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Some weeks ago I wrote a post about non-intelligent part numbers (here) and this was (as expected) one of the topics that fired up other people to react. Thanks to Oleg Shilovitsky (here), Ed Lopategui (here), David Taber (here) for your contribution to this debate. For me, the interesting conclusion was that nobody denies the advantage of non-intelligent part number anymore. Five to ten years ago this discussion would be more a debate between defenders of the old “intelligent” methodology and non-intelligent numbers. Now it was more about how to deal/wait/anticipate for the future. Great progress !!
Non-intelligent part number benefits
Again a short summary for those who have not read the posts referenced in the introduction. Non-intelligent part numbers provide the following advantages:
- Flexibility towards the future in case of mergers, new products, and technologies of number ranges not foreseen. Reduced risk of changes and maintenance for part numbers in the future.
- Reduced support for “brain related connectivity” between systems (error prone) and better support for automated connectivity (interfaces / digital scanning devices). Minimizing mistakes and learning time.
So when a company decides to move forward towards non-intelligent part numbers, there are still some more actions to take. As the part number becomes irrelevant for human beings, there is the need for more human-readable properties provided as metadata on screens or attributes in a report.
CLASSIFICATION: The first obvious need is to apply a part classification to your parts. Intelligent part numbers somehow were often a kind of classification based on the codes and position of numbers and characters inside the intelligent ID. The intelligent part number containing information about the type of part, perhaps the drawing format, the project or the year it was issued the first time. You do not want to lose this information and therefore, make sure it is captured in attributes (e.g. part type / creation date) or in related information (e.g. drawing properties, model properties, customer, project). In a modern PLM system, all the intelligence of a part number needs to be at least stored as metadata and relations.
Which classification to use is hard to tell. It depends on your industry and the product you are making. Each industry has it standards which are probably the optimized target when you work in that industry. Classifications like UNSPC might be too generic. Although when you classify, do not invent a new classification yourself. People have spent thousands of hours (millions perhaps) on building the best classification for your industry – don’t be smarter unless you are a clever startup.
And next, do not rely on a single classification. Make sure your parts can adhere to multiple classifications as this is the best way to stay flexible for the future. Multiple classifications can offer support for a marketing view, a technology view (design and IP usage), a manufacturing view and so on.
Legacy parts should be classified by using analytic tools and custom data manipulations to complete the part metadata in the future environment. There are standard tools in the market to support data discovery and quality improvement. Part similarity discovery done by Exalead’s One Part and for more specific tools read Dick Bourke’s article on Engineering.com.
DOWNSTREAM USAGE: As Mathias Högberg commented on my post, the challenge of non-intelligent part numbers has its impact downstream on the shop floor. Production line scheduling for variants or production process steps for half-fabricates often depends on the intelligence of the part number. When moving to non-intelligent numbers, these capabilities have to be addressed too, either by additional attributes, immediately identifying product families or by adding a more standardized description based on the initial attributes of the classification. Also David Taber in his post talked about two identifiers, one meaningless and fixed and a second used for the outside world, which could be build by a concatenation of attributes and can change during the part lifecycle.
In the latter case, you might say, we remove intelligence from the part number and we bring intelligence back in the description. This is correct. Still human beings are better in mapping a description in their mind than a number.
Do you know Jos Voskuil (a.k.a. virtualdutchman) or
Do you know NL 13.012.789 / 56 ?
Quality of data
Moving from “intelligent” part numbers towards meaningless part numbers enriched with classification and a standardized description, allow companies to gain significant benefits for just part reuse. This is what current enterprises are targeting. Discovering and eliminating similar parts already justifies this process. I consider this as a tactical advantage. The real strategic advantage will come in the next ten years when we will go more and more to a digital enterprise. In a digital enterprise, algorithms will play a significant role (see Gartner) amount of human interpretation and delays. However, algorithms only work on data with certain properties and a reliable quality.
Introducing non-intelligent part numbers has it benefits and ROI to stay flexible for the future. However consider it also as a strategic step for the long-term future when information needs to flow in an integrated way through the enterprise with a minimum of human handling.
Happy New Year to all of you and I am wishing you all an understandable and digital future. This year I hope to entertain you again with a mix of future trends related to PLM combined with old PLM basics. This time, one of the topics that are popping up in almost every PLM implementation – numbering schemes – do we use numbers with a meaning, so-called intelligent numbers or can we work with insignificant numbers? And of course, the question what is the impact of changing from meaningful numbers towards unique meaningless numbers.
Why did we create “intelligent” numbers?
Intelligent part numbers were used to help engineers and people on the shop floor for two different reasons. As in the early days, the majority of design work was based on mechanical design. Often companies had a one-to-one relation between the part and the drawing. This implied that the part number was identical to the drawing number. An intelligent part number could have the following format: A4-95-BE33K3-007.A
Of course, I invented this part number as the format of an intelligent part number is only known to local experts. In my case, I was thinking about a part that was created in 1995, drawn on A4. Probably a bearing of the 33K3 standard (another intelligent code) and its index is 007 (checked in a numbering book). The version of the drawing (part) is A
A person, who is working in production, assembling the product and reading the BOM, immediately knows which part to use by its number and drawing. Of course the word “immediately” is only valid for people who have experience with using this part. And this was in the previous century not so painful as it is now. Products were not so sophisticated as they are now and variation in products was limited.
Later, when information became digital, intelligent numbers were also used by engineering to classify their parts. The classification digits would assist the engineer to find similar parts in a drawing directory or drawing list.
And if the world had not changed, there would be still intelligent part numbers.
Why no more intelligent part numbers?
There are several reasons why you would not use intelligent part numbers anymore.
- An intelligent number scheme works in a perfect world where nothing is changing. In real life companies merge with other companies and then the question comes up: Do we introduce a new numbering scheme or is one of the schemes going to be the perfect scheme for the future?If this happened a few times, a company might think: Do we have to through this again and again? As probably topic #2 has also occurred.
- The numbering scheme does not support current products and complexity anymore. Products change from mechanical towards systems, containing electronic components and embedded software. The original numbering system has never catered for that. Is there an overreaching numbering standard? It is getting complicated, perhaps we can change ? And here #3 comes in.
- As we are now able to store information in a digital manner, we are able to link to this complex part number a few descriptive attributes that help us to identify the component. Here the number is becoming less important, still serving as access to the unique metadata. Consider it as a bar code on a product. Nobody reads the bar code without a device anymore and the device connected to an information system will provide the right information. This brings us to the last point #4.
