SHOPKO TESTS AUTOMATED MARKDOWNS
Byline: Brad Barth
NEW YORK — Hoping to mitigate the pain of markdowns, ShopKo, based in Green Bay, Wisc., is testing a tool that optimizes an item’s pricing schedule so that the product sells at maximum profit before reaching the end of its life cycle.
The ultimate goal, according to senior vice president and chief information officer Paul Burrows, is not markdown optimization. It’s markdown “sub-optimization.” That little prefix is the difference between developing one markdown scenario for an entire chain of stores and setting markdowns by individual location.
The consumer demand for goods is never uniform across a large retail operation, especially one like ShopKo, which has about 160 locations. “Each store has its own idiosyncrasies, customers, sell-through and on-hand” inventory levels, Burrows explained.
But adjusting markdowns on an individual store basis is a daunting concept, without the help of technology. “At any given time, there’s a significant number of sku’s [stockkeeping units] out there on clearance, and to try to manage the markdown of those items [manually]+on a store-by-store basis is virtually impossible, just by sheer numbers,” said Burrows.
“You’d have to have a battalion of people to do it,” agreed Mike Martin, director of business alignment and planning.
So rather than rounding up a retail army, ShopKo is beginning to pilot a markdown optimization tool from Spotlight Solutions, Cincinnati, across three product categories [home, apparel and hardware] comprising 350 sku’s.
The tests, which will continue into next year, will not sub-optimize on a store-by-store basis, but ShopKo will set markdowns differently in seven separate regions of stores. Sub-optimization would begin next year, assuming the tests are successful.
The first set of markdowns is scheduled for Nov. 1, and Burrows is optimistic that results will include higher sales margins and improved productivity.
“The bottom-line objective is to maximize our gross margins on items that we have to clear,” he said. At the same time, the retailer expects to see labor savings.
Burrows believes the solution will improve worker productivity by eliminating manual price changes and reducing the number of times new price labels are applied.
Such time-consuming labor is unfortunate for many retailers because marking down products is a guessing game of sorts. According to Burrows, retailers may discount a product up to four or five times as they try to hone in on the right markdown price for a particular sku.
The solution will automate the price markdown process so that manual entry is not needed to update the price management system, from Retek, Minneapolis.
As the tests continue, ShopKo will examine if clearance sell-through remains in line with the solution’s predicted demand curve. “We don’t want to clear it all in the first day, but we don’t want to clear it all on the ‘out’ date at the last minute,” said Burrows.
The optimization process is hosted by Spotlight. ShopKo feeds its sku’s store-by-store historical sales data — two to three years’ worth — to the vendor through a secure Internet connection, and the software then uses this information to calculate the probable demand curve of the product at each location. Noting the product’s end date, the solution will then develop optimal pricing schemes for the products at each store.
The tool will continue to moderate its original markdown plans as current sales figures feed into the system.
Although ShopKo plans to rely on the tool’s forecasting abilities, it will set up a few parameters to guide the solution. For example, ShopKo will establish certain dates before which no store can mark down a certain sku.
Beyond that, the tool eliminates human subjectivity. “It takes that human factor out of it a bit,” said Burrows. “We have to make sure that once the tool is in place and it works, the merchants actually accept what the optimizer says and+not override it because they think they know better.”