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Last week I attended the long-awaited joined conference from CIMdata and Eurostep in Stuttgart. As I mentioned in earlier blog posts. I like this conference because it is a relatively small conference with a focused audience related to a chosen theme.
Instead of parallel sessions, all attendees follow the same tracks and after two days there is a common understanding for all. This time there were about 70 people discussing the themes: Digitalizing Reality—PLM’s role in enabling the digital revolution (CIMdata) and Collaboration in the Engineering and Manufacturing Supply Chain –the Extended Digital Thread and Smart Manufacturing (EuroStep)
As you can see all about Digital. Here are my comments:
The State of the PLM Industry:
The Digital Revolution
Peter Bilello kicked off with providing an overview of the PLM industry. The PLM market showed an overall growth of 7.3 % toward 43.6 Billion dollars. Zooming in into the details cPDM grew with 2.9 %. The significant growth came from the PLM tools (7.7 %). The Digital Manufacturing sector grew at 6.2 %. These numbers show to my opinion that in particular, managing collaborating remains the challenging part for PLM. It is easier to buy tools than invest in cPDM.
Peter mentioned that at the board level you cannot sell PLM as this acronym is too much framed as an engineering tool. Also, people at the board have been trained to interpret transactional data and build strategies on that. They might embrace Digital Transformation. However, the Product innovation related domain is hard to define in numbers. What is the value of collaboration? How do you measure and value innovation coming from R&D? Recently we have seen more simplified approaches how to get more value from PLM. I agree with Peter, we need to avoid the PLM-framing and find better consumable value statements.
Nothing to add to Peter’s closing remarks:
An Alternative View of the Systems Engineering “V”
For me, the most interesting presentation of Day 1 was Don Farr’s presentation. Don and his Boeing team worked on depicting the Systems Engineering process for a Model-Based environment. The original “V” looks like a linear process and does not reflect the multi-dimensional iterations at various stages, the concept of a virtual twin and the various business domains that need to be supported.
The result was the diamond symbol above. Don and his team have created a consistent story related to the depicted diamond which goes too far for this blog post. Current the diamond concept is copyrighted by Boeing, but I expect we will see more of this in the future as the classical systems engineering “V” was not design for our model-based view of the virtual and physical products to design AND maintain.
Sponsor vignette sessions
The vignette sponsors of the conference, Aras, ESI,-group, Granta Design, HCL, Oracle and TCS all got a ten minutes’ slot to introduce themselves, and the topics they believed were relevant for the audience. These slots served as a teaser to come to their booth during a break. Interesting for me was Granta Design who are bringing a complementary data service related to materials along the product lifecycle, providing a digital continuity for material information. See below.
The PLM – CLM Axis vital for Digitalization of Product Process
Mikko Jokela, Head of Engineering Applications CoE, from ABB, completed the morning sessions and left me with a lot of questions. Mikko’s mission is to provide the ABB companies with an information infrastructure that is providing end-to-end digital services for the future, based on apps and platform thinking.
Apparently, the digital continuity will be provided by all kind of BOM-structures as you can see below.
In my post, Coordinated or Connected, related to a model-based enterprise I call this approach a coordinated approach, which is a current best practice, not an approach for the future. There we want a model-based enterprise instead of a BOM-centric approach to ensure a digital thread. See also Don Farr’s diamond. When I asked Mikko which data standard(s) ABB will use to implement their enterprise data model it became clear there was no concept yet in place. Perhaps an excellent opportunity to look at PLCS for the product related schema.
A general comment: Many companies are thinking about building their own platform. Not all will build their platform from scratch. For those starting from scratch have a look at existing standards for your industry. And to manage the quality of data, you will need to implement Master Data Management, where for the product part the PLM system can play a significant role. See Master Data Management and PLM.
Systems of Systems Approach to Product Design
Professor Martin Eigner keynote presentation was about the concepts how new products and markets need a Systems of Systems approach combined with Model-Based Systems Engineering (MBSE) and Product Line Engineering (PLE) where the PLM system can be the backbone to support the MBSE artifacts in context. All these concepts require new ways of working as stated below:
And this is a challenge. A quick survey in the room (and coherent with my observations from the field) is the fact that most companies (95 %) haven’t even achieved to work integrated for mechatronics products. You can imagine the challenge to incorporate also Software, Simulation, and other business disciplines. Martin’s presentations are always an excellent conceptual framework for those who want to dive deeper a start point for discussion and learning.
