Big Data in Food Industry

1. 1.3 billion tones of food is wasted annually. By using big data analytics to closely monitor inventory levels, it is possible to reduce food wastage without constantly ending up with bare shelves.

2. Food industry impacts the whole world. Everyone consumes food, and a majority of people are employed in some portion of the food industry, whether at the food manufacturing, in a supermarket, or in some part of the food chain. In a market that affects the majority of population, any innovation or improvement in efficiency always has a far-reaching effect. And with the rapid growth and expansion of big data, companies and researchers in the food industry are finding new ways of improving operations from end to end of the food supply chain.

3. Big data analytics can provide valuable analytics insights on processing and transportation of the food manufacturing. Big data also helps in determining the best transportation method and helps in optimizing routes.

4. Big data analytics can help food industry players to analyze data regarding food safety. Analyzing data can also help in faster recalls and driving automation thus, saving a significant amount of money.

5. On-time Delivery - Food delivery can be highly optimized and timed using various big data analysis tools and techniques. While this comes more under the role of big data in logistics, there are many food retailers who specialize in food delivery and not to forget the number of restaurants that provide home delivery options. Big data can collect data from various sources like road traffic, weather, temperature, route etc and provide a proper estimate for the time taken to deliver goods. Moreover, big data analysis can also predict the impact of all the above factors on food quality. Thus data analysis helps ensure that you don’t waste your resources in transporting stale products and deliver perishable food items in good quality.

6. Sentiment analysis is the monitoring of customer emotions over social media networks. Using techniques like natural language processing, data analysis tools go through the text and categorize it into positive, negative or neutral. This technique of big data analysis can be used by food companies to analyze their customer emotions on a scale. Any negative review can be analyzed at scale and preventive actions can be taken to prevent the spread of negative word.

7. Better Quality - The consumer always expects the same taste in food at the places they love. Though it sounds easy to maintain the same taste, it is a very challenging task. The taste of food not only depends upon the proper measurement of ingredients but also on their quality, storage and season. Big data analysis can analyze such changes and predict the impact of each on the food quality and taste. Data analysis can also analyze the impact of factors like storage and transportation on quality of packaged foods. The insights from such analysis can be used to understand pain points and suggest measures for improvement.