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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.

 

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.

 

This is the moment of the year to switch-off from the details. No more talking and writing about digital transformation or model-based approaches. It is time to sit back and relax. Two years ago I shared the PLM Songbook, now it is time to see one or more movies. Here are my favorite top five PLM movies:

Bruce Almighty

Bruce Nolan, an engineer in Buffalo, N.Y., is discontented with almost everything in the company despite his popularity and the love of his draftswoman Grace. At the end of the worst day of his life, Bruce angrily ridicules and rages against PLM and PLM responds. PLM appears in human form and, endowing Bruce with divine powers op collaboration, challenges Bruce to take on the big job to see if he can do it any better.

A movie that makes you modest and you realize there is more than your small ecosystem.

 

The good, the bad and the ugly

Blondie (The Good PLM consultant) is a professional who is out trying to earn a few dollars. Angel Eyes (The Bad PLM Vendor) is a PLM salesman who always commits to a task and sees it through, as long as he is paid to do so. And Tuco (The Ugly PLM Implementer) is a wanted outlaw trying to take care of his own hide. Tuco and Blondie share a partnership together making money off Tuco’s bounty, but when Blondie unties the partnership, Tuco tries to hunt down Blondie. When Blondie and Tuco come across a PLM implementation loaded with dead bodies, they soon learn from the only survivor (Bill Carson – the PLM admin) that he and a few other men have buried a stash of value on a file server. Unfortunately, Carson dies, and Tuco only finds out the name of the file server, while Blondie finds out the name on the hard disk. Now the two must keep each other alive in order to find the value. Angel Eyes (who had been looking for Bill Carson) discovers that Tuco and Blondie met with Carson and knows they know the location of the value. All he needs is for the two to ..

A movie that makes you realize that it is a challenging journey to find the value out of PLM. It is not only about execution – but it is also about all the politics of people involved – and there are good, bad and ugly people on a PLM journey.

The Grump

The Grump is a draftsman in Finland from the past. A man who knows that everything used to be so much better in the old days. Pretty much everything that’s been done after 1953 has always managed to ruin The Grump’s day. Our story unfolds The Grump opens a 3D Model on his computer, hurting his brain. He has to spend a weekend in Helsinki to attend a model-based therapy. Then the drama unfolds …….

A movie that makes you realize that progress and innovation do not come from grumps. In every environment when you want to do a change of the status quo, grumps will appear. With the exciting Finish atmosphere, a perfect film for Christmas.

Deliverance

The Cahulawassee River Valley company in Northern Georgia is one of the last analog companies in the state, which will soon change with the imminent implementation of a PLM system in the company, breaking down silos everywhere. As such, four Atlanta city slickers, alpha male Lewis Medlock, generally even-keeled Ed Gentry, slightly condescending Bobby Trippe, and wide-eyed Drew Ballinger decide to implement PLM in one trip, with only Lewis and Ed having experience in CAD. They know going in that the area is ethnoculturally homogeneous and isolated, but don’t understand the full extent of such until they arrive and see what they believe is the result of generations of inbreeding. Their relatively peaceful trip takes a turn for the worse when half way through they encounter a couple of hillbilly moonshiners. That encounter not only makes the four battle their way out of the PLM project intact and alive but threatens the relationships of the four as they do.

This movie, from 1972, makes you realize that in the early days of PLM starting a big-bang implementation journey into an area that is not ready for it, can be deadly, for your career and friendship. Not suitable for small children!

Diamonds Are Forever or Tron (legacy)

James Bond’s mission is to find out who has been drawing diamonds, which are appearing on blogs. He adopts another identity in the form of Don Farr. He joins up with CIMdata and acts as if he is developing diamonds, but everyone is hungry for these diamonds. He also has to avoid Mr. Brouwer and Mr. Kidd, the dangerous couple who do not leave anyone in their way when it comes to model-based. And Ernst Stavro Blofeld isn’t out of the question. He may have changed his looks, but is he linked with the V-shape? And if he is, can Bond finally defeat his ultimate enemy?

