Monitoring and Evaluation Plan Template (MEL, OECD DAC Criteria)

Monitoring, Evaluation and Learning Plan: [Programme or project name]

A monitoring, evaluation and learning (MEL) plan for a programme or grant-funded project: results chain, evaluation questions organised by the six OECD DAC evaluation criteria, an indicator framework with reference sheets, data sources and frequency, sampling, data quality, data protection and ethics, evaluation design, learning cycles, reporting, roles and the MEL budget. Evaluation questions follow the OECD DAC criteria as revised in "Better Criteria for Better Evaluation" (adopted by the DAC on 10 December 2019). Replace every [bracketed] value and every row or passage marked Example. Where the plan touches personal data or research with people, it is a planning format, not legal or ethics advice.

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Contents

1. Purpose and scope
2. Results chain
3. Evaluation questions
4. Indicator framework
5. Indicator reference sheets
6. Data collection plan and calendar
7. Sampling
8. Data quality assurance
9. Data protection and ethics
10. Evaluation design
11. Learning and adaptive management
12. Reporting and dissemination
13. Roles and responsibilities
14. MEL budget
15. Assumptions and MEL risks
16. Glossary and references

1. Purpose and scope

• Purpose: [Example: track delivery against plan, learn which parts of the intervention drive reading gains, report to the funder, and give the district education office evidence for taking over coaching after month 24.]
• Primary users and decisions:

• In scope: [Example: all 60 participating schools, 20 comparison schools, families attending sessions.]
• Out of scope: [Example: long-term tracking of pupils after year 3, which needs separate funding and consent.]

2. Results chain

Key assumptions to monitor (from the theory of change): [Example: schools protect daily reading time; teacher turnover stays below 15% a year; families can attend monthly sessions.]

3. Evaluation questions

The six OECD DAC criteria, each with its short guiding question as published in "Better Criteria for Better Evaluation" (2019):

Additional learning questions for internal use: [Example: LQ-1, does coaching frequency change teacher practice more than training alone? LQ-2, which session formats keep volunteers engaged in the farming season?]

4. Indicator framework

Consistency rule: IND-001 to IND-003 use the same IDs, baselines and targets as the objectives OBJ-1 to OBJ-3 in the proposal (nonprofit/grant-proposal) and the progress table in each grant report (nonprofit/grant-report).

5. Indicator reference sheets

5.1 IND-001 (Example): Year 3 pupils reading at benchmark

5.2 [IND-NNN]: [Indicator name]

6. Data collection plan and calendar

7. Sampling

Worked calculation for IND-003 (Example): the margin of error for a proportion p with n completed interviews at 95% confidence is about 1.96 × √(p × (1 − p) / n). With p = 0.20 and n = 400: 1.96 × √(0.16 / 400) = 1.96 × 0.02 = 0.039, so ±3.9 percentage points. The expected change from 20% to 50% is far larger than this margin. If you expect 15% non-response, draw 400 / 0.85 = 471 households, rounded up to 475. The formula ignores clustering; if households are sampled school by school, increase the sample or ask a statistician for the design effect.

8. Data quality assurance

Data quality review: [Example: the MEL officer runs a data quality check on two indicators each quarter, visiting two schools to compare registers with reported figures. Differences above 5% are investigated and corrected at source, and the correction is recorded.]

9. Data protection and ethics

10. Evaluation design

• Type: [Example: internal monitoring plus an independent endline evaluation in months 22 to 24.]
• Design: [Example: before-and-after measurement in 60 participating schools, with 20 comparison schools in a neighbouring sub-district matched on baseline reading scores and school size.]
• Analysis: [Example: difference in the change in IND-001 between participating and comparison schools; results by sex, cohort and disability; qualitative interviews with 30 teachers and 40 parents to explain the numbers.]
• Limitations: [Example: comparison schools were not randomly assigned, so differences between areas may bias the estimate; the comparison schools may adopt some methods informally.]
• Evaluator independence: [Example: endline evaluator selected by competitive process, reports to the board, has no other role in the programme.]
• Evaluation terms of reference: [Example: drafted by month 18, covering EQ-1 to EQ-6.]

11. Learning and adaptive management

Decisions taken in learning reviews are recorded in a decision log (business/decision-log) with the evidence that prompted them.

12. Reporting and dissemination

13. Roles and responsibilities

See business/raci for the role assignment format.

14. MEL budget

Check (Example): the totals match the monitoring and evaluation line in the proposal budget (year 1 USD 5,000, year 2 USD 7,000, total USD 12,000), which is 8.0% of the USD 149,600 award. The part-time MEL officer is costed under personnel, not here.

15. Assumptions and MEL risks

Programme risks are tracked in compliance/risk-register.

16. Glossary and references

References:

• OECD DAC Network on Development Evaluation, "Better Criteria for Better Evaluation: Revised Evaluation Criteria Definitions and Principles for Use", adopted by the DAC on 10 December 2019, OECD, https://doi.org/10.1787/15a9c26b-en
• OECD, "Applying Evaluation Criteria Thoughtfully", OECD Publishing, 2021, https://doi.org/10.1787/543e84ed-en
• Related templates: nonprofit/theory-of-change, nonprofit/grant-proposal, nonprofit/grant-report, nonprofit/impact-report, compliance/dpia, compliance/risk-register, business/decision-log, business/raci.

Standard and licence note

Based on the OECD DAC evaluation criteria (relevance, coherence, effectiveness, efficiency, impact and sustainability) and their two principles for use, as set out in "Better Criteria for Better Evaluation" (adopted by the DAC on 10 December 2019), together with common monitoring, evaluation and learning practice (results chains, indicator reference sheets, data quality dimensions and learning reviews). The guiding question for each criterion is cited by name with attribution to the OECD; all other text is original. Check the current OECD publications and your funder's MEL requirements before use; a funder's required indicators and formats take precedence. This is a planning format, not legal, data protection or ethics advice. Template licence: MIT.