The Best Impact Measurement Tools for Funders

Choosing the right impact measurement tool is one of the most consequential decisions a funder can make — not because the technology itself is transformative, but because the wrong choice creates years of unusable data, overburdened grantees, and boards who still cannot answer the question: "Is our funding actually making a difference?"

UK trusts and foundations gave over £8.2 billion in grants in 2023-24, a 12% increase on the previous year according to UKGrantmaking. Yet the sector's capacity to measure what that funding achieves has not kept pace with its generosity. Research from Plinth found that charities collectively spend an estimated 15.8 million hours per year on funder reporting — the equivalent of over 7,500 full-time roles — and much of that data goes underused. The problem is not that funders lack good intentions. It is that the tools and processes they use to collect impact data were often designed for compliance rather than learning.

The result is a paradox: funders ask for more data than they can analyse, while grantees produce reports that satisfy requirements but rarely capture the depth of their work. Good impact measurement technology should resolve this tension. It should make it easier for grantees to report, easier for funders to learn, and easier for both to demonstrate what works.

This guide is for programme officers, grants managers, and foundation leaders who are choosing or replacing impact measurement technology. It covers what to look for, what to avoid, and how the best tools balance rigour with proportionality.

What you will learn:

• Why most funder impact measurement fails and how to avoid common mistakes
• The key features to look for in impact measurement software
• How to balance rigour with proportionality in data collection
• How shared outcome frameworks reduce burden on both sides
• Where AI fits into impact measurement — and where it does not
• How to compare the main categories of tools available to UK funders

Who this is for: Programme officers, grants managers, foundation directors, and trustees choosing or reviewing impact measurement technology. Also relevant for charity infrastructure bodies advising funders on good practice.

Why Is Impact Measurement So Hard for Funders?

Impact measurement is conceptually simple — you want to know whether your funding made a difference — but operationally complex. Most funders face three overlapping challenges that technology alone cannot solve, but that the right technology can significantly reduce.

The first is the data collection problem. Funders depend on grantees to provide impact data, but grantees are already stretched. IVAR's research on proportionate grantmaking has consistently shown that reporting arrangements often become burdensome rather than useful. Their Funding Experience Survey, which gathered responses from over 1,200 charities, found that funded organisations spend too much time and energy second-guessing what funders want. The more foundations make their expectations visible and realistic, the easier it is for charities to report meaningfully.

The second challenge is aggregation. A funder running six programmes across 40 grantees might receive outcomes data in dozens of different formats — spreadsheets, PDF reports, email attachments, phone calls. Turning that into a coherent portfolio-level picture requires either enormous manual effort or a system designed for the task.

The third is use. Even when data is collected and aggregated, many funders struggle to translate it into action. According to research from NPC (New Philanthropy Capital), funders frequently collect impact data for accountability but rarely use it to inform programme design or strategic decisions. The gap between data collection and data use is where most measurement frameworks fail.

Good impact measurement tools address all three: they make collection easier for grantees, aggregate data automatically, and present it in formats that support decision-making.

What Should Funders Look for in an Impact Measurement Tool?

Not all impact measurement platforms are built for funders. Many were designed for individual charities measuring their own programmes, then adapted — often poorly — for funder use. A tool built for funders needs a different set of capabilities.

Shared outcome frameworks are essential. Funders need to define outcomes centrally and share them with grantees, so that everyone is measuring the same things in the same way. Without this, aggregation is impossible. Look for tools that allow you to create an outcome library, assign outcomes to specific funding programmes, and push those outcomes to grantee accounts automatically.

Proportionate data collection means the tool should support different levels of reporting for different grant sizes. A £2,000 community grant should not require the same monitoring form as a £200,000 multi-year programme. The best tools let funders configure reporting requirements by programme, grant size, or risk level.

Automated reminders and pre-filled fields reduce the chase. If a grantee's organisation details, grant amount, and programme outcomes are already in the system, the reporting form should pre-populate with that information. This saves grantee time and improves data quality.

Portfolio-level dashboards are what distinguish a funder tool from a charity tool. You need to see outcomes aggregated across your entire portfolio — by programme, by geography, by theme, by time period — not just one grant at a time.

Narrative alongside numbers matters. Impact is not purely quantitative. The best tools combine structured outcome data with qualitative evidence — case studies, beneficiary quotes, photos — and present both in a way that is useful for board reports and public communications.

How Do the Main Categories of Impact Tools Compare?

The market for impact measurement tools ranges from free survey platforms to enterprise grant management systems. Each category has strengths and limitations, and the right choice depends on your portfolio size, budget, and how integrated you need impact measurement to be with the rest of your grantmaking workflow.

Spreadsheets and online forms (Google Forms, Microsoft Forms, Excel) are where most small funders start. They work for a handful of grants but become unmanageable quickly. There is no aggregation, no automation, and every reporting cycle requires manual compilation.

