Some companies fool themselves into believing they know what their customers want by looking at their sales data. After all, it stands to reason that if people buy something, it is a strong signal that they want it. But what if customers are only buying something close to what they want because what they really want is not readily available?
But Toshifumi Suzuki, the former CEO of Seven-Eleven in Japan, who’s widely credited with its rise as the dominant Japanese retailer, understood how sales data can undermine your understanding of the customer. Most retailers use point of sale (POS) data to identify what items are selling well and to automatically re-stock their shelves with those items. Suzuki, however, did the inverse: that is, he identified the items that were not selling and got those items off the shelves to make room for new items that customers wanted to buy.
This inverse thinking resulted from Suzuki’s belief that POS data tells you little about what the customer truly wants. For example, a store might sell out of blue and red umbrellas. Most of his competitors would use this data to re-stock their supply of those two items. Suzuki noted that POS data tells you nothing about why the customer made that purchase. It could be that customers really wanted green umbrellas, but none were available. So they bought the blue and red ones. Or, perhaps the customers only wanted blue umbrellas, but once they were sold out, they were forced to buy the red ones. Or, perhaps the customer didn’t want umbrellas at all; they wanted rain ponchos. But, because the store didn’t carry ponchos, they opted for their second choice, the umbrellas, to solve their problem.
POS data also tells you nothing about how customer tastes or demand may be changing. It looks through the rear-view mirror instead of helping you predict the future. As with the rain poncho example above, POS data only tells you how your existing stock is doing, not the stock you don’t carry that might better solve the customer’s problem.
For these reasons, Seven-Eleven-Japan provides not just POS data to their stores, but also future demand analyses. This demand information is primarily generated by Seven-Eleven-Japan empowering their staff to get to know their customers and to try to predict what the customer would like to buy. In essence, the staff become retail scientists who develop hypotheses about what products will sell in the store. They then stock the shelves with what their customer knowledge tells them. The ringing of the cash register (or lack thereof) tells them if their experiments succeeded or failed. If they failed, then they go back to the customer to learn what they missed.
Critical Path Action Items
How does your company use sales data to predict future sales?
Are your customers getting what they really want from your critical path?