Big Data Analytics and the Global Hunger Challenge

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In a world where as many as one-ninth (around 800 million) of the global population of over 7 billion go hungry each day, 33% of the food produced for human consumption is wasted every year.

As regards India, it is home to the largest undernourished and hungry population in the world: 15.2% of India’s population is undernourished and 194.6 million people go hungry every day, according to India FoodBanking Network.

Certainly not a healthy picture—but possibly not one that technology cannot help redress.

According to a new report on McKinsey.com, global food waste and loss cost a staggering $940 billion A YEAR, with a carbon footprint of more than 8% of global greenhouse-gas emissions and a blue-water footprint that is 3.6 times the annual consumption of the US.

Such a sorry state of global food chain can be set right with appropriate use of digital innovation, including big data analytics, among others.

In my view, there is opportunity not just for governments but also for large businesses that plug into the huge global food supply chain in one way or another: the opportunity to apply creative thinking led by digital tools to bring down wastage, optimize costs and put more food on the table of poor people.

The McKinsey report suggests that cutting postharvest losses in half would produce enough food to feed a billion more people.

This and other social and economic benefits can be achieved by using technology to improve areas such as climate forecasting, demand planning, and the management of end-of-life products, argues McKinsey. The report quotes examples of work being done by startups and others in this area. For instance, a French startup, Phenix, runs a web-based marketplace to connect supermarkets with end-of-life food stocks to NGOs and consumers who could use them. “The platform enables the supermarkets to save the costs of disposal, gives consumable products a second life, and alleviates some of the social and environmental burden of waste,” it says.

For emerging economies such as India, the report suggests that innovations like precision agriculture, supply-chain efficiencies and agriculture-focused payment systems can make a huge difference.

For one, precision agriculture—which uses big data analytics, aerial imagery, sensors, etc.—is used to observe, measure and analyze the needs of individual fields and crops rather than take a one-size-fits-all approach to farming in a region or cluster of fields.

Startups as well as big behemoths are participating in this huge opportunity (the market for agricultural robotics alone is forecast to rise from $1 billion in 2014 to up to $18 billion by 2020).

So, while the startup Blue River uses computer vision and robotics to determine the needs of individual plants, Big Blue (also known as IBM) has developed a highly precise weather-forecast technology, Deep Thunder, and an agriculture-specific cloud technology.

Needless to say, we will need a basket of technologies from multiple vendors to keep large amounts of food from being thrown away or going waste, to optimize the yield from agriculture, to eliminate or reduce transportation inefficiencies—and do anything and everything to bring down the number of the daily hungry.