You are a senior MEAL specialist tasked with drafting a proposal-ready data collection plan that specifies how every indicator in the MEL plan will be measured, by whom, when, and with what instruments.
Program Context:
- Program name: "program name" (from the material, if given)
- Indicator set: "indicators" (from the material, if given)
- Program timeline: "program timeline" (from the material, if given)
- Sample context: "sample context" (from the material, if given)
Task: Produce a data collection plan that leaves no indicator without a specified method, schedule, sampling approach, responsible party, and instrument. The plan should be detailed enough that a field team could execute it without further guidance.
Requirements:
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Data Collection Methods per Indicator Category:
- Output indicators: typically program records, attendance sheets, distribution logs, administrative data (real-time, low cost)
- Outcome indicators: typically surveys (household, beneficiary, provider), structured observations, routine service data
- Goal/impact indicators: typically population-based surveys, census data, third-party datasets, qualitative depth studies
- For each indicator, specify the primary method and, where relevant, a triangulation method.
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Schedule:
- Baseline: timing (typically within first 3-6 months), scope (all outcome/goal indicators)
- Routine monitoring cycles: frequency (monthly, quarterly) and what is collected each cycle
- Midline (if applicable): timing, scope, purpose (course correction vs. reporting)
- Endline: timing (final 3-6 months), scope, links to evaluation
- Present as a Gantt-style timeline.
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Sampling Approach: For each survey or primary data collection activity:
- Target population and sampling frame
- Sample size calculation: state the "expected effect size" (from the material, if given), confidence level (typically 95%), and statistical power (typically 80%)
- Design effect (typically 1.5-2.0 for cluster sampling) applied to the base sample size
- Non-response buffer (typically 15-25% inflation) to protect final sample sizes
- Sampling strategy (simple random, stratified, cluster, purposive) with justification
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Instrument Inventory: List every data collection instrument the plan requires. Typical inventory:
- Household survey
- Key informant interview guide
- Focus group discussion guide
- Structured observation checklist
- Facility/service provider assessment tool
- Routine monitoring form (for program staff)
- Beneficiary feedback/complaints form
- For each instrument, note approximate length, language requirements, and whether it exists or needs to be developed/adapted.
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Responsibilities: For each data collection activity, specify who is responsible (role, not individual) across the chain: instrument design, field team training, data collection, data entry/upload, data quality checks, analysis, reporting. Use a simple RACI logic (Responsible, Accountable, Consulted, Informed).
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Digital vs. Paper Decision Rationale: Make an explicit choice between digital data collection ("digital tools" (from the material, if given)) and paper-based. Justify based on: connectivity in field sites, enumerator familiarity, budget, data complexity, time to clean data, and security/confidentiality needs. Hybrid approaches are acceptable if justified.
Output Format:
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Data Collection Plan Narrative (600-900 words): Walks through methods by indicator category, sampling rationale, instrument inventory logic, responsibilities, and the digital-vs-paper decision.
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Schedule Table:
| Activity | Method | Indicators Covered | Timing | Sample Size | Responsible Party | Instrument |
|---|
- Sampling Calculation Summary: One paragraph per primary data collection activity showing base sample size, design effect adjustment, non-response buffer, and final target sample size.
Where the material is silent, write "Not in the material" rather than guessing.
Source material: Attached, or pasted below. Base everything above on it and do not invent details that are not in it.