Restaurant Operations: A Case Study
An international restaurant chain was experimenting with new kitchen and server technologies.
- A leading chain realized that future growth will be driven by improving sales at current restaurants, rather than by adding sites.
- Using APT’s technology, the client rapidly tested and analyzed the impact of the new technologies on all relevant performance indicators (traffic, sales, satisfaction etc.).
- The restaurant chain altered its approach to technology introduction based on learning from this test.
The Company
A leading national restaurant chain
The Challenge
The client was investigating an investment in new technologies geared towards efficiency. While feedback from store managers indicated that the technologies would be effective, the company was not seeing a strong sales impact after the introduction of the new technologies. There was internal disagreement as to whether or not to roll out this technology to the entire network. The client looked to APT's enterprise Test & Learn for Sites™ software to identify the most profitable strategy.
The Solution
The Company first wanted to ensure that the new technology was tested in an appropriate manner. They needed to find answers to a host of questions, such as: How many restaurants would be required to test the program? How long would the test need to run to get statistically significant results? How should comparison groups be selected against which test restaurants performance could be benchmarked? Should control restaurants be selected from the same region as the test or spread across the country?
Using the APT Suite, the test was designed in such a way as to ensure that results would be clear and applicable to the rest of the network. APT’s test design tools helped the company to choose a set of stores for the test that was 1) large enough to ensure a statistically significant read on a break-even result and 2) representative of the entire network.
Prior to integrating all available data into the APT system, analysis of all relevant metrics for this technology introduction was difficult. With all data loaded into the APT system, however, the client was able to analyze the impact of the new technology on all key metrics: sales, margin, checks, guestsSatisfaction, efficiency, etc. Additionally, the restaurant was able to break down the impact across different parts of the day: Lunch vs. Dinner, the Peak (12 pm – 1 pm) vs. Off-Peak (1 pm – 2 pm).
Test & Learn™ analysis did not stop here. Results were also segmented to determine demographic and restaurant characteristics associated with success.
The Results
APT's analysis clearly determined the new technology’s impact on check-times by day-part, as well as the impact on sales and guest count. The management team incorporated these findings into their technology strategy going forward.