Sam Flynn, the tech-savvy 27-year-old son of Kevin Flynn, looks into his father’s disappearance and finds himself pulled into the same world of virtual twins and augmented reality where his father has been living for 20 years. Along with Kevin’s loyal confidant Quorra, father and son embark on a life-and-death journey across a visually-stunning cyber universe that has become far more advanced and exceedingly dangerous. Meanwhile, the malevolent program IoT, who dominates the digital world, plans to invade the real world and will stop at nothing to prevent their escape

I could not decide about number five. The future is bright with Boeing’s new representation of Systems Engineering, see my post on CIMdata’s PLM Europe roadmap event where Don Farr presented his diamond(s). However, the future is also becoming a mix of real with virtual and here Tron (legacy) will help my readers to understand the beauty of a mixed virtual and real world. You can decide – or send me your favorite PLM movies.

Note: All movie reviews are based on IMBd.com story lines, and I thank the authors of these story lines for their contribution and hope they agree with the PLM-related twist. Click on the image to find the full details and original review.

Conclusion

2018 has been an exciting year with a lot of buzzwords combined with the reality that the current PLM approach is incompatible with the future. How we can address this issue more in 2019 – first at PI PLMx 2019 in London (be there – last chance to meet people in the UK when they are still Europeans and share/discuss plans for the upcoming year)

Wishing you all the best during the break and a happy and prosperous 2019

 

During my holiday I have read some interesting books. Some for the beauty of imagination and some to enrich my understanding of the human brain.

Why the human brain? It is the foundation and motto of my company: The Know-How to Know Now.
In 2012 I wrote a post: Our brain blocks PLM acceptance followed by a post in 2014  PLM is doomed, unless …… both based on observations and inspired by the following books (must read if you are interested in more than just PLM practices and technology):

In 2014, Digital Transformation was not so clear. We talked about disruptors, but disruption happened outside our PLM comfort zone.

Now six years later disruption or significant change in the way we develop and deliver solutions to the market has become visible in the majority of companies. To stay competitive or meaningful in a global market with changing customer demands, old ways of working no longer bring enough revenue to sustain.  The impact of software as part of the solution has significantly changed the complexity and lifecycle(s) of solutions on the market.

Most of my earlier posts in the past two years are related to these challenges.

What is blocking Model-Based Definition?

This week I had a meeting in the Netherlands with three Dutch peers all interested and involved in Model-Based Definition – either from the coaching point of view or the “victim” point of view.  We compared MBD-challenges with Joe Brouwer’s AID (Associated Information Documents) approach and found a lot of commonalities.

No matter which method you use it is about specifying unambiguously how a product should be manufactured – this is a skill and craftsmanship and not a technology. We agreed that a model-based approach where information (PMI) is stored as intelligent data elements in a Technical Data Package (TPD) will be crucial for multidisciplinary usage of a 3D Model and its associated information.

If we would store the information again as dumb text in a view, it will need human rework leading to potential parallel information out of sync, therefore creating communication and quality issues. Unfortunate as it was a short meeting, the intention is to follow-up this discussion in the Netherlands to a broader audience. I believe this is what everyone interested in learning and understanding the needs and benefits of a model-based approach (unavoidable) should do. Get connected around the table and share/discuss.

We realized that human beings indeed are often the blocking reason why new ways of working cannot be introduced. Twenty-five years ago we had the discussion moving from 2D to 3D for design. Now due to the maturity of the solutions and the education of new engineers this is no longer an issue. Now we are in the next wave using the 3D Model as the base for manufacturing definition, and again a new mindset is needed.

There are a few challenges here:

  • MBD is still in progress – standards like AP242 still needs enhancements
  • There is a lack of visibility on real reference stories to motivate others.
    (Vendor-driven stories often are too good to be true or too narrow in scope)
  • There is no education for (modern) business processes related to product development and manufacturing. Engineers with new skills are dropped in organizations with traditional processes and silo thinking.

Educate, or our brain will block the future!

The above points need to be addressed, and here the human brain comes again into the picture.  Our unconscious, reptile brain is continuously busy to spend a least amount of energy as described in Thinking, Fast and Slow. Currently, I am reading the Idiot Brain: What Your Head Is Really Up To by Dean Burnett, another book confirming that our brain is not a logical engine making wise decisions

And then there is the Dunning-Kruger effect, explaining that the people with the lowest skills often have the most outspoken opinion and not even aware of this flaw. We see this phenomenon in particular now in social media where people push their opinion as if they are facts.

