How the Biggest Restaurant Brands Use Big Data to Stay Competitive
Why is big data for restaurants such a big deal? Because a lot of what we do in our personal and professional lives would not be possible without the interaction between big data and the services, apps, and software systems that use it all. Take Waze, for example. It uses traffic, navigation and user-generated […]
Why is big data for restaurants such a big deal? Because a lot of what we do in our personal and professional lives would not be possible without the interaction between big data and the services, apps, and software systems that use it all.
Take Waze, for example. It uses traffic, navigation and user-generated data to help its users find the fastest way to their destination. So, what does all this have to do with restaurants?
Restaurants have excelled at collecting large amounts of data through the various point systems used to manage labor, inventory, loyalty and marketing programs, and more. Here are just a few ways restaurants have used big data to make better decisions, optimize performance and improve – even innovate – the customer experience.
McDonald’s Drives Speed through the Drive-Thru
McDonald’s is using big data to enhance its drive-thru experience. The company uses three factors (design, information provided on the menu and the types of customers coming through) to predict consumer demand. For example, if bigger cars are expected to come, they expect larger orders and alert their staff to prepare for the spike in demand, improving efficiency and customer experience.
Wendy’s Predicts Traffic Patterns
Wendy’s utilizes big data to identify the most profitable new restaurant locations. The company analyzes data on past sales and customer demographics, and then use the insights to predict how far people are willing to travel to eat and which location will be the most profitable based on that information.
Starbucks Lands the Right Real Estate
There’s a Starbucks on every corner… or at least it seems like it. And that poses an interesting challenge for the brand: how do you open a new store and not hurt the sales of an existing store operating nearby? They use big data applications to analyze location-based demographics to determine the best location for a new store.
Pizza Hut Digs Deep into the Subconscious
This example is straight out of Blade Runner or The Minority Report. Pizza Hut has installed digital, interactive menus in some of their stores and are using big data to better understand the decision-making processes of their customers. The software tracks eye movements of customers when ingredients are shown on the screen with the goal of discovering what pizza their customers subconsciously want.
The Cheesecake Factory Makes Cross-Country Connections
The Cheesecake Factory is using big data applications to combine data from its hundreds of locations to deliver a better dining experience. For example, if a customer complained about bad tasting ketchup in a location in California and another customer made the same complaint in Boston, the software will be able to track the batch of ketchup that may have gone bad and alert locations that are using it to switch to a new batch.
IBM (Yes, you read it right)
IBM has entered the food industry by designing software that can create new recipes. Once the user gives the software a few parameters such as ingredients, cuisine, and the type of recipe, the software analyzes all data available on ingredients, their relationship with each other, chemical composition, taste palettes of that region, etc., and serve up original recipes that chefs can try out in their kitchen.
Can Data Answer Your Big Operational Challenges?
While restaurants are getting better about using all of their data to help create great experiences, there’s been less of a focus on using operational data to predict business outcomes. But it’s on the minds of leading tech and operations teams, alike.
For example, if it’s a sunny day, your business outcome for that day could be affected positively or negatively depending on the actions you take. Great weather could mean more guests in your restaurant. Should you open your patio? Do you have enough staff scheduled to accommodate the changes? Did you order enough food to run a special and really capitalize on the foot traffic? If so, what special will net you the best profit? These are all questions that data can answer.
Great weather could mean more guests in your restaurant. Should you open your patio? Do you have enough staff scheduled to accommodate the changes? Did you order enough food to run a special and really capitalize on the foot traffic? If so, what special will net you the best profit? These are all questions that restaurants can answer with big data.
The difference is that you need intelligent, actionable insights that give your manager a step-by-step guide to executing the day. Data will allow you to take the guesswork out of the decision making. The key is to aggregate data from multiple sources so that your managers get recommendations they can use in the moment, on the shift. It’s time to use data to improve business outcomes.
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