Data Governance in the B2B2C World

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1 WHITE PAPER Data Governance in the B2B2C World Today s empowered consumers and their demand for product data have given rise to challenges in product data management. Manufacturers and retailers more than ever need to ensure that the increasing amount of data about their products is accurate, complete, and relevant to create a positive consumer experience. Consumer shopping behavior has traditionally been influenced by manufacturers and retailers. However, that trend is changing significantly due to the multitude of virtual shopping options and information sources available to consumers. Today s consumers are increasingly leveraging information provided through mobile devices and social networks to enrich their shopping experience. These empowered consumers and their demand for product data have given rise to challenges in product data management. Manufacturers and retailers more than ever need to ensure that the increasing amount of data about their products is accurate, complete, and relevant to create a positive consumer experience. In addition to these challenges, manufacturers have traditionally experienced significant internal issues related to the availability, collection, and publication of finished product data to downstream trading partners. These are manifested, for example, in the new item set-up process when manufacturers may need to send basic attribute and retailer-specific data in various formats. From a retailer s perspective, any inconsistencies in product data provided by manufacturers may result in multiple issues ranging from warehouse operations to shelf space utilization to consumer protection agencies. These issues are distributed throughout the product data chain, and if not addressed, may impact business continuity and growth for manufacturers and retailers. In this evolving environment of increasing data complexity and volume, organizations need to streamline their existing processes while improving decision making through market insights about consumer behavior. They are also realizing the need to treat product data as a strategic asset to gain a competitive advantage. However, few realize the benefits of handling these assets through effective governance. This article presents an approach for managing this new data world with sets of tools and controls through the implementation of a data governance program. 1

2 B2B2C B2B B2C MANUFACTURER RETAILER/E-TAILER RETAILER/E-TAILER CONSUMER Dimensions Weights Seller Nutritional / Manufactuer Compliance Price Data of Availability Seller Product / Manufactuer Description Promotions Price Data of Availability Seller Product / Manufactuer Description Promotions Reviews Ratings Seller Social / Manufactuer Media Location Current Challenges The Case for Data Governance TODAY S B2B The challenges in product data management result from an increasing amount and variety of data required by data recipients. In other words, while manufacturers may focus primarily on data related to their internal operations, their trading partners are interested in a different set of product data attributes. These interests are continually broadened by evolving regulations around material handling, environmental sustainability, and consumer protection to name a few. The accuracy and completeness of this larger data set is critical to the retailer s compliance and merchandising efforts. Moreover, manufacturers may need to meet certain requirements about the format and timelines when providing data to retailers. The potential costs and risks associated with not satisfying these requirements could be significant enough to affect the bottom line for all participants in the data chain. EMERGING B2C In today s age of technology-savvy consumers, multiple online sources are being accessed to get additional value-added content about a product. For example, an e-tailer s website may display the weight, dimensions, and basic attributes that originate from the manufacturer. In addition, it may also be the source of attributes such as categories, features, promotions, ratings, and price comparisons for that product. Further, the consumer may tap into internet application providers (IAPs), mobile applications, and social networks to obtain additional information and share reviews about that product. This growing stream of structured and unstructured product data in the B2C space, which is generated by both organizations and individuals, is valuable to all parties. Consumers are using it increasingly to enrich their shopping experience while organizations are looking to draw insights not just about consumer behavior but also product performance. DATA EXPLOSION IN B2B2C The most significant multiplier for the complexity and volume of product data is the set of touch points across the entire data chain. Ranging from the manufacturer to the retailer, these interfaces transform the structured product data not only to highlight product features but also to meet specific trading partner requirements. In addition, the unstructured product data generated by e-tailers, IAPs, and consumers adds to the ever-expanding volume of available product data. The combination of these sources is giving rise to a data explosion in the product data management space. This data explosion can strain organizational capacity at all points in the product data chain as it is increasingly leveraged for competitive differentiation. According to a survey, 38% of consumers would not purchase the product if they did not trust the product information displayed about it on their smartphone. 1 It is essential to maintain the quality and reliability of the product data that ultimately influences the consumer s shopping behavior. To achieve this objective, a data governance program has become an essential tool for effective management of product data. 1. B2C Consumer Survey, GS1, March

