Bad Data Costs Businesses Big Money

Oct 05, 2010

According to Ovum, data of poor quality is now costing U.S. businesses an estimated $700 billion a year due to inefficiency and lost customers. Bad data is generally defined as data that includes outdated values, missing information, and inconsistent formats. An organization with pervasive bad data can lose money on poor targeting of resources and flawed pricing strategies. Ovum recommends obtaining a data quality tool to help reduce effect on the bottom line, though also warns businesses to weigh the benefits of the various tools on the market.