- In a digital enterprise, where data is flowing between systems, we need unique identifiers to connect datasets between systems. The most obvious example is the part master data. Related to a unique ID you will find in the PDM or PLM system the attributes relevant for overall identification (Description, Revision, Status, Classification) and further attributes relevant for engineering (weight, material, volume, dimensions).
In the ERP system, you will find a dataset with the same ID and master attributes. However here they are extended with attributes related to logistics and finance. The unique identifier provides the guarantee that data is connected in the correct manner and that information can flow or connected between systems without human interpretation or human-spent processing time.
What to do now in your company?
There is no business justification just to start renumbering parts just for future purposes. You need a business reason. Otherwise, it will only increase costs and create a potential for migration errors. Moving to meaningless part numbers can be the best done at the moment a change is required. For example, when you implement a new PLM system or when your company merges with another company. At these moments, part numbering should be considered with the future in mind.
And the future is no longer about memorizing part classifications and numbers, even if you are from the generation that used to structure and manage everything inside your brain. Future businesses rely on digitally connected information, where a person based on machine interpretation of a unique ID will get the relevant and meaningful data. Augmented reality (picture above) is becoming more and more available. It is now about human beings that need to get ready for a modern future.
Intelligent part numbers are a best practice from the previous century. Start to think digital and connected and try to reduce the dependency of understanding the part number in all your business activities. Move towards providing the relevant data for a user. This can be an evolution smoothening a future PLM implementation step.
Looking forward to discussing this topic and many other PLM related practices with you face to face during the Product Innovation conference in Munich. I will talk about the PLM identity change and lead a focus group session about PLM and ERP integration. Looking from the high-level and working in the real world. The challenge of every PLM implementation.
- It does not make sense to define the future of PLM
- PLM is not an engineering solution anymore
- Linearity of business is faster becoming a holdback
- The Product in PLM is no longer a mechanical Product
- Planet Lifecycle Management has made a next major step
It does not make sense to define the future of PLM
At the beginning of this year, there was an initiative to define the future of PLM for 2025 to give companies, vendors, implementors a guidance to what is critical and needed for PLM in 2015. Have a read here: The future of PLM resides in Brussels.
I believe it is already hard to agree what has been the recognized scope of PLM in the past 10 years, how can we define the future of PLM for the next 10 years. There are several trends currently happening (see the top 5 above) that all can either be in or out of scope for PLM. It is no longer about the definition of PLM; it is dynamically looking towards how businesses adapt their product strategy to new approaches.
Therefore, I am more curious how Product Innovation platforms or Business Innovation platforms will evolve instead of focusing on a definition of what should be PLM in 2025. Have a further look here, such as, The Next Step in PLM’s Evolution: Its Platformization a CIMdata positioning paper.
Conclusion: The future is bright and challenging, let´s not fence it in by definitions.
PLM is not an engineering solution anymore
More and more in all the discussions I had this year with companies looking into PLM, most of them see now PLM as a product information backbone throughout the lifecycle, providing a closed-loop of information flow and visibility across all discipline.
End-to-end visibility, End-to-end tractability, Real-time visibility were some of the buzz-words dropped in many meetings.
These words really express the change happening. PLM is no longer an engineering front-end towards ERP; PLM interacts at each stage of the product lifecycle with other enterprise systems.
End-to-end means when products are manufactured we still follow them through the manufacturing process (serialization) and their behavior in the field (service lifecycle management/field analytics).
All these concepts require companies to align in a horizontal manner, instead of investing in optimizing their silos. Platformization, as discussed above, is a logic step for extending PLM.
Conclusion: If you implement PLM now, start thinking first about the end-to-end flow of information. Or to be more concrete: Don´t be tempted to start with engineering first. It will lock your new PLM again in an extended PDM silo.
Linearity of business is faster becoming a holdback
Two years ago I started talking about: Did you notice PLM is changing ? This topic was not in the mainstream of PLM discussions two years ago. Now with the introduction of more and more software in products (products become systems), the linear process of bringing a product to the market has become a holdback.
The market /your customers expect faster and incremental innovations/ upgrades preferably without having to invest again in a new product. If you look back, the linear product development approach has not changed since the Second World War. We automated more and more the linear process. Remember the New Product Introduction hype around 2004 -2006, where companies started to extend the engineering process with a governance process to follow a product´s introduction from its early concept phase toward a globally available product. This process is totally linear. I wrote about it in my post: from a linear world to fast and circular, where the word circular is also addressing the change of delivering products as a service instead of deliver once and scrap them.
One of my favorite presentations is from Chris Armbruster: Rethinking Business for Exponential Times – enjoy if you haven´t seen this one.
Conclusion: The past two years the discussion related to modern, data-driven dynamic products and services has increased rapidly. Now with IoT, it has become a hype to be formalized soon as life goes faster and faster.
The Product in Product Lifecycle Management is no longer a mechanical Product
When I started to implement PDM systems in the nineties, we tried to keep electrical engineering outside the scope as we had no clue how to manage their information in the context of a mechanical design. It was very rudimentary. Now PLM best practices exist to collaborate and synchronize around the EBOM in an integrated manner.
The upcoming challenge now is due to the software used in products, which turn them into systems. And not only that, software can be upgraded in a minute. So the classical ECR / ECO processes designed for hardware are creating too much overhead. Agile is the motto for software development processes. Now, we (PLM consultants/vendors) are all working on concepts and implementations where these worlds come together. PLM (Product Lifecycle Management), ALM (Asset Lifecycle Management) and SysLM (System Lifecycle Management as introduced by Prof. Martin Eigner – have a read here) are all abbreviations representing particular domains that need to flow together.
Conclusion: For most companies their products become systems with electronics and software. This requires new management and governance concepts. The challenge for all vendors & implementors.
Planet Lifecycle Management has made a next major step
Finally good news came in the beginning of December, where for the first time all countries agreed that our planet needs to have a sustainable lifecycle. Instead of the classical lifecycle from cradle to grave we want to apply a sustainable lifecycle to this planet, when it is still possible. This decision is a major breakthrough pushing us all to leave the unsustainable past behind and to innovate and work on the future. The decisions taken in Paris should be considered as a call for innovative thinking. PLM can learn from that as I wrote earlier this year in my post PLM and Global Warming
Conclusion: 2015 was a year where some new trends became clear. Trends will become commodity faster and faster. A challenge for all of us to stay connected and understand what is happening. Never has the human brain challenged before to adapt to change with such an impact.
Closing 2015 means for me a week of quietness and stepping out of the fast lane. I wish you all a healthy 2016 with a lot of respect, compromises and changing viewpoints. The current world is too complex to solve issues by one-liners.
Take your time to think and reflect – it works!
