I read an interesting article in Apparel magazine about a Canadian retailer called Mark’s Work Wearhouse that is using weather data to help determine what clothes should be on the shelves (see Rain or Shine, Mark’s Work Wearhouse Has the Right Stuff). The company sells casual and business wear, outdoor apparel, work clothes and safety footwear, in some 300 stores from British Columbia to Nova Scotia.
Mark’s Work Wearhouse was struggling with how to get the right mix of clothes in each store, given the changing weather patterns across the country. That is, how do you avoid having displays of long underwear when there are two weeks of warm weather in Edmonton in October, or having shorts out when there is a cold snap in Vancouver in May?
The retailer turned to a company called Planalytics, a technology provider that helps companies reduce risk and improve profitability by identifying and managing the impact of the weather on their businesses. Apparel cites an example of how the retailer used weather data to make a pricing decision about shorts for a Father’s Day flyer. It was the first week of May, and the retailer had not sold even 10 percent of its shorts. Data from Planalytics had predicted a colder-than-usual spring and a warmer-than-usual summer, especially in Ontario, where sales of shorts typically comprise 50 percent of the total sold.
Mark’s Work Wearhouse decided to take a gamble. Knowing that the next two months were supposed to be hot, it decided not to discount the shorts heavily to move them. Instead, it marked down a select group of shorts just 25 percent, and left the rest at full price (counter to the company’s practice of dropping prices 50 percent for Father’s Day).
The weather predictions were accurate, and because Mark’s had not sold off the shorts at half price, it had more shorts available during the hot months of July and August. Mark’s sold significantly more than it had the previous year, with the average sales price per pair going up by $1. The company made an additional $50,000 due to the pricing strategy based on the weather forecast received from Planalytics. And because of information that predicted a warmer climate in western Canada than in the east, Mark’s moved an additional 8,000 pairs of men’s shorts to stores in Calgary, Vancouver and other western cities, selling them all and brining in an additional $200,000.
What’s interesting about this, to me, is the possibility of combining RFID data with weather data from a company such as Planalytics. For instance, what if you don’t have the shorts in your store when a heat wave is scheduled to hit? Can companies develop systems that incorporate weather data into their replenishment algorithms? Can replenishment systems use real-time RFID data to react more quickly to changes in weather patterns, rerouting shipments from one area to another?
This is a huge issue for all retailers. Home Depot, for example, struggles to have snow shovels in stock right before a big snowstorm in the Northeast.
Weather is a particular problem for the produce industry and supermarket chains. Making sure produce is picked at the right time, moved efficiently through the supply chain, and then marketed and promoted in a timely way is a real challenge. For instance, a warmer than expected spring might cause strawberries to ripen early. If software could predict that, then RFID data could provide information on what’s currently in the supply chain and in the stores. Grocery chains might have to discount the current fruit in the store to move the inventory and make room for the strawberries, so the strawberries can be sold before they go bad.
I have no idea if companies will ever set up and use systems that combine RFID data and weather forecasts, but I do believe that the real competitive advantage is not in using RFID systems, but in how you use RFID systems. The smartest companies will find new ways to combine RFID supply chain and store data with other information to drive business value in ways that others haven’t begun to imagine. And when one retailer is moaning about the rainy weather, another will be smiling, because it knows it has a shipment of boots, raincoats and umbrellas on the way.