The Strongest Predictor of Foundation Funding Growth Isn't Funder Count. It's Single-Funder Exposure.

In an earlier analysis, I showed that nonprofits with more foundation funders tend to receive disproportionately more foundation funding, even after controlling for organization size. But that was a snapshot. It could not tell us whether the pattern holds over time, or what drives it.

So I tested what happens over time.

What we did

I tracked about 82,000 nonprofits across three years of IRS 990 and 990-PF tax filings from 2023 to 2025, excluding donor-advised funds (DAFs), fiscal sponsors, and pass-through foundations to isolate direct foundation relationships.

At a high level, the earlier pattern still held: gaining foundation funders was associated with even stronger growth. But it was not the strongest signal.

What mattered most was how exposed the organization was to a single foundation funder: not as a share of foundation funding, but as a share of total revenue.

The exposure gradient

I measured each organization's top foundation funder's grants as a percentage of total organizational revenue (including earned revenue, government grants, individual giving, everything). The results form a smooth gradient:

Organizations whose top foundation funder accounted for less than 5% of total revenue were far more likely to grow their foundation funding than those with higher concentration. Those whose top funder exceeded 10% of total revenue saw median declines. At 35% or more, only about one in five grew their foundation funding.

To focus on organizations where foundation funding is a material revenue source, I narrowed the panel to nonprofits with at least $500K in revenue and foundation funding of at least 10% of revenue (24,600 organizations). The median dollar change tells the story:

These groups often had comparable numbers of funders. What differed was how exposed they were to a single relationship.

Why total revenue, not foundation funding?

We also tested foundation portfolio concentration: top funder as a share of total foundation funding rather than total revenue. For the broad population, it has almost no predictive power. Whether the top funder represents 30% or 85% of foundation grants, about 61% of organizations grew. The gradient is flat.

Foundation portfolio concentration does matter for organizations with $1M or more in foundation funding, where the internal distribution of dollars becomes material. But for the overall finding, organizational exposure (top funder / total revenue) is roughly nine times more predictive.

This makes intuitive sense. An organization whose top funder is 40% of total revenue is at real risk regardless of how many other funders it has. An organization whose top funder is 3% of total revenue barely notices if that funder leaves. The denominator matters.

What this is not

We tested the pattern across NTEE sector, geography, and organization size. It remained consistent.

But we also stress-tested the finding against 17 potential confounds across four rounds of analysis. The exposure gradient holds:

• Within every organization size band: from under $500K to over $25M in revenue
• Within the same funder count: among organizations with exactly 4-5 funders, 69% of the low-concentration group grew vs 17% of the high-concentration group
• Within every narrow baseline funding band: from $25K-$75K in foundation funding through $1.5M+
• Within every level of co-funder network connectivity: regardless of how many other nonprofits share funders with the organization
• After excluding spike-year organizations: 39% of the 35%+ band had an abnormally high 2022, and the gradient holds after removing them (though the magnitude decreases)
• After excluding organizations funded by the 50 largest declining foundations: foundation-side supply shocks affect all bands proportionally
• With or without DAFs included, and with or without significant government funding

What drives the difference

When I decomposed funder turnover, I compared organizations with lower foundation concentration (top funder under 40% of foundation funding) to those with higher concentration (top funder over 60%). Both groups gain and lose funders at roughly similar rates. The difference is in the dollars.

Diversified organizations do not just have more funders. They pair strong relationships with strong systems. At most size levels, the median diversified organization lost zero dollars to funder departures. Their key relationships were retained, and when turnover did occur, incoming funder dollars exceeded departing funder dollars 65-74% of the time. The loss of a single funder was typically immaterial.

Concentrated organizations experienced real dollar losses to departures at every size, and incoming dollars exceeded departures only 41-66% of the time.

Among large nonprofits ($25M-$100M in revenue) with meaningful foundation dependency, the contrast is stark: diversified organizations saw median growth of +$1.1M, with 4.5% experiencing severe decline. Concentrated organizations of the same size saw median losses of -$4.1M, with over half experiencing severe decline.

