Model-Based – an introduction

March 26, 2018 in Change, Data centric, Digital Enterprise, PLM | Tags: , , , | 1 comment

The recent years I have been mentioning several times addressing the term model-based in the context of a modern, digital enterprise. Posts like: Digital PLM requires a model-based enterprise (Sept 2016) or Item-Centric or Model-Centric (Sept 2017) describe some of the aspects of a model-based approach. And if you follow the PLM vendors in their marketing messages, everyone seems to be looking for a model-based environment.

This is however in big contrast with reality in the field. In February this year I moderated a focus group related to PLM and the Model-Based approach and the main conclusion from the audience was that everyone was looking at it, and only a few started practicing. Therefore, I promised to provide some step-by-step education related to model-based as like PLM we need to get a grip on what it means and how it impacts your company. As I am not an academic person, it will be a little bit like model-based for dummies, however as model-based in all aspects is not yet a wide-spread common practice, we are all learning.

What is a Model?

The word Model has various meanings and this is often the first confusion when people speak about Model-Based. The two main interpretations in the context of PLM are:

  • A Model represents a 3D CAD Model – a virtual definition of a physical product
  • A Model represents a scientific / mathematical model

And although these are the two main interpretations there are more aspects to look at model-based in the context of a digital enterprise. Let’s explore the 3D CAD Model first

The role of the 3D CAD Model in a digital enterprise

Just designing a product in 3D and then generating 2D drawings for manufacturing is not really game-changing and bringing big benefits. 3D Models provide a better understanding of the product, mechanical simulations allow the engineer to discover clashes and/or conflicts and this approach will contribute to a better understanding of the form & fit of a product. Old generations of designers know how to read a 2D drawing and in their mind understand the 3D Model.

Modern generations of designers are no longer trained to start from 2D, so their way of thinking is related 3D modeling. Unfortunate businesses, in particular when acting in Eco-systems with suppliers, still rely on the 2D definition as the legal document.  The 3D Model has brought some quality improvements and these benefits already justify most of the companies to design in 3D, still it is not the revolution a model-based enterprise can bring.

A model-based enterprise has to rely on data, so the 3D Model should rely on parameters that allow other applications to read them. These parameters can contribute to simulation analysis and product optimization or they can contribute to manufacturing. In both cases the parameters provide data continuity between the various disciplines, eliminating the need to create new representations in different formats. I will come back in a future post to the requirements for the 3D CAD model in the context of the model-based enterprise, where I will zoom in on Model-Based Definition and the concepts of Industry 4.0.

The role of mathematical models in a digital enterprise

The mathematical model of a product allows companies to analyze and optimize the behavior of a product. When companies design a product they often start from a conceptual model and by running simulations they can optimize the product and define low-level requirements within a range that optimizes the product performance. The relation between design and simulation in a virtual model is crucial to be as efficient as possible. In the current ways of working, often design and simulation are not integrated and therefore the amount of simulations is relative low, as time-to-market is the key driver to introduce a new product.

In a digital enterprise, design and simulations are linked through parameters, allowing companies to iterate and select the optimal solution for the market quickly. This part is closely related to model-based systems engineering (MBSE) , where the focus is on defining complex systems. In the context of MBSE I will also zoom in on the relation between hardware and software, which at the end will deliver the desired functionality for the customer. Again in this part we will zoom in on the importance of having a parameter model, to ensure digital continuity.

Digital Twin

There is still a debate if the Digital Twin is part of PLM or should be connected to PLM. A digital twin can be based on a set of parameters that represent the product performance in the field. There is no need to have a 3D representation, despite the fact that many marketing videos always show a virtual image to visualize the twin.

Depending on the business desire, there can be various digital twins for the same products in the field, all depending on the parameters that you want to monitor. Again it is about passing parameters, in this case from the field back to R&D and these parameters should be passed in a digital manner. In a future post I will zoom in on the targets and benefits of the digital twin.

Conclusion

There are various aspects to consider related to “model-based”.  The common thread for each of the aspects is related to PARAMETERS.  The more you can work with parameters to connect the various usages of a product/system, the closer you are related to the digital enterprise. The real advantages of a digital enterprise are speed (information available in real-time), end-to-end visibility (as data is not locked in files / closed systems).

PARAMETERS the objects to create digital continuity

 

 

 

 

PLM and Silos

March 11, 2018 in Change, Data centric, Digital Enterprise, Observations, PLM | Tags: , , , | Leave a comment

When PLM – Product Lifecycle Management – was introduced, one of the main drivers was to provide an infrastructure for collaboration and for sharing product information across the whole lifecycle. The top picture shows my impression of what PLM could mean for an organization at that time. The PLM circle was showing a sequential process from concept, through planning, development, manufacturing towards after sales and/or services when relevant. PLM would provide centralization and continuity of data. Through this continuity we could break down the information silos in a company.

Why do we want to break down the silos?

You might ask yourself what is wrong with silos if they perform in a consistent matter? Oleg Shilovitsky recently wrote about it: How PLM can separate data and organization silos.  Read the post for the full details, I will stay at Oleg’s conclusion:

Keep process and organizational silos, but break data silos. This is should be a new mantra by new PLM organization in 21st century. How to help designers, manufacturing planners and support engineers to stay on the same BOM? By resolving this problem, organization will preserve current functional structure, but will make their decisions extremely data drive and efficient. The new role of PLM is to keep organizational and process silos, but connect data silos. This is a place where new cloud based multi-tenant technologies will play key role in the future organization transformation from the vision of no silo extended enterprise to organized functional silos connected by common understanding of data.

When I read this post I had so much to comment, which lead to this post. Let me share my thoughts related to this conclusion and hopefully it helps in future discussions. Feel free to join the discussion:

Keep process and organizational silos, but break data silos. This is should be a new mantra by new PLM organization in 21st century

For me “Keep process and organizational silos ….. “ is exactly the current state of classical PLM, where PLM concepts are implemented to provide data continuity within a siloed organization. When you can stay close to the existing processes the implementation becomes easier. Less business change needed and mainly a focus on efficiency gains by creating access to information.

Most companies do not want to build their data continuity themselves and therefore select and implement a PLM system that provides the data continuity, currently mainly around the various BOM-views. By selecting a PLM system, you have a lot of data integration done for you by the vendor. Perhaps not as user-friendly as every user would expect, however no company has been able to build a 100% user-friendly PLM system yet, which is the big challenge for all enterprise systems. Therefore PLM vendors provide a lot of data continuity for you without the need for your company to take responsibility for this.

