[recuter]

   Our hypothesis: By making smarter kitchen equipment we can collect more data. By applying data to our restaurant, we can build more intelligent systems. By building more intelligent systems, we can better scale our business.

   As a simple example, imagine a forecasting model that attempts to predict how many Waffle Fries (or replace with your favorite Chick-fil-A product) should be cooked over every minute of the day. The forecast is created by an analytics process running in the cloud that uses transaction-level sales data from many restaurants. This forecast can most certainly be produced with a little work. Unfortunately, it is not accurate enough to actually drive food production. Sales in Chick-fil-A restaurants are prone to many traffic spikes and are significantly affected by local events (traffic, sports, weather, etc.).

   However, if we were to collect data from our point-of-sale system’s keystrokes in real-time to understand current demand, add data from the fryers about work in progress inventory, and then micro-adjust the initial forecast in-restaurant, we would be able to get a much more accurate picture of what we should cook at any given moment. This data can then be used to give a much more intelligent display to a restaurant team member that is responsible for cooking fries (for example), or perhaps to drive cooking automation in the future.

   Goals like this led us to develop an Internet of Things (IOT) platform for our restaurants. To successfully scale our business we need the ability to 1) collect data and 2) use it to drive automation in the restaurant.

The football game next door is over and the home team won? Start extra burgers in anticipation of hungry fans - great. I buy that.

The whole thing can be one app running on an iPad with multiple redundant data plans enabled, esims from AT&T and Verizon or whatever. You're going to need a touchscreen tablet for the POS anyway, no need for additional hardware or Kubernetes.

[joezydeco]

The game is over and carryout orders are starting to flood in from hundreds of customers on the smartphone app. And now Grubhub, Doordash, and UberEats are sending orders too.

The iPad is going to handle that and signal to the cooks to drop more chicken tenders?

[hgsgm]

Do people go out to eat more after wins than losses?

[recuter]

No idea, but I'm sure a super fancy machine learning big data model can run on the iPad/POS itself instead of 2000 Kubernetes clusters.