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Last week I attended the PI conference in Munich, which has become a tradition since 2011. Personally, I have been busy moving houses, so blogging has not been my priority recently. However, the PI Conference for me is still one of the major events happening in Europe. Excellent for networking and good for understanding what is going on in the world of PLM. Approximate 200 delegates attended from various industries and. Therefore, the two days were good to find and meet the right people.
As the conference has many parallel sessions, I will give some of the highlights here. The beauty of this conference is that all sessions are recorded. I am looking forward to catch-up with other meetings in the upcoming weeks. Here some of the highlights of the sessions that I attended.
Some of the highlights
The first keynote session was from Mark Gallagher with the title: High-Performance Innovation in Formula One. Mark took us through the past and current innovations that have been taken place in the F1. I was involved some years ago in a PLM discussion with one of the F1 team.
I believe F1 is a dream for engineers and innovators. Instead of a long time to market, in F1, it is all about bringing innovation to the team as fast as possible. And interesting to see IoT, direct feedback from the car during the race is already a “commodity” in F1 – see the picture. Now we need to industrialize it.
Peter Bilello (CIMdata) took us through The Future Sustainability of PLM. One of the big challenges for PLM implementations is to make the sustainable. Currently, we see many PLM implementations reaching a state of obsolescence, no longer able to support the modern business for various reasons.
Change of owner, mergers, a different type of product, the importance of software. All of these reasons can become a significant challenge when your PLM implementation has been tuned to support the past.
How to be ready for the future. Peter concluded that companies need to be pro-active manage their systems and PLM platforms might give an answer for the future. However, these platforms need to be open and rely on standards, to avoid locking in data in the platform.
Final comment: To stay competitive in the future companies need to have an adequate strategy and vision.
Gary Knight, PLM Business Architecture Manager from Jaguar Land Rover, gave an impressive presentation about the complete approach JLR has executed. Yes, there is the technical solution. However the required cultural change and business change to align the vision with execution on the floor are as important. Making people enthusiastic and take part in realizing the future.
The traditional productivity dip during a business transformation has been well supported by intensive change management support, allowing the company to keep the performance level equal without putting its employees under big pressure. Many companies I have seen could learn from that.
PLM and ERP
In the afternoon, I moderated a focus group related to PLM and ERP integration challenges. An old-fashioned topic you might think. However, the room was full of people (too many) all hoping to find the answers they need. Some conclusions:
- Understanding the difference between owning data and sharing data. Where sharing still requires certain roles to be responsible for particular data sets.
- First define the desired process how information should flow between roles in the organization without thinking in tools. Once a common agreement exists, a technical realization will not be the bottleneck.
- PLM and ERP integrations vary per primary process (ETO, BTO, CTO, and MTS). In each of these processes the interaction between PLM and ERP will be different due to timing issues or delivery model
Irene Gustafson from Volvo Cars explained the integration concept with partners / suppliers based on Eurostep´s ShareAspace. I wrote about this concept in my blog post: The weekend after PDT2015. Meanwhile, the concept of a collaboration hub instead of direct integration between an OEM and its supplier has become more traction.
Irene Gustafson made some interesting closing statements
- Integration should not be built into the internal structure, it takes away flexibility
- A large portion of collaborative data is important here and now. Long term only a limited part of that data will need to be saved
Eurostep announced their new upcoming releases based on different collaboration scenarios, InReach, InControl and InLife. These packages allow fast and more OOTB deployment of their collaboration hub (based on de PLCS standard)
Digital Transformation at Philips and GE
Anosh Thakkar, Chief Technology Officer from Philips, explained their digital business transformation from pushing products to the markets towards a HealthTech company, leaving the lightning division behind. Philips used three “transformers” to guide the business change:
- From Complex to Simple, aligning businesses to 4 simplified business model (instead of 75) and one process framework supported by core IT platforms reducing customizations and many applications (from 8000 to 1000)
- From Analog to Digital, connecting customer devices through a robust cloud-based platform. A typical example of modern digital businesses
- From Products to Solution, again with a focus on the end-user how they could work in an ideal way instead of delivering a device (the Experience economy)
Ronan Stephan, chief scientist of GE, presented the digital business transformation is working on. Ronan took us through the transformation models of Amazon, Apple, and Google, explaining how their platforms and the insight coming from platform information have allowed these companies to be extremely successful. GE is aiming to be the leader in the digital industry, connecting their company with all their customers (aerospace, transportation, power & healthcare) on their Predix platform.
