The gap between the impact data funders want and the impact data small grantees can realistically provide is one of the most persistent sources of friction in the grants sector.
Funders want evidence. Small organisations — often volunteer-run, often working with vulnerable populations, often with minimal administrative infrastructure — want to focus on the work. Somewhere in between, a reasonable compromise exists. Finding it requires funders to be more deliberate about what data is actually worth collecting.
Before designing data collection requirements, ask: what is the smallest amount of information that would tell us whether this grant is achieving its purpose?
For a programme funding community health education:
- The minimum useful dataset might be: number of people who attended, and whether they'd recommend the programme to a friend.
- A richer dataset adds: self-reported knowledge change and one or two behaviour intentions.
- A comprehensive dataset adds: follow-up data on actual behaviour change, health outcomes, and population-level indicators.
The minimum is always achievable. The comprehensive is rarely achieved in practice, because small organisations can't sustain the data collection infrastructure it requires.
Start with the minimum. If your programme has the relationships and the resources to support more, add to it. Don't design for comprehensive and then accept minimum as a fallback — design for minimum and treat anything more as a bonus.
The most common reason small organisations struggle with impact data is that they're asked to produce it at the end of the grant, when it's too late to build it into their programme design.
Agree your data requirements at the grant offer stage — ideally before the grantee finalises their activity plan. When grantees know what data you need, they can build collection into the programme itself: a sign-in sheet at every workshop, a two-minute verbal check-in at the end of each session, a brief survey administered while participants are still in the room.
Data collected in the moment is more accurate and less burdensome than data reconstructed from memory six months later.
Telling a grantee to "collect participant feedback" without giving them a tool is an unfunded mandate. A three-question paper survey they can print, administer, and summarise in an afternoon is a resource.
Build a small library of data collection tools your grantees can use:
These tools don't need to be elaborate. A one-page survey template and an example report can reduce reporting time for small grantees by hours.
Some indicators are important enough that you shouldn't rely on grantees to collect the data. For these, design funder-administered collection:
Funder-administered collection reduces burden on grantees and often produces more candid responses — participants are sometimes reluctant to give negative feedback to the organisation that delivered their programme.
For outcomes that can't be directly measured in a small-grants context, accept proxy indicators — related, measurable things that are good evidence the outcome is occurring.
For "improved financial resilience" in a small community organisation: a proxy might be whether the organisation now has a reserves policy (observable) rather than whether their actual financial position has improved (measurable only over years).
For "stronger relationships with community": a proxy might be whether the organisation has formed at least two new partnerships during the grant period (reportable) rather than a measure of social capital (complex to assess).
Document your proxy indicators and the rationale for accepting them. This matters if your impact evidence is ever scrutinised.
Individual grantee impact reports are useful for managing relationships and making renewal decisions. Aggregated impact data — across all your grantees — is what tells you whether the programme is working.
Build aggregation into your data collection design. This means:
Consistent measurement requires resisting the temptation to let each grantee define their own indicators. "Tell us how you measure success" produces varied, incomparable data. "Report against these three indicators" produces comparable data you can aggregate.
Before you finalise your impact data requirements, ask: if we receive exactly this data from all our grantees, what will we do with it?
If the answer is "put it in the board report," design for summary presentation. If the answer is "decide which grantees to renew," design for individual-level comparison. If the answer is "demonstrate programme effectiveness to our own funder," design for the evidence standard that funder requires.
Data collection without a clear use case is a burden on grantees and a cost to your programme. Design for use, not for completeness.
This article is part of the complete guide: What Great Grant Outcome Reporting Looks Like.