When you hear the term Big Data, the first thing that pops into your mind probably isn’t food, flavors, or family-owned restaurants. But analytics are playing an increasingly important role in the food industry. Josh Polsky writes, “Take a local family owned chain of restaurants for example. It’s highly doubtful that they have so much data coming in from their website, facebook page, or twitter account, that they would need to process it. They do however have plenty of data being collected in the kitchen everyday.” [“Cooking with Big Data in the Food Industry,” Xplenty Blog, 26 June 2013] He continues:
“Restaurants that serve food made from fresh ingredients, which is pretty much all of them, face the task of ordering just the right amount so they have enough to cook every dish ordered, but not too much that some will spoil and go to waste. It used to be that projected amounts were based on stats like previous amounts purchased, dishes sold, amount of spoiled product (one of the biggest problems faced by the food-service industry is inventory shrinkage, not the Seinfeld kind), estimated product shelf-life, not to mention the chef’s gut-instinct and past experience. It’s plenty good if the chef or kitchen manager has been around for a while and has his system down pat. But what about those that needed a little more help with their projections? How about technologies that alert you as to when your stock is running low, so you don’t run out before the next batch is ordered? And what about getting customer feedback to know what was good, what was bad, and what can be improved. Seriously, how often do you see comment cards with things other than obscenities and funny pictures? Imagine if a restaurateur could tie post-sale comments to his purchasing and ordering, as well as recipe amounts and financial stats like profit margin for actionable insights. All of this information is enough to steer a restaurant business in the right direction.”
Small business owners are especially sensitive to profit margins and they have probably shied away from using Big Data analytics assuming they would be unaffordable. Polsky, however, indicates that companies like his (Xplenty) provide applications that are affordable and can be tailored to the business. Kylie Jane Wakefield agrees with Polsky that restaurateurs need all the help they can get. “Succeeding in the restaurant industry is no easy task,” she writes. “According to the Washington, D.C.-based National Restaurant Association, a leading trade group, pre-tax profit margins range between three and five percent.” [“Restaurants utilize big data to stay competitive,” Tech Page One, 24 March 2014] The most successful restaurants, of course, are the ones that serve the best-tasting food. For them, as Ford Motor Company used to say, quality is job one. “The importance of quality,” Wakefield writes, “is why a number of restaurants are using big data to develop a better understanding of consumer preferences and to improve their food and service. In some cases, these businesses have already achieved revenue gains as a result of their efforts.”
As Polsky noted, most restaurateurs are not data scientists and need specialists to help them make sense of collected data. Wakefield adds, “Some restaurants are using outside software providers to gauge which dishes are likely to succeed and reduce the uncertainty of making menu changes.” One such vendor, she notes, is Food Genius. “Food Genius aggregates data from restaurant menus around the country to better understand pricing, food and marketing trends,” Wakefield reports. “For example, a restaurateur can see what types of food-related keywords and phrases are trending online, the average price of a certain dish, and which menu items are growing or shrinking in popularity.” To give you an example of the kind of insights Food Genius can provide, Teresa Novellino looks at what the company has to say about the all-American hamburger. [“How do you like your burger? Food Genius delivers the data,” Upstart, 21 March 2014] Food Genius, she reports, “has turned its attention to the burger with data that might help restaurateurs figure out what their burger competition is up to and how they stack up.” She continues:
“Perhaps not surprisingly, burgers are one of the most popular and common dishes on U.S. menus, mentioned on 56 percent of menus so the competition is wide and deep. Among the items that may surprise: peppers are mentioned more often as toppings on burgers than pickles, and cheddar cheese beats them all when it comes to cheese toppings with Swiss cheese coming in second, before American.”
It’s not just restaurants that are embracing Big Data analytics. The entire food industry is coming to appreciate the insights that can be gleaned from good analysis. “The food industry is one of the largest and most vital industries in the world,” asserts Ashish Thusoo Qubole. “It encompasses everything from producers and shipping companies, to grocers and restaurants. Everyone needs food for survival, and most of us thoroughly enjoy [eating]. 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.” [“How Big Data is Revolutionizing the Food Industry,” Wired Innovation Insights, 14 February 2014] Concerning his last point — using Big Data to create new recipes — Qubole notes that “IBM researchers have … jumped into food industry analytics by creating a computer program that generates original recipes.” Are those recipes any good? Mark Wilson thinks they are. “IBM sent me a bottle of BBQ sauce designed by Watson,” he writes, “so I ate it,” [“I Tasted BBQ Sauce Made By IBM’s Watson, And Loved It,” Fast Company, 23 May 2014] The ingredients that Watson blended to create its BBQ sauce might surprise you. They surprised Wilson. He explains:
“When I unwrapped the brightly colored box and found the bottle inside, I immediately flipped to the back label. Most BBQ sauces start with ingredients like vinegar, tomatoes, or even water, but IBM’s stands out from the get go. Ingredient one: White wine. Ingredient two: Butternut squash. The list contains more Eastern influences, such as rice vinegar, dates, cilantro, tamarind (a sour fruit you may know best from Pad Thai), cardamom (a floral seed integral to South Asian cuisine) and turmeric (the yellow powder that stained the skull-laden sets of True Detective) alongside American BBQ sauce mainstays molasses, garlic, and mustard. I pour a bit of the bottle onto a plate of roasted tofu and broccoli — even a pork lover has gotta watch his cholesterol — and tentatively took a bite. Watson’s golden sauce may have the pulpy consistency of baby food, but it packs a surprising amount of unique flavor. … I test it again and again. Finally I just slather my plate in the stuff. It’s delicious.”
You don’t have to be part of the food industry to put Big Data analytics to work for you. McCormick and Company worked with my firm, Enterra Solutions®, to create a personalized way for Big Data to increase your eating enjoyment. The program is called FlavorPrint.
You can sign up to get our own FlavorPrint by clicking on this link. As the website states, “Because flavor is at the heart of every meal, your FlavorPrint recommendations are powered by the flavors you love. The more you share, the smarter your recommendations become. So you can look less, cook more.” Put Big Data to work for you so that you can start enjoying some big flavors.
