance of PLM at business level is well illustrated by the discussion related to this LinkedIn post from Matthias Ahrens referring to the CIMdata roadmap conference CEO discussion.

My favorite quote:

Now it’s ‘lifecycle management,’ not just EDM or PDM or whatever they call it. Lifecycle management is no longer just about coming up with new stuff. We’re seeing more excitement and passion in our customers, and I think this is why.”

But it is not that simple

This is a perfect message for PLM vendors to justify their broad portfolio. However, as they do not focus so much on new methodologies and organizational change, their messages remain at the marketing level.

In the field, there is more and more awareness that PLM has a dual role. Just when I planned to write a post on this topic, Adam Keating, CEO en founder of CoLab, wrote the post System of Record meet System of Engagement.

Read the post and the comments on LinkedIn. Adam points to PLM as a System of Engagement, meaning an environment where the actual work is done all the time. The challenge I see for CoLab, like other modern platforms, e.g., OpenBOM, is how it can become an established solution within an organization. Their challenge is they are positioned in the engineering scope.

I believe for these solutions to become established in a broader customer base, we must realize that there is a need for a System of Record AND System(s) of Engagement.

In my discussions related to digital transformation in the PLM domain, I addressed them as separate, incompatible environments.

See the image below:

Now let’s have a closer look at both of them

What is a System of Record?

For me, PLM has always been the System of Record for product information. In the coordinated manner, engineers were working in their own systems. At a certain moment in the process, they needed to publish shareable information, a document(e.g., PDF) or BOM-table (e.g., Excel). The PLM system would support New Product Introduction processes, Release and Change Processes and the PLM system would be the single point of reference for product data.

The reason I use the bin-image is that companies, most of the time, do not have an advanced information-sharing policy. If the information is in the bin, the experts will find it. Others might recreate the same information elsewhere,  due to a lack of awareness.

Most of the time, engineers did not like PLM systems caused by integrations with their tools. Suddenly they were losing a lot of freedom due to check-in / check-out / naming conventions/attributes and more. Current PLM systems are good for a relatively stable product, but what happens when the product has a lot of parallel iterations (hardware & software, for example). How to deal with Work In Progress?

Last week I visited the startup company PAL-V in the context of the Dutch PDM Platform. As you can see from the image, PAL-V is working on the world’s first Flying Car Production Model. Their challenge is to be certified for flying (here, the focus is on the design) and to be certified for driving (here, the focus is on manufacturing reliability/quality).

During the PDM platform session, they showed their current Windchill implementation, which focused on managing and providing evidence for certification. For this type of company, the System of Record is crucial.

Their (mainly) SolidWorks users are trained to work in a controlled environment. The Aerospace and Automotive industries have started this way, which we can see reflected in current PLM systems.

Image: Aras impression of the digital thread

And to finish with a PLM buzzword: modern systems of record provide a digital thread.

 

What is a System of Engagement?

The characteristic of a system of engagement is that it supports the user in real-time. This could be an environment for work in progress. Still, more importantly, all future concepts from MBSE, Industry 4.0 and Digital Twins rely on connected and real-time data.

As I previously mentioned, Digital Twins do not run on documents; they run on reliable data.

A system of engagement is an environment where different disciplines work together, using models and datasets. I described such an environment in my series The road to model-based and connected PLM. The System of Engagement environment must be user-friendly enough for these experts to work.

Due to the different targets of a system engagement, I believe we have to talk about Systems of Engagement as there will be several engagement models on a connected (federated) set of data.

Yousef Hooshmand shared the Daimler paper: “From a Monolithic PLM Landscape to a Federated Domain and Data Mesh” in that context. Highly recommended to read if you are interested in a potential PLM future infrastructure.

Let’s look at two typical Systems of Engagement without going into depth.

The MBSE System of Engagement

In this environment, systems engineering is performed in a connected manner, building connected artifacts that should be available in real-time, allowing engineers to perform analysis and simulations to construct the optimal virtual solution before committing to physical solutions.

It is an iterative environment. Click on the image for an impression.

The MBSE space will also be the place where sustainability needs to start. Environmental impact, the planet as a stakeholder,  should be added to the engineering process. Life Cycle Assessment (LCA) defining the process and material choices will be fed by external data sources, for example, managed by ecoinvent, Higg and others to come. It is a new emergent market.

The Digital Twin

In any phase of the product lifecycle, we can consider a digital twin, a virtual data-driven environment to analyze, define and optimize a product or a process. For example, we can have a digital twin for manufacturing, fulfilling the Industry 4.0 dreams.

We can have a digital twin for operation, analyzing, monitoring and optimizing a physical product in the field. These digital twins will only work if they use connected and federated data from multiple sources. Otherwise, the operating costs for such a digital twin will be too high (due to the inefficiency of accurate data)

In the end, you would like to have these digital twins running in a connected manner. To visualize the high-level concept, I like Boeing’s diamond presented by Don Farr at the PDT conference in 2018 – Image below:

Combined with the Daimler paper “From a Monolithic PLM Landscape to a Federated Domain and Data Mesh.” or the latest post from Oleg Shilovistky How PLM Can Build Ontologies? we can start to imagine a Systems of Engagement infrastructure.

