# 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.

<!--
Guidance: How to use this template
- Start from the theory of change (nonprofit/theory-of-change) or logic
  model in the proposal. Every indicator here must measure a specific
  output or outcome in that chain; an indicator with no place in the
  chain is noise, and an outcome with no indicator is a blind spot.
- Write the evaluation questions before the indicators. Questions say
  what decision-makers need to know; indicators are only one way to
  answer them.
- Keep the indicator set small. Five to twelve indicators that are
  collected well beat forty that are collected badly. Use funder-required
  indicators verbatim and add your own only where they serve learning.
- Budget for MEL explicitly. A plan without staff time and money is a
  wish list.
- The worked example is the fictional Family Reading Initiative used in
  nonprofit/grant-proposal and nonprofit/grant-report: 60 rural schools,
  24 months, USD 149,600. Indicator IDs IND-001 to IND-003 match those
  documents.
-->

## Document control

<!-- Guidance: The MEL plan is a living document. Version it, and record every change to an indicator definition or target in the revision history, because changed definitions break comparisons over time. -->

| Field | Value |
|---|---|
| Document ID | [MEL-2026-005] |
| Programme / project | [Name and grant reference] |
| Period covered | YYYY-MM-DD to YYYY-MM-DD |
| Version | [0.1] |
| Status | [Draft / In review / Approved / Superseded] |
| Owner | [@mel-lead] |
| Approvers / reviewers | [@programme-lead, @executive-director, funder contact if required] |
| Last updated | YYYY-MM-DD |
| Next review | [*Example:* every 6 months and after the midline] |
| Classification | [Internal / Shared with funder / Public] |
| Linked documents | [Theory of change, proposal, risk register, data protection impact assessment] |

### Approvals

| Role | Name | Decision | Date |
|---|---|---|---|
| MEL lead | [@name] | [Prepared] | YYYY-MM-DD |
| Programme lead | [@name] | [Approved] | YYYY-MM-DD |
| Data protection lead | [@name] | [Data handling reviewed] | YYYY-MM-DD |
| Funder (if required) | [Name] | [Accepted] | YYYY-MM-DD |

### Revision history

| Version | Date | Author | Change summary |
|---|---|---|---|
| 0.1 | YYYY-MM-DD | [@name] | First draft |
| 0.2 | YYYY-MM-DD | [@name] | *Example:* Baseline values entered for IND-001 to IND-003 |
| 1.0 | YYYY-MM-DD | [@name] | *Example:* Approved with the grant agreement |

## Contents

<!-- Guidance: Keep in sync with headings. -->

1. [Purpose and scope](#1-purpose-and-scope)
2. [Results chain](#2-results-chain)
3. [Evaluation questions](#3-evaluation-questions)
4. [Indicator framework](#4-indicator-framework)
5. [Indicator reference sheets](#5-indicator-reference-sheets)
6. [Data collection plan and calendar](#6-data-collection-plan-and-calendar)
7. [Sampling](#7-sampling)
8. [Data quality assurance](#8-data-quality-assurance)
9. [Data protection and ethics](#9-data-protection-and-ethics)
10. [Evaluation design](#10-evaluation-design)
11. [Learning and adaptive management](#11-learning-and-adaptive-management)
12. [Reporting and dissemination](#12-reporting-and-dissemination)
13. [Roles and responsibilities](#13-roles-and-responsibilities)
14. [MEL budget](#14-mel-budget)
15. [Assumptions and MEL risks](#15-assumptions-and-mel-risks)
16. [Glossary and references](#16-glossary-and-references)

## 1. Purpose and scope

<!-- Guidance: Say who will use the MEL information and for which decisions: managers adjusting delivery, the board, funders, participants, the wider sector. Name what the plan covers and what it does not (for example, a separate external evaluation). -->

