Data Quality Score:
60.5 (D+)
Your enterprise data quality has degraded 8.5% this year. Bad data is costing $18.2M in restatements, wasted spend, and compliance risk. The board needs to see the root causes—and your remediation roadmap.
Data Quality Score Matrix
12-month degradation across 4 critical dimensions
Business Impact of Poor Data Quality
How data quality issues are hitting the P&L
| Business Area | Data Quality Issue | Financial Impact | Severity |
|---|---|---|---|
| Revenue Recognition | Incomplete transaction records | $12.3M revenue restatement | Critical |
| Customer Analytics | Duplicate customer records (18%) | $3.8M marketing waste | High |
| Supply Chain | SKU data inconsistencies | $2.1M excess inventory | High |
| Compliance | Missing audit trail data | SEC inquiry pending | Critical |
| Total Estimated Annual Cost | $18.2M | ||
Why Data Quality Keeps Degrading
The systemic issues behind the scores
Data Governance KPIs
Metrics the board needs to see
12-Month Remediation Roadmap
Path to 85+ data quality score
Show the Board Your Data Quality Roadmap
SlideStrike connects to your data systems to visualize quality metrics, business impact, and your remediation timeline—in a format the board can understand.
Data Quality Management FAQ
Common questions about data governance
QHow do you measure data quality across an enterprise?
Data quality is measured across six dimensions: accuracy (is the data correct?), completeness (are required fields populated?), consistency (do values match across systems?), timeliness (is data current?), uniqueness (are there duplicates?), and validity (does data conform to business rules?). SlideStrike aggregates these into a single score while showing dimension-level breakdowns for executive presentations.
QWhat's the typical ROI of a data quality initiative?
Gartner estimates that poor data quality costs organizations an average of $12.9M annually. A well-executed data quality program typically delivers 3-5x ROI within 18 months through reduced rework, improved decision-making, avoided compliance penalties, and recovered revenue from clean customer data.
QHow long does it take to improve data quality scores?
Quick wins in critical data domains can improve scores 5-10 points in 90 days. Sustainable improvement to 85+ scores typically requires 12-18 months of systematic work across data governance, master data management, and automated quality monitoring.
QWho should own data quality in an organization?
The CDO typically owns enterprise data quality strategy, but execution requires distributed accountability. Best practice is a Data Stewardship model where business domain experts own quality within their areas, supported by central Data Governance with standards, tools, and scorecards.
QHow do you present data quality issues to the board?
Translate technical metrics into business impact. Don't say 'We have 18% duplicate records.' Say 'Duplicate customer data is causing $3.8M in wasted marketing spend.' SlideStrike automatically links data quality metrics to P&L impact for board-ready presentations.