Research Reveals Need for Retail Labor Cost Optimization
For many corporations, labor costs can account for half of all expenditures. And for retailers that rely on seasonal and holiday help, these costs can balloon, researchers say, and impact the bottom line due to a lack of labor cost optimization.
However, two recent research findings revealed that retailers can deploy various strategies and use data-driven tactics to mitigate these costs.
Lisa Disselkamp, LaborWise Innovation Architect at Deloitte, told WWD that three of the most persistent impacts of labor to a retailer’s profits “come from things that retailers are not currently doing well enough, like capturing time, controlling spending and optimizing capacity in the right way.”
Disselkamp explained that “time capture” for retailers goes beyond arrival and departure. She said it’s “knowing things like what employees are doing and where they are stationed. These are simple ways to help manage compliance and productivity.”
Inefficiencies center on “time inflation” she said, adding that unnecessary overtime as well as over- and understaffing also impact costs. “Retailers have come to rely heavily on part-time workers, but it has come at a high cost,” Disselkamp said. “Turnover diverts much-needed funds away from revenue-driving investments and overall profitability. Capacity optimization models that ignore the need to deliver high-quality schedules that are predictable and stable and provide workers the hours they want drive up absenteeism, overtime and turnover costs, which in the end hit the bottom line with greater labor expense.”
Disselkamp said stable, sustained profits require solid time capture as well as controlling costs and creating “schedule capacity equilibrium.” Moreover, when staffing and labor costs are controlled and optimized, store managers, for example, can “focus on things like hiring the right people and managing inventory, and less time spent on managing labor and payroll.”
But how much is inefficient labor management costing retailers? Disselkamp said it can be up to 2.5 percent to total annual payroll. She also noted that companies don’t need to eliminate positions to mitigate these costs.
A good place to start is to look for hidden sources of labor costs, Disselkamp said. “Hidden labor spending can be converted into more customer-facing roles and associate relations roles that work to make sure high-quality schedules are delivered, reducing turnover,” she explained. “These new roles produce a more experienced, tenured workforce that can see their employer cares about balancing their work schedules with their personal commitments.”
Disselkamp said based on Deloitte’s analysis, resolving these issues could result in average savings of $200 to $800 per hourly employee, annually. “Additionally, by freeing up time spent on managing labor and by optimizing labor-related processes, employees and managers are able to focus on productivity — not only saving cost, but ultimately increasing profits.”
Deloitte offers LaborWise, which is a workforce-focused analytics solution “that identifies, quantifies and unlocks hidden sources of labor overspend, empowering organizations to optimize their workforce, drive sustainable savings and improve productivity,” the company said, adding that the main purpose of LaborWise “is to solve some of the most difficult employer challenges such as validating if the organization is effectively managing labor spending, reducing turnover and delivering good schedules for people.”
In separate but related research from the MIT Sloan School of Management, visiting professor Rogelio Oliva and his colleagues have developed a data-driven approach to optimizing staffing levels. “Testing the method with real data, they found that it could increase sales performance for an apparel retailer by approximately 10 percent,” an MIT spokesperson said.
“The ability to efficiently match store labor with incoming customer traffic is crucial, especially during the holidays when stores expect increased traffic and often rely on year-end sales. But optimizing staffing levels is very challenging, as retail environments are characterized by volatile store traffic, which makes it difficult to provide consistent service quality,” Oliva said.
Oliva and his team said that often, staffing is set by store-budget allocations. “A typical sales-based staffing rule is to match a constant ratio of expected store sales to the number of store associates,” he said. “However, this ignores the fact that retail sales are also affected by store traffic and might result in labor-to-traffic mismatches, which can negatively impact revenue. The scheduled labor may not be enough to meet customer traffic flows.”
By way of solution, Oliva leverages performance data across individual stores within a retail chain. “The approach enables retailers to derive aggregate labor requirements by utilizing traffic data, point-of-sale data, and labor data across stores with similar attributes like store format, product mix and market demographics,” he said, adding that by using this method, his team found that store managers were “systematically understaffing their stores.”
Oliva said if these retailers even slightly increased staffing levels, “they would generate incremental sales that would outweigh the labor costs. This highlights that employees are an important contributor to the sales process. When there aren’t enough sales associates, sales don’t reach their potential.”
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