Curated Collection
Frameworks, templates, and guides from leading M&E organizations, donors, and evaluation experts.
Comprehensive template for documenting baseline study findings, methodology, and recommendations. Covers executive summary, sampling approach, data quality procedures, and disaggregated results tables. Designed to meet donor reporting standards and establish a clear benchmark for endline comparison.
Structured format for organizing outcomes, indicators, and data collection plans across the results chain. Includes sections for output, outcome, and impact indicators with linked data sources and reporting frequencies. Pre-formatted to align with USAID, UN, and bilateral donor requirements.
Plan and schedule data collection activities throughout the project, linking each activity to specific indicators and responsible staff. Color-coded by data collection method (survey, focus group, key informant interview, observation). Adaptable for annual, quarterly, or rolling data collection cycles.
Track indicator progress against targets over time with automatic variance calculations. Supports disaggregation by sex, age, geography, and other custom categories. Includes a dashboard summary tab showing overall achievement rates across the results framework.
Standard logical framework matrix for project design, linking objectives, outcomes, outputs, and activities with corresponding indicators, means of verification, and assumptions. Pre-structured to meet DFAT, EU, and bilateral donor formatting requirements. Includes a companion narrative tab for Theory of Change documentation.
Plan and track M&E costs across project lifecycle phases, from design through final evaluation. Includes line-item categories for data collection, staffing, capacity building, and reporting. Built-in formulas calculate M&E as a percentage of total program budget.
Standard operating procedures for M&E systems, covering data collection protocols, quality assurance steps, data management workflows, and reporting cycles. Includes role-specific responsibilities, escalation procedures, and version control guidance. Designed to be adapted for both large and small program teams.
Ensure data privacy compliance before sharing datasets externally. Covers identification and removal of direct identifiers (names, IDs), quasi-identifiers (location, age, occupation), and sensitive categorical variables. Includes sign-off fields for data manager and program lead.
Methods for selecting representative samples for data collection, including simple random, stratified, cluster, and purposive approaches. Explains sample size determination with worked examples and links to standard power calculation assumptions. Covers common pitfalls such as design effect, non-response bias, and population list quality.
Best practices for questionnaire design, pre-testing, and field implementation, covering question types, skip logic, and response scale selection. Includes guidance on reducing interviewer bias, managing translation, and ensuring cultural appropriateness. Applicable to household surveys, KAP studies, and program participant assessments.
A curated collection of high-quality M&E materials, ready to download and use.
Frameworks, templates, and guides from leading M&E organizations, donors, and evaluation experts.
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