SEE AND HEAR YOU BACK IN 2016
Topics discussed in 2014-2015
- The importance of a PLM data model: EBOM – MBOM
- EBOM and (CAD) Documents
- Some more EBOM methodology
- Products, BOMs, and Parts
- The Importance of a PLM data model
PLM and Business Change
- Modern PLM brings Power to the People
- The Innovator’s dilemma and Generation change
- The importance of change management with PLM
- PLM and Global warming
- Breaking down the silos with data
- From a linear world to fast and circular ?
From a linear world to a circular and fast-blog
PLM and Business
The past weeks I have discussed at various events two topics that appeared to be different:
- The change from an analogue, document-driven enterprise towards a digital, data-driven enterprise with all its effects. E.g. see From a linear world to fast and circular?
- The change in generations upcoming. The behavior and the attitude of the analogue generation(s) and the difference in behavior from the digital generation(s).
During PDT2015 (a review of the conference here), we discussed all the visible trends that business in exponential changing in some industries due to digitalization and every cheaper technology. The question not answered during that conference was: How are we going to make this happen in your company?
Last week I spoke at a PLM forum in Athens and shared with the audience the opportunities for Greece to catch-up and become a digital service economy like Singapore. Here I pictured an idealistic path how this could happen (based on an ideal world where people think long-term).
A mission impossible, perhaps.
The primary challenge to move from analogue towards digital is to my opinion the difference in behavior of the analogue and digital generations (and I am generalizing of course)
The analogue generation has been educated that knowledge is power. Store all you know in your head or keep it in books close to you. Your job was depending on people needing you. Those who migrated to the digital world most of the time continued the same behavior. Keep information on your hard disk or mailbox. A job was designed for life and do not plan to share as your job might come at risk. Continuous education was not part of their work pattern. And it is this generation that is in power in most of the traditional businesses.
The digital generation has been educated (I hope so – not sure for every country) to gather information, digest and process it and come with a result. There is no need to store information in your head as there is already an information overflow. Store in your head methodology and practices to find and interpret data. The digital generation for sure wants a stable work environment but they already grew up with the mindset that there is no job for life, having seen several crises. It is all about being flexible and keep your skills up-to-date.
So we have the dilemma here that business is moving from analogue towards digital, where the analogue business represents the linear processes that the old generation was used to. Digital business is much more an iterative approach, acting and adapting on what happens around you. A perfect match for the digital generations.
A dilemma ?
Currently the old generation is leading and they will not easy step aside due to their classical education and behavior. We cannot expect behavior to change, just because it is logically explained. In that case, everyone would stop smoking or adopt other healthy standards.
The dilemma reminded me of the Innovators Dilemma, a famous theory from Clayton Christensen, which also could apply to analogue and digital businesses. Read more about the Innovators Dilemma here in one of my older blog posts: The Innovator´s dilemma and PLM. You can replace the incumbent with the old analogue generation and the disruptive innovation comes from using digital platforms and information understood by the digital generation. If you follow this theory, it would mean old businesses would disappear and new businesses would pop-up and overtake the old companies. Interesting conclusion, however, will there be disruption everywhere?
Recently I saw Peter Sondergaard from Gartner presenting at Gartner Symposium/ITxpo 2015 in Orlando. In his keynote speech, he talked about the value of algorithms introducing first how companies should move from their traditional analogue business towards digital business in a bimodal approach. Have a read of the press release here.
If you have the chance to view his slick and impressive keynote video (approx. 30 minutes) you will understand it better. Great presentation. In the beginning Peter talks about the bimodal approach sustaining old, slowly dying analogue businesses and meanwhile building teams developing a digital business approach. The graph below says it all.
Interesting from this approach is that a company can evolve without being disrupted. Still my main question remains: Who will lead this change from the old analogue business towards modern digital business approach. Will it be the old generation coaching the new generation or will there be a natural evolution at the board level required before this process starts?
I have no conclusion this time as I am curious to your opinion. A shift in business is imminent, but HOW will companies / countries pick-up this shift?
Your thoughts or experiences ?
Image and article related to the article “The Onrushing Wave” in the Economist Jan 18th, 2014
When PLM is discussed at management level, often the goal is to increase efficiency, which translates into doing the same with fewer people. And it is the translation that is creating worries inside the company. The PLM system is going to cut down the amount of jobs in our company.
The result: People, who fear their job is at risk, will make sure PLM will fail and become blockers. These people will be the ones defending the “good old way of working” and create a mood of complexity for the new PLM system.
I wrote some time ago a post about PLM and Blockers
At the end there is frustration at all levels in the company and PLM systems are to blame.
How to address the fear for disappearing jobs block a PLM implementation?
First of all if you implement PLM now, do not target efficiency only. There is a digital revolution ongoing, radically changing standard businesses and markets. The picture at the top says it all. If you are still not convinced, read the “old” article from the Economist or more related to PLM, I just read this article from Accenture consulting talking about Digital PLM. I liked the opening sentence from that article:
“It’s time to adopt a digital model for product lifecycle management – or get left behind.”
The digital revolution forces companies to become extremely flexible and agile. Business models can rapidly change. Where perhaps your company was the market leader, a few years you can be in trouble, due to the decoupling of products and services in a different business model. There are a few places where you do not have to worry (yet). If you are in a governmental type of business (no competition – you are the only preferred supplier) the less worried you might be for the upcoming digital revolution. Other types of companies need to make a strategic plan.
Making a strategic plan
The strategic plan starts at the board level and has, of course, elements of efficiency. However, the major strategic discussion should be: “How will we differentiate our company in the future and stay in business and profitable”. This cannot be by competing on price only. It requires you can excite your future customers and who these customers are might not be clear yet either.
Different business models can give the company a better position in the market. The current trend in competitive markets is that the value does not come from selling products. Selling services or operation capacity (OPEX instead of CAPEX) are currently upcoming new business models and they need constant anticipation to what happens in the market or at your potential customer base.
Digitalization of information and being able to work with real-time information, instead of information hidden in documents, handled by document controllers, creates the opportunity to change. For example the potential of “The Internet of Everything” is huge.
At the board level, you need the vision where the company should be in the next 5 to 10 years. It will not bubble up automatically in an organization. And when talking about PLM, it should be digital PLM.
It is not easy to communicate the above if you have not lived through the whole process in your mind. Management needs to be able to explain the vision and its impact on the organization in such a way that it empowers people instead of making them afraid of change. We all know the examples of charismatic CEOs, like Steve Jobs, who could energize a company and its customers. However, it is clear that not every CEO is like Steve Jobs.
