Frequently Asked Questions
The basics
Why does Know Your Ground exist?
The principle is simple: where you stand shapes what you can do. Yet, far too often, charity advice is focused on generalised guidance which doesn’t reflect the structural reality of the sector. Some organisations are set up in ways that make one-size-fits-all advice really hard to follow.
Know Your Ground shows what’s realistic for each charity’s position relative to the wider sector.
What does a structural analysis look like in practice?
The starting point is that financial data can help determine a charity’s structural position relative to its peers within the sector. Each structural position contains a set of relative constraints on what an organisation can feasibly achieve. Each constraint is often a trade-off imposed by the reliance on different income streams relative to the sector as a whole. These trade-offs create the conditions which make some strategies more viable than others.
An organisation that relies almost entirely on government contracts faces very different pressures from one that lives off investment income or public donations. Structural analysis makes those differences visible and comparable across large cohorts of organisations.
Key takeaway — A charity’s structural position doesn’t determine every outcome, but it does make some strategic choices more viable than others.
Why does the data look different to what I was expecting?
Taking a structural view shifts our perspective significantly. The focus moves from absolute proportions within a charity to relative proportions between charities.
You can use weather as a way to understand the difference. Over a 10 day period might get 7 days of sun and 3 days of rain. Looked at on its own, it seems like it was mostly sunny and that is completely accurate. But if the same location at the same time of year usually had 9 days of sun and 1 day of rain, then you actually had rainer weather than you’d typically expect. Those additional days of rain likely changed what was possible for you to do in that period of time.
In the same way, we ofen look at income composition in absolute terms. But this can be misleading at a structural level if what looks like a small share of income is actually a much higher proportion of income than most other charities are working with.
Benchmarking against relative proportions can offer a fresh perspective that enriches traditional benchmarking against absolute proportions.
How does it work?
What are the four axes?
Every charity’s income is broken down into four axes:
| Axis | Description |
|---|---|
| Donation | Donations, legacies, and grants |
| Government | Government contracts and government grants |
| Investment | Returns on invested assets and endowments |
| Market | Fees for charitable services and trading income |
Is each axis independent of the others?
No, because that’s not how funding works in practice. The academic literature has increasingly demonstrated the “hybridity” of nonprofit funding and the axes are designed to capture this dimension, aligning cleanly with current sector discussions around income exchange versus non-exchange substance. The emphasis is on the strategic realities of different funding mixes rather than their technical accounting definitions.
For example, an NHS-funded service delivery contract would sit under both the Government and the Market axes. At the same time, Grant-in-Aid income to Arm’s-Length Bodies is captured under both Donation and Government to reflect the constraints imposed by this form of state funding.
Rather than boxing each income stream into a single, absolute category, this approach captures the operational trade-offs produced by the relative composition of income within and between charities.
What is an archetype and how is it assigned?
An archetype is a four-character label that summarises an organisation’s funding position. Each character represents one of the four funding streams, and it is either H (higher) or L (lower) depending on whether that organisation relies on that stream more or less than the benchmark median.
An organisation labelled LHLH has lower donation income, higher government income, lower investment income, and higher market income. One labelled HLLL is primarily donation-funded with lower income from everything else.
Key takeaway — Think of it like a postcode for funding mix. Just as a postcode tells you roughly where something is without describing every detail of the building, an archetype tells you the broad structural position of an organisation without describing every line of its accounts.
Why doesn’t the archetype description match my charity as I expected?
An archetype represents an ideal type rather than a hyper-specific description of each charity. A charity’s position on each axis will determine how much more or less relevant the overall characteristics of the archetype represent its funding mix.
This is where treating an archetype like a postcode helps with interpreting it. Just as the owner of a house sitting near the boundary between two postcodes might see themselves as closer to what’s typical for a neighbouring postcode than their own, so might a charity close to the median of the benchmark feel aligned to aspects of a neighbouring archetype.
What do “higher” and “lower” actually mean?
Higher and lower are always relative to the benchmark median across the cohort in a given year. The measure isn’t relative to a fixed, absolute number. An organisation is H on government funding if it receives a larger share of its income from government than the typical organisation in the cohort. It is L if it receives less.
This means the labels are about structural position, i.e. where an organisation sits in the landscape, rather than about the absolute size of any income stream. A charity receiving 25% of its income from government grants might be H one year and L another if the cohort average shifts, even if its own funding has not changed at all. However, to avoid large swings and disproportionate influence of outliers, a sufficiently large cohort is necessary for each analysis.
Why use a simple higher/lower split rather than more categories?
Because the underlying data supports it. When you look at how organisations are actually distributed on each funding axis, they do not spread evenly from 0% to 100%. They tend to cluster at the extremes. Most organisations receive either very little from government or a lot. There are very few in the middle, and the same is true for market, donations, and investments.
This means a higher/lower split is reflecting a genuine polarisation already present in the data rather than imposing an artificial division on a continuous spread. Organisations naturally separate into two groups on each axis and the threshold sits in the sparse middle ground between them.
A more complex system with three or four categories per axis would generate hundreds of possible combinations, most of which would contain too few organisations to be meaningful. The binary system produces sixteen real, populated archetypes that can be compared and tracked over time.
What are the limitations?
The approach is designed to benchmark large charities (those with annual income over £500,000) to understand how they fund themselves and whether that funding position changes over time. The method can be repurposed for smaller organisations, however this comes with some significant caveats on reliability and methodological challenges which complicate the benchmarking process.
Charities above £500,000 income move out of the simplified Tier 1 reporting bracket of the Charities SORP 2026 and must prepare more detailed accounts. Below that threshold, legal reporting is less detailed and often relies on cash accounting, making structural comparisons highly unreliable.
There is also a theoretical reason. Organisations above this size typically have the professional infrastructure, e.g. dedicated finance staff, strategic planning processes. These organisations are in a better position to make deliberate choices about their funding mix. Smaller organisations often take whatever funding is available that enables them to fund the mission. The £500k threshold identifies the population where funding strategy is a meaningful concept.
The free reports
How were the profiles selected?
The free headline reports use official Charity Commission data (2018–2025) covering the same cohort of charities across the full period. Each organisation needed to have generated an income of at least £10m across each annual return cycle and its annual returns were validated to remove a small number of charities whose submissions included inaccuracies and data integrity issues.
Can I request a free report for my charity?
No, because the headline reports are only designed to demonstrate the concept at a high-level.
In practice, far more meaningful analysis is possible when a custom cohort is developed which matches the realities of the organisation conducting the benchmarking. This can mean intentionally excluding significantly larger and smaller charities. It can also mean restricting the cohort to the specific cause or geographies in which a charity operates.
For those charities that already track performance against a set of peers, this group can be integrated into a Custom Profile to enrich the insights.
Looking for something else?
This page explains the basics in plain English. If you’d like to learn more about what’s included in a Custom Profile or the types of more tailored support that are available, take a look at the pricing page or get in touch directly.