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The usage of standards has been a recurring topic the past 10 months, probably came back to the surface at PI PLMx Chicago during the PLM Leaders panel discussion. If you want to refresh the debate, Oleg Shilovitsky posted an overview: What vendors are thinking about PLM standards – Aras, Dassault Systemes, Onshape, Oracle PLM, Propel PLM, SAP, Siemens PLM.

It is clear for vendors when they would actively support standards they reduce their competitive advantage, after all, you are opening your systems to connect to other vendor solutions, reducing the chance to sell adjacent functionality. We call it vendor lock-in. If you think this approach only counts for PLM, I would suggest you open your Apple (iPhone) and think about vendor lock-in for a moment.

Vendors will only adhere to standards when pushed by their customers, and that is why we have a wide variety of standards in the engineering domain.

Take the example of JT as a standard viewing format, heavily pushed by Siemens for the German automotive industry to be able to work downstream with CATIA and NX models. There was a JT-version (v9.5) that reached ISO 1306 alignment, but after that, Siemens changed JT (v10) again to optimize their own exchange scenarios, and the standard was lost.

And as customers did not complain (too much), the divergence continued. So it clear  vendors will not maintain standards out of charity as your business does not work for charity either (or do you ?). So I do not blame them is there is no push from their customers to maintain them.

What about standards?

The discussion related to standards flared up around the IpX ConX19 conference and a debate between Oleg & Hakan Kardan (EuroSTEP) where Hakan suggested that PLCS could be a standard data model for the digital thread – you can read Oleg’s view here: Do we need a standard like PLCS to build a digital thread.

Oleg’s opening sentence made me immediately stop reading further as more and more I am tired of this type of framing if you want to do a serious discussion based on arguments. Such a statement is called framing and in particular in politics we see the bad examples of framing.

Standards are like toothbrushes, a good idea, but no one wants to use anyone else’s. The history of engineering and manufacturing software is full of stories about standards.

This opening sentence says all about the mindset related to standards – it is a one-liner – not a fact. It could have been a tweet in this society of experts.

Still later,I read the blog post and learned Oleg has no arguments to depreciate PLCS, however as he does not know the details, he will probably not use it. The main challenge of standards: you need to spend time to understand and adhere to them and agree on following them. Otherwise, you get the same diversion of JT again or similar examples.

However, I might have been wrong in my conclusion as Oleg did some thinking on a Sunday and came with an excellent post: What would happen if PLM Vendors agree about data standards. Here Oleg is making the comparison with a standard in the digital world, established by Google, Microsoft, Yahoo, and Yandex : Schema.org: Evolution of Structured Data on the Web.

There is a need for semantic mapping and understanding in the day-to-day-world, and this understanding makes you realize the same is needed for PLM. That was one of the reasons why I wrote in the past (2015) a series of posts related to the importance of a PLM data model:

All these posts were aimed to help companies and implementers to make the right choices for an item-centric PLM implementation. At that time – 2015, item-centric was the current PLM best practice. I learned from my engagements in the past 15 years, in particular when you have a flexible modeling tool like SmarTeam or nowadays Aras, making the right data model decisions are crucial for future growth.

Who needs standards?

First of all, as long as you stay in your controlled environment, you do not need standards. In particular, in the Aerospace and Automotive industry, the OEMs defined the software versions to be used, and the supply chain had to adhere to their chosen formats. Even this narrow definition was not complete enough as a 3D CAD model needed to be exported for simulation or manufacturing purposes. There was not a single vendor working on a single CAD model definition at that time. So the need for standards emerged as there was a need to exchange data.

Data exchange is the driving force behind standards.

In a second stage also neutral format data storage became an important point – how to save for 75 years an aircraft definition.

Oil & Gas / Building – Construction

These two industries both had the need for standards. The Oil & Gas industry relies on EPC (Engineering / Procurement / Construction)  companies that build plants or platforms. Then the owner/operator takes over the operation and needs a hand-over of all the relevant information. However if this information would be delivered in the application-specific formats the EPC companies have used, the owner/operator would require various software environments and skills, just to have access to the data.

Therefore if the data is delivered in a standard format (ISO 15926) and the exchange follows CFIHOS (Capital Facilities Information Hand Over Specification) this exchange can be done more automated between the EPC and Owner/Operator environment, leading to lower overall cost of delivering and maintaining the information combined with a higher quality. For that reason, the Oil & Gas industry has invested already for a long time in standards as their plants/platform have a long lifecycle.

And the same is happening in the construction industry. Initially Autodesk and Bentley were fighting to become the vendor-standard and ultimately the IFC-standard has taken a lot from the Autodesk-world, but has become a neutral standard for all parties involved in a construction project to share and exchange data. In particular for the construction industry,  the cloud has been an accelerator for collaboration.

So standards are needed where companies/people exchange information

For the same reason in most global companies, English became the standard language. If you needed to learn all the languages spoken in a worldwide organization, you would not have time for business. Therefore everyone making some effort to communicate in one standard language is the best way to operate.

And this is the same for a future data-driven environment – we cannot afford for every exchange to go to the native format from the receiver or source – common neutral (or winning) standards will ultimately also come up in the world of manufacturing data exchange and IoT.

Companies need to push

This is probably the blocking issue for standards. Developing standards, using standards require an effort without immediate ROI. So why not use vendor-formats/models and create custom point-to-point interface as we only need one or two interfaces?  Companies delivering products with a long lifecycle know that the current data formats are not guaranteed for the future, so they push for standards (aerospace/defense/ oil & gas/construction/ infrastructure).

3D PDF Model

Other companies are looking for short term results, and standards are slowing them down. However as soon as they need to exchange data with their Eco-system (suppliers/ customers) an existing standard will make their business more scalable. The lack of standards is one of the inhibitors for Model-Based Definition or the Model-Based Enterprise – see also my post on this topic: Model-Based – Connecting Engineering and Manufacturing

When we would imagine the Digital Enterprise of the future, information will be connected through data streams and models. In a digital enterprise file conversions and proprietary formats will impede the flow of data and create non-value added work. For example if we look to current “Digital Twin” concepts, the 3D-representation of the twin is recreated again instead of a neutral 3D-model continuity. This because companies currently work in a coordinated manner. In perhaps 10 years from now we will reach maturity of a model-based enterprise, which only can exist based on standards. If the standards are based on one dominating platform or based on a merger of standards will be the question.

To discuss this question and how to bridge from the past to the future I am looking forward meeting you at the upcoming PLM Roadmap & PDT 2019 EMEA conference on 13-14 November in Paris, France. Download the program here: PLM for Professionals – Product Lifecycle Innovation

Conclusion

I believe PLM Standards will emerge when building and optimizing a digital enterprise. We need to keep on pushing and actively working for meaningful standards as they are crucial to avoid a lock-in of your data. Potentially creating dead-ends and massive inefficiencies.  The future is about connected Eco-systems, and the leanest companies will survive. Standards do not need to be extraordinarily well-defined and can start from a high-level alignment as we saw from schema.org. Keep on investing and contributing to standards and related discussion to create a shared learning path.

Thanks Oleg Shilovitsky to keep the topic alive.

p.s. I had not time to read and process your PLM Data Commodizitation post

 

Last week I read Verdi Ogewell’ s article:  PTC puts the Needle to the Digital Thread on Engineering.com where Verdi raised the question (and concluded) who is the most visionary PLM CEO – Bernard Charles from Dassault Systemes or Jim Heppelman from PTC. Unfortunate again, an advertorial creating more haziness around modern PLM than adding value.

People need education and Engineering.com is/was a respected site for me, as they state in their Engineering.com/about statement:

Valuable Content for Busy Engineers. Engineering.com was founded on the simple mission to help engineers be better.

Unfortunate this is not the case in the PLM domain anymore. In June, we saw an article related to the failing PLM migration at Ericsson – see The PLM migration dilemma. Besides the fact that a big-bang migration had failed at Ericsson, the majority of the article was based on rumors and suggestions, putting the sponsor of this article in a better perspective.

