My background spans both research execution and monitoring and evaluation (M&E) systems across complex social programs. I work across the full lifecycle of development interventions—from reviewing Theories of Change and setting up indicator tracking matrices to managing multi-round field evaluations, including baseline, midline, endline, and impact assessments. Over the past decade, my work has focused on programs in education, public health, social protection, youth employment, and livelihoods, pairing quantitative survey architectures with qualitative evaluation tools to give funding partners and program teams reliable evidence on both implementation progress and outcomes.
How I approach the work
Grounding measurement in program logic:Any meaningful M&E system has to reflect the program’s Theory of Change and Results Framework. I work backwards from intended outcomes to establish measurable, practical indicators, clear unit definitions, and realistic data collection routines. This ensures we track the entire delivery chain—from inputs and routine outputs to short- and medium-term outcomes—without overburdening field teams with redundant data requirements.
Rigorous study design and field execution:Evaluation design must fit the questions being asked, whether that requires an experimental/quasi-experimental approach with baseline-to-follow-up tracking or a non-experimental assessment. I build digital survey instruments and sampling protocols that maintain comparability across evaluation rounds. For qualitative components, I use structured thematic frameworks and codebooks so that context, unintended outcomes, and beneficiary perceptions explain the how and why behind the numbers.
Real-time monitoring and adaptive learning:Monitoring is not just a passive reporting requirement; it is a management tool. I set up daily validation pipelines and tracking routines during active field operations to catch data issues, flag implementation bottlenecks early, and help program managers make informed operational adjustments in real time.
Honest, evidence-based reporting:I treat evaluation reporting with analytical discipline. Attribution, contribution, and limitations must be clearly defined; correlation should never be dressed up as causation unless the evaluation design supports it. Whether tracking indicator progress against donor targets or reporting on outcome shifts, my goal is to deliver clean, auditable evidence that program managers, donors, and stakeholders can defend under scrutiny.
What this looks like in practice
My hands-on experience includes developing evaluation protocols, designing multi-stage sampling plans, and coordinating large-scale data collection for both routine monitoring and formal impact evaluations. I combine formal training in impact evaluation methodologies and advanced survey programming with hands-on tool development across platforms like SurveyCTO, ODK, and Stata, alongside qualitative synthesis in ATLAS.ti. Across every engagement, I focus on building transparent data trails and robust indicator frameworks that support accountability and learning
Relevant areas of work
- Monitoring & Evaluation (M&E) System Design & Results Frameworks
- Theory of Change (ToC) Alignment & Indicator Development
- Quantitative & Qualitative Evaluation Designs (Experimental, Quasi-experimental, Mixed Methods)
- Multi-Stage Sampling Design & Weight Adjustments
- Baseline, Midline, Endline & Post-Event Coverage Surveys (PECS)
- Automated Quality Control, Real-Time Monitoring & High-Frequency Checks
- Qualitative Thematic Synthesis & Codebook Development (ATLAS.ti, NVivo)
- Outcome Tracking, Reproducible Data Pipelines & Evaluation Reporting