So how can we learn new model-based approaches and here I mean all the model-based aspects I have discussed recently, i.e., Model-Based Systems Engineering, Model-Based Definition/ Model-Based Enterprise and the Digital Twin? We cannot learn it from a book, as we are entering a new era.

First, you might want to understand there is a need for new ways of working related to complex products. If you have time, listen to Xin Guo Zhang’s opening keynote with the title: Co-Evolution of Complex Aeronautical Systems & Complex SE. It takes 30 minutes so force yourself to think slow and comprehend the message related to the needed paradigm shift for systems engineering towards model-based systems engineering

Also, we have to believe that model-based is the future. If not, we will find for every issue on our path a reason not to work toward the ultimate goal.

You can see this in the comments of my earlier post on LinkedIn, where Sami Grönstrand writes:

I warmly welcome the initiative to “clean up” these concepts  (It is time to clean up our model-based problem and above all, await to see live examples of transformations — even partial — coupled with reasonable business value identification. 

There are two kinds of amazing places: those you have first to see before you can believe they exist.
And then those kinds that you have to believe in first before you can see them…

And here I think we need to simplify en enhance the Model-Based myth as according to Yuval Harari in his book Sapiens, the power of the human race came from creating myths to align people to have long-term, forward-looking changes accepted by our reptile brain. We are designed to believe in myths. Therefore, the need for a Model-based myth.In my post PLM as a myth? from 2017, I discussed this topic in more detail.

Conclusion

There are so many proof points that our human brain is not as reliable as we think it is.  Knowing less about these effects makes it even harder to make progress towards a digital future. This post with all its embedded links can keep your brain active for a few hours. Try it, avoid to think fast and avoid assuming you know it all. Your thoughts?

 

Learning & Discussing more?
Still time to register for CIMdata PLM Roadmap and PDT Europe

 

 

This is my concluding post related to the various aspects of the model-driven enterprise. We went through Model-Based Systems Engineering (MBSE) where the focus was on using models (functional / logical / physical / simulations) to define complex product (systems). Next we discussed Model Based Definition / Model-Based Enterprise (MBD/MBE), where the focus was on data continuity between engineering and manufacturing by using the 3D Model as a master for design, manufacturing and eventually service information.

And last time we looked at the Digital Twin from its operational side, where the Digital Twin was applied for collecting and tuning physical assets in operation, which is not a typical PLM domain to my opinion.

Now we will focus on two areas where the Digital Twin touches aspects of PLM – the most challenging one and the most over-hyped areas I believe. These two areas are:

  • The Digital Twin used to virtually define and optimize a new product/system or even a system of systems. For example, defining a new production line.
  • The Digital Twin used to be the virtual replica of an asset in operation. For example, a turbine or engine.

Digital Twin to define a new Product/System

There might be some conceptual overlap if you compare the MBSE approach and the Digital Twin concept to define a new product or system to deliver. For me the differentiation would be that MBSE is used to master and define a complex system from the R&D point of view – unknown solution concepts – use hardware or software?  Unknown constraints to be refined and optimized in an iterative manner.

In the Digital Twin concept, it is more about a defining a system that should work in the field. How to combine various systems into a working solution and each of the systems has already a pre-defined set of behavioral / operational parameters, which could be 3D related but also performance related.

You would define and analyze the new solution virtual to discover the ideal solution for performance, costs, feasibility and maintenance. Working in the context of a virtual model might take more time than traditional ways of working, however once the models are in place analyzing the solution and optimizing it takes hours instead of weeks, assuming the virtual model is based on a digital thread, not a sequential process of creating and passing documents/files. Virtual solutions allow a company to optimize the solution upfront instead of costly fixing during delivery, commissioning and maintenance.

Why aren’t we doing this already? It takes more skilled engineers instead of cheaper fixers downstream. The fact that we are used to fixing it later is also an inhibitor for change. Management needs to trust and understand the economic value instead of trying to reduce the number of engineers as they are expensive and hard to plan.