Standalone survey tools (SurveyMonkey, Typeform) offer better data collection but lack funder-specific features. They cannot push shared outcome frameworks to grantees, do not provide portfolio dashboards, and require manual linking between surveys and grants.

Dedicated impact platforms (such as Salesforce Nonprofit with Impact Management, Socialsuite, or Upshot) focus specifically on outcomes measurement. They typically offer outcome libraries, benchmarking, and dashboards. However, they often sit alongside your grant management process rather than inside it, creating data silos.

Integrated grant management systems combine impact measurement with the rest of the grant lifecycle — applications, assessments, awards, monitoring, and reporting. This means impact data is collected in the context of the grant, linked to award details, and available alongside financial and compliance information. Tools like Plinth take this approach, combining shared outcome frameworks, automated monitoring forms, and AI-generated impact reports within a single platform that handles the full grant cycle.

How Can Shared Outcome Frameworks Reduce Burden?

One of the biggest sources of reporting burden is that every funder asks for different things in different formats. A charity funded by five trusts might need to report the same basic outcomes — people supported, hours delivered, satisfaction scores — five times, in five different ways. Shared outcome frameworks solve this by standardising what is measured across a funder's portfolio.

The concept is straightforward: a funder defines the outcomes they care about for each programme, and those outcomes are automatically included in grantee reporting forms. Grantees report against the same indicators, making it possible to aggregate data across the portfolio without manual reconciliation.

IVAR's six principles for better reporting emphasise this approach. Their first principle — "Be rigorous in agreeing what you need" — encourages funders to define reporting requirements clearly at the outset and avoid collecting data they will not use. Their third principle — "Be respectful in lightening the burden" — calls for funders to minimise duplication and accept existing evidence where possible.

In practice, a shared outcome framework works best when it is co-designed with grantees rather than imposed. The outcomes should align with what grantees are already measuring for their own purposes, and the reporting format should allow grantees to add their own context and narrative alongside the standardised data.

Plinth supports this through its shared outcomes feature, which allows funders to define outcomes at the programme level and push them to all funded organisations. Grantees see those outcomes in their own account and can report against them alongside any outcomes they track for their own purposes. The data flows back to the funder's dashboard automatically, aggregated and ready for analysis — without either side doing manual compilation.

What Role Does AI Play in Impact Measurement?

Artificial intelligence is increasingly present in grant management and impact measurement, but its value to funders is uneven. Some applications are genuinely useful today; others are more promise than practice.

Where AI adds real value for funders:

• Summarising narrative reports. Grantees often provide rich qualitative data in narrative form, but reading 40 end-of-grant reports to identify patterns is time-consuming. AI can summarise themes, flag concerns, and highlight success stories across a portfolio.
• Generating board-ready reports. AI can take structured outcome data and narrative evidence and produce a formatted impact report suitable for trustees, annual reports, or public communications. This saves significant programme officer time.
• Pre-filling reporting forms. Where grantee data already exists in the system — from applications, previous reports, or linked programme data — AI can pre-populate monitoring forms, reducing the time grantees spend on repetitive data entry.
• Identifying patterns across a portfolio. AI can surface insights that would take humans hours to find: which types of intervention produce the strongest outcomes, which grantees are outliers, or where results are weaker than expected.

Where caution is needed:

• Automated scoring of impact. Reducing a grantee's impact to a single score is fraught with risk. Impact is context-dependent, and automated scoring can penalise organisations working in harder-to-measure areas or with more disadvantaged populations.
• Replacing human judgement. AI can surface patterns and draft summaries, but decisions about what constitutes good impact, whether a programme should continue, or how to support a struggling grantee still require human judgement and relationship.

Plinth integrates AI across its monitoring and reporting features. Its AI agent, Pippin, can generate tailored funder impact reports from programme data, summarise outcomes across a portfolio, and produce reports in multiple languages and formats. The AI works from actual data in the system — attendance records, survey responses, outcome measurements, case studies — rather than generating content from thin air, which is critical for maintaining the reliability that funders and their boards require. For more on AI reliability in this context, see the guide on AI-generated impact reports and their reliability.

How Should Funders Approach Proportionate Monitoring?

Proportionality is the principle that monitoring and reporting requirements should match the size and risk of the grant. It sounds obvious, but in practice many funders apply a one-size-fits-all approach — the same monitoring form for a £3,000 small grant and a £300,000 multi-year programme.

Over 170 UK funders have now signed up to IVAR's Open and Trusting community commitments, collectively making grants worth over £1 billion in 2023-24 (IVAR, 2025). These commitments include reviewing reporting requirements to ensure they are proportionate and useful. The movement reflects a genuine sector shift: funders recognise that disproportionate reporting does not produce better data — it produces worse data, because overstretched grantees submit rushed, formulaic responses rather than thoughtful reflections on what they have learned.

