Magazine Article | July 18, 2007

Strategically Allocate Your Merchandise

Source: Innovative Retail Technologies

Big Lots uses allocation software to relate inventory to store volume, improve merchandise distribution to its 1,350 stores, and reduce overall inventory.

Integrated Solutions For Retailers, August 2007

Big Lots is one of many retailers that  have garnered sizeable benefits from allocation software, which uses algorithms to improve supply chain effectiveness.

The company used an aged, proprietary legacy inventory allocation system that lacked functionality to effectively distribute products to its 1,350 stores. The software met Big Lots' needs when it distributed a limited number of items to a fewer number of stores; however, the retailer grew out of the software. Big Lots' SVP of Merchandise Planning/Allocation and CIO, Lisa Bachmann, had exhausted her efforts to enhance Big Lots' existing system. "The allocation software was a piece in a large supply chain project," says Bachmann. "We had initiatives in planning, allocation, and merchandising that included process changes as well as software deployments and integration." So, Big Lots developed new allocation processes prior to searching for software that met its requirements. After defining the business need, it sent out RFPs to select allocation software vendors.

Due to prior working relationships with key MID Retail principals, Bachmann sent an RFP to the company, even though it was in its infancy. The MID allocation software was not used in a production environment at any retail sites at that time, but Bachmann made the risky decision to choose MID's solution anyway. In February 2003, the allocation project began. Within nine months, Big Lots was ready to pilot test the software. The team made a conscious effort not to deploy the software during the holidays. Therefore, Big Lots trained employees on the software and tested the effects of analytic algorithms on store planning/allocation, but didn't deploy it until after the holidays.

"We began using basic forecasting only, which makes up approximately 60% of the software," says Bachmann. "We implemented a subset of merchandise that was distributed to all stores, then added products and advanced algorithms to our processes until we reached 100% implementation in July 2004." 

Pinpoint Demand In Great Detail
The effectiveness of merchandise allocation is one of Big Lots' key performance indicators. Within four months of implementation, Bachmann saw a balancing of sales and inventory by store volume. "We rank our stores by volume, and we immediately saw higher volume stores receiving more inventory and smaller volume stores being allocated less," says Bachmann. "It enabled us to cluster [i.e. categorize and distribute merchandise within] our stores in more detail than ever before. Our primary cluster is volume, but we can distribute merchandise at a class or subclass level using MID, causing reduced overall inventory." For example, Big Lots clusters stores and allocates merchandise by warm, hot, and cold climate zones in certain geographical areas during specific times of the year. Additionally, an overall A-volume store (a high-volume store) may be only a C-volume store (an average-volume store) in food sales. Within food sales, one store might sell lots of cereal (a subclass), but not cookies. Bachmann now organizes merchandise through a few thousand subclasses, which was previously impossible to achieve with her existing staff and 1,350 stores.

Big Lots did not change its allocation staff numbers due to the MID implementation; however, it did modify roles and responsibilities for its allocation employees, who required thorough training. The tool contains more statistics and was more sophisticated than the prior system, so employees who allocated merchandise required additional analytical skills. Allocation analysts continually optimize the placement of inventory and delineate the placement of goods by volume group and cluster. Analysts complete monthly allocation scorecards, which measure their allocation effectiveness. The team has continually improved the allocation of merchandise throughout the chain as employees learn about the software. Bachmann would not provide a percentage of efficiency gained by the deployment, but she confirmed that all supply chain improvements (process and software related for planning, allocation, and merchandising) have contributed to growth of the business.

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