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Which recurring data errors justify fixing at the source?
Compare recurring repair work and downstream losses with a prevention investment.
Example scenario
Editable demonstration inputs, not verified industry benchmarks. Enable JavaScript to calculate your own scenario.
- Records processed / year
- 1,000,000
- Records needing repair
- 3 %
- Repair minutes / bad record
- 8
- Loaded repair cost / hour
- $40
- Expected downstream loss / bad record
- $3
- Errors prevented by source fix
- 70 %
- Annualized prevention investment
- $100,000
Annual data-quality net benefit
Example result only, not a forecast or promise.
- Bad records prevented
- 21,000
- Repair hours released
- 2,800
- Expected downstream loss avoided
- $63,000
What to do with this result
Trace the highest-cost error types to the source; avoid adding downstream losses already included in repair time.
Know what is inside the model.
Planning model, not personalized financial advice. Your inputs remain in your browser.
Calculation method
Annual benefit = records × error rate × prevented share × (repair minutes / 60 × loaded cost + expected downstream loss) − prevention investment.
Assumptions and limitations
- Example inputs are editable scenarios, not Aryo results or independently verified industry benchmarks.
- Time value is not guaranteed payroll savings. Include adoption, human review, exceptions, security and change management in implementation decisions.