And if you know SAP, they go even further. Their mantra is that when using SAP PLM, you even do not need to integrate with ERP.  You can still have long discussions with companies when it comes to PLM and ERP integrations.  The main complexity is not the technical interface but the agreement who is responsible for which data sets during the product lifecycle. This should be clarified even before you start talking about a technical implementation. SAP claims that this effort is not needed in their environment, however they just shift the problem more towards the CAD-side. Engineers do not feel comfortable with SAP PLM when engineering is driving the success of the company. It is like the Swiss knife; every tool is there but do you want to use it for your daily work?

In theory a company does not need to buy a PLM system. You could build your own PLM-system, based on existing infrastructure capabilities. CAD integrations might be trickier, however this you could solve by connecting to their native environments.  For example, Microsoft presented at several PDT conferences an end-to-end PLM story based on Microsoft technology.  Microsoft “talks PLM” during these conferences, but does not deliver a PLM-system – they deliver the technologies.

The real 21st-century paradigm

What is really needed for the 21st century is to break down the organizational silos as current ways of working are becoming less and less applicable to a modern enterprise. The usage of software has the major impact on how we can work in the future. Software does not follow the linear product process. Software comes with incremental deliveries all the time and yes the software requires still hardware to perform. Modern enterprises try to become agile, being able to react quickly to trends and innovation options to bring higher and different value to their customers.  Related to product innovation this means that the linear, sequential go-to-market process is too slow, requires too much data manipulation by non-value added activities.

All leading companies in the industry are learning to work in a more agile mode with multidisciplinary teams that work like startups. Find an incremental benefit, rapidly develop test and interact with the market and deliver it. These teams require real-time data coming from all stakeholders, therefore the need for data continuity. But also the need for data quality as there is no time to validate data all the time – too expensive – too slow.

Probably these teams will not collaborate along the various BOM-views, but more along digital models, both describing product specifications and system behavior. The BOM is not the best interface to share system information. The model-based enterprise with its various representations is more likely to be the backbone for the new future in the 21st century. I wrote about this several times, e.g. item-centric or model-centric.

And New cloud-based multi-tenant technologies …

As Oleg writes in his conclusion:

This is a place where new cloud-based multi-tenant technologies will play key role in the future organization transformation from the vision of no silo extended enterprise to organized functional silos connected by common understanding of data.

From the academic point of view, I see the beauty of new cloud-based multi-tenant technologies. Quickly build an environment that provides information for specific roles within the organization – however will this view be complete enough?  What about data dictionaries or is every integration a customization?

When talking with companies in the real world, they are not driven by technology – they are driven by processes. They do not like to break down the silos as it creates discomfort and the need for business transformation. And there is no clear answer at this moment. What is clear that leading companies invest in business change first before looking into the technology.

Conclusion

Sometimes too much academic and wishful thinking from technology providers is creating excitement.  Technology is not the biggest game changer for the 21st century. It will be the new ways of working and business models related to a digital enterprise that require breaking organizational silos. And these new processes will create the demand for new technologies, not the other way around.

Break down the walls !

The weekend after PLMx Hamburg 2018

February 25, 2018 in Data centric, Digital Enterprise, PLM | Tags: , , , | 1 comment

At the moment this post is published I have had time to digest the latest PLMx conference organized by MarketKey. See the agenda here. For me it was a conference with mixed feelings this time and I will share more details a little further on.

Networking during the conference was excellent, good quality of conversations, however the number of people attending was smaller than previous conferences, perhaps due to too much diversification in the PI conferences?

There were several inspiring sessions and as I participated in three sessions myself, I missed a lot of potential exciting sessions that were in parallel at the same time. I believe four parallel tracks is too much and downloading the presentations later does not give you the real story.  Now some of the notable sessions I attended:

Building a Better Urban Mobility Future

The first keynote session was meant to inspire us and think of solving issues differently. Lewis Horne from a Swedish automotive startup explained their different approach to designing an electrical vehicle. Not based on classical paradigms – you do not need a steering wheel – you can navigate differently. And switching the indicator on when going left or right is now a swipe. Of course these were not the only differences.

Unity will not certify for the highest safety classes like other vehicles as car safety rules are a lot based on mechanical / human handling and responses. A fully computerized and full of sensors has complete different dynamics. And a light city car does not ride on the high-speed way. Based on the first prototype there are already more than 1000 pre-orders but Unity does not have a manufacturing facility. This will be franchised. Unity used the Apple mode – focus on an unmatched user-experience instead of manufacturability. Let’s see what happens when the first Unity’s start riding – current target prices 20.000 Euro. Will it be the new hype for modern citizens?

Focus on quality – not on happy engineers

Not only the title of this paragraph but also other statements were made by Hilmer Brunn, head of global PLM from Mettler-Toledo related to their PLM implementation strategy.  As Hilmer stated:

We should not focus to give engineers more time to design only. The job of engineering is more comprehensive than just creating designs. Engineers also need to solve issues that are related to their design – not leave it to the others.

Another interesting statement:

As long as you do not connect simulation to your design in 3D, you are actually working with 3D as if you do it with 2D. The value of 3D is more than just representation of geometry.

And the last quote I want to share from Hilmer was again related to engineering.

Engineering should consider themselves as a service provider of information to the rest of the company, providing the full information associated with a design, instead of behaving like extreme, intelligent people who need more resources to translate and complete their work.

Grand statements although during Q&A it became clear that also Mettler-Toledo did not have the magic bullet to get an organization work integrated.

Working towards a Model-Based Enterprise with PLM

I consider Model-Based practices as one of the essential needs for future PLM as this approach reduces the amount of derived information related to a product/ system. And it provides a digital continuity. In the last PDT conference in Gothenburg this topic was shared on a quit extensive matter. Have a read to fresh-up your memory here:  The weekend after PDT Europe – part 1 and part 2

The focus group  which I moderated was with approximate 20 attendees and the majority was looking for getting a better understanding what model-based would mean for their organization. Therefore, the discussion was at the end more around areas where a few persons had the experience while others still tried to grasp the concepts. For me a point to take action related to education and in future posts I will go deeper into the basics.

