data quality 101 liz crawford, gs1 go director data quality & gdsn
TRANSCRIPT
© 2012 GS12
Agenda
• Defining DQ• Information Supply Chain• Business Case: B2B / B2C• DQ Recommendations• DQ Tools
“Be a yardstick of quality. Some people aren't used to an environment where excellence is expected.”
Steve Jobs
“I know it, when I see it”Potter Stewart,
Associate Justice US Supreme Court
© 2012 GS14
Define Data QualityWhat DQ is not
• 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 GS15
What is Data Quality?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: McGraw-Hill, 1951
Information Supply Chain
"In God we trust, all others bring data.“ Unknown
“Quality is everyone's responsibility” W. Edwards Deming
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© 2012 GS1
Challenge: It’s The Data…
Ventana Research conducted a multiple industry survey of large corporations and found the top five concerns regarding data to be:
1. We spend more time reconciling data than analyzing it (33%).
2. No one is accountable for the quality of information (17%).
3. We cannot determine which spreadsheet has correct data (12%).
4. It takes weeks to close our books (11%).
5. We duplicate R&D efforts (6%).
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© 2012 GS18
Information Supply Chain – B2B 2C
Data Providers
Data RecipientsDemandSupply
Aggregators End UsersBusiness UsersSynch
DQ
DQ Business Case
It is not necessary to change. Survival is not mandatory.”
~W. Edwards Deming
© 2012 GS1
How did we get here?
• Lack of data governance – an absence of ownership and
accountability for key data assets
• Lack of identified internal / external “authoritative” data sources -
leading to poor data accuracy within and across business areas
• Complex IT infrastructure (multiple systems, many LOBs)
• Silo-driven, application-centric solutions (TMS, SUS, HXA1)
• Multiple disconnected processes at local, regional, and corporate
levels which may be in conflict
• Tactical initiatives to “re-solve” data accuracy rather than
understanding and addressing root causes
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© 2012 GS1
£€¥$Data Quality Benefits – B2B
Enterprise Intangibles– Ease of doing business with Users– Decision making - inaccurate information
cannot support well informed decisions– Organizational trust– Confidence in enterprise
Risk– Regulatory– System investment & development (cannot
be fully utilized)– Integration (new systems, acquisitions)– Fraud – exploitation of failures or loopholes
within the system
Costs– Error prevention – (proactive)– Error detection and correction – (reactive)– Overpayments (claims/settlement costs)– Rework /Increased workload/Increased
process times– Increase cost per volume (throughput, avg
cost transaction, volume pricing)
Revenues– Impaired forecasting– Erroneous bill-backs/Invoicing– Delayed or lost collections
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Shared handling of data between entities with different business rules and data definitions creates inconsistency and leads to poor data quality across the supply chain.
Poor data quality negatively impacts the following key management areas:
Improving data quality reduces costs, increases operational efficiency, increases profitability and yields better business information for decision making.
© 2012 GS112
“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 GS113
Data Quality Drivers – “C2B”
• Big data – 2012 year of “Big Data”• Technology is rapidly changing • One provider - Apple (Q1 FY 2012)
• 37.04M iPhones (up 128%)• 15.4M tablets (up 111%)
• Test – (5 min) search for “shopping” apps• 22 general shopping aps• 30 brand specific
© 2012 GS114
Are you standing on a burning platform?
DQ Recommendations
Do or do not… there is no try. ~Yoda
Quality is never an accident. It is always the result of intelligent effort.
John Ruskin
© 2012 GS1
Chrysler Building Taipei 101
DQ is FoundationalBut, How Big a Foundation is Needed?
Not a formula: there is no E=mc2
Best practices are the foundation not the ceiling
Your foundation is unique: Decisions regarding the breadth, depth, and timing of DQ will determine the scope and resource requirements for DQ 16
© 2012 GS1
DQ StrategyEssential Elements
• Data managed at enterprise level
• Data ownership & accountability, clearly defined roles & responsibilities
• Development efforts that affect critical business data championed from the top down and supported with change management processes
• 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. 17
A strategic approach to DQ generates accurate and reliable business information which becomes an enterprise asset.
© 2012 GS118
OK, so what should we do ?
