In the last two weeks, I have had mixed discussions related to PLM, where I realized the two different ways people can look at PLM. Are implementing PLM capabilities driven by a cost-benefit analysis and a business case? Or is implementing PLM capabilities driven by strategy providing business value for a company?

Most companies I am working with focus on the first option – there needs to be a business case.

This observation is a pleasant passageway into a broader discussion started by Rob Ferrone recently with his article Money for nothing and PLM for free. He explains the PDM cost of doing business, which goes beyond the software’s cost. Often, companies consider the other expenses inescapable.

At the same time, Benedict Smith wrote some visionary posts about the potential power of an AI-driven PLM strategy, the most recent article being PLM augmentation – Panning for Gold.

It is a visionary article about what is possible in the PLM space (if there was no legacy ☹), based on Robust Reasoning and how you could even start with LLM Augmentation for PLM “Micro-Tasks.

Interestingly, the articles from both Rob and Benedict were supported by AI-generated images – I believe this is the future: Creating an AI image of the message you have in mind.

When you have digested their articles, it is time to dive deeper into the different perspectives of value and costs for PLM.

 

From a system to a strategy

The biggest obstacle I have discovered is that people relate PLM to a system or, even worse, to an engineering tool. This 20-year-old misunderstanding probably comes from the fact that in the past, implementing PLM was more an IT activity – providing the best support for engineers and their data – than a business-driven set of capabilities needed to support the product lifecycle.

 

The System approach

Traditional organizations are siloed, and initially, PLM always had the challenge of supporting product information shared throughout the whole lifecycle, where there was no conventional focus per discipline to invest in sharing – every discipline has its P&L – and sharing comes with a cost.

At the management level, the financial data coming from the ERP system drives the business. ERP systems are transactional and can provide real-time data about the company’s performance. C-level management wants to be sure they can see what is happening, so there is a massive focus on implementing the best ERP system.

In some cases, I noticed that the investment in ERP was twenty times more than the PLM investment.

Why would you invest in PLM? Although the ERP engine will slow down without proper PLM, the complexity of PLM compared to ERP is a reason for management to look at the costs, as the PLM benefits are hard to grasp and depend on so much more than just execution.

See also my old 2015 article:   How do you measure collaboration?

As I mentioned, the Cost of Non-Quality, too many iterations, time lost by searching, material scrap, manufacturing delays or customer complaints – often are considered inescapable parts of doing business (like everyone else) – it happens all the time..

The strategy approach

It is clear that when we accept the modern definition of PLM, we should be considering product lifecycle management as the management of the product lifecycle (as Patrick Hillberg says eloquently in our Share PLM podcast – see the image at the bottom of this post, too).

When you implement a strategy, it is evident that there should be a long(er) term vision behind it, which can be challenging for companies. Also, please read my previous article: The importance of a (PLM) vision.

I cannot believe that, although perhaps not fully understood, the importance of a data-driven approach will be discussed at many strategic board meetings. A data-driven approach is needed to implement a digital thread as the foundation for enhanced business models based on digital twins and to ensure data quality and governance supporting AI initiatives.

It is a process I have been preaching: From Coordinated to Coordinated and Connected.

We can be sure that at the board level, strategy discussions should be about value creation, not about reducing costs or avoiding risks as the future strategy.

 

Understanding the (PLM) value

The biggest challenge for companies is to understand how to modernize their PLM infrastructure to bring value.

* Step 1 is obvious. Stop considering PLM as a system with capabilities, but investigate how you transform your infrastructure from a collection of systems and (document)  interfaces towards a federated infrastructure of connected tools.

Note: the paradigm shift from a Single Source of Truth (in my system) towards a Nearest Source of Truth and a Single Source of Change.

 

* Step 2 is education. A data-driven approach creates new opportunities and impacts how companies should run their business. Different skills are needed, and other organizational structures are required, from disciplines working in siloes to hybrid organizations where people can work in domain-driven environments (the Systems of Record) and product-centric teams (the System of Engagement). AI tools and capabilities will likely create an effortless flow of information within the enterprise.

* Step 3 is building a compelling story to implement the vision.   Implementing new ways of working based on new technical capabilities requires also organizational change. If your organization keeps working similarly, you might gain some percentage of efficiency improvements.

The real benefits come from doing things differently, and technology allows you to do it differently. However, this requires people to work differently, too, and this is the most common mistake in transformational projects.

Companies understand the WHY and WHAT but leave the HOW to the middle management.

People are squeezed into an ideal performance without taking them on the journey. For that reason, it is essential to build a compelling story that motivates individuals to join the transformation. Assisting companies in building compelling story lines is one of the areas where I specialize.

Feel free to contact me to explore the opportunity for your business.

It is not the technology!

With the upcoming availability of AI tools, implementing a PLM strategy will no longer depend on how IT understands the technology, the systems and the interfaces needed.

As Yousef Hooshmand‘s  above image describes, a federated infrastructure of connected (SaaS) solutions will enable companies to focus on accurate data (priority #1) and people creating and using accurate data (priority #1). As you can see, people and data in modern PLM are the highest priority.

Therefore, I look forward to participating in the upcoming Share PLM Summit on 27-28 May in Jerez.

It will be a breakthrough – where traditional PLM conferences focus on technology and best practices. This conference will focus on how we can involve and motivate people. Regardless of which industry you are active in, it is a universal topic for any company that wants to transform.

 

Conclusion

Returning to this article’s introduction, modern PLM is an opportunity to transform the business and make it future-proof. It needs to be done for sure now or in the near future. Therefore PLM initiatives should be considered from the value point first instead of focusing on the costs.  How well are you connected to your management’s vision to make PLM a value discussion?

Enjoy the podcast – several topics discuss relate to this post.