We don’t just track outputs; we track transformation. Our Monitoring & Evaluation practice brings the rigour of applied anthropology to the discipline of M&E — ensuring every project is not only accountable to funders, but honest with the communities it serves. Data, for us, is not a report card. It is a conversation that tells a project when to hold its course and when to change it.
Our Monitoring & Evaluation Expertise:
- Theory of Change & Indicator Design: Co-constructing logical frameworks, results chains, and indicators that are grounded in local realities, not lifted from a template built for somewhere else.
- Baseline & Endline Studies: Establishing rigorous starting points and measuring genuine change over time, using methods calibrated to the context rather than convenience.
- Mixed-Methods Data Collection: Pairing structured surveys and administrative data with ethnographic interviews, participant observation, and oral histories to capture what numbers alone miss.
- Participatory & Community-Led Evaluation: Positioning residents as co-evaluators rather than research subjects, so findings are owned — and trusted — by the people they describe.
- Real-Time Learning Systems: Building dashboards and feedback loops that surface course corrections while a project is still underway, not after the funding cycle has closed.
- Impact & Contribution Analysis: Moving beyond activity counts to assess attribution, unintended consequences, and the counterfactual — what would have happened anyway.
- Donor & Institutional Reporting: Translating field-level complexity into clear, evidence-backed reports for funders, government bodies, and academic partners, without flattening the nuance that got us there.
- Ethics, Consent & Data Safeguarding: Embedding informed consent, data protection, and safeguarding protocols throughout every stage of data collection — particularly with vulnerable or marginalised populations.
The Outcome: Evaluation that communities recognize as accurate, funders trust as rigorous, and teams can actually use to adapt course — not a report that gets filed away, but a system that keeps a project learning for as long as it runs.