Mind the gap: enabling data-smart agriculture for all
HAISHAN FU & MARTIEN VAN NIEUWKOOP
The datafication of agriculture promises better yields, reduced food loss and waste, and more farmers receiving fair pay for what they produce. This is potentially great news for the 570 million smallholder farmers worldwide whose production accounts for around a third of global food production. These smallholder farmers also comprise a large proportion of the world’s poor, who live on less than $2.15 a day. Agricultural development is, after all, one of the most pro-poor forms of growth, being two to four times more effective in raising incomes among the poorest compared to other sectors.
However, as we enter an age of data ubiquity, we must be careful not to view technology as a panacea for what ails the agricultural sector, especially for the world’s smallholder farmers. Indeed, without making the fundamental building blocks of development data – censuses, surveys, civil registration, and administrative systems – and the underlying technological infrastructure equally available to all, the digital revolution in agriculture is exacerbating the divide between the haves and have nots.
The (unequal) datafication of agriculture
Data have tremendous potential to transform how the world’s farmers put food onto the tables of over eight billion consumers. Apps can flip traditional economies of scale by substantially reducing farmers’ transaction costs, effectively lowering farm size constraints for farmers and ensuring their integration into new markets. Meanwhile, fintech is disrupting the traditional, collateral-based system of agricultural lending to smallholder farmers that has resulted in a financing gap of USD 150 billion. Remote satellite data and in-situ sensors are improving the accuracy and reducing the cost of monitoring crop growth and the quality of land or water. Whether it’s today’s soil quality, next season’s rainfall, or the long-term price stability of maize in Mozambique, digital technologies are facilitating the flow of data through the food system, shrinking information asymmetries and fashioning new markets along the way.
But this is not the whole picture.
Unequal access to the data infrastructure that underpins the digital revolution means that its benefits are not available where they’re most needed. Countries need information about their populations to appropriately target interventions and effectively allocate resources for policy reform. However, the countries with the largest poor, hungry, and marginalized populations face severe data deprivation that limits their ability to support their most vulnerable citizens.
This is especially relevant for moving the needle on the goal of zero hunger. Most low- and lower-middle-income countries cannot produce three indicators necessary for tracking Sustainable Development Goal 2 (SDG2) to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture.
That’s why we need to focus on both traditional sources of development data like household surveys, as well as new sources of data such as geospatial data, remote sensing technologies, mobile device data, and data from social media. In order to enable data-smart agriculture for all, we need to balance the foundation with the frontier by integrating these complementary data sources in innovative ways to achieve new insights.
Bad data = bad decisions
Good decisions are fundamental for agricultural growth. Yet, decisions can only be as good as the evidence that informs them. Each year, low- and lower-middle-income countries spend around 600 billion dollars in the agricultural sector, often without good evidence to inform those investments. Governments and businesses, including smallholder producers, are often shooting in the dark, making critical policy and investment decisions without the benefit of quality agricultural data.
The scarcity of high-quality, timely agricultural data makes it extremely difficult for policymakers to make sound decisions to drive their country’s economic growth and reduce poverty. This leads to suboptimal outcomes, causing losses in productivity, shortfalls in agricultural income and, ultimately, more hunger and poverty. Closing the agricultural data gap, and keeping it closed, is therefore a critical precondition for the evidence-based decision making and investments needed to foster agricultural development and achieve SDG2.
Closing the gap
The 50×2030 Initiative to Close the Agricultural Data Gap was developed to answer this need. 50×2030 is a 10-year, US$500 million program that aims to increase the capacity of 50 low- and lower-middle-income countries to produce, analyze, interpret, and apply data to decisions in the agricultural sector that support rural development and food security. It scales and builds upon the experiences of the Food and Agriculture Organization of the United Nations’ (FAO) Agricultural Integrated Survey (AGRISurvey) Programme and the World Bank’s Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) to help countries build robust national agricultural and rural statistical systems.
50×2030 supports countries to collect high-quality data that are sufficiently disaggregated to elucidate underlying trends and patterns, which is critical for monitoring inequality and targeting programs effectively. It strengthens country capacity to identify the data they need to increase and sustain evidence-based decision-making in agriculture for economic, human, and social development. In order to close the agricultural data gap, the Initiative pushes the frontier both by integrating new types of data sources as well as by making foundational data sources like household surveys more innovative through the incorporation of new technologies and methods. To achieve sustainability, the Initiative prioritizes data use by strengthening national data ecosystems – e.g., stakeholders, data assets, and the structures that govern them – through better skills, communications, policies, and practices.
The Initiative brings together the vision and resources of development agencies – the United States Agency for International Development, the Bill and Melinda Gates Foundation, Germany’s Federal Ministry of Economic Cooperation and Development, Australia’s Department of Foreign Affairs and Trade, and Italy’s Ministry of Foreign Affairs and International Cooperation – with the technical and operational capabilities of key multilateral implementers – FAO, the International Fund for Agricultural Development, and the World Bank – and the expertise of partner countries. A little over two thirds of the 50×30 financing comes from its partner countries, through World Bank IDA/IBRD financing resources, with the remaining financing contributed by donors and philanthropic organizations primarily through a multi-donor trust fund. In the future, donor financing could be channeled in a complementary way through the Global Data Facility – a World Bank-hosted umbrella trust fund specifically targeted to raise resources to fill the data gap in developing countries.
Ultimately, 50×2030 aims to ensure equity in agriculture’s newest revolution: data-smart agriculture. This means enabling all countries and all farmers to leverage the benefits of the digital revolution , bringing about a world where new technologies can be put to use to strengthen old tools: evidence-based policies and investments.