Of course, Engineering.com needs sponsoring to host their content, and vendors are willing to spend marketing money on that. However, it would be fairer to mention in a footnote who sponsored the article – although per article you can guess. Some more sincere editors or bloggers mention their sponsoring that might have influenced their opinion.

Now, why did the article PTC puts the Needle to the Digital Thread made me react ?

Does a visionary CEO pay off?

It can be great to have a visionary CEO however, do they make the company and their products/services more successful? For every successful visionary CEO, there are perhaps ten failing visionary CEOs as the stock market or their customers did not catch their vision.

There is no lack of PLM vision as Peter Bilello mapped in 2014 when imagining the gaps between vision, available technology, and implementations at companies (leaders and followers). See below:

The tremendous gap between vision and implementations is the topic that concerns me the most. Modern PLM is about making data available across the enterprise or even across the company’s ecosystem. It is about data democratization that allows information to flow and to be presented in context, without the need to recreate this information again.

And here the marketing starts. Verdi writes:

PTC’s Internet of Things (IoT), Industrial Internet of Things (IIoT), digital twin and augmented reality (AR) investments, as well as the collaboration with Rockwell Automation in the factory automation arena, have definitely placed the company in a leading position in digital product realization, distribution and aftermarket services

With this marketing sentence, we are eager to learn why

“With AR, for example, we can improve the quality control of the engines,” added Volvo Group’s Bertrand Felix, during an on-stage interview by Jim Heppelmann. Heppelmann then went down to a Volvo truck with the engine lifted out of its compartment. Using a tablet, he was able to show how the software identified the individual engine, the parts that were included, and he could also pick up the 3D models of each component and at the same time check that everything was included and in the right place.

Impressive – is it real?

The point is that this is the whole chain for digital product realization–development and manufacturing–that the Volvo Group has chosen to focus on. Sub-components have been set up that will build the chain, much is still in the pilot stage, and a lot remains to be done. But there is a plan, and the steps forward are imminent.

OK, so it is a pilot, and a lot remains to be done – but there is a plan. I am curious about the details of that plan, as a little later, we learn from the CAD story:

The Pro/ENGINEER “inheritor” Creo (engine, chassis) is mainly used for CAD and creation of digital twins, but as previously noted, Dassault Systémes’ CATIA is also still used. Just as in many other large industrial organizations, Autodesk’s AutoCAD is also represented for simpler design solutions.

There goes the efficient digital dream. Design data coming from CATIA needs to be recreated in Creo for digital twin support. Data conversion or recreation is an expensive exercise and needs to be reliable and affordable as the value of the digital twin is gone once the data is incorrect.

In a digital enterprise, you do not want silos to work with their own formats, you want a digital thread based on (neutral) models that share metadata/parameters from design to service.

So I dropped the article and noticed Oleg had already commented faster than me in his post: Does PLM industry need a visionary pageant? Oleg refers also to CIMdata, as they confirmed in 2018 that the concept of a platform for product innovation (PIP), or the beyond PLM is far from reality in companies. Most of the time, a PLM-implementation is mainly a beyond PDM environment, not really delivering product data downstream.

I am wholly aligned with Oleg’s  technical conclusion:

What is my(Oleg’s) conclusion? PLM industry doesn’t need another round of visionary pageants. I’d call democratization, downstream usage and openness as biggest challenges and opportunities in PLM applications. Recent decades of platform development demonstrated the important role network platforms played in the development of global systems and services. PLM paradigm change from isolated vertical platforms to open network services required to bring PLM to the next level. Just my thoughts..

My comments to Oleg’s post:

(Jos) I fully agree we do not need more visionary PLM pageants. It is not about technology and therefore I have to disagree with your point about Aras. You call it democratization and openness of data a crucial point – and here I agree – be it that we probably disagree about how to reach this – through standards or through more technology. My main point to be made (this post ) is that we need visionary companies that implement and rethink their processes and are willing to invest resources in that effort. Most digital transformation projects related to PLM fail because the existing status quo/ middle management has no incentive to change. More thoughts to come

And this the central part of my argumentation – it is not about technology (only).

Organizational structures are blocking digital transformation

Since 2014 I have been following several larger manufacturing companies on their path from pushing products to the market in a linear mode towards a customer-driven, more agile, fast responding enterprise. As this is done by taking benefit of digital technologies, we call this process: digital transformation.

(image depicting GE’s digital thread)

What I have learned from these larger enterprises, and both Volvo Trucks and GE as examples, that there is a vision for an end result. For GE, it is the virtual twin of their engines monitored and improved by their Predix platform. For Volvo Trucks, we saw the vision in the quote from Verdi’s article before.

However, these companies are failing in creating a horizontal mindset inside their companies. Data can only be efficient used downstream if there is a willingness to work on collecting the relevant data upstream and delivering this information in an accessible format, preferably data-driven.

The Middle Management Dilemma

And this leads to my reference to middle management. Middle managers learn about the C-level vision and are pushed to make this vision happen. However, they are measured and driven to solve these demands, mainly within their own division or discipline. Yes, they might create goodwill for others, but when it comes to money spent or changing people responsibilities, the status quo will remain.

I wrote about this challenge in The Middle Management dilemma. Digital transformation, of course, is enabled by digital technologies, but it does not mean the technology is creating the transformation. The crucial fact lies in making companies more flexible in their operations, yet establishing better and new contacts with customers.

It is interesting to see that the future of businesses is looking into agile, multidisciplinary teams that can deliver incremental innovations to the company’s portfolio. Somehow going back to the startup culture inside a more significant enterprise. Having worked with several startups, you see the outcome-focus as a whole in the beginning – everyone contributes. Then when the size of the company grows, middle-management is introduced, and most likely silos are created as the middle management gets their own profit & loss targets.

Digital Transformation myths debunked

This week Helmut Romer (thanks Helmut) pointed me to the following HBR-article: Digital does not need to be disruptive where the following myths are debunked:

  1. Myth: Digital requires radical disruption of the value proposition.
    Reality: It usually means using digital tools to better serve the known customer need.
  2. Myth: Digital will replace physical
    Reality: It is a “both/and.”
  3. Myth: Digital involves buying start-ups.
    Reality: It involves protecting start-ups.
  4. Myth: Digital is about technology.
    Reality: It’s about the customer
  5. Myth: Digital requires overhauling legacy systems.
    Reality: It’s more often about incremental bridging.

If you want to understand these five debunked myths, take your time to read the full article, very much aligned with my argumentation, albeit it that my focus is more on the PLM domain.

Conclusions

Vendor sponsoring at Engineering.com has not improved the quality of their PLM articles and creates misleading messages. Especially as the sponsor is not mentioned, and the sponsor is selling technology – the vision gap is too big with reality to compete around a vision.

Transforming companies to take benefit of new technologies requires an end-to-end vision and mindset based on achievable, incremental learning steps. The way your middle management is managed and measured needs to be reworked as the focus is on horizontal flow and understanding of customer/market-oriented processes.

 

In my previous post, the PLM blame game, I briefly mentioned that there are two delivery models for PLM. One approach based on a PLM system, that contains predefined business logic and functionality, promoting to use the system as much as possible out-of-the-box (OOTB) somehow driving toward a certain rigidness or the other approach where the PLM capabilities need to be developed on top of a customizable infrastructure, providing more flexibility. I believe there has been a debate about this topic over more than 15 years without a decisive conclusion. Therefore I will take you through the pros and cons of both approaches illustrated by examples from the field.

PLM started as a toolkit

The initial cPDM/PLM systems were toolkits for several reasons. In the early days, scalable connectivity was not available or way too expensive for a standard collaboration approach. Engineering information, mostly design files, needed to be shared globally in an efficient manner, and the PLM backbone was often a centralized repository for CAD-data. Bill of Materials handling in PLM was often at a basic level, as either the ERP-system (mostly Aerospace/Defense) or home-grown developed BOM-systems(Automotive) were in place for manufacturing.

