Labor is one of the largest variable costs in a retailer’s operating budget. During the past several years, retailers have worked to create lean processes and gain efficiencies with impressive bottom-line results. Some lean retailing initiatives have even yielded as much as a 15 percent reduction in retail operating costs.
With competition increasing and customers demanding greater service levels, retailers need to find new ways to increase efficiencies while enhancing customer service. One key area of focus is retail labor scheduling and budgeting. However, many retailers rely more on gut feel than on data, often resulting in poor staffing decisions and schedules that fail to match customer behavior and customer expectations.
With complex nature of creating accurate staff schedules and budgets, even sophisticated retailers can find opportunity for improvement. While projected revenue has long been used as a criterion for employee scheduling, it creates flawed staffing models because it fails to take into account customer buying patterns (average sales per transaction, units per transaction, shoppers to staff ratio, etc.). While off-the-shelf retail staffing software excels at monitoring employee attendance and managing payroll, it does not allow retailers to measure lost sales and customer conversion metrics.
Many retailers still mandate labor budgets in a top-down manner that does not take into account the operating environment at each location. According to McKinsey & Company, differences among stores can result in labor-cost differences of as much as 30 percent even if the stores’ sales are equivalent.
In order to produce more than generic schedules, retailers need to use shopper-based metrics to identify a store’s peak times and traffic patterns in order to adapt to shopper’s actual buying behaviors.
It’s All about the Metrics
Staffing schedules rarely align with a store’s true labor needs, often causing labor budgets to be mismatched with the store’s operating reality. In order to optimize staffing to shoppers’ buyer behavior, it is essential to look at the relationship between key shopper-based metrics:
- Shoppers to Staff Ratio
- Shopper Value
- Average Shopper Dwell Time
- Conversion Rate Percentage
When Do Shoppers Engage in Specific Buying Behaviors?
What activities cause bottlenecks and long lines in your store? For a grocery store such as Kroger, it may be long lines at the deli and bakery counters. McKinsey & Company found that deli and bakery service counters account for a European grocer had higher share of revenue on weekends than weekdays.
Comparing multiple metrics such as shoppers to staff ratio, average shopper dwell time and shopper traffic distributions can reveal peak times when the deli and bakery counters need additional staff to serve demand. In this example, the Kroger may find that the deli counter is busiest from 10 a.m. to 4 p.m. on Saturdays and Sundays when shoppers are stocking up on deli items for the next week of lunches. What’s more, further analyses may reveal that the store’s overall conversion rate percentage dips when dwell time at the deli counter becomes too long and customers leave in frustration.
Break the Bottleneck
How does a retailer break the bottleneck and overcome long lines and customer frustration? It is essential to determine what operational activities take employees away from the retail floor and customer facing activities in order to improve efficiency.
Key Questions
- What activities take place each day?
- How much time is needed to complete the activity?
- What are the main drivers of the activity?
- How often must the activity be completed?
Once essential activities are identified, retailers need to communicate the most efficient procedures to employees. The procedures should include how to complete each task and how much time each task should take. Establishing target times and procedures for the most important activities ensures that operations will be handled the same way across all of a retailer’s locations.
All stores should be given the same amount of time for each task, with adjustments for store-specific differences, such as the distance an employee must walk to perform a task.
Essential functions, such as restocking and inventory tracking should be schedule for non-peak times.
When retailers can better predict the number and skill sets of employees that each store needs by the hour of the week, customers will receive prompt customer service and shelves will be restocked in a timely manner. What’s more, employees will not be idle nor will they be overworked and, in most cases, labor costs will decrease.
Create An Adaptive Staffing Model
Shopper-based metrics can also uncover opportunities for improving a retail store’s processes and can become the foundation of a continuous improvement program. This can be particularly valuable to stores that employee 20 or more people per location. By leveraging a mix of full-time, part-time and temporary employees, retailers can create an adaptive workforce able to respond to schedules that change weekly or even daily.
To actually improve staffing, retailers need to compare multiple shopper metrics from their store’s traffic analytics platform for each functional area. For a our Kroger example, this would mean breaking shopper and staff data into departments such as check out, produce, deli, bakery, meat and fish, etc.
Use Shopper-Based Metrics as KPIs
By using shopper-based metrics as benchmarks, individual store locations can remain up-to-date with the staffing demands at their location, enabling store managers to proactively respond to changes in the marketplace. Long-term staffing optimization efforts should introduce key performance indicators (KPIs) for shopper-based metrics with clear productivity-based service level targets to ensure that all stores are complying.
Sustainable Staffing Improvements
According to McKinsey & Company, chief operating officers at some of the nation’s leading retailers have begun looking closely at store activities and are taking a more data driven approach to staffing and budgeting. These retailers have realized savings of between 4 to 12 percent while at the same time improving customer service with shorter checkout lines or more staff on the sales floor, boosting employee satisfaction. Ultimately, a shopper-based metric approach to staffing creates sustained improvements in store productivity, customer service and employee satisfaction while keeping labor costs in line.