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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In the past few years, there has been a discussion if the acronym PLM (Product Lifecycle Management) is perhaps outdated.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.

Image:  21stcenturypublicservant.wordpress.com/

I have talked a lot the past years about Digital Transformation and in particular its relation to PLM. This time I want to focus a little more on Digital Transformation and my observations related to big enterprises and small and medium enterprises. I will take you starting from the top, the C-level to the work floor and then try to reconnect through the middle management. As you can imagine from the title of this post, there is a challenge. And I am aware I am generalizing for the sake of simplicity.

Starting from the C-level of a large enterprise

Large and traditional enterprises are having the most significant challenge when aiming at a digital transformation for several reasons:

  • They have shareholders that prefer short-term benefits above long-term promising but unclear higher benefits. Shareholders most of the time have no personal interest in these companies, they just want to earn money above the average growth.
  • The CEO is the person to define the strategy which has to come with a compelling vision to inspire the shareholders, the customers and the employees in the company – most of the time in that order of priority.
  • The role of the CEO is to prioritize investments and stop or sell core components to make the transformation affordable. Every transformation is about deciding what to stop, what to start and what to maintain.
  • After four to seven years (the seven years’ itch) it is time for a new CEO to create a new momentum as you cannot keep the excitement up too long.
  • Meanwhile, the Stop-activities are creating fear within the organization – people start fearing their jobs and the start-activities are most of the time of such a small-scale that their successes are not yet seen. So at the work floor, there will be reservations about what’s next

Companies like ABB, Ericsson, GE, Philips – in alphabetical order – are all in several stages of their digital transformation and in particular I have followed GE as they were extremely visible and ambitious. Meanwhile, it is fair to say that the initial Digital Transformation plan from GE has stalled and a lot of lessons learned from that.

If you have time – read this article: The Only Way Manufacturers Can Survive – by Vijay Govindarajan & Jeff Immelt (you need to register). It gives useful insights about what the strategy and planning were for digital transformation. And note PLM is not even mentioned there J

Starting from the C-level of a small and medium enterprise

In a small or medium enterprise, the distance between the C-level and the work floor is most of the time much shorter and chances are that the CEO is a long-term company member in case of a long-standing family-owned business. In this type of companies, a long-term vision can exist and you could expect that digital transformation is more sustainable there.

Unfortunate most of the time it is not, as the C-level is often more active in current business strategies and capabilities close to their understanding instead of investing energy and time to digest the full impact of a digital transformation. These companies might invest in the buzz-words you hear in the market, IoT, Digital Twins and Augmented Reality/Virtual Reality, all very visionary topics, however of low value when they are implemented in an isolated way.

In this paragraph, I also need to mention the small and medium enterprises that are in the hands of an investment company.  Here I feel sorry as the investment company is most of the time trying to optimize the current ways of working by simplifying or rationalizing the business, not creating a transformative vision (as they do not have the insights. In this type of companies, you will see on a lower scale the same investments done as in the other category of small and medium enterprises, be it on a lesser scale.

Do people need to change?

Often you hear that the problem with any change within the companies is because people do not want to change. I think this is too much a generalization. I have worked in the past five years with several companies where we explored the benefits and capabilities of PLM in a modern way, sometimes focusing on an item-centric approach, sometimes focusing on a model-based approach. In all these engagements there was no reluctance from the users to change.

However, there were two types of users in these discussions. I would characterize as evolutionary thinkers (most of the time ten years or more in the company) and love-to-change thinkers (most of them five years or less in the company). The difference between these groups was that the evolutionary thinkers were responding in the context of the existing business constraints where the love-to-change thinkers were not yet touched by the “knowledge how good everything was”.

