You are currently browsing the category archive for the ‘Data centric’ category.
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:
- What is MBD, and what are its benefits?
- MBD Efficiencies for Small Manufacturers
- 5 reasons to use MBD
- 10 reasons why everyone is moving away from traditional 2D drawings
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.
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
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?
In February, the PLM Global Green Alliance published our first interview discussing the relationship between PLM and Sustainability with the main vendors. We talked with Darren West from SAP.
You can find the interview here: PLM and Sustainability: talking with SAP. We spoke with Darren about SAP’s Responsible Design and Production module, allowing companies to understand their environmental and economic impact by calculating fees and taxes and implement measures to reduce regulatory costs. The high reliance on accurate data was one of the topics in our discussion.
In March, we interviewed Zoé Bezpalko and Jon den Hartog from Autodesk. Besides Autodesk’s impressive sustainability program, we discussed Autodesk’s BIM technology helping the construction industry to become greener and their Generative Design solution to support the designer in making better material usage or reuse decisions.
The discussion ended with discussing Life Cycle Assessment tools to support the engineer in making sustainable decisions.
In my last blog post, the Innovation Dilemma, I explored the challenges of a Life Cycle Assessment. As it appears, it is not about just installing a tool. The concepts of a data-driven PLM infrastructure and digital twins are strong transformation prerequisites combined with the Inner Development Goals (IDG).
The IDGs are a human attitude needed besides the Sustainability Development Goals.
Therefore we were happy to discuss last week with Florence Verzelen, Executive Vice President Industry, Marketing & Sustainability and Xavier Adam, Worldwide Sustainability Senior Manager from Dassault Systemes. We discussed Dassault Systemes’ business sustainability goals and product offerings based on the 3DEXPERIENCE platform.
Have a look at the discussion below:
The slides shown in the recording can be found HERE.
What I learned
Dassault Systemes’ purpose has been to help their customers imagine sustainable innovations capable of harmonizing product, nature, and life for many years. A statement that now is slowly bubbling up in other companies too. Dassault Systemes has set a clear and interesting target for themselves in 2025. In that year two/thirds of their sales should come from solutions that make their customers more sustainable.
Their Eco-design solution is one of the first offerings to reach this objective. Their Life Cycle Assessment solution can govern your (virtual) product design on multiple criteria, not only greenhouse gas emissions. It will be interesting to follow up on this topic to see how companies make the change internally by relying on data and virtual twins of a product or a manufacturing process.
Want to learn more?
- Our Sustainability Commitment
- Unleashing Sustainable Innovation (a page full of resources)
- Virtual Twin Experiences
- Life Cycle Assessment Solution on the 3DEXPERIENCE Platform to Transform the Sustainable Innovation Process
Conclusion
80 % of the environmental impact of products is decided during the design phase. A Lifecycle Assessment Solutions combined with a virtual product model, the virtual design twin, allows you to decide on trade-offs in the virtual space before committing to the physical solution. Creating a data-driven, closed-loop between design, engineering, manufacturing and operations based on accurate data is the envisioned infrastructure for a sustainable future.
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.
In the past four weeks, I have been writing about the various aspects related to PLM Education. First, starting from my bookshelf, zooming in on the strategic angle with CIMdata (Part 1).
Next, I was looking at the educational angle and motivational angle with Share PLM (Part 2).
And the last time, I explored with John Stark the more academic view of PLM education. How do you – students and others – learn and explore the full context of PLM (Part 3)?
Now I am talking with Dave Slawson from Quick Release_ , exploring their onboarding and educational program as a consultancy firm.
How do they ensure their consultants bring added value to PLM-related activities, and can we learn something from that four our own practices?
Quick Release
Dave, can you tell us something more about Quick Release, further abbreviated to QR, and your role in the organization?
.
Quick Release is a specialist PDM and PLM consultancy working primarily in the automotive sector in Europe, North America, and Australia. Robust data management and clear reporting of complex subjects are essential.
Our sole focus is connecting the data silos within our client’s organizations, reducing program or build delays through effective change management.
