Advanced data analytics for program design for Fairfood and Trabocca

Description of the project:
Fairfood and Trabocca faced the challenge of designing interventions for reducing the living income gap of coffee farmers in two supply chains in Guji, Ethiopia. To address this, they commissioned Akvo for a detailed analysis based on available data, to understand how different groups of farmers relate to the gaps and what type of interventions are required to increase the income of different farmer groups.

Akvo's support was crucial in this regard, as it combined advanced clustering techniques with relevant domain expert knowledge to identify relevant farmer groups. The analysis identified three groups with large differences in income and coffee production and modelled how several interventions may lead to increased income. Akvo's team shared an overview of interventions that have a high chance of leading to increased income for the farmer groups. This helped Fairfood and Trabocca to have data-informed discussions with local partners and decide upon the interventions that will be part of the next phase of their project.

Read more about our approach to using clustering techniques here.