The current gold standard for zipping patrons through a lunch line (what the industry calls "throughput") is Chipotle. According to its 2014 annual report, Chipotle manages to serve 300 meals per hour—a transaction every 12 seconds—at its best-performing locations, and the chain is so obsessed with its productivity that it assigns employees efficiency roles with names like "linebacker."
When Maple launched its first location in April, it served around 50 meals per hour at peak times. Less than a year later, on average it is now serving 800 meals per hour from each of its four kitchens. A few days before I visited in February, it had set a new record: 1,100 meals cooked and delivered in one hour...
That’s why continuing to invest in technology that can squeeze every last bit of efficiency out of its modest space and crew is important. Maple recently introduced, for instance, ordering windows that serve a dual purpose of allowing customers to schedule their lunch delivery at certain times and, at some point, helping to manage demand. The app could, for instance, allow people in a building where deliveries are already scheduled to order lunch, while telling a customer in an address not already scheduled in a route that lunch is sold out. Or, it could accept your order for instant delivery of a salad, which can be prepared in minutes and can join a trip to your address that’s almost ready to leave the kitchen, but tell your coworker who wants to order a chicken breast, which takes longer to cook, that his order will need to be slotted into the next hour’s trip.
With data science and smartphones, possibilities for increasing efficiency seem endless. As it scales, Maple even plans to coordinate its couriers so that they don’t need to come back to one kitchen to pick up orders—they can return to a different, closer hub, or receive a new order from another courier they’ll pass on the way.
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