Can You See the Opportunities Staring You in the Face?

Companies suffer from inattention blindness too. And in a business context, the weird thing that gets overlooked can turn out to be a crucial differentiating factor. If one company doesn’t notice it, another will—to great advantage says Chris Briggs in HBR.

A perfect example is the high-end retail company that, like its competitors, needed to close certain stores because more and more customers were buying online or via catalog. But unlike its competitors, this company sensed that the closure of a store might have harmful network effects.

In a study of customer data on purchases made by people who lived within a short driving distance of its stores, the company could see that customers were visiting stores to look at the merchandise, then going home to compare other options and make their purchases. Closing a store would deprive customers of their showroom. The hunch that this would hurt sales was corroborated by a dip in online and catalog sales in areas around stores that had previously closed.

Not only did the company end up closing fewer stores than it originally thought necessary, it now had a new method to evaluate the overall positive impacts that new or relocated stores would have on the retailer’s bottom line—across all sales channels.

The importance of stores’ network effects is just the kind of thing companies often miss when they’re focusing intently on the mass of conventional data they collect on customer behavior. In fact, I’ve come to believe that less than 1% of the data is truly useful.

The challenge, of course, is figuring out which 1% really matters, and with the recent explosion of data types and sources, making that kind of distinction is getting harder and harder. Big-data initiatives are proliferating, and the information is getting more complex all the time. In the next couple of years—not decades, but years—companies will have access to data not only from customers’ mobile devices, but from wearable tech and automobiles, for example. Soon, retailers will have all kinds of information about customers who are walking through stores and will be able to send them targeted messages. 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.

But let’s say you’re a small organization—a group of restaurants, say, or a retail chain with just a few locations. You don’t have anyone on staff with a statistics background, and you can’t afford to hire such a person. There’s one thing you can do to ensure that you make informed decisions and don’t let the numbers lead you astray: Get a solid understanding of who your core customers are, what their value is to the company, and what your objectives are. Learn which customers are profitable and which ones aren’t, and decide what you want to do to increase the profitability and number of good customers. Use that information as the center point of all your decisions.

Will that cure your inattention blindness? Maybe not entirely, but if you can get a good understanding of what distinguishes a good customer from a bad one, and a sense of what makes your good customers tick, you’ll immediately cut half the noise out there. That will make it a lot easier to see the opportunities that are staring you in the face.