Can You See the Opportunities Staring You in the Face?

I’ve come to believe that less than 1% of the data is truly useful.

Exactly!  Most businesses are very simple if you look for the key metrics.  So many times people want to show their worth by over thinking the problem.  If I can come up with some new innovative way to look at this problem, I'll be a superstar.  But more times than not it isn't a complex problem.  Humans are fairly simple to predict.  Most humans will fall into patterns and want very straightforward things.  New data doesn't need to be introduced until you have gotten everything out of the current data you have.

Big-data initiatives are proliferating, and the information is getting more complex all the time.

There’s a lot of potential benefit for both retailers and customers.

But only if the data is well managed and well understood. Statistics literacy isn’t very high in most businesses. A few educational institutions have realized this and are making a push to turn out business graduates who know their way around a regression analysis. But for the most part, businesspeople aren’t familiar enough with statistics to use them as the basis for good decisions. If you don’t understand the numbers, you can go a long way down a bad road very quickly. That’s why every team charged with making decisions about customers should include a trusted individual who understands statistics. If that understanding isn’t between your own two ears, make sure you bring a person with that skill set onto your team.

Being able to understand what the data is telling you is more important that having a degree in statistics.  Interpreting data is really where the opportunities present themselves, not in figuring out the most optimal model.  I suggest having someone who is proficient in building statistical models and ask a lot of questions from the output.  Start to understand what the answers  of models are telling you and simplify the results into something that can be used in the future.  A model may tell you that people who buy a particular item are likely to be loyal, but is it the item that drives the loyalty or is this just a coincidence?  The better you understand your data, the better decisions you will make and you don't have to be a data scientist to do that.