Primary vs Secondary DataQuick Reference
Primary data is collected firsthand for a specific purpose; secondary data is existing data repurposed for new analysis. Each has distinct trade-offs in cost, timeliness, and relevance.
The responsibility to be transparent, report, and respond to stakeholders about program performance and decisions.
An evaluation focused on assessing whether a program is meeting its obligations to stakeholders, including donors, beneficiaries, and regulatory bodies.
The systems, processes, and structures that enable organizations to answer to stakeholders, including communities, donors, and partners, for their performance, decisions, and use of resources.
What a program DOES with its inputs to produce outputs; the direct work or services delivered.
A management approach that uses continuous learning from monitoring and evaluation data to adjust program strategies and activities in response to changing evidence or context.
A structured, time-bound reflection process conducted immediately after a specific activity or milestone to capture what was planned, what happened, why the difference, and what should change.
Conditions outside program control that must hold true for the program to succeed as planned.
The distinction between proving a program directly caused outcomes (attribution) versus building a credible case that it contributed to outcomes alongside other factors (contribution).
An evaluation focused on assessing financial probity, internal controls, and compliance with financial regulations and procurement standards.
Audits examine financial and regulatory compliance; evaluations assess program effectiveness and impact.
Initial conditions data collected at the start of a project to establish a reference point for measuring change and setting indicator targets.
A structured approach to collecting initial condition data that directly informs project decisions, minimizes burden, and enables valid comparison with endline measurements.
A reference point or standard value used to measure progress, typically derived from historical data, industry standards, or comparable programs.
A person, household, or organization that receives direct benefits from a program's activities or outputs.
Systematic collection and use of input from program beneficiaries about their experiences, needs, and priorities to improve accountability and program relevance.
Systematic error in data collection, analysis, or interpretation that distorts results and threatens the validity of M&E findings.
The process of strengthening the knowledge, skills, systems, and resources that organizations and individuals need to design, implement, and use monitoring and evaluation effectively.
The process of developing skills, systems, and relationships that enable individuals and organizations to achieve their development goals sustainably.
The process of determining whether an intervention caused observed outcomes by establishing a credible counterfactual and ruling out alternative explanations.
A census measures every unit in a population; a sample measures a representative subset. This guide explains the trade-offs in cost, precision, and inference, and how to decide which approach fits your program.
USAID framework for integrating collaboration, learning, and adaptation into program design and management.
A sampling method that divides the population into clusters and randomly selects entire clusters rather than individuals.
Intentional approaches to sharing M&E findings and program information with stakeholders to influence decisions, build accountability, and promote learning.
An evaluation focused on assessing whether a program adheres to legal, regulatory, donor, and organizational requirements and standards.
Tracking whether a program is implemented according to agreed standards, policies, and legal requirements.
A composite indicator combines multiple individual indicators into a single index or score, enabling measurement of multidimensional concepts that cannot be captured by a single metric.
Extraneous variables that correlate with both the intervention and the outcome, creating spurious associations that threaten causal inference in evaluation.
A systematic approach to analyzing communication content, identifying patterns, themes, and biases in text, audio, or video data through structured coding.
A systematic, ongoing approach to enhancing program performance through iterative learning, feedback, and adaptation.
A structured approach to building a credible case for how and why a program contributed to observed outcomes, without requiring experimental attribution.
A systematic approach to comparing the costs and outcomes of alternative interventions to identify which delivers the best value for money in achieving specific objectives.
The comparison between what happened and what would have happened in the absence of an intervention, the fundamental basis for establishing causal attribution in impact evaluation.
The choice between donor-provided standard indicators and program-specific custom indicators, balancing compliance requirements with contextual relevance.
A visual display of key monitoring indicators enabling rapid assessment of program performance at a glance.
The line-item budget covering the actual costs of collecting M&E data: enumeration, transport, instruments, devices, training, supervision. Typically 30-50% of the total M&E budget for programs with primary data collection, more for survey-heavy programs.
