Optimizing Labor Hours: A Case Study
A leading US convenience retailer turned to APT to design a test that would isolate the impact of labor force size on sales and help to set optimal staffing levels.
- In an attempt to boost customer traffic, the retailer turned to APT to design an in-store test to determine optimal staffing levels.
- Based on the test, APT identified the profile of stores where the sales lift offset the additional labor cost.
- Targeting additional labor hours to high potential stores generated $4 million in incremental annual profits.
The Company:
A leading US convenience retailer with over 1,000 stores
The Challenge:
The APT client is a leading US convenience retailer with many offerings – fuel, merchandise, deli, carwash, etc. Unless the deli area is clean, the lines short, and the employees welcoming, customers will take their business elsewhere. In an attempt to boost customer traffic, a large US convenience retailer turned to APT to design a test that would isolate the impact of labor force size on deli sales and thereby help to set optimal staffing levels.
The Solution:
Using APT's Test & Learn for Sites™, the retailer identified a subset of stores that were representative of the chain as a whole, executed an unbiased test of the impact of increasing labor hours by 2%, and determined the incremental impact of the increase in labor hours. Over the course of a difficult quarter, sales and margin of the test store delis rose 1.0% above control store delis. The non-deli sales of test stores were equal to those in the rest of the chain, resulting in no incremental impact.
The 1.0% lift in deli sales was not high enough to offset the cost of additional labor across the chain, but thanks to the analytic power of Test & Learn™, the data provided statistical confidence in the advantages of labor increases in certain contexts. APT’s analyses identified specific site characteristics that were directly linked to increased sales performance. For example, one major driver of success was competitive environment; stores in highly competitive regions experienced sales lifts of 4%, compared to only 0.6% or 0.2% lift in locations with medium or low competitive intensity.
This insight gave the retailer hard data that revealed where labor hours matter most. Customers proved to be more sensitive to customer service when alternative stores are located nearby. Therefore, the chain could drive greater traffic and sales by increasing labor hours only in those stores that were located in close proximity to competitor sites.
The Results:
Based on the findings of their in-store tests, the retailer created a targeted strategy for increasing labor hours only in specific, high-opportunity locations. The strategy generated $4 million in annual incremental cash flow for the company.
Next Steps:
