How to Understand the Needs of the Rural Poor on a Global Scale

Rural Household Multiple Indicator Survey

The days of top-down, one-size-fits-all "solutions" for poor rural farmers are gone. Scientists interested in development questions have known this for some time. They fan out across the globe, questionnaires in hand, to learn about the needs of coffee producers in Honduras, bean growers in Kenya, and rice farmers in Vietnam. This works well to tailor research-for-development projects to local circumstances. But researchers overlook one critical element: standardizing surveys so others could use the information they gathered.

A team of scientists at the CGIAR, a consortium of international research institutes, set out to change this. They pioneered and standardized a survey system and brought on dozens of colleagues to help deploy it across the rural tropics. We published our first analysis of our surveys in February in Scientific Data, an open-access journal from Nature for the description of scientifically valuable datasets.

In the paper, we describe the Rural Household Multiple Indicator Survey, or RHoMIS, and explain how to access and analyze data collected from 13,000-plus households from 21 countries. Adoption of the tool has been phenomenal. Between writing the paper and publishing it – about six months – RHoMIS  grew to include 31,000 households from 33 countries. Data from surveys are added almost daily.

Today, researchers, development agencies, governments and NGOs are using RHoMIS to effectively invest development money according to local needs. Simultaneously, data collectors are contributing to what we hope will become the largest, standardized open-access database of its kind.

Big data, meet smallholder

As an agricultural and environmental researcher who relies upon reams of data, standardization is revolutionizing the way my colleagues and I work with surveys. Instead of taking months to crunch numbers – to estimate the carbon footprint of a farm, compare the economic benefits of one crop versus another, analyze the role of gender in a given household, or quantify agricultural biodiversity of a given community, to name just a few – we get these numbers almost instantaneously. These analyses used to take months.

RHoMIS also allows us to stand back and map the multiple variables – more than 700 that we have divided into 40 groups – that affect the farmers’ bottom lines and wellbeing. While we can still make global analyses concerning access to credit, adaptation and mitigation to climate change, the role of women in households, and nutritional and food security needs, we can zoom in and analyze the effectiveness of specific actions. 

Numerous studies have already been published using RHoMIS, including research on  climate-smart agriculture in East Africa and Central America, changes over time in livelihoods and food security in Tanzania, identifying farmer innovators who have improved farm sustainability, using  mobile phone services for tailored agricultural advice in East Africa, and  food security research in Central America’s dry corridor. 

One of the things I’m most excited about is the use of this tool for citizen science, the direct involvement of volunteers in scientific research. Citizen science has been done primarily in ecological research, for example, by bird watchers who record their sightings in an app and contribute these data to science. For agriculture, we have recently shown that it is possible to engage farmers massively in testing different technology options, such as crop varieties or crop management practices. Usually, technologies are created in a laboratory or experimental setting and then tested only on a handful of farms, leading to very imprecise recommendations. By linking test results on thousands of farms to data about those farms, we can provide very precise recommendations.

These new data-driven tools are quickly finding practical applications. RHoMIS is already being used for development work. One example is Tree Aid, an NGO that plants valuable trees to help rural communities and uses the tool to evaluate its income-enhancing work in West Africa. One Acre Fund, another non-profit, is using RHoMIS to make credit decisions, and is piloting citizen science to test varieties of maize, cassava and potato with farmers in Rwanda.

A tool for the SDGs

For the United Nations’ Sustainable Development Goals (SDGs) to be successful, progress in one area should not be achieved at the expense of another area. Therefore, progress towards the SDG targets is tracked simultaneously by 232 unique indicators. Also, rural livelihoods are far too complex to distill into a single indicator of well-being. Improved food security and income are essential, but we cannot work to achieve these goals while ignoring the environment, gender or income distribution in households.

As the study’s lead author from the International Livestock Research Institute  Mark van Wijk says, RHoMIS allows us to gain a consistent level of detail over a wide range of topics, allowing us to understand the multiple social and economic interactions that are observable in a wide diversity of locations, projects, cultures or climate zones. For example, we found in East Africa that female control over income goes up when households have more types of crops or livestock, but tends to go down when households sell a larger proportion of their agricultural products on the market.

In summary, RHoMIS can make development-related actions more efficient, more effective, and quicker to deploy. Our goal is that in five years the RHoMIS-based dataset is the go-to place for information on smallholder farming. By then, it could be the biggest single database for research and development for rural farming households in the world.

Field Notes

The Chicago Council is pleased to present the blog series, "Breaking Ground," to explore how food systems innovation and agricultural research and development can empower farmers and feed the world. This post is part of a special subsection of this series, "Field Notes," which features voices from Feed the Future Innovation Labs and CGIAR centers.

Acknowledgments

Feed the Future Lab support

The research paper was made possible, in part, by the Feed the Future Innovations Lab, which is funded by the United States Agency for International Development. Among other initiatives, Feed the Future supports applied research to improve nutrition and agriculture in the countries where my colleagues and I work. We believe this tool will help us better tackle the global challenges of nutrition and rural livelihoods at local scales.

The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT)

The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) delivers research-based solutions that harness agricultural biodiversity and sustainably transform food systems to improve people's lives. Alliance solutions address the global crises of malnutrition, climate change, biodiversity loss, and environmental degradation. The Alliance is part of CGIAR, a global research partnership for a food-secure future.