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· Private foundation

Ann J & Edward P McKenna Foundation

Its FY2019 filing reports that it funds preselected organizations and did not take unsolicited requests; check the foundation's own site before ruling it out.

$29k
Granted FY2019
3
Grants FY2019
2
States reached
$23k
Largest
01What it funds
0194% classified

What it funded, over time

Every grant placed by its stated purpose and the recipient’s mission, by year, FY2017 to 2019.

Human Services$31kEnvironment$6kReligion$2kPhilanthropy$1kEducation$850Youth Development$500Arts & Culture$250Crime & Legal$100Other$0
02FY2019 · 3 grants

Where the money goes

Grants by size, and the largest recipients.

By grant size · FY2019

  • Under $10k2 grants · $6k
  • $10k–50k1 grant · $23k
$5,000
Median grant
2
States reached
$0
Total assets
Largest grants
RecipientAmount
CASA de la MISERICORDIA PRO-VIDA AC$23,000
PEASE DAY 365$5,000
COOL CAP FUND$500
02The need
03

Does the money reach high-need areas?

Each grant placed by the hardship in its grantee’s ZIP, against the area’s typical level.

show:

Its human-services grants (FY17–17, $1k) land where the poverty rate runs at 14%, against an area that typically sits at 12%. 100% of those dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 12%SANCTUARY OF HOPE: $1k → 14%0%20%40%50%more need →
grant to an above-average-need area below average· circle size = grant amount
How this is measured
Matched: human-services grants are those whose grantee’s IRS cause code is Human Services. Placed by people below the poverty line in the grantee’s ZIP, averaged from the tracts in that ZIP.
How this is measured
US grants placed by each grantee’s ZIP, which can differ from where services are delivered. Need from public data (U.S. Census/ACS, CDC PLACES, Eviction Lab, USDA), shown as context about the area, never attributed to the funder’s giving.
03Its grantees
repeat funding

Who it funds again

Organizations funded in more than one year, against those funded once.

8%of every dollar goes to organizations it has funded before.
$3k · 3 repeat orgs$38k to everyone else

3 repeat relationships: 1 still active in FY2019, 2 since wound down; 2 grantees were first funded in FY2019 (too recent to call).

How the two cohorts compare

Re-uppedFunded once

Organizations

3
9

Total granted

$3k
$10k

Median revenue growth · since first grant

+767%
+1787%

Still filing today

33%
44%

New vs renewed · share of each year

In FY2019, 2% of grant dollars renewed an existing relationship; $28k went to new ones.

50%100%’17’18’19
RenewedFirst-time

Where new relationships form · theme of each grantee’s first grant

’17’18’19
Arts & CultureHuman ServicesPublic Safety & DisasterOther
How this is measured
First-time means a grantee’s first year in the filing window; renewed means funded in an earlier year too. The renewed share climbs naturally as a portfolio matures, so the signal is a year that bucks it (a wave of new grantees). The earliest year is left-censored: relationships that predate the data read as new. Theme is the grantee’s IRS cause.

Backed again, and grew

  • IC
    IMMACULATE CONCEPTION
    2× · 2017–2018 · $2k
  • CF
    COOLCAP FUND INC
    2× · 2018–2019 · $1k · revenue +767%
  • CS
    CORP SERV NEVADA
    2× · 2017–2018 · $250

Funded once

  • P
    PVBLIC
    one grant, 2018 · $5k
  • CD
    CASA de la Misericordia orphanage
    one grant, 2018 · $2k
  • SO
    Sanctuary of Hopegraduated
    one grant, 2017 · $1k · revenue ×19
How this is measured

Repeat means funded in two or more distinct years. Growth and survival are read from each grantee’s own subsequent IRS filings.

04Its field
04the grantee network

5 grantees tracked through their own filings, 2017–2025.

Each grant beside the grantee’s revenue from every source, year by year.

How this is measured

Counted here: distinct organizations funded across 2017 to 2025, not grant rows in a single year, so this will not match the grant count on the cover. 5 of the 14 grantees resolved in that span have returns of their own we could reconcile.

Each grantee is resolved to its own IRS returns. Association, dated; never a causal claim.