For digital transformation, you need to create the love-to-change attitude while using the existing knowledge as a base to improve. And this is not a people change, it is an organizational change where you need to enable people to work in their best mode. It needs to be an end-to-end internal change – not changing the people, but changing the organizational parameters: KPIs, divisions, departments, priorities. Have a look at this short movie, you can replace the word ERP by PLM, and you will understand why I like this movie (and the relaxing sound)

The Middle Management dilemma

And here comes my last observation. At the C-level we can find inspiring visions often outcome-based, talking about a more agile company, closer to the customer, empowered workers, etc.  Then there is the ongoing business that cannot be disrupted and needs to perform – so the business units, the departments all get their performance KPIs, merely keeping the status quo in place.

Also, new digital initiatives need to be introduced. They don’t fit in the existing business and are often started in separation – like GE Digital division, and you can read Jeff Immelt’ s thoughts and strategy how this could work. (The Only Way Manufacturers Can Survive). However as the majority of the business runs in the old mode, the Digital Business became another business silo in the organization, as the middle management could not be motivated to embed digital in their business (no KPIs or very low significance of new KPIs)

I talked about the hybrid/bimodal approach several times in my blog posts, most recently in The Challenges of a Connected Ecosystem.  One of the points that I did not address was the fact that probably nobody wants to work in the old mode anymore once the new approach is successful and scaled up.

When the new mode of business is still small, people will not care so much and continue business as usual. Once the new mode becomes the most successful part of the company, people do want to join this success if they can. And here the change effort is needed. An interesting article in this context is The End of Two-Speed IT from the Boston Consultancy Group (2016). They already point at the critical role of middle management. Middle management can kill digital transformation or being part of it, by getting motivated and adopting too.

Conclusion

Perhaps too much text in this post and even more content when you dive more in-depth in the provided content. Crucial if you want to understand the digital transformation process in an existing company and the critical place of middle management. They are likely the killers of digital transformation if not give the right coaching and incentives.  Just an observation – not a thought 😉

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…….

 

 

 

 

 

 

 

 

 

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.

 

 

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.

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

 

 

 

 

 

Last week I published a dialogue I had with Flip van der Linden, a fellow Dutchman and millennial, eager to get a grip on current PLM. You can read the initial post here: A PLM dialogue.  In the comments, Flip continued the discussion (look here).  I will elaborate om some parts of his comments and hope some others will chime in. It made me realize that in the early days of blogging and LinkedIn, there were a lot of discussions in the comments. Now it seems we become more and more consumers or senders of information, instead of having a dialogue. Do you agree? Let me know.

Point 1

(Flip) PLM is changing – where lies the new effort for (a new generation of) PLM experts.  I believe a huge effort for PLM is successful change management towards ‘business Agility.’ Since a proper response to an ECR/ECO would evidently require design changes impacting manufacturing and even after-sales and/or legal.  And that’s just the tip of the iceberg.

 

You are right, the main challenge for future PLM experts is to explain and support more agile processes, mainly because software has become a major part of the solution. The classical, linear product delivery approach does not match the agile, iterative approach for software deliveries. The ECR/ECO process has been established to control hardware changes, in particular because there was a big impact on the costs. Software changes are extremely cheap and possible fast, leading to different change procedures. The future of PLM is about managing these two layers (hardware/software) together in an agile way. The solution for this approach is that people have to work in multi-disciplinary teams with direct (social) collaboration and to be efficient this collaboration should be done in a digital way.

A good article to read in this context is Peter Bilello’s article: Digitalisation enabled by product lifecycle management.

 

(Flip) What seems to be missing is an ‘Archetype’ of the ideal transformed organization. Where do PLM experts want to go with these businesses in practice? Personally, I imagine a business where DevOps is the standard, unique products have generic meta-data, personal growth is an embedded business process and supply chain related risks are anticipated on and mitigated through automated analytics. Do you know of such an evolved archetypal enterprise model?

I believe the ideal archetype does not exist yet. We are all learning, and we see examples from existing companies and startups pitching their story for a future enterprise. Some vendors sell a solution based on their own product innovation platform, others on existing platforms and many new vendors are addressing a piece of the puzzle, to be connected through APIs or Microservices. I wrote about these challenges in Microservices, APIs, Platforms and PLM Services.  Remember, it took us “old PLM experts” more than 10-15 years to evolve from PDM towards PLM, riding on an old linear trajectory, caught up by a new wave of iterative and agile processes. Now we need a new generation of PLM experts (or evolving experts) that can combine the new concepts and filter out the nonsense.

