COM A. White, D. Hope-Ross, K. Peterson, D. Ackerman

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1 A. White, D. Hope-Ross, K. Peterson, D. Ackerman Research Note 7 February 2003 Commentary Product Content and Data Management Promises Savings By 2013, standardized ways of describing products will prevent errors and help manufacturers, distributors and retailers cut costs. Implementation will not be cheap, but the payoffs will be too big to ignore. Product data is the DNA of the value chain. Without it, no trade could take place. Product data describes what a product is; how to make it; how it's designed; what is needed to trade it; and what its purpose is. How enterprises create, store, associate, consume, distribute and manage product data directly affects their bottom-line profits. Yet enterprises traditionally isolate product data inside departments, and behind their own four walls. It will take between three and 10 years to change the relevant applications, skills and behaviors to broader approaches. Product content and data management (PCDM) is a set of related disciplines, technologies, and solutions used to create and maintain consistent interpretation of product data to facilitate commercial exchange. PCDM seeks to describe the very basic objects of commerce, the items that organizations buy and sell, based on design and manufacturing information, helping to create and enrich vocabularies so that enterprises can share a common language. By 2013, PCDM will be key to strategies using transaction cost reduction to improve operational efficiency. It is naïve to think that data on every product worldwide can be described through the same semantic structure. PCDM must embrace a more heterogeneous environment, supported by architectures that exploit semantic reconciliation. This will require investment, proactive administration and selective adoption of a wide array of technologies, but will be justified by businesses' constant need to improve the efficiency of their commercial transactions. PCDM will be propelled from obscurity to ubiquity, as a common underpinning of buy-sell processes and a catalyst for change in supply chain management (SCM). The Dimensions of the Problem All organizations create and consume product data. Data about a specific item may be generated by product definition systems in the design and engineering departments. The data may then used by manufacturing processes. For example, a milling machine may use it to cut the metal to the correct size (see "PLM Success Demands Product Data Exchange," SPA ). During final assembly, the Gartner 2003 Gartner, Inc. and/or its Affiliates. All Rights Reserved. Reproduction of this publication in any form without prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The reader assumes sole responsibility for the selection of these materials to achieve its intended results. The opinions expressed herein are subject to change without notice.

2 product data may be combined with external data, such as supplier part numbers or purchase order data, to create bills of materials and bills of resource. The sales or distribution process may use the same core product data, as well as additional information, to interact with buyers or market intermediaries. Predefined data exchange schemata and structures can support procurement and sourcing initiatives from established and potential customers. PCDM will emerge from this need to sustain multienterprise business process improvement. It cannot be done without synchronized and unified product data. The Power of Inhibition PCDM will evolve and spread extremely slowly until well into this decade. Broad-based, multienterprise PCDM will not be widespread before This slow development is because: PCDM will require culture change. Moving from managing data and processes autonomously, on a departmental level, to coordinating data and process management across the enterprise or industry can occur only very slowly. New behaviors, organizational structures and reward structures must evolve to support this transition. The history of other enterprisewide and industrywide initiatives suggests painfully slow progress. PCDM will require tremendous investment. Many organizations will find it difficult or impractical to devote the technical, human and financial resource required to address the complexities of PCDM. Precursors to PCDM, such as business-to-business e-marketplaces and aggregated catalogs, have not found a successful business model. Standards are evolving slowly and with difficulty. Even a very high-level item categorization schema, such as the Universal Standard Products and Services Classification, is experiencing adoption problems. The domain knowledge is esoteric. Organizations will have to retrain to fully understand and react to PCDM. Although it may be easy to agree that not adopting PCDM is costing an organization money or opportunities, it is often unclear who should lead PCDM projects or how they should be funded. To be successful, PCDM must involve many departments; therefore, it must compete with many other initiatives for senior management attention. From Present to Future Organizations lack uniform, structured methods of creating and exchanging data to describe objects of commerce, such as goods or services. The absence of uniform ways to represent product information has greatly diminished the ability to share information within and among enterprises, preventing technology-driven, supply-chain advances in efficiency. Yet every organization in the value chain creates and uses product data. Heterogeneity in creation and consumption drives diversity in the form and use of product data throughout the product creation, manufacturing, distribution and sales cycles. The diversity of associated disciplines has created a fragmented view of product information and generated singleenterprise, departmental responses to the problem (see Figure 1). PCDM will slowly evolve to address this issue. 7 February