PLMPulse Survey results and panel discussion

Nick Leeder presented the context of the PLMPulse survey and the results in a precise manner, where perhaps the result was not that surprising to the audience as many of us are involved in PLM. Two recurring points: PLM is still considered as an engineering tool and: The value related to PLM is most of the time not clear. You can register and download the full report from here.

Next Nick lead a panel discussion where people from the audience could participate.  And here we got into a negative spiral where it became an inward-looking discussion why PLM has never been able to show the value and get out of the engineering domain. It was a someone said like an anonymous PLM meeting where members stood up and confessed they were also part of the group that could not change this behavior.

Was it the time of the day? Was it the mood of the audience? Too much old experiences?  I believe it has to do with the fact that in PLM projects and conferences we focus too much on what we do and how we do things, not connecting it to tangible benefits that are recognized at the board level. And we will see an example later.

Solar Stratos

The food and drinks at the end of day 1 probably washed away the PLMPulse feedback session and Raphael Domjan inspired us with his SolarStratos project – a mission to develop a plane that can fly on solar energy on the heights of the stratosphere. Raphael is working hard with a team now to get there.

Designing an airplane, more a glider, that can take off en reach the stratosphere on solar energy requires solving a combination of so many different challenges. The first test flight reached an altitude of 500 m, but you can imagine challenges with the stratosphere – lack of oxygen / air pressure need to be solved. Raphael is looking for funding and you can find more details here. Back to the relative easy PLM challenges

The future of PLM Consultancy

Together with Oleg Shilovitsky we had a discussion related to the ways PLM could be realized in different manners thanks to changing technology. The dialogue started through our blogs – read it here. In this session there was a good dialogue with the audience and MarketKey promised to share the video recording of this session soon.  Stay tuned to Oleg’s blog or my blog and you can watch it.

PLM in the context of digitization

This was my main personal contribution to the conference. Sharing insights why we have to approach PLM in a different manner. Not the classical linear engineering approach but as a mix of system of record and system of engagement. You can see the full presentation on SlideShare here.

My main conclusions are that PLM consultants / experts focus too much on what and how they do PLM, where the connection to WHY is missing. (See also my post PLM WHY?).

In addition I defended the statement that old and new PLM are incompatible and therefore you need to accept they will exist both in your organization. For a while or for a long time, depending on your product lifecycle.  In order to reduce the gap between old and new PLM, there is a need for data governance, model-based ways of working, which allow the company to connect at some stages the old/record data and the new data. And don’t do pilots anymore experimenting new ways of working and then stop because the next step seems to be overwhelming. Start your projects in small, multidisciplinary teams and make them real. The only way to be faster in the future.

PLM in Manufacturing as Backbone of the Smart Factory

Susanne Lauda, Director, Global Advanced Manufacturing Technology, AGCO Corporation provided an overview related to AGCO’s new PLM journey and how they were benefiting from a digital thread towards manufacturing. It felt like a smooth vendor demo as everything looked nice and reasonable. It was all about the WHAT. However two points that brought the extra:

When moving to the new system the tried to bring in the data from an existing product into then new system. According to Susanne a waste of time as the data required so much rework – there was no real value added for that. This confirms again my statement that old and new PLM are incompatible and one should not try to unify everything again in one system.

Second, I got excited at the end when we discussed the WHY for PLM and the business value of PLM. Here Suzanne mentioned PLM started as a “must-do strategic” project.  PLM lead to a reduction of time to market with almost 50 %. Suzanne did not give exact number, but you can imagine I have heard these numbers from other companies too. Why aren’t we able to connect these benefits in the mindset of the management to PLM ? Perhaps still too much engineering focused.

Next Susanne explained that they investigated the cost for quality for their manufacturing plants. What if something was produced wrong, the wrong parts were ordered, the delays to fix it, the changes needed to be made on the shop floor?  These results were so high that people were even afraid to report them. This is the case at many companies I worked with – even their PLM consultants do not receive these numbers – you just have to imagine they are big.

At AGCO they were able to reduce the cost for quality in a significant manner and Susanne explain that PLM was a main contributor to that success. However, success always has many fathers – so if your PLM team does not claim loud (and we are modest people not used to talk finance) – the success will not be recognized.

PLM’s Place Within an Enterprise Application Architecture

Peter Bilello from CIMData in the closing keynote speech gave an excellent summary and overview of where and which capabilities fit in an enterprise architecture and the positioning of a product innovation platform. A blueprint that can be used for companies to grasp the holistic view before jumping into the details of the tools.

Conclusion

PLMx Hamburg 2018 was an event with valuable highlights for me and potential I missed several more due to the fact of parallel streams. I hope to catch-up with these sessions in the upcoming month and share interesting thoughts that I discover with you. What remains crucial I believe for all vendor-neutral events is to find new blood. New companies, new experiences that are focused on the future of PLM and connect to the WHY or the WHAT WE LEARNED values.

PLM WHY?

February 11, 2018 in Customer centric, Observations, PLM, ROI on PLM | Tags: , , | Leave a comment

Perhaps an ambiguous title this time as it can be interpreted in various ways. I think that all these interpretations are one of the most significant problems with PLM. Ambiguity everywhere. Its definition, its value and as you might have noticed from the past two blog posts the required skill-set for PLM consultants.

As I am fine-tuning my presentation for the upcoming PLMx 2018 Event in Hamburg, some things become clearer for me. This is one of the advantages of blogging, speaking at PLM conferences and discussing PLM with companies that are eager to choose to right track for PLM. You are forced to look in more depth to be consistent and need to have arguments to support your opinion about what is happening in the scope of PLM. And from these learnings I realize often that the WHY PLM remains a big challenge for various reasons.

Current PLM

In the past twenty years, companies have implemented PLM systems, where the primary focus was on the P (Product) only from Product Lifecycle Management. PLM systems have been implemented as an engineering tool, as an evolution of (Product Data Management).

PLM systems have never been designed from the start as an enterprise system. Their core capabilities are related to engineering processes and for that reason that is why most implementations start with engineering.  Later more data-driven PLM-systems like Aras and Autodesk have begun from another angle, data connectivity between different disciplines as a foundation, avoiding to get involved with the difficulty of engineering first.

