Most managers know, anecdotally at least, that poor quality data is troublesome. Bad data wastes time, increases costs, weakens decision making, angers customers, and makes it more difficult to execute any sort of data strategy. Indeed, data has a credibility problem.
Only 3% of Companies’ Data Meets Basic Quality Standards
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Few managers understand the extent of their data quality issues. A simple exercise can be illuminating: assemble 100 data records completed by your department and work through each record, marking obvious errors. They then count up the total of error-free records. This number represents the percent of data created correctly — a Data Quality (DQ) Score. When 75 executives completed this exercise, they were horrified to realize how bad their data was. On average, 47% of newly-created data records had at least one critical error, and only 3% of the DQ scores in our study can be rated “acceptable” using the loosest-possible standard. These results should scare all managers everywhere. Unless you have strong evidence to the contrary, managers must conclude that bad data is adversely affecting their work.
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