Additive Manufacturing (Enabled Supply) at Moog
Moog Inc, a manufacturer of precision motion controls for various industries have made a strategic move towards Additive Manufacturing. Peter Kerl, Moog’s Engineering Systems Manager, gave a good introduction what is meant by Additive Manufacturing and how Moog is introducing Additive Manufacturing in their organization to create more value for their customer base and attract new customers in a less commodity domain. As you can image delivering products through Additive Manufacturing requires new skills (Design / Materials), new processes and a new organizational structure. And of course a new PLM infrastructure.
Jim van Oss, Moog’s PLM Architect and Strategist, explained how they have been involved in a technology solution for digital-enabled parts leveraging blockchain technology. Have a look at their VeriPart trademark. It was interesting to learn from Peter and Jim that they are actively working in a space that according to the Gartner’s hype curve is in the early transform phase. Peter and Jim’s presentation were very educational for the audience.
For me, it was also interesting to learn from Jim that at Moog they were really practicing the modes for PLM in their company. Two PLM implementations, one with the legacy data and the wrong data for the future and one with the new data model for the future. Both implementations build on the same PLM vendor’s release. A great illustration showing the past and the future data for PLM are not compatible
Value Creation through Synergies between PLM & Digital Transformation
Daniel Dubreuil, Safran’s CDO for Products and Services gave an entertaining lecture related to Safran’s PLM journey and the introduction of new digital capabilities, moving from an inward PLM system towards a digital infrastructure supporting internal (model-based systems engineering / multiple BOMs) and external collaboration with their customers and suppliers introducing new business capabilities. Daniel gave a very precise walk-through with examples from the real world. The concluding slide: KEY SUCCESS FACTORS was a slide that we have seen so many times at PLM events.
Apparently, the key success factors are known. However, most of the time one or more of these points are not possible to address due to various reasons. Then the question is: How to mitigate this risk as there will be issues ahead?
Bringing all the digital trends together. What’s next?
The day ended with a virtual Fire Place session between Peter Bilello and Martin Eigner, the audience did not see a fireplace however my augmented twitter feed did it for me:
Some interesting observations from this dialogue:
Peter: “Having studied physics is a good base for understanding PLM as you have to model things you cannot see” – As I studied physics I can agree.
Martin: “Germany is the center of knowledge for Mechanical, the US for Electronics and now China becoming the center for Electronics and Software” Interesting observation illustrating where the innovation will come from.
Both Peter and Martin spent serious time on the importance of multidisciplinary education. We are teaching people in silos, faculties work in silos. We all believe these silos must be broken down. It is hard to learn and experiment skills for the future. Where to start and lead?
Conclusion:
The PLM roadmap had some exciting presentations combined with CIMdata’s PLM update an excellent opportunity to learn and discuss reality. In particular for new methodologies and technologies beyond the hype. I want to thank CIMdata for the superb organization and allowing me to take part. Next week I will follow-up with a review of the PDT Europe conference part (Day 2)
Ontology example: description of the business entities and their relationships
In my recent posts, I have talked a lot about the model-based enterprise and already after my first post: Model-Based – an introduction I got a lot of feedback where most of the audience was automatically associating the words Model-Based to a 3D CAD Model.
Trying to clarify this through my post: Why Model-Based – the 3D CAD Model stirred up the discussion even more leading into: Model- Based: The confusion.
A Digital Twin of the Organization
At that time, I briefly touched on business models and business processes that also need to be reshaped and build for a digital enterprise. Business modeling is necessary if you want to understand and streamline large enterprises, where nobody can overview the overall company. This approach is like systems engineering where we try to understand and simulate complex systems.
With this post, I want to close on the Model-Based series and focus on the aspects of the business model. I was caught by this catchy article: How would you like a digital twin of your organization? which provides a nice introduction to this theme. Also, I met with Steve Dunnico, Creator and co-founder of Clearvision, a Swedish startup company focusing on modern ways of business modeling.
Introduction
Jos (VirtualDutchman): Steve can you give us an introduction to your company and the which parts of the model-based enterprise you are addressing with Clearvision?
