At a recent workshop hosted by NuSocia, a group of CSR funders discussed a shared challenge: how to verify the accuracy of the programme monitoring data they collect and report to their boards. With small teams, limited budgets, and often limited technical capacity in monitoring and evaluation (M&E), building robust verification systems is difficult. Funders typically manage portfolios of dozens or hundreds of projects, which makes it impractical to send teams into the field to collect data with statistically sound sample sizes.
Two broad approaches emerged. The first is to request supporting evidence for self-reported data, which is workable but limited in rigour. The second, used by several international funding organisations, is to work with implementation agencies that maintain their own independent M&E function. This second approach addresses the verification problem directly, but it raises a further question for many NGOs: where does the funding to build that function come from?
This is the central tension this piece explores: strong data systems are increasingly required to access funding, yet funding rarely covers the cost of building those systems.
What Funders Are Asking For
Funders’ expectations vary, but a pattern is emerging. A government scheme may want to see a working pilot before committing larger public funds. An international donor may expect a full M&E framework to run for the life of a grant, not just a closing report. A CSR funder that once accepted a utilisation certificate and a site photo increasingly expects more. The Social Stock Exchange requires a logic model at listing and an independent impact assessment every three years, conducted by a qualified auditor. Philanthropic foundations, outcome-based financing structures, incubation prizes, and multilateral programmes each bring their own version of this requirement.
What these approaches share is a shift in what “accountable” means. It is no longer sufficient to show that funds were spent as intended. Increasingly, funders want assurance that the results being reported can be verified independently supported through data systems built to withstand scrutiny they were not originally designed for.
This changes what is being asked of implementation partners. Running a good programme is no longer enough; organisations must also be able to demonstrate, to an external party, that the programme delivers what it claims to. Implementation and evidence generation have become two distinct functions, and the second is often expected of organisations that are not resourced to build it.
The Funding Gap
Programme grants are typically earmarked for direct delivery costs: field staff, materials, and outreach. M&E, where it is funded at all, is usually a small line item – a data officer, a quarterly report, occasionally a dashboard. It rarely covers the organisational capacity needed to run monitoring as an independent function, with separate reporting lines and systems built for external scrutiny rather than internal reporting alone.
As a result, expectations and funding have moved apart. Funders are asking for more – verified data, real-time reporting, evidence that can withstand an audit. This is gathering momentum at a time when AI-enabled tools and tighter compliance requirements are raising the standard for what constitutes reliable data. At the same time, funding for the infrastructure that produces this data has remained largely unchanged: short-term, tied to programme outputs, and rarely allocated to institutional capacity.
This creates a structural gap: strong M&E capacity is increasingly a condition for funding, yet funding is needed to build that capacity. Smaller and mid-sized implementation partners are most likely to be affected, as their organisational systems have had the least opportunity to keep pace with rising expectations.
A Structural Issue, Not a Question of Trust
This pattern is sometimes read as funders not trusting NGOs, or NGOs resenting the scrutiny. That framing does not reflect the underlying dynamics well.
Funders’ interest in assurance is reasonable, given the increased scrutiny CSR funding now faces; an independent M&E function is a sound response to a genuine verification need. Implementation organisations are also reasonable when they note that they were not originally resourced to build this capacity. Both positions are consistent with the constraints each side operates under. The issue is not a failure of goodwill, but a mismatch between what funding instruments were designed to cover and what they are now expected to produce. This distinction matters: it points toward a solution based on better-designed funding instruments, rather than one based on rebuilding relationships.
Possible Ways Forward
If independent M&E capacity is becoming a genuine precondition for funding, it is worth considering how the capacity itself might be funded, not only its output. A few directions merit further discussion:
- Core or unrestricted grants could be explicitly positioned as capacity-building instruments, with M&E infrastructure named as one intended use, rather than folded into a general “overheads” category that is often underfunded.
- Funders investing in data assurance could direct part of that investment toward helping grantees build their own M&E function, rather than building parallel, external verification systems. Both approaches aim to produce data that funders can trust; the difference lies in whether that capability is built once, within the organisation, or reconstructed externally each cycle.
- A distinct funding category for MEL infrastructure that is sized realistically for staffing, systems, and institutional independence, rather than a year-end report which could be considered separately from programme costs.
- Pooled or intermediary funding mechanisms could allow multiple funders to co-invest in building M&E capacity across shared grantee organisations, rather than each funder addressing the assurance question independently.
These approaches do not replace the case for rigorous third-party evaluation, which serves a different purpose and cannot be substituted by internal M&E capacity alone. What this piece addresses is a more foundational need: the organisational capacity to generate monitoring data that an organisation can stand behind, independent of whether an external evaluation follows.
The sector has made progress in asking implementation partners for stronger evidence. It has made less progress in funding the systems that evidence depends on.