Point 2

(Flip) But then given point 2: ‘Model-based enterprise transformations,’ in my view, a key effort for a successful PLM expert would also be to embed this change mgt. as a business process in the actual Enterprise Architecture. So he/she would need to understand and work out a ‘business-ontology’ (Dietz, 2006) or similar construct which facilitates at least a. business processes, b. Change (mgt.) processes, c. emerging (Mfg.) technologies, d. Data structures- and flows, e. implementation trajectory and sourcing.

And then do this from the PLM domain throughout the organization per optimization.  After all a product-oriented enterprise revolves around the success of its products, so eventually, all subsystems are affected by the makeup of the product lifecycle. Good PLM is a journey, not a trip. Or, does a PLM expert merely facilitates/controls this enterprise re-design process? And, what other enterprise ontologism tools and methods do you know of?

Only this question could be a next future blog post. Yes, it is crucial to define a business ontology to support the modern flow of information through an enterprise. Products become systems, depending on direct feedback from the market. Only this last sentence already requires a redefinition of change processes, responsibilities. Next, the change towards data-granularity introduces new ways of automation, which we will address in the upcoming years. Initiatives like Industry 4.0 / Smart Manufacturing / IIoT all contribute to that. And then there is the need to communicate around a model instead of following the old documents path. Read more about it in Digital PLM requires a Model-Based Enterprise. To close this point:  I am not aware of anyone who has already worked and published experiences on this topic, in particular in the context of PLM.

 

Point 3

(Flip) Where to draw the PLM line in a digital enterprise? I personally think this barrier will vanish as Product Lifecycle Management (as a paradigm, not necessarily as a software) will provide companies with continuity, profitability and competitive advantage in the early 21st century. The PLM monolith might remain, but supported by an array of micro services inside and outside the company (next to IoT, hopefully also external data sets).

I believe there is no need to draw a PLM line. As Peter’s article: Digitalisation enabled by product lifecycle management already illustrated there is a need for a product information backbone along the whole (circular) lifecycle, where product information can interact with other enterprise platforms, like CRM, ERP and MES and BI services. Sometimes we will see overlapping functionality, sometimes we will see the need to bridge the information through Microservices. As long as these bridges are data-driven and do not need manual handling/transformation of data, they fit in the future, lean digital enterprise.

Conclusion:

This can be an ongoing dialogue, diving into detailed topics of a modern PLM approach. I am curious to learn from my readers, how engaged they are in this topic? Do you still take part in PLM dialogues or do you consume? Do you have “tips and tricks” for those who want to shape the future of PLM?


Let your voice be heard! (and give Flip a break)

 

Last week I got the following question:

Many companies face the challenges relevant to the cooperation and joint ventures and need to integrate in a smart way the portfolio’s to offer integrated solutions. In the world of sharing and collaboration, this may be a good argument to dig into. Is PLM software ready for this challenge with best practice solutions or this is a matter that is under specific development case by case? Any guidelines?

Some history

When PLM solutions were developed their core focus was on bringing hardware products to the market in a traditional manner as shown in the figure below. clip_image001

Products were pushed to the market based on marketing research and closed innovation. Closed innovation meant companies were dependent on their internal R&D to provide innovative products. And this is the way most PLM systems are implemented: supporting internal development. Thanks to global connectivity, the internal development teams can collaborate together connected to a single PLM backbone/infrastructure.

Third Party Products (TPP) at that time were sometimes embedded in the EBOM, and during the development phase, there would be an exchange of information between the OEM and the TPP provider. Third Party Products were treated in a similar manner as purchase items. And as the manufacturing of the product was often defined in the ERP system, there the contractual and financial interactions with the TTP provider were handled, creating a discontinuity between what has been defined for the product and what has been shipped. The disconnect between the engineering intent and actual delivery to the customer often managed in Excel spreadsheets or proprietary databases developed to soften the pain

What is happening now?

