Data Quality Training Introduction to Data Quality Principles

Data Quality Training Introduction to Data Quality Principles and The Data Quality Framework

Data Quality Training Introduction – Liz Crawford-Rowe • About 20 years of experience in healthcare, product distribution and online B 2 B • Master of Business Administration from the Rice University, Jones Graduate School of Management • Team Lead, Sysco Corporation responsible for Information Governance, Material Enrichment and SAP • Director, of Data Quality for GS 1 GO © 2012 GS 1 2

Data Quality Training Objectives • Acquire a fundamental understanding of the principles of data quality • Learn how to apply the Data Quality Framework as a tool for data quality improvement • Obtain recommendations for developing local programs that support data quality improvement for members • What are your objectives? © 2012 GS 1 3

Data Quality Training Overview Quality is not an act, it is a habit. Aristotle Quality means doing it right when no one is looking. Henry Ford

Data Quality Training Schedule & Agenda Morning Sessions What is Data Quality (DQ)? - An Introduction Why is DQ important? - The Business Case for DQ Break How do you Improve DQ? Best Practices & the Data Quality Framework (DQF) Lunch Afternoon Sessions How do you Measure DQ? - DQF Self Assessment & KPIs How do you Organize for DQ? DQF Data Quality Management System Break How do you facilitate DQ? - DQ Programmes & Services DQF Case Study - P&G & GS 1 Mexico Adjourn © 2012 GS 1 5

GS 1 & Data Quality The Goal GS 1 delivers neutral industry standards, that Create a foundation of common data elements, whereupon Best practices may be applied, to Generate high-quality information assets, Shared via an impartial, transparent, global network, Used to make informed business decisions, ultimately Creating a competitive advantage, that Maximizes business and shareholder value. © 2012 GS 1 6

What is Data Quality? An Introduction “I know it, when I see it” Potter Stewart, Associate Justice, US Supreme Court “Be a yardstick of quality. Some people aren't used to an environment where excellence is expected. ” Steve Jobs

Data vs. Information Data are a component of Information Data • Facts or statistics; a series of observations or measurements. Information • Knowledge gained or acquired concerning a particular fact, or set of facts. • © 2012 GS 1 The goal is to generate complete, accurate and unambiguous facts on which to support informed business decisions.

What is Data Quality? What DQ is not • DQ is not a tactical “IT task” • DQ is not a one-time solution • DQ is not linear • DQ is not technology specific • DQ is not a “thing” – like a program or application - it’s a perception © 2012 GS 1 9

What is Data Quality? Operational Definition Data Quality is a perception or an assessment of data's reliability and fitness to serve its purpose in a given context. Data are of high quality "if they are fit for their intended uses in operations, decision making, and planning" (J. M. Juran). Quality Control Handbook, New York, NY: Mc. Graw-Hill, 1951 © 2012 GS 1 10

What is Data Quality? Operational Definition - Dimensions • • Complete • Is data missing? Consistent • Is data consistent across systems for the same field? (zip code - 5 or 9)? Accurate & Timely • Is data precise, correct, and current? Standards Based • Have formatting rules and global standards been applied? Logical • Is data valid or conflicting across data sets? (Does L x W x H = Cube? ) Integrated • Are there appropriate data linkages between systems? Unique • Are there unnecessary representations of the same data? 11 Without enterprise-level controls on data, the information generated will not provide reliable support for business decisions. © 2012 GS 1

What is Data Quality? Operational Definition - Dimensions System Accessibility Ease of Manipulation Timeliness Value Added Use Reputation System Supported Free of Errors Completeness Purpose IQ Objectivity Amount of Information Representation Relevancy Concise Representation Content Inherent Understandability Interpretability Believability Consistent Representation * DGIQ 2007 © 2012 GS 1 12

What is Data Quality? Customer Definition “Quality in a product or service is not what the supplier puts in. It is what the customer gets out and is willing to pay for. Customers pay only for what is of use to them and gives them value. Nothing else constitutes quality. ” ~Peter Drucker “Retailers need to think of their business as a multi-channel environment that can potentially include mobile, online, and bricks and mortar stores. Winning with shoppers requires a consistent experience across channels …whether it be price, service, reviews, selection, style or other key attributes. " John Burbank, President of Strategic Initiatives, Nielsen (PC World, 3/12/12) © 2012 GS 1 13