In the construction industry, companies are discovering the power of BIM (Building Information Model) , introduced to enhance the efficiency and productivity of all stakeholders involved. Massive benefits can be achieved if the construction of the building and its future behavior and maintenance can be optimized virtually compared to fixing it in an expensive way in reality when issues pop up.

The same concept applies to process plants or manufacturing plants where you could virtually run the (manufacturing) process. If the design is done with all the behavior defined (hardware-in-the-loop simulation and software-in-the-loop) a solution has been virtually tested and rapidly delivered with no late discoveries and costly fixes.

Of course it requires new ways of working. Working with digital connected models is not what engineering learn during their education time – we have just started this journey. Therefore organizations should explore on a smaller scale how to create a full Digital Twin based on connected data – this is the ultimate base for the next purpose.

Digital Twin to match a product/system in the field

When you are after the topic of a Digital Twin through the materials provided by the various software vendors, you see all kinds of previews what is possible. Augmented Reality, Virtual Reality and more. All these presentations show that clicking somewhere in a 3D Model Space relevant information pops-up. Where does this relevant information come from?

Most of the time information is re-entered in a new environment, sometimes derived from CAD but all the metadata comes from people collecting and validating data. Not the type of work we promote for a modern digital enterprise. These inefficiencies are good for learning and demos but in a final stage a company cannot afford silos where data is collected and entered again disconnected from the source.

The main problem: Legacy PLM information is stored in documents (drawings / excels) and not intended to be shared downstream with full quality.
Read also: Why PLM is the forgotten domain in digital transformation.

If a company has already implemented an end-to-end Digital Twin to deliver the solution as described in the previous section, we can understand the data has been entered somewhere during the design and delivery process and thanks to a digital continuity it is there.

How many companies have done this already? For sure not the companies that are already a long time in business as their current silos and legacy processes do not cater for digital continuity. By appointing a Chief Digital Officer, the journey might start, the biggest risk the Chief Digital Officer will be running another silo in the organization.

So where does PLM support the concept of the Digital Twin operating in the field?

For me, the IoT part of the Digital Twin is not the core of a PLM. Defining the right sensors, controls and software are the first areas where IoT is used to define the measurable/controllable behavior of a Digital Twin. This topic has been discussed in the previous section.

The second part where PLM gets involved is twofold:

  • Processing data from an individual twin
  • Processing data from a collection of similar twins

Processing data from an individual twin

Data collected from an individual twin or collection of twins can be analyzed to extract or discover failure opportunities. An R&D organization is interested in learning what is happening in the field with their products. These analyses lead to better and more competitive solutions.

Predictive maintenance is not necessarily a part of that.  When you know that certain parts will fail between 10.000 and 20.000 operating hours, you want to optimize the moment of providing service to reduce downtime of the process and you do not want to replace parts way too early.


The R&D part related to predictive maintenance could be that R&D develops sensors inside this serviceable part that signal the need for maintenance in a much smaller time from – maintenance needed within 100 hours instead of a bandwidth of 10.000 hours. Or R&D could develop new parts that need less service and guarantee a longer up-time.

For an R&D department the information from an individual Digital Twin might be only relevant if the Physical Twin is complex to repair and downtime for each individual too high. Imagine a jet engine, a turbine in a power plant or similar. Here a Digital Twin will allow service and R&D to prepare maintenance and simulate and optimize the actions for the physical world before.

The five potential platforms of a digital enterprise

The second part where R&D will be interested in, is in the behavior of similar products/systems in the field combined with their environmental conditions. In this way, R&D can discover improvement points for the whole range and give incremental innovation. The challenge for this R&D organization is to find a logical placeholder in their PLM environment to collect commonalities related to the individual modules or components. This is not an ERP or MES domain.

Concepts of a logical product structure are already known in the oil & gas, process or nuclear industry and in 2017 I wrote about PLM for Owners/Operators mentioning Bjorn Fidjeland has always been active in this domain, you can find his concepts at plmPartner here  or as an eLearning course at SharePLM.

To conclude:

  • This post is way too long (sorry)
  • PLM is not dead – it evolves into one of the crucial platforms for the future – The Product Innovation Platform
  • Current BOM-centric approach within PLM is blocking progress to a full digital thread

More to come after the holidays (a European habit) with additional topics related to the digital enterprise

 

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 …..

 

 

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 !

 

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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