Once you are able to communicate the vision, it will be logical that the organization needs new processes and in modern digital processes create different responsibilities and need different management styles.
When you start implementing PLM in a modern approach (digital PLM according to Accenture) there will be jobs disappearing. There is no need to be secretive about that; it is a result of the vision that should be known to everyone in the company.
Disappearing jobs are:
- jobs where people are processing data (from one format to the other) and checking follow-up processes (from on Excel to the other). If your daily job is collecting data and filling spreadsheets with data your job is at risk. In a digital environment, the data will be real-time available and can be filtered and presented in automatic reports or dashboards.
- Jobs where team managers have the major task to decide on priorities for the team and fight with other discipline team managers on priorities. In a digital environment, empowered employees will understand conflicting activities and they will be able to discuss and decide immediately with the relevant people. No need for an intermediate layer of people handling escalations only. It is true that this modern approach requires a different management style and people who can deal with being empowered. In general, empowered people feel more motivated that employees who are just doing what their managers tell them to do. The business change from hierarchical and siloed organizations towards networked organizations is critical and challenging – all depending on trust and the right change management.
- The classical fire-fighters. At first glance they are considered as crucial as they solve all the issues with great energy, do not run away when work needs to be done and make it happen. From the management perspective, these people are blocking change as they flourish from the chaos and do not fix or prevent new issues coming up.
For all other people in the company, digital PLM should bring relief – see the Gartner quote below.
Digital business jobs imply spending less time in searching for information. Less work in a reactive mode as information in the right context in real-time will be available. End to end visibility of information combined with transparency will lead to higher performance and motivation. It requires changing behaviors, motivation must come from the inspiration of the management and the understanding that your company is becoming more flexible and more competitive than before. And for that reasons keeping you in business and providing you an interesting place to work.
Conclusion: Do not use PLM to improve efficiency only and ROI discussions. There is a strategic need to be ready and stay in business for the future. Modern PLM is an enabler, however, requires a vision, inspiring communication and a path for employees to be empowered.
I am curious about your opinion – will this happen to your company / industry?
As a genuine Dutchman, I was able to spend time last month in the Netherlands, and I attended two interesting events: BIMOpen2015, where I was invited to speak about what BIM could learn from PLM (see Dutch review here) and the second event: Where engineering meets supply chain organized by two startup companies located in Yes!Delft an incubator place working close to the technical university of Delft (Dutch announcement here)
Two different worlds and I realized later, they potential have the same future. So let’s see what happened.
BIMopen 2015 had the theme: From Design to Operations and the idea of the conference was to bring together construction companies (the builders) and the facility managers (the operators) and discuss the business value they see from BIM.
First I have to mention that BIM is a confusing TLA like PLM. So many interpretations of what BIM means. For me, when I talk about BIM I mean Building Information Management. In a narrower meaning, BIM is often considered as a Building Information Model – a model that contains all multidisciplinary information. The last definition does not deal with typical lifecycle operations, like change management, planning, and execution.
The BIMopen conference started with Ellen Joyce Dijkema from BDO consultants who addressed the cost of failure and the concepts of lean. Thinking. The high cost of failure is known and accepted in the construction industry, where at the end of the year profitability can be 1 % of turnover (with a margin of +/- 3 % – so being profitable is hard).
Lean thinking requires a cultural change, which according to Ellen Joyce is an enormous challenge, where according to a study done by Prof Dr. A. Cozijnsen there is only 19 % of chance this will be successful, compared to 40 % chance of success for new technology and 30 % of chance for new work processes.
It is clear changing culture is difficult and in the construction industry it might be even harder. I had the feeling a large part of the audience did not grasp the opportunity or could find a way to apply it to their own world.
My presentation about what BIM could learn from PLM was similar. Construction companies have to spend more time on upfront thinking instead of fixing it later (costly). In addition thinking about the whole lifecycle of a construction, also in operations can bring substantial revenue for the owner or operator of a construction. Where traditional manufacturing companies take the entire lifecycle into account, this is still not understood in the construction industry.
This point was illustrated by the fact that there was only one person in the audience with the primary interest to learn what BIM could contribute to his job as facility manager and half-way the conference he still was not convinced BIM had any value for him.
A significant challenge for the construction industry is that there is no end-to-end ownership of data, therefore having a single company responsible for all the relevant and needed data does not exist. Ownership of data can result in legal responsibility at the end (if you know what to ask for) and in a risk shifting business like the construction industry companies try to avoid responsibility for anything that is not directly related to the primary activities.
Some larger companies during the conference like Ballast Nedam and HFB talked about the need to have a centralized database to collect all the data related to a construction (project). They were building these systems themselves, probably because they were not aware of PLM systems or did not see through the first complexity of a PLM system, therefore deciding a standard system will not be enough.
I believe this is short-term thinking as with a custom system you can get quick results and user acceptance (it works the way the user is asking for) however custom systems have always been a blockage for the future after 10-15 years as they are developed with a mindset from that time.
If you want to know, learn more about my thoughts have a look at 2014 the year the construction industry did not discover PLM. I will write a new post at the end of the year with some positive trends. Construction companies start to realize the benefits of a centralized data-driven environment instead of shifting documents and risks.
The cloud might be an option they are looking for. Which brings me to the second event.
Engineering meets Supply Chain
This was more an interactive workshop / conference where two startups KE-Works and TradeCloud illustrated the individual value of their solution and how it could work in an integrated way. I had been in touch with KE-Works before because they are an example of the future trend, platform-thinking. Instead of having one (or two) large enterprise system(s), the future is about connecting data-centric services, where most of them can run in the cloud for scalability and performance.
KE-Works provides a real-time workflow for engineering teams based on knowledge rules. Their solution runs in the cloud but connects to systems used by their customers. One of their clients Fokker Elmo explained how they want to speed up their delivery process by investing in a knowledge library using KE-works knowledge rules (an approach the construction industry could apply too)
In general if you look at what KE-works does, it is complementary to what PLM-systems or platforms do. They add the rules for the flow of data, where PLM-systems are more static and depend on predefined processes.
TradeCloud provides a real-time platform for the supply chain connecting purchasing and vendors through a data-driven approach instead of exchanging files and emails. TradeCloud again is another example of a collection of dedicated services, targeting, in this case, the bottom of the market. TradeCloud connects to the purchaser’s ERP and can also connect to the vendor’s system through web services.
The CADAC group, a large Dutch Autodesk solution provided also showed their web-services based solution connecting Autodesk Vault with TradeCloud to make sure the right drawings are available. The name of their solution, the “Cadac Organice Vault TradeCloud Adapter” is more complicated than the solution itself.