- **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**:

| User | Decision the information supports | When |
|---|---|---|
| Programme team *(Example)* | Adjust coaching frequency and family session times | Quarterly review |
| Board *(Example)* | Continue, scale or stop the programme | Annual |
| Funder *(Example)* | Release of year 2 instalment | Month 12 report |
| District education office *(Example)* | Absorb coaching into in-service training | Month 24 |
| Participants and communities *(Example)* | Know what changed and give feedback | Termly |

- **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

<!-- Guidance: Summarise the logic from inputs to impact in one diagram and one table, with IDs that the indicator framework reuses. Copy from the theory of change rather than reinventing it; if the two disagree, fix the theory of change first. -->

```mermaid
flowchart LR
    IN["Inputs: coaches, books, partner, funding"] --> ACT["Activities ACT-1 to ACT-6"]
    ACT --> OUT1["OUT-1: 240 teachers trained and coached"]
    ACT --> OUT2["OUT-2: 60 classroom libraries in use"]
    ACT --> OUT3["OUT-3: family reading sessions held"]
    OUT1 --> OC2["OC-2: teachers use structured method (IND-002)"]
    OUT2 --> OC1["OC-1: pupils read at benchmark (IND-001)"]
    OUT3 --> OC3["OC-3: weekly shared reading at home (IND-003)"]
    OC2 --> OC1
    OC3 --> OC1
    OC1 --> IMP["Impact: children read with comprehension by end of year 3"]
```

| Level | ID | Statement | Indicators |
|---|---|---|---|
| Impact *(Example)* | IMP | Children in [District] read with comprehension by the end of year 3 | National assessment results (context only, not attributed) |
| Outcome *(Example)* | OC-1 | Year 3 pupils in participating schools read at benchmark | IND-001 |
| Outcome *(Example)* | OC-2 | Teachers use the structured reading method | IND-002 |
| Outcome *(Example)* | OC-3 | Parents read with their children weekly | IND-003 |
| Output *(Example)* | OUT-1 | Teachers trained and coached | IND-004, IND-005 |
| Output *(Example)* | OUT-2 | Classroom libraries installed and lending | IND-006 |
| Output *(Example)* | OUT-3 | Family reading sessions held | IND-007 |
| [Level] | [ID] | [Statement] | [IND-NNN] |

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

<!-- Guidance: Write three to eight key questions that the evaluation must answer, grouped by the OECD DAC criteria. Not every criterion needs equal weight: the DAC's own principles say the criteria should be applied thoughtfully and according to the purpose of the evaluation, not mechanically. Mark which questions monitoring data can answer and which need an evaluation study. -->

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

| Criterion | Guiding question | Evaluation question for this programme | Answered by |
|---|---|---|---|
| Relevance | Is the intervention doing the right things? | EQ-1 *(Example)*: Does the programme respond to the reading needs of pupils, teachers and families in [District], including pupils with disabilities? | Baseline, stakeholder interviews |
| Coherence | How well does the intervention fit? | EQ-2 *(Example)*: How well does the programme fit the district's in-service training and other literacy programmes in the area? | Document review, district interviews |
| Effectiveness | Is the intervention achieving its objectives? | EQ-3 *(Example)*: To what extent were OC-1 to OC-3 achieved, for which groups, and why? | IND-001 to IND-003, comparison schools |
| Efficiency | How well are resources being used? | EQ-4 *(Example)*: What does it cost per pupil reaching the benchmark, and was delivery timely? | Financial data, activity logs |
| Impact | What difference does the intervention make? | EQ-5 *(Example)*: What difference did the programme make beyond the targeted outcomes, intended or not? | Endline evaluation, qualitative study |
| Sustainability | Will the benefits last? | EQ-6 *(Example)*: Will coaching and libraries continue after funding ends, and with whose resources? | District agreement, follow-up visit |