 

You need both

And now the unwanted message for companies – you need both: a system of record and potential one or more systems of engagement. A System of Record will remain as long as we are not all connected in a blockchain manner. So we will keep producing reports, certificates and baselines to share information with others.

It looks like the Gartner bimodal approach.

An example: If you manage your product requirements in your PLM system as connected objects to your product portfolio, you will and still can generate a product specification document to share with a supplier, a development partner or a certification company.

So do not throw away your current System of Record. Instead, imagine which types of Systems of Engagement your company needs. Most Systems of Engagement might look like a siloed solution; however, remember they are designed for the real-time collaboration of a certain community – designers, engineers, operators, etc.

The real challenge will be connecting them efficiently with your System of Record backbone, which is preferable to using standard interface protocols and standards.

 

The Hybrid Approach

For those of you following my digital transformation story related to PLM, this is the point where the McKinsey report from 2017 becomes actual again.

 

Conclusion

The concepts are evolving and maturing for a digital enterprise using a System of Record and one or more Systems of Engagement. Early adopters are now needed to demonstrate these concepts to agree on standards and solution-specific needs. It is time to experiment (fast). Where are you in this process of learning?

 

 

 

 

 

 

 

 

 

While preparing my presentation for the Dutch Model-Based Definition solutions event, I had some reflections and experiences discussing Model-Based Definition. Particularly in traditional industries. In the Aerospace & Defense, and Automotive industry, Model-Based Definition has become the standard. However, other industries have big challenges in adopting this approach. In this post, I want to share my observations and bring clarifications about the importance.

 

What is a Model-Based Definition?

The Wiki-definition for Model-Based Definition is not bad:

Model-based definition (MBD), sometimes called digital product definition (DPD), is the practice of using 3D models (such as solid models, 3D PMI and associated metadata) within 3D CAD software to define (provide specifications for) individual components and product assemblies. The types of information included are geometric dimensioning and tolerancing (GD&T), component level materials, assembly level bills of materials, engineering configurations, design intent, etc.

By contrast, other methodologies have historically required the accompanying use of 2D engineering drawings to provide such details.

When I started to write about Model-Based definition in 2016, the concept of a connected enterprise was not discussed. MBD mainly enhanced data sharing between engineering, manufacturing, and suppliers at that time. The 3D PMI is a data package for information exchange between these stakeholders.

The main difference is that the 3D Model is the main information carrier, connected to 2D manufacturing views and other relevant data, all connected in this package.

 

MBD – the benefits

There is no need to write a blog post related to the benefits of MBD. With some research, you find enough reasons. The most important benefits of MBD are:

  • the information is and human-readable and machine-readable. Allowing the implementation of Smart Manufacturing / Industry 4.0 concepts
  • the information relies on processes and data and is no longer dependent on human interpretation. This leads to better quality and error-fixing late in the process.
  • MBD information is a building block for the digital enterprise. If you cannot master this concept, forget the benefits of MBSE and Virtual Twins. These concepts don’t run on documents.

To help you discover the benefits of MBD described by others – have a look here:

 

MBD as a stepping stone to the future

When you are able to implement model-based definition practices in your organization and connect with your eco-system, you are learning what it means to work in a connected matter. Where the scope is limited, you already discover that working in a connected manner is not the same as mandating everyone to work with the same systems or tools. Instead, it is about new ways of working (skills & people), combined with exchange standards (which to follow).

Where MBD is part of the bigger model-based enterprise, the same principles apply for connecting upstream information (Model-Based Systems Engineering) and downstream information(IoT-based operation and service models).

Oleg Shilovitsky addresses the same need from a data point of view in his recent blog: PLM Strategy For Post COVID Time. He makes an important point about the Digital Thread:

Digital Thread is one of my favorite topics because it is leading directly to the topic of connected data and services in global manufacturing networks.

I agree with that statement as the digital thread is like MBD, another steppingstone to organize information in a connected manner, even beyond the scope of engineering-manufacturing interaction. However, Digital Thread is an intermediate step toward a full data-driven and model-based enterprise.

To master all these new ways is working, it is crucial for the management of manufacturing companies, both OEM and their suppliers, to initiate learning programs. Not as a Proof of Concept but as a real-life, growing activity.

Why MBD is not yet a common practice?

If you look at the success of MBD in Aerospace & Defense and Automotive, one of the main reasons was the push from the OEMs to align their suppliers. They even dictated CAD systems and versions to enable smooth and efficient collaboration.

In other industries, there we not so many giant OEMs that could dictate their supply chain. Often also, the OEM was not even ready for MBD. Therefore, the excuse was often we cannot push our suppliers to work different, let’s remain working as best as possible (the old way and some automation)

Besides the technical changes, MBD also had a business impact. Where the traditional 2D-Drawing was the contractual and leading information carrier, now the annotated 3D Model has to become the contractual agreement. This is much more complex than browsing through (paper) documents; now, you need an application to open up the content and select the right view(s) or datasets.

