In recent years, retailers have taken steps to “lean out” their processes and gain efficiencies—with impressive results. Lean-retailing initiatives have yielded as much as a 15 percent reduction in retailers’ operating costs. But with competition intensifying and with customers expecting ever-higher service levels, many retailers are now looking for new ways to further improve productivity and enhance customer service.
One major area of opportunity is workforce management: specifically, labor scheduling and budgeting. Because of the complexity inherent in creating accurate staffing schedules and budgets for a large number of stores, even sophisticated retailers find substantial room for improvement in this area. Off-the-shelf software and solutions—although useful for important tasks such as monitoring employee attendance and managing payroll—typically produce generic schedules that don’t take into account store-specific factors and workload fluctuations. The unfortunate results include high labor costs, inconsistent customer service, and dissatisfied employees.
If a retailer could better predict the number and skill set of employees that each of its stores needs every day (or, better, every hour) of the week, then customers would get prompt sales assistance, shelves would be replenished in a timely manner, employees would be neither idle nor overworked, and, in most stores, labor costs would go down. That’s already happening at a few leading retailers. Chief operating officers have begun looking closely at store activities and taking a more data-driven approach to labor scheduling and budgeting. In doing so, they have captured between 4 and 12 percent in cost savings while also improving customer service—for example, by shortening checkout queues or by having more staff available on the sales floor to assist customers—and boosting employee satisfaction. This level of impact has been achieved at several different types of retailers, from large supermarket chains in Europe to specialty retailers in emerging markets.