Bad Data Is Sapping Your Team’s Productivity

Data science was supposed to create a new productivity boom. But, for many companies, that boom never arrived. What’s gone wrong? While companies have invested in data tools, much of the data that’s fed into these systems is low quality — with mislabeled, missing, or incorrect information, which in turn creates more work, and more drag in the system. To address this, companies should: 1) rally employees to the cause and drive home why this is important, 2) measure data quality across the full range of departments, functions, and tasks, 3) relentlessly attack the sources of the data quality tax.