In the interaction between engineering and manufacturing, you could hear statements like:

you can use the 3D Model for your NC programming, but be aware the 2D drawing is leading. We cannot guarantee consistency between them.

In particular, this is a business change affecting the relationship between an OEM and its suppliers. And we know business changes do not happen overnight.

Smaller suppliers might even refuse to work on a Model-Based definition, as it is considered an extra overhead they do not benefit from.

In particular, when working with various OEMs that might have their own preferred MBD package content based on their preferred usage. There are standards; however, OEMs often push for their preferred proprietary format.

It is about an orchestrated change.

Implementing MBD in your company, like PLM, is challenging because people need to be aligned and trained on new ways of working. In particular, this creates resistance at the end-user level.

Similar to the introduction of mainstream CAD (AutoCAD in the eighties) and mainstream 3D CAD (Solidworks in the late nineties), it requires new processes, trained people, and matching tools.

This is not always on the agenda of C-level people who try to avoid technical details (because they don’t understand them – read this great article: Technical Leadership: A Chronic Weakness in Engineering Enterprises.

I am aware of learning materials coming from the US, not so much about European or Asian thought leaders. Feel free to add other relevant resources for the readers in this post’s comments. Have a look and talk with:

Action Engineering with their OSCAR initiative: Bringing MBD Within Reach. I spoke with Jennifer Herron, founder of Action Engineering, a year ago about MBD and OSCAR in my blog post: PLM and Model-Based Definition.

Another interesting company to follow is Capvidia. Read their blog post to start with is MBD model-based definition in the 21st century.

The future

What you will discover from these two companies is that they focus on the connected flow of information between companies while anticipating that each stakeholder might have their preferred (traditional) PLM environment. It is about data federation.

The future of a connected enterprise is even more complex. So I was excited to see and download Yousef Hooshmand’s paper:  ”From a Monolithic PLM Landscape to a Federated Domain and Data Mesh”.

Yousef and some of his colleagues report about their PLM modernization project @Mercedes-Benz AG, aiming at transforming a monolithic PLM landscape into a federated Domain and Data Mesh.

This paper provides a lot of structured thinking related to the concepts I try to explain to my audience in everyday language. See my The road to model-based and connected PLM thoughts.

This paper has much more depth and is a must-read and must-discuss writing for those interested – perhaps an opportunity for new startups and a threat to traditional PLM vendors.

Conclusion

Vellum drawings are almost gone now – we have electronic 2D Drawings. The model-based definition has confirmed the benefits of improving the interaction between engineering, manufacturing & suppliers. Still, many industries are struggling with this approach due to process & people changes needed. If you are not able or willing to implement a model-based definition approach, be worried about the future. The eco-systems will only run efficiently (and survive) when their information exchange is based on data and models. Start learning now.

p.s. just out of curiosity:
If you are model-based advocate support this post with a

 

Once and a while, the discussion pops up if, given the changes in technology and business scope, we still should talk about PLM. John Stark and others have been making a point that PLM should become a profession.

In a way, I like the vagueness of the definition and the fact that the PLM profession is not written in stone. There is an ongoing change, and who wants to be certified for the past or framed to the past?

However, most people, particularly at the C-level, consider PLM as something complex, costly, and related to engineering. Partly this had to do with the early introduction of PLM, which was a little more advanced than PDM.

The focus and capabilities made engineering teams happy by giving them more access to their data. But unfortunately, that did not work, as engineers are not looking for more control.

Old (current) PLM

Therefore, I would like to suggest that when we talk about PLM, we frame it as Product Lifecycle Data Management (the definition). A PLM infrastructure or system should be considered the System of Record, ensuring product data is archived to be used for manufacturing, service, and proving compliance with regulations.

In a modern way, the digital thread results from building such an infrastructure with related artifacts. The digital thread is somehow a slow-moving environment, connecting the various as-xxx structures (As-Designed, As-Planned, As-Manufactured, etc.). Looking at the different PLM vendor images, Aras example above, I consider the digital thread a fancy name for traceability.

I discussed the topic of Digital Thread in 2018:  Document Management or Digital Thread. One of the observations was that few people talk about the quality of the relations when providing traceability between artifacts.

The quality of traceability is relevant for traditional Configuration Management (CM). Traditional CM has been framed, like PLM, to be engineering-centric.

Both PLM and CM need to become enterprise activities – perhaps unified.

Read my blog post and see the discussion with Martijn Dullaart, Lisa Fenwick and Maxim Gravel when discussing the future of Configuration Management.

New digital PLM

In my posts, I talked about modern PLM. I described it as data-driven, often in relation to a model-based approach. And as a result of the data-driven approach, a digital PLM environment could be connected to processes outside the engineering domain. I wrote a series of posts related to the potential of such a new PLM infrastructure (The road to model-based and connected PLM)

Digital PLM, if implemented correctly, could serve people along the full product lifecycle, from marketing/portfolio management until service and, if relevant, decommissioning). The bigger challenge is even connecting eco-systems to the same infrastructure, in particular suppliers & partners but also customers. This is the new platform paradigm.

Some years ago, people stated IoT is the new PLM  (IoT is the new PLM – PTC 2017). Or MBSE is the foundation for a new PLM (Will MBSE be the new PLM instead of IoT? A discussion @ PLM Roadmap conference 2018).

