Food & Beverage

Advanced analytics for better decision making

About the industry

There are several subsections of the Food and Beverage Industry, including food manufacturing, food and beverage stores, and accommodation and food services. The Bureau of Labor Statistics gives excellent summaries of each subsection, described below. 

Food Manufacturing

“Industries in the Food Manufacturing subsector transform livestock and agricultural products into products for intermediate or final consumption. The industry groups are distinguished by the raw materials (generally of animal or vegetable origin) processed into food products. The food products manufactured in these establishments are typically sold to wholesalers or retailers for distribution to consumers, but establishments primarily engaged in retailing bakery and candy products made on the premises not for immediate consumption are included.”

Food and Beverage Stores

“Industries in the Food and Beverage Stores subsector usually retail food and beverages merchandise from fixed point-of-sale locations. Establishments in this subsector have special equipment (e.g., freezers, refrigerated display cases, refrigerators) for displaying food and beverage goods. They have staff trained in the processing of food products to guarantee the proper storage and sanitary conditions required by regulatory authority.” 

Accommodation and Food Services

“The Accommodation and Food Services sector comprises establishments providing customers with lodging and/or preparing meals, snacks, and beverages for immediate consumption. The sector includes both accommodation and food services establishments because the two activities are often combined at the same establishment.”

Analytics in the industry

With its fast paced, competitive, and changing environment, now is the time for food and beverage companies to embrace big data, integrate analytics, and optimize decisions. KPMG details the importance and benefits of integrating BI in the industry in the Food, Drink, and Consumer Goods Industry Outlook Survey. “By harnessing big data . . . Food and beverage companies are capturing granular customer insight and great scale and speed in order to increase the relevance and value of their product portfolios, assess opportunities, enhance innovation, and speed time to market. Modern big data platforms are becoming more commonplace in the industry. These powerful tools can handle the analytical workload of huge amounts of complex and fast-moving data. But the oftentimes overwhelming amount of data available to collect, organize, mine, analyze, and distribute only leads to better insights and empowers decision making when organizations develop a thoughtful approach to data analysis and information management. Before investing in big data technology, food and beverage business and IT leaders need to align all stakeholders on its intended business value and develop quantifiable metrics around each priority business initiative. To realize the promised impact of their investment, they also need to develop a repeatable and automated process for data acquisition integration, and consumption and “operationalize” big data technologies in the business by transforming governance policies and addressing talent gaps. Food and beverage organizations that turn customer data into actionable intelligence can improve sales and customer retention and achieve lasting competitive advantage.”

How do we serve your industry?

Competitive Analytics advises and develops analytical workflows for successful companies within the food and beverage industry, such as Brown Foreman. Due to the fierce competition among players in the F&B Industry, Competitive Analytics works with companies to integrate both internal big data with external big data in order to drive powerful pricing and demand forecasting platforms. Other strategic analytical initiatives include customer insight, brand management, real-time market and operational intelligence, improving and optimizing supply chain processes, price optimization, product research and segmentation analysis, market expansion strategy, predictive analytics related to consumer demand, cost minimization, and risk minimization.