Data Quality Lunch and Learn

1. Data Quality Lunch and Learn Gabriel Sobrino GSMP Spring Event 2008 Brussels, Belgium

2. Agenda • What is Data Quality? • What is the Data Quality Steering Committee? • What is the Data Quality Framework? • The Data Quality Challenge • How can I learn more?

3. 1.- What is Data Quality?

4. The industry must be able to trust the quality of data flowing through the GDSN! Why Data Quality? • To realise the full potential of the GDSN, Trading Partners must ensure the following: • Accurate product information is aligned across internal manufacturer systems • Good quality product information is synchronised through the GDSN • Product information within retailer systems is aligned with product information received via the GDSN

5. Manufacturer Source Systems PIM/Publication Process Product Information GDSN PIM/Receiving Process Recipient Systems Retailer Data Quality Principles Las 5 dimensiones de la calidad de datos*: Completeness All the required values are electronically recorded Standards-based Data conforms to industry standards Consistency Data values aligned across systems Accuracy Data values are right, at the right time Time-stamped Validity timeframe of data is clear *Source: GCI/CapGemini Report: “Internal Data Alignment”, May 2004

6. 2008 2009 Why are internal processes important:The “Leaky Pipes” of Data Quality Internal processes Internal Process Constant data corrections and fixes

7. 2.- What is the Data Quality Steering Committee?

8. What is the DQ Steering Committee? • The Data Quality Steering Committee is a group established to function as an advisory body to the Board of Directors of GS1 GDSN Inc. under the stewardship of GS1 (management & funding). The steering committee is responsible to manage the Data Quality Framework.

9. GS1 Management Board GS1 GDSN, Inc. Board of Directors Data Quality Steering Committee (DQF) Data Quality Adoption Subgroup

10. Mission The purpose of the Data Quality Steering Committee is to guide the industry toward improved data quality from source to consumer.  We are committed to developing the Data Quality Framework, tools and education, complemented by best practices for all users, addressing the business needs and incorporating continuous improvement feedback from the industry.  The ultimate objective of these deliverables is to positively affect data quality in the supply chain as used by trading partners across a variety of sectors and especially within GDSN, to reduce cost, increase efficiency and consumer satisfaction.

11. Tasks • Data Quality Framework The Steering Committee will own, produce and maintain the GS1 Data Quality Framework to be used as a “best practice” guide collaboratively by trading partners. • Self-Assessment The Steering Committee will be responsible for the ongoing maintenance of the DQ Self-Assessment procedure. The Self-Assessment enables companies to assess their own internal processes for data management against the GS1 Data Quality Framework. • Certification The Steering Committee has the responsibility to evaluate the need and readiness for a data quality certification process and, if necessary, to create a definition and model.

12. Tasks • Continuous Improvement The Steering Committee recognises that our industries are dynamic and changing. As best practices and standards evolve, the Steering Committee will implement and maintain a feedback process for continuous improvement and relevance of the DQ Framework. • Industry Benchmarking The Data Quality Steering Committee is responsible to develop benchmark measurements for tracking the success of implementing the Data Quality Framework. • Marketing, Communication and Education One of the key value-added responsibilities of the Steering Committee is to support the adoption of the Data Quality Framework through: • Marketing - Sharing compelling business cases and desired outcomes. • Education - Enabling the necessary knowledge and tools. • Communication - Continuously informing the extended industry community and constituent groups on progress and timeline of Steering Committee activities to increase awareness.

13. 3.- What is the Data Quality Framework?

14. The Data Quality Framework • The Data Quality Framework (DQF) brings together a comprehensive set of best practices that organisations can follow to set up internal processes for data quality. The DQF provided the basic elements for a sustainable, long term solution for data quality.

15. Data Quality Framework Guiding Principles • Based on user needs • Strongly encouraged, yet voluntary • Can adapt to the needs and requirements of specific trading partner relationship • Comprehensive, yet flexible • Can be included in any kind of quality management system • Minimises implementation costs – enabling benefits • Complementary to GS1 System standards • Open to several ways to show compliance

16. Data Quality Framework • Main sections: • Data Quality Management Systems (DQMS) Requirements, including chapters on: • Self-declaration • Certification • A management system like ISO 9000, aimed at the proper management of data • Self-assessment procedure • Procedure to execute a self-assessment • Questionnaire to assess conformity to DQMS requirements • KPI Model to validate actual accuracy of the 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

17. The Industry “DQ Framework” Elevator Pitch Rationale & Benefits: Without good, accurate data, Global Data Synchronisation will only enable the rapid, seamless transfer of bad data! Data Quality 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 Framework 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 and support the trading partners For more information visit the link below: http://www.gs1.org/dataquality

18. 4.- The Data Quality Challenge

19. How to get started Step 1Acknowledge you are not where you would like to be on data quality Step 2Decide to take on the Data Quality Challenge Step 3 Familiarise yourself with the DQF Step 4 Do a self-assessment using the DQF

20. Closing the cycle Step 5 Evaluate results of the assessment and plan changes Step 6 Implement changes Step 7 Re-assess your organisation Step 8 Enjoy the benefits from good quality data 20

21. Timeline Feb 09 April 08 May 08 Aug 08 Dec 08 Project kick-off Education and preparation Self- assessment phase Results calculation Publication of the results (phase 1)

22. 5.- How can I learn more?

23. Data Quality Resources • Global Data Quality Helpdesk: dataqualityinfo@gs1.org • New and improved Data Quality Website: http://www.gs1.org/gdsn

24. GDSN Data Quality Web Site Resources • Data Quality Framework and support documentation • Frequently Asked Questions (FAQs) • Data Quality Implementation Guide • Data Quality Program Internal Implementation Example • DQ Framework Background Presentation • Data Quality Videos • Links to Related Technical Documents • Measurement Tolerances Standard • Package Measurement Rules for Data Alignment • GDSN Standards Documents

25. Contact Details Gabriel Sobrino Programme Manager, Data Quality GS1 GDSN, Inc. T + 31 20 5113898 E gabriel.sobrino@gs1.nl