Optimal Headcount and Labor Standards use cases
Updated
by
Leigh Hutchens
Use case 1: Optimizing staffing for peak hours in retail
Scenario
A large retail chain experiences fluctuating customer footfall throughout the day. During peak hours, such as lunch breaks or evenings, customers significantly increase, requiring more cashiers and floor staff. However, fewer staff members are needed during off-peak hours to reduce labor costs.
Solution
- Use labor standards with linear rules to predict the number of cashiers needed based on forecasted sales transactions during peak hours.*
- Configure dynamic rules to account for varying productivity levels (e.g., faster transaction processing during peak hours).
- Typically, you would use either linear or dynamic rules, not both, as combining them can overestimate headcount by summing needs calculated from each rule.
- Linear rules may work best for cashiers, as their transaction speed typically remains consistent regardless of the queue length.
- Dynamic rules, on the other hand, could be more suitable for floor workers, as they tend to spend less time per customer when the number of customers increases.
- Typically, you would use either linear or dynamic rules, not both, as combining them can overestimate headcount by summing needs calculated from each rule.
- Implement minimum rules to ensure at least one manager is always present during store hours.
- Minimum rules or static rules can be used in retail stores to ensure that someone starts working 15 minutes before and after opening hours to open and close the store, which is a very common scenario.
Outcome
The optimal headcount ensures sufficient staff during peak hours while minimizing overstaffing during quieter periods, improving customer service and labor efficiency.
* We use historical sales data to predict future sales, but for labor standards, we apply linear rules based on the projected future sales.
Use case 2: Managing labor standards across multiple locations
Scenario
A fast-food franchise operates in different locations with varying productivity levels due to equipment differences (e.g., older machines in one branch take longer to prepare food).
Solution
- Configure location-specific labor standards to reflect differences in productivity for each unit.
- For example, use a different labor standard for a branch with a slower coffee machine, adjusting the number of baristas required.
- Use static rules to ensure a fixed number of key roles (e.g., one manager and two cashiers) are always staffed across all locations.
Outcome
Each location operates efficiently according to its unique needs, and labor costs are optimized without compromising service quality.
Use Case 3: Automating schedule creation for a call center
Scenario
A customer service call center must match staffing levels with call volume forecasts to maintain service level agreements (SLAs). During peak hours, more agents are required, while during low-demand periods, fewer agents are needed.
Solution
- Use Dynamic Rules to match forecasted call volumes with the required number of agents per hour.
- Apply Min/Max Rules to ensure that a minimum number of agents are available to handle unexpected call surges but not exceed the maximum capacity due to limited seating.
- Leverage the Auto Schedule feature to generate shifts based on optimal headcount and availability.
Outcome
The call center achieves consistent SLA compliance, reduces agent idle time, and avoids overstaffing during low-volume periods, saving costs while maintaining service quality.
