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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.
And this is one of the big benefits of a digital enterprise, reducing overhead in data handling, often reducing the cost of data handling with 50 % or more (people / customizations)
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.
Conclusion
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.
This time I would like to receive some feedback from my readers as I believe the topic I am discussing here might be similar to a PLM / ERP discussion – a discussion between religions. I have preached the past two years a more data-centric approach for PLM, instead of file management and related tot this data-centric approach, the concept of a PLM platform / Business Platform – CIMdata/ Innovation Platform – Gartner becomes clear.
What´s the issue?
As I wrote in my earlier post (random PLM future thoughts), I realized that talking about platforms is not that straight-forward when meeting companies with their history and terminology. Some claim they are already using a business platform, others have no clue what makes a platform different from a their current PLM implementation ? Therefore I will summarize the different approaches I have seen in my network and give a non-academic opinion as a base for discussion. Looking forward to your opinion.
The platform approach
My definition of a PLM platform:
- A central repository of data based on a core data model. Information is stored as data in a unique way
- On top of this repository, applications can run, using a subset of the overall data elements, proving dedicated functionality and user interface to a particular user / role
- Access to the platform is provided through web-technology. Storage could be on the cloud.
- External applications and data can be connected through an open (standardized?) API embedded or federated
- The PLM platform can be a collection of services and functionality coming from various vendors / suppliers – the app store concept
- The platform approach is THE DREAM for business, being flexible to combine and edit data in any desired context in dedicated apps / environments
In the PLM world, Dassault Systems with their 3DExperience approach is following this trend although here you might argue about the ease of use to add external apps to this platform – is it open ? Aras and Autodesk might also claim they have a PLM platform, where you might question the same and if the depth of the data model and the provided solutions on top of the data model are mature enough. Finally also SAP can be considered as a platform, but I would not name it a PLM platform at this moment in time. An important question for me would be: How can achieve openness of a PLM platform?
Your thoughts?
The PLM backbone approach
My definition of a PLM backbone:
- The core PLM functionality is provided by a single, proprietary PLM system
- Additional functionality that is not part of the core development (acquisitions) is connected to the backbone through proprietary interfaces
- External authoring tools are linked to the backbone through integrations or interfaces which could be developed by third parties
- External system can interface to the PLM backbone through open interfaces
- The PLM backbone is THE DREAM for engineering, as historically this was the domain where PLM started to be implemented
I would consider Siemens and PTC (see picture) the best examples of a PLM backbone approach with their PLM portfolio. Teamcenter and Windchill are both rich PLM systems further connected to several systems, covering the product lifecycle. I am not expert enough to state that the same conclusion is valid for Oracle´s Agile, where I believe the backbone is bigger than the PLM system. What do you think ? Will these PLM vendors also move to a platform approach? And what will be the platform?
The Service Bus approach
My understanding of the Service Bus (I am not an IT-expert):
- Service Bus has a standardized interface to request for data or to post data that needs to be stored in other systems
- The Service Bus approach reduces the amount of (custom) interfaces between systems by requiring standardized inputs and outputs per system
- Providing a user with information that is not entirely available in a single system, the service bus needs to acquire the data from other systems, which might not give a high-performance as expected by business people
- The Service Bus is the IT DREAM as it simplifies the complexity for IT to manage point-to-point solutions between systems and makes an upgrade strategy easier to support.
From a very high-level view, the service bus approach has some similarities to a platform. The service bus concept allows business to select the systems they like the most (provided they connect to the service bus) – Image property of IBM.com
The main difference would be the persistence of information, where is the real data stored? I came across the service bus approach more often in the past, where the target was most of the time to integrate the PDM functionality (PLM as an enterprise solution was never in scope here).
For the Service Bus approach, I am curious to learn its relevance for future PLM implementations as the challenge would be to provide any user in the company with the relevant information in context. Is the service bus going to be replaced by the platform? Who would be the major players here?
