Over the weekend, in preparation for watching the Boston Red Sox, I bought some beer and pizza. Later that night, after a thrilling victory that sent the Red Sox to the 2013 World Series, I was cleaning up the kitchen and was about to throw out the receipt when I couldn’t help but notice two data quality issues.
First, although I had purchased Samuel Adams Octoberfest, the receipt indicated I had bought Spring Ale, which, although it’s still available in some places and it’s still good beer, it’s three seasonal beers (Summer Ale, Winter Lager, Octoberfest) old. This data quality issue impacts the store’s inventory and procurement systems (e.g., maybe the store orders more Spring Ale next year because people were apparently still buying it in October this year).
The second, and far more personal, data quality issue was that the age verification portion of my receipt indicated I was born on or before November 22, 1922, making me at least 91 years old! While I am of the age (42) typical of a midlife crisis, I wasn’t driving a new red sports car, just wearing my old Red Sox sports jersey and hat. As for the store, this data quality issue could be viewed as a regulatory compliance failure since it seems like their systems are set up by default to allow the sale of alcohol without proper age verification. Additionally, this data quality issue might make it seem like their only alcohol-purchasing customers are very senior citizens.
What examples (good or poor) of data quality have you encountered? Please share them by posting a comment below.
This blog was originally posted at OCDQblog.com. Published with permission.