Even Digital Transformation was mentioned at that time. I don’t believe Digital Transformation is pointing to a domain, more to an ongoing process that most companies have t go through. And because it is so commonly used, it becomes too vague for the specifics of our domain. I liked Monica Schnitger‘s LinkedIn post: Digital Transformation? Let’s talk. There is enough to talk about; we have to learn and be more specific.

 

What is the difference?

The challenge is that we need more in-depth thinking about what a “digital transformed” company would look like. What would impact their business, their IT infrastructure, and their organization and people? As I discussed with Oleg Shilovitsky, a data-driven approach does not necessarily mean simplification.

I just finished recording a podcast with Nina Dar while writing this post. She is even more than me, active in the domain of PLM and strategic leadership toward a digital and sustainable future. You can find the pre-announcement of our podcast here (it was great fun to talk), and I will share the result later here too.

What is clear to me is that a new future data-driven environment becomes like a System of Engagement. You can simulate assumptions and verify and qualify trade-offs in real-time in this environment. And not only product behavior, but you can also simulate and analyze behaviors all along the lifecycle, supporting business decisions.

This is where I position the digital twin. Modern PLM infrastructures are in real-time connected to the business. Still, PLM will have its system of record needs; however, the real value will come from the real-time collaboration.

The traditional PLM consultant should transform into a business consultant, understanding technology. Historically this was the opposite, creating friction in companies.

Starting from the business needs

In my interactions with customers, the focus is no longer on traditional PLM; we discuss business scenarios where the company will benefit from a data-driven approach. You will not obtain significant benefits if you just implement your serial processes again in a digital PLM infrastructure.

Efficiency gains are often single digit, where new ways of working can result in double-digit benefits or new opportunities.

Besides traditional pressure on companies to remain competitive, there is now a new additional driver that I have been discussing in my previous post, the Innovation Dilemma. To survive on our planet, we and therefore also companies, need to switch to sustainable products and business models.

This is a push for innovation; however, it requires a coordinated, end-to-end change within companies.

Be the change

When do you decide to change your business model from pushing products to the marker into a business model of Product as a Service? When do you choose to create repairable and upgradeable products? It is a business need. Sustainability does not start with the engineer. It must be part of the (new) DNA of a company.

Interesting to read is this article from Jan Bosch that I read this morning: Resistance to Change. Read the article as it makes so much sense, but we need more than sense – we need people to get involved. My favorite quote from the article:

“The reasonable man adapts himself to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable man”.

Conclusion

PLM consultants should retrain themselves in System Thinking and start from the business. PLM technology alone is no longer enough to support companies in their (digital/sustainable) transformation. Therefore, I would like to introduce BLM (Business Lifecycle Management) as the new TLA.

However, BLM has been already framed as Black Lives Matter. I agree with that, extending it to ALM (All Lives Matter).

What do you think should we leave the comfortable term PLM behind us for a new frame?

Yes, it is not a typo. Clayton Christensen famous book written in 1995 discussed the Innovator’s Dilemma when new technologies cause great firms to fail. This was the challenge two decades ago. Existing prominent companies could become obsolete quickly as they were bypassed by new technologies.

The examples are well known. To mention a few: DEC (Digital Equipment Corporation), Kodak, and Nokia.

Why the innovation dilemma?

This decade the challenge has become different. All companies are forced to become more sustainable in the next ten years. Either pushed by global regulations or because of their customer demands. The challenge is this time different. Besides the priority of reducing greenhouse gas emissions, there is also the need to transform our society from a linear, continuous growth economy into a circular doughnut economy.

The circular economy makes the creation, the usage and the reuse of our products more complex as the challenge is to reduce the need for raw materials and avoid landfills.

The circular economy concept – the regular product lifecycle in the middle

The doughnut economy makes the values of an economy more complex as it is not only about money and growth, human and environmental factors should also be considered.

Doughnut Economics: Trying to stay within the green boundaries

To manage this complexity, I wrote SYSTEMS THINKING – a must-have skill in the 21st century, focusing on the logical part of the brain. In my follow-up post, Systems Thinking: a second thought, I looked at the human challenge. Our brain is not rational and wants to think fast to solve direct threats. Therefore, we have to overcome our old brains to make progress.

An interesting and thought-provoking was shared by Nina Dar in this discussion, sharing the video below. The 17 Sustainability Development Goals (SDGs) describe what needs to be done. However, we also need the Inner Development Goals (IDGs) and the human side to connect. Watch the movie:

Our society needs to change and innovate; however, we cannot. The Innovation Dilemma.

The future is data-driven and digital.

What is clear to me is that companies developing products and services have only one way to move forward: becoming data-driven and digital.

Why data-driven and digital?

Let’s look at something companies might already practice, REACH (Registration, Evaluation, Authorization and Restriction of Chemicals). This European directive, introduced in 2007, had the aim to protect human health and protect the environment by communicating information on chemicals up and down the supply chain. This would ensure that manufacturers, importers, and their customers are aware of information relating to the health and safety of the products supplied.

