Business intelligence levels the playing field inside organizations with multi-store retailing operations, improves performance and raises profitability
It's ironic that one of the key decisions in multi-store retailing operations has often been relegated to an entry-level employee or, at best, to an up-and-coming associate who will quickly move on to greater things within the company. The role of the allocator — the person who ultimately decides how many units of a product each store gets — is critical: give a store too much and you create a markdown situation. Shortchange a store and it can lose precious revenue. Misjudge several stores' selling potential and the whole chain suffers.
Allocation is the last step in a complex process that involves many prior decisions about corporate goals, store locale, product mix and floor space, among others. Ideally, a good allocator will feed a store just the right amount of product to ensure the most full-price sales and the fewest post-seasonal markdowns.
The situation — merchandise, store, season, inventory — helps the allocator to determine what method or methods to use. Depending on these variables, the allocator knows when to apply certain methods and in what order to apply them. This knowledge is learned and perfected through experience until the allocator masters the distribution process.
Research has shown that the top allocators make better decisions when they've learned all of the key variables and know how to apply the appropriate methods. Once they've learned these critical influencers, top allocators consistently make better decisions and produce the best practice methods of allocation decisions.
But what if everyone in an organization could allocate as well as the top performers? On average, allocators are responsible for shipping tens of millions of dollars of merchandise to stores each year. By closing the gap between the best and the rest by even a percentage point, a retailer can significantly improve its bottom line. For a retailer with annual revenue of $100 million, reducing markdowns by one percentage point generates approximately $450,000 in savings for the company. In addition, inventory improvements of one-tenth of a turn equate to a savings of approximately $275,000 for the same-sized retailer.
Current Automated Systems Only as Good as the Allocators Driving Them
Current allocation systems help to identify key variables that influence the allocation process and provide tools to capture this information for the allocator. The information helps save time and improve consistency in the process by allowing the allocator to make more informed decisions.
However, the allocator is ultimately in charge of what methods to use and must take into account a multitude of variables. The actual quality of the allocation decision is determined by his/her ability to weigh all of these factors and recommend the best allocation decision.
Dynamic Learning Solutions Add Intelligence To the System
Today, emerging technology can help allocators uncover all the critical drivers of the allocation process and map data situations to best practice allocation results. Business intelligence (BI) software introduces successful past performance into the allocation equation and draws on the decisions made in similar situations by the company's top performers. The software models the best decision-making practices of top allocators and uses this knowledge and expertise for all users in the organization.
When used with current automated allocation systems, new BI software provides the needed intelligence to help retailers significantly improve the productivity and quality of allocation decisions and quickly realize lower operational costs and higher profitability.
Jim Dixon is president and CEO of Applied Intelligence Solutions (http://www.aisllc.com/), a company targeted toward retail companies to improve the quality of their allocation decisions. He can be reached at firstname.lastname@example.org.