​Our RHoMIS work has led to a unique harmonised database of quantitative information on smallholder livelihoods in low and middle income countries (now containing interviews of more than 28,000 households in 31 countries). We are now in full force analysing these data to identify pathways towards food security, and underpin strategic studies trying to identify the drivers of diverse diets and possible trade offs between agricultural production intensification and key welfare indicators like gender equity.

What is less known is that our RHoMIS research actually originated from work focusing on bringing together existing household survey data from a wide range of projects and using those data to identify common indicators of food security, and farm livelihood characteristics determining food security. 

​RHoMIS is being utilised in a nutrition study led by the International Livestock Research Institute (ILRI) and the Thai Nguyen University of Agriculture and Forestry (TNUAF). The study aims to compare diet diversity data collected for the immediate past with data collected from the same household over a 12 month recall period. ​

​I’ve worked with the RHoMIS survey for over a year now, built close to thirty applications, and worked with research teams in over twenty countries. Yet my trip to Uganda last week was my inaugural experience with applying the tool in situ. The trip gave me a first-hand experience of some of the challenges and nuances of local application of a survey.

Scientists and development practitioners around the world are working with smallholder farmers to transform their agricultural practices to better adapt to, and even mitigate, climate change. The international development community has prioritized two strategies in this regard - increasing the sale of crop and livestock products through increased market participation (commercialization) and increasing the number of crop and livestock species on-farm (diversification).

​However, little is known as to the gendered impacts of these changes and specifically, whether these strategies may intensify inequalities between men and women. 

Around the world, agricultural development organizations often struggle with surprisingly weak adoption of innovations that had previously been successful at other places. If all goes well, the smallholder farmers addressed by a development program readily adopt and adapt newly introduced practices, such as improved management of crops and livestock. Not so rarely, however, promising innovations do not fit with local culture, cause extra labor at times when the farmers are already extremely busy, or show other unexpected downsides in the new context.
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Avoiding locally unsuitable interventions and designing better agricultural development programs by working closely with the local community is possible, of course. But participatory research can take a long time, and results are sometimes biased towards the local opinion-leaders, who are not always the most successful farmers. Could there not be a simpler way to find out “what works” under specific local conditions?