In the past 10 – 15 years there is the growing importance of first electronic components and their embedded software now followed by new go-to-market approaches, where the customer proposition changes from just a product, towards a combined offering of hardware, software, and services. Let´s have a look how this could be done in a PLM environment.

From Products to Solutions

The first step is to manage the customer proposition in a logical manner instead of managing all in a BOM definition. In traditional businesses, most companies still work around multiple Bill of Materials. For example, read this LinkedIn post: The BOM is King. This approach works when your company only delivers hardware.

Not every PLM system supports Out-Of-The-Box a logical structure. I have seen implementations where this logical structure was stored in an external database (not preferred) or as a customized structure in the PLM system. Even in SmarTeam, this methodology was used to support Asset Lifecycle Management. I wrote about this concept early 2014 in the context of Service Lifecycle Management(SLM) two posts: PLM and/or SLM ? and PLM and/or SLM (continued). It is no coincidence that concepts used for connecting SLM to PLM are similar to defining customer propositions.

PropositionIn the figure to the left, you can see the basic structure to manage a customer proposition and how it would connect to the aspects of hardware, software, and services. In an advanced manner, the same structure could be used with configuration rules to define and create a portfolio of propositions. More about this topic potential in a future blog post.

For hardware, most PLM systems have their best practices based on the BOM as discussed before. When combining the hardware with embedded software, we enter the world of systems. The proposition is no longer a product it becomes a system or even an experience.

For managing systems, I see two main additions to the classical PLM approach:

  1. The need for connected systems engineering. As the behavior of the system is much more complicated than just a hardware product, companies discover the need to spend more time on understanding all the requirements for the system and its potential use cases in operation – the only way to define the full experience. Systems Engineering practices coming from Automotive & Aerospace are now coming into the world of high-tech, industrial equipment, and even consumer goods.
  2. The need to connect software deliverables. Software introduces a new challenge for companies, no matter if the software is developed internally or embedded through TTP. In both situations, there is the need to manage change in a fast and iterative manner. Classical ECR /ECO processes do not work here anymore. Working agile and managing a backlog becomes the mode. Application Lifecycle Management connected to PLM becomes a need.

In both domains, systems engineering, and ALM, PLM vendors have their offerings, and on the marketing side, they might all look the same to you. However, there is a fundamental need that is not always visible on the marketing slides, the need for complete openness.

Openness

opennessTo manage a portfolio based on systems a company can no longer afford to manually check in multiple management systems all the dependencies between the product and its components combined with the software deliverables and TTPs. Automation, traceability on changes and notifications are needed in a modern, digital environment, which you might call a product innovation platform. My high-speed blog buddy Oleg Shilovitsky just dedicated a post to “The Best PLM for Product Innovation Platform” sharing several quotes from CIMdata´s talk about characteristics of a Product Innovation Platform and stressing the need for openness.

It is true if you can only manage your hardware (mechanics & electronics) and software in dedicated systems, your infrastructure will be limited and rigid as the outside world is in constant and fast changes. No ultimate solution or product does it all and will do it all in the future. Therefore openness is crucial.

Services

In several companies, original in the Engineering, Procurement & Construction industry, I have seen the need to manage services in the context of the customer delivery too. Highly customized systems and/or disconnected systems were used here. I believe the domain of managing a proposition, a combination of hardware, software, AND services in a connected environment is still in its early days. Therefore the question marks in the diagram.

Conclusion

How Third Party Products management are supported by PLM depends very much on the openness of the PLM system. How it connects to ALM and how the PLM system is able to manage a proposition. If your PLM system has been implemented as a supporting infrastructure for Engineering only, you are probably not ready for the modern digital enterprise.

Other thoughts ???

changeRecently, I have written about classical PLM (document-driven and sequential) and modern PLM (data-driven and iterative) as part of the upcoming digital transformation that companies will have to go through to be fit for the future. Some strategic consultancy companies, like Accenture, talk about Digital PLM when referring to a PLM environment supporting the digital enterprise.