On the second day, I presented to a relatively small audience (5 parallel sessions – all interesting) a session with the title: The PLM Identity crisis. Luckily there were still people in the conference that have the feeling something is changing in PLM. My main message was that PLM like everything else in the current world suffers from rapid changing business models (hardware products towards software driven systems) and lack of time to distinguish between facts and opinions. The world of one-liners. To my opinion existing PLM, concepts are no longer enough, however, the PLM market still is mainly based on classical linear thinking as my generation (the baby boomers) are still leading the business. Have a look at the presentation here, of find a nice complementary related post from my blog buddy Oleg Shilovitsky here.
As I am in the middle of moving houses, now in no man’s land, I do not have the time and comfortable environment to write a more extensive review this time. Perhaps I will come back with some other interesting thoughts from this conference after having seen more recordings.
My observation after the conference:
A year ago I wrote The Weekend After Product Innovation 2015 in Düsseldorf where managing software in the context of PLM was the new topic. This year you could see the fast change as now IoT platforms and M2M communication was the main theme. The digital revolution is coming …..
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.
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)
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
In my previous post describing the various facets of the EBOM, I mentioned several times classification as an important topic related to the PLM data model. Classification is crucial to support people to reuse information and, in addition, there are business processes that are only relevant for a particular class of information, so it is not only related to search/reuse support.
In 2008, I wrote a post about classification, you can read it here. Meanwhile, the world has moved on, and I believe more modern classification methods exist.
Why classification ?
First of all classification is used to structure information and to support retrieval of the information at a later moment, either for reuse or for reference later in the product lifecycle. Related to reuse, companies can save significant money when parts are reused. It is not only the design time or sourcing time that is reduced. Additional benefits are lower risks for errors (fewer discoveries), reduced process and approval time (human overhead), reduced stock (if applicable), and more volume discount (if applicable) and reduced End-Of-Life handling.
Classification can also be used to control access to certain information (mainly document classification), or classification can be used to make sure certain processes are followed, e.g. export control, hazardous materials, budget approvals, etc. Although I will speak mainly about part classification in this post, classification can be used for any type of information in the PLM data model.
Depending on the industry you are working in, there are various classification standards for parts. When I worked in the German-speaking countries (the DACH-länder) the most discussed classification at that time was DIN4000 (Sachmerkmal-liste), a must have standard for many of the small and medium sized manufacturing companies. The DIN 4000 standard had a predefined part hierarchy and did not describe the necessary properties per class. I haven’t met a similar standard in other countries at that time.
Another very generic classification I have seen are the UNSPC standard, again a hierarchical classification supporting everything in the universe but no definition of attributes.
Other classification standards like ISO13399, RosettaNET, ISO15926 and IFC exist to support collaboration and/or the supply chain. When you want to exchange data with other disciplines or partners. The advantage of a standard definition (with attributes) is that you can exchange data with less human processing (saving labor costs and time – the benefit of a digital enterprise).
I will not go deeper into the various standards here as I am not the expert for all the standards. Every industry has its own classification standards, a hierarchical standard, and if more advanced the hierarchy is also supported by attributes related to each class. But let´s go into the data model part.
Classification and data model
The first lesson I learned when implementing PLM was that you should not build your classification hard-coded into the PLM, data model. When working with SmarTeam is was very easy to define part classes and attributes to inherit. Some customers had more than 300 classes represented in their data model just for parts. You can imagine that it looks nice in a demo. However when it comes to reality, a hard-coded classification becomes a pain in the model. (left image, one of the bad examples from the past)
1 – First of all, classification should be dynamic, easy to extend.
2 – The second problem however with a hard-coded classification was that once a part is defined for the first time the information object has a fixed class. Later changes need a lot of work (relinking of information / approval processes for the new information).
3 – Finally, the third point against a hard-coded classification is that it is likely that parts will be classified according to different classifications at the same time. The image bellow shows such a multiple classification.
So the best approach is to have a generic part definition in your data model and perhaps a few subtypes. Companies tend to differentiate still between hardware (mechanical / electrical) parts and software parts.
Next a part should be assigned at least to one class, and the assignment to this class would bring more attributes to the part. Most of the PLM systems that support classification have the ability to navigate through a class hierarchy and find similar parts.
When parts are relevant for ERP they might belong to a manufacturing parts class, which add particular attributes required for a smooth PLM – ERP link. Manufacturing part types can be used as templates for ERP to be completed.
Think part of the challenge moving forward is we’ve always handled these as parts under different methodologies, which requires specific data structures for each, etc. The next gen take on all this needs to be more malleable perhaps. So there are just parts. Be they service or make/buy or some combination – say a long lead functional standard part and they would acquire the properties, synchronizations, and behaviors accordingly. People have trouble picking the right bucket, and sometimes the buckets change. Let the infrastructure do the work. That would help the burden of multiple transitions, where CAD BOM to EBOM to MBOM to SBOM eventually ends up in a chain of confusion.