3 Definition of Product Data Governance Product data governance is a disciplined approach for administering the product data of an organization that ensures a credible single source of truth while maintaining data quality. The overall structure and execution of product data governance can vary among organizations but is commonly comprised of three primary components: Organizational alignment around governing principles and program objectives Data lifecycle management for the entire product data chain Data ownership to drive accountability and ensure product data quality Manufacturer B2B Retailer/ E-tailer B2B2C Data Governance Consumer B2C A study conducted by GS1 UK and the Cranfield School of Management found that 91% of mobile barcode scans returned incorrect product descriptions and 75% returned no product data at all. 2 A sophisticated data governance program can increase the possibility of improving the completeness and quality of data in the entire B2B2C product data chain. Handling these issues in an efficient and timely manner can provide a competitive edge in exceeding customer satisfaction. Strategic Focus Areas for Product Data Governance Data governance needs to be a collaborative program initiated across multiple touch points to gain alignment throughout the entire organization. Each organization and its product data are unique and the approach for building a data governance strategy can differ significantly. However, there are core areas of strategic focus that organizations need to address in their data governance program. 1 Technology Standards PROGRAM GOALS AND OBJECTIVES A data governance program should be developed on a business case that recognizes and supports larger organizational goals. A clear organizational alignment about the definition of data governance, identification of objectives, and establishing scope are critical in determining priorities within the program. Furthermore, it is also important to evaluate the program s success through the development and publication of specific performance metrics related to new product introduction and ongoing maintenance. These Goals and Objectives Product Data Governance Data Quality performance metrics are an essential step in communicating the program s benefit to all levels of the organization. As the organization s business evolves, these goals, objectives, and metrics must be periodically re-evaluated and re-aligned with business priorities. 2 Structure and Roles Data Mangement Processes GOVERNANCE STRUCTURE AND ROLES A data governance program requires an organization to establish a governance structure as well as define and empower specific roles for product data management. This structure and roles can be organized by either a centralized, decentralized, or hybrid model which includes oversight by a governing board. In addition, these roles must fit the cultural and the practical realities of the organization. Specific governance roles related to product data management tasks and responsibilities should report either directly or indirectly into the governing board. In addition to the governance roles, the program must establish business roles and responsibilities as well as define broad obligations of other stakeholders. 2. Mobile-savvy shopper report, GS1 UK and Cranfield School of Management, January

4 3 DATA MANAGEMENT PROCESSES Establishing the right data management processes is fundamental to governing product data. These processes lie at the critical intersection of governance objectives and functional execution. Optimizing these processes ensures that ownership and accountability is established. Usually, there are multiple owners representing different areas of the business coming together to create and maintain the entire product data record. However, these areas may have differing priorities. Experience with both data sources and data recipients has shown that issues arise due to lack of clear understanding about ownership and accountability. In such cases, the coordination and communication achieved through governance are vital to resolving these issues. It is this facilitation among different business areas that keeps the data management processes flowing smoothly, thus contributing towards faster product setup and completeness of data. 4 DATA QUALITY The quality of product data is becoming increasingly important for businesses to enrich the consumer s shopping experience. Therefore, data quality is essential to maintaining a competitive advantage in today s B2B2C world. 74% of consumers using mobile applications consider it important that product information is trustworthy and 35% would never use an app again if it contained incorrect product information. 2 Substandard data quality not only costs organizations by way of lost sales but also can undermine its credibility and brand image. Based on our experience, a lot of organizations are reactive instead of being proactive in addressing data quality. Reactive organizations do not recognize data quality issues in certain areas due to the lack of focus and specific measures. On the other hand, proactive organizations ensure high quality data through constant assessment and monitoring of their product data. 5 TECHNOLOGY Technology does not provide governance by itself. It enables the execution of business functions and provides a means to govern that execution. It also helps optimize governance functions by connecting business processes to governance controls. The right levels of control, enabled through technology, can prevent governance from being an overwhelming task that impacts process efficiency. During multiple technology implementations like data synchronization solutions, data accuracy tools, and product information management systems, we have come across some common pitfalls that organizations tend to overlook. These include using technology capabilities to define business processes, underutilizing control functionalities, ineffective process design, and ignoring product data quality. Developing and implementing a well-defined data governance strategy in parallel with the technology implementation can help in avoiding these issues. 6 STANDARDS Product data must be standardized for efficient and scalable information exchange between trading partners throughout the supply chain. Data governance must take into full consideration the adoption and usage of standards into business process and technology. A globally aligned product identifier, such as the GTIN, allows a product to be uniquely identified on a global scale. Product packaging measurement standards provide tremendous value in the fact that any party in the supply chain can correctly interpret critical logistical information about a product. Classification code sets, like Global Product Codes (GPC), allow a single common classification scheme across for all consumer products, irrespective of the industry. To successfully implement a data governance practice, standards must be applied to ensure accuracy and consistency. Data Governance Success Factors EMPOWERED LEADERSHIP The executive sponsor of the program plays a critical role in providing the necessary organizational support for a product data governance effort. This role facilitates key executive-level connections across the various business areas to gain alignment on priorities. The executive sponsor is also responsible for building a strong working committee of product data stakeholders from key business areas like product management, manufacturing, supply chain, marketing, sales, logistics, finance, IT, and customer service. 2. Mobile-savvy shopper report, GS1 UK and Cranfield School of Management, January