What I saw that afternoon was three solutions providers connected using the cloud and web services to support a part of a company’s business flow. I could imagine that adding services from other companies like OnShape (CAD in the cloud), Kimonex (BOM Management for product design in the cloud) and probably 20 more candidates can already build and deliver a simplified business flow in an organization without having a single, large enterprise system in place that connects all.
I believe this is the future and potential a breakthrough for the construction industry. As the connections between the stakeholders can vary per project, having a configurable combination of business services supported by a cloud infrastructure enables an efficient flow of data.
As a PLM expert, you might think all these startups with their solutions are not good enough for the real world of PLM. And currently they are not – I agree. However disruption always comes unnoticed. I wrote about it in 2012 (The Innovators Dilemma and PLM)
Innovation happens when you meet people, observe and associate in areas outside your day-to-day business. For me, these two events connected some of the dots for the future. What do you think? Will a business process based on connected services become the future?
Sometimes we have to study careful to see patterns have a look here what is possible according to some scientists (click on the picture for the article)
The conference was hosted by Eurostep supported by CIMdata, Airbus, Siemens Energy and Volvo AB.
For me, the PDT conference is interesting because there is a focus on architecture and standards flavored with complementary inspiring presentations. This year there were approximate 110 participants from 12 countries coming from different industries listening to 25 presentations spread over two days.
Peter Bilello from CIMdata kicked off the conference with his presentation: The Product Innovation Platform: What’s Missing.
Peter explained how the joined vision from CIMdata, Gartner and IDC related to a product innovation platform is growing.
The platform concept is bringing PLM to the enterprise level as a critical component to support innovation. The main challenge is to make the complex simple – easier said than done, but I agree this is the real problem of all the software vendors.
Peter showed an interesting graph based on a survey done by CIMdata, showing two trends.
- The software and technology capabilities are closing more and more the gap with the vision (a dream can come true)
- The gap between the implemented capabilities and the technical possible capabilities is growing too. Of course, there is a difference between the leaders and followers.
Peter described the three success factors determining if a platform can be successful:
- Connection: how easy is it for others to connect and plug into the platform to participate as part of the platform. Translated to capabilities this requires the platform to support open standards to connect external data sources as you do not want to build new interfaces for every external source. Also, the platform provider should provide an integration API with a low entry level to get the gravity (next point)
- Gravity: how well does the platform attract participants, both producers, and consumers. Besides a flexible and targeted user interfaces, there must be an infrastructure that allows companies to model the environment in such a manner that it supports experts creating the data, but also support consumers in data, who are not able to navigate through details and want a consumer-friendly environment.
- Flow: how well does the platform support the exchange and co-creation of value. The smartphone platforms are extremely simple compared to a business platform as the dimension of lifecycle status and versioning is not there. A business platform needs to have support for versioning and status combined with relating the information in the right context. Here I would say only the classical PLM vendors have in-depth experience with that.
Having read these three bullet points and taking existing enterprise software vendors for PLM, ERP, and other “platforms” in mind, you see there is still a way to go before we have a “real” platform available.
According to Peter, companies should start with anchoring the vision for a business innovation platform in their strategic roadmap. It will be an incremental journey anyway. How clear the vision is connected to business execution in reality differentiates leaders and followers.
Next Marc Halpern from Gartner elaborated on enabling Product Innovation Platforms. Marc started to say that the platform concept is still the process of optimizing PLM.
Marc explained the functional layers making up a product innovation platform, see below
According to Marc, in 2017 the major design, PLM and business suite vendors will all offer product innovation platforms, where certain industries are more likely to implement product innovation platforms faster than others.
Marc stressed that moving to a business innovation platform is a long, but staged, journey. Each stage of the journey can bring significant value.
Gartner has a 5-step maturity model based on the readiness of the organization. Moving from reactive, repeatable, integrating towards collaborating and ultimately orchestrating companies become business ready for PDM first, next PLM and the Product Innovation Platform at the end. You cannot skip one of these steps according to Marc. I agree, PLM implementations in the past failed because the company was dreaming that the PLM system would solve the business readiness of the organization.
Marc ended with a case study and the conclusions were not rocket science.
The importance of change management, management understanding and commitment, and business and IT joined involvement. A known best practice, still we fail in many situations to act accordingly, due to underestimation of the effort. See also my recent blog post: The importance of change management for PLM.
She described how Anders Wilhemson, original a professor in architecture, focused on solving a global, big problem addressing 2.5 billion people in the world. These 2.5 billion persons, the poorest of the world, lack sanitation, which results in a high death rate for children (every 15 seconds a child dies because of contaminated water). Also the lack of safe places for sanitation lead to girls dropping out of school and women and children being at risk for rape when going to toilet places.
The solution is a bag, made of high-performance biodegradable plastics combined with chemicals, already in the bag, processing the feces to kill potential diseases and make the content available as fertilizer for the agricultural industry.
The plastic bag might not be new, but adding the circular possibilities to it, make it a unique approach to creating a business model providing collection and selling of the content again. For the poorest every cent they can earn makes a different.
Currently in initial projects the Peepoo system has proven its value: over 95 % user acceptance. It is the establishment that does not want to introduce Peepoo on a larger scale. Apparently they never realized themselves the problems with sanitation.
Peepoo is scaling up and helping the bottom of our society. And the crazy fact is that it was not invented by engineers but by an architect. This is challenging everyone to see where you can contribute to a better world. Have a look at peepoople.com – innovation with an enormous impact!
Next Volvo Cars and Volvo Trucks presented similar challenges: How to share product data based on external collaboration. The challenge of Volvo Cars is that it has gone through different ownerships and they require a more and more flexible infrastructure to share data. It is not about data pushing to a supplier anymore, it is about integrating partners where you have to share a particular part of your IP with the partner. And where the homegrown KPD system is working well for internal execution, it was never designed for partner sharing and collaboration. Volvo Cars implemented a Shared Technology Control application outside the firewall based on Share-A-space, where inside and outside data is mapped and connected. See their summary below. A pragmatic approach which is bringing direct benefits.
Concluding from the Volvo sessions: Apparently it ‘s hard to extend an existing system or infrastructure for secure collaboration with an external partner. The complexity of access right, different naming conventions, etc. Instead of that it is more pragmatic to have an intermediate system in the middle, like Share-A-space, that connects both worlds. The big advantage of Share-A-space is that the platform is based on the ISO 10303 (PLCS) standard and, therefore, has one of the characteristics of a real platform: openness based on standards.
Jonas Hammerberg from the Awesome Group closed day one with an inspiring and eye-opening presentation: Make PLM – The Why and How with Gamification FUN.
