Dear Average Retailer,
It’s tough out there. Here’s one more thing you’re up against:
Call it the Moneyball-ization of retail. Increasingly, the biggest retailers are looking beyond traditional merchandising, typically based on a mix of intuition and gut-feel, and are instead using data and analytics to drive these decisions. A recent Wall Street Journal article detailed how companies like Kohl’s, Target and Walmart are forgoing the crucial Chief Merchant position altogether in favor of folding those responsibilities into the same teams responsible for other data-driven decision making.
It was anticipated that J.C. Penney might make a similar move, but in the end they refilled the spot after a recent retirement. Perhaps going the Moneyball route was too much for the moment, as the company continues to plot its path to firmer ground. Still, these types of issues are clearly top of mind. “We have great data; we just aren’t using it,” Penney’s CEO was quoted recently as saying.
He’s not alone. Not only are retailers not effectively leveraging their data, they’re hoarding it to themselves when sharing it with consumers, this WSJ article notes, would enable them to attract new customers and offer existing ones greater value.
Of course, that would require another set of technical skills and business processes.
The average retailer has to be asking itself, how do my analytics chops compare to what these companies are bringing to bear? If I try to compete with data-driven insights using a “this is the way we’ve always done it” approach to merchandising, what are the chances of success?
But wait, there’s more than just the big retailers to worry about. Increasingly, start-up retailers are placing big bets on data and analytics. For example, at the recent Shop.org Digital Summit, I heard Julie Bornstein from four-year old Stitch Fix report that they have fifty – fifty! – data scientists on staff, including one with the title Chief Algorithm Officer (first time I’ve heard that one).
The scariest part: Julie said in her experience the average retailer today doesn’t even have one data scientist. While an unsubstantiated claim, from what I’ve seen – to quote Seinfeld – “sounds about right.”
So, is it time to post a job description for a data scientist? Wish it were that easy. They’re in extraordinarily high demand, with salaries sky-rocketing. And working at a mid-sized retailer is probably not at the top of the list for the best and brightest – especially when landing the right gig at a Silicon Valley start-up could yield a quick jackpot.
What’s an average retailer to do?
One hot tip: look to leverage analytics built into your core tools – such as your commerce platform. Just like cars will soon be driving themselves, commerce platforms will increasingly use embedded analytics to help retailers make smarter decisions at every turn.
Demandware is hard at work on this. Check out this video for what we’ve been up to lately.
This is not to say every retailer shouldn’t be working very hard to get smarter about data and analytics. But the good news it’s not all on you.
Good luck out there.