DSW automates and optimizes product distribution to get stores the right inventory
Fashion moves fast. And with SAS® Size Optimization, shoe retailer DSW is staying ahead of the curve.
DSW is a leading footwear and accessories retailer. It offers a wide selection of brand names and designer dress, casual and athletic footwear and accessories. The retailer operates more than 500 stores in 42 states, as well as a robust online shop and mobile site.
Shoe merchandising is evolving in several ways, explains Linda Canada, Vice President of Planning and Allocation. Customers are more demanding, fashion cycles are accelerating, and acquiring stock from overseas suppliers provides new challenges. And unlike clothes, shoes come in a wide variety of sizes and fit tends to be quite individual.
“With clothing, if a store doesn’t have your size you might buy a size up or a size down, but that doesn’t happen with shoes,” Canada says.
This is where SAS makes a big difference … we can now develop accurate size curves. Mike Ezell Allocation Manager DSW
Limited space for inventory
One of DSW’s challenges was to customize pack sizes by store to meet local demand for certain styles and sizes. Historically, shoes are shipped in standard 12 packs. It doesn’t matter if a store needs to replenish a single size – they’ll get a pack that includes every size.
This is difficult, explains Canada, because store size limits the amount of extra merchandise that can be held. “Our products come in hard boxes, so you can’t just stuff more under the table. And our back rooms are generally small. There’s only a certain amount of product that will fit in our stores, so having the right mix is critical.”
In addition, DSW needed a solution that could integrate with its supply chain systems to ensure suppliers had enough lead time to meet customized inventory requests.
DSW – Facts & Figures
shoe retailer in America
Getting the right product mix
Before SAS, store managers often knew what sizes would sell out quickly and which would land on the clearance rack. But they could only request extra packs of a certain style or size in an ad hoc manner. There was no optimized, sustainable or automated system in place.
With SAS Size Optimization, DSW now uses historical sales data to provide a more customized and automated approach to stocking stores and filling pack sizes.
“Other solutions tended to throw out a lot of data,” says Allocation Manager Mike Ezell. “This is where SAS makes a big difference. We can now develop accurate size curves.”
SAS has enabled DSW to develop a “size by store” model, and optimize inventory through a combination of packs and size unit replenishment. The SAS analytics engine not only accurately predicts the needs of individual stores, but it correctly identifies stores with atypical size profiles. The result of automating the inventory selection process has been fewer markdowns and stockouts because stores receive the right product mix.
DSW is particularly happy with how SAS helps the company stock seasonal items. The shelf life of a sandal is much shorter than a dress shoe, for example, so DSW can now calculate forward sales on seasonal items to order the right quantity.
“It was a big win for us to build forward sales into our inventory plan,” Canada says.
Buyers and suppliers on board
The system has been so effective that DSW has convinced buyers to reduce the amount of inventory they purchase. In the past, buyers didn’t want to be caught without enough of a hot seasonal style. Now they order fewer packs with confidence they’ve stocked the right products.
“We’ve helped them understand they can buy less while selling the same amount and making more money,” says Phil Brown, Senior Director of Allocation and Replenishment.
Vendors have been receptive as well, despite the need to pack shoes in different configurations. Because the solution is integrated with DSW’s supply chain, vendors are alerted well in advance to the need for different pack sizes.
“They see the benefit,” Ezell says, “They don’t want to see their products marked down either.”
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