This week I saw the publication of the PLMPulse survey results by i42R / MarketKey where they claim:

The results from first industry-led survey on our status of Product Lifecycle Management and future priorities

The PLMPulse report is based on five different surveys as shown in the image above. Understanding the various aspects of PLM from usage, business value, organizational constraints, information value and future potential. More than 350 people from all around the world answered the various questions related to these survey.  Unfortunate inputs from some Asian companies are missing. We are all curious what happens in China as there, companies do not struggle with the same legacy related to PLM as other countries. Are they more embracing PLM in a different way?

The results as the editors also confirm, are not shocking and confirming that PLM has the challenge to get out of the engineering domain. Still, I recommend downloading the survey as it has interesting details. After registration you can download the report from here.

What’s next

During the upcoming PLMx 2018 Hamburg conference there will be a panel discussion where the survey results will be discussed. I am afraid that this debate will result again in a discussion where we will talk about the beauty and necessity of PLM and we wonder why PLM is not considered crucial for the enterprise.

There are a few challenges I see for PLM and hopefully they will be addressed. Most discussions are about WHAT PLM should/could do and not WHY.  If you want to get to the WHY of PLM, you need to be able to connect the value of PLM to business outcomes that resonate at C-level. Often PLM implementations are considered costly and ROI and business value are vague.

As the PLMPulse report also states, the ROI for PLM is most of the time based on efficiency and cost benefits related to the current way of working. These benefits usually do not offer significant ROI numbers. Major benefits come for working in a different way and focusing on working closer to your customer. Business value is hard to measure.

How do you measure the value of multidisciplinary collaboration or being more customer-centric? What is the value of being better connected to your customer and being able to react faster? These situations are hard to prove at the board level, as here people like to see numbers, not business transformations.

Focus on the WHY and HOW

A lot of the PLM messages that you can read through various marketing or social channels are related to futuristic concepts and high-level dreams that will come true in the next 10-20 years. Most companies however have a planning horizon of 2 years max 5 years. Peter Bilello from CIMdata presented one of their survey results at the PDT conference in 2014, shown below:

Technology and vision are way ahead of reality. Even the area where the leaders focusing the distance between technology and vision gets bigger. The PLM focus is more down-to-earth and should not be on what we are able to do, but the focus should be on what would be the next logical step for our company to progress to the future.

System of Record and System of Engagement

At the PLMx conference I will share my experiences related to PLM transformations with the audience. One and a half-year ago we started talking about the bi-modal approach. Now more and more I see companies adopting the concepts of bi-modal related to PLM.  Still most organizations struggle with the fact that their PLM should be related to one PLM system or one PLM vendor, where I believe we should come to the conclusion that there are two PLM modes at this moment. And this does not imply there need to be only one or two systems – it will become a federated infrastructure.

Current modes could be an existing PLM backbone, focusing on capturing engineering data, the classical PLM system serving as a system of record. And a second, new growing PLM-related infrastructure which will be a digital, most likely federated, platform where modern customer-centric PLM processes will run. As the digital platform will provide real-time interaction it might be considered as a system of engagement, complementary to the system of record.

It will be the system of engagement that should excite the board members as here new ways of working can be introduced and mastered. As there are no precise blueprints for this approach, this is the domain where innovative thinking needs to take place.

That’s why I hope that neutral PLM conferences will less focus on WHAT can be done. Discussions like MBSE, Digital Thread, Digital Twin, Virtual Reality / Augmented Reality are all beautiful to watch. However, let’s focus first on WHY and HOW. For me besides the PLMx Hamburg conference, other upcoming events like PDT 2018 (this time in the US and Europe) are interesting events and currently PDT the call for papers is open and hopefully we  find speakers that can teach and inspire.

CIMdata together with Eurostep are organizing these events in May (US) and October (Europe). The theme for the CIMdata roadmap conference will be “Charting the Course to PLM Value together – Expanding the value footprint of PLM and Tackling PLM’s Persistent Pain Points” where PDT will focus on Collaboration in the Engineering Supply Chain – the extended digital thread.  These themes need to be addressed first before jumping into the future. Looking forward to meeting you there.

 

Conclusions

In the world of PLM, we are most of the time busy with explaining WHAT we (can/will) do. Like a cult group sometimes we do not understand why others do not see the value or beauty of our PLM concepts. PLM dialogues and conferences should therefore focus more on WHY and HOW. Don’t worry, the PLM vendors/implementers will always help you with WHAT they can do and WHY it is different.

 

PLM Consultants are still alive and have an exit strategy

January 28, 2018 in Change, Data centric, Digital Enterprise, Observations, PLM | Tags: , , , | Leave a comment

If you have followed my blog over the past 10 years, I hope you realize that I am always trying to bring sense to the nonsense and still looking into the future where new opportunities are imagined. Perhaps due to my Dutch background (our motto: try to be normal – do not stand out) and the influence of working with Israeli’s (a country where almost everyone is a startup).

Given this background, I enjoy the current discussion with Oleg Shilovitsky related to potential PLM disruptions. We worked for many years together at SmarTeam, a PDM/PLM disruptor at that time, in the previous century. Oleg has continued his passion for introducing potential disruptive solutions  (Inforbix / OpenBOM) where I got more and more intrigued by human behavior related to PLM. For that reason, I have the human brain in my logo.

Recently we started our “The death of ….” Dialogue, with the following episodes:

Jan 14th – How to democratize PLM knowledge and disrupt traditional consulting experience

Jan 21st – The death of PLM Consultancy

Jan 22nd – Why PLM consultants are questioning new tools and asking about cloud exit strategy?

Here is episode 4  – PLM Consultants are still alive and have an exit strategy

Where we agree

We agreed on the fact that traditional consultancy practices related to PLM ranking and selection processes are out of time. The Forester Wave publication was the cause of our discussion. For two reasons:

  1. All major PLM systems cover for 80 percent the same functionalities. Therefore there is no need to build, send and evaluate lengthy requirements lists to all potential candidates and then recommend on the preferred vendor. Waste of time as the besides the requirements there is much more to evaluate than just performing tool selection.
  2. Many major consultancy firms have PLM practices, most of the time related to the major PLM providers. Selecting one of the major vendors is usually not a problem for your reputation, therefore the importance of these rankings. Consultancy firms will almost never recommend disruptive tool-sets.

