Recently I connected with a fellow countryman, Flip, through LinkedIn and we had a small dialogue related to PLM. Flip describes himself as a millennial thinking loud about PLM and shared some of his thoughts trying to define “the job of PLM.” Instead of keeping it a Dutch dialogue, I would like to open the dialogue to all (millennials), as we need a new generation of PLM consultants
Point 1
(Flip) You cannot automate design activities easily, but the rest you can. Isn’t PLM an evolution of 3D Design tooling (and with that the next step in design – theory)
You are right. Historically PLM originated from managing 3D design in a collaborative manner, although at that time we would call it cPDM (Collaborative Product Data Management). PDM was very design focused. However, PDM also supported the connection to an Engineering Bill of Materials (EBOM) and connected engineering change processes (Engineering Change Request / Engineering Change Order – read more: ECR/ECO for Dummies)
PTC’s Windchill was the first modern cPDM software that still exists. At the same time, Dassault Systemes and Siemens extended the support for design towards the manufacturing planning and execution, introducing the term PLM (Product Lifecycle Management). In the following years, PLM systems started to support the full go-to-market lifecycle as the figure shows below.
This linear go-to-market process is currently rapidly changing because PLM is changing.
The P standing for Product now represents a System (hardware & software interacting with the environment). The L standing for Lifecycle is also under change.
Support for the Lifecycle of a “product” has changed in two ways. First, the lifecycle is no longer going to be a linear process, but also be more iterative and incremental for the same “product.” Secondly, the lifecycle is stretched to support the “products” in the fields thanks to feedback from sensors (IoT – Internet of Things). That’s why PTC now claims IoT is PLM. Read more: Best Practices or Next Practices.
Finally, the M from Management is under change as thanks to a data-driven approach we should be able to (semi-)automate processes using algorithms. Favorite buzz words here are machine-learning, cobots (collaborative robots) and preventive actions thanks to data analysis & trends.
Point 2
(Flip) Storing data in a structured manner creates more complexity (you need to choose what to store). With simulation, complexity could be reduced to make meaningful (design) decisions, so PLM is about clever data hoarding?
I believe there is always a challenge with managing structured data for two reasons. People often only create the data they require. Adding more context more data or a richer context is often considered “extra work,” for with the department is not rewarded or adding more data is not known as these persons do not know the future use of their information. This is a typical exercise for companies now engaging in a digital transformation. (read more: The importance of accurate data)
When you talk about simulation, I immediately thought about the current trend to work towards a model-based enterprise, where the model is the center of all information. And with the model, we do not only mean the 3D Model but also the functional and logical model which we can simulate. (Read more: Digital PLM requires a Model-Based Enterprise)
Point 3
(Flip) Automation from manufacturing with more and more resources requires new ways to drive manufacturing so a team of 8 people can do the work of 80 people through a PLM system?
Here you are addressing exactly the point that initiatives like Industry 4.0 or in the Netherlands Smart Industry are addressing. Instead of a linear, document-driven process, where each step new versions of information need to be created, the dream is to work around a model (the model-based enterprise).
The idea is that data is flowing through the organization – digital continuity / digital thread – without conversion and by using algorithms and machine learning, the data is consumed and created during the manufacturing process in an automated manner. Indeed, reducing the amount of people involved drastically.
I am not sure of we still would call this PLM, it is more a digital enterprise, where digital platforms interact together. PLM could be considered the source for the Product Innovation Platform, but there will also be Execution platforms (ERP and MES as the main source) and customer related platform (CRM as a source). As vendors from all these platforms will provide overlapping functionality, it will be hard to draw exact lines. The main goal for a company will be that the data is flowing and not locked into a proprietary format or systems. And here we still have a lot of work to do,
Conclusion
No conclusion this time as it is an on-going dialogue. Feel free to comment or send your questions, and we can all learn from the dialogue (always better than a monologue).
Jos Voskuil's Weblog 
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June 27, 2017 at 2:36 pm
Flip
Thanks for these insights Jos, I totally agree. Reading through your post, yet another question pops up: in a changing PLM landscape, where lies the new effort for (a new generation of) PLM experts?
Given point 1: ‘A new PLM oriented design rationale’, I believe a huge effort for PLM is successful change management towards ‘business Agility’. Since a proper response to an ECR/ECO would evidently require design changes impacting manufacturing and even after-sales and/or legal. And that’s just the tip of the iceberg.
But then given point 2: ‘Model-based enterprise transformations’, in my view, a key effort for a successful PLM expert would also be to embed this change mgt. as a business process in the actual Enterprise Architecture. So he/she would need to understand and work out a ‘business-ontology’ (Diets, 2006) or similar construct which facilitates at least a. business processes, b. change (mgt.) processes, c. emerging (mfg.) technologies , d. data structures- and flows, e. implementation trajectory and sourcing. And then do this from the PLM domain throughout the organization per optimization.
After all a product-oriented enterprise revolves around the success of its products, so eventually all subsystems are affected by the makeup of the product lifecycle. Good PLM is a journey, not a trip.
Or, does a PLM expert merely facilitates / controls this enterprise re-design process? And, what other enterprise ontologism tools and methods do you know of?
This indeed boils down to point 3: ‘Where to draw the PLM line in a digital enterprise’. I personally think this barrier will vanish as Product Lifecycle Management (as a paradigm, not necessarily as a software) will provide companies with continuity, profitability and competitive advantage in the early 21st century. The PLM monolith might remain, but supported by an array of micro services inside and outside the company (next to IoT, hopefully also external datasets). A great example of this is Apple: they have the ambition to close the lifecycle by recycling their products within the coming decade. They own the product design process up to the retailing. They know all of their customers through their usage of Apple hard- and software. But of course also Apple has its struggles.
What seems to be missing is an ‘Archetype’ of the ideal transformed organization. Where do PLM experts want to go with these businesses in practice? Personally, I imagine a business where DevOps is the standard, unique products have generic meta-data, personal growth is an embedded business process and supply chain related risks are anticipated on and mitigated through automated analytics. Do you know of such an evolved archetypal enterprise model?
Kind regards, Flip
Flip interesting thoughts and I think you will find the answers in the next dialogue post. If I have time this weekend.
Thanks for keeping the dialogue going. Best regards Jos
p.s. I noticed your response came in the Spam category as nobody has such a long comment on a blog post it seems 🙂
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