Use What, Who, How Much, Contribution and Risk to examine an impact claim and identify the evidence still missing.
The Five Dimensions of Impact are What, Who, How Much, Contribution and Risk. They organize questions about an outcome, who experiences it, its extent, the enterprise’s contribution and the risk that impact differs from expectations. The norms originated through the Impact Management Project and are maintained by Impact Frontiers.
They are not a universal numerical score, certification or substitute for evidence. You can use them to structure a discussion, an assessment or a data collection plan. Start with a material outcome rather than trying to assign one undifferentiated score to an entire organization. Read the current Impact Frontiers guidance.
| Dimension | Question to investigate | Evidence to seek |
|---|---|---|
| What | What outcome occurs, and how important is it? | A defined outcome and evidence of its significance. |
| Who | Who experiences it, and what is their context? | Relevant characteristics, needs and starting conditions. |
| How Much | How many are affected, how deeply and for how long? | Scale, depth and duration. |
| Contribution | What likely would have happened otherwise? | Evidence about other influences and a plausible counterfactual. |
| Risk | What could make the impact different from expectations? | Uncertainty, evidence gaps and possible adverse effects. |
“People served” describes reach. “People can access a reliable service” describes an outcome to investigate. Ask affected people what matters, and identify whether the observed condition meets a relevant threshold. Do not assume that the easiest indicator is the most meaningful one.
One activity can produce several outcomes, including negative ones. A service may improve access while increasing costs for some users. Decide which effects are material enough to examine, and document that decision. Explore the What dimension.
Describe the affected groups and their starting conditions. Relevant distinctions may include location, access barriers or relationship to the enterprise. Collect sensitive characteristics only when justified and protect confidentiality.
An average improvement can coexist with deterioration for a smaller group. Use appropriate disaggregation and qualitative evidence to understand that distribution. Avoid publishing small groups that could identify individuals. Explore the Who dimension.
Scale concerns how many people experience the outcome; depth concerns the extent of change; duration concerns how long it lasts. A large number reached is not enough to establish depth or persistence.
For an employment example, distinguish people enrolled from people experiencing improved employment conditions, the size of the improvement and whether it lasts. Keep follow-up coverage visible: an unknown outcome is not automatically a success or failure. Explore How Much.
Change after an intervention is not necessarily change caused by it. Other services, economic conditions and participants’ own actions may contribute. Identify a plausible comparison and the limitations of the evidence available.
The enterprise’s contribution to outcomes is distinct from the investor’s contribution to the enterprise. Do not use an investor’s provision of capital as proof that all observed outcomes are additional. Read the enterprise-contribution guidance.
List what could make the actual result different from the expected one. Examples include weak evidence, an outcome not lasting, a delivery interruption or effects on people being overlooked. These examples help begin the review; consult the current norms when using their formal risk categories.
For each important risk, record its evidence, the action available and the person responsible for review. A confident-looking rating should not hide an unresolved data gap.
The following is illustrative. A provider reports that 60 of 100 trainees entered work. Thirty-six respond six months later; 28 report remaining in work. The review needs more than a placement count.
| Dimension | Review finding |
|---|---|
| What | Define the quality and suitability of employment, not just any placement. |
| Who | Check which participants obtained work and which faced barriers. |
| How Much | Report 60 placements, follow-up coverage of 36/60 and the 28 observed retained jobs separately. |
| Contribution | Examine local hiring conditions and other support. Placement alone does not establish additionality. |
| Risk | Missing follow-up and uncertain job quality limit the claim. Plan the next evidence collection. |
Use a small evidence register: outcome, dimension, measure, source, period, owner and limitation. Keep common definitions across comparable investments, while retaining measures specific to each business model. Documents and interviews may support the review alongside metrics.
If you choose a scoring rubric, document its rules and weighting, distinguish missing evidence from poor performance, and test whether reviewers interpret it consistently. The resulting score is your assessment method; it is not an official universal Five Dimensions score.
The dimensions organize the questions. IRIS+ provides a system for impact measurement and management, including standardized metrics. A metric may supply evidence for a dimension, but selecting a metric does not answer every question about importance, contribution or risk. Check the current IRIS+ definitions before adopting a measure.
For a practical way to connect measures to intended results, continue to the results framework guide.
The dimensions developed through the Impact Management Project. Impact Frontiers now maintains the relevant norms; use the current guidance rather than assuming an older summary is unchanged.
You may design an assessment rubric, but it requires explicit rules and judgment. The dimensions do not supply a universal additive score.
They can also help enterprises and practitioners examine material outcomes. Investor contribution is a related but distinct question.
No. A score reflects the evidence and assessment rules used. It cannot remove uncertainty or establish causation by itself.