Jonas started to describe the behavioral drivers new generations have based on immediate feedback for the feeling of achievement, pride and status and being in a leading environment combined with the feelings of being in a group feeling friendship, trust, and love.
Current organizations are not addressing these different behaviors, it leads to disengagement at the office / work floor as Jonas showed from a survey held in Sweden – see figure. The intrinsic motivation is missing. One of the topics that concerns me the most when seeing current PLM implementations.
The Awesome group has developed apps and plug-ins for existing software, office and PLM bring in the feelings of autonomy, mastery and purpose to the individual performing in teams. Direct feedback and stimulating team and individual performance as part of the job.
By doing so the organization also gets feedback on the behavior, activity, collaboration and knowledge sharing of individuals and how this related to their performance. An interesting concept to be implemented in situations where gamification makes sense.
Owe Lind and Magnus Lidström from Scania talked about their Remote Diagnostics approach where diagnostic readings can be received from a car through a mobile phone network either to support preventive maintenance or actual diagnostics on the road and provide support.
Interesting Owe and Magnus were not using the word IoT (Internet of Things) at all, a hype related to these capabilities. Have a look here on YouTube
There was no chance to fall asleep after lunch, where Robin Teigland from the Stockholm School of Economics took us in a whirlwind through several trends under the title: The Third Revolution – exploring new forms of value creation through doing more with less.
The decomposition of traditional business into smaller and must faster communities undermine traditional markets. Also concepts like Uber, Bitcoin becoming a serious threat. The business change as a result of connectivity and communities leading to more and more networks of skills bringing together knowledge to design a car (Local Motors), funding (Kickstarter) – and it is all about sharing knowledge instead of keeping it inside – sharing creates the momentum in the world. You can look at Robin’s presentation(s) at Slideshare here.
All very positive trends for the future, however, a big threat to the currently established companies. Robin named it the Third Revolution which is in line with what we are discussing in our PLM world, although some of us call it even the Fourth Revolution (Industry 4.0).
Professor Martin Eigner from the Technical University of Kaiserslautern brought us back to reality in his presentation: Industry 4.0 or Industrial Internet: What is the impact for PLM?
Martin stood at the base for what we call PLM and already for several years he is explaining to us that the classical definition for PLM is too narrow. More and more we are developing systems instead of products. Therefore, he prefers the abbreviation SysLM, which is more than 3 characters and therefore probably hard to accept by the industry.
System development and, therefore, multidisciplinary development of systems introduces a new complexity. Traditional change management for Mechanical CAD (ECO/ECR) is entirely different from how software change management is handled (baselines / branches related to features). The way systems are designed, require a different methodology where systems engineering is an integral part of the development process, see Model-Based Systems Engineering (MBSE).
Next Martin discussed 4 potential IT-architectures where, based on the “products” and business needs, a different balance of PLM, ALM or ERP activities is required.
Martin’s final point was about the need for standards support these architectures, bringing together OSLC, PCLS, etc.
Standards are necessary for fast and affordable integrations and data exchange.
The first topic is related to big data and analytics. Many are trying to get a grip on big data with analytics. However, the real benefit of big data comes when you are able to apply algorithms to it. Gartner just made an interesting statement related to big data (below) and Marc Halpern added to this quote that there is an intrinsic need for data standards in order to apply algorithms.
When algorithms can be used, classical processes like ECO, ECR or managers might become obsolete and even a jobs like an accountant is at risk. This as predicted in article in the Economist in February 2014 – the onrushing Wave
The second topic, where I believe we are still hesitating too long at management level, is making decisions, to anticipate the upcoming digital wave and all of its side effects. We see a huge wave coming. If we do not mobilize the people, this wave might be a tsunami for those still at the seaside
Conclusion: PDT2015 was an inspiring, well-balanced conference with excellent opportunity to network with all people attending. For those interested in the details of the PLM future and standards an ideal opportunity to get up to date. And next the challenge: Make it happen at your company!
.. if you reach this point, my compliments for your persistency to read it all. Too long for a blog post and even here I had to strip
In my series describing the best practices related to a (PLM) data model, I described the general principles, the need for products and parts, the relation between CAD documents and the EBOM, the topic of classification and now the sensitive relation between EBOM and MBOM.
First some statements to set the scene:
- The EBOM represents the engineering (design) view of a product, structured in a way that it represents the multidisciplinary view of the functional definition of the product. The EBOM combined with its related specification documents, models, drawings, annotations should give a 100 % clear definition of the product.
- The MBOM represents the manufacturing view of a product, structured in a way that represents the way the product is manufactured. This structure is most of the time not the same as the EBOM, due to the manufacturing process and purchasing of parts.
A (very) simplified picture illustrating the difference between an EBOM and a MBOM. If the Car was a diesel there would be also embedded software in both BOMs (currently hidden)
For many years, the ERP systems have claimed ownership of the MBOM for two reasons
- Historically the MBOM was the starting point for production. Where the engineering department often worked with a set of tools, the ERP system was the system where data was connected and used to have a manufacturing plan and real-time execution
- To accommodate a more advanced integration with PDM systems, ERP vendors began to offer an EBOM capability also in their system as PDM systems often worked around the EBOM.
These two approaches made it hard to implement “real” PLM where (BOM) data is flowing through an organization instead of stored in a single system.
By claiming ownership of the BOM by ERP, some problems came up:
- A disconnect between the iterative engineering domain and the execution driven ERP domain. The EBOM is under continuous change (unless you have a simple or the ultimate product) and these changes are all related to upstream information, specifications, requirements, engineering changes and design changes. An ERP system is not intended for handling iterative processes, therefore forcing the user to work in a complex environment or trying to fix the issue through heavy customization on the ERP side.
- Global manufacturing and outsourced manufacturing introduced a new challenge for ERP-centric implementations. This would require all manufacturing sites also the outsourced manufacturers the same capabilities to transfer an EBOM into a local MBOM. And how do you capitalize the IP from your products when information is handled in a dispersed environment?
The solution to this problem is to extend your PDM implementation towards a “real” PLM implementation providing the support for EBOM, MBOM, and potential plant specific MBOM. All in a single system / user-experience designed to manage change and to allow all users to work in a global collaborative way around the product. MBOM information then will then be pushed when needed to the (local) ERP system, managing the execution.
Note 1: Pushing the MBOM to ERP does not mean a one-time big bang. When manufacturing parts are defined and sourced, there will already be a part definition in the ERP system too, as logistical information must come from ERP. The final push to ERP is, therefore, more a release to ERP combined with execution information (when / related to which order).