PLM businesses transformation

At this point, we are communicating at a different wavelength. Oleg talks about PLM business transformation as follows:

Cloud is transforming PLM business. Large on-premise PLM projects require large capital budget. It is a very good foundation for existing PLM consulting business. SaaS subscription is a new business model and it can be disruptive for lucrative consulting deals. Usually, you can see a lot of resistance when somebody is disrupting your business models. We’ve seen it in many places and industries. It happened with advertising, telecom and transportation. The time is coming to change PLM, engineering and manufacturing software and business.

I consider new business models less relevant compared to the need for a PLM practice transformation. Tools like Dropbox, perhaps disruptive for PDM systems, are tools that implement previous century methodology (document-driven / file-based models). We are moving from item-centric towards a model-driven future.

The current level of PLM practices is related to an item-centric approach, the domain where also OpenBOM is bringing disruption.
The future, however, is about managing complex products, where products are actually systems, a combination of hardware and software. Hardware and software have a complete different lifecycle, and all major PLM vendors are discovering an overall solution concept to incorporate both hardware and software. If you cannot manage software in the context of hardware in the future, you are at risk.  Each PLM vendor has a different focus area due to their technology history. I will address this topic during the upcoming PLMx conference in Hamburg. For a model-driven enterprise, I do not see an existing working combination of disruptors yet.

Cloud security and Cloud exit strategy

Oleg does not really see the impact of the cloud as related to the potential death of PLM consulting as you can read here:

I agree, cloud might be still not for everyone. But the adoption of cloud is growing and it is becoming a viable business model and technology for many companies. I wonder how “cloud” problem is related to the discussion about the death of PLM consulting. And…  here is my take on this. It is all about business model transformation.

I am not convinced that in the PLM cloud is the only viable business model. Imagine an on-premise rigid PLM system. Part of the cloud-based implementation benefits come from low upfront costs and scalable IT. However, cloud also pushes companies to defend a no-customization strategy – configuration of the user interface only.  This is a “secret” benefit for cloud PLM vendors as they can say “NO” to the end users of course within given usability constraints. Saying “NO” to the customer is lesson one for every current PLM implementation as everyone knows the problem of costly upgrades later

Also, make a 5-10 years cost evaluation of your solution and take the risk of raising subscription fees into account. No vendor will drop the price unless forced by the outside world. The initial benefits will be paid back later because of the other business model.

Cloud exit strategy and standards

When you make a PLM assessment, and usually experienced PLM consultants do this, there is a need to consider an exit strategy. What happens if your current PLM cloud vendor(s) stops to exist or migrate to a new generation of technology and data-modeling? Every time when new technology was introduced, we thought it was going to be THE future. The future is unpredictable. However, I can predict that in 10 years from now we live with different PLM concepts.

There will be changes and migrations and cloud PLM vendors will never promote standardized exports methods (unless forced) to liberate the data in the system. Export tools could be a niche market for PLM partners, who understand data standards. Håkan Kårdén, no finders fee required, however, Eurostep has the experience in-house.

 

Free downloads – low barriers to start

A significant difference in opinion between Oleg and me is Oleg’s belief in bottom-up, DIY PLM as part of PLM democratization and my belief in top-down business transformation supported by PLM. When talking about Aras, Autodesk, and OpenBOM,  Oleg states:

All these tools have one thing in common. You can get the tool or cloud services for free and try it by yourself before buying. You can do it with Aras Innovator, which can be downloaded for free using enterprise open source. You can subscribe for Autodesk Fusion Lifecycle and OpenBOM for trial and free subscriptions. It is different from traditional on-premise PLM tools provided by big PLM players. These tools require months and sometimes even years of planning and implementation including business consulting and services.

My experience with SmarTeam might influence this discussion. SmarTeam was also a disruptive PDM solution thanks to its easy data-modeling and Microsoft-based customization capabilities like Aras. Customers and implementers could build what they want, you only needed to know Visual Basic. As I have supported the field mitigating installed SmarTeam implementations, often the problem was SmarTeam has been implemented as a system replicating/automating current practices.

Here Henry Ford’s statement as shown below applies:

Implementations became troublesome when SmarTeam provided new and similar business logic. Customers needed to decide to use OOTB features and de-customize or not benefits from new standard capabilities. SmarTeam had an excellent business model for service providers and IT-hobbyists/professionals in companies. Upgrade-able SmarTeam implementations where those that remained close to the core, but meanwhile we were 5 – 8 years further down the line.

I believe we still need consultants to help companies to tell and coach them towards new ways of working related to the current digitization. Twenty years old concepts won’t work anymore. Consultants need a digital mindset and think holistic. Fitting technology and tools will be there in the future.

Conclusion

The discussion is not over, and as I reached already more than 1000 words, I will stop. Too many words already for a modern pitch, not enough for a balanced debate. Oleg and I will continue in Hamburg, and we both hope others will chime in, providing balanced insights in this discussion.

To be continued …..?

 

The death of PLM consultancy?

January 21, 2018 in Digital Enterprise, PLM | Tags: , , | 3 comments

In my earlier post; PLM 2018 my focus, your input, I invited you to send PLM related questions that would spark of a dialogue. As by coincidence Oleg Shilovitsky wrote a post with the catchy title: Why traditional PLM ranking is dead. PLM ranking 2.0. Read this post and the comments if you want to follow this dialogue.

Oleg reacts in this post on the discussion that had started around the Forester Wave ranking PLM Vendors, which on its own is a challenging topic. I know from my experience that these rankings depend very much on a mix of functions and features, but also are profoundly influenced by the slideware and marketing power of these PLM Vendors. Oleg also quotes Joe Barkai’s post: ranking PLM Vendors to illustrate that this kind of ranking does not bring a lot of value as there is so much commonality between these systems.

I agree with Oleg and Joe. PLM ranking does not make sense for companies to select a PLM solution. They are more an internal PLM show, useful for the organizing consultancy companies to conduct, but at the end, it is a discussion about who has the biggest and most effective button. Companies need to sell themselves and differentiate.

Do we need consultancy?

We started a dialogue on the comments of Oleg’s blog post where I mentioned that PLM is not about selecting a solution from a vendor, there are many other facets related to a PLM implementation. First of all, the industry your company is active in. No solution fits all industries.

But before selecting a solution, you first need to understand what does a company want to achieve in the future. What is the business strategy and how can PLM support this business strategy?

In most cases, a strategy is future-oriented and not about consolidating the current status quo. Therefore I believe a PLM implementation is always done in the context of a business transformation, which is most of the time not only related to PLM – it is about People, Processes and then the tools.