Information Supply Chain – B 2 B 2 C Synch Aggregators Business Users DQ Data Providers © 2012 GS 1 Supply Demand End Users Data Recipients 14

What is Data Quality? Responsibility Who is responsible for Data Quality? Ensuring DQ is the shared responsibility of all trading partners: • Data providers are the source of the product data and so are the starting point for needed improvements in process for creating good data • Data recipients have responsibility to maintain accurate data within their systems and ensure its integrity in their processes “Quality is everyone's responsibility” W. Edwards Deming © 2012 GS 1 15

What is Data Quality? The Foundation Data Quality is foundational. But, how big a foundation is needed? Not a formula: there is no E=mc 2 Your foundation is unique: Decisions regarding the breadth, depth, timing and application of DQ will determine the scope and resource requirements for DQ Chrysler Building © 2012 GS 1 Taipei 101 16

What is Data Quality? Key Concepts • Internal - Fit for purpose • External - it’s whatever the recipient perceives as value • Specific to now – e. Commerce – consistent unified experience across channels • Joint responsibility • DQ must be a foundation • © 2012 GS 1 Operational improvement only is short sighted. For long term benefits & organization viability you need a strategic approach to DQ 17

What is Data Quality? Insight The goal is to provide complete, accurate and unambiguous facts on which to support informed business decisions. Information assets A fundamental change in information governance and business processes related to data and how it is managed. It is the strategy and organization used to manage people and business processes and enabled by technology. © 2012 GS 1 18

What is Data Quality? Mission Create a competitive advantage by implementing DQ Strategy that combines People, Processes, and Technology to generate high quality information assets which can be leveraged across the enterprise to maximize business and shareholder value. People Data Quality Technology Process 19 © 2012 GS 1

What is Data Quality? Data Governance To fully exploit and utilize the data available, a strategic approach to data governance at the enterprise level is required. Manufacturing Distribution Retail Data Governance The formal designation of People, across lines of business, function, and location, to enable an organization to leverage data as an enterprise asset Local Regional Corporate Finance Operations Marketing © 2012 GS 1 20

What is Data Quality? Processes To support data governance, business processes must be developed from industry best practices using global standards; with additional input from academia, industry groups, and other thought leaders. Optimized* Business Processes characterized for the organization, are proactive and application neutral. They are quantitatively measured and controlled, and the focus is on continuous process improvement *Capability Maturity Model Integration (CMMI) © 2012 GS 1 21

What is Data Quality? Technology To enable data governance, the technology group must understand how the business uses data and codifies the business processes which ensure data quality. When Data is entered, stored, transmitted, and reported. Why How © 2012 GS 1 Where Technology Providing technology to support data governance and business process, as defined by the business, to enable organizational and operational efficiency. 22

What is Data Quality? Requirements People Process Technology © 2012 GS 1 • Enterprise Organization Structures & Awareness • Information Stewardship • Information Policies • Information assessment • Information Risk Management & Compliance • Data Quality Management • Classification & Metadata • Information Lifecycle Management • Audit Information & Reporting • Data Architecture • Information Security & Privacy 23

What is Data Quality? Strategy - Essential Elements • Data managed at enterprise level • Development efforts that affect critical business data championed from the top down and supported with change management processes • Data ownership & accountability; clearly defined roles & responsibilities • An enterprise forum to ensure end-to-end impact assessment of all data management efforts • Adoption and enforcement of best practices including standardization, definitions, rules and business processes. A strategic approach to DQ generates accurate and reliable business information which becomes an enterprise asset. © 2012 GS 1 24

What is Data Quality? Strategy - Key Activities (JIMO) JIMO • Justify • Establish the Business Case • Improve • Best Practices, Standards, Policies & Procedures • Measure • Identify Critical Business processes and develop Key Performance Indicators/KPIs linked to them • Organize • “Independent” organization managing DQ at the enterprise level. © 2012 GS 1 25

What is Data Quality? Summary - Elevator Pitch • Data Quality is a perception of fitness and value that enables business to function efficiently. It is dependent upon shared responsibility; supporting and encouraging a common understanding of facts. • To generate data of high quality, and produce strategic information assets, an organization must execute an enterprise-wide strategy and deploy an organization to manage the people, business processes and technologies that enable them. © 2012 GS 1 26