In this scenario, the MBOM will be already in ERP containing engineering data complemented with manufacturing data. Therefore from the PLM side we talk more about sharing BOM information instead of owning. Certain disciplines have the responsibility for particular properties of the BOM, but no single ownership.
Note 2: The whole concept of EBOM and MBOM makes only sense if you have to deliver repetitive products. For a one-off product, more a project, the engineering process will have the manufacturing already in mind. No need for a transition between EBOM and MBOM, it would only slow down the delivery.
Now let´s look at some EBOM-MBOM specifics
EBOM phantom assemblies
When extracting an EBOM directly from a 3D CAD structure, there might be subassemblies in the EBOM due to a logical grouping of certain items. You do not want to see these phantom assemblies in the MBOM as they only complicate the structuring of the MBOM or lead to phantom activities. In an EBOM-MBOM transition these phantom assemblies should disappear and the underlying end items should be linked to the higher level.
In the EBOM, there might be materials like a rubber tube with a certain length, a strip with a certain length, etc. These materials cannot be purchased in these exact dimensions. Part of the EBOM to MBOM transition is to translate these EBOM items (specifying the exact material) into purchasable MBOM items combined with a fitting operation.
EBOM end-items (make)
For make end-items, there are usually approved manufacturers defined and it is desirable to have multiple manufacturers (certified through the AML) for make end-items, depending on cost, capacity and where the product needs to be manufactured. Therefore, a make end-item in the EBOM will not appear in a resolved MBOM.
EBOM end-items (buy)
For buy end-items, there is usually a combination of approved manufacturers (AML) combined with approved vendors (AVL). The approved manufacturers are defined by engineering, based on part specifications. Approved vendors are defined by manufacturing combined with purchasing based on the approved manufacturers and logistical or commercial conditions
Are EBOM items and MBOM items different?
There is a debate if EBOM items should/could appear in an MBOM or that EBOM items are only in the EBOM and connected to resolved items in the MBOM. Based on the previous descriptions of the various EBOM items, you can conclude that a resolved MBOM does not contain EBOM items anymore in case of multiple sourcing. Only when you have a single manufacturer for an EBOM item, the EBOM item could appear in the MBOM. Perhaps this is current in your company, but will this stay the same in the future?
It is up to your business process and type of product which direction you choose. Coming back to one-off products, here is does not make sense to have multiple manufacturers. In that case, you will see that the EBOM item behaves at the same time as an MBOM item.
What about part numbering?
Luckily I reached the 1000 words so let´s be short on this debate. In case you want an automated flow of information between PLM and ERP, it is important that shared data is connected through a unique identifier.
Automation does no need intelligent numbering. Therefore giving parts in the PLM system and the ERP system a unique, meaningless number you ensure guaranteed digital connectivity.
If you want to have additional attributes on the PLM or ERP side that describe the part with a number relevant for human identification on the engineering side or later at the manufacturing side (labeling), this all can be solved.
An interesting result of this approach is that a revision of a part is no longer visible on the ERP side (unless you insist). Each version of the MBOM parts is pointing to a unique version of an MBOM part in ERP, providing an error free sharing of data.
Life can be simple if you generalize and if there was no past, no legacy and no ownership of data thinking. The transition of EBOM to MBOM is the crucial point where the real PLM vision is applied. If there is no data sharing on MBOM level, there are two silos, the characteristic of the old linear past.
(See also: From a linear world to a circular and fast)
What do you think? Is more complexity needed?
I will be soon discussing these topics at the PDT2015 in Stockholm on October 13-14. Will you be there ?
And for Dutch/Belgium readers – October 8th in Bunnik:
Op 8 oktober ben ik op het BIM Open 2015 Congres in Bunnik waar ik de overeenkomsten tussen PLM en BIM zal bespreken en wat de constructie industrie kan leren van PLM
This is a post I published on LinkedIn on July 28th related to a discussion around Excel and PLM usage and usability.
Reposted for my blog subscribers.
This post is written in the context of two posts that recently caught my attention. One post from Lionel Grealou – comparing PLM and Excel collaboration and reaction on this post and its comments by Oleg Shilovitsky – PLM Need for speed.
Both posts discuss the difference between Excel (easy to use / easy to deploy ) and a PLM system (complex to use / complicated deployment). And when you read both posts you would believe that it is mainly deployment and usability that are blocking PLM systems to be used instead of Excel.
Then I realized this cannot be the case. If usability and deployment were blocking issues for an enterprise system, how would it be possible that the most infamous system for usability, SAP, it one of the top-selling enterprise applications. Probably SAP is the best-selling enterprise application. In addition, I have never heard about any company mentioning SAP is easy to deploy. So what is the difference?
I assume if Excel had existed in its current state in the early days of MRP, people might be tempted to use Excel for some ERP functions. However they would soon realize that Excel is error prone and when you buy the wrong materials or when make errors in your resource scheduling, soon you would try to solve it in a more secure way. Using an ERP system.
ERP systems have never been sold to the users for their usability. It is more that the management is looking for guarantees that the execution process is under control. Minimize the potential for errors and try to automate all activities as much as possible. As the production process is directly linked to finance, it is crucial to have it under control. Goodbye usability, safety first.
Why is this approach not accepted for PLM?
Why do we talk about usability?
First of all, the roots for PLM come from the engineering department (PDM) and, therefore, their primary data management system was not considered an enterprise system. And when you implement a system for a department, discussions will be at the user level. So user acceptance became necessary for PDM and PLM.
But this is not the main reason. Innovation, Product Development, Sales Engineering, Engineering are all iterative activities. In contrary to ERP, there is no linear process defined how to develop the ultimate product the first time right. Although this believe existed in the nineties by an ERP country manager that I met that time. He told me
“Engineers are resources that do not want to be managed, but we will get them.”
An absurd statement I hope you agree. However, the thoughts behind this statement are correct. How do you make sure product development is done in the most efficient manner?
If you look at large enterprises in the aerospace or automotive industry, they implemented PLM, which for sure was not user-friendly. Why did they implement PLM? As they did not want to fix the errors, an Excel-like implementation would bring.
Using Excel has a lot of hidden costs. How to make sure you work with the right version as multiple copies exist? How do you know if the Excel does not contain any type indicating wrong parts? You will learn this only once it is too late. How do you understand the related information to the Excel (CAD files, specifications, etc., etc.)? All lead to a lot of extra manual work depending on the accuracy and discipline of every employee in the company. Large enterprises do not want to be dependent on individual skills.
Large enterprise have shown that it is not about usability in the first place if you wish to control the data. Like for ERP systems, they are aware of the need for PLM with reduced usability above being (fl)Exel with all its related inconvenience.
