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The trend of today’s products in industrial equipment manufacturing is ever-increasing complexity. What fuels this growth is market demand and the competitive drive for higher functionality and customization without compromising quality. In a recent survey conducted by the Aberdeen Group, IEM respondents were 21% more likely than all respondents to identify market demand for customization and complex products as one of the top three pressures driving them to improve their product development. (See the full report here: The Importance of Configuration Management in Industrial Equipment Manufacturing.) Rightly so, a strategy that strives for product differentiation can pay huge dividends for companies that have the right configuration management in place. However, companies often lack the proper tools to implement a system that ensures consistency in building to requirements, maintains accuracy in meeting targets, and upholds performance throughout a product’s entire lifecycle. For many, configuration management is largely a manual, handwritten process. And unfortunately, for those who are at the bottom of the industry, product complexity is a trend that remains for the foreseeable future.

Over the past two years, IEMs have reported double digit increases in the number of mechanical parts, electrical components, and software lines of codes.  This rise in product parts pushes the importance of Bill of Materials (BOM) accuracy to the forefront. 54% of IEM respondents, and over 42% of all respondents said maintaining accuracy was their top challenge in BOM management. BOM accuracy, paired with meeting project targets, product requirements, and quality standards all point to the need for a proper configuration management (CM) tool. The reason being, CM provides the blueprint by which products will be produced and services delivered. Without good configuration management, manufacturing, and service processes will be inefficient at best, and in some cases can evolve to one-off design and build exercises, which most IEM’s are not equipped to handle from a resource, delivery, and cost perspective.

To identify best practices for configuration management, Aberdeen measured participants’ ability to meet product launch dates, quality targets, cost targets, revenue targets, and change in development time. Aberdeen categorized industrial equipment manufacturing respondents into two groups: Leaders (Top 33%) and Followers (Bottom 67%). Over the past two years, IEM leaders were over 80% for products meeting launch dates, revenue targets, and cost targets. They also saw a 20% decrease in length of development time. In comparison, Followers were 66% in launch dates and revenue targets met and 70% in cost targets met. For decrease in length of development time over the past two years, Followers saw only a 5% decrease.

How are IEM leaders separating themselves from the Followers? They are using configuration management in almost every aspect of their BOM management. The differences are particularly notable in their use of CM in electrical BOMs (71% over 56%) and product requirements (50% over 34%).

PRODUCT DATA MANAGED THROUGH CONFIGURATION MANAGEMENTIEM

The second biggest divider between IEM Leaders and Followers are the Leaders automation of the configuration management process through Product Lifecycle Management (PLM) software. Leaders are 21% more likely than followers to have PLM implemented and configuration management automated through a PLM system. PLM drives natural growth by linking a company’s ideas to its business strategy. It empowers management to improve time to market, drive costs down, and complements creativity and growth.

In industrial equipment manufacturing, the complexity of the product and business is inherent and growing. The rising demand for customization along with shortened timelines creates more opportunities for error. Leaders in the industry have turned to configuration management to combat these issues.

For the full report, read: The Importance of Configuration Management in Industrial Equipment Manufacturing

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