The food industry is by one of the largest and most vital industries in the world. It encompasses everything from producers and shipping companies, to grocers and restaurants. Everyone needs food for survival, and most of us thoroughly enjoy to eat. Thus, it makes sense that the industry would take advantage of the same big data services as financial firms and marketing departments to better understand their consumer, increase efficiency and even create new recipes to try. Here are just three examples of how big data is revolutionizing the food industry.
Of Recipes and Bacon
Bacon has always been a versatile ingredient. It fits in at any meal and is great on its own or added to anything from soup and salad to sandwiches and burgers. Lately, however, our obsession with bacon seems to have been taken to a whole new level, with bacon inundating our desserts, cocktails and even our clothing. A data mining project completed byand analyzed this obsession to see if bacon truly was a magical ingredient that made any dish taste better. The project sifted through 906,539 ratings and discovered that sandwiches that include bacon see the biggest improvements in ratings. Unfortunately for those bacon dessert lovers, it was found that bacon does not improve ratings on dessert recipes.
Lada Adamic, a computer scientist at the University of Michigan confirmed the project’s results, but also noted several other ingredients that tend to boost ratings: cream cheese, whipped topping, strawberries and avocado.
Creative Recipes Made by Data
IBM researchers have also jumped into food industry analytics by creating a computer program that generates original recipes. The program works in five steps to ensure that the recipes are creative, unusual and will still be pleasing to eat. The first step of the program asks you to set some parameters for the type of recipe you would like to create by selecting a single ingredient, a regional cuisine and then a type of dish.
Next, the computer gets to work going through a giant collection of data that includes everything from relationships of ingredients in particular recipes and the molecules and chemical compounds present in each ingredient, to human flavor preferences. In the third step, the computer starts to generate new ideas based on traditional recipes and the parameters set in step one. At step four, the computer selects the best ideas based on novelty and quality, and in step five the recipes are created and presented as a list for the team to go try out in the kitchen.
This technology could very well revolutionize the way food manufacturers and even top chefs come up with new ideas for their recipes, which is good news for those who quickly become bored eating the same meal over and over.
Individual restaurant chains have also started exploring how big data can help them improve their business. McDonalds, for example, has been actively pursuing a data-driven culture by turning to trend-analytics to better understand what is happening at each individual restaurant, and to identify best practices to improve restaurants overall. For instance, the fast food chain uses big data analytics to optimize the drive-thru experience based on three factors: design, information provided on the menu and the types of customers coming through. Looking for trends in increased consumer demand, such as large cars of customers coming through, can be particularly beneficial for improving efficiency and preparing for that spike in demand ahead of time.
Thanks to big data in the cloud, making big data technology more accessible regardless of expertise or budget, we can expect to see more application of data analytics throughout the food industry in the future. It will be exciting to see what creative new dishes and trends restaurants and food manufacturers start to come out with once this type of technology really takes off. In the meantime, bacon anyone?