0
Load-bearing (≥25% of a budget)
5
Early backer (in before they grew)
5/5
Grantees still filing
5/5
Grew since first funded

Where the money sits, by cause and then by grantee

CASA de la MISERICORDIA PRO-VIDA AC: $23,000 · OtherCASA de la MISERICORDIA PRO-VIDA ACPEASE DAY 365: $5,000 · OtherPEASE DAY 365PVBLIC: $5,000 · OtherPVBLICIMMACULATE CONCEPTION: $2,150 · OtherIMMACULATE CONCEPTIONCASA de la Misericordia orphanage: $1,500 · Other+5 more: $2,300 · Other+5 moreSanctuary of Hope: $1,000 · Human ServicesGET LIT - WORDS IGNITE INC: $500 · Arts & CultureAMAZING GRACE CONSERVATORY INC: $250 · Arts & CultureWESTSIDE COALITION: $500 · Public Safety & Disaster
Other$38,950Human Services$1,000Arts & Culture$750Public Safety & Disaster$500

Each grantee by its size and the funder’s share of it; top left is load-bearing

25%50%75%100%$1.0Mgrantee revenue →↑ funder's share of their budgetSanctuary of Hope: $1,000 over 1y, 0.4% of budgetGET LIT - WORDS IGNITE INC: $500 over 1y, 0.0% of budgetWESTSIDE COALITION: $500 over 1y, 4.4% of budgetAMAZING GRACE CONSERVATORY INC: $250 over 1y, 0.1% of budget
Grantee by grantee: a decade per organization, before and after funding

A decade per grantee: revenue shaded, grants as bars, all rows on one timeline.

  • Who funds Sanctuary of Hope ↗
  • Who funds COOLCAP FUND INC ↗
  • Who funds GET LIT - WORDS IGNITE INC ↗
  • Who funds WESTSIDE COALITION ↗
  • Who funds AMAZING GRACE CONSERVATORY INC ↗

How much its grantees rely on government

Each dot is one organization Ann J & Edward P McKenna Foundation funds: left to right is the share of its income from government, bottom to top the share from Ann J & Edward P McKenna Foundation. Bigger dots raise more.

2023
’20’21’22’23’24’25
no gov · 10%0%1%3%5%funder's share of their income ↑0%6%13%19%25%share of the org’s income from government →
    no gov moneyreceives it· size = income
    1get no government money at all
    1report government grants on their 990 we could not trace to a source (not plotted)
    0rely on government for over half their income
    ⤢ axis zoomed · 0–25%
    typical government reliance, FY20–25
    How this is measured
    Government income is each org’s traced federal awards (USASpending grants and contracts) plus state payments (open checkbooks) as a share of its total revenue (IRS Form 990); the self-reported government-grant line (990 line 1e) is carried for cross-check: a grantee that reports government grants we could not trace to a source is left off the chart rather than shown as receiving none. An association, not a claim that a grant caused the public funding. Coverage is precision-first, a floor rather than a census; state records exist for 9 states, so a grantee outside them shows no state figure (dimmed) rather than a false zero. Federal award amounts are obligations, which can span years, so a single-year share is indicative. 990 filings lag 12 to 24 months.

    On method. Every financial figure here is read from IRS e-file XML, the funder’s own 990/990-PF, and from the multi-year returns of the 14 grantees we resolved, each linked to its source. Grantee outcomes are each organization’s own program-service reporting (Form 990, Part III), read as association with funding, never as caused by it. Low-confidence name matches are suppressed rather than guessed. How we build these →

    How this is measured
    Each figure carries one of six labels. Filed is what the funder reported on its return. Official is another government record about an organization, such as a federal award or a charity register, joined by name where no shared identifier exists. Resolved is an identity we worked out where the filing named a recipient without an EIN, kept only above a measured confidence threshold. Computed is arithmetic over those, like themes, portfolio clusters and co-funder strength. Context is a statistic about a place rather than about an organization, which is what the need overlay is: it describes the area a grantee’s address sits in, not where its work lands. Inferred is drawn by a model from text, like the partnerships read out of public news and organization websites. Each is labeled where it appears.

    Generated from the IRS Form 990-PF e-file return for fiscal year 2019, released 2019. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Source object · view filing

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