A practical approach to proportionate monitoring involves tiering requirements:

• Light touch (small grants, low risk): A short end-of-grant form with 3-5 outcome questions and space for a brief narrative. No interim reports.
• Standard (medium grants, moderate risk): An interim progress report at the midpoint and a final report. Outcome data against shared indicators, plus a case study or beneficiary feedback.
• Enhanced (large grants, high risk or innovation): Quarterly or six-monthly reporting, detailed outcome data, independent evaluation, and learning reflections. Possibly a site visit or review meeting.

The key is that the tool you use should support this tiering without requiring you to build three entirely separate reporting systems. The best platforms let funders configure different monitoring templates for different programme tiers, with the appropriate level of detail built in. For a deeper treatment of this topic, see the guide on reducing the burden on grant applicants.

How Do You Turn Impact Data into Better Funding Decisions?

Collecting impact data is only worthwhile if it changes how you fund. Too many funders treat monitoring as a compliance exercise — data goes in, gets filed, and is never looked at again until someone asks a difficult question at a board meeting.

The shift from compliance to learning requires three things: accessible data, regular review, and a willingness to act on what the data shows.

Accessible data means dashboards that programme officers and trustees can use without exporting spreadsheets. The data should be filterable by programme, geography, and time period, and presentable in formats suitable for different audiences — detail for programme teams, summaries for trustees, narratives for public communications.

Regular review means building impact data into governance rhythms. If the board only sees impact data in the annual report, decisions are being made without it for eleven months of the year. Quarterly impact summaries give trustees the information they need to ask informed questions.

Acting on insights is where the real value lies. Impact data should inform decisions such as: Which programme models produce the strongest outcomes? Which grantees need additional support? Should funding criteria change based on what the data shows?

Plinth's dashboard features support this cycle. Funders can view aggregated KPIs across their portfolio, filter by programme or time period, and generate board reports directly from the dashboard. The AI reporting tool produces narrative summaries that contextualise the numbers. For more on centralised dashboards, see the guide on why funders need centralised grant dashboards.

What About Collecting Qualitative Evidence?

Numbers tell part of the story, but funders increasingly recognise that qualitative data — case studies, beneficiary voices, practitioner reflections — is essential for understanding how and why change happens. The challenge is collecting qualitative evidence at scale without creating an unreasonable burden on grantees.

Traditional approaches — asking grantees to write formal case studies in specific templates — are time-consuming and often produce stilted, formulaic narratives. Frontline workers are busy delivering services; asking them to become writers on top of everything else is a recipe for resentment and poor data.

Better approaches meet people where they are. Voice recording is one example: a project worker records a two-minute reflection after a session, and AI transcribes and structures it into a case study format. Photo evidence is another: a community group photographs their event, and the images are linked to attendance data and outcome records. Survey responses with open-text fields capture beneficiary perspectives in their own words.

Plinth supports several of these approaches. Its voice-to-case-study feature lets frontline staff record a conversation or reflection, which AI then transcribes and structures into a formatted case study. Its paper register scanning feature allows organisations to photograph a paper sign-in sheet, and AI extracts the attendance data automatically. These features reduce the effort required to produce qualitative evidence from hours to minutes, making it realistic for even the smallest grantees to contribute meaningful stories alongside their outcome numbers. For practical guidance on collecting case studies at scale, see the guide on how to collect charity case studies.

How Do You Ensure Data Quality and Security?

Impact data often includes sensitive information about vulnerable people — health outcomes, safeguarding concerns, demographic details. Funders have a responsibility to ensure that the tools they ask grantees to use meet appropriate data protection standards.

At a minimum, any impact measurement platform should offer:

• Encryption in transit and at rest for all data
• Role-based access controls so that staff only see the data they need
• GDPR compliance, including clear data processing agreements, the ability to handle subject access requests, and defined data retention and deletion policies
• UK or EU data residency — knowing where your data is physically stored matters for compliance and risk
• Audit trails showing who accessed or changed data and when

Data quality is a separate but equally important concern. The best tools build quality in at the point of collection: validation rules that prevent impossible values, mandatory fields for critical data points, and structured formats that reduce ambiguity. Pre-filled fields — where the system populates known information automatically — also improve quality by reducing manual entry errors.

For funders operating across multiple programmes, consistency is key. If one programme measures "number of people supported" and another measures "number of beneficiaries reached" but they mean the same thing, aggregation becomes unreliable. Shared outcome frameworks with clear definitions and standardised indicators solve this problem at source.

Choosing the Right Tool: A Practical Checklist

Selecting an impact measurement tool is a procurement decision, but it is also a design decision about your relationship with grantees. The tool you choose shapes what data you collect, how grantees experience reporting, and what insights you can extract. Here is a practical checklist for the evaluation process.

