Impact measurement is one of the most discussed and most contested topics in contemporary philanthropy. How can funders know whether their grants are making a difference? What counts as evidence? How should foundations balance the rigor of measurement against the burden it places on grantees? This article explores the main frameworks and practical approaches that foundations use to understand and communicate their impact.
The case for measurement
Foundations have an obligation to their donors, their boards, and the communities they serve to invest wisely. Without understanding what their grants achieve, foundations cannot improve their grantmaking, cannot make the case for philanthropic investment, and cannot contribute to shared learning about what works.
The limits of measurement
Social change is complex, multi-causal, and slow-moving. Many of the most important outcomes — culture change, systemic reform, social norm shifts — are difficult or impossible to attribute to specific grants. Heavy measurement requirements can burden grantees, distort their behaviour toward the measurable, and undermine the trust-based relationships that produce the best results.
The best impact measurement is honest about these tensions — rigorous enough to generate useful knowledge, pragmatic enough to be proportionate to grant size and purpose.
A theory of change is the foundation of any meaningful impact measurement. It articulates:
- Inputs: What resources (grants, staff time, expertise) are invested
- Activities: What the funded organisation does with those resources
- Outputs: The immediate, countable results of those activities
- Outcomes: The changes in knowledge, attitudes, behaviour, or conditions for people served
- Impact: The longer-term changes in social conditions that the programme contributes to
A theory of change makes explicit the assumptions and causal logic connecting activities to outcomes. It identifies what needs to be true for the programme to work, and therefore what should be measured and monitored.
Good theories of change are co-created with grantees and communities — not imposed by funders. They are living documents that are revised as evidence accumulates.
A logic model is a visual representation of a theory of change — typically a table or diagram showing the inputs → activities → outputs → outcomes → impact chain. Logic models are useful for:
- Communicating the programme's logic clearly
- Identifying what should be measured at each stage
- Highlighting assumptions that need to be tested
- Structuring programme monitoring
Logic models can become overly mechanistic if treated as the whole story rather than a simplified representation of complex social reality.
Attribution — proving that a grant caused a specific outcome — is often impossible in complex social systems where multiple actors influence outcomes. Contribution analysis is an alternative framework that asks not "did this grant cause this outcome?" but "did this grant contribute to this outcome, and how?"
Contribution analysis builds a causal story — assembling evidence that the programme theory was implemented as intended, that outcomes occurred, and that the programme plausibly contributed to those outcomes — without claiming exclusive attribution.
Outcomes are changes in people's lives or social conditions: improved mental health, increased employment, reduced reoffending, stronger community connections, better environmental conditions. Indicators are measurable proxies for outcomes — evidence that an outcome has occurred.
Choosing good indicators requires understanding what can be practically measured, at what cost, and with what validity. Common indicator types:
- Self-reported wellbeing (surveys, interviews)
- Administrative data (school attendance, employment records, hospital admissions)
- Observation and assessment (clinical ratings, environmental monitoring)
- Community-generated data (participatory evaluation, community report cards)
The right mix depends on what the programme is trying to achieve and what measurement is proportionate.
SROI calculates the social value generated per dollar invested, expressed as a ratio (e.g., $4.50 of social value for every $1 invested). It works by:
1. Identifying all stakeholders and the outcomes they experience
2. Placing monetary values on those outcomes (using proxies like cost savings, earnings increases, quality-adjusted life years)
3. Calculating total social value
4. Dividing by total investment
SROI is useful for communicating the scale of social value in terms that decision-makers and donors understand. But it has significant limitations: the monetisation of social outcomes involves judgments that can be contested; SROI can create false precision; and it favours measurable, near-term outcomes over harder-to-measure systemic change.
Many foundations aim to contribute to change at the population or system level — reduced poverty rates, improved environmental conditions, stronger civic participation. These systemic impacts are:
- Difficult to attribute to any specific funder or programme
- Requiring long timeframes (years to decades)
- Dependent on multiple actors working in alignment
Measuring systemic impact requires tracking population-level indicators over time, and honestly acknowledging the limits of attribution. Some foundations commission independent population-level studies; others rely on tracking publicly available administrative data.
Grantee reports are one source of impact data, but they have significant limitations: grantees may emphasise positive results, reporting formats may not capture what matters most, and the quality of grantee self-assessment varies.
Better alternatives or complements include:
- External evaluation: Independent evaluation of specific programmes or portfolio areas
- Developmental evaluation: Real-time learning evaluation that accompanies complex, evolving work
- Participatory evaluation: Communities and grantees as active participants in evaluation design and interpretation
- Grantee perception surveys: Structured surveys of grantee experience (like CEP's Grantee Perception Report)
- Field scans: Horizon-scanning for evidence on what approaches work in a given area
Not every grant requires sophisticated impact measurement. A small grant for sports equipment doesn't warrant an SROI analysis. A major multi-year investment in systemic change does. Proportionate measurement means:
- Small grants: simple output tracking (e.g., number of participants, pieces of equipment purchased)
- Medium grants: outcome tracking (e.g., participant skill development, community use of facility)
- Large grants and portfolios: population-level monitoring, independent evaluation, systemic learning
Matching measurement to grant scale and purpose reduces burden while maintaining accountability.
Grants management platforms increasingly include impact measurement tools — data collection, indicator tracking, portfolio analysis, and reporting dashboards. Technology reduces the cost of measurement but doesn't resolve the fundamental questions about what to measure and how to interpret data.
Tahua's grants management platform includes built-in impact measurement tools — with outcome tracking, indicator dashboards, portfolio analytics, and reporting templates that help foundations understand and communicate their philanthropic impact.