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A credible assessment of project results starts before any data is collected. Name the people who will use the findings and the decisions those findings should inform, show how project activities are expected to produce outcomes, then choose questions, indicators, and an evaluation design that can support the conclusions you want to draw. Claims about what the project caused need a stronger design than claims about what was achieved, and the findings should say which is which.
The approach below is general. It is meant for any project, whether a development intervention, a public program, or an internal initiative. The specific questions, indicators, and methods have to be adapted to the intervention, its stakeholders, and the decisions it is meant to inform.
Start with the users and the decision
Before choosing methods, write down who will read the evaluation and what they will do with it. The purpose may be improving the project while it runs, deciding where to allocate resources, meeting an accountability requirement, or planning a successor project. Each purpose asks for different questions and different levels of evidence, and an evaluation that tries to serve all of them at once often answers none of them well.
The CDC’s Program Evaluation Framework, updated in 2024, lays out a practical sequence that works for projects outside public health as well:
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- Assess the context in which the project operates.
- Describe the project, including its need, inputs, activities, and expected results.
- Focus the evaluation questions and choose a design.
- Gather credible evidence.
- Generate and support conclusions.
- Act on the findings.
The framework also asks evaluators to carry three commitments through every step: engage stakeholders collaboratively, promote fair and just evaluation practices and outcomes, and learn from and use what the evaluation reveals. It is designed as a guide rather than a fixed formula, so treat the sequence as a checklist of things to consider, not steps to complete in a rigid order. Source: CDC Program Evaluation Framework.
Describe the project and its logic
An outcome can only be assessed against an expectation of what the project was supposed to change. Write that expectation down in the project’s own terms: the need it addresses, the inputs it uses, the activities it carries out, the outputs those activities produce, and the outcomes it hopes to achieve. Note the contextual factors, such as funding conditions, staffing, political or market conditions, or community circumstances, that could help or hinder the chain.
A logic model or roadmap makes this visible. It connects activities to outputs and to short-term, intermediate, and long-term outcomes. The most useful part is usually the set of assumptions linking each step, because that is where the project can fail without anyone noticing. For example, a training program might chain together like this:
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- Activity: a three-day training course for clinic staff.
- Output: staff complete the course.
- Short-term outcome: staff can describe and apply the new protocol.
- Intermediate outcome: the protocol is used in routine consultations.
- Long-term outcome: patient results improve.
Each arrow is an assumption. The assumption that staff who can describe the protocol will use it is testable in its own right, and it should be listed so the evaluation can check it.
Choose criteria and questions that fit the project
The OECD Development Assistance Committee offers six complementary criteria for evaluating development and other interventions where they fit: relevance, coherence, effectiveness, efficiency, impact, and sustainability. Each addresses a different attribute of an intervention. OECD guidance is clear that they should be selected and interpreted according to the purpose, context, and stakeholder needs, and that they are not a method or a checklist to apply mechanically. The table below gives the plain-language question each criterion asks.
| Criterion | Question it asks |
|---|---|
| Relevance | Does the project respond to the needs it was designed to meet? |
| Coherence | Does the project fit with other efforts in the same setting? |
| Effectiveness | Is the intervention achieving its objectives? |
| Efficiency | Are resources being used well to deliver results? |
| Impact | What broader changes, intended or not, is the project producing? |
| Sustainability | Do the benefits continue after support ends? |
Effectiveness is the criterion most readers reach for first, and OECD guidance frames it as the question “Is the intervention achieving its objectives?” Keep the set of questions manageable. Five well-chosen questions tied to the decisions identified at the start will produce more useful findings than twenty questions drawn from a template. Source: OECD, Evaluation Criteria.
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Pick the evaluation type that matches the question
CDC describes evaluation as taking several forms, depending on purpose. None is universally superior, so choose by the question being asked.
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- Process or implementation evaluation examines how the project was delivered and how that delivery relates to the intended theory of change.