Depending on the business needs of the company, the target was too connect as much as possible engineering data sources to the PLM backbone – PLM originated from engineering and is still considered by many people as an engineering solution. For connectivity interfaces and integrations needed to be developed in a time that application integration frameworks were primitive and complicated. This made PLM implementations complex and expensive, so only the large automotive and aerospace/defense companies could afford to invest in such systems. And a lot of tuition fees spent to achieve results. Many of these environments are still operational as they became too risky to touch, as I described in my post: The PLM Migration Dilemma.

The birth of OOTB

Around the year 2000, there was the first development of OOTB PLM. There was Agile (later acquired by Oracle) focusing on the high-tech and medical industry. Instead of document management, they focused on the scenario from bringing the BOM from engineering to manufacturing based on a relatively fixed scenario – therefore fast to implement and fast to validate. The last point, in particular, is crucial in regulated medical environments.

At that time, I was working with SmarTeam on the development of templates for various industries, with a similar mindset. A predefined template would lead to faster implementations and therefore reducing the implementation costs. The challenge with SmarTeam, however, was that is was very easy to customize, based on Microsoft technology and wizards for data modeling and UI design.

This was not a benefit for OOTB-delivery as SmarTeam was implemented through Value Added Resellers, and their major revenue came from providing services to their customers. So it was easy to reprogram the concepts of the templates and use them as your unique selling points towards a customer. A similar situation is now happening with Aras – the primary implementation skills are at the implementing companies, and their revenue does not come from software (maintenance).

The result is that each implementer considers another implementer as a competitor and they are not willing to give up their IP to the software company.

SmarTeam resellers were not eager to deliver their IP back to SmarTeam to get it embedded in the product as it would reduce their unique selling points. I assume the same happens currently in the Aras channel – it might be called Open Source however probably it is only high-level infrastructure.

Around 2006 many of the main PLM-vendors had their various mid-market offerings, and I contributed at that time to the SmarTeam Engineering Express – a preconfigured solution that was rapid to implement if you wanted.

Although the SmarTeam Engineering Express was an excellent sales tool, the resellers that started to implement the software began to customize the environment as fast as possible in their own preferred manner. For two reasons: the customer most of the time had different current practices and secondly the money come from services. So why say No to a customer if you can say Yes?

OOTB and modules

Initially, for the leading PLM Vendors, their mid-market templates were not just aiming at the mid-market. All companies wanted to have a standardized PLM-system with as little as possible customizations. This meant for the PLM vendors that they had to package their functionality into modules, sometimes addressing industry-specific capabilities, sometimes areas of interfaces (CAD and ERP integrations) as a module or generic governance capabilities like portfolio management, project management, and change management.

The principles behind the modules were that they need to deliver data model capabilities combined with business logic/behavior. Otherwise, the value of the module would be not relevant. And this causes a challenge. The more business logic a module delivers, the more the company that implements the module needs to adapt to more generic practices. This requires business change management, people need to be motivated to work differently. And who is eager to make people work differently? Almost nobody,  as it is an intensive coaching job that cannot be done by the vendors (they sell software), often cannot be done by the implementers (they do not have the broad set of skills needed) or by the companies (they do not have the free resources for that). Precisely the principles behind the PLM Blame Game.

OOTB modularity advantages

The first advantage of modularity in the PLM software is that you only buy the software pieces that you really need. However, most companies do not see PLM as a journey, so they agree on a budget to start, and then every module that was not identified before becomes a cost issue. Main reason because the implementation teams focus on delivering capabilities at that stage, not at providing value-based metrics.

The second potential advantage of PLM modularity is the fact that these modules supposed to be complementary to the other modules as they should have been developed in the context of each other. In reality, this is not always the case. Yes, the modules fit nicely on a single PowerPoint slide, however, when it comes to reality, there are separate systems with a minimum of integration with the core. However, the advantage is that the PLM software provider now becomes responsible for upgradability or extendibility of the provided functionality, which is a serious point to consider.

The third advantage from the OOTB modular approach is that it forces the PLM vendor to invest in your industry and future needed capabilities, for example, digital twins, AR/VR, and model-based ways of working. Some skeptic people might say PLM vendors create problems to solve that do not exist yet, optimists might say they invest in imagining the future, which can only happen by trial-and-error. In a digital enterprise, it is: think big, start small, fail fast, and scale quickly.

OOTB modularity disadvantages

Most of the OOTB modularity disadvantages will be advantages in the toolkit approach, therefore discussed in the next paragraph. One downside from the OOTB modular approach is the disconnect between the people developing the modules and the implementers in the field. Often modules are developed based on some leading customer experiences (the big ones), where the majority of usage in the field is targeting smaller companies where people have multiple roles, the typical SMB approach. SMB implementations are often not visible at the PLM Vendor R&D level as they are hidden through the Value Added Reseller network and/or usually too small to become apparent.

Toolkit advantages

The most significant advantage of a PLM toolkit approach is that the implementation can be a journey. Starting with a clear business need, for example in modern PLM, create a digital thread and then once this is achieved dive deeper in areas of the lifecycle that require improvement. And increased functionality is only linked to the number of users, not to extra costs for a new module.

However, if the development of additional functionality becomes massive, you have the risk that low license costs are nullified by development costs.

The second advantage of a PLM toolkit approach is that the implementer and users will have a better relationship in delivering capabilities and therefore, a higher chance of acceptance. The implementer builds what the customer is asking for.

However, as Henry Ford said, if I would ask my customers what they wanted, they would ask for faster horses.

Toolkit considerations

There are several points where a PLM toolkit can be an advantage but also a disadvantage, very much depending on various characteristics of your company and your implementation team. Let’s review some of them:

Innovative: a toolkit does not provide an innovative way of working immediately. The toolkit can have an infrastructure to deliver innovative capabilities, even as small demonstrations, the implementation, and methodology to implement this innovative way of working needs to come from either your company’s resources or your implementer’s skills.

Uniqueness: with a toolkit approach, you can build a unique PLM infrastructure that makes you more competitive than the other. Don’t share your IP and best practices to be more competitive. This approach can be valid if you truly have a competing plan here. Otherwise, the risk might be you are creating a legacy for your company that will slow you down later in time.

Performance: this is a crucial topic if you want to scale your solution to the enterprise level. I spent a lot of time in the past analyzing and supporting SmarTeam implementers and template developers on their journey to optimize their solutions. Choosing the right algorithms, the right data modeling choices are crucial.

Sometimes I came into a situation where the customer blamed SmarTeam because customizations were possible – you can read about this example in an old LinkedIn post: the importance of a PLM data model

Experience: When you plan to implement PLM “big” with a toolkit approach, experience becomes crucial as initial design decisions and scope are significant for future extensions and maintainability. Beautiful implementations can become a burden after five years as design decisions were not documented or analyzed. Having experience or an experienced partner/coach can help you in these situations. In general, it is sporadic for a company to have internally experienced PLM implementers as it is not their core business to implement PLM. Experienced PLM implementers vary from size and skills – make the right choice.

 

Conclusion

After writing this post, I still cannot write a final verdict from my side what is the best approach. Personally, I like the PLM toolkit approach as I have been working in the PLM domain for twenty years seeing and experiencing good and best practices. The OOTB-box approach represents many of these best practices and therefore are a safe path to follow. The undecisive points are who are the people involved and what is your business model. It needs to be an end-to-end coherent approach, no matter which option you choose.

 

 

 

I am writing this post during the Easter weekend in the Netherlands. Easter / Passover / Pascha / are religious festivities that happen around this time, depending on full moons, etc. I am not the expert here, however, what I like about Easter is that is it is an optimistic religious celebration, connecting history, the “dark days,” and the celebration of new life.