 

From classical PLM to Digital PLM?

The challenge for all companies is to transform their businesses to become customer-centric and find a transformation path from the old legacy PLM environment towards the new digital environment. Companies want to do this in an evolutionary mode. However my current observations are that the pace of an evolutionary approach is too slow related to what happens in their market. This time the change is happening faster than before.

A Big Bang approach towards the new environment seems to be a big risk. History has taught us that this is very painful and costly. To be avoided too. So what remains is a kind of bimodal approach, which I introduced in my recent blog posts (Best Practices or Next Practices). Although one of my respected readers and commenters Ed Lopategui mentioned in his comment (here) bimodal is another word for coexistence. He is not optimistic about this approach either

So, what remains is disruption?

And disruption is a popular word and my blog buddy Oleg Shilovitsky recently dived into that topic again with his post: How to displace CAD and PLM industry incumbents. An interesting post about disruption and disruption patterns. My attention was caught by the words: digital infrastructure.
I quote:

How it might happen? Here is one potential answer – digital infrastructure. Existing software is limited to CAD files stored on a desktop and collaboration technologies developed 15-20 years using relational database and client-server architecture.

Digital Infrastructure

imageAs I mentioned the words, Digital Infrastructure triggered me to write this post. At this moment,  I see companies marketing their Digital Transformation story in a slick way, supported by all the modern buzz words like; customer-centric, virtual twin and data-driven. You would imagine as a PLM geek that they have already made the jump from the old document-driven PLM towards modern digital PLM. So what does a modern digital PLM environment look like ?

The reality, however, behind this slick marketing curtain, is that there are still the old legacy processes, where engineers are producing drawings as output for manufacturing. Because drawings are still legal and controlled information carriers. There is no digital infrastructure behind the scenes. So, what would you expect behind the scenes?

Model-Based Definition as part of the digital infrastructure

Crucial to be ready for a digital infrastructure is to transform your company´s product development process from a file-based process where drawings are leading towards a model-based enterprise. The model needs to be the leading authority (single source of truth) for PMI (Product Manufacturing Information) and potentially for all upfront engineering activities. In this case, we call it Model-Based Systems Engineering sometimes called RFLP (Requirements-Functional-Logical-Product), where even the product can be analyzed and simulated directly based on the model.

A file-based process is not part of a digital infrastructure or model-based enterprise architecture. File-based processes force the company to have multiple instances and representations of the same data in different formats, creating an overhead of work to keep up quality and correctness of data, that is not 100 % secure. A digital infrastructure works with connected data in context.

econimistTherefore, if your company is still relying on drawings and you want to be ready for the future, a first step towards a digital infrastructure would be fixing your current processes to become model-based. Some good introductions can be found here at ENGINEERING.com – search for MBD and you will find:

Moving to Mode-Based is already a challenging transformation inside your company before touching the challenge of moving towards a full digital enterprise, through evolution, disruption or bimodal approach – let the leading companies show the way.

Conclusion

Companies should consider and investigate how to use a Model-Based Engineering approach as a first step to becoming lean and fit for a digital future. The challenge will be different depending on the type of industry and product.
I am curious to learn from my readers where they are on the path to a digital enterprise.

clip_image002At this moment I am finalizing my session for PDT2016 where I will talk about the importance of accurate data. Earlier this year I wrote a post about that theme: The importance of accurate data. Act now!

My PDT session will be elaborating on this post, with a focus on why and how we need this change in day-to-day business happen. So if you are interested in a longer story and much more interesting topics to learn and discuss, come to Paris on 9 and 10 November.

