Remember when PLM, as a concept, was introduced years ago? At that time, PDM had been around for a few years so we had a decent idea of what it was. But this new thing? PLM? Well, the industry struggled for some time to really differentiate PLM from PDM. Over time though, we come to some good definitions. Here are two from wikipedia.

Product data management (PDM) is the business function often within product lifecycle management that is responsible for the creation, management and publication of product data. [reference: PDM wikipedia entry]

In industry, product lifecycle management (PLM) is the process of managing the entire lifecycle of a product from its conception, through design and manufacture, to service and disposal. … Product lifecycle management is one of the four cornerstones of a corporation’s information technology structure. All companies need to manage communications and information with their customers (CRM-Customer Relationship Management), their suppliers (SCM-Supply Chain Management), their resources within the enterprise (ERP-Enterprise Resource Planning) and their planning (SDLC-Systems Development Life Cycle). [reference: PLM wikipedia entry]

Since PLM was first conceived, it has almost been inseparable from PDM. The majority of PLM deployments included PDM as part of the PLM deployments. However, more recently, the idea that PDM must be deployed with PLM has been eschewed. Some new PLM solutions only offer plug-ins or integrations to 3rd party PDM systems, all of which is optional. Is this a good or bad idea? To answer that question, let’s revisit some arguments on both sides.

Disassociating Product Data and Process Execution is Problematic

Traditional thinking is that PLM and PDM should be integrated. Why? The idea is that while executing a process with a PLM system, stakeholders will need to reference and review product data which resides in the PDM system. An integration between these two systems enables the PLM system to always point at the right version of the product data. As a result, decisions in the process are always made against the correct product data. If done manually, decisions may be made against the incorrect version of product data, leading to erroneous decisions. This same core concept extends to reporting and analytics that may be based on product data. It also extends to generating an traceable audit trail for liability or legal reasons.

Smaller Bite-Sized Deployments are More Pragmatic

The fly in the ointment with the above argument is how PLM systems are deployed today. Very few companies go with a big bang deployment of PLM. It’s just too expensive and too long before an return-on-investment is achieved. Instead, many manufacturers use a phased approach composed of intermittent projects that on show a ROI on an individual basis. Where’s the problem? The deployment of PDM across multiple sites, multiple continents or an extensive supply chain requires a significant investment in terms of time and money. As a PDM deployment must often be completed prior to the start of the PLM deployment, it can be years before the PLM system addresses process issues.

Conclusion and Summary

What do I think? I honestly think whether or not you should deploy PDM, PLM or a couple PDM-PLM system depends on what type of business initiative you are trying to support. If your goal is to enable extensive supply chain collaboration on product data, then a global PDM system is your answer. If your goal is to mange the ideation and portfolio management process, then a pure PLM system is a good fit. If you need regulatory compliance reports pulled off CAD generated BOMs, then an integrated PDM-PLM system is the right way to go.

What do you think? Is PLM without PDM just fundamentally a bad idea? Is taking on PDM prior to PLM a killer for IT justifications? Don’t be shy. Sound off and let me know what you think.

Take care. Talk soon. And thanks for reading.