Of course, my PLM-twisted brain never stops associating and looking into an analogy, I saw last week a LinkedIn post from Mark Reisig, about Aras ACE 2019 opening with the following statement:

Digital Transformation – it used to be called PLM,” said Aras CEO Peter Schroer, as he opened the conference with some thoughts around attaining sustainable Digital Transformation and owning the lifecycle.

Was this my Easter Egg surprise? I thought we were in the middle of the PLM Renaissance as some other vendors and consultants talk about this era. Have a look at a recent Engineering.com TV-report: Turning PLM on its head

All jokes aside, the speech from Peter Schroer contained some interesting statements and I want to elaborate on them in this post as the space to comment in LinkedIn is not designed for a long answer.

PLM is Digital Transformation?

In the past few years, there has been a discussion if the acronym PLM (Product Lifecycle Management) is perhaps outdated. PTC claimed thanks to IoT (Internet of Things) now PLM equals IoT, as you can read in  Mark Taber’s 2018 guest article in Digital Engineering: IoT Equals PLM.
Note: Mark is PTC’s vice president of marketing and go-to-market marketing according to the bio at the bottom of the article. So a lot of marketing words, which  strengthens the believers of the old world, that everything new is probably marketing.

Also during the PDT conferences, we discussed if PLM should be replaced by a new acronym and I participated in that discussion too – my Nov 2018 postWill MBSE be the new PLM instead of IoT? is a reflection of my thoughts at that time.

For me, Digital Transformation is a metamorphosis from a document-driven, sequential processes towards data-driven, iterative processes. The metamorphosis example used a lot at this moment, is the one from Caterpillar towards the Butterfly. This process is not easy when it comes to PLM-related information, as I described in my PI PLMx 2019 London Presentation and blog post: The Challenges of a Connected Ecosystem for PLM. The question is even: Will there be a full metamorphosis at the end or will we keep on working in two different modes of operations?

However, Digital Transformation does not change the PLM domain. Even after a successful digital transformation, there will be PLM. The only significant difference in the future – PLM boarders will not be so evident anymore when implementing capabilities in a system or a platform. The upcoming of digital platforms will dissolve or fade the traditional PLM-mapped capabilities.

You can see these differences already by taking an in-depth look at how Oracle, SAP or Propel address PLM. Each of them starts from a core platform with different PLM-flavored extensions, sometimes very different from the traditional PLM Vendors. So Digital transformation is not the replacement of PLM.

Back to Peter Schroer’s rebuttal of some myths. Note: DX stands for Digital Transformation

Myth #1: DX leverages disruptive tech

Peter Schroer:

 It’s easy to get excited about AI, AR, and the 3D visual experience. However, let’s be real. The first step is to get rid of your spreadsheets and paper documentation – to get an accurate product data baseline. We’re not just talking a digital CAD model, but data that includes access to performance data, as-built parts, and previous maintenance work history for everyone from technicians to product managers

Here I am fully aligned with Peter. There are a lot of fancy features discussed by marketing teams, however, when working in the field with companies, the main challenge is to get an organization digital aligned, sharing data accessible along the whole lifecycle with the right quality.

This means you need to have a management team, understanding the need for data governance, data quality and understanding the shift from data ownership to data accountability.  This will only happen with the right mix of vision, strategy and the execution of the strategy – marketing does not make it happen

 

Myth #2: DX results in increased market share, revenue, and profit

Peter Schroer:

Though there’s a lot of talk about it – there isn’t yet any compelling data which proves this to be true. Our goal at Aras is to make our products safer and faster. To support a whole suite of industrial applications to extend your DX strategy quite a bit further.

Here I agree and disagree, depending on the context of this statement. Some companies have gone through a digital transformation and therefore increased their market share, revenue, and profit. If you read books like Leading Transformation or Leading Digital, you will find examples of companies that have gone through successful digital transformations. However, you might also discover that most of these companies haven’t transformed their PLM-domain, but other parts of their businesses.

Also, it is interesting to read a 2017 McKinsey post: The case for digital reinvention, where you will get the confirmation that a lot of digital initiatives did not bring more top-line revenue and most of the times lead to extra costs. Interesting to see where companies focus their digital strategies – picture below:

Where only 2 percent of the respondents were focusing on supply chains, this is, according to the authors of the article, one of the areas with the highest potential ROI. And digital supply chains are closely related to modern PLM – so this is an area with enough work to do by all PLM practitioners– connecting ecosystems (in real-time)

Myth #3: Market leaders are the most successful at DX

Peter Schroer:

If your company is hugely profitable at the moment, it’s highly likely that your organization is NOT focused on Digital Transformation. The lifespan of S&P 500 companies continuing to shrink below 20 years.

How to Attain Sustainable Digital Transformation

– Stop buying disposable systems. It’s about an adaptable platform – it needs to change as your company changes.

– Think incremental. Do not lose momentum. Continuous change is a multi-phase journey. If you are in or completed phase I, then that means there is a phase II, a phase III, and so on.

– Align people & processes.  Mistakes will happen, “the tech side is only 50% of DX” – Aras CEO.

Here I agree with Peter on the business side, be it that some of the current market leaders are already digital. Look at Apple, Google, and Amazon. However, the majority of large enterprises have severe problems with various aspects of a digital transformation as the started in the past before digital technologies became affordable..

Digitization allows information to flow without barriers within an organization, leading to rapid insights and almost direct communication with your customers, your supply chain or other divisions within your company. This drives the need to learn and build new, lean processes and get people aligned to them. Learning to work in a different mode.

And this is extremely difficult for a market leader – as market leader fear for the outside changing world is often not felt. Between the C-level vision and people working in the company, there are several layers of middle management. These layers were created to structure and stabilize the old ways of working.

I wrote about the middle management challenge in my last blog post: The Middle Management dilemma. Almost in the same week there was an article from McKinsey: How companies can help midlevel managers navigate agile transformations.
Conclusion: It is not (only) about technology as some of the tech geeks may think.

Conclusion

Behind the myths addressed by Peter Schroer, there is a complex transformation on-going. Probably not a metamorphosis. With the Easter spirit in mind connected to PLM, I believe digital transformations are possible – Not as a miracle but driven by insights into all aspects. I hope this post gave you some more ideas and please read the connected articles – they are quite relevant if you want to discover what’s below the surface.

In this post, I will explain the story behind my presentation at PI PLMx London. You can read my review of the event here: “The weekend after ……” and you can find my slides on SlideShare: HERE.

For me, this presentation is a conclusion of a thought process and collection of built-up experiences in the past three to  five years, related to the challenges digital transformation is creating for PLM and what makes it hard to go through compared to other enterprise business domains.  So here we go:

Digital transformation or disruption?

Slide 2 (top image) until 5 are dealing with the common challenges of business transformation. In nature, the transformation from a Caterpillar (old linear business) to a Butterfly (modern, agile, flexible) has the cocoon stage, where the transformation happens. In business unfortunate companies cannot afford a cocoon phase, it needs to be a parallel change.

Human beings are not good at change (slide 3 & 4), and the risk is that a new technology or a new business model will disrupt your business if you are too confident – see examples from the past. The disruption theory introduced by Clayton Christensen in his book, the Innovators Dilemma is an excellent example of how this can happen.  Some of my thoughts are in The Innovator’s dilemma and generation change (2015)

Although I know some PLM vendors consider themselves as disruptor, I give them no chance in the PLM domain. The main reason: The existing PLM systems are so closely tied to the data they manage, that switching from one PLM system to a more modern PLM system does not pay off.  The data models are so diverse that it is better to stay with the existing environment.

What is clear for modern digital businesses is that if you could start from scratch or with almost no legacy you can move faster forward than the rest. But only if supported by a strong leadership , a(understandable) vision and relentless execution.

The impression of evolution

Marc Halpern’s slide presented at PDT 2015 is one of my favorite slides, as it maps business maturity to various characteristics of an organization, including the technologies used.