Oleg suggests that this complexity is created by the consulting business, as he writes:

Complex business and product strategies are good for consulting business you do. High level of complexity with high risk of failure for expensive PLM projects is a perfect business environment to sell consulting. First create complexity and then hire consulting people to explain how to organize processes and build business and product strategy. Win-win

Enterprise and engineering IT are hiring consulting to cover their decision process. That was a great point made by Joe Barkai- companies are buying roadmaps and long-term commitments, but rarely technologies. Technologies can be developed, and if even something is missed, you can always acquire independent vendors or technology later – it was done many times by many large ISVs in the past.

Here I agree with a part of the comments. If you hire consultancy firms just for the decision process, it does not make sense/ The decision process needs to be owned by the company. Do not let a consultancy company prescribe your (PLM) strategy as there might be mixed interests. However, when it comes to technologies, they are derived from the people and process needs.

So when I write in the comment:

We will not change the current status quo and ranking processes very soon. Technology is an enabler, but you need a top-down push to work different (at least for those organizations that read vendor rankings).

Oleg states:

However, the favorite part of your comments is this – “We will not change the current status quo and ranking processes very soon.” Who are “we”???? Management consulting people?

With “we” I do not mean the consulting people. In general, the management of companies is more conservative than consultants are. It is our human brain that is change averse and pushes people to stay in a kind of mainstream mode. In that context, the McKinsey article: How biases, politics, and egos derail business decisions is a fascinating read about company dynamics. Also, CIMdata published in the past a slide illustrating the gap between vision, real capabilities and where companies really are aiming at.

There is such a big gap between where companies are and what it possible. Software vendors describe the ideal world but do not have a migration path. One of the uncomfortable discussions is when discussing a cloud solution is not necessary security (topic #1) but what is your exit strategy? Have you ever thought about your data in a cloud solution and the vendor raises prices or does no longer have a viable business model. These are discussions that need to take place too.

Oleg also quotes a CIMdata cloud PLM research how companies are looking for solutions as they are “empowered” by the digital world. Oleg states:

In a digital world, companies are checking websites, technologies, watching YouTube and tried products available online. Recent cloud PLM research published by CIMdata tells that when companies are thinking about cloud PLM, the first check they do is independent software providers recommendations and websites (not business process consultants).

I am wondering the value of this graph. The first choice is independent software recommendations/websites.  Have you ever seen independent software recommendations?

Yes, when it comes to consumer tools. “I like software A because it gives me the freedom what to do” or “Software B has so many features for such a low price – great price/value ratio.”

These are the kind of reviews you find on the internet for consumers. Don’t try to find answers on a vendor website as there you will get no details, only the marketing messages.

I understand that software vendors, including Oleg’s company OpenBOM, needs to differentiate by explaining that the others are too complex. It is the same message you hear from all the relative PLM newcomers, Aras, Autodesk, …….

All these newcomers provide marketing stories and claim successes because of their tools, where reality is the tool is secondary to the success. First, you need the company to have a vision and a culture that matches this tool. Look at an old Gartner picture (the hockey stick projection) when all is aligned. The impact of the tool is minimal.

Conclusion

Despite democratization of information, PLM transformations will still need consultants or a well-educated workforce inside your company. Consultants have the advantage of collected experience, which often is not the case when you work inside a company. We should all agree that at the end it is about the business first (human beings are complex) and then the tools (here you can shop on the internet what matches the vision)

Although this post seems like ping-pong match of arguments, I challenge you to take part of this discussion. Tell us where you agree or disagree combined with argumentation as we should realize the argumentation is the most valuable point.
Your thoughts?

PLM 2018 – my focus, your input?

January 7, 2018 in Change, Digital Enterprise, Observations, PLM | Tags: , , , , | Leave a comment

Happy New Year to all of you. A new year comes traditionally with good intentions for the upcoming year.  I would like to share my PLM intentions for this year with you and look forward to your opinion. I shared some of my 2017 thoughts in my earlier post: Time for a Break. This year will I focus on the future of PLM in a digital enterprise, current PLM practices and how to be ready for the future.

Related to these activities I will zoom in on people-related topics, like organizational change, business impact and PLM justification in an enterprise. When it happens during the year, or based on your demands, I will zoom in on architectural stuff and best practices.

The future of PLM

Accenture – Digital PLM

At this moment digital transformation is on the top of the hype curve and the impact varies of course per industry. For sure at the company’s C-level managers will be convinced they have the right vision and the company is on the path to success.

Statements like: “We will be the first digital industrial enterprise” or “We are now a software company” impress the outside world and often investors in the beginning.

 

Combined with investments in customer related software platforms a new digital world is relative fast created facing the outside world.  And small pilots are celebrated as significant successes.

What we do not see is that to show and reap the benefits of digital transformation companies need to do more than create a modern, outside facing infrastructure. We need to be able to connect and improve the internal data flow in an efficient way to stay competitive. Buzzwords like digital thread and digital twin are relevant here.

To my understanding we are still in the early phases of discovering the ideal architecture and practices for a digital enterprise. PLM Vendors and technology companies show us the impressive potential as-if the future already exists already now. Have a reality check from Marc Halpern (Gartner) in this article on engineering.com – Digital Twins: Beware of Naive Faith in Simplicity.

I will focus this year on future PLM combined with reality, hopefully with your support for real cases.

Current PLM practices

Although my curiosity is focused on future PLM, there is still a journey to go for companies that have just started with PLM.  Before even thinking of a digital enterprise, there is first a need to understand and implement PLM as an infrastructure outside the engineering department.

Many existing PLM implementations are actually more (complex) document management systems supporting engineering data, instead of using all available capabilities of a modern PLM systems. Topics like Systems Engineering, multidisciplinary collaboration, Model-Based Enterprise, EBOM-MBOM handling, non-intelligent numbering are all relevant for current and future PLM.

Not exploring and understanding them in your current business will make the gap towards the future even bigger. Therefore, keep on sending your questions and when time allows I will elaborate. For example, see last year’s PLM dialogue – you find these posts here: PLM dialogue and PLM dialogue (continued). Of course I will share my observations in this domain too when I bump into them.