Quick Release promise – PDT 2019
I am QR’s head of Learning and Development, and I’ve been with the company since late 2014.
I’ve always had a passion for developing people and giving them a platform to push themselves to realize their potential. QR wants to build talent from within instead of just hiring experienced people.
However, with our rapid growth, it became necessary to have dedicated full-time resources to faster onboarding and upskilling our employees. This is combined with having an ongoing development strategy and execution.
QRs Learning & Development approach
Let’s focus on Learning & Development internally at QR first. What type of effort and time does it take to onboard a new employee, and what is their learning program?
.
We have a six-month onboarding program for new employees. Most starters join one of our “boot camps”, a three-week intensive program where a cohort of between 6 and 14 new starters receive classroom-style sessions led by our subject matter experts.
During this, new starters learn about technical PDM and PLM and high-performance business skills that will help them deliver excellence for or clients and feel confident in their work.
Quick Release BoB track process – click to enlarge
While the teams spend a lot of time with the program coordinator, we also bring in our various Subject Matter Experts (SMEs) to ensure the highest quality and variety in these sessions. Some of these sessions are delivered by our founders and directors.
As a business, we believe in investing senior leadership time to ensure quality training and give our team members access to the highest levels of the company.
Since the Covid-19 pandemic started, we moved our training program to be primarily distance learning. However, some sessions are in person, with new starters attending workshops in our regional offices. Our sessions focus on engagement and “doing” instead of just watching a presentation. New starters have fed back that they are still just as enjoyable via distance learning.
Following boot camp, team members will start work on their client projects, supported by a Project Manager and a mentor. During this period, their mentor will help them use the on-the-job experience to build up their technical knowledge on top of their bootcamp learning. The mentor is also there to help them cope with what we know is a steep learning curve. Towards the end of the six months program, each new starter will carry out a self-evaluation designed to help them recognize their achievements to date and identify areas of focus for ongoing personal development.
We gather feedback from the trainers and trainees throughout the onboarding programs, ensuring that the former is shared with their mentors to help with coaching.
The latter is used to help us continuously improve our offering. Our trainers are subject matter experts, but we encourage them to evolve their content and approach based on feedback.
The learning journey
Some might say you only learn on the job – how do you relate to this statement? Where does QR education take place? Can you make a statement on ROI for Learning & Development?
It is important to always be curious related to your work. We encourage our team members to challenge themselves to learn new things and dig deeper. Indeed, constant curiosity is one of our core values. We encourage people to challenge the status quo, challenge themselves, and adopt a growth mindset through all development and feedback cycles.
The learning curve in PDM and PLM can be steep; therefore, we must give people the tools and feedback that they can use to grow. At QR, this starts with our onboarding program and flows into an employee’s full career with us. In addition, at the end of every quarter, team members receive performance feedback from their managers, which feeds into their development target setting.
We have a wealth of internal resources to support development, from structured training materials to our internally compiled PDM Wiki and our suite of development “playbooks” (curated learning journeys catering to a range of learning styles).
On-the-job learning is critically important. So after the boot camp, we put our team members straight into projects to make sure they apply and build on their baseline knowledge through real-world experience. Still, they are supported with formal training and ongoing access to development resources.
Regarding Return on Investment, while it is impossible to give a specific number, we would say that quality training is invaluable to our clients and us. In seven years, the company has grown from 60 to 300 employees. In addition, it now operates in three other continents, illustrating that our clients trust the quality of how we train our consultants!
We also carried out internal studies regarding the long-term retention of team members relative to onboarding quality. These studies show that team members who experience a more controlled and structured onboarding program are mostly more successful in roles.
Investing in education?
I understood some of your customers also want to understand PLM processes better and ask for education from your side. Would the investment in education be similar? Would they be able to afford such an effort?
Making a long-term and tangible impact for our clients is the core foundation of what QR are trying to achieve. We do not want to come in to resolve a problem, only for it to resurface once we’ve left. Nor do we want to do work that our clients could easily hire someone to do themselves.
