Irrespective of the location across the globe, you’ve been a part of the food and beverage industry, often as a consumer. As we’re all aware, the food and beverage industry is divided into multiple sub-sections, ranging from—fine dining to fast food. First, let’s talk about the latter.
Though often criticized for its nutritional value, fast food is here to stay. The increasing prevalence of fast-food restaurants is offering a greater number of people with affordable and varied meal options, as well as treats, beverages, baked goods, and more. The fast-paced nature of service and sizeable menus of these restaurants requires them to run smoothly and efficiently in order to keep customers happy and profits rolling in, a task that can seem difficult to anyone who has been in a crowded fast-food restaurant trying to get a chicken nugget meal at 2 am.
Luckily, big data and food and beverage data analysis are here to save the day. Using data analytics, every French fry, late-night chicken nugget, and ice cream sundae sold generates data for fast-food chains to analyze and act on, improving quality across the board.
Here are a few big data analytics in food industry that changes the food and beverage business practices to make better informed decisions:
Test New Products
Fast food chains can use data analytics to evaluate the financial impact and popularity of new products—including food items and in-restaurant technologies—before they implement them. Using food and beverage analytics to look at how customers interact with drive-through menus, for example, can give chains insights as to how they will react to certain technologies and changes. They can also utilize publicly available data for further knowledge of customer preferences and habits. Additionally, chains can conduct surveys that will allow customers to give them direct feedback about how they would respond to a new product or in-store attraction or service.
As more and more fast-food restaurants begin to offer delivery, they can use analytics to increase the speed and quality of service. They can also derive insights from the data collected from delivery orders and get a better picture of where their customers live and what they are willing to spend money on having delivered. Analytics and big data can also improve in-store operations—for example, chains could analyze data on wait times to improve service and decrease the number of time customers spend standing in line to order and receive their food or could use findings from food and beverage data analysis and food and beverage industry predictive analytics to alter staffing schedules in accordance with the busiest days and times an individual restaurant experiences.
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Cater More Effectively to Customers
Analysis of data about what food products customers prefer can help fast food chains to optimize their menus and increase sales. The use of food and beverage analysis for fast food menus lets chains know what the most popular or most frequently purchased menu items are, as well as which largely unpopular items they can cut to save costs without much outcry from customers. It can also tell them what changes they can make to their menu to expand their customer base—data about the prevalence of food allergies, for example, can help chains decide what ingredients to alter or omit so that a larger number of people can safely access their products.
While we’ve glossed over the industry benefits for customers, let’s look at the benefits for the organizations themselves. The food industry across the world is facing an interesting challenge. The world population is constantly on the rise whereas agricultural land is on a steep decline due to urbanization. To tackle such problems, key players in the food industry are resorting to vertical farming, genetic engineering, and most importantly big data. The explosion of data in the field of agriculture and food processing regarding seed type, soil type, climate, and other agri-supply chain data can help drive decision making, which, in turn, can transform the value chain of the food industry. Here’s a look at how big data can bring about a revolution in the food industry.
The advent of GPS and GNSS technology has enabled precise location tracking of field maps to measure variables such as crop yield, terrain topography, organic matter content, and moisture levels. Such data helps the farmers in effective water management, waste minimization, crop yield increment, and minimizing environmental impact. The data captured from thousands of tractors on farms across the world can then be collected and analyzed in real-time.
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Accurate Information and Forecasts
The food industry depends on accurate forecasts and right information to maximize crop yield. Integrating information relating to soil, weather, and market prices with granular data can provide inputs to optimize the agricultural input factors. Additionally, optimizing the agricultural input factors increases the crop yield, optimizes resource usage, and lowers cost.
Food Safety and Traceability
Big data is set to change the landscape of the food industry by enhancing food safety and traceability. Big data along with IoT proactively monitors the condition of food right from the farm to fork and sends out an alert when discrepancies are found. As a result, consumers are always assured of the food quality and food wastages are minimized.
