The big tech companies all deal with this issue as well. One of the big problems when I started at Google in 2009 was that an experiment would show a mild negative effect on click-throughs when what was actually happening is that it was a mild positive effect for users but broke logging on IE6, hence resulting in a 0 CTR for that population. They solved this by building a system that automatically sliced results by population, alerted immediately if any one population was a serious outlier, and displayed sliced results on the experiment dashboard.
The big old-line brick & mortar chains just didn't think it worthwhile to build this sort of granularity into their systems, and are paying the price for it. I suspect that many executives who grew up in the 50s-70s think in terms of "Is this change good or bad?" vs. "Why is this change good or bad?" (Note that brick & mortar retailers who have embraced extensive data operations - notably Walmart, Target, and Safeway - are doing great. It's the Sears & JC Penneys of this world that are failing.)