Therefore the idea of delivering a version of our training and onboarding program to clients is very attractive to us. We offer clients a shortened version of our bootcamp (focused on technical PDM, PLM and complexity management without the consultancy skills to our clients).
This is combined with an ongoing support program that transitions the responsibilities within the client team away from our consultants towards the client’s own staff.
We’d look to run that program over approximately 6 months so that the client can be confident that their staff has reached the level of technical expertise. There would be an upfront cost to the client to manage this.
However, the program is designed to support quality skills development within their organization.
PLM and Digital Transformation?
Education and digital transformation is a question I always ask. Although QR is already established in the digital era, your customers are not. What are the specific parts of digital transformation that you are teaching your employees and customers
The most inefficient thing we see in the PDM space is the reliance on offline, “analog” data and the inability to establish one source of truth across a complex organization. To support business efficiency through digital transformation, we promote a few simple core tenets in everything we do:
- Establish a data owner who not only holds the single reference point but also is responsible for its quality
- Right view reporting – clearly communicate exactly what people need to know, recognizing that different stakeholders need to know different things and that no one has time to waste
- Clear communications – using the right channels of communication to get the job done faster (including more informal channels such as instant messaging or collaborative online working documents)
- Smart, data-led decision making – reviewing processes using accurate data that is analyzed thoroughly, and justifying recommendations based on a range of evidence
- Getting your hands dirty! – Digital Transformation is not just a “systems” subject but relies on people and human interaction. So we encourage all of our consultants to actually understand how teams work. Not be afraid to roll up their sleeves and get stuck in instead of just analyzing from the outside!
Want to learn more?
Dave, Could you point us to relevant Learning & Development programs and resources that are valuable for the readers of this blog?
.
If you are interested in learning within the PDM and PLM space, follow Quick Release on LinkedIn as we publish thought leadership articles designed to support industry development.
For those interested in Learning & Development strategy, there is lots of UK and Ireland guidance available from the Chartered Institute of Personnel and Development (CIPD). Similar organizations exist in other countries, such as the Society for Human Resource Management (SHRM) in the USA) which are great resources for building Learning & Development specific skills.
In my research, I often find really thought-provoking articles that shape my approach and thinking regarding Learning & Development, HR and a business approach published by Forbes and Harvard Business Review.
What I learned
When I first discovered Quick Release as a company during one of the PLM Roadmap & PDT conferences (see “The weekend after PLM Roadmap & PDT 2019″) I was impressed by their young and energetic approach combined with being pragmatic and focused on making the data “flow”. Their customers were often traditional automotive companies having the challenge to break the silos. You could say QR was working on the “connected” enterprise as I would name it.
PLM consultancy must change
Besides their pragmatic approach, I discovered through interactions with QR that they are a kind of management consultancy firm you would expect in the future. As everything is going to be faster experience counts. Instead of remaining conceptual and strategic, they do not fear being with their feet in the mud.
This requires a new type of consultant and training, as employees need to be able to connect both to specialists at their customers and also be able to communicate with management. These types of people are hard to get as this is the ideal profile of a future employee.
The broad profile
What I learned from Dave is that QR invests seriously in meaningful education and coaching programs for their employees – to give them a purpose and an environment where they feel valued. I would imagine this applies actually to every company of the future, therefore I am curious if you could share your experiences from the field, either through the comments to this post or contact me personally.
Conclusion
We have seen now four dimensions of PLM education and I wish they gave you insights into what is possible. For each of the companies, I interviewed there might be others with the same skills. What is important is to realize the domain of PLM needs those four dimensions. In my next (short) post I will provide a summary of what I learned and what I believe is the PLM education of the future. Stay connected!
And a bonus you might have seen before – the digital plumber:
After two quiet weeks of spending time with my family in slow motion, it is time to start the year.
First of all, I wish you all a happy, healthy, and positive outcome for 2022, as we need energy and positivism together. Then, of course, a good start is always cleaning up your desk and only leaving the relevant things for work on the desk.
