User-centred design of a digital advisory service: enhancing public agricultural extension for sustainable intensification in Tanzania

Sustainable intensification (SI) is promoted as a rural development paradigm for sub-Saharan Africa. Achieving SI requires smallholder farmers to have access to information that is context-specific, increases their decision-making capacities, and adapts to changing environments. Current extension services often struggle to address these needs. New mobile phone-based services can help. In order to enhance the public extension service in Tanzania, we created a digital service that addresses smallholder farmers’ different information needs for implementing SI. Using a co-design methodology – User-Centered Design – we elicited feedback from farmers and extension agents in Tanzania to create a new digital information service, called Ushauri. This automated hotline gives farmers access to a set of pre-recorded messages. Additionally, farmers can ask questions in a mailbox. Extension agents then listen to these questions through an online platform, where they record and send replies via automated push-calls. A test with 97 farmers in Tanzania showed that farmers actively engaged with the service to access agricultural advice. Extension agents were able to answer questions with reduced workload compared to conventional communication channels. This study illustrates how User-Centered Design can be used to develop information services for complex and resource-restricted smallholder farming contexts

Household-specific targeting of agricultural advice via mobile phones: Feasibility of a minimum data approach for smallholder context

In recent years, agricultural extension services in developing countries have increasingly introduced modern information and communication technologies (ICT) to deliver advice. But to realize efficiency gains, digital applications may need to address heterogeneous information needs by targeting agricultural advisory contents in a household-specific way. We explore the feasibility of an automated advisory service that collects household data from farmers, for example through the keypads of conventional mobile phones, and uses this data to prioritize agricultural advisory messages accordingly. To reduce attrition, such a system must avoid lengthy inquiry. Therefore, our objective was to identify a viable trade-off between low data requirements and useful household-specific prioritizations of advisory messages. At three sites in Ethiopia, Kenya, and Tanzania in-dependently, we collected experimental preference rankings from smallholder farmers for receiving information about different agricultural and livelihood practices. At each site, we identified socio-economic household variables that improved model-based predictions of individual farmers’information preferences. We used the models to predict household-specific rankings of information options based on 2–4 variables, requiring the farmer to answer between 5 and 10 questions through an ICT interface. These predicted rankings could inform household-specific prioritizations of advisory messages in a digital agro-advisory application. Household-specific “top 3” options suggested by the models were better-fit to farmers’preferences than a random selection of 3 options by 48–68%, on average. The analysis shows that relatively limited data inputs from farmers, in a simple format, can be used to increase the client-orientation of ICT-mediated agricultural extension. This suggests that household-specific prioritization of agricultural advisory messages through digital two-way communication is feasible. In future digital agricultural advisory applications, collecting little data from farmers at each interaction may feed into learning algorithms that continuously improve the targeting of advice