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

<!-- Guidance: One row per indicator. Define it so that two different people would compute the same number. Give baseline, targets by period, data source, method, frequency, disaggregation and who is responsible. Prefer a mix of outcome and output indicators; include at least one qualitative or feedback measure. Check SMART: specific, measurable, achievable, relevant, time-bound. -->

| ID | Indicator | Level | Unit | Baseline (date) | Target month 12 | Target month 24 | Data source and method | Frequency | Disaggregation | Responsible |
|---|---|---|---|---|---|---|---|---|---|---|
| IND-001 *(Example)* | % of year 3 pupils in participating schools reading at the national benchmark | OC-1 | % of pupils assessed | 47% (month 1) | 55% | 65% | Standardised oral reading assessment, all year 3 pupils | Baseline, midline, endline | Sex, school, disability | MEL officer |
| IND-002 *(Example)* | % of observed lessons in which the structured reading method is used | OC-2 | % of observed lessons | 9% (month 1) | 50% | 70% (month 18) | Classroom observation tool, 4 lessons per teacher per year | Termly | Teacher sex, cohort | Coaches, verified by MEL |
| IND-003 *(Example)* | % of parents reporting shared reading with their child at least weekly | OC-3 | % of respondents | 20% (month 2) | 35% | 50% | Household survey, random sample of 400 | Baseline, midline, endline | Sex of respondent, remoteness | Independent enumerators |
| IND-004 *(Example)* | Number of teachers completing the 5-day training | OUT-1 | Teachers | 0 | 240 | 240 | Attendance registers | After each cohort | Sex, cohort | Programme lead |
| IND-005 *(Example)* | Number of coaching visits completed | OUT-1 | Visits | 0 | 1,700 | 3,600 | Coaching logs | Monthly | School | Coaches |
| IND-006 *(Example)* | Average book loans per pupil per month | OUT-2 | Loans | 0 | 3 | 4 | Library loan registers, sample of 15 schools | Termly | School | Library coordinator |
| IND-007 *(Example)* | Number of family reading sessions held | OUT-3 | Sessions | 0 | 240 | 480 | Partner session logs | Monthly | School | Partner NGO |
| IND-008 *(Example)* | % of feedback items closed with a response within 30 days | Accountability | % of items | Not applicable | 90% | 90% | Feedback log | Quarterly | Channel | MEL officer |
| [IND-NNN] | [Indicator] | [Level] | [Unit] | [Value (date)] | [Target] | [Target] | [Source and method] | [Frequency] | [Groups] | [@owner] |

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

<!-- Guidance: Give each outcome indicator a reference sheet so the definition survives staff changes. The sheet fixes the numerator, denominator, data source, collection method, calculation, known limitations and how to report. Copy the sheet below for each key indicator. -->

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

| Field | Definition |
|---|---|
| Precise definition | Share of year 3 pupils enrolled in participating schools who score at or above the national oral reading fluency benchmark on the day of assessment |
| Numerator | Pupils assessed who score at or above the benchmark |
| Denominator | All year 3 pupils assessed in participating schools (not all enrolled) |
| Benchmark used | [*Example:* national benchmark of [N] correct words per minute, ministry circular dated YYYY-MM-DD] |
| Data source | One-to-one oral reading assessment using the [tool name and version] |
| Collection method | Trained assessors who do not coach the same schools; same tool and passage difficulty at each round |
| Frequency and timing | Month 1 (baseline), month 12 (midline), month 23 (endline), same school term each year where possible |
| Disaggregation | Sex, school, cohort, disability status as recorded by the school |
| Calculation | Numerator divided by denominator, to one decimal place; report coverage (assessed divided by enrolled) alongside |
| Known limitations | Absent pupils are not assessed; benchmark may change nationally; assessor drift |
| Quality checks | 10% of assessments double-scored by a second assessor; agreement target 90% |
| Reporting | Interim and final grant reports, annual impact report |
| Owner | [@mel-officer] |