Still, I have some books at arm’s length, either physical or on my e-reader, that I want to share with you – first, the non-obvious ones:
The Innovators Dilemma
A must-read book was written by Clayton Christensen explaining how new technologies can overthrow established big companies within a very short period. The term Disruptive Innovation comes up here. Companies need to remain aware of what is happening outside and ready to adapt to your business. There are many examples even recently where big established brands are gone or diminished in a short period.
In his book, he wrote about DEC (Digital Equipment Company) market leader in minicomputers, not having seen the threat of the PC. Or later Blockbuster (from video rental to streaming), Kodak (from analog photography to digital imaging) or as a double example NOKIA (from paper to market leader in mobile phones killed by the smartphone).
The book always inspired me to be alert for new technologies, how simple they might look like, as simplicity is the answer at the end. I wrote about in 2012: The Innovator’s Dilemma and PLM, where I believed cloud, search-based applications and Facebook-like environments could disrupt the PLM world. None of this happened as a disruption; these technologies are now, most of the time, integrated by the major vendors whose businesses are not really disrupted. Newcomers still have a hard time to concur marketspace.
In 2015 I wrote again about this book, The Innovator’s dilemma and Generation change. – image above. At that time, understanding disruption will not happen in the PLM domain. Instead, I predict there will be a more evolutionary process, which I would later call: From Coordinated to Connected.
The future ways of working address the new skills needed for the future. You need to become a digital native, as COVID-19 pushed many organizations to do so. But digital native alone does not bring success. We need new ways of working which are more difficult to implement.
Sapiens
The book Sapiens by Yuval Harari made me realize the importance of storytelling in the domain of PLM and business transformation. In short, Yuval Harari explains why the human race became so dominant because we were able to align large groups around an abstract theme. The abstract theme can be related to religion, the power of a race or nation, the value of money, or even a brand’s image.
The myth (read: simplified and abstract story) hides complexity and inconsistencies. It allows everyone to get motivated to work towards one common goal. A Yuval says: “Fiction is far more powerful because reality is too complex”.
Too often, I have seen well-analyzed PLM projects that were “killed” by management because it was considered too complex. I wrote about this in 2019 PLM – measurable or a myth? claiming that the real benefits of PLM are hard to predict, and we should not look isolated only to PLM.
My 2020 follow-up post The PLM ROI Myth, eludes to that topic. However, even if you have a soundproof business case at the management level, still the myth might be decisive to justify the investment.
That’s why PLM vendors are always working on their myths: the most cost-effective solution, the most visionary solution, the solution most used by your peers and many other messages to influence your emotions, not your factual thinking. So just read the myths on their websites.
If you have no time to read the book, look at the above 2015 Ted to grasp the concept and use it with a PLM -twisted mind.
Re-use your CAD
In 2015, I read this book during a summer holiday (meanwhile, there is a second edition). Although it was not a PLM book, it was helping me to understand the transition effort from a classical document-driven enterprise towards a model-based enterprise.
Jennifer Herron‘s book helps companies to understand how to break down the (information) wall between engineering and manufacturing.
At that time, I contacted Jennifer to see if others like her and Action Engineering could explain Model-Based Definition comprehensively, for example, in Europe- with no success.
As the Model-Based Enterprise becomes more and more the apparent future for companies that want to be competitive or benefit from the various Digital Twin concepts. For that reason, I contacted Jennifer again last year in my post: PLM and Model-Based Definition.
As you can read, the world has improved, there is a new version of the book, and there is more and more information to share about the benefits of a model-based approach.
I am still referencing Action Engineering and their OSCAR learning environment for my customers. Unfortunately, many small and medium enterprises do not have the resources and skills to implement a model-based environment.
Instead, these companies stay on their customers’ lowest denominator: the 2D Drawing. For me, a model-based definition is one of the first steps to master if your company wants to provide digital continuity of design and engineering information towards manufacturing and operations. Digital twins do not run on documents; they require model-based environments.
The book is still on my desk, and all the time, I am working on finding the best PLM practices related to a Model-Based enterprise.