Dreaming is free

Recently I found a cartoon on LinkedIn and shared it with my contacts, illustrating the optimistic view companies have when they are aiming to find the best solution for their business, going through an RFI phase, the RFP phase, and ultimately negotiation the final deal with the PLM solution provider or vendor. See the image below:

clip_image003

All credits to the author – I found this image here

The above cartoon gives a humoristic view of the (PLM) sales process (often true). In addition, I want to share a less optimistic view related to PLM implementations after the deal has been closed. Based on the PLM projects if have been coaching in the past, the majority of these projects became in stress mode once the stakeholders involved only focused on the software, the functions and features and centralizing data. Implementing the software without a business transformation caused a lot of discomfort.

clip_image005Users started to complain that the system did not allow them to do their day-to-day work in the same way. And they were right! They should have a new day-to-day work in the future, with different priorities based on the new PLM infrastructure.

This cultural change (and business change) was often not considered as the PLM system was implemented from an IT-perspective, not with a business perspective.

Over time, a better understanding of PLM and the fact that vendors and implementers have improved their portfolio and implementation skills, classical PLM implementations are now less disruptive.

A classical PLM implementation can be done quickly is because the system most of the time does not change the roles and responsibilities of people. Everyone remains working in his/her own silo. The difference: we store information in a central place so it can be found. And this approach would have worked if the world was not changing.

The digital enterprise transformation.

With the upcoming digitization and globalization of the market, enterprises are forced to adapt their business to become more customer-driven. This will have an impact on how PLM needs to be implemented. I wrote about this topic in my post: From a linear world to fast and circular. The modern digital enterprise has new roles and responsibilities and will eliminate roles and responsibilities that can be automated through a data-driven, rule-based approach. Therefore implementing PLM in a modern approach should be related (driven) by a business transformation and not the other way around!

Benefits realization

In the past two years, I have explained this story to all levels inside various organizations. And nobody disagreed. Redefining the processes, redefining roles was the priority. And we need a team to help people to make this change – these people are change management experts. The benefits diagram from Gartner as shown below was well understood, and most companies agreed the ambition should be to the top curve, in any case, stay above the red curve

clip_image007

But often reality relates to the first cartoon. In the majority of the implementations I have seen the past two years, the company did not want to invest in change management, defining the new process and new roles first for an optimum flow of information. They spent the entire budget on software and implementation services. With a minimum of staff, the technology was implemented based on existing processes – no change management at all. Disappointing, as short-term thinking destroyed the long-term vision and benefits were not as large as they had been dreaming.

Without changing business processes and cultural change management, the PLM team will fight against the organization, instead of surfing on the wave of new business opportunities and business growth.

Conclusion

If your company is planning to implement modern PLM which implicit requires a business transformation, make sure cultural change management is part of your plan and budget. It will bring the real ROI. Depending on your company´s legacy, if a business transformation is a mission impossible, it is sometimes easier to start a new business unit with new processes, new roles and potentially new people. Otherwise, the benefits will remain (too) low from your PLM implementation.

I am curious to learn your experience related to (the lack) of change management – how to include it into the real scope – your thoughts ?

Addition:
As a reaction to this post, Oleg Shilovitsky wrote a related blog post: PLM and the death spiral of cultural change.  See my response below to this post as it will contribute to the understanding of this post

Oleg, thanks for contributing to the theme of cultural change. Your post illustrates that my post was not clear enough, or perhaps too short. I do not believe PLM is that difficult because of technology, I would even claim that technology is a the bottom of my list of priorities. Not stating it is not important, but meaning that when you are converging with a company to a vision for PLM, you probably know the kind of technologies you are going to use.

The highest priority to my opinion is currently the business transformation companies need to go through in order to adapt their business to remain relevant in a digital world. The transformation will require companies to implement PLM in a different manner, less silo-oriented, more focus on value flows starting from the customer.

Working different means cultural change and a company needs to allocate time, budget and energy to that. The PLM implementation is supporting the cultural change not driving the cultural change.

And this is the biggest mistake I have seen everywhere. Management decides to implement a new PLM as the driver for cultural change, instead of the result of cultural change. And they reason this is done, is most of the time due to budget thinking as cultural change is ways more complex and expensive than a PLM implementation.

 

 

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