Network effects are real but secondary

I also tested whether co-funder network position explains the concentration result. It does not. Concentration is roughly 5 times more predictive than any network metric.

However, one network variable showed real secondary signal: the bridge score, which measures whether an organization's funders connect to distinct funding communities rather than overlapping ones. Within the same concentration band, organizations with higher bridge scores were 10-13 percentage points more likely to grow their foundation funding. But bridge score cannot overcome high dollar concentration.

Diversification is a long-term strategy

I also examined whether concentrated organizations can transition to lower concentration over time. The answer is nuanced.

Over the three-year window, 69% of organizations starting in the 35%+ band moved to a lower concentration band. But their median funding change was -81%. They did not diversify by building new funder relationships. Their top funder left or cut back, and funding collapsed.

Organizations that stayed in the 35%+ band actually did better (50% grew) than those that "escaped" (2% grew).

This suggests that concentration changes over a short window are driven by funder events (acquisitions and departures), not by gradual portfolio diversification. Intentional diversification likely operates on a 5-10 year timescale. An organization building new $10K-$25K foundation relationships today would not meaningfully shift its concentration ratio against a $1M anchor funder within two or three years.

Implications

Foundation relationships do appear to compound over time. But the compounding works in both directions:

Low exposure compounds growth. High exposure compounds risk.

For development teams, the implication is that managing single-funder exposure may be more important than simply adding new funders. The data suggests this is a long-term structural imperative, not something that can be addressed in a single grant cycle.

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Full methodology and robustness testing

Panel: ~82,000 nonprofits present in all three years of IRS 990 and 990-PF tax filings (tax years 2022-2024, filed 2023-2025) with at least one matched foundation funder. Chart population narrowed to 24,600 nonprofits with $500K+ revenue and foundation funding >= 10% of revenue.

Exclusions: Grants from DAFs (Fidelity Charitable, Schwab Charitable, Vanguard Charitable, etc.), fiscal sponsors, and other pass-through foundations excluded (~2,763 foundations removed) to isolate direct foundation relationships.

Exposure measure: Top funder's grant total divided by total organizational revenue (all sources, from most recent 990 filing). This measures organizational exposure, not foundation portfolio concentration. We also tested top funder / total foundation funding as an alternative; it has roughly one-ninth the predictive power and shows a flat gradient for most organizations. Foundation portfolio concentration only predicts outcomes for organizations with $1M+ in foundation funding. Validated against an independently-sourced IRS income classification (71% band agreement, near-identical gradient).

Robustness checks (17 tests across 4 rounds):

Strictest combined filter: Excluding spike years, requiring recurring top funder, baseline >= $10K, 2+ funders: gradient is +129% to -29% (74% vs 30% grew).

Spearman rank correlations with funding % change:

| Predictor | |rho| | |---|---| | Organizational exposure (top funder / total revenue) | 0.68 | | Baseline funding | 0.56 | | Funder count | 0.26 | | Bridge score (network diversity) | 0.12 | | Foundation portfolio concentration (top funder / fdn funding) | 0.07 | | Total peers (network degree) | 0.05 | | Jaccard (network insularity) | 0.00 |

Caveats:

• Survivorship bias: organizations that lost all foundation funders exit the panel. Dropout rate is highest (29%) for the most concentrated band, meaning reported outcomes understate risk.
• Regression to the mean inflates the magnitude of decline for the 35%+ band. After excluding spike-year organizations, the decline is approximately -30% rather than -55%.
• Partial mechanical correlation: concentrated organizations are mechanically more exposed to the departure of their top funder. The gradient holds even when the top funder stays, but is amplified when they leave.
• Concentration transitions over the 3-year window are driven by funder events, not gradual diversification. The observation window is too short to measure intentional long-term diversification strategies.
• Correlation, not causation: organizations with stronger programs and leadership may both attract funders and grow funding.
• Three-year observation window: we cannot confirm whether these patterns are structural or period-specific.

Data source: SciRise Foundation Intelligence dataset