With most of my career being spent with the front-of-the-house supply chain (customer service, sales, marketing, logistics), my natural perspective of the product lifecycle is:
It is likely you see the obvious point that the product already exists by the time the above activities come into play. To limit the perspective of PLM to the sales & marketing arena ignores all R & D and pre-production efforts that precede them. That would be analogous to a baby being born but ignoring the 9 months that went into developing that new life. Likewise, if one focused primarily on the back-of-the-house perspective (R & D, design & engineering, or materials management in sourcing, prototyping, production, inventory control) and never give thought to what comes after. That would be tantamount to forgetting about the “care and feeding” of our new product once it was “born.”
I started to research the various strategies for harmonizing these perspectives to maximize benefits and efficiencies. Most of the articles I came across seem to focus on one perspective or another. Many of them point to the inefficiencies of multiple legacy systems and difficulty in gaining overall visibility for product managers, sales & marketing, finance, engineering, production & procurement.
What is it that we as an organization seek to gain from a PLM system? From inception or idealization through to the final stage of decline, data is generated that needs to be captured, managed, analyzed in order to optimize a product or product family throughout its lifecycle. Do we have a single source of truth that meets the needs of all who are vested in the care of our product, or is data scattered across various systems?
Are we able to collaborate across functions to maximize efficiencies? If a regulatory body required information from all sides in the event of an audit or claim, are all parties involved in our product’s life referring to the same data/version of it?
One thing in common amongst the various perspectives is that the product lifecycle is comprised of 4 basic stages, but each perspective comes with a different frame of reference or context as to the content of each stage. For example, the introduction might be inception/design/development/small scale production on one side, but fully vetted and market-ready product on the other.
The focus of a given system draws distinctions between PLM, PDM (Product Data Management for design & engineering) and PIM (Product Information Management geared more toward sales & marketing). One thing I noticed is that many also mention the same types of data. The blueprint of a part that engineering needs to provide to production, maybe the same one that sales need to provide to a customer who is interested in purchasing that part.
To be effective in its use of PLM, an organization should seek to be holistic and cross-functional to reduce data redundancy and capitalize on potential synergies. This will help it define what it is they stand to gain from the effort. A single source of truth can benefit all in determining what the product’s current stage is, as well as foresee the next along with the form it will likely take. This enables an organization to proactively adapt in the appropriate arena – be it in sales/marketing, engineering, production, material management or procurement.
Read the first article in this series, product lifecycle management to understand the five core processes that drive strategic integration.
Read the next article in this series to grab insights on how SAP can communicate and plan phases in product lifecycle management.Tags: ERP system, PLM, Product Data Management, Product Lifecycle, Production, Supply chain