3 stand out points from the HBR case study on Data Quality issues at AT&T

As I read the recent HBR article “Even the Tiniest Error Can Cost a Company Millions“, three key points stood out:

  1. ┬áThe perceived problem isn’t always the real issue. It can be a manifestation of a different problem, related to a process or a system.
  2. As you dig deeper into data quality issues, it can reveal some surprising insights into the everyday operation of a business – and more opportunities to improve how things are done.
  3.  The approach to investigating and resolving data quality issues will vary depending on circumstances. For example, the volume of data, turnaround time for transactions, the type and nature of information contained in the data, and available resources all play a part in how you approach the problem.

As with most improvement initiatives, acknowledging the existence of a problem is always the best starting point. You can only improve from there.