Global competition, the blurring of lines among sales channels and fast-fashion pressures combine to speed the decision-making process for retailers.
This story first appeared in the July 11, 2007 issue of WWD. Subscribe Today.
And predictive analytics are helping companies get smarter about merchandise decisions, from early planning right through to pricing and size, said Diana McHenry, global retail practice director for SAS, a software vendor in Cary, N.C. “There is not always enough lead time to make these decisions as in the past,” she added.
As more companies begin to share financial gains credited to software based on analytics and predictive modeling, technology seems less like “rocket science,” she said.
McHenry pointed to Kohl’s department stores, which expects its use of markdown optimization software to increase gross margins by 30 to 40 basis points. Kohl’s is using SAS’s software to guide the timing and depth of markdowns on a regional level. This fall, the $15.5 billion Menomonee Falls, Wis., retailer will expand the practice to the store level, she said.
“Here is an organization that is a terrific merchant, terrific at its promotional strategy and leveraging markdown optimization on top of that to get even better results,” she said. Kohl’s is also using size optimization software to determine the correct mix of sizes based on profiles of a store’s customers.
One unnamed client of SAS, a $1 billion retailer, saw stockouts fall 1 percent and gross margin rise 30 basis points as a result of using size optimization software, she added. That boost in profits translated to $7 million for the bottom line.
Another unnamed customer, a $2 billion retailer using price optimization software, saw gross margin rise 3.1 percentage points, a gain of $109 million, McHenry said.
A third unnamed client, a $5 billion vertically integrated retailer, followed an approach similar to the one outlined by Famous Footwear’s John Dembinski. The company adopted integrated merchandise planning that incorporates location data, store clustering and various factors influencing demand. Smarter planning, assortment and allocation led to a 17 percent inventory reduction that translated to a $106 million annual savings for that company.
“That was a terrific reinvestment opportunity because they were able to use that [capital] the following year to invest in new stores,” she said.