Data is an increasingly important part of organizations today. It can be leveraged for traditional operations and efficiency, but now is also being used to gain a better understanding of the consumer, prompt personalized marketing messages and determine a host of new product innovations.
The increasing use of data is putting a greater spotlight on information and how it is used. But many companies have issues with their data. In fact, a recent Experian Data Quality study found that U.S. companies believe on average a quarter of the information in their databases is inaccurate.
The high degree of inaccurate information is driving action. Eighty-nine percent of companies are investing in data quality solutions as they look to do more with data. And they aren’t spending an insignificant amount of budget on these tools either, with the bulk of organizations spending over $500K annually on data quality technology.
Companies are investing in a wide variety of solutions and implementation types, including on-premise and SaaS. There is certainly not a one-size-fits-all data quality solution in the market. Some of the most popular types of tools to implement include:
Most companies—79 percent—believe they are seeing a return from these types of tools. In fact, only five percent of companies flat out say they do not see a return at all.
However, there is a difference between perceived value and calculated value. The perceived value alludes to a positive perception of data quality tools, but that can fade as staffing changes or organizations restructure. The only way to truly demonstrate return of investment over time is by calculating it with hard figures.
Today, 59 percent of companies annually calculate the return on investment of data quality solutions. But that still leaves a large number of companies who only perceive a return on investment, rather than know it has a hard fact.
Join us next week for a webinar on demonstrating ROI to hear more about this research and tips for generating ROI metrics. Register for the webinar at https://www.brighttalk.com/webcast/9847/133027.
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