Case Studies > Operating Hours: What are the most profitable operating hours?

Operating Hours: What are the most profitable operating hours?

Company Size

1,000+

Region

America

Country

United States

Product

APT’s Test & Learn for Sites software

Tech Stack

Test & Learn approach

Implementation Scale

Pilot projects

Impact Metrics

Customer Satisfaction
Revenue Growth

Technology Category

Analytics & Modeling - Predictive Analytics
Analytics & Modeling - Real Time Analytics

Applicable Industries

Automotive

Applicable Functions

Business Operation

Use Cases

Predictive Replenishment
Process Control & Optimization

Services

Software Design & Engineering Services
System Integration

About The Customer

The customer is a leading auto service chain with numerous locations across the United States. The company is known for providing a wide range of automotive services, including maintenance, repairs, and inspections. With a large customer base and significant weekend traffic, the company is focused on optimizing its operations to maximize profitability. The management team is proactive in exploring new strategies and technologies to enhance customer satisfaction and operational efficiency. They are particularly interested in data-driven approaches to decision-making and have partnered with APT to leverage advanced analytics for their business operations.

The Challenge

Executives at a leading auto service chain wanted to identify the optimal operating schedule for its locations. Given heavy customer traffic on the weekends, management planned to open its service centers two hours earlier on Saturdays, but first wanted to understand the total profit impact of the change. Specifically, the client sought to understand if the extended hours would generate a sufficient increase in sales to offset the associated costs.

The Solution

Using APT’s Test & Learn for Sites software, the client designed an in-market experiment to test the new hours in a representative subset of service centers and measure the incremental impact on profit. The software compared 'test locations,' where the hours were changed, to customized groups of similar 'control locations,' that did not undergo hour changes, to isolate the incremental profit impact of the operating hour changes. APT’s rigorous test-and-control analysis showed that the extended hours led to an 8.4% ($210 per location) lift in Saturday gross profit throughout the test period. The software revealed that the lift in profit came primarily from the extra hours and only caused slight cannibalization of mid-morning profits. However, while there was negligible impact on weekday profit, the analysis identified a 1.1% ($28 per store) decline in Sunday gross profit. Accounting for this cannibalization of Sunday profit and the required $170 in additional labor/operating costs per store, the auto service chain found that extending hours would cause a $43 decline in profit per store on average.

Operational Impact

APT software identified select locations in the network where the hour changes would have a positive impact.
The software automatically analyzed thousands of factors, such as market demographics and store attributes, to identify characteristics associated with higher performance.
Specifically, the software revealed that in service centers located in areas with lower income, larger households, and more competitors nearby, the extended hours would drive a large enough profit increase to have a positive net profit impact.
A network-wide rollout of the hours change would have caused a decline in profits, but by employing a Test & Learn approach, the client limited implementation of the change to the locations predicted to respond best.
Targeting the operating hours change to the right service centers made the program profitable and resulted in a $2.5MM incremental annual profit improvement.

Quantitative Benefit

8.4% ($210 per location) lift in Saturday gross profit throughout the test period.
1.1% ($28 per store) decline in Sunday gross profit.
$170 in additional labor/operating costs per store.
$43 decline in profit per store on average.
$2.5MM incremental annual profit improvement.