It is a learning journey to deal with a data-driven, model-based environment, not only for PLM but also for CM experts, as you might have seen from my recent dialogue with CM experts: The future of Configuration Management.
Products2019
This book was an interesting novelty published by John Stark in 2020. John is known for his academic and educational books related to PLM. However, during the early days of the COVID-pandemic, John decided to write a novel. The novel describes the learning journey of Jane from Somerset, who, as part of her MBA studies, is performing a research project for the Josef Mayer Maschinenfabrik. Her mission is to report to the newly appointed CEO what happens with the company’s products all along the lifecycle.
Although it is not directly a PLM book, the book illustrates the complexity of PLM. It Is about people and culture; many different processes, often disconnected. Everyone has their focus on their particular discipline in the center of importance. If you believe PLM is all about the best technology only, read this book and learn how many other aspects are also relevant.
I wrote about the book in 2020: Products2019 – a must-read if you are new to PLM if you want to read more details. An important point to pick up from this book is that it is not about PLM but about doing business.
PLM is not a magical product. Instead, it is a strategy to support and improve your business.
System Lifecycle Management
Another book, published a little later and motivated by the extra time we all got during the COVID-19 pandemic, was Martin Eigner‘s book System Lifecycle Management.
A 281-page journey from the early days of data management towards what Martin calls System Lifecycle Management (SysLM). He was one of the first to talk about System Lifecycle Management instead of PLM.
I always enjoyed Martin’s presentations at various PLM conferences where we met. In many ways, we share similar ideas. However, during his time as a professor at the University of Kaiserslautern (2003-2017), he explored new concepts with his students.
I briefly mentioned the book in my series The road to model-based and connected PLM (Part 5) when discussing SLM or SysLM. His academic research and analysis make this book very valuable. It takes you in a very structured way through the times that mechatronics becomes important, next the time that systems (hardware and software) become important.
We discussed in 2015 the applicability of the bimodal approach for PLM. However, as many enterprises are locked in their highly customized PDM/PLM environments, their legacy blocks the introduction of modern model-based and connected approaches.
Where John Stark’s book might miss the PLM details, Martin’s book brings you everything in detail and with all its references.
It is an interesting book if you want to catch up with what has happened in the past 20 years.
More Books …..
More books on my desk have helped me understand the past or that helped me shape the future. As this is a blog post, I will not discuss more books this time reaching my 1500 words.
Still books worthwhile to read – click on their images to learn more:
I discussed this book two times last year. An introduction in PLM and Modularity and a discussion with the authors and some readers of the book: The Modular Way – a follow-up discussion
x
x
A book I read this summer contributed to a better understanding of sustainability. I mentioned this book in my presentation for the Swedish CATIA Forum in October last year – slide 29 of
System Thinking becomes crucial for a sustainable future, as I addressed in my post PLM and Sustainability.
Sustainability is my area of interest at the PLM Green Global Alliance, an international community of professionals working with Product Lifecycle Management (PLM) enabling technologies and collaborating for a more sustainable decarbonized circular economy.
Conclusion
There is a lot to learn. Tell us something about your PLM bookshelf – which books would you recommend. In the upcoming posts, I will further focus on PLM education. So stay tuned and keep on learning.
Image http://www.mdux.net
As promised in my early November post – The road to model-based and connected PLM (part 9 – CM), I come back with more thoughts and ideas related to the future of configuration management. Moving from document-driven ways of working to a data-driven and model-based approach fundamentally changes how you can communicate and work efficiently.
Let’s be clear: configuration management’s target is first of all about risk management. Ensuring your company’s business remains sustainable, efficient, and profitable.
By providing the appropriate change processes and guidance, configuration management either avoids costly mistakes and iterations during all phases of a product lifecycle or guarantees the quality of the product and information to ensure safety.
Companies that have not implemented CM practices probably have not observed these issues. Or they have not realized that the root cause of these issues is a lack of CM.
Similar to what is said in smaller companies related to PLM, CM is often seen as an overhead, as employees believe they thoroughly understand their products. In addition, CM is seen as a hurdle to innovation because of the standardization of practices. So yes, they think it is normal that there are sometimes problems. That’s life.