The total time, effort, and resources required from respondents and implementers to complete data collection activities, balanced against data quality needs and program capacity.
The systematic processes for collecting, storing, securing, and maintaining data quality throughout the data lifecycle to ensure information is accurate, accessible, and usable for decision-making.
A systematic process for verifying that collected data meets five quality dimensions, Validity, Integrity, Precision, Reliability, and Timeliness, ensuring data is fit for decision-making.
The strategic use of charts, dashboards, and infographics to communicate monitoring data to diverse stakeholders, transforming raw numbers into actionable insights for decision-making.
An evaluation approach designed for complex, adaptive programs in which goals and processes are emergent, and the evaluator works alongside the program team as an embedded learning partner.
The breakdown of aggregate data by sub-group characteristics, such as sex, age, location, or vulnerability status, to reveal inequities and differences in program reach and outcomes.
Active, intentional process of sharing M&E findings with relevant audiences to promote understanding, learning, and evidence use.
The foundational M&E principle that program and evaluation activities must not expose participants, communities, or program staff to physical, psychological, social, or economic harm, and must actively identify and mitigate harm risks before they occur.
Donor reporting communicates program progress, results, and financial information to funders according to their specific requirements. This guide covers what goes in a donor report and how to meet common funder expectations.
M&E obligations specified in grant agreements and donor policies that shape system design and reporting.
A self-evaluation approach where program participants systematically assess their own work to improve programs and secure future ownership.
A final data collection point at program completion that measures achieved outcomes against baseline and target values.
The principles and standards that guide the ethical conduct of monitoring and evaluation, protecting the rights and dignity of participants, ensuring honest reporting, and managing power responsibly.
A preliminary review of whether a program is sufficiently mature and documented to be meaningfully evaluated.
The OECD-DAC framework provides five standard criteria, relevance, efficiency, effectiveness, impact, and sustainability, for systematically assessing the merit and value of development interventions.
A structured mapping document that links each evaluation question to its data sources, collection methods, indicators, and analysis approach, the operational blueprint for executing an evaluation.
The overarching questions an evaluation will investigate, distinct from survey or interview questions.
A formal document that defines the scope, objectives, methodology, and requirements for an evaluation, serving as the primary contract between the commissioning organization and the evaluation team.
The systematic process of identifying, selecting, and integrating findings from multiple studies to inform program design, evaluation, and decision-making.
Using M&E evidence to inform program, management, and policy decisions rather than intuition or habit.
Ex-ante evaluation happens before a program starts to inform design; ex-post happens after to assess outcomes and lessons. This guide explains what each involves, how they differ, and when each is appropriate.
A structured process for collecting, analyzing, and acting on information to improve program performance and outcomes.
A qualitative data collection method that brings together 6-10 participants to discuss a specific topic, generating rich insights through group interaction and shared experiences.
Evaluation conducted during program implementation to inform improvement, answering what is working, what needs to change, and how the program can deliver better. Paired with summative evaluation (which happens at or after program completion) as the two core evaluation purposes.
Formative evaluation improves programs during implementation; summative evaluation judges their overall merit after completion.
An approach to monitoring and evaluation that systematically examines how programs affect women, men, girls, and boys differently, and ensures that M&E processes themselves do not reinforce gender inequalities.
Long-term, higher-level effects attributable or contributed to by a program; broader change beyond individual outcomes.
A rigorous evaluation approach that measures the causal effect of a program on outcomes by comparing what happened with what would have happened in its absence.
Narrative accounts that illustrate how a program has influenced the lives of beneficiaries, combining quantitative outcomes with qualitative human experience.
An inception report is the first formal deliverable from an evaluation team: confirming the refined methodology, workplan, and analytical approach before fieldwork begins. This guide covers what it contains and why it matters.
A specific, observable, measurable variable that tracks progress toward an outcome or output.