Before you evaluate tools:

• Define what you actually need to know (not what would be nice to know)
• Map your current reporting processes and identify the biggest pain points — for your team and for grantees
• Decide whether you need a standalone impact tool or an integrated grant management system
• Set a realistic budget, including implementation, training, and ongoing costs

During evaluation, ask:

• Can the tool support shared outcome frameworks that are pushed to grantees?
• Does it allow different reporting templates for different grant sizes or programmes?
• Can grantees access and use the tool easily, without training or technical expertise?
• Does it aggregate data across your portfolio into dashboards and reports?
• Can it handle both quantitative outcome data and qualitative evidence?
• Does it integrate with your existing systems (finance, CRM, board papers)?
• What are the data security and GDPR compliance provisions?
• Is there a free tier or pilot option so you can test before committing?

After implementation:

• Co-design reporting templates with a sample of grantees before rolling out
• Start with a small number of core outcomes and expand gradually
• Review whether the data you are collecting is actually being used — if not, stop collecting it
• Ask grantees for feedback on the reporting experience after each cycle

Plinth offers a free tier that allows funders to explore its impact measurement features before committing, which makes it possible to test whether the tool fits your workflow and your grantees' capacity. For a broader comparison of grant management platforms, see the guide on top grant management software.

FAQs

Do we need a bespoke impact framework, or can we use standard outcomes?

Most funders do not need a bespoke framework. Standard outcome libraries — such as those aligned with the outcomes approaches recommended by NPC or sector-specific frameworks — cover the majority of what funders need to measure. Start with standard outcomes and add bespoke indicators only where your programmes have genuinely unique goals. Building everything from scratch is expensive, delays implementation, and makes benchmarking impossible.

Can impact data be collected in real time?

Yes, if the tool supports online reporting forms with automated submission. Data appears on funder dashboards as soon as grantees submit their reports. However, "real time" in practice usually means "as frequently as your reporting cycle allows." Most funders use quarterly or six-monthly reporting, which means dashboards update at those intervals. Some data — such as attendance or survey responses — can flow in continuously if grantees are using a platform that captures it as part of service delivery.

How do we keep impact data safe and comply with GDPR?

Use a platform with encryption, role-based access controls, clear data processing agreements, and UK or EU data residency. Ensure the platform supports data retention policies and can handle subject access requests. Avoid collecting personally identifiable information unless it is genuinely necessary for your impact measurement — aggregated and anonymised data is sufficient for most funder reporting purposes.

How much should we expect to spend on impact measurement software?

Costs vary widely. Spreadsheet-based approaches are free but expensive in staff time. Dedicated platforms typically range from £3,000 to £30,000 per year depending on portfolio size and features. Integrated grant management systems with impact measurement built in often offer better value than buying separate tools for each function. Some platforms, including Plinth, offer a free tier for smaller funders or those wanting to pilot before committing.

What if our grantees are not digital-ready?

This is a legitimate concern. Not all grantees have the digital skills or infrastructure to use online platforms confidently. The best tools are designed to be simple enough for non-technical users, with clear interfaces, mobile access, and minimal training requirements. Some tools also support alternative submission methods — uploading existing documents, phone-based data entry, or paper form scanning — so that digital exclusion does not become a barrier to reporting. For a deeper exploration of this issue, see the guide on the digital divide in grantmaking.

Should we require all grantees to use the same tool?

It depends on your approach. Requiring a single platform makes aggregation easier but may impose burden on grantees who already use their own systems. A middle path is to define standardised outcome indicators and reporting formats, then accept submissions through the funder's platform while also allowing grantees to upload existing reports. The priority is consistent data, not necessarily a consistent tool.

How do we measure impact for capacity-building or infrastructure grants?

Capacity-building grants — funding for organisational development, training, or systems — are harder to measure because the outcomes are often indirect and long-term. Use a mix of self-assessed progress indicators (e.g., "To what extent has your organisation's governance improved?"), milestone tracking, and qualitative reflection. Avoid forcing capacity-building grants into outcome frameworks designed for direct service delivery.

How long does it take to implement an impact measurement system?

For a standalone tool with simple outcome frameworks, implementation can take 4-8 weeks including configuration and grantee onboarding. For an integrated system with complex reporting requirements, expect 2-4 months. The biggest variable is not the technology — it is agreeing internally on what to measure and designing proportionate reporting templates.

Recommended Next Pages

• Impact Measurement for Small Charities — Practical guidance for the grantees who will be reporting to you
• What Is a Theory of Change? — The foundational framework that should underpin your impact measurement approach
• Reducing the Burden on Grant Applicants — How to design proportionate processes across the full grant lifecycle
• AI-Generated Impact Reports: How Reliable Are They? — What funders need to know about AI in reporting
• Why Funders Need Centralised Grant Dashboards — The case for real-time portfolio visibility

Last updated: February 2026