I already wrote about this topic in 2010 PLM, CM and ALM – not sexy 😦 – where ALM means Asset Lifecycle Management – my focus at that time.
Hear it from the experts
To shape the discussion related to the future of Configuration Management, I had a vivid discussion with three thought leaders in this field: Lisa Fenwick, Martijn Dullaart and Maxime Gravel. A short introduction of the three of them:
Lisa Fenwick, VP Product Development at CMstat, a leading company in Configuration Management and Data Management software solutions and consulting services for aviation, aerospace & defense, marine, and other high-tech industries. She has over 25 years of experience with CM and Deliverables Management, including both government and commercial environments.
Ms. Fenwick has achieved CMPIC SME, CMPIC CM Assessor, and CMII-C certifications. Her experience includes implementing CM software products, CM-related consulting and training, and participation in the SAE and IEEE standards development groups
Martijn Dullaart is the Lead Architect for Enterprise Configuration Management at ASML (Our Dutch national pride) and chairperson of the Industry 4.0 committee of the Institute Process Excellence (IPX) Congress. Martijn has his own blog mdux.net, and you might have seen him recently during the PLM Roadmap & PDT Fall conference in November – his thoughts about the CM future can be found on his blog here
Maxime Gravel, Manager Model-Based Engineering at Moog Inc., a worldwide designer, manufacturer, and integrator of advanced motion control products. Max has been the director of the model-based enterprise at the Institute for Process Excellence (IPX) and Head of Configuration and Change Management at Gulfstream Aerospace which certified the first aircraft in a 3D Model-Based Environment.
What we discussed:
We had an almost one-hour discussion related to the following points:
- The need for Enterprise Configuration Management – why and how
- The needed change from document-driven to model-based – the impact on methodology and tools
- The “neural network” of data – connecting CM to all other business domains, a similar view as from the PLM domain,
I kept from our discussion the importance of planning – as seen in the CMstat image on the left.
To plan which data you need to manage and how you will manage the data. How often are you doing this in your company’s projects?
Next, all participants stressed the importance of education and training on this topic – get educated. Configuration Management is not a topic that is taught at schools. Early next year, I will come back on education as the benefits of education are often underestimated. Not everything can be learned by “googling.”
Conclusion
The journey towards a model-based and data-driven future is not a quick one to be realized by new technologies. However, it is interesting to learn that the future of connected data (the “neural network”) allows organizations to implement both CM and PLM in a similar manner, using graph databases and automation. When executed at the enterprise level, the result will be that CM and PLM become natural practices instead of other siloed system-related disciplines.
Most of the methodology is there; the implementation to make it smooth and embedded in organizations will be the topics to learn. Join us in discussing and learning!
This week I attended the PLM Roadmap & PDT Fall 2021 with great expectations based on my enthusiasm last year. Unfortunately, the excitement was less this time, and I will explain in my conclusions why. This time it was unfortunate again a virtual event which makes it hard to be interactive, something I realize I am missing a lot.
Over two hundred attendees connected for the two days, and you can find the agenda here. Typically I would discuss the relevant sessions; now, I want to group some of them related to a theme, as there was complementary information in these sessions.
Disruption
Again like in the spring, the theme was focusing on DISRUPTION. The word disruption can give you an uncomfortable feeling when you are not in power. It is more fun to disrupt than to be disrupted, as I mentioned in my spring presentation. Read The week after PLM Roadmap & PDT Spring 2021
In his keynote speech Peter Bilello (CIMdata) kicked off with: The Critical Dozen: 12 familiar, evolving trends and enablers of digital transformation that you cannot or should not live without.
You can see them on the slide below:
I believe many of them should be familiar to you as these themes have been “in the air” already for quite some time. Vendors first and slowly companies start to investigate them when relevant. You will find many of them back in my recent series: The road to model-based and connected PLM, where I explored the topics that would cross your path on that journey.
Like Peter said: “For most of the topics you cannot pick and choose as they are all connected.”
