Indicators & Evidence

Numbers give your report credibility. But raw indicator data — without context, comparison, and narrative — is inert. This guide shows you how to transform indicator values into evidence-backed narrative that donors can act on.

The Difference Between an Indicator and Evidence

An indicator is a metric that measures change. It answers: how much? how many? how well?

Evidence is the source material that confirms your indicator values are accurate and real. It answers: how do we know?

Example: "87% of children aged 6–23 months received minimum dietary diversity" is an indicator result. The evidence might be: "Data drawn from 312 household surveys conducted in June 2026 across all 12 target villages, using the FAO Minimum Dietary Diversity questionnaire."

Both are necessary. Neither is sufficient alone.

Understanding Indicator Types

Different indicator types require different narrative treatment.

Quantitative Indicators (Number, Percentage, Ratio)

These are the most common indicator types. They need:

• The actual value achieved vs. the target
• Context: what happened, why, and what it means
• Comparison with previous periods if available

Good narrative:

"The project achieved a measles vaccination coverage rate of 91% among children 12–23 months, exceeding the project target of 85%. This represents a 6-point increase from the previous reporting period (85%), attributable to the supplementary immunisation campaign conducted in March and improved community mobilisation through trained local volunteers."

Binary Indicators (Yes/No)

These require a clear description of the process, not just the result.

Good narrative:

"A functional complaints and feedback mechanism was established in all 15 target health facilities by end of Q2, as required by the grant agreement. The mechanism uses a paper-based form available in local languages, with a designated focal point at each facility who compiles monthly summaries. In the reporting period, 47 complaints were received and 43 (91%) were resolved within the 14-day response standard."

Qualitative Indicators

These measure perception, satisfaction, or knowledge — and are harder to evidence. They require:

• Methodology notes (who was asked, how, when, sample size)
• Direct quotes where appropriate
• Clear link to the indicator definition

Good narrative:

"Beneficiary satisfaction with project services was assessed through 210 exit interviews conducted in July across six distribution points. 84% of respondents reported being 'satisfied' or 'very satisfied' with the quality of services received, compared to 71% at baseline. Qualitative responses highlighted improved waiting times as the primary driver of satisfaction."

Writing with Indicator Data

The Three-Question Framework

Before writing about any indicator, answer three questions:

1. What was the result? (State the figure)
2. Was the target met, exceeded, or missed? (Compare to target)
3. Why does this matter? (Connect to the broader goal or story)

Apply this to each indicator you include in your narrative.

Using Comparison Values

Donors love to see change over time. If you have previous-period data, always use it:

"Indicator 1.2a — Children receiving nutrition counselling: Achieved 3,214 vs. target 3,000. This is a 22% improvement over the same period last year (2,632), reflecting the addition of two community nutrition promoters in March."

This comparison is called period-on-period narration and is one of the most powerful tools in donor reporting.

Handling Missed Targets

Missed targets are not failures to report — they are opportunities to demonstrate analytical honesty.

Do not: Ignore them or shift blame vaguely.

Do:

1. State the target and the actual
2. Explain the specific reason(s)
3. Describe what was done in response
4. State the revised forecast

Example:

"Indicator 3.1b — Farmers adopting climate-smart practices: 412 farmers adopted at least two climate-smart practices, against a target of 500. The 18% gap is attributed to delayed seed distribution caused by late onset of rains in the Karamoja sub-region (confirmed by meteorological data from Uganda National Meteorological Authority). To address this, the project adjusted its approach in Q3 by introducing drought-tolerant crop varieties. The revised end-of-project target is 480 farmers, and the project team assesses this as achievable."

Explaining Variance

Always explain variance — both positive and negative. Donors call this variances analysis and expect it in every narrative.

Common variance explanations:

• Seasonal factors (rainy season, harvest cycle, school terms)
• Security constraints restricting access
• Staff turnover or capacity gaps
• Supply chain delays
• Policy or regulatory changes
• COVID-19 or other emergency impacts

Evidence: The Foundation of Credible Reporting

Evidence is any documented source that supports your reported results.

Types of Evidence Acceptable to Most Donors

Evidence Type	Best Used For	Notes
Household surveys	Outcome/impact indicators	Include methodology, sample size, dates
Programme records (attendance, distribution)	Output indicators	Must be countersigned or system-generated
Routine health facility data (DHIS2)	Health programme indicators	Reference the specific facility and period
Official statistics (national census, WHO)	Context indicators	Cite source and year
Partner reports	Joint output indicators	Submit as annexes
Case studies / testimonials	Qualitative indicators	Use with methodology note
Programme monitoring visit reports	Verification	Reference the visit date and observer
Photos with caption and consent	Visibility and participation	Must include date, location, subject

Evidence Quality Standards

Donors have quality standards for evidence. Your evidence should be:

• Verifiable — Can be traced back to its source
• Timely — Collected during or immediately after the activity
• Representative — Not just the most positive examples
• Disaggregated — By sex, age, location, and other relevant characteristics
• Methodologically sound — Based on a clear approach described in the report or an annex

Disaggregation

Always disaggregate by sex at minimum. Other disaggregation dimensions:

• Age (children under 5, youth 15–24, adults 25+, elderly 60+)
• Geographic location (region, district, camp/host community)
• Disability status
• Specific marginalisation criteria relevant to your sector

Example:

"A total of 4,812 beneficiaries received WASH services, of whom 2,647 (55%) were female, 1,521 (32%) were children under 18, and 312 (6%) were persons with disabilities. Of the 1,240 households reached, 680 (55%) were headed by women."

The Evidence Inventory

Maintain an evidence inventory throughout the project — not just at reporting time. For each piece of evidence, record:

• Evidence title and reference (a consistent code helps)
• Date of collection
• Type and methodology
• Indicator(s) it supports
• Person responsible for data quality
• Storage location (Google Drive link or DonorDesk-managed file)

This practice makes report writing fast, accurate, and auditable.

Linking Evidence to Narratives in DonorDesk

In DonorDesk you do not have to type evidence references by hand. You build the chain from claim to proof by linking data:

1. Enter and verify the indicator value for the period (Update Project).
2. Upload the supporting file to the Evidence library and link it to the indicator or activity it proves.
3. Generate the draft. Each section shows its Sources (evidence files, activities, indicator updates), and every factual statement is checked against them.

This creates a traceable chain from claim → data → supporting document that auditors love and donors trust. If your donor also wants explicit references in the text, add them yourself (for example the evidence's title or your own code) when you edit the section.

Checklist Before Submitting

• Every indicator value cited in the narrative has a corresponding evidence record
• All figures in the narrative match the logframe
• Figures are disaggregated by sex and at least one other dimension
• Missed targets are explained with specific reasons
• Comparison with previous periods is included where data is available
• Evidence is linked to the indicators it supports and every flagged statement has a decision
• Methodology is described for all surveys or assessments cited
• Quotes are attributed (with consent) and contextualised

Next: Read Writing Clearly for Donors for style and tone guidance.