The detailed per-indicator specification document (definition, unit of measure, disaggregation, data source, frequency, responsibility, baseline, target, quality controls) that turns an indicator name into a usable measurement protocol. Mandatory for USAID PMPs; best practice everywhere.
The systematic collection, compilation, and presentation of indicator data to track program performance and communicate results to stakeholders and donors.
The systematic process of choosing and refining performance indicators that are specific, measurable, achievable, relevant, and time-bound to track program progress effectively.
Resources invested in a program (money, staff, materials, time) that enable activities to happen.
The causal chain connecting program activities to intended outcomes, showing how and why a set of interventions is expected to lead to desired change.
In-depth, semi-structured interviews with individuals selected for their specific knowledge, experience, or perspectives relevant to the evaluation questions.
The systematic process of capturing, organizing, and applying lessons, evidence, and insights from M&E across programs and over time to improve organisational decision-making.
The deliberate practice of capturing, organizing, and distributing insights, lessons, and best practices across teams and organizations to improve program performance and avoid repeating mistakes.
The systematic process of gathering evidence, reflecting on it, and using it to improve program strategy and implementation.
A structured set of prioritized questions a program commits to answering through its M&E system, focusing M&E resources on generating evidence for specific programmatic decisions.
A structured set of priority learning questions that guide systematic inquiry throughout program implementation, turning monitoring data into actionable knowledge for decision-making.
Structured, recurring periods of reflection and adaptation where program teams review data, draw lessons, and adjust implementation accordingly.
Documented insights from programs identifying what worked, what did not work, and why, with actionable specificity.
The portion of a team member's time committed to a specific program, typically expressed as a percentage of FTE (full-time equivalent) or as days per year. The budget unit that connects staffing plans to program cost in proposals.
A systematic, critical synthesis of existing research on a specific topic, identifying what is known, gaps in knowledge, and evidence for program design.
A structured matrix that summarizes a project's design, linking activities to expected results through a clear hierarchy of objectives with indicators, verification sources, and assumptions.
Logical Quality Assessment Sampling is a rapid decision-making method that classifies programs or areas as pass/fail against a threshold, commonly used for health program monitoring.
The portion of a program budget dedicated to monitoring, evaluation, and learning activities.
The structured document specifying what will be measured, how, by whom, and how often.
A detailed operational document that translates your logframe and theory of change into actionable M&E requirements, specifying what data to collect, when, from whom, and how it will be used.
The proposal and MEL plan component that specifies the monitoring and evaluation team: roles, level of effort, reporting lines, qualifications, and coverage across the program lifecycle. The difference between an M&E plan that can run and one that cannot.
A structured approach to building the organizational infrastructure, processes, and capacities needed to collect, analyze, and use M&E data for decision-making throughout a program's life.
The specific data source and method that will be used to measure each logframe indicator: survey, administrative record, third-party data, document review. The difference between a logframe that can be verified and one that cannot.
The systematic evaluation of an evaluation's quality, assessing whether it met professional standards and produced credible, useful findings.
A data collection point conducted midway through a program to assess trajectory and enable adaptive decisions.
A significant intermediate checkpoint or event that signals progress toward a target, used to track whether a program is on schedule to achieve its intended outcomes.
An evaluation approach that systematically combines quantitative and qualitative data to provide a more complete understanding of program effects, mechanisms, and context.
Monitoring tracks program progress continuously; evaluation assesses outcomes and impact periodically. Both are essential to M&E, and this guide explains the difference and how they work together.
A participatory qualitative monitoring approach that systematically collects and selects stories of change to identify and share the most significant outcomes of a program.
Qualitative, story-based reporting that contextualizes quantitative indicators with explanations of what happened, why it happened, and what it means for program learning and decision-making.
A systematic process for identifying and analyzing gaps between current conditions and desired outcomes, establishing the evidence base for program design and indicator selection.
