Data Quality issues are NOT always a data problem

What appears as a #data problem is NOT always a data problem. It is usually a human error, training issue, or a process mistake.

I moved to my current residence a little over 2 years now. Given that we are a distributed team at #khyanafi, I still use its primary address, where it was initially set up in Dallas.

The mails get forwarded to me. Except, on the last two occasions it went to my old address.

The first thing I did was to go to my office provider’s site and checked my profile.

The address entries are accurate, just as it has been the last 2 years.

Then why did the mail go to the old address?

I visited individual account settings as we have offices set up in more than one state. No issues anywhere.

I called the provider this morning to find out that the labels on file with the new address had run out and that they had to be reprinted. I pressed for more info as this didn’t explain why my mails were sent to the old address.

Someone forgot to remove the old address labels when they put in the set with new labels. And when new labels ran out, someone used the old labels.

It’s easy to get into a rabbit hole chasing #dataquality issues. Simultaneously research multiple angles during the analysis phase to shorten the timeframe of identifying the root cause.