I believe when there is a discussion about PLM or Excel, we have not reached the needed conceptual level to implement PLM. PLM is about sharing data and breaking down silos. Sharing allows better and faster collaboration, maintaining quality, and this is what companies want to achieve. Therefore the title: How do you measure collaboration. This is the process you wish to optimize, and I suspect that when you would compare user-friendly collaboration with Excel with less user-friendly PLM, you might discover PLM is more efficient.
Therefore stop comparing Excel and PLM. It is all about enabling collaboration and changing people to work together (the biggest challenge – more than usability).
Conclusion: Once we have agreed on that concept, PLM value is about collaboration, there is always to hope to enhance usability. Even SAP is working on that – it is an enterprise software issue.
Someone notified me that not everyone subscribed to my blog necessary will read my posts on LinkedIn. Therefore I will repost the upcoming weeks some of my more business oriented posts from LinkedIn here too. This post was from July 3rd and an introduction to all the methodology post I am currently publishing.
The importance of a (PLM) data model
What makes it so hard to implement PLM in a correct manner and why is this often a mission impossible? I have been asking myself this question the past ten years again and again. For sure a lot has to do with the culture and legacy every organization has. Imagine if a company could start from scratch with PLM. How would they implement PLM nowadays?
My conclusion for both situations is that it all leads to a correct (PLM) data model, allowing companies to store their data in an object-oriented manner. In this way reflecting the behavior the information objects have and the way they mature through their information lifecycle. If you making compromises here, it has an effect on your implementation, the way processes are supported out-of-the-box by a PLM system or how information can be shared with other enterprise systems, in particular, ERP. PLM is written between parenthesis as I believe in the future we do not talk PLM or ERP separate anymore – we will talk business.
Let me illustrate this academic statement.
A mid-market example
When I worked with SmarTeam in the nineties, the system was designed more as a PDM system than a PLM system. The principal objects were Projects, Documents, and Items. The Documents had a sub-grouping in Office documents and CAD documents. And the system had a single lifecycle which was very basic and designed for documents. Thanks to the flexibility of the system you could quickly implement a satisfactory environment for the engineering department. Problems (and customizations) came when you wanted to connect the data to the other departments in the company.
The sales and marketing department defines and sells products. Products were not part of the initial data model, so people misused the Project object for that. To connect to manufacturing a BOM (Bill of Material) was needed. As the connected 3D CAD system generated a structure while saving the assemblies, people start to consider this structure as the EBOM. This might work if your projects are mechanical only.
However, a Document is not the same as a Part. A Document has a complete different behavior as a Part. Documents have continuous iterations, with a check-in/checkout mechanism, where the Part definition remains unchanged and gets meanwhile a higher maturity.
The correct approach is to have the EBOM Part structure, where Part connect to the Documents. And yes, Documents can also have a structure, but it is not a BOM. SmarTeam implemented this around 2004. Meanwhile, a lot of companies had implemented their custom solution for EBOM by customization not matching this approach. This created a first level of legacy.
When SmarTeam implemented Part behavior, it became possible to create a multidisciplinary EBOM, and the next logical step was, of course, to connect the data to the ERP system. At that time, most implementations have been pushing the EBOM to the ERP system and let it live there further. ERP was the enterprise tool, SmarTeam the engineering tool. The information became disconnected in an IT-manner. Applying changes and defining a manufacturing BOM was done manually in the ERP system and could be done by (experienced) people that do not make mistakes.
Next challenge comes when you want to automate the connection to ERP. In that case, it became apparent that the EBOM and MBOM should reside in the same system. (See old and still actual post with comments here: Where is the MBOM) In one system to manage changes and to be able to implement these changes quickly without too much human intervention. And as the EBOM is usually created in the PLM system, the (commercial/emotional) PLM-ERP battle started. “Who owns the part definition”, “Who owns the MBOM definition” became the topic of many PLM implementations. The real questions should be: “Who is responsible for which attributes of the Part ?” and “Who is responsible for which part of the MBOM definition ?” as data should be shared not owned.
The SmarTeam evolution shows how a changing scope and an incomplete/incorrect data model leads to costly rework when aligning to the mainstream. And this is happening with many implementation and other PLM systems. In particular when the path is to grow from PDM to PLM. An important question remains what is going to be mainstream in the future. More on that in my conclusion.
A complex enterprise example
In the recent years, I have been involved in several PLM discussions with large enterprises. These enterprises suffer from their legacy. Often the original data management was not defined in an object-oriented manner, and the implementation has been expanding with connected and disconnected systems like a big spaghetti bowl.
The main message most of the time is:
“Don’t touch the systems it as it works for us”.
The underlying message is;
“We would love to change to a modern approach, but we understand it will be a painful exercise and how will it impact profitability and execution of our company”
The challenge these companies have is that it extremely hard to imagine the potential to-be situation and how it is affected by the legacy. In a project that I participated several years ago the company was migrating from a mainframe database towards a standard object-oriented (PLM) data model. The biggest pain was in mapping data towards the object-oriented data model. As the original mainframe database had all kind of tables with flags and mixed Part & Document data, it was almost impossible to make a 100 % conversion. The other challenge was that knowledge of the old system had vaporized. The result at the end was a customized PLM data model, closer to current reality, still containing legacy “tricks” to assure compatibility.
All these enterprises at a particular time have to go through such a painful exercise. When is the best moment? When business is booming, nobody wants to slow-down. When business is in a lower gear, costs and investments are minimized to keep the old engine running efficiently. I believe the latter would be the best moment to invest in making the transition if you believe your business will still exist in 10 years from now.
Back to the data model.
Businesses should have today a high-level object-oriented data model, describing the main information objects and their behavior in your organization. The term Master Data Management is related to this. How many companies have the time and skills to implement a future-oriented data model? And the data model must stay flexible for the future.
Once you have a business data model, you are able to implement processes on top of it. Processes can change over time, therefore, avoid hard-coding specific processes in your enterprise systems. Like the brain, we can change our behavior (applying new processes) still it will be based on the data model stored inside our brain.
A lot of enterprise PLM implementations are in a challenging situation due to legacy or incomplete understanding and availability of an enterprise data model. Therefore cross-department implementations and connecting others systems are considered as a battle between systems and their proprietary capabilities.
The future will be based on business platforms and realizing this take years – imagine openness and usage of data standards. An interesting conference to attend in the near future for this purpose is the PDT2015 conference in Stockholm.
Meanwhile I also learned that a one-day Master Data Management workshop will be held before the PDT2015 conference starts on the 12th of October. A good opportunity to deep-dive for three days !