Data Quality Protocol and Data Synchronization 23 October 2006

Video: “The Sales Call of the Future” This is from the title master template (except for the text)

Data Quality and Data Sync Data accuracy is the responsibility of both manufacturers and retailers Elements: Physical inspection, accuracy of item data, and internal processes Data quality activity will track with data sync activity Data quality is foundational to data sync Initiatives should take place in tandem

Realizing Benefits Requires… To realize the full potential of the GDSN, Trading Partners must ensure the following: Accurate product information is aligned across internal manufacturer systems Accurate product information is synchronized through the GDSN Product information within retailer systems is aligned with product information received via the GDSN The industry must trust the quality of data flowing through the GDSN …

Data Quality Protocol Background

The 5 Dimensions of Data Quality* Manufacturer Source Systems Completeness Standards Based Consistency Accuracy Time Stamped Required values electronically recorded Data conforms to industry standards Data values aligned across systems Data values are right, at the right time Validity timeframe of data is clear PIM/Publication Process Product Information GDSN PIM/Receiving Process Recipient Systems *Source: GCI/Cap Gemini Internal Data Alignment Report, May 2004 Retailer

An Industry Call to Action … In late 2004 / early 2005, a number of different industry and country-specific work groups were independently formed to address the data quality issue However, the work groups encountered the risk of creating multiple solutions As a result, in April 2005, the GCI Executive Board recommended the creation of a Joint Business Planning Data Accuracy Task Force … with the charter to develop a framework for a global data quality solution

Created Data Quality Framework, including: Achievements Created Data Quality Framework, including: Data Quality Guiding Principles Data Quality Protocol (for industry review) Data Quality Management System (DQMS) Data Inspection Procedure Aligned with, or considered, other industry initiatives Measurement Tolerances Data Accuracy GSMP Project Team Internal Data Alignment (IDA) methodologies Agreed an industry governance model and transition and hand-off to GS1 (GDSN)

Steering Committee: Support GS1 GDSN GS1 (GDSN)– Data Quality Framework Manager Stewardship / Certification Oversight / Continuous Improvement Steering Committee: Support GS1 GDSN Accreditation Body Accredited Service Providers Service Providers Data Quality Protocol Trading Partners Legend Certification via accredited entity Compliance to protocol via non-accredited entity Compliance to protocol

Oversight and Governance

GDSN Inc. Organisation Chart

Governance and Management DQ Steering Committee reports directly to GDSN Board Terms of Reference Document outlines roles/responsibilities Staff Resources: Executive on loan (Ahold): Hugo Byrnes DQ Program Manager: TBD Sally Herbert

Steering Committee Members Manufacturers: Nigel Bagley - Unilever Sue Mackasey - Kraft Foods Terry Mochar - Reckitt Benckiser TBD Retailers: Bruce Hawkins - Wal*Mart Ruud van der Pluijm - Ahold Marianne Timmons - Wegmans GS1 Member Organisations: Hein Gorter de Vries - GS1 Netherlands Richard Jones - GS1 Australia Gabriel Sobrino Medina - GS1 Mexico Mary Wilson - GS1 US Note: Seeking a retailer/supplier Committee Chairperson.

Data Quality Within the GDSN Definitions How It All Fits Together

Data Quality Framework: Definitions Data Quality: The desirable characteristics of data as published in GDSN data pools and trading partner systems Complete, standards based, consistent, accurate and time stamped Data Quality Framework: Best practices for the management of data quality systems Depending on market needs, compliance can be demonstrated through: Self-declaration Third party certification based on inspection and auditing

Definitions (Continued) Internal Data Alignment (IDA): Internal management of data across various business systems to achieve data quality One aspect of achieving data quality Measurement Services: External measurement service to help businesses publish accurate dimensional data Offered by several GS1 Member Organizations and Data Pools Voluntary or mandatory based on market agreement

Data Quality Within the GDSN The Data Quality Framework In More Detail

Strongly encouraged, yet voluntary Guiding Principles Based on user needs Strongly encouraged, yet voluntary Based on the requirements of a given trading partner relationship Comprehensive, yet flexible Can be included in any kind of quality management system Minimizes implementation costs – enabling benefits Complementary to GS1 System standards Open to certification and self-declaration

Data Quality Protocol Two sections: Data Quality Management Systems Requirements, including chapters on: Self-declaration Certification A management system like ISO 9000, aimed at the proper management of data Data Inspection Procedure A procedure for the physical inspection of products and data Stand alone, or Part of a Data Quality Management Systems audit

Best practice procedures regarding how to manage data Data Quality Management Systems Requirements (Chapter 3 of the Framework) Best practice procedures regarding how to manage data Establishing a Data Management Policy Setting objectives Defining responsibilities Providing resources Establishing the work processes Establishing a database infrastructure Establishing an IT infrastructure Internal communications

