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Business Innovation Homepage > Business Agility

Deploying Product Life-Cycle Management
 
Applications that manage information at all phases of a product's life help organizations improve quality and processes.


By Bob Violino
August 8, 2007

Managing all the information associated with the stages of a product’s life cycle has become an increasingly complex task for manufacturers. Product life-cycle management (PLM) technology provides an effective way to manage this data and improve processes.

PLM applications can help organizations get a handle on information through the many product life-cycle stages, including conceptualization, design, engineering, sourcing, manufacturing, rollout, maintenance and repair, and retirement/disposal.

It’s a growing market. Daratech Inc., a research firm focused on manufacturing-related technologies, estimates that spending on PLM software and services exceeded $12.3 billion in 2006, up 8 percent from the year before. The firm expects the PLM market to reach $13.4 billion in 2007, an 8 percent increase over 2006.

PLM isn’t a single software product but a set of applications that applies to the different life-cycle phases. With an effective PLM strategy, organizations can better manage product specifications and designs, and track such things as production history and genealogies, and measure the quality of products. This can in turn lead to benefits such as improved product quality, shorter time to market and more satisfied customers.

Users of PLM software can include market researchers, product designers and engineers, production managers, sales and marketing representatives, and others involved in the product life cycle.

Among the specific data that can be stored, shared and updated are information on patents and licenses, production equipment and materials, product packaging, shipping, maintenance, and product retirement or disposal. This information can be housed in a central database accessible from desktop and mobile computers.

In the past, information generated during the different stages of a product’s life cycle wasn’t connected. The data existed in “silos,” and teams responsible for different aspects of a product’s life cycle couldn’t always get easy access to information. The consolidation of product data into PLM enables organizations to more easily manage the information.

Cross-functional teams working on the development, production and marketing of a product can now access information as the product moves through different stages. This enables them to be aware of changes that take place at the different stages, so they can make more-informed decisions.

For example, people in production can access data on product design and engineering, and note changes that affect manufacturing processes. Marketing and field service reps can access information on production schedules, so they can know when a product or enhancement is likely to be available.

This cross-functional access to product information “is a primary benefit of PLM,” says Michael Burkett, an analyst at AMR Research Inc. “Manufacturers have used concurrent engineering and integrated product teams as a business process for many years. However, engineering information during design was inaccessible, often residing in an engineering-centric product data management application.”

Modern PLM applications expose this data to cross-functional teams, Burkett says, “letting them see the latest design changes that may have an impact on their business functions, such as a manufacturing process design for a new product.”

Information generated from PLM can be shared with external partners such as suppliers, consultants and third-party service providers. The internal and external use of PLM data allows organizations to shorten lead times and get products to market more quickly.

Organizations planning a move to PLM should be aware of the implementation challenges. The biggest is related to the cross-functional nature of new product introduction, Burkett says. “The challenge is less technical than it is cultural change management — getting these cross-functional teams to understand and agree on their process requirements,” he says. “The second biggest challenge is data migration from legacy systems. Often data is in hard copy, or it is not neatly defined in a way that is usable within the PLM application.”

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