5 The most significant multiplier for the complexity and volume of product data is the set of touch points across the entire data chain. QUALITY MANAGEMENT Product data quality issues can surface far removed from the initial source of the error. Determining the root cause of quality issues along with having a process for managing these issues helps ensure permanent resolution. It is important that product data governance looks beyond its organizational boundaries to develop external feedback channels about data usage and data quality with upstream suppliers and downstream customers. Tools like the Global Data Synchronization Network (GDSN ) and data accuracy scorecards are used by both manufacturers and retailers to consistently measure their product data quality, identify discrepancies, and actively collaborate on improvements. PERFORMANCE MEASUREMENT Establishing metrics and KPIs within the data governance program is critical for evaluating the effectiveness of the program as well as communicating its value to the organization. Some common KPIs include: product data quality for weights and dimensions, number of changes to product data, invoicing discrepancies, pricing errors, inconsistent product hierarchies, and incorrect GTIN assignments. METADATA MANAGEMENT Metadata management of product data includes development of clear functional and technical definitions for data attributes. This process can be initiated by focusing on the data attributes that are shared with trading partners and/or consumers. This metadata can include code value sets, standards, technical specifications, communication protocols, aliases, validations, and delivery mechanisms. REFERENCE DOCUMENTATION AND MAINTENANCE A comprehensive set of documentation that specifies topics ranging from strategy to tactic is essential for overall clarity and accountability. Governance policies, product data workflows, and standard operating procedures need to be updated as changes occur. All documentation needs to be reviewed at least annually with participation from all key stakeholders. In addition, the creation of ad hoc workflow documentation at the individual user level must be discouraged. Deviations from the standard processes should be reviewed and approved by all stakeholders. CHANGE MANAGEMENT It is a challenge to coordinate numerous interwoven product data processes and owners, with different priorities, to work towards the common objectives. This may require participants to change their traditional methods and adopt new ones as part of the data governance program. Seemingly small changes to product data can have wide reaching impacts across the data chain. Handling this complexity requires horizontal and vertical organizational alignment, as well as excellent understanding of the end-to-end product data chain. This can be achieved by undertaking a change management initiative across the organization. It needs to take into account the organizational culture and implement a methodology to manage the rate and scope of change required for the program. Communication and training are helpful tools towards preparing for this change. 5

6 For more information, contact: ALI MOOSANI VP Professional Services T M E NIKHIL PUJARI Advisory Services Manager T M E Conclusion Today s consumers are increasingly leveraging information provided through mobile devices and social networks to enrich their shopping experience. This experience is strongly dependent on the completeness and accuracy of product data. Brand owners and retailers are coming to the realization of this trend and have started treating product data as a strategic asset. Data governance provides a means to establish the essential controls and strong focus on product data within an organization to achieve the objective of providing complete and accurate data to the consumer. Why 1WorldSync? 1WorldSync manages the world s product data so that companies can share trusted product information with each other and with consumers, driving business and convenience for everyone. As the industry leader in global product data management and data pool solutions certified for the Global Data Synchronization Network (GDSN), 1WorldSync can meet the needs of any trading partner in any industry. 1WorldSync is part of GS1, the developer of the global standards for identifying, capturing, and sharing product information. 1WorldSync Professional Services are based on our diverse expertise in Product Data Management implementations. Our core strengths are in business process optimization, data accuracy, data governance, and strategy management. Valued as a trusted partner enabling organizations to meet current challenges around Product Data Management on both strategic and operational levels, 1WorldSync leverages over a decade of experience in implementing suppliers, distributors, operators, and retailers on PDM solutions. An assessment evaluates the usage of standards, technology, and industry best practices in current business processes to achieve operational efficiencies. It provides guidance around industry best practices and enables organizations to increase value chain efficiencies by eliminating costly data errors. It also provides a complete gap analysis along with a vision for the future state and next steps. More than 15,000 customers across 40 countries. Joint venture locations across the globe. Connect With Us: 1WorldSync WorldSync 1009 Lenox Drive, Suite 202, Lawrenceville, NJ USA T F E 1worldsync.com

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