Operational controls: Data Quality Management Systems Requirements (Chapter 3 of the Framework) II Operational controls: Data generation and verification Product measurement Data input Data publishing Measuring and monitoring Processing user feedback Establishing preventive action Establishing corrective action

Data Quality Management Systems Requirements (Chapter 3 of the Framework) III Closing the circle: Internal audits Management review Continuous improvement

Data Quality Management Systems Compliance Assessment Based on a given trading relationship, there may be a need to confirm compliance to the Data Quality Management System Requirements. This can be achieved through: Self-declaration (Chapter 4 of the Framework, under development) Third party auditing (Chapter 5) Chapter 5 provides requirements for the third party auditors

Inspection procedure (Chapter 6) Comparison of a sample size of actual product against related data Limited to key attributes: Global Trade Item Number Classification Category Code (yes or no) Trade Item Description (for information purposes only) Dimensions Content and weight Pallet configuration Procedure(s) to be used: Internally (self-declaration) Third party auditor

The Industry “DQ Protocol” Elevator Pitch Rationale & Benefits: Without good, accurate data, Global Data Synchronisation will only enable the rapid, seamless transfer of bad data! Data Accuracy is achievable & many companies are reaping benefits now What is it? A process for improving data quality within your business Who manages it? GS1 (GDSN) manages the protocol for the industry Why do I need to use it? Because inaccurate, unreliable data is costing you and your trading partners money What is the role of the GS1 Member Organisation? Educate the trading partners For more information visit the link below: http://www.gs1.org/dataquality

Key Activities

Governance and Management Establish foundational governance and program management Steering Committee formed (Jul-Sep 2006) Still seeking Chair and 2 committee members Terms of Reference Approval by GDSN Board (Jul-Sep 2006) Hire permanent DQ Framework Program Manager (Oct-Dec 2006)

DQ Protocol Maintenance Maintain, continually improve, and communicate the DQ Protocol July- September 2006 Draft of Implementation Guide User Implementation Example Help Desk and email Support Subcommittee formed to address MO Implementation of Protocol Initial KPI Questions incorporated into GCI Scorecard October 2006 – March 2007 Develop and Launch Implementation Program Plan Draft of MO Implementation Program Develop Marcomm Plan for DQ Protocol Education plan to community (includes course and webinars) Launch of Implementation Program to MOs Whitepaper on DQ and GDS Linkage Begin work on online course for DQ Protocol Develop Industry KPIs April – June 2007 Implementation Program completed and results communicated DQ Version 2.0 release DQ Protocol online course complete

Web Site Resources Data Quality Framework and Protocol Document Frequently Asked Questions (FAQs) Data Quality Implementation Guide Data Quality Program Internal Implementation Example DQ Protocol Background Presentation GCI Data Accuracy Video Links to Related Technical Documents Measurement Tolerances Standard Package Measurement Rules for Data Alignment GDSN Standards Documents GPC

Compliance: Self-Declaration, Certification and Accreditation Establish self-declaration and certification process Project launched with Capgemini, AIM B2B group, GS1 and several users to establish self-declaration structure (Oct 2006 – Mar 2007) Subcommittee formed to address accreditation and certification process (Jul – Sep 2006) Draft of Certification and Accreditation Plan (Jan – Mar 2007) Issue RFI for Accreditation Bodies (Apr – Jun 2007) Pilot Certification and Accreditation Plan (Jul – Sep 2007) Launch Certification and Accreditation Plan (Sep 2007)

Closing Comments and Discussion

Data Quality Momentum and Support DQ Protocol and the importance in relation to data sync initiatives GS1 Management Board GCI Executive Board GDSN Board of Directors EXECUTIVE MESSAGES: 1. INCREASE FOCUS ON DATA QUALITY PROTOCOL PROMOTION AND DEVELOPMENT 2. LINK DATA QUALITY TO DATA SYNC INITIATIVES

Critical Success Factors Consistent interpretation and implementation across Member Organizations (SME community) Education and awareness in key data pools supporting major retailers and manufacturers Completion and acceptance of Self-Declaration module Creation of a thorough but simple certification and accreditation process Continued industry awareness and focus on data quality as part of GDS

Questions and Recommendations What challenges do we face as we roll this out globally? Acceptance by the community? Is the importance broadly realized? How best to communicate? Formal education course (web-based or classroom)? Case studies: companies willing to participate in 2007? Self-declaration and certification Can self-declaration be “trusted” to provide necessary rigor? Is certification too complex for our short term needs?

For more information: www.gs1.org/dataquality dataqualityinfo@gs1.org Email Response