PLM Interest Group

The twin drives towards Professional PLM and the PLM Body of Knowledge have enormous synergy, and need a well-structured approach to achieve them.

The PLM 2025-35 Project provides the over-arching framework that maximises the cross-over benefits while minimising the input required from participants.

			The aim is not just to establish the advanced knowledge and professional techniques of right-first-time PLM, but to embody them in real implementations.

By integrating the two programmes, everyone who participates learns from both streams and can make use of the combined knowledge set.

Professional PLM discussions in 2025 showed clearly that, despite the hype, PLM itself is not progressing (Forgetting What You Never Knew):-

Way back in 2010 a 10-Year PLM Vision was published, entitled '2020 PLM'.  It set out some reasonable aspirations as to how the PLM industry could progress over the forthcoming decade, and how things would be better at the end of it.  Needless to say, when 2020 arrived absolutely none of this had been achieved. The PLM scenario was completely unchanged.

If this is true (and there are no case histories to show that it isn't) then this is a lost opportunity for everybody.  Repeating mistakes costs money, so every implementation that does it is overspending. Learning takes time, and learning the hard way takes longer.

Global corporations have business and geographical requirements for PLM that need very complex, structured solutions. Over the years, the complexity of that effort leads each company to generate its own methodologies based on what is found to work best.

This represents many man-years of experience and learning that have never been shared or re-used. Thousands of different implementations around the world with locked-in knowledge.

The solution is very simple.  Take a number of user implementations that have each developed in their own random way, in response to their different business drivers and technical competences.  Array them in parallel, and we find that their strengths and weaknesses are in different areas.  Where one implementation has a weakness, others will have strengths - so the 'weaker' implementation gets a problem solution for free, immediately.  And that same implementation will have strengths that the others will use.

Not only does this resolve a wide range of specific problems and issues for the direct participants, but it builds the kernel of an industry-wide Body of Knowledge that can be used worldwide, for right-first-time adoption and as the basis for a future PLM Profession.

The PLM 2025-35 Project will run for a year initially, aligned with the natural pace of actual PLM implementations and consisting of two streams:-

PLMIG experience with user groups shows that users come up with much more detailed and practical ideas when working amongst themselves than they do when vendors or advisors are present.  Keeping the separation provides a double benefit, because in order to derive common, neutral conclusions from the Users' work, the findings must be distilled and rationalised - which is exactly what is needed for a Body of Knowledge.

There is obviously an overhead in setting the project up, and for each participant to apply the comparison tools, but this is a fraction of the time and effort it would take to chase through each problem in isolation. The project activity as a whole helps improve governance and adds a layer of discipline, and the overall pace matches the ongoing implementations.  The solutions come holistically and can be applied immediately.

Current AI is woefully inadequate for PLM, and will stay that way unless we reconsider how it should work.
If you are interested in this, there is an opportunity for you to define the new, productive AI environment that we all need.

PLM 2025-35 will generate the core Body of Knowledge over the forthcoming twelve months.  Somehow, AI will be a necessary part of it - not in creating the Knowledge, but as a sort of "tour guide" or instructor that shows practitioners where to find the material they need and how to apply it in their live, day-to-day environment.

We need to develop the answer to this, and so the Project includes a Working Group to produce a definitive AI tool for PLM - if such a thing is possible.

There are two streams in PLM 2025-35 (User Collaboration and Knowledge Development) and members of the AI Working Group can come from either of them.  Anyone who is part of the Project can opt in.  This allows participants to learn about serious AI as the Project unfolds, and also enables the advanced AI practitioners to build the model using the structured framework as a testbed.

The Proposal explains everything.  It shows how the User Collaboration stream passes expertise and solutions between PLM Teams, and how the Knowledge Development stream refines the new material into the Body of Knowledge structure. The 12-month Gantt chart is straightforward, structured around the central Solution Generation activity in which PLMIG workshops address the priority issues of the participants.

The role of the AI Working Group is also covered, explaining how it integrates with the two working streams as they become the testbed for the new PLM AI Solution.

The management approach is based on the PLM Solution Map and is far more comprehensive than anything that currently exists.  It is also far more interactive than anything that currently exists, channeling synergy between implementations in a way that has not been possible before.

Download the Proposal [Word] >>>                              Download the Proposal [PDF] >>>

The Input Forms for the PLM Solution Map have been processed and the Solution Map itself is now being written.

The first draft will be published shortly and will be thrown open for review, including via some on-line meetings.  This represents a significant step forward, and international feedback is important.

In the meantime, if you would like any other information about the Initiative, you can request it via
plm2025-35@plmig.com.

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