The regulation is currently still suffering in execution as most of the reporting and evaluation of chemicals is done manually. Suppliers report their chemicals in documents, and companies report the total of chemicals in their summary reports. Then, finally, authorities have to go through these reports.

Where the scale of REACH is limited, the manual effort to have end-to-end reporting is relatively high. In addition, skilled workers are needed to do the job because reporting is done in a document-based manner.

Life Cycle Assessments (LCA)

Where you might think REACH is relatively simple, the real new challenges for companies are the need to perform Life Cycle Assessments for their products. In a Life Cycle Assessment. The Wiki definition of LCA says:

Life cycle assessment or LCA (also known as life cycle analysis) is a methodology for assessing environmental impacts associated with all the stages of the life cycle of a commercial product, process, or service. For instance, in the case of a manufactured product, environmental impacts are assessed from raw material extraction and processing (cradle), through the product’s manufacture, distribution and use, to the recycling or final disposal of the materials composing it (grave)

This will be a shift in the way companies need to define products. Much more thinking and analysis are required in the early design phases. Before committing to a physical solution, engineers and manufacturing engineers need to simulate and calculate the impact of their design decisions in the virtual world.

This is where the digital twin of the design and the digital twin of the manufacturing process becomes relevant. And remember: Digital Twins do not run on documents – you need connected data and various types of models to calculate and estimate the environmental impact.

LCA done in a document-based manner will make your company too slow and expensive.

I described this needed transformation in my series from last year: The road to model-based and connected PLM – nine posts exploring the technology and concept of a model-based, data-driven PLM infrastructure.

Digital Product Passport (DPP)

The European Commission has published an action plan for the circular economy, one of the most important building blocks of the European Green Deal. One of the defined measures is the gradual introduction of a Digital Product Passport (DPP). As the quality of an LCA depends on the quality and trustworthy information about products and materials, the DPP is targeting to ensure circular economy metrics become reliable.

This will be a long journey. If you want to catch a glimpse of the complexity, read this Medium article: The digital product passport and its technical implementation related to the DPP for batteries.

The innovation dilemma

Suppose you agree with my conclusion that companies need to change their current product or service development into a data-driven and model-based manner. In that case, the question will come up: where to start?

Becoming data-driven and model-based, of course, is not the business driver. However, this change is needed to be able to perform Life Cycle Assessments and comply with current and future regulations by remaining competitive.

A document-driven approach is a dead-end.

Now let’s look at the real dilemmas by comparing a startup (clean sheet / no legacy) and an existing enterprise (experience with the past/legacy). Is there a winning approach?

The Startup

Having lived in Israel – the nation where almost everyone is a startup – and working with startups afterward in the past 10 years, I always get inspired by these people’s energy in startup companies. They have a unique value proposition most of the time, and they want to be visible on the market as soon as possible.

This approach is the opposite of systems thinking. It is often a very linear process to deliver this value proposition without exploring the side effects of such an approach.

For example, the new “green” transportation hype. Many cities now have been flooded with “green” scooters and electric bikes to promote transportation as a service. The idea behind this concept is that citizens do not require to own polluting motorbikes or cars anymore, and transportation means will be shared. Therefore, the city will be cleaner and greener.

However, these “green” vehicles are often designed in the traditional linear way. Is there a repair plan or a plan to recycle the batteries? Reuse of materials used.? Most of the time, not. Please, if you have examples contradicting my observations, let me know. I like to hear good news.

When startup companies start to scale, they need experts to help them grow the company. Often these experts are seasoned people, perhaps close to retirement. They will share their experience and what they know best from the past:  traditional linear thinking.

As a result, even though startup companies can start with a clean sheet, their focus on delivering the product or service blocks further thinking. Instead, the seasoned experts will drive the company towards ways of working they know from the past.

Out of curiosity: Do you know or work in a startup that has started with a data-driven and model-based vision from scratch?  Please add the name of this company in the comments, and let’s learn how they did it.

The Existing company

Working in an established company is like being on board a big tanker. Changing its direction takes a clear eye on the target and navigation skills to come there. Unfortunately, most of the time, these changes take years as it is impossible to switch the PLM infrastructure and the people skills within a short time.

From the bimodal approach in 2015 to the hybrid approach for companies, inspired by this 2017 McKinsey article: Toward an integrated technology operating model, I discovered that this is probably the best approach to ensure a change will happen. In this approach – see image – the organization keeps running on its document-driven PLM infrastructure. This type of infrastructure becomes the system of record. Nothing different from what PLM currently is in most companies.

In parallel, you have to start with small groups of people who independently focus on a new product, a new service. Using the model-based approach, they work completely independently from the big enterprise in a data-driven approach. Their environment can be considered the future system of engagement.

The data-driven approach allows all disciplines to work in a connected, real-time manner. Mastering the new ways of working is usually the task of younger employees that are digital natives. These teams can be completed by experienced workers who behave as coaches. However, they will not work in the new environment; these coaches bring business knowledge to the team.