 

To be ready for the future

The most prominent challenge for most companies however is how to transform their existing business towards a modern digital business where new processes and business opportunities need to be implemented inside an existing enterprise. These new processes and business opportunities are not just simple extensions of the current activities, they need new ways of working like delivering incremental results through agile and multidisciplinary teams. And these ways of working combined with never-existing-before interactivity with the market and the customer.

How to convince management that these changes are needed and do not happen without their firm support? It is easier to do nothing and push for small incremental changes. But will this be fast enough? Probably not as you can read from research done by strategic consultancy firms. There is a lot of valuable information available if you invest time in research. But spending time is a challenge for management.

I hope to focus on these challenges too, as all my clients are facing these challenges. Will I be able to help them? I will share successes and pitfalls with you, combined supporting information that might be relevant for others

Your input?

A blog is a modern way of communicating with anyone connected in the world. What I would like to achieve this year is to be more interactive. Share your questions – there are no stupid questions as we are all learning. By sharing and learning we should be able to make achievable steps and become PLM winners.

Best wishes to us all and be a winner not a tweeter …..

 

 

Time for a break

December 24, 2017 in Change, Data centric, Digital Enterprise, Innovation | Tags: , , , | 2 comments

Dear readers, it is time for me to relax and focus on Christmas and a New Year upcoming. I realize that not everyone who reads my posts will be in the same mood. You might have had your New Year three months ago or have New Year coming up in a few months. This is the beauty and challenge of a global, multicultural diverse society. Imagine we are all doing the same, would you prefer such a world ? Perhaps it would give peace to the mind (no surprises, everything predictable) however for human survival we need innovation and new ways of life.

This mindset is also applicable to manufacturing companies. Where in the past companies were trying to optimize and standardize their processes driven by efficiency and predictability, now due to the dynamics of a globally connected world, businesses need to become extremely flexible however still reliable and profitable.

How will they make the change ?

Digital transformation is one of the buzz words pointing to the transition process. Companies need to go through a change to become flexible for the future and deliver products or solutions for the individual customer. Currently companies invest in digital transformation, most of the time in areas that bring direct visibility to the outside world or their own management, not necessarily delivering profitable results as a recent article from McKinsey illustrated: The case for digital reinvention.

And for PLM ?

I have investigated digital transformation in relation to PLM  with particular interest this year as I worked with several companies that preached to the outside world that they are changing or were going to make a change. However what is happening at the PLM level ? Most of the time nothing. Some new tools, perhaps some new disciplines like software engineering become more critical. However the organization and people do not change their ways of working as in particular the ongoing business and related legacy are blocking the change.

Change to ?

This is another difficult question to answer.  There is no clearly defined path to share. Yes, modern PLM will be digital PLM, it will be about data-driven connected information. A final blueprint for digital PLM does not exist yet. We are all learning and guessing.  You can read my thoughts here:

Software vendors in various domains are all contributing to support a modern digital product innovation management future. But where to start?  Is it the product innovation platform? Is it about federated solutions? Model-Based? Graph-databases? There are even people who want to define the future of PLM.  We can keep throwing pieces of the puzzle on the table, but all these pieces will not lead to a single solved puzzle. There will be different approaches based on your industry and your customers. Therefore, continuous learning and investing time to understand the digital future is crucial. This year’s PDT Europe conference was an excellent event to learn and discuss the themes around a model-based lifecycle enterprise. You can read my reviews here: The weekend after PDT Europe 2017 part 1 and part 2.

The next major event where I plan to discuss and learn about modern PLM topics is the upcoming PI PLMx event in Hamburg on February 19-20 organized by MarketKey. Here I will discuss the Model-Based Enterprise and lecture about the relation between PLM and digital transformation. Hoping to see some of you there for exciting discussions and actions.

Conclusion

Merry Christmas for those who are celebrating and a happy, healthy and prosperous 2018 to all of you. Thanks for your feedback. Keep on asking questions or propose other thoughts as we are all learning. The world keeps on turning, however for me the next two weeks will the time relax.

Talk to you in 2018 !

 

Intelligent Part or Product Numbers?

December 10, 2017 in Customer centric, Digital Enterprise, ERP, Observations, PLM | Tags: , | 2 comments

 

For those who have followed my blog over the years, it must be clear that I am advocating for a digital enterprise explaining benefits of a data-driven approach where possible. In the past month an old topic with new insights came to my attention: Yes or No intelligent Part Numbers or do we mean Product Numbers?

 

 

What’s the difference between a Part and a Product?

In a PLM data model, you need to have support for both Parts and Products and there is a significant difference between these two types of business objects. A Product is an object facing the outside world, which can be a company (B2B) or customer (B2C) related. Examples of B2C products are the Apple iPhone 8, the famous IKEA Billy, or my Garmin 810 and my Dell OptiPlex 3050 MFXX8.  Examples of B2B products are the ABB synchronous motor AMZ 2500, the FESTO standard cylinder DSBG.  Products have a name and if there are variants of the product, they also have an additional identifier.

A Part represents a physical object that can be purchased or manufactured. A combination of Parts appears in a BOM. In case these Parts are not yet resolved for manufacturing, this BOM might be the Engineering BOM or a generic Manufacturing BOM. In case the Parts are resolved for a specific manufacturing plant, we talk about the MBOM.

I have discussed the relation between Parts and Products in a earlier post Products, BOMs and Parts which was a follow-up on my LinkedIn post, the importance of a PLM data model. Although both posts were written more than two years ago, the content is still valid. In the upcoming year, I will address this topic of products further, including software and services moving to solutions / experiences.

Intelligent number for Parts?

As parts are company internal business objects, I would like to state if the company is serious about becoming a digital enterprise, parts should have meaningless unique identifiers. Unique identifiers are the link between discipline or application specific data sets. For example, in the image below, where I imagined attributes sets for a part, based on engineering and manufacturing data sets.

Apart from the unique ID, there might be a common set of attributes that will be exposed in every connected system. For example, a description, a classification and one or more status attributes might be needed.

Note 1: A revision number is not needed when you create every time a new unique ID for a new version of the part.  This practice is already common in the electronics industry. In the old mechanical domain, we are used to having revisions in particular for make parts based on Form-Fit-Function rules.

Note 2: The description might be generated automatically based on a concatenation of some key attributes.

