Two fifths of companies surveyed recently by Experian Data Quality spend more than $1 million annually on data quality technology, and another 22% spends at least $500,000, but a significant number of them do not calculate the return on their investment from data quality tools.
The September poll of 200 cross-functional executives in small to large enterprises conducted by GMI found that 59% did annual calculations of ROI on data quality inspections. But another 20% said they merely perceived a return on investment and 10% said they didn’t consider ROI. Seven percent said they were unaware of any ROI measurements performed on data quality by their companies.
Data cleansing, particularly popular among retailers and marketers in general, is employed by 52% of companies, though data quality monitoring and audit tools are used the most. Some 62% of those surveyed said their companies deployed such controls to ensure that data continues to conform to organizational business rules.
Experian Data Quality suggests three steps for measuring data ROI:
- Start by monitoring individual products, especially ones just out of the box. Metrics to consider include number of duplicate records, amount of returned mail, and number of personalized offers accepted.
- Test results within a defined time period, then do it again for a similar period and consider variations across several performance points.
- Share metrics with business units. Negative results can spur change, positive ones can inspire continued vigilance.