 

Slide 7 till 18 are zooming in on the terms Coordinated and Connected and the implications it has for data, people and business. I have written about Coordinated and Connected recently: Coordinated or Connected (2018)

A coordinated approach: Delivering the right information at the right moment in the proper context is what current PLM implementations try to achieve. Allowing people to use their own tools/systems as long as they deliver at the right moment their information (documents/files) as part of the lifecycle/delivery process. Very linear and not too complicated to implement you would expect. However it is difficult ! Here we already see the challenge of just aligning a company to implement a horizontal flow of data. Usability of the PLM backbone and optimized silo thinking are the main inhibitors.

In a connected approach: Providing actual information for anyone connected in any context the slide on the left shows the mental picture we need to have for a digital enterprise. Information coming from various platforms needs to be shareable and connected in real-time, leading, in particular for PLM, to a switch from document-based deliverables to models and parameters that are connected.

Slide 15 has examples of some models.  A data-driven approach creates different responsibilities as it is not about ownership anymore but about accountability.

The image above gives my PLM-twisted vision of which are the five core platforms for an enterprise.  The number FIVE is interesting as David Sherburne just published his Five Platforms that Enable Digital Transformation and in 2016 Gartner identified Five domains for the digital platform .- more IT-twisted ? But remember the purpose of digital transformation is: FIVE!

From Coordinated to Connected is Digital Transformation

Slide 19 till 27 further elaborate on the fact that for PLM there is no evolutionary approach possible, going from a Coordinated technology towards a Connected technology.

For three reasons:  different type of data (document vs. database elements), different people (working in a connected environment requires modern digital skills) and different processes (the standard methods for mechanical-oriented PLM practices do not match processes needed to deliver systems (hardware & software) with an incremental delivery process).

Due to the incompatibility of the data, more and more companies discover that a single PLM-instance cannot support both modes – staying with your existing document-oriented PLM-system does not give the capabilities needed for a model-driven approach. Migrating the data from a traditional PLM-environment towards a modern data-driven environment does not bring any value. The majority of the coordinated data is not complete and with the right quality to use a data-driven environment. Note: in  a data-driven environment you do not have people interpreting the data – the data should be correct for automation / algorithms.

The overlay approach, mentioned several times in various PLM-blogs, is an intermediate solution. It provides traceability and visibility between different data sources (PLM, ALM, ERP, SCM, …). However it does not make the information in these systems better accessible.

So the ultimate conclusion is: You need both approaches, and you need to learn to work in a hybrid environment !

What can various stakeholders do?

For the management of your company, it is crucial they understand the full impact of digital transformation. It is not about a sexy customer website, a service platform or Virtual Reality/Augmented Reality case for the shop floor or services. When these capabilities are created disconnected from the source (PLM), they will deliver inconsistencies in the long-term. The new digital baby becomes another silo in the organization. Real digital transformation comes from an end-to-end vision and implementation.  The result of this end-to-end vision will be the understanding that there is a duality in data, in particular for the PLM domain.

Besides the technicalities, when going through a digital transformation, it is crucial for the management to share their vision in a way it becomes a motivational story, a myth, for all employees. As Yuval Harari, writer of the book Sapiens,  suggested, we (Home Sapiens) need an abstract story, a myth to align a larger group of people to achieve a common abstract goal. I discussed this topic in my posts: PLM as a myth? (2017)  and PLM – measurable or a myth?

Finally, the beauty of new digital businesses is that they are connected and can be monitored in real-time. That implies you can check the results continuously and adjust – scale of fail!

Consultants and strategists in a company should also take the responsibility, to educate the management and when advising on less transformational steps, like efficiency improvements: Make sure you learn and understand model-based approaches and push for data governance initiatives. This will at least narrow the gap between coordinated and connected environments.

This was about strategy – now about execution:

For PLM vendors and implementers, understanding the incompatibility of data between current PLM practices – coordinated and connected – it will lead to different business models. Where traditionally the new PLM vendor started first with a rip-and-replace of the earlier environment – no added value – now it is about starting a new parallel environment.  This implies no more big replacement deals, but more a long-term. strategic and parallel journey.  For PLM vendors it is crucial that being able to offer to these modes in parallel will allow them to keep up their customer base and grow. If they would choose for coordinated or connected only it is for sure a competitor will work in parallel.

For PLM users, an organization should understand that they are the most valuable resources, realizing these people cannot make a drastic change in their behavior. People will adapt within their capabilities but do not expect a person who grew up in the traditional ways of working (linear / analogue) to become a successful worker in the new mode (agile / digital). Their value lies in transferring their skills and coaching new employees but do not let them work in two modes. And when it comes to education: permanent education is crucial and should be scheduled – it is not about one or two trainings per year – if the perfect training would exist, why do students go to school for several years ? Why not give them the perfect PowerPoint twice a year?

Conclusions

I believe after three years of blogging about this theme I have made my point. Let’s observe and learn from what is happening in the field – I remain curious and focused about proof points and new insights. This year I hope to share with you new ideas related to digital practices in all industries, of course all associated with the human side of what we once started to call PLM.

Note: Oleg Shilovitsky just published an interesting post this weekend: Why complexity is killing PLM and what are future trajectories and opportunities? Enough food for discussion. One point: The fact that consumers want simplicity does not mean PLM will become simple – working in the context of other information is the challenge – it is human behavior – team players are good in anticipating – big egos are not. To be continued…….

 

 

 

 

 

 

 

 

 

I was happy to take part at the PI PLMx London event last week. It was here and in the same hotel that this conference saw the light in 2011  – you can see my blog post from that event here: PLM and Innovation @ PLMINNOVATION 2011.

At that time the first vendor-independent PLM conference after a long time and it brought a lot of new people together to discuss their experience with PLM. Looking at the audience that time, many of the companies that were there, came back during the years, confirming the value this conference has brought to their PLM journey.

Similar to the PDT conference(s) – just announced for this year last week – here – the number of participants is diminishing.

Main hypotheses:

  1. the PLM-definition has become too vague. Going to a PLM conference does not guarantee it is your type of PLM discussions you expect to see?
  2. the average person is now much better informed related to PLM thanks to the internet and social media (blogs/webinars/ etc.) Therefore, the value retrieved from the PLM conference is not big enough any more?
  3. Digital Transformation is absorbing all the budget and attention downstream the organization not creating the need and awareness of modern PLM to the attention of the management anymore. g., a digital twin is sexier to discuss than PLM?

What do you think about the above three hypotheses – 1,2 and/or 3?

Back to the conference. The discussion related to PLM has changed over the past nine years. As I presented at PI from the beginning in 2011, here are the nine titles from my sessions:

2011       PLM – The missing link
2012       Making the case for PLM
2013       PLM loves Innovation
2014       PLM is changing
2015       The challenge of PLM upgrades
2016       The PLM identity crisis
2017       Digital Transformation affects PLM
2018       PLM transformation alongside Digitization
2019       The challenges of a connected Ecosystem for PLM

Where the focus started with justifying PLM, as well as a supporting infrastructure, to bring Innovation to the market, the first changes became visible in 2014. PLM was changing as more data-driven vendors appeared with new and modern (metadata) concepts and cloud, creating the discussion about what would be the next upgrade challenge.

The identity crisis reflected the introduction of software development / management combined with traditional (mechanical) PLM – how to deal with systems? Where are the best practices?

Then from 2017 on until now Digital Transformation and the impact on PLM and an organization became the themes to discuss – and we are not ready yet!

