Total Information Risk Management

Foreword by Thomas C. Redman

People in the data quality profession should feel rightly proud in having created a body of thinking, approaches, methods, and tools that work! When applied with reasonable diligence, departments and companies that first direct their data quality efforts on preventing errors at the source, focus on the most important needs of the most important customers, identify and eliminate the root causes of error, and build in controls to keep root causes from coming back nearly always succeed. They make huge improvements, sometimes an order of magnitude or more. And they reap enormous benefits!

At the same time, people in the data quality profession have to ask themselves the hard question: “So why doesn’t everyone pick ...