Finding where an agricultural programme needed to adapt.
Assessing progress in an agricultural value chain programme in Nigeria to guide adjustments during implementation.
Explore the findingsStudy at a glance
At the halfway point, what needed to change?
A donor-funded agricultural value chain programme was implemented across selected states in Nigeria to improve smallholder farmer productivity, market access, and household income. Midway through implementation, the client engaged SurveySphere Africa to conduct an independent midline evaluation to assess progress, identify implementation gaps, and inform adaptive programme management.
Testing progress and identifying course corrections
Measure progress against programme outputs and outcome indicators.
Assess changes in agricultural practices, productivity, and income levels.
Evaluate the effectiveness of training, extension services, and market linkages.
Identify operational challenges and opportunities for course correction.
Learning from farmers and the systems around them
Surveys with 2,000 farmers were combined with group discussions and interviews across programme delivery, extension services and markets.
Structured household surveys using CAPI (n = 2,000 farmers)
FGDs with farmer groups
KIIs with programme staff, extension agents, and market actors
results-based monitoring framework
OECD-DAC criteria focusing on effectiveness, relevance, and efficiency
Progress was visible, but it was not even across regions.
Improved adoption of climate-smart and improved agricultural practices among participating farmers.
Positive trends in yield and income compared to baseline levels.
Identified regional disparities in programme performance linked to extension coverage and market access.
Evidence for adjustments while delivery continued.
The midline evaluation provided actionable recommendations that informed programme adjustments, strengthened implementation strategies, and improved alignment with intended outcomes. Findings supported donor reporting requirements and enhanced learning for future scale-up.
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