A systematic approach to collecting data by directly watching and recording behaviors, interactions, and processes as they occur in natural settings.
The six OECD Development Assistance Committee evaluation criteria (relevance, coherence, effectiveness, efficiency, impact, sustainability) that structure most bilateral donor evaluations. Adopted in 1991, revised 2019 to add coherence.
The systematic process by which an organization captures, analyzes, and applies lessons from experience to improve program performance and decision-making.
Changes in behavior, knowledge, skills, or conditions resulting from program outputs, experienced by beneficiaries.
A retrospective evaluation approach that identifies, verifies, and analyses outcomes that have occurred, then determines whether and how the program contributed to them.
An indicator measuring applied change in participants or beneficiaries: behavior, practice, capability, capacity, or condition that has shifted as a result of program activity. Sits above output indicators and below impact indicators in the results chain.
A participatory planning and monitoring approach that tracks behavior changes in the people, groups, and organizations a program works with directly, rather than long-term development outcomes.
The systematic examination of outcomes to determine whether a program achieved its intended results, distinguishing between expected and unexpected outcomes, and assessing the significance and sustainability of changes observed.
Direct, tangible products of program activities; what the program produces, not what beneficiaries gain.
An indicator that counts tangible deliverables produced by the program (trainings held, kits distributed, people reached). Sits at the output level of the results chain, just above activities and just below outcomes. The most-commonly-reported indicator type in development M&E.
An evaluation approach that actively involves stakeholders and beneficiaries throughout all stages, from design through use of findings, ensuring local ownership and relevance.
An approach to monitoring and evaluation that actively involves stakeholders, especially beneficiaries, at every stage, from design through to using findings for decision-making.
Visual management interfaces that display key performance indicators in real-time, enabling program teams and stakeholders to monitor progress, identify issues, and make data-driven decisions.
An assessment of how well a program or organization is achieving its intended results and operating efficiently against established standards and targets.
The systematic use of monitoring data, evaluation findings, and feedback to guide program decisions, improve results, and ensure accountability to stakeholders.
USAID's planning document operationalizing the Results Framework into measurable indicators, targets, data collection methods, and responsibilities. Required by ADS 201 for USAID-funded programs and increasingly expected by other bilateral donors.
Primary data is collected firsthand for a specific purpose; secondary data is existing data repurposed for new analysis. Each has distinct trade-offs in cost, timeliness, and relevance.
Process evaluation examines how a program is being implemented: whether activities are delivered as designed, to the right people, and at the right quality. It answers the 'how?' before asking 'did it work?'
An indicator measuring the quality and fidelity of program implementation: how activities are being delivered, at what dose, with what adherence to protocol. Distinguished from output indicators (which count deliverables) by focus on delivery quality rather than quantity.
A within-case method for causal inference that tests whether the causal mechanisms predicted by a theory of change actually operated in a specific case, using systematic evidence to evaluate causal claims.
The explicit articulation of how a program is expected to produce change.
A periodic document submitted by programs to donors detailing implementation progress, indicator performance, and key issues.
Indirect measures used when direct measurement of the intended outcome is impossible, impractical, or too costly, requiring careful validation to ensure they accurately represent the target construct.
A non-probability sampling approach where researchers deliberately select participants based on specific characteristics or knowledge relevant to the research objectives.
Non-numerical information captured through words, images, or observations that reveals the how and why behind program outcomes, providing depth and context to quantitative findings.
Numerical data collected through structured measurement, enabling statistical analysis, generalization, and objective comparison across programs and contexts.
A family of evaluation designs that estimate causal program effects without random assignment, using statistical methods to construct credible comparison groups.
A probability sampling method where every member of the population has an equal, known chance of selection, enabling statistical inference to the broader population.
An experimental evaluation design that randomly assigns participants to treatment and control groups to establish causal attribution between an intervention and observed outcomes.
