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Benchmark Research Finds Companies Struggling with Product Information

  • Colin Snow
  • DM Review Special Report, October 2007

This a VentanaView from Ventana Research dated September 7, 2007.

A recent benchmarking project by Ventana Research finds that the quality of product information is a significant concern for companies and that they are looking to improve their product information management (PIM) to resolve both analytic and operational issues. The research finds that the majority of organizations doubt the quality of their product data and find it difficult or impractical to standardize product information. Given the costs associated with inconsistent product information and the current lack of confidence in product data quality, Ventana Research sees a huge opportunity for new processes and technologies to make major impacts on business.

View

The Ventana Research benchmark research, "Product Information Management: Business and Technology Trends" (sponsored by DataFlux, Heiler Software and Silver Creek Systems and also supported by media sponsors Business Intelligence Review, DM Review, Intelligent Enterprise, IT Business Edge, Montgomery Research and TechTarget), surveyed qualified IT professionals, users and business executives and managers at 240 qualified organizations from all major industries and company sizes inside and outside the U.S. We defined product information management as the processes and technologies required to manage data about products, items or materials enterprise-wide. The benchmark research also asked questions about the components of information management, among them master data management (MDM), data quality, data association and data integration.

This research shows that companies are looking to improve their product information management to resolve issues in two aspects of business: analysis and operations. In the analytic area, the top priority, shared by 45 percent of participants, was to support a business intelligence (BI) initiative. In the operational sector, the top priority, also selected by 45 percent of participants, was to improve customer support. The next-highest priority was strategic sourcing - an operational issue - selected by 35 percent of participants. Both operational and analytic product information are important to the performance of an organization; companies should address both at the same time by using PIM. Otherwise they are likely to misinterpret operational performance.

The research also reveals that product data is spread throughout most organizations and that managing it is a cross-functional responsibility - and worry. We found that 80 percent of participants are not confident of the quality of their product data; this correlates to the finding that desktop spreadsheets are a significant source of product data, second only to enterprise resource planning (ERP) systems. For enterprise business processes, spreadsheets are notoriously unreliable. Our research also shows that companies struggle to accomplish the basic goal of PIM - that is, to standardize product information in a consistent and reliable form. Only 27 percent said doing that requires minimal effort or is not a problem. All the rest (73 percent) reported they find it difficult or impractical.

This does not mean that organizations aren't trying: More than two-fifths (41 percent) of participants said their companies have a PIM project planned or under investigation. But several barriers prevent more from starting an initiative; the most prevalent obstacle, cited by 36 percent of participants, was lack of budget. However, three-quarters of respondents, a surprisingly large percentage, said their current method of creating a single, consistent and dependable product record is unreliable. The more innovative companies know this and have found there is a strong business case to begin a PIM initiative, even if it starts by addressing only a specific business issue within one line of business.

Assessment

Most businesses today rely on a complex array of enterprise applications and information systems. Each application or system has specific functionality, handles data about products or materials in its own way, stores it in a separate data store and may be unable to exchange and synchronize the data with other systems. The result is inconsistency in product data across the organization. These disconnects between applications and inconsistency in product data can have costly impacts on a company. Requests for information can take weeks, not days, to satisfy - an unacceptable delay given today's accelerated pace of business.

In this context, product information management is an increasingly popular solution. PIM includes all the steps and supporting information management technologies to produce complete, consistent and reliable product records. Based on the insights gained from our benchmark research results and the experiences of the most successful companies that manage product information, Ventana Research recommends that IT departments work with business units and potential partners to develop a business case for adopting PIM technology that not only takes into account the full cost to the business of errors arising from incorrect and inconsistent product data but also identifies the key performance indicators (KPIs) that they will use to monitor and assess success.


Colin Snow is VP and research director - Operational and Supply Chain Performance Management. Snow heads up the Ventana Research Operational Performance Management (OPM) practice focusing on the alignment of business and information technology in the areas of supply chain, operations and business process management.  His research investigates what organizations need to manage their operational processes and supply chain for performance improvement.  

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