Now some of the highlights from the conference. As there were parallel sessions, I had to divide my attention – you can see the full agenda here:

How to Build Critical Architecture Models for the New Digital Economy

The conference started with a refreshing presentation from David Sherburne (Carestream) explaining their journey towards a digital economy.  According to David, the main reason behind digitization is to save time, as he quoted Harvey Mackay an American Businessman and Journalist,

Time is free, but it is priceless. You cannot own it, but you can use it. You can’t keep it, but you can spend it. Once you have lost it, you never can get it back

I tend to agree with this simplification as it makes the story easy to explain to everyone in your company. Probably I would add to that story that saving time also means less money spent on intermediate resources in a company, therefore, creating a two-sided competitive advantage.

David stated that today’s digital transformation is more about business change than technology and here I wholeheartedly agree. Once you can master the flow of data in your company, you can change and adapt your company’s business processes to be better connected to the customer and therefore deliver the value they expect (increases your competitive advantage).

Having new technology in place does not help you unless you change the way you work.

David introduced a new acronym ILM (Integrated Lifecycle Management) and I am sure some people will jump on this acronym.

David’s presentation contained an interesting view from the business-architectural point of view. An excellent start for the conference where various dimensions of digital transformation and PLM were explored.

Integrated PLM in the Chemical industry

Another interesting session was from Susanna Mäentausta  (Kemira oy)  with the title: “Increased speed to market, decreased risk of non-compliance through integrated PLM in Chemical industry.” I selected her session as from my past involvement with the process industry, I noticed that PLM adoption is very low in the process industry. Understanding Why and How they implemented PLM was interesting for me. Her PLM vision slide says it all:

There were two points that I liked a lot from her presentation, as I can confirm they are crucial.

  • Although there was a justification for the implementation of PLM, there was no ROI calculation done upfront. I think this is crucial, you know as a company you need to invest in PLM to stay competitive. Making an ROI-story is just consoling the people with artificial number – success and numbers depend on the implementation and Susanna confirmed that step 1 delivered enough value to be confident.
  • There were an end-to-end governance and a communication plan in place. Compared to PLM projects I know, this was done very extensive – full engagement of key users and on-going feedback – communicate, communicate, communicate. How often do we forget this in PLM projects?

Extracting More Value of PLM in an Engineer-to-Order Business

Sami Grönstrand & Helena Gutierrez presented as an experienced duo (they were active in PI P PLMx Hamburg/Berlin before) – their current status and mission for PLM @ Outotec. As the title suggests, it was about how to extract more value from PL M, in an Engineering to Order Business.

What I liked is how they simplified their PLM targets from a complex landscape into three story-lines.

If you jump into all the details where PLM is contributing to your business, it might get too complicated for the audience involved. Therefore, they aligned their work around three value messages:

  • Boosting sales, by focusing on modularization and encouraging the use of a product configurator. This instead of developing every time a customer-specific solution
  • Accelerating project deliverables, again reaping the benefits of modularization, creating libraries and training the workforce in using this new environment (otherwise no use of new capabilities). The results in reducing engineering hours was quite significant.
  • Creating New Business Models, by connecting all data using a joint plant structure with related equipment. By linking these data elements, an end-to-end digital continuity was established to support advanced service and support business models.

My conclusion from this session was again that if you want to motivate people on a PLM-journey it is not about the technical details, it is about the business benefits that drive these new ways of working.

Managing Product Variation in a Configure-To-Order Business

In the context of the previous session from Outotec, Björn Wilhemsson’s session was also addressing somehow the same topic of How to create as much as possible variation in your customer offering, while internally keep the number of variants and parts manageable.

Björn, Alfa Laval’s OnePLM Programme Director, explained in detail the strategy they implemented to address these challenges. His presentation was very educational and could serve as a lesson for many of us related to product portfolio management and modularization.

Björn explained in detail the six measures to control variation, starting from a model-strategy / roadmap (thinking first) followed by building a modularized product architecture, controlling and limiting the number of variants during your New Product Development process. Next as Alfa Laval is in a Configure-To-Order business, Björn the implementation of order-based and automated addition of pre-approved variants (not every variant needs to exist in detail before selling it), followed by the controlled introduction of additional variants and continuous analysis of quoted and sold variant (the power of a digital portfolio) as his summary slides shows below:

Day 1 closed with an inspirational keynote; Lessons-Learnt from the Mountaineering Experience 8848 Meter above sea level  – a mission to climb the highest mountain on each of the continents in 107 days – 9 hours – setting a new world record by Jonathan Gupta.

There are some analogies to discover between his mission and a PLM implementation. It is all about having the total picture in mind. Plan and plan, prepare step-by-step in detail and rely on teamwork – it is not a solo journey – and it is about reaching a top (deliverable phase) in the most efficient way.

The differences: PLM does not need world records, you need to go with the pace an organization can digest and understand. Although the initial PLM climate during implementation might be chilling too, I do not believe you have to suffer temperatures below 50 degrees Celsius.

During the morning, I was involved in several meetings, therefore unfortunate unable to see some of the interesting sessions at that time. Hopefully later available on PI.TV for review as slides-only do not tell the full story. Although there are experts that can conclude and comment after seeing a single slide. You can read it here from my blog buddy Oleg Shilovitsky’s post : PLM Buzzword Detox. I think oversimplification is exactly creating the current problem we have in this world – people without knowledge become louder and sure about their opinion compared to knowledgeable people who have spent time to understand the matter.

Have a look at the Dunning-Kruger effect here (if you take the time to understand).

 

PLM: Enabling the Future of a Smart and Connected Ecosystem

Peter Bilello from CIMdata shared his observations and guidance related to the current ongoing digital business revolution that is taking place thanks to internet and IoT technologies. It will fundamentally transform how people will work and interact between themselves and with machines. Survival in business will depend on how companies create Smart and Connected Ecosystems. Peter showed a slide from the 2015 World Economic Forum (below) which is still relevant:

Probably depending on your business some of these waves might have touched your organization already. What is clear that the market leaders here will benefit the most – the ones owning a smart and connected ecosystem will be the winners shortly.

Next, Peter explained why PLM, and in particular the Product Innovation Platform, is crucial for a smart and connected enterprise.  Shiny capabilities like a digital twin, the link between virtual and real, or virtual & augmented reality can only be achieved affordably and competitively if you invest in making the source digital connected. The scope of a product innovation platform is much broader than traditional PLM. Also, the way information is stored differs – moving from documents (files) towards data (elements in a database).  I fully agree with Peter’s opinion here that PLM is conceptually the Killer App for a Smart & Connected Ecosystem and this notion is spreading.

A recent article from Forbes in the category Leadership: Is Your Company Ready For Digital Product Life Cycle Management? shows there is awareness.  Still very basic and people are still confused to understand what is the difference with an electronic file (digital too ?) and a digital definition of information.

The main point to remember here: Digital information can be accessed directly through a programming interface (API/Service) without the need to open a container (document) and search for this piece of information.

Peter then zoomed in on some topics that companies need to investigate to reach a smart & connected ecosystem. Security (still a question hardly addressed in IoT/Digital Twin demos), Standards and Interoperability ( you cannot connect in all proprietary formats economically and sustainably) A lot of points to consider and I want to close with Peter’s slide illustrating where most companies are in reality

The Challenges of a Connected Ecosystem for PLM

I was happy to present after Peter Bilello and David Sherburne (on day 1) as they both gave a perspective on digital transformation complementary to what I submitted. My presentation was focusing on the incompatibility of current coordinated business systems and the concept of a connected ecosystem.

You can already download my slides from SlideShare here: The Challenges of a Connected Ecosystem for PLM . I will explain my presentation in an upcoming blog post as slides without a story might lead to the wrong interpretation, and we already reached 2000 words. Few words to come.

How to Run a PLM Project Using the Agile Manifesto

Andrew Lodge, head of Engineering Systems at JCB explained how applying the agile mindset towards a PLM project can lead to faster and accurate results needed by the business. I am a full supporter for this approach as having worked in long and waterfall-type of PLM implementations there was always the big crash and user dissatisfaction at the final delivery. Keeping the business involved every step seems to be the solution. The issue I discovered here is that agile implementation requires a lot of people, in particular, business, to be involved heavily. Some companies do not understand this need and dropped /reduced business contribution to the least, killing the value of an agile approach

 

Concluding

For me coming back to London for the PI PLMx event was very motivational. Where the past two, three conferences before in Germany might have led to little progress per year, this year, thanks to new attendees and inspiration, it became for me a vivid event, hopefully growing shortly. Networking and listening to your peers in business remains crucial to digest it all.

