Mapping community foundation success factors

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					WINGS Forum 2006
Satellite Meeting WINGS-CF

The really exciting thing about this presentation is that the work I am going to talk about
grew out of a presentation made at the Global Forum of Community Foundations held in
Berlin in December 2004, in which WINGS was involved. This sort of gathering provides
a great opportunity to gain ideas and inspiration about dilemmas or issues that one is
trying to think through, whether as a practitioner, researcher, adviser or funder.

In this presentation, I will first explain why this project came about, give an overview of
the methodology and then explain what the findings have meant for us in Australia using
some examples.


The groundbreaking research presented by Prof Renee Irvin by the University of
Oregon, The Invisible Hands of Altruists: A Study of Community Foundation Economics,1
identified several socio-economic factors that are present in a community supporting a
financially successful community foundation in the US. More about the actual success
factors in a moment.

The idea that one could apply some sort of logical framework to working out where
community foundations could be most successful held my attention.

At home in Australia, I had been working with the Foundation for Rural and Regional
Renewal (FRRR) and community foundations themselves to build a community
foundation movement in Australia. However, we had hit a number of really challenging

One issue was the very small pool of philanthropic funding available to seed the start up
of community foundations. We just did not – and still don’t! - have a Charles Stewart
Mott Foundation or a Ford Foundation or a Kellogg Foundation. Australia has a smaller
philanthropic sector with only a few foundations having a real interest in developing
philanthropy, including community foundation, more generally.

Even the most supportive foundation, the Foundation for Rural and Regional Renewal,
had limited grantmaking funds and a Board that didn’t want the community foundation
program to become a ‘black hole’. How many times had I heard the dreaded words
“opening the floodgates”?! FRRR has played an important role in seed funding many
community foundations in rural Australia since 20000 and is still doing this, although on
a reduced scale. It continues to fund community foundations within its other program
areas, eg rural education and youth philanthropy programs.

 The Invisible Hand of Altruists: a study of Community Foundation Economics, University of
Oregon, Prof Renee Irvin PhD, Draft 2004

Given the limited seed funds available, there was clearly a need to find some more
targeted basis for making grants to new community foundations. The objective was to
find a way to plan where seed funding could most usefully be spent.

So the University of Oregon study gave me the idea of applying the success factors that
they had identified in the US to the Australian situation – and to see if it came up with a
useful result.

I would like to note that this research focused on the financial capacity of community
foundations, not on their capacity as community builders. Most rural community
foundations in Australia are active community builders as well as grant makers.

Before I go into the factors and the Australian results, I want to add a proviso. It is
possible that a successful community foundation could be established in a less likely
region if other influences are at play. These factors might be outstanding local leadership
and perhaps a key donor, maybe even a donor that gives back to his or her roots but
now lives in Melbourne or Sydney – or even elsewhere in the world.



So let’s first look at the initial study before moving on to how I applied the findings to
Australian data.

The Invisible Hand of Altruistic – a study of Community Foundation Economics by the
University of Oregon, led by Prof Renee Irvin, applied detailed census data over
community foundation asset data to identify whether there were determinants which
linked with the establishment of financially successful community foundation.

The study linked a database of 640 community foundations listing location and asset
size with US state, city and county-level census data on:
    • Income from various sources;
    • Age;
    • Ethnicity;
    • Education level;
    • Population density; and
    • Population stability.

In summary, the factors that did indicate likely success were:
    1. A stable population;
    2. Higher geographic density; and
    3. A highly educated population.

“..Mobility and density of the population interact when they are measured against
community foundation assets.”2

 The Invisible Hand of Altruists: a study of Community Foundation Economics, University of
Oregon, Prof Renee Irvin PhD, Draft March 2005

Perhaps surprisingly, overall neither level of income nor level of wealth was a
determinant of successful growth of community foundations or their assets.

In discussions after the Global Forum, Prof Irvin recommended that the age of the
population (i.e. % of the population over 65 years) should also be included as a factor
as an older population is also a factor for success in the US context.


The next step was to apply the study in reverse using Australian data i.e. to review the
Australian data against each success factor or determinant to identify which regions
could best host a community foundation. FRRR generously agreed to pay for the special
reports from the Australian Bureau of Statistics and to contribute towards the time I
spent working on the analysis.

The project was approached in the following stages. This section may seem a little dry
but it led to some very practical results – and I became more adept at the science and
art of economics!


The indicators for success were confirmed with Prof Irvin. Suitable measures were

The Australian Bureau of Statistics was contacted to discuss what useful data sets were
available to examine the four factors, and what reports could be generated. I even met
with them as the project seemed a bit outside their usual bread and butter work!

Stage 2

Research was commissioned from ABS Consultancy Services to analyse census date
by statistical divisions (several local government areas) against agreed indicators. This
stage involved telephone calls with ABS to talk over progress of the reports.

Stage 3

This is where the rubber really hit the road!

Each data set was analysed and quartiles established for each indicator. I emailed Prof
Irvin a few times at this stage to get some advice about what would be the best
approach to developing the ranking system. The ranking system is explained in the
following table.

