Bad Data Is Costing You Millions, Here's How to Fix It
Poor data quality costs organizations an average of $12.8 million per year according to Gartner, and with data volumes growing exponentially, that figure will only climb. This definitive guide cuts through the myths, maps the real dimensions of data quality, and delivers a practical six-step framework so every team in your organization can stop firefighting bad data and start competing on trusted insights.
Published
2025-10-24
17 • Pages
Qlik and IPC Global
Cross-Industry
AUTHOR
IPC Global
PUBLISHED
2025
AUDIENCE
CDOs, Data & Analytics Leaders
INDUSTRY
Cross-Industry / Enterprise
TOPIC
Enterprise Data Quality
White Paper Snapshot
Everything you need to know in under 30 seconds
Key Topics
Five Myths Keeping Your Data Strategy Stuck
Data quality is not a one-time project, it demands always-on monitoring, continuous validation, and iterative improvement as business processes, data sources, and regulations constantly evolve.
Treating data quality as IT's problem alone is a guaranteed path to failure; modern organizations succeed only when business users, data stewards, and technology teams share accountability across the entire data lifecycle.
Fixing bad data at the end of the information chain costs 10x more than addressing it at the source, yet most organizations still wait until downstream failures make the problem impossible to ignore.
Today's data quality tools are no longer complex IT-only systems; self-service platforms now allow any member of the organization to identify and resolve bad data without specialized technical skills.
Data quality cannot be solved once and forgotten, changes in business processes, regulatory requirements, or data sources will continuously introduce new quality issues if proactive observability is not in place.
Highlights
Real-World Proof: Data Quality Delivers Measurable Returns
A global energy company reduced its data rejection rate significantly after implementing Qlik Talend, critical for a pipeline processing over 90,000 new opportunities every single week across 70 country entities.
A leading pharmaceutical company leveraged clean, unified data to accelerate drug development and distribution across nearly 100,000 employees in 90+ countries, with Qlik Talend described as a "key enabler" for delivering medicines to patients faster.
Travelodge used data quality capabilities to power personalized customer offers that generated millions of pounds in additional revenue per year, all driven by a 180-gigabyte operational data store processed through 2,000 daily executions.
Canada's largest mutual insurer, Beneva, cut project delivery cycles from 9–12 months down to three-week agile sprints after standardizing and cleansing its data with Qlik Talend's matching and stewardship capabilities.
Across every industry, insurance, energy, pharma, hospitality, the pattern is consistent: organizations that invest in data quality gain a unified customer view, lower operational costs, and faster, more confident decision-making.
Results & Impact
$12.8M Saved Annually
Gartner estimates poor data quality costs the average organization $12.8 million per year, a figure that grows exponentially as data volumes increase. Organizations that prioritize data quality directly protect this budget and redirect those savings toward growth.
10x Cheaper at the Source
Fixing data quality issues at the beginning of the data chain costs ten times less than addressing them downstream, making proactive data governance one of the highest-return investments an organization can make in its data strategy.