3 Figure 1 Value Chain Scope of PCDM Source: Gartner Research Some industries are trying to solve this challenge, as shown by the proliferation of industry standards. Through 2013, industry standards will fail to solve enterprise PCDM challenges because enterprises typically operate within an industry matrix (that is, they are part of more than one industry and must conform to several sets of standards because of the variety of items they buy and sell). Although a consistent approach at an industry level is helpful common semantics, terminology, descriptive data and units of measurement it will not solve the problem on its own. Industries have not yet moved beyond this basic understanding, but if they do not solve the problem of consistent product data, they will lose competitive advantage. The Role of Application Vendors Major application vendors are unlikely to help solve this problem. Gartner expects that mainstream business application vendors will make little progress in supporting enterprise PCDM initiatives. This is because: The cross-departmental and cross-enterprise nature of PCDM means that there will be no single buying center. The complex and obscure nature of the discipline makes it difficult for vendors and decision makers to understand. Vendor attempts to manage isolated aspects of the challenge, such as e-procurement catalogs and e-marketplaces, have failed or performed poorly. Standards bodies such as RosettaNet and the Uniform Code Council (now merged into one body) have advanced painfully slowly in addressing the problem. Industry-level solutions increase the complexity and expense of the project and slow down decision making. Services and solution components lacking as an integrated, interoperable, scalable, proven offering. 7 February

4 Though 2008, 80 percent of mainstream application vendors will fail to articulate and create solutions in response to the PCDM challenge (0.8 probability). However, from 2008, technology-driven SCM advances and concrete business drivers focused on industrywide transaction cost reduction will propel PCDM to the fore. Quantifiable Costs of Ignoring PCDM: Managing product data at departmental or enterprise level encourages the development of separate collections of data that are contradictory, incomplete or obsolete. The cost of this "bad" data is incalculable. The business implications of poor product data include: Lost revenue: Sale of goods will be delayed because incorrect items are sent and must be reprocessed. Higher material costs: Users will not be able to spot errors when invoiced goods arrive, so the company must bear the cost of returns. Users unable to find items may use other suppliers. Procurement inefficiency: Mismatched product definitions and supporting data can make it difficult to see what has been ordered, leading to high transaction error rates and incomplete records of spending against budget. Higher sales and marketing costs: Suppliers must maintain multiple catalogs, even though customer needs are identical. Manufacturers must organize credit returns for salable products when distributors incorrectly package or label products. Higher corporate overhead: IT budgets increase every year to support new interdepartmental data cleaning programs. Some industries have already begun working on PCDM initiatives. The cost of bad data was quantified at the 1Q99 ECR conference. For the U.S. grocery industry, up to 1 percent of net revenue lost, and one in 2,000 of sales lost because the item was out of stock, were attributable to bad master data. This is because the processes and activities in the value chain assume that a pear is a pear. But if the scanner, purchase order or bill of material records that it is an orange, the processes fail and things stop working. Conflicting interpretations of events and inaccurate inventory balances then lead to slow or stalled payment cycles. Indirect Costs of Ignoring PCDM: The "soft" costs of ignoring PCDM are incalculable, but include competitive disadvantage and decreased flexibility. Business decisions will be based on out-of-date information because of delays receiving data. Strategic PCDM Business Drivers Beyond the financial implications associated with poor product information lie more strategic issues. When data describing products is not synchronized among trading partners, or is obsolete, friction in the trading processes is increased. This increases latency and erodes efficiencies. This impedes supply chain visibility, so that trading partners view the same items differently. Collaborative commerce a discrete set of business processes leading to more advanced competitive advantage for enterprises working together will be blocked because the underlying information is scrambled. Additional processes will have to be developed to cope with this mismatch in product information, costing more money. Therefore, the costs of ignoring PCDM include greater supply chain latency, competitive disadvantage and lower flexibility. 7 February

5 Bottom Line: Managing product data in a multienterprise environment will assume increasing importance during the next five to 15 years. Traditionally, product data has been dealt with on a departmental level, leading to isolated "silos" of contradictory information. Enterprises should adopt a holistic IT strategy that seeks to meet multiple industry standards and synchronize definitions. However, development of solutions and adoption will be slow, despite the potential for business improvement. Organizations should remain committed to observing and adopting techniques selectively as they emerge and evolve. The pioneers to watch are the consumer packaged goods, retail and high-technology industries. 7 February