Steve (Clearvision): Clearvision started as a concept over two decades ago – modeling complex situations across multiple domains needed a simplistic approach to create a copy of the complete ecosystem. Along the way, technology advancements have opened up big-data to everyone, and now we have Clearvision as a modeling tool/SaaS that creates a digital business ecosystem that enables better visibility to deliver transformation.
As we all know, change is constant, so we must transition from the old silo projects and programs to a business world of continuous monitoring and transformation.
Clearvision enables this by connecting the disparate parts of an organization into a model linking people, competence, technology services, data flow, organization, and processes.
Complex inter-dependencies can be visualized, showing impact and opportunity to deliver corporate transformation goals in measured minimum viable transformation – many small changes, with measurable benefit, delivered frequently. This is what Clearvision enables!
Jos: What is your definition of business modeling?
Steve: Business modeling historically, has long been the domain of financial experts – taking the “business model” of the company (such as production, sales, support) and looking at cost, profit, margins for opportunity and remodeling to suit. Now, with the availability of increased digital data about many dimensions of a business, it is possible to model more than the financials.
This is the business modeling that we (Clearvision) work with – connecting all the entities that define a business so that a change is connected to process, people, data, technology and other dimensions such as cost, time, quality. So if we change a part, all of the connected parts are checked for impact and benefit.
Jos: What are the benefits of business modeling?
Steve: Connecting the disparate entities of a business opens up limitless opportunities to analyze “what is affected if I change this?”. This can be applied to simple static “as-is” gap analyses, to the more advanced studies needed to future forecast and move into predictive planning rather than reactive.
The benefits of using a digital model of the business ecosystem are applicable to the whole organization. The “C-suite” team get to see heat-maps for not only technology-project deliveries but can use workforce-culture maps to assess the company’s understanding and adoption of new ways of working and achievement of strategic goals. While at an operational level, teams can collaborate more effectively knowing which parts of the ecosystem help or hinder their deliveries and vice-versa.
Jos: Is business modeling applicable for any type or size of the company?
The complexity of business has driven us to silo our way of working, to simplify tasks to achieve our own goals, and it is larger organizations which can benefit from modeling their business ecosystems. On that basis, it is unlikely that a standalone small business would engage in its own digital ecosystem model. However, as a supplier to a larger organization, it can be beneficial for the larger organizations to model their smaller suppliers to ensure a holistic view of their ecosystem.
The core digital business ecosystem model delivers integrated views of dependencies, clashes, hot-spots to support transformation
Jos: How is business modeling related to digital transformation?
Digital transformation is an often heard topic in large corporations, by implication we should take advantage of the digital data we generate and collect in our businesses and connect it, so we benefit from the whole not work in silos. Therefore, using a digital model of a business ecosystem will help identify areas of connectivity and collaboration that can deliver best benefit but through Minimum Viable Transformation, not a multi-year program with a big-bang output (which sometimes misses its goals…).
Today’s digital technology brings new capabilities to businesses and is driving competence changes in organizations and their partner companies. So another use of business modeling is to map competence of internal/external resources to the needed capabilities of digital transformation. Mapping competence rather than roles brings a better fit for resources to support transformation. Understanding which competencies we have and what the gaps are pr-requisite to plan and deliver transformation.
Jos: Then perhaps close with your Clearvision mission where you fit (uniquely)?
Having worked on early digital business ecosystem models in the late 90’s, we’ve cut our teeth on slow processing time, difficult to change data relationships and poor access to data, combined with a very silo’d work mentality. Clearvision is now positioned to help organizations realize that the value of the whole of their business is greater than the sum of their parts (silos) by enabling a holistic view of their business ecosystem that can be used to deliver measured transformation on a continual basis.
Jos: Thanks Steve for your contribution and with this completing the series of post related to a model-based enterprise with its various facets. I am aware this post the opinion from one company describing the importance of a model-based business in general. There are no commercial relations between the two of us and I recommend you to explore this topic further in case relevant for your situation.
Conclusion
Companies and their products are becoming more and more complex, most if it happening now, a lot more happening in the near future. In order to understand and manage this complexity models are needed to virtually define and analyze the real world without the high costs of making prototypes or changes in the real world. This applies for organizations, for systems, engineering and manufacturing coordination and finally in-field operating systems. They all can be described by – connected – models. This is the future of a model-based enterprise
Coming up next time: CIMdata PDM Roadmap Europe and PDT Europe. You can still register and meet a large group of people who care about the details of aspects of a digital enterprise
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