Analysis

Feed the world with big data

23rd June 2015
Nat Bowers
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Big data can be the most flexible tool for increasing the efficiency of food production through precision agriculture: a quantified approach to cultivation that uses sensing, input modulation and data analytics to enhance the efficiency of agriculture. Using it correctly will be essential to feeding the world’s growing population while also improving the environment, according to Lux Research.

Today, farmers struggle to find value in big data - tech developers need to focus on meeting strategic and tactical goals, as well as identifying use and business cases to lay the groundwork for adoption and growth.

“There’s no dearth of information or computing power; today’s challenge is integrating the deluge of data in a way that farmers buy into,” said Mark Bünger, Director, Lux Research and one of the lead authors of the Big Data in Precision Agriculture report. “While many farmers are still reluctant despite increasing availability of information and technology, there are clear ways to use big data in agriculture now."

Lux Research analysts assessed the various ways in which big data can help precision agriculture and their economic viability. They found that big data strategies in agriculture must start with overall farm-to-fork economics, focusing on data-driven tactical goals like increasing the profitability of crops and strategic goals like minimising the environmental impact of agriculture while ensuring food security.

Based on an analysis of 120 use cases for big data in agriculture, Lux Research identified five categories: reduce input and environmental impact while maintaining output; manage and maintain machinery; finance and administration; obtain best possible price at market; and comply with regulations.

For big data in agriculture, even the most apparently beneficial use case needs a business case. The payback should be based on measurable increases in revenue or reductions in cost, complemented by soft benefits like improved customer satisfaction or competitive dynamics.

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