### 5.2 [IND-NNN]: [Indicator name]

| Field | Definition |
|---|---|
| Precise definition | [Definition] |
| Numerator | [Numerator] |
| Denominator | [Denominator] |
| Data source | [Source] |
| Collection method | [Method] |
| Frequency and timing | [Frequency] |
| Disaggregation | [Groups] |
| Calculation | [Formula and rounding] |
| Known limitations | [Limitations] |
| Quality checks | [Checks] |
| Reporting | [Where reported] |
| Owner | [@owner] |

## 6. Data collection plan and calendar

<!-- Guidance: Turn the framework into a calendar with dates, tools and owners, so field work, holidays and reporting deadlines do not collide. Check school terms, harvest seasons, religious holidays and weather. Leave a buffer between data collection and report deadlines for cleaning and analysis. -->

| Round | Indicators | Tool | Months | Collected by | Report due |
|---|---|---|---|---|---|
| Baseline *(Example)* | IND-001, IND-002, IND-003 | Reading assessment, observation tool, household survey | 1 to 2 | Assessors, enumerators | Month 3 baseline note |
| Routine *(Example)* | IND-004 to IND-008 | Registers and logs | Monthly | Programme staff, partner | Quarterly dashboard |
| Termly observation *(Example)* | IND-002 | Observation tool | Each term | Coaches, 10% verified by MEL | Quarterly dashboard |
| Midline *(Example)* | IND-001, IND-003 | Assessment, survey | 12 | Assessors, enumerators | Month 12 interim report |
| Endline *(Example)* | IND-001, IND-002, IND-003 | All tools, plus qualitative interviews | 23 to 24 | Assessors, enumerators, evaluator | Final report |
| [Round] | [IND-NNN] | [Tool] | [Months] | [Who] | [Report] |

```mermaid
gantt
    title MEL calendar (24 months, Example)
    dateFormat YYYY-MM-DD
    section Surveys
    Baseline              :b1, 2026-01-01, 60d
    Midline               :b2, 2026-12-01, 30d
    Endline               :b3, 2027-11-01, 45d
    section Routine
    Monthly logs          :r1, 2026-01-01, 730d
    section Learning
    Quarterly review 1    :l1, 2026-03-25, 5d
    Quarterly review 2    :l2, 2026-06-24, 5d
    Quarterly review 3    :l3, 2026-09-23, 5d
    Quarterly review 4    :l4, 2026-12-21, 5d
    section Reports
    Interim report        :p1, 2027-01-01, 30d
    Final report          :p2, 2027-12-15, 45d
```

## 7. Sampling

<!-- Guidance: For each sample-based indicator, state the population, sampling frame, method, size and the precision it gives. Show the calculation. Allow for non-response. If you use a census (everyone), say so. Ask a statistician to check designs with clusters, strata or comparison groups, because the effective sample size falls when respondents are clustered. -->

| Indicator | Population | Frame | Method | Sample size | Precision |
|---|---|---|---|---|---|
| IND-001 *(Example)* | Year 3 pupils in 60 schools (about 2,400) | School enrolment lists | Census of pupils present on assessment day | All present | Not sampled |
| IND-003 *(Example)* | Parents of year 3 pupils in 60 schools | Enrolment lists with household contacts | Simple random sample of households | 400 completed interviews | ±3.9 percentage points at 95% confidence, at a 20% baseline |
| [IND-NNN] | [Population] | [Frame] | [Method] | [N] | [Precision] |

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

<!-- Guidance: Name the checks that make the numbers trustworthy. Common dimensions are validity (measures what it says), reliability (same result when repeated), timeliness, precision and integrity (protected from manipulation). Say who checks, how often and what happens when a check fails. -->

| Dimension | Risk | Control | Frequency | Owner |
|---|---|---|---|---|
| Validity *(Example)* | Observation tool records activity, not method quality | Tool piloted in 5 schools; rubric with examples | Before baseline | MEL lead |
| Reliability *(Example)* | Assessors score differently | Training, 10% double scoring, 90% agreement threshold | Each round | MEL officer |
| Timeliness *(Example)* | Partner logs arrive late | Logs due by day 5 of each month; dashboard flags gaps | Monthly | Programme lead |
| Precision *(Example)* | Survey too small for subgroups | Sample size set in section 7; subgroup results flagged when n < 50 | Each survey | MEL lead |
| Integrity *(Example)* | Coaches score their own schools favourably | 10% of observations repeated by MEL staff unannounced | Termly | MEL officer |
| [Dimension] | [Risk] | [Control] | [Frequency] | [@owner] |

