Food Industry and Technology

Big data and data analytics are transforming the way the Food industry works. The way we grow, produce, process, distribute, and consume food is undergoing a digital revolution. Big data allows companies to unearth complex data patterns into easy to understand models which have a meaningful and result oriented impact on their business. For instance, it has the potential to uncover new correlations between diet and health, linking specific foods to health risks and diseases. The best thing about data analytics is that it can be done anywhere in the world. Even a small lab in Asia can study huge datasets and do predictive analysis of weather conditions and crop yield in a remote village in Africa. Isn't it fascinating? There are numerous such successful case studies where data is revolutionizing the food industry, and the best part is that this is just the start of the technology innovation.

Out of all the steps in the food cycle, farming is the most important, but has benefited the least from digitization and big data till now. In most parts of the world, and specially developing countries, farming is still done by century old methods and techniques. This is not helping in increasing the land productivity. As per several forecasts, the world population will grow to around 9 billion by 2050. Such a large population will require about 50% more food than the current production levels. So what can be done to meet these targets? Well, apart from all the modern day farming machinery and latest hardware, big data is one field, which can actually help the agriculture industry to dramatically increase the crop yield. A lot of data is being generated in the farming industry: data from sensors, irrigation data, historical data of the soil nutrients, weather condition, the seed yield, crop maturity time, pesticides used etc. When meticulously studied and analyzed, these datasets can provide unimaginable insight to farmers, which would help them make right decisions. The end result would be increased productivity, reduced costs, minimized losses, and much more. Historical weather data can alert farmers about potential disasters and they can plan the harvesting accordingly; soil and yield data can help farmers optimize use of pesticides. There are many proven cases where water usage has been minimized just by analyzing various data points coming from the field. As one can imagine, the possibilities of improvements and optimization of farming methods are endless with the use of big data, analytics, artificial intelligence (AI) and continuous learning.

Let's have a look at how restaurants are utilizing big data and data analytics to optimize their processes. Some people may feel that only recently restaurants have started utilizing the big data benefits, but that is not true. Pizza chains like Domino's and Papa Johns have been creating databases of their customers for a very long time. They know the location, contact details, and preferences of millions of people who have used their services. So what changed in recent years? Well, with the advances in mobile, cloud and computational power, data scientists and machine learning experts can create extremely complex algorithms and models based on big data which can produce unprecedented results. More and more restaurants are taking help of data analytics to optimize costs, reduce food wastage, learn consumer behavior, improve recipes, and so on. Customer analytics can help with targeted offers. So for instance once you know a family visits your outlet regularly, you can give them targeted discount offers when they book a table, or push a free parking coupon to their mobile as soon as they approach the restaurant. Analyzing sales and demand data also helps with optimizing menu prices to maximize sales volumes and profits.

Big data and analytics are playing a role in the entire food industry value chain – from processing, distribution to ordering. Deeper understanding of data and the intelligence gained from the analytics is helping optimize processes and create superior user experiences. Some manufacturers are taking this opportunity to create increased transparency with customers. Few brands have already started using smart labels on their products. Consumers can scan these smart labels and get details such as nutrients value, presence of any harmful chemicals, the origin of the product, the raw materials used, and much more.

Scientists and various startups are working hard to develop complex algorithms to get the best possible results from data analytics. For example, researchers are analyzing historical data of seeds and trying to create a super seed, which can yield crops in poor weather conditions. If successful, imagine the possible results - explosive food production and reduction in world hunger. Big data adoption is growing at a fast pace and it is time for the food industry to embrace it. The next few years are very exciting as companies will innovate and leverage the power of data and analytics. The result of all these efforts would be superior food quality, better dining out experience, safer and more nutritious food and increased income for farmers.