People cannot work in two modes, but organizations can. As you can see from the McKinsey chart, the digital teams will get bigger and more important for the core business over time. In parallel, when their data usage grows, more and more data integration will occur between the two operation modes. Therefore, the old PLM infrastructure can remain a System of Record and serve as a support backbone for the new systems of engagement.

The Innovation Dilemma conclusion

The upcoming ten years will push organizations to innovate their ways of working to become sustainable and competitive. As discussed before, they must learn to work in a data-driven, connected manner. Both startups and existing enterprises have challenges – they need to overcome the “thinking fast and acting slow” mindset. Do you see the change in your company?

 

Note: Before publishing this post, I read this interesting and complementary post from Jan Bosch Boost your digitalization: instrumentation.

It is in the air – grab it.

 

Two weeks ago, I wrote a generic post related to System Thinking, in my opinion, a must-have skill for the 21st century (and beyond). Have a look at the post on LinkedIn; in particular interesting to see the discussion related to Systems Thinking: a must-have skill for the 21st century.

I liked Remy Fannader’s remark that thinking about complexity was not something new.

This remark is understandable from his personal context. Many people enjoy thinking – it was a respected 20th-century skill.

However, I believe, as Daniel Kahneman describes in his famous book: Thinking Fast and Slow, our brain is trying to avoid thinking.

This is because thinking consumes energy, the energy the body wants to save in the case of an emergency.

So let’s do a simple test (coming from Daniel):

xx

A bat and a ball cost together $ 1.10 –  the bat costs one dollar more than the ball. So how much does the ball cost?

Look at the answer at the bottom of this post. If you have it wrong, you are a fast thinker. And this brings me to my next point. Our brain does not want to think deeply; we want fast and simple solutions. This is a challenge in a complex society as now we hear real-time information coming from all around the world. What is true and what is fake is hard to judge.

However, according to Kahneman, we do not want to waste energy on thinking. We create or adhere to simple solutions allowing our brains to feel relaxed.

This human behavior has always been exploited by populists and dictators: avoid complexity because, in this way, you lose people. Yuval Harari builds upon this with his claim that to align many people, you need a myth. I wrote about the need for myths in the PLM space a few times, e.g., PLM as a myth? and The myth perception

And this is where my second thoughts related to Systems Thinking started. Is the majority of people able and willing to digest complex problems?

My doubts grew bigger when I had several discussions about fighting climate change and sustainability.

 

 

Both Brains required

By coincidence, I bumped on this interesting article Market-led Sustainability is a ‘Fix that Fails’…

I provided a link to the post indirectly through LinkedIn. If you are a LinkedIn PLM Global Green Alliance member, you can see below the article an interesting analysis related to market-led sustainability, system thinking and economics.

Join the PLM Global Green Alliance group to be part of the full discussion; otherwise, I recommend you visit Both Brains Required, where you can find the source article and other related content.

It is a great article with great images illustrating the need for systems thinking and sustainability. All information is there to help you realize that sustainability is not just a left-brain exercise.

The left brain is supposed to be logical and analytical. That’s systems thinking, you might say quickly. However, the other part of our brain is about our human behavior, and this side is mostly overlooked. My favorite quote from the article:

Voluntary Market-Led activities are not so much a solution to the sustainability crisis as a symptom of more profoundly unsustainable foundations of human behavior.

The article triggered my second thoughts related to systems thinking. Behavioral change is not part of systems thinking. It is another dimension harder to address and even harder to focus on sustainability.

The LinkedIn discussion below the article Market-led Sustainability is a ‘Fix that Fails’… is a great example of the talks we would like to have in our PLM Global Green Alliance group. Nina Dar, Patrick Hillberg and Richard McFall brought in several points worth discussing. Too many to discuss them all here – let’s take two fundamental issues:

1. More than economics

An interesting viewpoint in this discussion was the relation to economics. We don’t believe that economic growth is the main point to measure. Even a statement like:  “Sustainable businesses will be more profitable than traditional ones” is misleading when companies are measured by shareholder value or EBIT (Earnings Before Interest or Taxes). We briefly touched on Kate Raworth’s doughnut economics.

This HBR article mentioned in the discussion: Business Schools Must Do More to Address the Climate Crisis also shows it is not just about systems thinking.
We discussed the challenges of supply chains, not about resilience but about sustainability. Where an OEM can claim to be sustainable, there are often not aware of what happens at the level of their suppliers. As the OEM measure their suppliers mostly on Quality/Reliability and Cost, they usually do not care about local human issues or sustainability issues.

We have seen this in the Apparel industry with the horrible collapse of a factory in Bangladesh  (2013). Still, the inhumane accidents happen in southeast Asia. I like to quote Chris Calverley in his LinkedIn article: Making ethical apparel supply chains achievable on a global scale.

 

No one gets into business because they want to behave unethically. On the contrary, a lack of ethics is usually driven by a common desire to operate more efficiently and increase profit margins. 

In my last post, I shared a similar example from an automotive tier 2  supplier. Unfortunately, suppliers are not measured or rewarded for sustainability efforts; only efficiency and costs are relevant.

The seventeen Sustainability Development Goals (SDG), as defined by the United Nations, are the best guidance for sustainable drivers beyond money. Supporting the SDGs enforce systems thinking when developing a part, a product, or a solution. Many other stakeholders need to be taken care of, at least if you truly support sustainability as a company.

