Monitoring Programs & Policies

Agile Data Approaches & Innovations for Monitoring(ADAIM)

Agile Data Approaches and Innovations for Monitoring (ADAIM)

The Agile Data Approaches and Innovations for Monitoring project envisions to be the North Star for monitoring, learning, and evaluating in Foundations’s AgDev programs in India and Africa. Frequent, effective, and low-cost data snapshots provide the basis for immediate action during the life of the project rather than waiting for a midterm or final evaluation.

We envision for AgDev a future where MLE, based on consistent, standardized data, is undertaken regularly for understanding individual projects, and also for understanding a portfolio of projects as a whole. Comparability is possible and facilitates the ability for AgDev to compare and draw out learning from similar initiatives. By using common, universal metrics – whether it is climate adaptation, gender inclusion, or income generation – the data works across categories and geographies. It points to interesting differences, similarities, strengths, and opportunities to improve.

Timeline :

  • 2022-2026

Target Benfeciaries :

  • Small-scale farmers and producers

ADAIM Objective

To establish functional, scalable, agile data gathering and monitoring systems that deliver timely, credible, and actionable data to inform evidence-based decision making for Bill and Melinda Gates Foundation’s agricultural development sustainability investments

Micro Level Data Collection

Micro level data collection that tests different agile technologies and lean data systems to enhance demographic profiles, engage their opinions, and provide regular feedback to program managers and to beneficiaries.

Meso Level Research

Meso level research to better understand and monitor the factors such as governance, markets, or value chain dynamics that can affect outcomes and systemic change.

Agile Data Research

Agile Data research to study and validate new use cases, such as baselines, using agile approaches that collect data in a way that is inclusive, reliable, and repeatable, and can monitor factors such as cost-effectiveness, elements of risk and resilience, or internal validity, etc. in diverse situations.

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