Another interesting observation was that we are more and more moving away from the concept of related structures (digital thread) but more to connected datasets (digital web). Marc Halpern first introduced this topic last year at the 2020 conference and has become an excellent image to frame what we should imagine in a connected world.
Digital web also has to do with the uprise of the graph database mentioned by Peter Bilello as a potentially disruptive technology during the fireside chat. Relational databases can be seen as rigid, associated with PLM structures. On the other hand, graph databases can be associated with flexible relations between different types of data – the image of the digital web.
Where Peter was mainly telling WHAT was happening, two presentations caught my attention because of the HOW.
First of all, Dr. Rodney Ewing (Cummins) ‘s session: A Balanced Strategy to Reap Continuous Business Value from Digital PLM was a great story of a transformational project. It contained both having a continuous delivery of business value in mind while moving to the connected enterprise.
As Rodney mentioned, the contribution of TCS was crucial here, which I can imagine. It is hard for a company to understand what is happening in the outside (PLM) world when applying it to your company. Their transformation roadmap is an excellent example of having the long-term vision in mind, meanwhile delivering value during the transformation.
Talking about the right partner and synergy, the second presentation I liked in this context of disruption was Ian Quest’s presentation (Quick Release): Open-source Disruption in Support of Audacious Goals. As a sponsor of the conference, they had ten minutes to pitch their area of expertise.
After Ian’s presentation, focused on audacious goals (for non-English natives translated as “brave” goals), there was only one word that stuck to my mind: pragmatic.
Instead of discussions about the complexity, Ian gave examples of where a pragmatic data-centric approach could lead to great benefits, as you can see from one of the illustrated benefits below:
Standards
A characteristic topic of this conference is that we always talk about standards. Torbjörn Holm (Eurostep) gave an excellent overview of where standards have led to significant benefits. For example, the containerization of goods has dramatically improved transportation of goods (we all benefit) while killing proprietary means of transport (trains, type of ships, type of unloading). See the image below:
Torbjörn rightfully expanded this story to the current situation in the construction industry or the challenges for asset operators. Unfortunately, in these practices, many content suppliers remain focusing on their unique capabilities, reluctantly neglecting the demand for interoperability among the whole value chain.
It is a topic Marc Halpern also mentioned last year as an outcome of their Gartner PLM benefits survey. Gartner’s findings:
Time to Market is not so much improved by using PLM as the inefficient interaction with suppliers is the impediment.
Like transport before containerization, the exchange of information is not standardized and designed for digital exchange. Torbjorn believes that more and more companies will insist on exchange standards – like CHIFOS – an ISO1596-derived exchange standard in the process industry. It is a user-driven standard, the best standard.
In this context, the presentation from Kenny Swope (Boeing) and Jean Yves Delaunay (Airbus) The Business Value of Standards-based Information Interoperability for Aerospace & Defense illustrated this fact.
While working for competitors, the Aerospace industry understands the criticality of standards to become more efficient and less vendor-dependent. In the aerospace & defense group, they discuss these themes. The last year’s 2020 Fall sessions showed the results. You can read their publications here
The A&D PLM action group uses the following framework when evaluating standards – as you can see on the image below:
The result – and this is a combined exercise of many participating experts from the field; this is their recommendation:
To conclude:
People often complain about standards, framed by proprietary data format vendors, that they lead to a rigid environment, blocking agility.
In reality, standards allow companies to be more agile as the (proprietary) data flow is less an issue. Remember the containerization example.
Sustainability and System Thinking
This conference has always been known for its attention to the circular economy and green thinking. In the past, these topics might have been considered disconnected from our PLM practices; now, they have become a part of everyone’s mission.
Two presentations stood out on this topic for me. First, Ken Webster, with his keynote speech: In the future, you will own nothing and you will be happy was a significant oversight of how we as consumers currently are disconnected from the circular economy. His plea, as shown below, for making manufacturers responsible for the legal ownership of the materials in the products they deliver would impact consumer behavior.
