Is data-driven farming the future of ACP agriculture? The short answer is it depends…
It may well be, but different areas of agriculture are benefiting in very different ways.
At government level – policy makers
Management of the agricultural situation in a country definitely is data-driven, with the opportunities from remote sensing for mapping and better weather prediction leading to a fuller understanding of threats.
At business level – agribusinesses
Throughout the value chain the exchange of price data has improved and more systems to track suppliers have clearly changed the opportunities for agriculture.
For the smallholder farmer
Data-driven systems are being used by Women in Business Development Inc. (WIBDI), in the Pacific, to manage the supply from smallholder organic growers to hotels and restaurants. Markets that were difficult to reach because of the difficulty of ensuring a stable supply. Through the use of data-driven systems the logistics of delivery, and the choice of crops to grow to supply the market, can be managed.
But data-driven doesn’t mean that the farmer will always be using the technology that collects, analyses or processes the data. There are often many steps between the raw data and the farm, with the farmer receiving advice derived from data through radio or word of mouth, not always through high technology.
Across the ACP farming is changing to take advantage of the range of data available. The improvement of weather forecasts has helped with answering when to plant and when to harvest, and communication of price information has informed the choice on what to plant for the best financial return. The global availability of mobile phones, satellites, drones, sensors and cloud computing have changed the range of data available and its application.
Open satellite data can be used to determine when to irrigate and has made fourfold increases in yields in trials in the Gezira in Sudan. In this case, individual farmers were reached through a standard mobile phone by SMS with simple instructions on when to irrigate. This proof of concept, however, requires the substantial processing power of an agency to interpret the satellite images.
Opening access to data from governments and companies through initiatives, such as Global Open Data for Agriculture and Nutrition (GODAN), can improve agriculture by providing more analysis and services to be developed using that data. These services can be brought together in one package, as in the Market-led, User-owned ICT4Ag-enabled Information Service (MUIIS) launched in March in Uganda.
A data-driven agriculture approach has shown that efficiencies can be gained in terms of yields and income, but the same data can be used to reduce environmental impacts and encourage cooperative working. As with all interventions in agriculture there are potential pitfalls.
As the opportunities to collect data have grown with technology, the ability to harness this data and analyse it is still in the hands of the larger organisations. It is important that farmers know how their data can potentially be used before agreeing to share. A consideration of the rights which a farmer has as to how their data is used ensures that they are not exploited by the larger companies.
There is also a danger that data capture and analysis can have gender biases if data is not disaggregated by gender, or women are not involved in collection or analysis.
So data-driven agriculture is happening on the ground in ACP countries, through private enterprise and government assistance, and the opportunities must be taken with consideration for the control that the farmer keeps over their own data to ensure they are not exploited.