I fully agree with his statement and consider this as the future trend of modern PLM: Shared data that will be enriched by different usage through the lifecycle.
Why don’t we classify all data in PLM?
There are two challenges for classification in general.
- The first one is that the value of classification only becomes visible in the long-term, and I have seen several young companies that were only focusing on engineering. No metadata in the file properties, no part-centric data management structure and several years later they face the lack of visibility what has been done in the past. Only if one of the engineers remembers a similar situation, there is a chance of reuse.
- The second challenge is that through a merger or acquisition suddenly the company has to manage two classifications. If the data model was clean (no hard-coded subclasses) there is hope to merge the information together. Otherwise, it might become a painful activity to discover similarities.
SO THINK AHEAD EVEN IF YOU DO NOT SEE THE NEED NOW !
Modern search based applications
There are ways to improve classification and reuse by using search-based application which can index archives and try to find similarity in properties / attributes. Again if the engineers never filled the properties in the CAD model, there is little to nothing to recover as I experienced in a customer situation. My PLM US peer, Dick Bourke, wrote several articles about search-based applications and classification for engineering.com, which are interesting to read if you want to learn more: Useful Search Applications for Finding Engineering Data
So much to discuss on this topic, however I reached my 1000 words again
Classification brings benefits for reuse and discovery of information although benefits are long-term. Think long-term too when you define classifications. Keep the data model simple and add attributes groups to parts based on functional classifications. This enables a data-driven PLM implementation where the power is in the attributes not longer in the part number. In the future, search-based applications will offer a quick start to classify and structure data.
Two weeks ago I got this message from WordPress, reminding me that I started blogging about PLM on May 22nd in 2008. During some of my spare time during weekends, I began to read my old posts again and started to fix links that have been disappearing.
Initially when I started blogging, I wanted to educate mid-market companies about PLM. A sentence with a lot of ambiguities. How do you define the mid-market and how do you define PLM are already a good start for a boring discussion. And as I do not want to go into a discussion, here are my “definitions”
Warning: This is a long post, full of generalizations and a conclusion.
PLM and Mid-market
The mid-market companies can be characterized as having a low-level of staff for IT and strategic thinking. Mid-market companies are do-ers and most of the time they are good in their domain based on their IP and flexibility to deliver this to their customer base. I did not meet mid-market companies with a 5-year and beyond business vision. Mid-market companies buy systems. They bought an ERP system 25-30 years ago (the biggest trauma at that time). They renewed their ERP system for the Y2K problem/fear and they switched from drawing board towards a 2D CAD system. Later they bought a 3D CAD system, introducing the need for a PDM system to manage all data.
PLM is for me a vision, a business approach supported by an IT-infrastructure that allows companies to share and discover and connect product related information through the whole lifecycle. PLM enables companies to react earlier and better in the go-to-market process. Better by involving customer inputs and experience from the start in the concept and design phases. Earlier thanks to sharing and involving other disciplines/suppliers before crucial decisions are made, reducing the amount of iterations and the higher costs of late changes.
Seven years ago I believed that a packaged solution, combined with a pre-configured environment and standard processes would be the answer for mid-market companies. The same thought currently PLM vendors have with a cloud-based solution. Take it, us it as it is and enjoy.
Here I have changed my opinion in the past seven years. Mid-market companies consider PLM as a more complex extension of PDM and still consider ERP (and what comes with that system) as the primary system in the enterprise. PLM in mid-market companies is often seen as an engineering tool.
LESSON 1 for me:
The benefits of PLM are not well-understood by the mid-market
To read more:
Globalization and Education
In the past seven years, globalization became an important factor for all type of companies. Companies started offshoring labor intensive work to low-labor-cost countries introducing the need for sharing product data outside their local and controlled premises. Also, acquisitions by larger enterprises and by some of the dominant mid-market companies, these acquisitions introduced a new area of rethinking. Acquisitions introduced discussions about: what are real best practices for our organization? How can we remain flexible, meanwhile adapt and converge our business processes to be future ready?
Here I saw two major trends in the mid-market:
Lack of (PLM) Education
To understand and implement the value of PLM, you need to have skills and understanding of more than just a vendor-specific PLM system. You need to understand the basics of change processes (Engineering Change Request, Engineering Change Order, Manufacturing Change Order and more). And you need to understand the characteristics of a CAD document structure, a (multidisciplinary) EBOM, the MBOM (generic and/or plant specific) and the related Bill of Processes. This education does not exist in many countries and people are (mis-)guided by their PLM/ERP vendor, explaining why their system is the only system that can do the job.