Product as a Service (PaaS) and new ways to provide a service is becoming essential. For example, buildings as power stations, as they are a place to collect solar or wind energy?
His thoughts are aligned with what is happening in Europe related to the European Green Deal (not in his presentation). There is a push for a PaaS model for all products as this would be an excellent stimulant for the circular economy. PaaS combined with a Digital Product Passport – more on that next year.
Making upgrades to your products has less impact on the environment than creating new products to sell (and creating waste of the old product). Ken Webster was an interesting statement about changing the economy – do we want to own products or do we want to benefit from the product and leave the legal ownership to the manufacturer.
A topic I discussed in the PLM Roadmap & PDT Conference Spring 2021 – look here at slide 11
Patrick Hillberg‘s presentation Rising to the challenge of engineering and optimizing . . . what? was the one closest to my heart. We discussed Sustainability and Systems Thinking with Patrick in our PLM Global Green Alliance, being pretty aligned on this topic. Patrick started by explaining the difference between Systems Engineering and Systems Thinking. Looking at the product go-to-market of an organization is more than the traditional V-model. Economic pressure and culture will push people to deviate from the ideal technological plan due to other priorities.
Expanding on this observation, Partick stated that there are limits to growth, a topic discussed by many people involved in the sustainable economy. Economic growth is impossible on a limited planet, and we have to take more dimensions into account. Patrick gave some examples of that, including issues related to the infamous Boeing 737 Max example.
For Patrick, the COVID-pandemic is the end of the old 2nd Industrial Revolution and a push for a new Fourth Industrial Revolution, which is not only technical, as the slide below indicates.
With Patrick, I believe we are at a decisive moment to disrupt ourselves, reconsider many things we do and are used to doing. Even for PLM practitioners, this is a new path to go.
Data
There were two presentations related to digitization and the shift from document-based to a data-driven approach.
First, there was Greg Weaver (Gulfstream) with his presentation Indexing Content – Finding Your Needle in the Haystack. Greg explained that by using indexation of existing document-based information combined with a specific dashboard, they could provide fast access to information that otherwise would have been hidden in so many document or even paper archives.
It was a pragmatic solution, making me feel nostalgic seeing the SmarTeam profile cards. It was an excellent example of moving to a digital enterprise, and Gulfstream has always been a front runner on this topic.
Warning: Don’t use this by default at home (your company). The data in a regulated industry like Aerospace is expected to be of high quality due to the configuration management processes in place. If your company does not have a strong CM practice, the retrieved data might be inaccurate.
Martijn Dullaart (ASML)’s presentation The Next disruption, please….. was the next step into the future. With his statement “No CM = No Trust,” he made an essential point for data-driven environments.
There is a need for Configuration Management, and I touched on this topic in my last post: The road to model-based and connected PLM (part 9 – CM).
Martijn’s presentation can also be found on his blog here, and I encourage you to read it (saving me copy & paste text). It was interesting to see that Martijn improved his CM pyramid, as you can see, more discipline and activity-oriented instead of a system view. With Martijn and others, I will elaborate on this topic soon.
Conclusion
This has been an extremely long post, and thanks for reading until the end. Many interesting topics were presented at the conference. I was less excited this time because many of these topics are triggers for a discussion. Innovation comes from meeting people with different backgrounds. In a live conference, you would meet during the break or during the famous dinner. How can we ensure we follow up on all this interesting information.
Your thoughts? Contact me for a Corona Friday discussion.
Jos Voskuil's Weblog 
[…] (The following post from PLM Green Global Alliance cofounder Jos Voskuil first appeared in his European PLM-focused blog HERE.) […]
[…] recent discussions in the PLM ecosystem, including PSC Transition Technologies (EcoPLM), CIMPA PLM services (LCA), and the Design for…
Jos, all interesting and relevant. There are additional elements to be mentioned and Ontologies seem to be one of the…
Jos, as usual, you've provided a buffet of "food for thought". Where do you see AI being trained by a…
Hi Jos. Thanks for getting back to posting! Is is an interesting and ongoing struggle, federation vs one vendor approach.…