 

According to LinkedIn, there are over a 7500 PLM consultants in my network.  It is quite an elite group of people as I have over 100.000 CEOs in my network according to LinkedIn. Being a CEO is a commodity.

PLM consultants share a common definition, the words Product Lifecycle Management. However, what we all mean by PLM is one of the topics that has evolved over the past 19 years in a significant way.

PLM or cPDM (collaborative PDM)?

In the early days, PLM was considered as an engineering tool for collaboration, either between global subsidiaries or suppliers. The main focus of PLM was to bring engineering information to manufacturing in a controlled way. PLM and cPDM, often seen as solving the same business needs as the implementation of a PLM system most of the time got stuck at the cPDM level.

Main players at that time were Dassault Systemes, UGS (later Siemens PLM) and PTC – their solutions were MCAD-driven with limited scope – bringing engineering information towards manufacturing in a coordinated way.

PLM was not really an approach that created visibility at the management level of a company. How do you value and measure collaboration? Because connectivity was expensive in the early days of PLM, combined with the idea that PLM systems needed to be customized, PLM was framed as costly and hard to deliver value.

Systems Engineering and New Product Introduction

Then, 2005 and beyond, thanks to better connectivity and newcomers in the PLM market, the solution landscape from PLM became broader.  CAD integrations were not a necessary part of the PLM scope according to these newcomers as they focused on governance (New Product Introduction), Bill of Materials or at the front-end of the product design cycle, connecting systems engineering by adding requirements management to their PLM suite.

New players in this domain where SAP, Aras, followed by Autodesk – their focus was more metadata-driven, connection and creating an end-to-end data flow for the product. Autodesk started the PLM and cloud path.

These new capabilities brought a broader scope for PLM indeed. However, they also strengthened the idea that PLM is there for engineers. For the management too complicated, unless they understood the value of coordinated collaboration. Large enterprises saw the benefits of having common processes for PLM as an essential reason to invest in PLM. The graph below showed the potential of PLM, where the shaded area indicates the potential revenue benefits.

Still, this graph does not create “hard numbers,” and it requires visionaries to get a PLM implementation explained and justified across the board.  PLM is framed as expensive even if the budgets spent on PLM are twenty percent or less compared to ERP implementations. As PLM is not about transactional data, the effects of PLM are hard to benchmark. Success has many fathers, and in case of difficulties, the newcomer is to blame.

PLM = IoT?

With the future possibilities, connectivity to the machine-level (IoT or IIoT), a new paradigm related to PLM was created by PTC.  PLM equals IoT – read more here.

Through IoT, it became possible to connect to products/assets in the field, and the simplified message from PTC was that now thanks to IoT (read ThingWorx) PLM was now really possible, releasing traditional PLM out of its engineering boundaries. The connected sensors created the possibility to build and implement more advanced and flexible manufacturing processes, often called Smart Manufacturing or Industrie 4.0.

None of the traditional PLM vendors is talking about PLM solely anymore. Digital transformation is a topic discussed at the board level, where GE played a visionary role with their strong message for change, driven by their CEO Jeff Immelt at that time – have a look at one of his energizing talks here.

However is PLM part of this discussion?

Digital Transformation opened a new world for everyone. Existing product lifecycle concepts could be changed, products are becoming systems, interacting with the environment realized through software features. Systems can be updated/upgraded relatively fast, in particular when you are able to watch and analyze the performance of your assets in almost real-time.

All consultants (me included) like to talk about digital transformation as it creates a positive mood towards the future, imagining everything that is possible. And with the elite of PLM consultants we are discovering the new roles of PLM – see picture below:

Is PLM equal to IoT or Digital Transformation?

I firmly believe the whole Digital Transformation and IoT hypes are unfortunately obfuscating the maximum needs for a digital enterprise. The IoT focus only exposes the last part of the lifecycle, disconnected from the concept and engineering cycles – yes on PowerPoint slides there might be a link. Re-framing PLM as Digital Transformation makes is even vaguer as we discussed during the CIMdata / PDT Europe conference last October. My main argument: Companies fail to have a link with their digital operations and dreams because current engineering processes and data, hardware (mechanical and electronics) combined with software are still operating in an analog, document-driven mode.

PLM = MBSE?

However what we also discussed during this conference was the fact that actually there is a need for an end-to-end model-based systems engineering infrastructure to support the full product lifecycle. Don Farr’s (Boeing) new way to depict the classical systems engineering “V” also hinted into that direction. See the image below – a connected environment between the virtual modeled word and the physical world at any time of the product lifecycle

So could MBSE be the new naming for PLM?

The problem is as Peter Bilello also mentioned during the CIMdata/PDT conference is that the word “ENGINEERING” is in Model-Based Systems Engineering. Therefore keeping the work what the PLM “elite” is doing again in the engineering box.

So perhaps Model-Based Enterprise as the new name?

Unfortunate MBE has already two current definitions – look here and here. Already too much confusion, and there a lot of people who like confusion. See Model-Based – The confusion. So any abbreviation with Model-Based terminology in it will not get attention at the board level. Even if it is crucial the words, Model-Based create less excitement as compared to Digital Twin, although the Digital Twin depends on a model-based approach.

Conclusion

Creating and maintaining unique products and experiences for their customers is the primary target of almost every company. However, no easy acronym that frames these aspects to value at the board level. Perhaps PID – the Product Innovation Diamond approach will be noticed? Your say ….

 

A week ago I attended the joined CIMdata Roadmap and PDT Europe conference in Stuttgart as you can recall from last week’s post: The weekend after CIMdata Roadmap / PDT Europe 2018. As there was so much information to share, I had to split the report into two posts. This time the focus on the PDT Europe. In general, the PDT conferences have always been focusing on sharing experiences and developments related to standards. A topic you will not see at PLM Vendor conferences. Therefore, your chance to learn and take part if you believe in standards.

This year’s theme: Collaboration in the Engineering and Manufacturing Supply Chain – the Extended Digital Thread and Smart Manufacturing. Industry 4.0 plays a significant role here.

 

Model-based X: What is it and what is the status?

I have seen Peter Bilello presenting this topic now several times, and every time there is a little more progress. The fact that there is still an acronym war illustrated that the various aspects of a model-based approach are not yet defined. Some critics will be stating that’s because we do not need model-based and it is only a vendor marketing trick again.  Two comments here:

  • If you want to implement an end-to-end model-based approach including your customers and supply chain, you cannot avoid standard. More will become clear when you read the rest of this post. Vendors will not promote standards as it reduces their capabilities to deliver unique So standards must come from the market, not from the marketing.
  • In 2007 Carl Bass, at that time CEO at Autodesk made his statement: “There are only three customers in the world that have a PLM problem; Dassault, PTC, and There are no other companies that say I have a PLM problem”. Have a look here. PLM is understood by now and even by Autodesk. The statement illustrates that in the beginning the PLM target was not clear and people thought PLM was a system instead of a strategic approach. Model-based ways of working have to go through the same learning path, hopefully, faster.

Peter’s presentation was a good walk-through pointing out what exists, where we focus and that there is still working to be done. Not by vendors but by companies. Therefore I wholeheartedly agree with Peter’s closing remarks – no time to sit back and watch if you want to benefit from model-based approaches.

