Linens 'n Things Finds A Home With 4R Systems After Experiencing Great Results With Live Pilot Program

Linens 'n Things, Inc. (LnT) is one of the nation's largest and fastest-growing specialty retailers of home textiles, housewares and decorative home accessories. With more than 380 superstores nationwide and 27,000 SKUs, LnT is at any given time required to make millions of business decisions about what, where, when and how much to stock on their shelves. These decisions pose an ongoing challenge that clearly requires much more than a simple Excel spreadsheet.

Supply Chain Challenges

4R Systems was introduced to LnT by American Pacific Enterprises, a leading supplier of fashion bedding and accessories and a 4R customer. American Pacific had been achieving impressive results with 4R and believed LnT could also benefit from 4R's Supply Planning Product Suite.

Matching supply with demand is difficult for LnT because demand is highly seasonal and variable, and because the company must set inventory levels weekly for over 4 million store/SKU combinations. In this complex environment, 4R was challenged by LnT to prove that it could help the retailer improve all aspects of the buying process, beginning with determining the best stores in which to test a new product, followed by optimizing the initial buy and store allocation, and finally computing optimal store/SKU order points each week once a product was on replenishment. The goal at each stage of this process was to do more with less - to increase in-stock and sales while reducing the cost of inventory carrying and inventory obsolescence at the end of a product's life. .

The Proof is in the Pilot

4R was able to demonstrate through a series of pilots in which it applied the 4R Supply Planning Product Suite to historical data that it could improve LnT's buying decisions and optimize their stock levels. Given this success, LnT opted to take the next step in a live pilot, where 4R would feed LnT optimal order points for a given set of SKUs over a reasonable amount of time.

4R worked closely with LnT and American Pacific to choose the SKUs and pilot metrics that would serve as the benchmarks of success or failure. Two sets of SKUs were identified -- one set would be completely planned by 4R (the pilot SKUs), and the other that would continue to be managed by LnT (the peer SKUs). The two sets had similar product and selling characteristics.

At the beginning of the test, the pilot group started with store on hand inventory equal to 15 weeks of supply and the peer group with 30 weeks of supply. Each week, 4R received LnT point of sale and inventory data, processed it through the 4R Supply Planning software, and then supplied LnT with optimized order points via a flat-file extract that was then uploaded into their JDA MMS system for transaction execution.

Various key performance metrics were recorded for both the pilot and peer SKUs, including weeks of supply on hand at stores, inventory levels and the percentage of sales lost due to stock outs. These metrics were tracked over a four-month period to ensure that results could be attributed to 4R's order points rather than transitory market conditions.

High Impact Results

The final results were impressive. 4R demonstrated that its sophisticated forecasting and replenishment algorithms were significantly better - more accurate and cost-effective - than the traditional methods that LnT used to plan and optimize stock levels.

Despite having less merchandise than the peer SKUs, 4R's pilot group demonstrated increased sales, reduced lost sales, and a reduction in inventory. The increase in sales and decrease in inventory resulted in an increase to gross margin that would flow directly to the bottom line. No extra people to hire, no business process reengineering -- just more productive inventory resulting in higher operating profits.

The company also evaluated 4R on a core-basic category of SKUs that had little fashion content - almost opposite to the SKUs from the live pilot. Results from this project indicated the retailer would benefit from increasing inventory levels to gain increased sales - and that the cost of the extra inventory would be more than offset by the additional gross margin earned on increased sales. LnT found that depending on the product type, its movement and demand patterns, 4R could be used to optimize inventory levels rather than simply recommending inventory reductions across the board.

This convinced the LnT team of 4R's value. 4R was able to determine the right mix and amount of inventory for the specified product category in each of the retailer's stores. 4R's software is now being rolled out to forecast and plan inventory stock levels for all replenishment SKUs at 380 LnT stores across the U.S. LnT will be using 4R's unique algorithms to plan new product introductions and rollouts as it pursues a competitive growth strategy focused on an aggressive expansion into new markets.