Of course if you are aiming for a full digital enterprise, and I think you should, do not waste time fixing the past. In some situations, I learned that an external consultant recommended the company to rename their old meaningful part numbers to the new non-intelligent part numbering scheme. There are two mistakes here. Renumbering is too costly, as all referenced information should be updated. And secondly as long as the old part numbers have a unique ID for the enterprise, there is no need to change. The connectivity of information should not depend on how the unique ID is formatted.

Read more if you want here: The impact of Non-Intelligent Part Numbers

Intelligent numbers for Products?

If the world was 100 % digital and connected, we could work with non-intelligent product numbers. However, this is a stage beyond my current imagination.  For products we will still need a number that allows customers to refer to, for when they communicate with their supplier / vendor or service provider. For many high-tech products the product name and type might be enough. When I talk about the Samsung S5 G900F 16G, the vendor knows which kind of configuration I am referring too. Still it is important to realize that behind these specifications, different MBOMs might exist due to different manufacturing locations or times.

However, when I refer to the IKEA Billy, there are too many options to easily describe the right one consistent in words, therefore you will find a part number on the website, e.g. 002.638.50. This unique ID connects directly to a single sell-able configuration. Here behind this unique ID also different MBOMs might exist for the same reason as for the Samsung telephone. The number is a connection to the sales configuration and should not be too complicated as people need to be able to read and recognize it when you go to a warehouse.

Conclusion

There is a big difference between Product and Part numbers because of the intended scope of these business objects. Parts will soon exist in connected, digital enterprises and therefore do not need any meaningful number anymore. Products need to be identified by consumers anywhere around the world, not yet able or willing to have a digital connection with their vendors. Therefore smaller and understandable numbers will remain needed to support exact communication between consumer and vendor.

The emerging role of a Product Manager

November 26, 2017 in Change, Customer centric, Data centric, Digital Enterprise, Observations, PLM | Tags: , , , , | 1 comment

When I started working with SmarTeam Corp.  in 1999, the company had several product managers, who were responsible for the whole lifecycle of a component or technology. The Product Manager was the person to define the features for the new release and provide the justification for these new features internally inside R&D.  In addition the Product Manager had the external role to visit customers and understand their needs for future releases and building and explaining a coherent vision to the outside and internal world. The product manager had a central role, connecting all stakeholders.

In the ideal situation the Product Manager was THE person who could speak in R&D-language about the implementation of features, could talk with marketing and documentation teams to explain the value and expected behavior and could talk with the customer describing the vision, meanwhile verifying the product’s vision and roadmap based on their inputs.All these expected skills make the role of a product manager challenging. Is the person too “techy” than he/she will enjoy working with R&D but have a hard time understanding customer demands. From the other side if the Product Manager is excellent in picking-up customer and market feedback he/she might not be heard and get the expected priorities from R&D. For me, it has always been clear that in software world a “bi-directional” Product Manager is crucial to success.

Where are the Product Managers in the Manufacturing Industry?

Approximate four years ago new concepts related to digitalization for PLM became more evident. How could a digital continuity connect the various disciplines around the product lifecycle and therefore provide end-to-end visibility and traceability? When speaking of end-to-end visibility most of the time companies talked about the way they designed and delivered products, visibility of what is happening stopped most of the time after manufacturing. The diagram to the left, showing a typical Build To Order organization illustrates the classical way of thinking. There is an R&D team working on Innovation, typically a few engineers and most of the engineers are working in Sales Engineering and Manufacturing Preparation to define and deliver a customer specific order. In theory, once delivered none of the engineers will be further involved, and it is up to the Service Department to react to what is happening in the field.

A classical process in the PLM domain is the New Product Introduction process for companies that deliver products in large volumes to the market, most of the time configurable to be able to answer to various customer or pricing segments. This process is most of the time linear and is either described in one stream or two parallel streams. In the last case, the R&D department develops new concepts and prepares the full product for the market. However, the operational department starts in parallel, initially involved in strategic sourcing, and later scaling-up manufacturing disconnected from R&D.

I described these two processes because they both illustrate how disconnected the source (R&D/ Sales)  are from the final result in the field. In both cases managed by the service department. A typical story that I learned from many manufacturing companies is that at the end it is hard to get a full picture from what is happening across the whole lifecycle, How external feedback (market & customers) have the option to influence at any stage is undefined. I used the diagram below even  before companies were even talking about a customer-driven digital transformation. Just understanding end-to-end what is happening with a product along the lifecycle is already a challenge for a company.

Putting the customer at the center

Modern business is about having customer or market involvement in the whole lifecycle of the product. And as products become more and more a combination of hardware and software, it is the software that allows the manufacturer to provide incremental innovation to their products. However, to innovate in a manner that is matching or even exceeding customer demands, information from the outside world needs to travel as fast as possible through an organization. In case this is done in isolated systems and documents, the journey will be cumbersome and too slow to allow a company to act fast enough. Here digitization comes in, making information directly available as data elements instead of documents with their own file formats and systems to author them. The ultimate dream is a digital enterprise where date “flows”, advocated already by some manufacturing companies for several years.

In the previous paragraph I talked about the need to have an infrastructure in place for people in an organization to follow the product along the complete lifecycle, to be able to analyze and improve the customer experience. However, you also need to create a role in the organization for a person to be responsible for combining insights from the market and to lead various disciplines in the organization, R&D, Sales, Services. And this is precisely the role of a Product Manager.

Very common in the world of software development, not yet recognized in manufacturing companies. In case a product manager role exists already in your organization, he/she can tell you how complicated it currently is to get an overall view of the product and which benefits a digital infrastructure would bring for their job. Once the product manager is well-supported and recognized in the organization, the right skill set to prioritize or discover actions/features will make the products more attractive for consumers. Here the company will benefit.

Conclusion

If your company does not have the role of a product manager in place, your business is probably not yet well enough engaged in the customer journey.  There will be broken links and costly processes to get a fast response to the market.  Consider the role of a Product Manager, which will emerge as seen from the software business.

NOTE 1: Just before publishing this post I read an interesting post from Jan Bosch: Structure Eats Strategy. Well fitting in this context

NOTE 2: The existence of a Product Manager might be a digital maturity indicator for a company, like for classical PLM maturity, the handling of the MBOM (PDM/PLM/ERP) gives insight into PLM maturity of a company.

Related to the MBOM, please read: The Importance of a PLM data model – EBOM and MBOM

 

 

 

 

 

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

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

  4. Lewis Kennebrew's avatar

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

  5. Håkan Kårdén's avatar