• Get Executive Buy-in• DQ Assessment
• Look at Critical Business Processes– Internal Lens – run the business– External Lens – supporting customer POV
• Identify Key Attributes when missing or incorrect will cause those critical business processes to fail.
• Based on standards
• Fix the critical stuff• Quick wins - Low hanging fruit /biggest bang for your buck, 80/20• In house or external Third party
• Synchronize the data• Information Governance Program (Long Term)
• Policies, procedures, information lifecycle, organization (roles responsibilities)
DQ ToolsHelp and Guidance
Quality is not an act, it is a habit.Aristotle
Quality means doing it right when no one is looking.
Henry Ford
© 2012 GS120
How can GS1 Help?
GS1 Program/Projects Overview Owner Status User Base
Data Quality Framework (DQF)
Comprehensive platform of Industry DQ Guidelines
GS1 GO Available / Implemented
Local MO’sData SourcesData Recipients3rd Parties
GS1 MO Programs
Various local support programs with many different capabilities and features
Local Country MO
Available / In Progress
Local MO’s Data SourcesData Recipients
Data Quality 2020 Expansion of DQF GS1 GO In Progress Local MO’sData SourcesData Recipients3rd Parties
© 2012 GS1
GS1 Data Quality Framework
• A checklist of current best practices and desirable requirements for an optimal management of data quality.
• The Framework contains three main sections:• Requirements for a good Data Quality Management System• A product inspection procedure• A self-assessment procedure for companies
• Developed and endorsed by the Industry
© 2012 GS1
Who can help me? Users - Your local GS1 MO
• Local DQ Programmes serving local needs. There is no interoperability between MO programmes but a common thread is the Data Quality Framework (DQF)
• From the GS1 MO Survey existing or planned DQ Programmes:• 86% have Awareness & Communication activities
• 74% perform Community Management activities
• 70% offer Training & Education activities
• 52% with Consulting activities
• 56% perform Validations & Integrity Checks
• 43% have Product Inspections.
• 30% have Accreditation & Authentication activities
• 39% provide On-boarding tools
• Full survey detail is on the GS1 DQ website
© 2012 GS1
• GS1 MO DQ Programmes Inventory Summary results reflecting current and future activities
Training & Education
Data Quality Awareness &
CommunicationCommunity
Management
Product Inspection
s
Validations & Integrity
ChecksAccreditation & Authentication
On-boarding
Tools ConsultingGS1 MO
Australia
Brazil
Canada
China
Colombia
Croatia
France
Germany
Hong Kong
Hungary
India
Italy
Japan
Mexico
Netherlands
New Zealand
Poland
Russia
South Africa
Spain
Sweden
UK
US
Table key
Active; actions or services of this sort have been rolled-out and/or implemented. Under development; activities of this type are not yet fully operational but they are being developed and are expected to be released in the short term.Tentative; actions may tentatively occur in the short-term future but no work has been started. Plans may be not fully approved or may be still dependant on other factors.None; No plans or deployed activities exist in this area.
Data return by Category and MO
Who can help me? Your local GS1 MO
© 2012 GS124
Who can help me? GS1 GO
Training & Modules on DQ & DQF• Online Self-Paced (updated)• Hands on sessions – as requested by MOs, • As there demand dictates we may schedule sessions in
conjunction with I&S or regional forum events, or special sessions when required.
© 2012 GS1
The Data Quality Framework PACKAGE is publically available
• All you need to use the Framework in one package
• Includes:• The Data Quality Framework v3.0• Implementation Guides (user’s manual!)• Automated scorecard for self-assessment• Automated scorecard for KPIs• Data Quality Introductory Presentation• Read me
http://www.gs1.org/gdsn/dqf/data_quality_framework
© 2012 GS1
Data Quality Website and Library
• Website
• Library
http://www.gs1.org/gdsn/dqf
• Data Quality Framework and support documentation
• Case studies, white papers
• Data Quality Program Internal Implementation Example
• Data Quality Videos
• Links to Related Technical Documents on standards
http://www.gs1.org/gdsn/dqf/library
Liz Crawford
Director, Data Quality & GDSN
Princeton Pike Corporate Center
1009 Lenox Drive, Suite 202
Lawrenceville, NJ 08648
T + 1 609 557 4245
W www.gs1.org
Contact Details