The interconnectedness of various devices and sensors is opening up a huge potential in the food safety market. These networks of sensors can collect data from factories, vehicles, homes, hospitals, shops, and supply chains across the world. Consequently, businesses are getting aboard on the trend of using IoT and big data to improve operational efficiency and food safety. They are now able to get access and notification to real-time data relating to storage conditions, temperature, and hygiene of food products.
IoT and big data are helping players in the food safety market to enhance traceability from farm to fork through a series of interconnected devices and centralized networks. In this article, we bring o you some evidence of IoT and big data revolutionizing the food safety market landscape.
Companies have evolved from using barcodes and RFID manually to incorporating it within the IoT. This interconnectivity facilitates the food traceability from their point of origin to subsequent follow-up destinations across each level of the supply chain until the grocery store. Companies are using advanced sensors to track and identify food dust particles, temperature, humidity, and contamination across the distribution channel. This enables them to determine where the contamination took place and take action to mitigate the situation.
Food Safety Efficiency
IoT is considered a breakthrough in the food safety market with its ability to closely monitor food safety data points such as temperature and humidity. These sensors can automatically send out alerts to a central network notifying the user to take action. The technological advancement has progressed to such levels that with the help of big data it is possible to analyze the genome of bacteria within the food and detect anomalies in food samples with harmful bacteria.
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Food Safety Through Multiple Data Sources
Big data takes the food safety game to the next level by gathering data across other verticals apart from just temperature and humidity. For instance, regulatory inspection programs are taking advantage of publicly available information such as food inspection reports, 311 service data, community and crime information, and weather data to run predictive models to identify restaurants that are likely to breach food safety regulations.
Big data has caught the attention of the IT industry – where every organization is striving to explore and implement big data; thus, adding value and driving profitability. Several analytics giants are investing in building a robust data processing power to leverage actionable insights from big data. With the help of big data, the past data can be combined with real-time information obtained through social media, point of sale terminals and other customer touchpoints to gain relevant and actionable insights. The benefits of big data can be leveraged by companies across industries such as retail and consumer packaged goods, food service, and telecommunication among others.
The foodservice industry is extremely fragmented and competitive with very low customer loyalty. Traditionally, food service companies have focused on reporting rather than analyzing the available data. The consumer trends and preferences constantly keep on changing; thereby, making big data analytics all the more essential and revolutionizing food industry practices.
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Role of Big Data Analytics for the Food and Beverage Industry
Big data helps in the analysis of both structured as well as unstructured data, which is gathered from various traditional and modern sources that can be used to gain valuable insights about consumer behavior, shopping trends, and identify market developments. Big data analytics offers a comprehensive industry view to food and beverage companies that can be leveraged to create a competitive advantage over the other players in the market.
Big data analytics helps companies in the food service industry to understand customer needs and preferences by obtaining real-time information about consumers, products, brands, and competitors. The food and beverage manufacturers can use these insights in new product development, product launch, reducing food wastage, and menu improvement based on customer responses.
Data generated by foodservice companies can offer valuable insights that can help create the best promotional offers to attract and retain customers. However, it isn’t a simple task considering the staggering volumes of data generated.
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Big data analytics can help food service companies to devise tailor-made marketing campaigns and promotional activities to target their customers better. The food and beverage companies can determine optimum offers and discounts, measure the performance of their campaigns, and make recommendations to customers, and leverage cross-selling and up-selling opportunities. Data and analytics enable the organization to undertake dynamic pricing based on geographic area and customer demographics, personalizing the communication message, building customer relationships; thereby, optimizing their return on investment.
The pivotal part of the foodservice industry is the supply chain, operations, and security. Big data integration enables companies to reduce waste, minimize supply chain costs, and improve the overall efficiency of the organization. Foodservice companies can achieve this by using barcodes, RFID tags, and sensors to track food and its journey to provide fresh food to the end-user and eliminate wastage.
Key Takeaways of Big Data Analytics in Food Industry:
- Analyzed new sources of data and made agile and better decisions to realize an increase in ROI by 34%
- Effectively gauged customer needs and created new products to meet the customer requirements
- Get timely insights into healthcare and uncover new growth opportunities
- Effectively manage patient records, health plans, and insurance information
- Provided diagnoses and treatment options within a very short time