Why is Data Quality Important?The DQ Business Case & Interdependence

“It is not necessary to change. Survival is not mandatory.”

W. Edwards Deming

© 2012 GS12

The Business Case

“A business case captures the justification for initiating a project or task by estimating the effects a particular decision will have on profitability.”

© 2012 GS13

Why is Data Quality Important?Impacts

• Operational Impact• Internal business systems and processes• Compliance with regulations

– Sarbanes-Oxley, Basel I, Basel II, HIPAA, EU 1169/2011

• External Impact• Outward facing processes that influence opinions and buying

behavior – remember “perception is reality”

© 2012 GS1

£€¥$Why is Data Quality Important?Operational Impacts

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– Low level of confidence in analysis and

reporting

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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:

© 2012 GS15

Why is Data Quality Important?External Impact

• Customer Satisfaction• Agility in responding to consumer demand & market changes

– Early identification of challenges– Opportunities for innovative solutions

• Available when, where, and how the customer wants it• Trading partner demands

• Brand Image• One common global representation

• Reputation• Trusted source of data• Sustaining a competitive advantage

Improving data quality increases the strength and overall viability of the organization

© 2012 GS1

Why is Data Quality Important?For Manufacturers

Effectively managing product information throughout the supply chain helps manufacturers increase revenue and decrease costs by:

• Accelerate new product introductions• Increase market share for early arrival of new items• Reduce item maintenance efforts• Reduce costs through consistent packaging and fewer retailer-

specific processes• Decrease error rates• Increase productivity• Reduce rework administration• Reduce out-of-stocks• Minimize invoice deductions

© 2012 GS1

£€¥$Why is Data Quality Important?For Retailers & Distributors

Category Management & Promotion– Less need for local agents or

intermediation– Ability to expand supplier base– Improved visibility for stock-level planning– Simplified/enhanced category reporting– Quicker and easier new item introductions– Shorter lead time on product promotions– Price changes or corrections easier to

manage, less need for costly human intervention

Administrative Data Handling– Less in-store labour required: cost savings– Less administrative personnel needed:

cost savings – Less time spent maintaining catalogues– Less need for duplicate catalogues – No need for cross-reference tables– Fewer invoice disputes– Fewer order defects– Better fill rates

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Effectively managing product information throughout the supply chain helps Retailers increase revenue and decrease costs by

© 2012 GS1

£€¥$Why is Data Quality Important?For Retailers & Distributors (cont’d)

Smoother logistics– Savings from more accurate weights &

measures– Error-free shipment receiving– Fewer return shipments– Fewer backorders– Less excess or "safety" stock– Optimized location despatch– Reduction in shrink

Better Bottom Line– Increased sales

More Satisfied Customers– Better on-shelf availability– Quicker checkout times– More promotions

Initiatives– Traceability– Supply Chain Efficiency

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© 2012 GS19

Why is Data Quality Important?In a Nutshell…

• Why improve DQ? • Reduces costs• Increases profitability• Increases operational efficiency, • Preserve your reputation• Generate better business

information to enable more informed decision making.

• Achieve and sustain a competitive advantage

© 2012 GS110

Data Quality is Interdependent

© 2012 GS111

Why is Data Quality Important?Interdependence

© 2012 GS112

Information Supply Chain

Coming together is a beginning. Keeping together is progress. Working together is success.

~Henry Ford

"In God we trust, all others bring data“ Unknown

© 2012 GS1

Information Supply Chain – B2B2C

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Data Providers

Data RecipientsDemandSupply

Aggregators End UsersBusiness UsersSynch

DQ

© 2012 GS1

Information Supply Chain – B2B2CData Sources

1. Supply Chain • Supply chain is not linear • Multiple operations, systems, and applications• Different data a different plant – multiple versions• Strategic Sourcing – increased complexity• Transactional and Logistical analysis/information

is dependent upon Product data

2. Crowd-sourced and third party data - not linked to data owner

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Data Providers Supply

DQ

© 2012 GS1

Information Supply Chain – B2B2CData Sources

3. Marketing• Product databases which are incomplete, include

non-standard data, or are missing attributes• Managed on spreadsheets.• Multiple versions of the same product data • Combination of manual and automated processes

to re-key or update data • Multiple sources of customer or prospect data

(avg 3)• “Work arounds” are the standard solution rather

than address the root cause

Requires high level of visibility and coordination

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Data Providers Supply

DQ

© 2012 GS1

Information Supply Chain – B2B2CData Synch

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Data Providers Supply

DQ

• 30% SKUs updated each year (avg)• Not including seasonality, promotions, packaging

changes • Manual processes to get data into the system

• Labor intensive• Error prone

• Slow - likely out of date by the time it’s entered – needs monitoring

• Trading Partner constraints – different levels of sophistication

• Options• File Transfer (not synchronised)• One-to-one trading partner interface• One network interface

© 2012 GS1

Information Supply Chain – B2B2CAggregators

Compile information from multiple sources• iTrade – Food industry• Nutrifacts – Nutrition

information• GHX – Healthcare • Edgenet – Hardlines• GS1 MO – multi-sector

Challenges• Receive upstream from

multiple platforms• Multiple locations for same

info• Manage catalogue

updates and maintenance• Deliver downstream in

multiple formats

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Data Providers

Data RecipientsDemandSupply

© 2012 GS1

Information Supply Chain – B2B2CData Recipients

Business Users / Retailers• Unit of Measure – confusion or misuse • Weights (net, gross, tare)

• One SKU with multiple weight depending on case pack - “rounding” impact s freight charges

• Truck Cube – orders don’t fill or are too large for truck,

• Packaging Dimensions – fit on shelf, Plan-O-Gram

• Promotion & Rebates – Time sensitive, unit specific

• Manual data management efforts• Store operations - Availability and Out-

of-stock

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Data RecipientsDemand

© 2012 GS1

Information Supply Chain – B2B2CData Recipients

End Users / customers use data to make an informed purchasing decision. Data must be:• Available

• When – Considering or Making a purchasing decision. If data is missing, the product may be invisible and the sale is lost.

• Where & How – Received in the customer’s preferred medium. Web, mobile, kiosk, smart shelves, tablet, and next new technology…

• Fresh• Data is perishable, it must be current and up-to-date

• Accurate & Reliable• Is it from a trustworthy source?

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Data RecipientsDemand

© 2012 GS1

Information Supply Chain – B2B2C

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Data Providers

Data RecipientsDemandSupply

Aggregators End UsersBusiness UsersSynch

DQ

© 2012 GS1

Why is Data Quality Important?Information Supply Chain

Without reliable data in the Information Supply Chain, trading partners are forced to set up additional means to control data quality, resulting in a longer, more complicated ‘road’ for the information.

© 2012 GS1

Why is Data Quality Important?Summary - Elevator Pitch

Improving Data Quality Enables:• Common understanding of business policies and processes across

enterprise and with business partners/channels• Singular definition and location of master data and related policies to

enable transparency and auditabilty essential to regulatory compliance• Cross-organisation implementation of shared application solutions• Uniform communications with data owners and recipients through

multiple channels based on the veracity and accuracy of key master data• Continuous data quality improvement as data quality processes are

embedded throughout the Information Supply Chain

Failing to address the quality of data will cost organisations money and may damage your reputation

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