As spring arrives, farmers around the world are making decisions about what crops to plant and how to manage them. In the U. S., farmers typically have big data to help make these decisions. These data have a clear upside. They make farms more productive. In the U.S., the past five years have seen a series of good harvests for both com and soybean. A big part is generated by effectively using data to produce more food from the same amount of land, seed and fertilizer.
In the poorer parts of the world, however, the picture is much different. Many farmers are guided only by their history with the land and their community's traditions. Their skills and knowledge are impressive, but they suffer from a poverty of data. They rely on technical advisors for advice from governments and academic centers who often have very little knowledge of the local area. For seeds and fertilizers and other materials used in the field, they rely on companies that lack data on how their products will perform in the local conditions.
About 10 years ago, East African officials and their development partners started to explore why so few smallholder dairy farmers made profits from growing demand from urban consumers. Surveys of farmers in the region suggested poor access to veterinary(禽畜的) care and breeding assistance. An effort to provide these services has helped farmers get more milk.
Data would matter little if farming was easy and the paths to productivity were obvious. But in reality, agriculture is a complex mix of many factors, including climate, biology, chemistry, physics, economics and culture—all of which vary from region to region. In this situation, good data is necessary.