Factor        Measure             Ranking 1    Ranking 2     Ranking 3      Ranking 4

Education     % of the            0-9.9%       10-19.9%      20-29.9%       30%+
level         population with
              degree or

Population    Population per      50-249       250-499       500-749        750+
density       1,000 sq km

Population    % of the            30-39.9%     40-49.9%      50-59.9%       60%+
stability     population living
              in the same
              house for the
              past 5 years

Population    % of population     0-3.5%       3.6-6.9%      7-9.9%         10%+
age           aged over 65

Current data for Australia provided by the Australian Bureau of Statistics was analysed
against the indicators and each statistical division was assigned a ranking against each
factor using four quartiles. Each indicator was weighted equally. The cut off points were
chosen to reflect the spread of results in each area. A final overall score calculated.
Areas with 10 or more out of a possible 16 scored very well. Areas of 8 or 9
demonstrated some positive factors. Areas ranking 7 or below would find it difficult
to support a financially robust community foundation.


The first thing to understand about Australia is that we have large areas of very low
populations. Half the area of the continent contains only 0.3% of the population, and the
most densely populated 1% of the continent contains 84% of the population. The
distribution of Australia's population is shown in map 1 (below).

As mentioned, the highest possible overall score was 16. The highest actual ranking was
13 (i.e. 81.25%) for Inner Western Sydney, Lower Northern Sydney, and Boorondara
City (in Melbourne).


The results confirmed several of our experiences trying to support the start up of
community foundations.

Case Study 1: Central Queensland

Despite seed funding from the Foundation for Rural and Regional Renewal in 2001/02
and local support from the Area Consultative Council, Central Queensland Community
Foundation started with a bang, and is now struggling.

If you look at the Success Factor rankings for the region, it begins to explain why the
area is not an easy one for establishing a community foundation. These are low scores.

                         Rockhampton            Fitzroy Statistical   Gladstone Statistical
                         Statistical Division   Division              Division
Education Level                    1                       1                    1
Population Density                 0                       0                    0
Stability ranking                  3                       2                    2
%over 65 years                     3                       2                    2
Overall Ranking
                                  7                         5                     5

Case Study 2: Darwin & Northern Territory

Despite offers of seed funding and several visits by Philanthropy Australia, a Northern
Territory or Darwin Community Foundation has simply not emerged. This is not now so

                        Darwin               Litchfield Shire         Daly Statistical Division
                        Statistical Division

Education Level                   2                        1                       1
Population Density                1                        0                       0
Population Stability              2                        2                       4
% over 65 years                   1                        1                       1

Overall Ranking                   6                        4                       6

                                                                                 continued over/

Case Study 3: Melbourne and Boroondara Community Foundations

By contrast, both these community foundations have done well and achieved a relatively
high total score, out of a potential total of 16 points.

                            Northern Middle         Eastern Middle              Boroondara City
                               Melbourne               Melbourne               Statistical Division
                           Statistical Division    Statistical Division

Education Level                      2                       3                              4
Population Density                   3                       2                              3
Population Stability                 4                       4                              3
% over 65 years                      3                       3                              3

Overall Ranking                      12                     12                          13


Case Study 4: Greater South West Community Foundation (Victoria)

Following a feasibility study and several years of local discussions and planning, FRRR
provided seed funding for this community foundation in October 2006. We will follow
developments with interest.

                         Warrnambool       Hopkins                   Glenelg
                         City              Statistical Division      Statistical Division
Education Level                  2                     1                           1
Population Density               1                     0                           0
Population Stability %           3                     4                           4
over 65 years                    3                     3                           3

Overall Ranking                  9                     8                           8

A feasibility study was also approved for the Fleurieu Peninsula in South Australia which
had rated reasonably well.

Case Study 5: Tasmanian Community Foundation

Tasmanian Community Foundation is ten years old. It has made some wonderful grants
and focused a great deal of its work on funding youth projects, and most recently
working with a youth philanthropy advisory group. However, the wonderful Executive
Officer burnt out a year ago and the last remaining Board Members have also run out of
energy. The environment is not easy in Tasmania and that data is helping us think
through the best form of support from here on. The two highest scoring regions in
Tasmania were North Eastern and Great Hobart, both with only a score of 8.

                             North Eastern                     Greater Hobart Statistical
                             Statistical Division              Division

Education Level                              1                                 2
Population Density                           0                                 0
Population Stability %                       4                                 3
over 65 years                                3                                 3

Overall Ranking                              8                                 8

In summary, the findings from this research have been useful. They have explained why
some community foundations have not taken off. They explain why some have! They
have helped target seed and feasibility study funding and are providing some useful
information about reviewing how the Tasmanian Community Foundation will move
forward from its current difficult situation.

Catherine Brown
Philanthropy Consultant

Prof Renee Irvin, the author of the original research by the University of Oregon, can be
contracted on

        Source ABS, Table 5.13 Distribution of Population Source: 2000 Year Book Australia, ABS Cat No. 1301.0;


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