Case Studies
Detailed accounts of how data, research, and AI solutions have created measurable development impact.
Building Evidence-Based Governance in Galmudug State
Client: Galmudug Policy Insight Center (GPIC)
The Challenge
Galmudug State faced critical governance challenges including weak policy frameworks, limited institutional research capacity, and decisions being made without adequate data or evidence. Government ministries lacked structured mechanisms for policy analysis and research.
The Approach
Established the Galmudug Policy Insight Center (GPIC) as a dedicated policy research institution. Developed a comprehensive research agenda, trained government researchers, and created systematic processes for policy analysis, stakeholder consultation, and knowledge management.
The Solution
Designed and implemented an evidence-based policy framework connecting research findings to policy decisions. Built data collection systems, developed policy templates and standards, and established peer review processes to ensure policy quality.
📈 Key Results
- ✓15+ evidence-based policy briefs published
- ✓40+ government officials trained in policy research
- ✓Formal policy research unit established in 3 ministries
- ✓Improved policy consistency and coherence across sectors
- ✓International partnerships established for technical support
Tools & Technologies
Data-Driven Education Sector Planning
Client: Ministry of Education
The Challenge
The education ministry struggled with fragmented data across 20+ districts, manual reporting processes that took weeks, and insufficient information for evidence-based resource allocation. Decision-makers lacked real-time visibility into education sector performance.
The Approach
Conducted a comprehensive data audit across all district education offices. Designed a standardized data collection framework and deployed mobile data collection tools to field officers. Developed a centralized data management system with automated quality checks.
The Solution
Built an interactive Power BI dashboard connecting all district data sources, providing real-time visibility into key education indicators. Automated reporting workflows reduced manual work and created dashboards tailored for different user levels — from field officers to senior ministry officials.
📈 Key Results
- ✓Reporting time reduced from 3 weeks to 2 days
- ✓30+ education officials trained on dashboard
- ✓Resource allocation improved based on data insights
- ✓Out-of-school children identification improved by 45%
- ✓Teacher deployment optimization saved 15% of budget
Tools & Technologies
Multi-Sector Needs Assessment for Development Planning
Client: UN Agency & International NGO Consortium
The Challenge
A consortium of UN agencies and international NGOs required comprehensive, multi-sector needs assessment data to inform humanitarian programming and development planning in conflict-affected areas. Existing data was outdated, incomplete, and fragmented across organizations.
The Approach
Designed a multi-sector assessment framework covering food security, health, education, WASH, shelter, and protection. Developed standardized questionnaires, trained 50 enumerators, and implemented rigorous quality assurance processes for data collection and analysis.
The Solution
Deployed KoboToolbox for mobile data collection across 500+ communities. Conducted real-time data quality checks, cleaned and analyzed datasets in SPSS, and produced comprehensive sector-specific reports with interactive visualizations for each agency partner.
📈 Key Results
- ✓10,000+ households surveyed across 15 districts
- ✓Data quality rate exceeded 98%
- ✓Reports delivered 3 weeks ahead of deadline
- ✓Findings used by 8 agencies for program design
- ✓$5M+ in programs informed by assessment data
Tools & Technologies
AI-Powered Data Processing for Development Organizations
Client: Multiple Development Organizations
The Challenge
Development organizations faced bottlenecks in processing large volumes of qualitative data from field research. Manual coding of open-ended survey responses and interview transcripts was time-consuming, inconsistent, and prone to researcher bias.
The Approach
Analyzed existing data processing workflows to identify automation opportunities. Designed an AI-powered processing pipeline using NLP techniques adapted for local language content. Developed custom models for thematic coding and sentiment analysis.
The Solution
Built and deployed an AI pipeline that automatically processes, codes, and categorizes qualitative research data. Integrated with existing data collection workflows and produced structured outputs compatible with SPSS and Power BI for further analysis.
📈 Key Results
- ✓Qualitative coding time reduced by 80%
- ✓Consistency in thematic coding improved significantly
- ✓Processing capacity increased 10x
- ✓Cost savings of 60% on data processing
- ✓Adopted by 4 organizations for ongoing use
Tools & Technologies
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