The Business Intelligence approach
This method I discovered in project-centric companies (Oil & Gas companies, EPCs, Construction companies) but strangely enough also at some manufacturing companies, where I would assume integration of systems would bring large benefits.
- Each type of information is managed only in one single system avoiding interfaces or duplication of data.
- Only where needed, data will be pushed from one system to other systems
- Business Intelligence applications extract information from the relevant system and present this in context to the user, giving him/her a better of understanding
- Business users will work have to work in multiple systems to complete their tasks
- The BI approach is the ULTIMATE IT DREAM as it simplifies their works dramatically and shuts down business demands.
I have seen an example where IT dictated that for document management we use product ABC (well-known Content Management system). Next for internal documents we use SharePoint. For CAD, we use product PQR as much as possible (heavily adapted) or AutoCAD 2D (to support the minimum). For ERP, the standard system is XYZ (a famous ERP system – you do not lose your job by selecting them) and of course everyone uses Excel as a common interface of information between people.
It was impossible in this company to have a business view on the solution landscape. As you can imagine, this company’s margins are not (yet) under pressure as their industry is very conservative.
What do you think?
Is the future for PLM in platforms? If Yes, what about openness? Who are the candidates to offer such a platform? Or will lack of industry standards and openness block wider adoption? If No, will there be a massive PLM system in the future, connected to other enterprise systems (ERP/CRM)? Or will PLM be implemented as a collection of smaller systems communicating through an enterprise service bus?
I am looking forward discussing the topic here and soon during the upcoming Product Innovation conference in Düsseldorf
Human beings are a strange kind of creatures. We think we make a decision based on logic, and we think we act based on logic. In reality, however, we do not like to change, if it does not feel good, and we are lazy in changing our habits.
Disclaimer: It is a generalization which is valid for 99 % of the population. So if you feel offended by the previous statement, be happy as you are one of the happy few.
Our inability to change can be seen in the economy (only the happy few share). We see it in relation to global climate change. We see it in territorial fights all around the world.
Owning instead of sharing. ?
The cartoon below gives an interesting insight how personal interests are perceived more important than general interest.
It is our brain !
More and more I realize that the success of PLM is also related to his human behavior; we like to own and find it difficult to share. PLM primarily is about sharing data through all stages of the lifecycle. A valid point why sharing is rare , is that current PLM systems and their infrastructures are still too complex to deliver shared information with ease. However, the potential benefits are clear when a company is able to transform its business into a sharing model and therefore react and anticipate much faster on the outside world.
But sharing is not in our genes, as:
- In current business knowledge is power. Companies fight for their IP; individuals fight for their job security by keeping some specific IP to themselves.
- As a biological organism, composed of a collection of cells, we are focused on survival of our genes. Own body/family first is our biological message.
Breaking these habits is difficult, and I will give some examples that I noticed the past few weeks. Of course, it is not completely a surprise for readers of my blog, as a large number of my recent posts are related to the complexity of change. Some are related to human behavior:
August 2012: Our brain blocks PLM acceptance
April 2014: PLM and Blockers
Ed Lopategui, an interesting PLM blogger, see http://eng-eng.com, wrote a long comment to my PLM and Blockers post. The (long) quote below is exactly describing what makes PLM difficult to implement within a company full of blockers :
“I also know that I was focused on doing the right thing – even if cost me my position; and there were many blockers who plotted exactly that. I wore that determination as a sort of self-imposed diplomatic immunity and would use it to protect my team and concentrate any wrath on just myself. My partner in that venture, the chief IT architect admitted on several occasions that we wouldn’t have been successful if I had actually cared what happened to my position – since I had to throw myself and the project in front of so many trains. I owe him for believing in me.
But there was a balance. I could not allow myself to reach a point of arrogance; I would reserve enough empathy for the blockers to listen at just the right moments, and win them over. I spent more time in the trenches than most would reasonably allow. It was a ridiculously hard thing and was not without an intellectual and emotional cost.