**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

<!-- Guidance: MEL often collects personal data about children, families and staff. Decide the lawful basis, minimise what you collect, get informed consent (and parental consent plus the child's own agreement for children), protect the data and set a retention period. Where data protection law applies (for example the EU or UK GDPR), consider whether a data protection impact assessment is needed. Seek ethics review where your organisation, funder or the law requires it. This section is a planning aid, not legal advice. -->

| Question | Answer |
|---|---|
| What personal data is collected, and is each item needed? | [*Example:* pupil name and school for linking rounds, then replaced by a code] |
| Lawful basis or authority for processing | [*Example:* determined with the data protection lead; record in the record of processing] |
| Consent process | [*Example:* written parental consent and child's verbal assent before assessment; right to stop at any time] |
| Special category or sensitive data | [*Example:* disability status, recorded only as reported by the school] |
| Data protection impact assessment needed? | [Yes / No, with reason; see compliance/dpia] |
| Storage and access | [*Example:* encrypted tablets; data uploaded weekly to an access-controlled folder; names held separately from scores] |
| Sharing with partners and funder | [*Example:* only aggregated or pseudonymised data; data sharing agreement with the partner NGO] |
| Retention and deletion | [*Example:* identifiable data deleted 12 months after the final report] |
| Ethics review | [*Example:* reviewed by [ethics committee] on YYYY-MM-DD, reference [N]] |
| Safeguarding during data collection | [*Example:* enumerators vetted and trained under nonprofit/safeguarding-policy; never alone with a child out of sight of others] |

## 10. Evaluation design

<!-- Guidance: Describe how you will judge whether changes are due to the programme. Be honest about the strength of the design: a before-and-after comparison cannot separate the programme from other changes, a non-random comparison group helps, and a randomised design is strongest but not always ethical or feasible. Say whether the evaluation is internal or independent, and its timing. -->

- **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

<!-- Guidance: Data only matters if someone uses it. Set regular moments when the team looks at the data, asks what it means and decides what to change. Record decisions so the next report can show how learning changed practice. -->

| Forum | Participants | Frequency | Inputs | Outputs |
|---|---|---|---|---|
| Quarterly learning review *(Example)* | Programme team, partner, two head teachers | Quarterly | Dashboard, field notes, feedback log | Decision log entries, adjustments to the work plan |
| Annual reflection *(Example)* | Team, board member, district officer | Annual | Midline or endline results | Revised theory of change if needed |
| Participant feedback loop *(Example)* | Parents, teachers, pupils | Termly | Suggestion boxes, phone line, meetings | Changes communicated back to schools |
| [Forum] | [Participants] | [Frequency] | [Inputs] | [Outputs] |

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

## 12. Reporting and dissemination

<!-- Guidance: List every report the MEL system feeds, its audience, content, format and date. Plan how results go back to participants and communities in a form they can use, not only to funders. -->

| Product | Audience | Content | Format | Due |
|---|---|---|---|---|
| Quarterly dashboard *(Example)* | Programme team, board | IND-004 to IND-008, data gaps | One page | Day 15 after quarter end |
| Interim grant report *(Example)* | Funder | All indicators, finances, changes | Funder form (nonprofit/grant-report) | Month 12 |
| Final evaluation report *(Example)* | Funder, district, public summary | EQ-1 to EQ-6 answered | Report and 2-page summary | Month 24 |
| Annual impact report *(Example)* | Donors, public | Headline results and stories | nonprofit/impact-report | Annual |
| Community feedback session *(Example)* | Parents, teachers | Results for their school | Meeting, poster in local language | After midline and endline |
| [Product] | [Audience] | [Content] | [Format] | [Date] |