Interesting enough the most read posts on my blog are about the MBOM, the ETO, BTO and CTO processes. This illustrates there is a need for a proper, vendor-independent and global accepted terminology for PLM
Some educational posts:
Bill of Materials for Dummies – ETO ranked #1
ECR/ECO for Dummies ranked #2
BOM for Dummies – CTO ranked #4
BOM for Dummies: BOM and CAD ranked #7
The dominance of ERP
As ERP systems were introduced long before PLM (and PDM), these systems are often considered by the management of a mid-market company as the core. All the other tools should be (preferably) seen as an extension of ERP and if possible, let´s implement ERP vendor´s functionality to support PLM – the Swiss knife approach – one tool for everything. This approach is understandable as at the board level there are no PLM discussions. Companies want to keep their “Let´s do it”-spirit and not reshuffle or reorganize their company, according to modern insights of sharing. Strangely enough, you see in many businesses the initiative to standardize on a single ERP system first, instead of standardizing on a single PLM approach first. PLM can bring the global benefits of product portfolio management and IP-sharing, where ERP is much more about local execution.
PLM is not understood at the board level, still considered as a tool
Some post related to PLM and ERP
Where is the MBOM ? ranked #3
The human factor
A lot of the reasons why PLM has the challenge to become successful have to do with its broad scope. PLM has an unclear definition and most important, PLM forces people to share data and work outside their comfort zones. Nobody likes to share by default. Sharing makes day-to-day life more complicated, sharing might create visibility on what you actually contribute or fix. In many of my posts, I described these issues from various viewpoints: the human brain, the innovators dilemma, the way the older generation (my generation) is raised and used to work. Combined with the fact that many initial PLM/PDM implementations have created so many legacies, the need to change has become a risk. In the discussion and selection of PLM I have seen many times that in the end a company decides to keep the old status quo (with new tools) instead of really having the guts to move toward the future. Often this was a result of investors not understanding (and willing to see) the long term benefits of PLM.
PLM requires a long-term vision and understanding, which most of the time does not fit current executive understanding (lack of education/time to educate) and priority (shareholders)
Many recent posts are about the human factor:
The digital transformation
The final and most significant upcoming change is the fact that we are entering a complete new era: From linear and predictable towards fast and iterative, meaning that classical ways we push products to the market will become obsolete. The traditional approach was based on lessons learned from mechanical products after the second world-war. Now through globalization and the importance of embedded software in our products, companies need to deliver and adapt products faster than the classical delivery process as their customers have higher expectations and a much larger range to choose from. The result from this global competitiveness is that companies will change from delivering products towards a more-and-more customer related business model (continuous upgrades/services). This requires companies to revisit their business and organization, which will be extremely difficult. Business wise and human change require new IT concepts – platform? / cloud services? / Big data?
Older enterprises, mid-market and large enterprises will be extremely challenged to make this change in the upcoming 10 years. It will be a matter of survival and I believe the Innovator´s Dilemma applies here the most.
The digital transformation is apparent as a trend for young companies and strategic consultants. This message is not yet understood at the board level of many businesses.
Some recent post related to this fast upcoming trend:
ROI (Return On Investment)
I also wrote about ROI – a difficult topic to address as in most discussions related to ROI, companies are talking about the costs of the implementation, not about the tremendous larger impact a new business approach or model can have, once enabled through PLM. Most PLM ROI discussions are related to efficiency and quality gains, which are significant and relevant. However these benefits are relative small and not comparable with the ability to change your business (model) to become more customer centric and stay in business.
Some of the ROI posts:
A (too) long post this time however perhaps a good post to mark 7 years of blogging and use it as a reference for the topics I briefly touched here. PLM has many aspects. You can do the further reading through the links.
From the statistics it is clear that the education part scores the best – see rankings. For future post, let me know by creating a comment what you are looking for in this blog: PLM Mid-Market, Education, PLM and ERP, Business Change, ROI, Digitalization, or …??
Also I have to remain customer centric – thanks for reading and providing your feedback
Three weeks ago there was the Product Innovation conference in Düsseldorf. In my earlier post (here) I described what I experienced during this event. Now, after all the information is somehow digested, here a more high-level post, describing the visible change in business and how it relates to PLM. Trying to describe this change in non-academic wording but in images. Therefore, I described the upcoming change in the title: from linear to circular and fast.
Let me explain this image step by step
In the middle of the previous century, we were thinking linear in education and in business. Everything had a predictable path and manufacturing companies were pushing their products to the market. First local, later in time, more global. Still the delivery process was pretty linear:
This linear approach is reflected in how organizations are structured, how they are aligned to the different steps of the product development and manufacturing process. Below a slide I used at the end of the nineties to describe the situation and the pain; lack of visibility what happens overall.
