Structure
Standard, documented data structures before dashboards. Validation at the point of entry, so data is clean before anyone analyses it.
Connect
Surveys, field records and platform data linked into a single pipeline, with sampling and definitions that are written down and reproducible.
Decide
Findings with clear implications and honest limits: contribution, not attribution, and early signals reported as early signals.
- MEL frameworks and programme design
Problem analysis and theory of change as the starting point, so indicators measure what the programme actually expects to change.
- MIS and data platforms
Management information systems built on standard, documented structures, with validation at the point of entry so data is clean before anyone analyses it.
- Survey design and sampling
Instruments and samples that hold up to scrutiny, documented well enough to be reproduced.
- Evaluation and research
Process and outcome evaluation with equity designed in and honest limits set in advance.
- Dashboards and analytics
Dashboards connected to the source system, with a written definition for every measure, so teams can check progress without waiting for a report.
- Data quality and funder reporting
Data quality built into the workflow, and reporting that stays honest under pressure.
- Data protection and governance
Standards for people whose data is collected, and for the organizations that hold it.
- Capacity building
Training by doing, so the in-country team can run and extend the work.
Selected work
South Africa
A management information system the programme team can run and extend
An ActivityInfo MIS, defensible sampling and live Power BI indicators, plus an AI-assisted field-visit advisory the agronomy team reviews before acting.
Read the case →India
Evaluating a WhatsApp advisory pilot
A bilingual mixed-methods evaluation that reframed a reach gap as a fixable registration problem among the most disadvantaged farmers.
Read the case →Cambodia · Philippines
Measuring a hidden crime
Externally reviewed studies using time-space sampling, from the earlier career that built the practice’s foundations.
Read the case →About
Led by Dave Shaw, Principal Consultant
A senior MEL and data systems leader. Data and learning leadership in agricultural development since 2020, and justice research and data systems before that, from 2008.
Career and background →Platforms
- ActivityInfo
- Power BI
- Tableau
- KoboToolbox / ODK
- Salesforce
- Python
- R