Score decompositions can be built along many dimensions :
- data elements
- data quality rules
- subject populations
- record subsets.
Score Decompositions (report, answers)
Decomposition may indicate that :
- in 80% of cases it is caused by the problem with the employee compensation data; in 15% of cases the reason is missing or incorrect employment history; and in 5% of cases the culprit is invalid date of birth.
- over 70% of errors are for employees from a specific subsidiary. This may suggest a need to improve data collection procedures in that subsidiary.
- 6.3% of all calculations are incorrect because of data quality problems, such a score is extremely valuable
Data quality scorecard is a valuable analytical tool that allows to :
- measure the cost of bad data for the business
- estimate ROI of data quality improvement initiatives
- allow us to make better decisions and take actions