Smart Manufacturing

Kenny Swope, known from his presentations related to Boeing, now spoke to us as the Chair of the ISO/TC 184/SC 4 workgroup related to Industrial Data. To say it in decoded mode: Kenny is heading Sub-committee 4 with a focus on Industrial Data. SC4 is part of a more prominent theme: Automation Systems and integration identified by TC 184 all as part of the ISO framework. The scope:

Standardization of the content, meaning, structure, representation and quality management of the information required to define an engineered product and its characteristics at any required level of detail at any part of its lifecycle from conception through disposal, together with the interfaces required to deliver and collect the information necessary to support any business or technical process or service related to that engineered product during its lifecycle.

Perhaps boring to read if you think about all the demos you have seen at trade shows related to Smart Manufacturing. If you want these demos to become true in a vendor-independent environment, you will need to agree on a common framework of definitions to ensure future continuity beyond the demo. And here lies the business excitement, the real competitive advantages companies can have implementing Smart Manufacturing in a Scaleable, future-oriented way.

One of the often heard statements is that standards are too slow or incomplete. Incomplete is not a problem when there is a need, the standard will follow. Compare it with language, we will always invent new words for new concepts.

Being slow might be the case in the past. Kenny showed the relative fast convergence from country-specific Smart Manufacturing standards into a joined ISO/IEC framework – all within three years. ISO and IEC have been teaming-up already to build Smart Manufacturing Reference models.

This is already a considerable effort,  as the local reference models need to be studied and mapped to a common architecture. The target is to have a first Technical Specification for a joint standard final 2020 – quite fast!

Meinolf Gröpper from the German VDMA  presented what they are doing to support Smart Manufacturing / Industrie 4.0. The VDMA is a well-known engineering federation with 3200 member companies, 85 % of them are Small and Medium Enterprises – the power of the German economy.

The VDMA provides networking capabilities, readiness assessments for members to be the enabler for companies to transform. As Meinolf stated Industrie 4.0 is not about technology, it is about cross-border services and international cooperation. A strategy that every company has to develop and if possible implement at its own pace. Standards will accelerate the implementation of Industrie 4.0

The Smart Manufacturing session was concluded by Gunilla Sivard, Professor at KTH in Stockholm and Hampus Wranér, Consultant at Eurostep. They presented the work done on the DIgln project, targeting an infrastructure for Smart Manufacturing.

The presentation showed the implementation of the testbed using twittering bus communication and the ISO 10303-239 PLCS information standard as the persistent layer. The results were promising to further build capabilities on top of the infrastructure below:

The conclusion from the Smart Manufacturing session was that emerging and available standards can accelerate the deployment.

 

Enabling digital continuity in the Factory of the Future

Alcibiades Gonzalez-Noval from Airbus shared challenges and the strategy for Airbus’s factory of the future based on digital continuity from the virtual world towards the physical world, connecting with PLM, ERP, and MOM. Concepts many companies are currently working on with various maturity stages.

I agree with his lessons learned. We cannot think in silos anymore in a digital future – everything is connected. And please forget the PoC, to gain time start piloting and fail or succeed fast. Companies have lost years because of just doing PoCs and not going into action. The last point, networks segregation for sure is an issue, relevant for plant operations. I experienced this also in the past when promoting PLM concepts for (nuclear) owners/operators of plants. Network security is for sure an issue to resolve.

 

Cross-Discipline Lifecycle Collaboration Forum
Setting up the digital thread across engineering and the value chain.

Peter Gerber, Chairman of CDLC Forum and Data Exchange & Integration Leader at Schaefller and Pierre Bodin at Senior Manager Mews Partners, presented their findings related to the challenge of managing complex products (mechanical, electrical, software using system engineering methodology)  to work properly at affordable cost in a real-time mode, multidisciplinary and coordination across the whole value chain. Something you might expect could be done when reviewing all PLM Vendor’s marketing materials, something you might expect hard to do when remembering Martin Eigner’s statement that 95 % of the companies have not solved mechatronics collaboration yet. (See: The weekend after CIMdata PLM Roadmap and PDT Europe)

A demonstrator was defined, and various vendors participated in building a demonstrator based on their Out-Of-The-Box capabilities. The result showed that for all participants there were still gaps to resolve for full collaboration. A new version of the demonstrator is now planned for the middle of next year – curious to learn the results at that time. Multi-disciplinary collaboration is a (conceptual) pillar for future digital business – it needs to be possible.

 

A Digital Thread based on the PLCS standard.

Nigel Shaw, Eurostep’s managing director in the UK, took us through his evolution of PLCS (Product Life Cycle Support) and extension of the ISO 10303 STEP standard. (STEP Standard for Exchange of Product data). Nigel mentioned how over all these years, millions (and a lot of brain power) have been invested in PLCS to where it is now.

PLCS has been extremely useful as an interface standard for contracting, provide product data in a neutral way. As an example, last year the Swedish Defense organization (FMV) and France’s DGA made PLCS DEXs as part of the contractual conditions. It would be too costly to have all product data for all defense systems in proprietary vendor formats and this over the product lifecycle.

Those following the standards in the process industry will rely on ISO 15926 / CFIHOS as this standard’s dictionary, and data model is more geared to process data- and in particular the exchange of data from the various contractors with the owner/operator.

Coming back to PLCS and the Digital Twin – it is all about digital continuity of information. Otherwise, if we have to recreate information in every lifecycle stage of a product (design/manufacturing / operations), it will be too costly and not digital connected. This illustrates the growing needs for standards. I had nothing to add to Nigel’s conclusions:

It is interesting to note that product management has moved a long way over the last 10-20 years however as we include more and more into PLM, there are all the time new concepts to be solved. The cases we discuss today in our PLM communities were most of the time visions 10 years ago. Nowadays we want to include Model-Based Systems Engineering, 3D Modeling and simulation, electronics and software and even aftermarket, product support in true PLM. This was not the case 20 years ago. The people involved in the development of PLCS were for sure visionaries as product data connectivity along the whole lifecycle is needed and enabled by the standard.

 

Investing in Industry 4.0?
Hard Realities of the Grand Vision.

Marc Halpern from Gartner is one of the regular speakers at the PDT conference. Unfortunate he could not be with us that day, however, through a labor-intensive connection (mobile phone close to the speaker and Nigel Shaw trying to stay in sync with the presented slides) we could hear Marc speak about what we wanted to achieve too – a digital continuity.

Marc restated the massive potential of Industrie 4.0 when it comes to scalability, agility, flexibility, and efficiency.

Although technologies are evolving rapidly, it is the existing legacy that inhibits fast adoption. A topic that was also central in my presentation. It is not just a change in technology, there is much more connected.

Marc recommends a changing role for IT, where they should focus more on business priorities and business leadership strategies. This as opposed to the classical role of the IT organization where IT needed to support the business, now they will be part of leading the business too.

To orchestrate such an IT evolution, Marc recommends a “systems of systems” planning and execution across IT and Business. One of my recent blog posts: Moving to a model-based enterprise:  The business (information) model can be seen in that context.

How to deal with the incompatible future?

I was happy to conclude the sessions with the topic that concerns me the most at this time. Companies in their current business are already struggling to get aligned and coordinated between disciplines and external stakeholders, the gap to be connected is vast as it requires a master data management approach, an enterprise data model and model-based ways of working. Read my posts from the past ½ year starting here, and you get the picture.

Note: This image is based on Marc Halpern’s (Gartner) Technology/Maturity diagram from PDT 2015

I concluded with explaining companies need to learn to work in two modes. One mode will be the traditional way of working which I call the coordinated approach and a growing focus on operating in a connected mode.  You can see my full presentation here on SlideShare: How to deal with the incompatible future.

Conclusion

The conference was closed with a panel discussion where we shared our concerns related to the challenges companies face to change their traditional ways of working meanwhile entering a digital era. The positive points are there – baby steps – PLM is becoming understood, the significance of standards is becoming more clear. The need: a long-term vision.

 This concludes my review of an excellent conference – I learned again a lot and I hope to see you next year too. Thanks again to CIMdata and Eurostep for organizing this event

 

 

 

 

 

 

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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