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Assessing the costs of poor data quality

Data is a great resource for companies looking to garner valuable insights about their processes, products and efficiencies, but it can also become a huge problem if firms don't maintain strong data quality. It may seem difficult to quantify the impact of dirty data quality, but the results are quite tangible, according to Ina Felsheim who recently wrote a post for The Decision Factor. 

In fact, research firm Gartner estimates that data quality impacts productivity by approximately 20 percent. If companies have poor information in their databases, they may see increases in returned shipments, miss billing deadlines and see disappointing metrics for email marketing efforts, Felsheim adds. On top of these consequences, they have to assign additional resources to fix incorrect entries. 

On top of heightened business costs, there are other repercussions that impact operations, according to Business Solutions. Manufacturing firm 3M is constantly generating data to account for its 80,000 employees around the world who help produce items that span multiple industries, from healthcare to transportation. If the global company lets its data quality get off track, or entries in its address management system become outdated, processes may suffer greatly during a circumstance that requires the use of action-critical information.