2. The downside of social media

The LinkedIn discussion related to Market-led Sustainability is a ‘Fix that Fails’… The thread shows that LinkedIn, like other social media, is not really interested in supporting in-depth discussions – try to navigate what has been said in chronological order. With Patrick, Nina and Richard, we agreed to organize a follow-up discussion in our PLM Global Green Alliance Group.

And although we are happy with social media as it allows each of us to reach a global audience, there seems to be a worrying contra-productive impact. If you read the book Stolen Focus. A quote:

All over the world, our ability to pay attention is collapsing. In the US, college students now focus on one task for only 65 seconds, and office workers, on average, manage only three minutes

This is worrying, returning to Remy Fannader’s remark: thinking about complexity was not something new. The main difference is that it is not new. However, our society is changing towards thinking too fast, not rewarding systems thinking.

Even scarier, if you have time, read this article from The Atlantic: about the impact of social media on the US Society. It is about trust in science and data. Are we facing the new (Trump) Tower of Babel in our modern society? As the writers state: Babel is a metaphor for what some forms of social media have done to nearly all of the groups and institutions most important to the country’s future—and to us as a people.

 

I have talked in previous posts about the Dunner-Kruger effect, something that is blocking systems thinking. The image to the left says it all. Due to social media and the safe place behind a keyboard, many of us consider ourselves confident experts explaining to the real expert why they are wrong. For addressing the topics of sustainability and climate change, this attitude is killing. It is the opposite of systems thinking, which costs energy.

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The fact that you reached this part of the post means your attention span has been larger than 3 minutes, showing there is hope for people like you and me. As an experiment to discover how many people read the post till here, please answer with the “support” icon if you have reached this part of the post.

I am curious to learn how many of us who saw the post came here.

 

Conclusion

Systems Thinking is a must-have skill for the 21st century. Many of us working in the PLM domain focus on providing support for systems thinking, particularly Life Cycle Assessment capabilities. However, the discussion with Patrick Hillberg, Nina Darr and Richard McFall made me realize there is more: economics and human behavior. For example, can we change our economic models, measuring companies not only for the money profit they deliver? What do?

Answering this type of question will be the extended mission for PLM consultants of the future – are you ready?

 

The answer to the question with the ball and the bat:

A fast answer would say the price of the ball is 10 cents. However, this would make the price of the bat $1.10, giving a total cost of $1.20. So the right answer should be 5 cents. To be honest, I got tricked the first time too. Never too late to confirm you make mistakes, as only people who do not do anything make no mistakes.

In the past four weeks, I have been discussing PLM education from different angles through interviews with Peter Bilello (CIMdata), Helena Gutierrez (Share PLM), John Stark (John Stark Associates) and Dave Slawson (Quick Release). Each of these persons brought their specialized focus on PLM.

In this post, I want to conclude and put their expertise in the context of PLM – people, processes and tools.

CIMdata

Originally CIMdata became known for their CAD/CAM market analysis, later expanding into simulation and PLM vendors analysis. And they are still a reference for everyone following the PLM Market. They provide market numbers and projections related to PLM for that part. Together with ARC, they are for me the two sources to understand what is happening business-wise in the PLM market.

Thanks to the contacts with all the vendors, they have a good overview of what is happening. That makes their strategic advice and training useful for companies that want to benchmark where they are and understand the current trends, all vendor-independent.

Their PLM Roadmap conferences have been one of the few consistent vendor-independent conferences that still take place.

If you search for the term “The weekend after PLM Roadmap …..” you will find many of my reviews of these conferences.

Besides these activities, they are also facilitating industry action groups where similar companies in an industry discuss and evaluate various methodologies and how they could be implemented using various PLM systems – the most visible for me is the Aerospace & Defense PLM Action Group

Share PLM

Share PLM is still a young organization focusing on Humanizing PLM. Their focus is on the end-to-end PLM education process. Starting from an education strategy focusing on people, they can organize and help you build attractive and didactical training or elearnings related to your PLM processes and systems in use.

Besides their core offering, they are also justifying their name; they really share PLM information. So have a look at their Our Work tab with samples. In particular, as I mentioned in my interview with them, I like their podcasts.

 

In this post, I try to find similar people or companies to those I interviewed.

When looking at Share PLM, Action Engineering in the US comes to my mind. They are the specialists dedicated to helping organizations large and small achieve their Model-Based Definition (MBD) and Model-Based Enterprise (MBE) goals.

To refresh your memory, read my post with Jennifer Herron, the founder of Action Engineering here: PLM and Model-Based Definition

 

John Stark

Although John might be known as a leading writer of PLM books, he is also active in advising companies in their PLM journeys. Somehow similar to what I do, the big difference is that John takes the time to structure the information and write it down in a book. Just have a look at his list of published PLM books here.

My blog posts are less structured and reflect my observations depending on the companies and people I meet. Writing a foundational book about PLM would be challenging, as concepts are radically changing due to globalization and digitization.

