Chain Restaurant Data Analytics: No Weak Links
When you run a chain restaurant, you’re always considering the parts of the whole. These individual restaurants make up the “links” that comprise the entire operation. To a degree, these operators sit at the top of the proverbial restaurant mountain regarding quantities. Restaurants in this segment see immense numbers in volume and revenue – so operators analyzing a chain restaurant’s analytics know that every granular detail or every single site counts in the long run. Chain restaurants take many forms, some offering quick service style-cuisine, others more formal sit-down fare. With them, comes off-premise dining capabilities, delivery systems and a whole smattering of restaurant features, concepts, and variations within. That’s pages upon pages of data, sometimes spanning multiple continents, through which an operator must sift.
For Ian, a chain restaurant operator, the question of using a kitchen display system to track his data wasn’t a question of “if” but one of “how much?” He needed to know the in’s and out’s of all his specific restaurants, and also metrics in the big picture. Chain restaurants represent efficiency and ubiquity for customers. They’re familiar comforts and can be beacons of stability in unfamiliar places. Customers turn to chain restaurants to get the food and service they know and love. To maintain those standards, Ian ensures his KDS has a recipe viewer. With this feature, all his staff, no matter their location, are trained on the same processes. While consistency across the entire chain remains essential to Ian, he also knows that with each of his sites, comes its specific challenges.
He also swears by a solid front-of-house platform – a restaurant reservation system that integrates with his KDS. This integration provides real-time data for staffers in the front and back, so the entire operation is unified. His kitchen workers can maintain cognizance of what’s going on upfront, while hosts won’t need to keep running back and forth to check on the status of an order. Automated, these processes carry on and update in real-time so staff can focus on providing an exemplary customer experience.
In reviewing his restaurant’s kitchen analytics, Ian can customize the metrics he assigns to different sites, corresponding to their thresholds. He can assign different “warning” metrics to his high and low-traffic sites, accounting for their strengths and weaknesses. What may be a low-income night for one store may be high for another. With every process in his restaurant automated, updating in real-time, Ian’s staff can focus on those in-the-moment necessities necessary to keep a restaurant running.
At the chain level, Ian needed the ability to access his restaurant data from anywhere through an enterprise portal. With this kind of data flexibility, he can access the “nitty-gritty” analytics of his restaurants, like the speed of service metrics for a certain restaurant, and how it performs every Thursday between 6 and 8 pm, or the “broad picture” analytics like total revenue for all his sites in the Tri-Cities.
A KDS with robust redundancy features comes paramount to running a chain. With this kind of volume, an in-store backup that keeps tracking the data should his restaurant lose connectivity, means that even in the worse-possible scenario, his operations continue uninterrupted and he’s not losing data. Were his KDS running on an entirely cloud-based framework, he wouldn’t have this luxury! Once his KDS reconnects, the data resyncs and it’s as if there weren’t a loss in connection at all.
Ian knows that from the top to the bottom, link by link, his data are also being tracked. He knows his technology will keep every restaurant process updated in real-time and also, that these incremental time-saving measures create efficiency wins. Through technology, he’s managed to systematically cut down on food waste across the board. Think about it, if every one of his sites wastes $10 a day, this account for substantial savings compounded by years and months.
Furthermore, he’s been able to significantly increase profits by streamlining his entire operation. Excellence at every station, at every restaurant, all the way up the chain. That’s how you do chain restaurant analytics.
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About the Author
Brian leads the Implementation, Project Management, Training, and Support Services groups at QSR Automations. He has dual degrees in Information Systems and Operations Management and is a big baseball fan. He’s visited most of the Major League Baseball parks! Outside of that, he loves spending summer evenings with his family, especially at Louisville Bats games.