In many industries, the supply chain is multi-tiered and involves complex relationships. In fact, it is arguably more accurate to use the term "supply network," especially if we take the broader "lifecycle" view of the supply chain that encompasses product development at the front end and the product in-service life through to retirement at the back end. We have also seen shifts in responsibility throughout industrial supply chains, from the organization at the "top of the chain" pushing its defined requirements for, say, components and sub-assemblies down to the supplying organizations, to those supplying organizations doing the design and subsequent product definition themselves. The increased breadth of supply chain activities and distribution of responsibilities makes the problem of management of product data much more complex.
PLM systems have long been regarded as essential for managing the vast quantity and variety of data associated with complex products. From their early incarnations as solutions for providing version control for product data and workflow management through the product development phase (so-called product data management, or PDM), today’s leading PLM technologies do indeed offer full lifecycle product data management. For example, Oracle talks about its PLM technology in terms of “product value chain management” in order to emphasize the completion of the loop that involves exploiting field experience as an input to front-end innovation.
Taking the broadest view, users of PLM would include not only the members of the design-to-delivery supply chain but also the post-sale/installation service organizations so as to give them access to the current product information as well as the opportunity to report product issues back.
The problem has been accessibility. To take full advantage of PLM across the supply chain, it needs to involve all significant users of and contributors to the product data. In the past, PLM technologies have been essential components of companies’ IT stacks but were rather “heavyweight” in terms of IT infrastructure, process definition, data structures, etc. This is changing substantially. A combination of technology infrastructure – not only cloud, but mobile devices, especially for the field service end of the product lifecycle – coupled with and great strides in ease of use and configurability are making PLM highly accessible. A leading example of cloud-based, readily configured and affordable PLM is Autodesk’s PLM 360 technology, while NVIDIA’s recent GRID GPU announcements demonstrate the progress that has been made in cloud-based infrastructures that enable a wider range of users on a greater range of devices to access complex, compute-intensive product information (3D models, simulations, visualizations).
Taken together, these technological advances are expanding the reach of PLM dramatically. Things are moving quickly and we expect to see accelerating adoption of PLM and the resulting benefits across more and more industry supply chains.
I have never seen a commentary on supply chain issues that has pointed out that speed and cost pressures are decreasing! Those pressures, together with what seems to be increasing complexity as industry players take a full lifecycle view of their product/service development and delivery processes, mean that accurate “single source of truth” product information is a necessity. PLM’s role as a supply chain enabler will therefore continue to grow in importance.
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