Formulate Hypothesis: Problem Statement - AgriDatum

Objective

Develop a clear, evidence-based problem statement grounded in our interactions with farmers, NGOs, and agricultural stakeholders and use these insights to form a strong hypothesis that guides the direction of AgriDatum.

Building the Hypothesis

Based on Our Research, We Reviewed the Following:

• Ground Truth findings
• Community stories
• Observed behaviors
• Patterns across different farmer groups
• Insights from NGOs and extension workers

Key Insights that Inform Our Hypothesis

Insight 1: Farmers lack reliable and verifiable data records

Most smallholder farmers do not document their planting, harvest, or sales data. Even when they try, the records are inconsistent or lost, making it difficult for NGOs, buyers, and funders to trust the information.

Insight 2: Support programs struggle to target the right farmers

NGOs and cooperatives experience delays and errors when distributing aid because they rely on unverified, handwritten, or secondhand reports. This leads to mismatches, fraud cases, and wasted resources.

Insight 3: Communities desire simple, trustworthy tools that reflect their real work

Farmers want tools that are easy to use, available on mobile, and speak their language. They want something that makes their work visible, not something complicated that frustrates them.

Problem Statement

The Problem (Draft 1)

Many smallholder farmers do not have a simple and reliable way to record, verify, or share their farm data, leading to low trust between farmers, NGOs, buyers, and financial institutions. This results in reduced funding opportunities, wasted resources, and poor decision-making.

Target Audience:

1. Smallholder farmers
2. NGOs and agricultural support organizations
3. Cooperatives

Geographic Scope:

1. Rural communities in Nigeria (initial)
2. Expandable across East and West Africa

Scale:

1. Millions of farmers currently rely on informal documentation
2. High number of NGOs funding agricultural programs without verifiable data
3. Large community groups lacking reliable reporting tools

The Problem (Refined)

Smallholder farmers and agricultural support organizations lack a verified, transparent, and easy-to-use system for recording and validating farm activities. The absence of credible data causes mistrust, misallocation of resources, limited access to funding, and missed opportunities for growth.

Final Problem Statement

Smallholder farmers and NGOs struggle with unreliable, unverified agricultural data, resulting in mistrust, poor decision-making, and limited access to essential support. AgriDatum aims to solve this by providing a simple, transparent, blockchain-backed system for capturing and validating farm data.

Hypothesis Statement

We believe that smallholder farmers and NGOs face significant challenges in recording, validating, and trusting farm data because current methods are manual, inconsistent, and easily manipulated and if we provide a simple, AI-assisted, Cardano-backed platform to record and verify this data, then farmers will gain credibility, NGOs will distribute resources more effectively, which will result in greater transparency, reduced fraud, higher productivity, and stronger community resilience.

Assumptions to Test

Assumption 1: Farmers are willing to adopt a digital tool if it is simple and useful.

• How to test: Pilot onboarding with 20–50 farmers
• Risk if wrong: Low adoption and limited impact

Assumption 2: NGOs want verifiable, transparent data for decision-making.

• How to test: Interviews + dashboard prototype testing with NGO partners
• Risk if wrong: Limited NGO engagement and weak ecosystem growth

Assumption 3: Cardano-based data anchoring improves trust and reduces fraud.

• How to test: Compare verification times and fraud cases before and after use
• Risk if wrong: Identity or verification issues persist and need alternative validation

Success Criteria

Quantitative Metrics

1. 60%+ farmers complete onboarding in the first week
2. At least 200 data entries submitted in the pilot
3. 30% reduction in inconsistencies or duplicate reports
4. NGO verification requests processed within minutes

Qualitative Indicators

1. Farmers report feeling “seen,” “supported,” and “understood”
2. NGOs describe improvements in trust and transparency
3. Extension workers report easier field documentation

Constraints & Limitations

Known Constraints

1. Time: Hackathon timeline limits how much can be built in Phase 1
2. Resources: Small team, limited funding for field testing
3. Technical: Cardano integration complexity
4. Regulatory: Data privacy requirements for storing farmer information

Scope Boundaries (Out of Scope for MVP)

1. Full end-to-end marketplace integration
2. Large-scale national rollout
3. Hardware-based soil or irrigation sensors
4. Complex credit scoring (reserved for future phases)

Next Steps

Proceed to Define Opportunity to explore multiple solution approaches.