John’s books are an excellent foundation for students who want to learn PLM’s various aspects during their academic years. Students can sit down and take the time to study PLM concepts. Later, suppose you want to acquire PLM knowledge relevant to your company.

In that case, you might focus on specialized training, like the ones CIMdata provides.

There are many books on PLM – have a look at this list. Which book to read depends probably a lot on your country and the university you are associated with. In my network, I have recently seen books from Martin Eigner and  Uthayan Elangovan.   Rosemary Astheimer’s book Model-Based Definition in the Product Lifecycle is still on my to-read list.

And then, there is a lot of research done by universities worldwide. So, if you are lucky, there is good education for PLM-related practices in your country.

Quick Release

My post with Quick Release illustrated the challenges of a PLM consultancy company. It showed their efforts to enable their consultants to be valuable for their customers and create a work environment that inspires them to grow and enjoy their work.

Quick Release aims for a competitive advantage to have their consultants participate in actual work for their customers.

Not only from the conceptual point of view but also to get their hands “dirty”.

There are many other PLM consultancy firms. Having worked with Atos, Accenture, Capgemini, Delloite, PWC, who have their PLM practices, you realize that these companies have their methodologies and preferences. The challenge of their engagements is often the translation of a vision into an affordable roadmap.

Example of Accenture Digital PLM message

Consultancy firms need to be profitable, too, and sometimes they are portrayed as a virus. Once they are in, it is hard to get rid of them.

I do not agree with that statement, as companies often keep relying on consultants because they do not invest in educating their own people. It is a lack of management prioritization or understanding of the importance. Sometimes the argument is: “We are too busy” – remember the famous cartoons.

Consultants cannot change your company; in the end, you have to own the strategy and execution.

And although large consultancy firms might have many trained resources, my experience with these companies is that success often depends on one or two senior consultants. Consultancy is also a human-centric job, being able to connect to the customer in their language and culture.

Good consultants show their value by creating awareness and clarity first. Next, by helping the customer execute their strategy without big risks or hiccups. Finally, a good consultant becomes redundant as the knowledge has been transferred and digested to the customer.

It is like growing up.

System Integrators

It is a small step from consultancy firms to system integrators, as many consultancy firms have specialists in their company that are familiar with certain vendors’ systems. And you might have discovered that the systems that require the most integration or configuration work have the largest practices globally.

So I did a “quick and dirty” search on LinkedIn, looking for people with the xxx PLM consultant role, where xxx is the name of the PLM Vendor.

This to understand how big is the job market for such a specialized PLM consultant.

The image shows the result and I let you draw your own conclusions.

System Integrators are usually the most important partners for a PLM implementation once you choose. Therefore, when I support a PLM selection process, I always look at the potential implementation partner. Their experience, culture and scale are as important as selecting the best tools.

System Integrators can benefit from their past experiences and best practices. It is a myth that every company is so unique and should be treated differently. Instead, companies are different because of historical reasons. And these differences to best practices are sometimes inhibitors instead of advantages.

Related to education, System Integrators are often focused on technical training. Still, they might also have separate experts in training or organizational change management.

 

PLM Vendors

For me, the PLM vendors are the ones that should inspire the customers. Have a look at the “famous” CIMdata slide illustrating the relation between vision, technology and implemented practices – there is a growing gap between the leaders and the followers.

PLM Vendors often use their unique technical capabilities as a differentiator to the competition and inspiration for C-level management. Just think about the terms: Industry 4.0, Digital Twin, Digital Thread, Digital Platform, Model-Based Enterprise and more about sustainability targeted offerings.

The challenge however is to implement these concepts in a consistent manner, allowing people in an organization to understand why and what needs to be done.

The PLM editor’s business model is based on software sales or rental. Therefore, they will focus on their benefits and what competitors fail to do. And as they have the largest marketing budgets, they are the most visible in the PLM-related media.

Of course reality is not that dramatic – education is crucial

You can compare PLM Vendors also with populists. The aim of a populist is to create an audience by claiming they can solve your problems (easily) by using simple framing sentences. However, the reality is that the world and the current digitalization in the PLM domain are not simple.

Therefore we need education, education and education from different sources to build our own knowledge. It is not about the tool first. It is people, process and then tools/technology

 

People, Process, Tools

Education and the right education for each aspect of PLM are crucial to making the right decision. To simplify the education message, I tried to visualize and rate each paragraph along with the People, Process and Tools assessment.

What do you think? Does this make sense related to education?

 

Conclusion

Education is crucial at every level of an organization and at every stage of your career. Take your time to read and digest the information you see and compare and discuss it with others. Be aware of the People, Process and Tools matrix when retrieving information. Where does it apply, and why.

I believe PLM is considered complex because we are dealing with people who all have different educational backgrounds and, therefore, an opinion. Invest in alignment to ensure the processes and tools will be used best.

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  1. Jos, one could take the approach that there is an engineering transformation strategy that can be realized by implementing PLM…

  2. Jos, I agree we should break out from the monolithic approach as this typically means lock-in, risk and frustration. The…

  3. Jos, Thanks for these insights. I believe that the mature capabilities provided by advanced toolsets can also be of benefit…

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