In that crucible, I realized that finding people with such perspective (putting the ideal above their own position) within each corporation is *exceptionally* rare. People naturally don’t like to jump in front of trains. It can be career-limiting. That’s kind of a problem, don’t you think? It’s a limiting factor without a doubt, and not one that can be fulfilled with consultants alone. You often need someone with internal street cred and long-earned reputation to push through the tough parts”
Ed concludes that it is exceptionally rare to find people putting the ideal above their own position. Again referring to the opening statement that only a (happy) few are advocates for change
Now let´s look at some facts why it is exceptionally rare, so we feel less guilty.
On Intelligence
Last month I read the book On Intelligence from Jeff Hawkins well written by Sandra Blakeslee. (Thanks Joost Schut from KE-Works for pointing me to this book).
Although it was not the easiest book to read during a holiday, it was well written considering the complexity of the topic discussed. Jeff describes how the information architecture of the brain could work based on the neocortex layering.
In his model, he describes how the brain processes information from our senses, first in a specific manner but then more and more in an invariant approach. You have to read the book to get the full meaning of this model. The eye opener for me was that Jeff described the brain as a prediction engine. All the time the brain anticipates what is going to happen, based on years of learning. That’s why we need to learn and practice building and enrich this information model.
And the more and more specialized you are on a particular topic, it can be knowledge but it can also be motoric skill, the deeper in the neocortex this pattern is anchored. This makes is hard to change (bad) practices.
The book goes much further, and I was reading it more in the context of how artificial intelligence or brain-like intelligence could support the boring PLM activities. I got nice insights from it, However the main side observation was; it is hard to change our patterns. So if you are not aware of it, your subconscious will always find reasons to reject a change. Follow the predictions !
Thinking Fast and Slow
And this is exactly the connection with another book I have read before: Thinking Fast and Slow from Daniel Kahneman. Daniel explains that our brain is running its activities on two systems:
System 1: makes fast and automatic decisions based on stereotypes and emotions. System 1 is what we are using most of the time, running often in subconscious mode. It does not cost us much energy to run in this mode.
System 2: takes more energy and time; therefore, it is slow and pushes us to be conscious and alert. Still system 2 can be influenced by various external, subconscious factors.
Thinking Fast and Slow nicely complements On Intelligence, where system 1 described by Daniel Kahneman is similar to the system Jeff Hawkins describes as the prediction engine. It runs in an subconscious mode, with optimal energy consumption allowing us to survive most of the time.
Fast thinking leads to boiling frogs
And this links again to the boiling frog syndrome. If you are not familiar with the term follow the link. In general it means that people (and businesses) are not reacting on (life threating) outside change when it goes slowly, but would react immediately if they are confronted with the end result. (no more business / no more competitive situation)
Conclusion: our brain by default wants to keep business in predictive mode, so implementing a business change is challenging, as all changes are painful and against our subconscious system.
So PLM is doomed, unless we change our brain behavior ?
The fact that we are not living in caves anymore illustrates that there have been always those happy few that took a risk and a next step into the future by questioning and changing comfortable habits. Daniel Kahneman´s system 2 and also Jeff Hawkins talk about the energy it takes to change habits, to learn new predictive mechanisms. But it can be done.
I see two major trends that will force the classical PLM to change:
- The amount of connected data becomes so huge, it does not make sense anymore to store it and structure the information in a single system. The time required to structure data does not deliver enough ROI in a fast moving society. The old “single system that stores all”-concept is dying.
- The newer generations (generation Y and beyond) grew up with the notion that it is impossible to learn, capture and own specific information. They developed different skills to interpret data available from various sources, not necessary own and manage it all.
These two trends lead to the point where it becomes clear that the future in system thinking becomes obsolete. It will be about connectivity and interpretation of connected data, used by apps, running on a platform. The openness of the platform towards other platform is crucial and will be the weakest link.
Conclusion:
The PLM vision is not doomed and with a new generations of knowledge workers the “brain change” has started. The challenge is to implement the vision across systems and silos in an organization. For that we need to be aware that it can be done and allocate the “happy few” in your company to enable it.
What do you think ???????????????????????????
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