## 13. Roles and responsibilities

<!-- Guidance: Name who collects, checks, analyses, approves and uses each type of data. Make sure the MEL lead has the time and authority to challenge numbers. -->

| Task | MEL lead | MEL officer | Programme lead | Coaches | Partner NGO | Evaluator |
|---|---|---|---|---|---|---|
| Maintain this plan *(Example)* | Responsible, accountable | Consulted | Consulted | | | |
| Routine data collection *(Example)* | Informed | Accountable | Consulted | Responsible | Responsible | |
| Data quality checks *(Example)* | Accountable | Responsible | Informed | Consulted | Consulted | |
| Analysis and dashboard *(Example)* | Accountable | Responsible | Consulted | | | |
| Endline evaluation *(Example)* | Accountable | Consulted | Consulted | | | Responsible |
| Use of findings *(Example)* | Consulted | Informed | Accountable, responsible | Consulted | Consulted | Informed |

See business/raci for the role assignment format.

## 14. MEL budget

<!-- Guidance: Cost every MEL activity: staff time, tools, field costs, enumerators, data systems, the external evaluation and dissemination. Many funders expect MEL to be visible in the budget; check whether they set a share. Totals must match the proposal budget. -->

| Item | Year 1 | Year 2 | Total |
|---|---|---|---|
| Assessment and survey field costs *(Example)* | USD 3,000 | USD 4,000 | USD 7,000 |
| Data entry tablets and software *(Example)* | USD 1,000 | USD 0 | USD 1,000 |
| External endline evaluator *(Example)* | USD 0 | USD 2,500 | USD 2,500 |
| Dissemination and community sessions *(Example)* | USD 1,000 | USD 500 | USD 1,500 |
| **Total MEL budget** | **USD 5,000** | **USD 7,000** | **USD 12,000** |

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

<!-- Guidance: List what could stop the MEL system from working and how you will respond. Link programme-level risks to the risk register instead of duplicating them. -->

| ID | Risk or assumption | Effect on MEL | Mitigation | Owner |
|---|---|---|---|---|
| MR-01 *(Example)* | National benchmark changes during the project | IND-001 not comparable across rounds | Score against both old and new benchmark at endline | MEL lead |
| MR-02 *(Example)* | Low survey response in remote villages | IND-003 biased toward accessible households | Draw about 475 households for 400 interviews, allowing for 15% non-response (section 7); record and report non-response by area | MEL officer |
| MR-03 *(Example)* | Comparison schools start a similar programme | Effect estimate understated | Track other programmes through district records | MEL lead |
| MR-04 *(Example)* | Staff turnover in the MEL role | Definitions drift | Indicator reference sheets; handover checklist | Programme lead |
| [MR-NN] | [Risk] | [Effect] | [Mitigation] | [@owner] |

Programme risks are tracked in compliance/risk-register.

## 16. Glossary and references

<!-- Guidance: Define terms readers may use differently, and list the frameworks and documents the plan relies on, with editions and dates. -->

| Term | Meaning in this plan |
|---|---|
| Monitoring | Routine, continuous collection of data on delivery and results |
| Evaluation | A periodic, systematic assessment that judges merit or worth against criteria |
| Learning | Using monitoring and evaluation evidence to change decisions and practice |
| Indicator | A defined measure of a result, with a unit, source and frequency |
| Baseline | The value of an indicator before the intervention starts |
| Target | The value the programme commits to reach by a given date |
| Disaggregation | Breaking results down by groups such as sex, age, disability or location |
| Comparison group | People or sites not receiving the intervention, used to estimate what would have happened without it |
| Margin of error | The range around a sample estimate within which the true value is likely to lie at a stated confidence level |

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.