If you want to understand how big data can transform the restaurant industry, start by reading Michael Lewis’s Moneyball: The Art of Winning an Unfair Game. The book depicts how Billy Beane, general manager of the Oakland A’s, turned one of baseball’s poorest teams into a playoffs contender by ignoring conventional baseball statistics like stolen bases and RBIs. Instead, Beane analyzed data to find metrics that really predict success (like on-base percentage), then mined that information to assemble an underrated team that ended up in the playoffs in 2002 and 2003.
The restaurant industry is having its Moneyball moment. Now that mobile and cloud technology are cheap and widely available, any restaurant can collect, analyze and act on huge swaths of data. Whether you have an Oakland A’s or New York Yankees budget, your restaurant has the ability to cut costs and increase profits by using big data that was invisible until recently.
When you collect in-store, near-store and above-store data, and then connect it all together in the cloud (i.e. on powerful computers located outside your restaurant), you see problems and opportunities that have gone unnoticed. You can begin to change conventional processes that have been killing your profit margins and losing you customers.
In-store data is all the information that comes from your restaurant. Your POS devices, fryers, refrigerators, temperature sensors and labor scheduling system can all communicate useful data. Combine them in the cloud, and you can detect patterns.
For example, one global restaurant brand learned that its fryers were a huge source of inefficiency. Five times per year, when they added new menu items, all 100,000 fryers had to be reconfigured and each required 30 minutes of labor. So, the company developed a way to push new instructions to fryers via the cloud. Now, an IT guy clicks one button, and all 100,000 fryers know how to cook the new menu item. It’s similar to the way Keanu Reeves learns Kung Fu in The Matrix.
By comparison, near-store and above-store data is all the information that originates outside the restaurant and above the restaurants in the company hierarchies. Near-store data includes weather, Yelp reviews, sports calendars, school holidays, special events and any other external data that could affect revenue and therefore the inventory and labor.
Normally, a good manager keeps an eye on the near-store data and adjusts inventory and labor based on experience or gut feel. When you instead connect all this data in the cloud and compare it against sales, both real time and historical, you can build much more efficient labor and inventory models for your restaurant. Instead of guessing, your managers forecast inventory and labor needs with fewer errors, all on their smartphones.
There are few limits on the data you can collect and analyze, which means your Moneyball edge could look very different from a competitor’s, especially if you experiment with emerging technologies.
For instance, WiFi beacons—internet devices that connect with customers’ smartphones using Bluetooth—could give you data few competitors have. With a mobile app and loyalty program that requires customers to check in at your restaurant via their phone, your beacons could track the spending patterns of every customer and push personalized coupons to their smartphones. If you connected this beacon data to social media data, you could determine what types of people are likely to be valuable customers and market to them. Data becomes a tool for slashing expenses, growing sales and optimizing your marketing budget.
In Marc Andreessen’s op-ed “Why Software is Eating the World,” the famous investor argued that software companies are taking over the economy. Amazon is eating retail. LinkedIn is eating recruitment. Uber is eating the taxi industry. Dominant restaurant brands, too, will look like software and data companies that happen to make food. The days of gut feeling and good food are dwindling. It’s time to embrace data and play Moneyball.