A condensed data collection approach designed to generate actionable insights quickly, typically using streamlined qualitative and quantitative methods in time-constrained contexts.
An evaluation approach conducted during program implementation to provide immediate feedback for adaptive management and mid-course corrections.
The continuous collection and analysis of data during program implementation to enable rapid detection of issues and timely corrective action.
An evaluation approach that asks what works, for whom, in what circumstances, and why, by identifying the mechanisms through which programs produce outcomes in specific contexts.
Structured gatherings where program teams and stakeholders pause to examine what happened, why it happened, and what should change as a result.
The consistency and repeatability of a measurement, whether the same tool produces stable results across repeated applications, different raters, or different time periods.
The principles and practices for producing evaluation and monitoring reports that are clear, credible, actionable, and tailored to their intended audiences.
The sequential hierarchy of change from activities through outputs, outcomes, and impact that shows how a program is expected to create change.
A structured collection of indicators organized by results level that tracks program performance across a portfolio, focusing on what changed rather than what was delivered.
A management approach that focuses organisational decisions, resources, and accountability on achieving defined results, using evidence from monitoring and evaluation.
External factors that could prevent program success and their planned mitigation strategies.
A structured evaluation approach using predefined criteria and performance levels to systematically assess programs, projects, or interventions against established standards.
Systematic approaches for selecting a subset of a population to represent the whole, balancing statistical validity with practical constraints.
A document specifying what an evaluator or consultant will deliver, within what timeframe, budget, and constraints.
A quality framework for designing indicators that are Specific, Measurable, Achievable, Relevant, and Time-bound, ensuring they provide reliable, actionable data for decision-making.
A participatory indicator framework (Subjective, Participatory, Interpreted, Communicable, Empowering, Diverse) designed as an alternative to SMART when community-led measurement, hard-to-quantify outcomes, or learning-focused evaluation matters more than standardized comparability.
Evaluation framework that assigns monetary values to social outcomes to calculate return on investment.
A structured process for identifying all parties with an interest in a program, mapping their roles, influence, and information needs, and informing how M&E should engage them.
A statistical measure indicating whether observed results are likely due to a real effect rather than random chance, typically assessed using p-values and hypothesis testing.
The strategic use of narrative to make M&E findings memorable, actionable, and influential for decision-makers and stakeholders.
Evaluation conducted at or after program completion to judge overall results, typically against the program's objectives, targets, and theory of change. The counterpart to formative evaluation and the primary basis for donor accountability reporting.
The process of designing structured questionnaires and survey protocols to collect reliable, valid, and actionable data from a defined population.
Assessment of a program's continued benefits and functionality after external funding has ended, examining whether outcomes persist and systems remain operational.
A rigorous, structured approach to identifying, appraising, and synthesizing all available evidence on a specific evaluation question using explicit, reproducible methods.
The specific value an indicator is expected to reach by a defined date, quantifying what success looks like.
The process of establishing specific, time-bound performance benchmarks against which program progress and achievement will be measured.
A systematic method for identifying, analyzing, and reporting patterns (themes) in qualitative data through coding and categorization.
A structured explanation of how and why a set of activities is expected to lead to desired outcomes, mapping the causal logic from inputs to impact.
An evaluation approach that tests whether a program's theory of change holds in practice, using process tracing and evidence-at-each-step reasoning rather than relying solely on counterfactual comparison. Strong alternative when RCTs or quasi-experimental designs are infeasible.
Using multiple data sources, methods, or perspectives to cross-verify findings and strengthen the validity of evaluation conclusions.
An evaluation approach where every design decision is driven by the needs of the primary intended users, the specific people who will actually use the findings to make specific decisions.
The degree to which an evaluation accurately demonstrates causal relationships (internal validity) and generalizes findings beyond the study context (external validity).
The optimal balance of cost, quality, and outcomes, achieving the best results for the resources invested, assessed through the 4Es: economy, efficiency, effectiveness, and equity.