- Outcome evaluation measures the extent to which intended outcomes were achieved.
- Impact evaluation assesses whether a causal relationship between the project and its outcomes can be established.
- Economic evaluation relates program effects to program costs.
A project that did not reach its participants may need a process evaluation before any outcome question is worth asking. A project that has delivered as planned but cannot show change may need an outcome evaluation with better indicators. Source for the typology: CDC, CDC Program Evaluation Framework, 2024 (MMWR).
Match indicators and data to each question
Each evaluation question needs evidence that directly represents the expected result it refers to. Define that result first, then choose an indicator that measures it, and specify the measure and the data source. An indicator with no named source is a plan that cannot yet be carried out.
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CDC recommends indicators that are SMART: Specific, Measurable, Achievable, Relevant, and Timebound. The same guidance calls for enough data of adequate quality, and for measures that may be quantitative or qualitative depending on the question. Before collecting anything new, check the following:
- Whether existing instruments or data sets can be adapted rather than built from scratch.
- Whether collection protocols will be applied consistently across sites, staff, and time periods.
- Whether the data plan addresses security, including who can access identifiable information and how it is stored.
Qualitative evidence, such as interviews, observation, or document review, often explains why an indicator moved or did not move. Treat it as part of the evidence base rather than an afterthought. The CDC’s detailed guidance on this step is in Step 4 – Gather Credible Evidence.
Achieved outcomes are not proof of cause
The most common overstatement in project reporting is treating an achieved outcome as evidence that the project produced it. An outcome evaluation measures the extent to which intended outcomes were achieved, but on its own it cannot attribute causality. An impact evaluation compares outcomes with and without the intervention, and is designed to test whether a causal relationship can be established.
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| Feature | Outcome evaluation | Impact evaluation |
|---|---|---|
| Main question | Were the intended outcomes achieved? | Did the intervention cause the outcomes? |
| Comparison required | Not required to describe achievement | Outcomes are compared with and without the intervention |
| Causal claim it supports | Association between project and outcome, without attribution on its own | A causal relationship, if the design and analysis can establish one |
Choose the design to match the claim you intend to make. If the findings will say the project caused a change, the design must rule out plausible alternative explanations, such as other programs, economic shifts, or changes in who was measured. If the findings will only say that outcomes were reached, state that clearly and avoid causal language. Limitations and alternative explanations belong in the findings, not in a footnote.
Choose a design the project can actually support
Method choice should weigh several factors together. Consider the evaluation purpose and questions, the context, the quality of available evidence, the strength of causal claim required, feasibility, available skills and resources, timing, ethics, and how useful the results will be to the intended users. CDC notes that the choice should balance evaluation goals, scale, timeline, feasibility, and resources. A rigorous design that cannot be finished before the decision it serves is less useful than a modest design delivered on time, provided its limits are stated.
Turn evidence into supported conclusions
Analyze and interpret the evidence against the questions and criteria you set at the start. The findings should explain what the evidence supports and where it is limited. Look at intended and unintended results alike, and check for differences across groups where they are relevant, because an average can hide a result that only some participants experienced.
CDC’s framework treats generating supported conclusions and acting on findings as separate steps. Prepare findings in a form people can use, help the intended users engage with them, and connect them to concrete decisions such as program improvement, resource allocation, accountability, or planning. Findings that arrive after the decision has been made are a failure of timing, even if they are technically correct.
Check the work against five quality standards
The CDC framework gives a short set of standards that can serve as a final check on any evaluation. In its words: “High-quality evaluation should consider these five evaluation standards: Relevance and utility; Rigor; Independence and objectivity; Transparency; Ethics.” (Centers for Disease Control and Prevention, Program Evaluation Framework, 2024.) Ask of each finding whether it is useful to its intended readers, whether the method is rigorous enough for the claim being made, whether the evaluators were independent enough to report unwelcome results, whether the methods and limitations are open to scrutiny, and whether the work respected the people it involved.
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