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20 resources
TemplateMethodology

Results Framework Template

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.

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TemplateMethodology

Baseline Report Template

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.

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MatrixAI for M&E

AI-Assisted Data Quality Tools Matrix

Compare AI-powered data cleaning software, custom ML models, and AI-assisted scripting libraries for M&E data quality verification.

|5 min read
MatrixAI for M&E

AI Integration for Donor Compliance Reporting Matrix

Compare four levels of AI integration for donor compliance reporting: from manual approaches to advanced automation. Make informed decisions on where to invest.

|6 min read
Reference CardMethodology

The Decision Test: 5 Questions for Every Indicator

Every indicator should pass the Decision Test before it earns a place in your monitoring plan. These 5 questions expose indicators that collect data no one will use.

|6 min read
ChecklistMethodology

Evaluation Terms of Reference Quality Checklist

Ensure your Terms of Reference will produce an evaluation that changes decisions, not one that gathers dust.

|5 min read
Reference CardMethodology

Evaluation Types Comparison Matrix

Compare five evaluation types at a glance: Formative, Summative, Developmental, Impact, and Process. Choose the right evaluation for your program stage and purpose.

|5 min read
GuideAI for M&E

AI-Assisted Indicator Development and SMART Validation

Reduce indicator development time from 3-4 hours to 1 hour per set using a structured AI-assisted workflow with consistent SMART validation.

|5 min read
GuideAI for M&E

Cleaning Messy Datasets for M&E Analysis

75% of M&E datasets have quality issues affecting analysis accuracy. Learn how to use OpenRefine and AI tools to clean survey data in 2-3 hours instead of 15-20.

|5 min read
GuideAI for M&E

Generating Survey Questions with AI

Use AI tools to accelerate survey development from weeks to days while maintaining quality through structured prompting and field expert validation.

|5 min read
GuideAI for M&E

PII Removal Before Sharing Data with AI

A practical checklist and workflow for identifying and removing personally identifiable information from M&E data before using AI tools for analysis.

|5 min read
GuideAI for M&E

Prompt Engineering for M&E Practitioners

Most M&E practitioners write vague prompts and get mediocre AI outputs. The 4Cs Framework (Clear, Complete, Contextual, Constrained) delivers 5-10x better results from the same tools.

|5 min read
TemplateMethodology

M&E SOP Template

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.

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TemplateMethodology

Logframe Template

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.

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GuideMethodology

Sampling Guide

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.

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GuideMethodology

Survey Design Guide

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.

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TemplateWorkflows

Indicator Tracking Table

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.

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TemplateMethodology

Data Collection Calendar

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.

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ChecklistTools

PII Removal Checklist

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.

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TemplateMethodology

M&E Budget Template

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.

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What You'll Find

A curated collection of high-quality M&E materials, ready to download and use.

Guides & Reference Cards

Practical guides and quick-reference materials written by M&E practitioners, not vendors.

Templates & Frameworks

Ready-to-use templates in Word and Excel formats, aligned with major donor requirements.

Checklists & Matrices

Free checklists and comparison matrices to support data quality, evaluation design, and AI adoption.

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