It is discouraging to see that this situation still exists in many companies.
At the end of the nineties, early 2000, PLM was introduced, conceptually managing the whole lifecycle. In reality, it was mainly a more tight connection between design and manufacturing preparation, pushing data into ERP. The main purpose was managing the collaboration between different design disciplines and dispersed teams.
Jim Brown (Tech-Clarity) wrote at that time a white paper, which is still valid for many businesses, describing the complementary roles of PLM and ERP. See the picture below:
Jim introduced the circle and the arrow. PLM: a circle with iterations, interacting with ERP: the arrow for execution. Here visual it became already clear an arrow does not have the same behavior as a circle. The 100 % linearity in business was gone.
Let´s have a closer look at the PLM circle
This is how PLM is deployed in most organizations:
Information is pushed in the ERP system as disconnected information, no longer managed and connected to its design intent.
Next, the ERP system is most of the time not well-equipped for managing after sales and services content. Another disconnect comes up.
Yes, spare parts could be ordered through ERP, but issues appearing at the customer base are not stored in ERP, often stored in a separate system again (if stored beyond email).
The result is that when working in the concept phase, there is no information available for R&D to have a good understanding of how the market or customers work with their product. So how good will it be? Check in your company how well your R&D is connected with the field?
And then the change started …
This could have stayed reality for a long time if there were not a huge business change upcoming. The world becomes digital and connected. As a result, local inefficiencies or regional underperformance will be replaced by better-performing companies. The Darwin principle. And most likely the better performing companies are coming from the emerging markets as there they do not suffer from the historical processes and “knowledge of the past”. They can step into the digital world much faster.
In parallel with these fast growing emerging markets, we discovered that we have to reconsider the ways we use our natural resources to guarantee a future for next generations. Instead of spilling resources to deliver our products, there is a need to reuse materials and resources, introducing a new circle: the circular economy.
The circular economy can have an impact on how companies bring products to the market. Instead of buying products (CAPEX) more and more organizations (and modern people) start using products or services in a rental model (OPEX). No capital investment anymore, pay as you go for usage or capacity.
The digital and connected world can have a huge impact on the products or services available in the near future. You are probably familiar with the buzz around “The Internet of Things” or “Smart and Connected”.
No longer are products depending on mechanical behavior only, more and more products are relying on electrical components with adaptive behavior through software. Devices that connect with their environment report back information to the manufacturer. This allows companies to understand what happens with their products in the field and how to react on that.
Remember the first PLM circle?
Now we can create continuity of data !
Combine the circular economy, the digital and connected world and you will discover everything can go much faster. A crucial inhibitor is how companies can reorganize themselves around this faster changing, circular approach. Companies need to understand and react to market trends in the fastest and adequate way. The future will be probably about lower volumes of the same products, higher variability towards the market and most likely more and more combining products with services (the Experience Model). This requires a flexible organization and most likely a new business model which will differ from the sequential, hierarchical organizations that we know at this moment.
The future business model ?
The flexibility in products and services will more and more come from embedded software or supported by software services. Software services will be more and more cloud based, to avoid IT-complexity and give scalability.
Software development and integration with products and services are already a challenge for classical mechanical companies. They are struggling to transform their mechanical-oriented design process towards support for software. In the long-term, the software design process could become the primary process, which would mean a change from (sequential – streamlined) lean towards (iterative – SCRUM) agile.
Once again, we see the linear process becoming challenged by the circular iterations.
This might be the end of lean organizations, potentially having to mix with agile conepts..
If it was a coincidence or not, I cannot judge, however during the PI Conference I learned about W.L. Gore & Associates, with their unique business model supporting this more dynamic future. No need to have a massive organization re-org to align the business, as the business is all the time aligning itself through its employees.
Last weekend, I discovered Semco Partners in the newspaper and I am sure there are more companies organizing themselves to become reactive instead of linear – for sure in high-tech world.
Linearity is disappearing in business, it is all about reactive, multidisciplinary teams within organizations in order to support customers and their fast changing demands.
Fast reactions need new business organizations models (flexible, non-hierarchical) and new IT-support models (business information platforms – no longer PLM/ERP system thinking)
What do you think ? The end of linear ?
I have talked enough about platforms recently. Still if you want to read more about it:
Engineering.com: Prod. Innovation Platform PlugnPlay in next generation PLM
Gartner: Product Innovation Platforms
VirtualDutchman: Platform, Backbone, Service Bus or BI