How pooling our data can build our collective intelligence Ways to have your cake and eat it!

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How pooling our data can build our collective intelligence Ways to have your cake and eat it!

Transcript of How pooling our data can build our collective intelligence Ways to have your cake and eat it!

Page 1: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

How pooling our data can build our collective intelligenceWays to have your cake and eat it!

Page 2: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

Overview• What is comparative & collective data and what is it good for?• Common Data Traps• What benefits are accruing to those who DO benchmark?• What other sources of data can I make use of?• A few tips for making best use of these data sources• A look at some data• An overview of who else is interested in benchmarking in the

third sector

Page 3: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

What is comparative data• Your data compared confidentially and anonymously vs. your

peers• Financial data (profit & loss, balance sheet), social impact data

etc• It’s nothing new - Keynote, Mintel and other published reports• Online benchmarking .. is newer but we’ve been doing it since

late ’90’s so not that new!

Page 4: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

What is comparative & collective data good for?Internal goal setting:• Seeing where you are strong (vs. your peers)• Seeing what needs improvement• Diversifying income and/or managing cost• Setting targets that are more than ‘plus a bit/minus a bit’

To stakeholders, funders etc:• Stronger funding applications• Galvanizing Volunteers & Members• Communicating your achievements

Page 5: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

What is comparative & collective data good for?With trade bodies and professional organisations:• Identifying areas where support or development is required• Monitoring trends and the impact of sector development

activities

For the non-profit culture sector as a whole:• Communication of the overall contribution to GDP (or it would

be if we had a total for the turnover of the sector)• Lobbying to the Treasury by DCMS and others

Page 6: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

Common Data Traps• Lack of data on peers • Lack of data that is sliced by region, sector, size, role in

ecosystem• Focus only on the best practice of the large organisations and

expecting this to be relevant to small & non-venue based organisations

• Filling in surveys but not holding the survey owners accountable for the usefulness of results reporting

• Too long a delay between survey completion and results publication/access

• Using above as excuses to not bother comparing progress and over reliance on qualitative arguments

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What benefits are accruing to those who DO benchmark?• Pragmatic and realistic goal setting for new areas of income

development e.g. donations & sponsorship• Greater clarity on how a business model may change as an

organisation grows e.g. changes from <£200k to £750k to £2m• More detailed understanding of how the ‘best in class’ achieve

their successes• Succinct summary of greatest weaknesses and risks• Development of key comparison points for their organisation

so that staff and board can track these regularly• Greater visibility with and respect from funders• Seen as leaders who are using all the resources available to

them to continue to develop their organisation in a tough climate e.g. Common Practice

Page 8: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

What other (collective) data can I make use of ?

Data Source Use

Arts & Business Comparison of private giving – details by region, size of organisation and art form

National Campaign for the Arts National headlines on approx. 20 key indicators

Charity Commission Report & accounts information on thousands of arts non-profits

ACE RFO statistics (or the equivalent for Scotland, NI and Wales)

Headlines for financial, governance and audience comparisons but mostly national totals not per organisation stats

NCVO Annual data in their almanac based on 80,000 charities, headline level only

Trade body annual reports and survey results

Sector specific reports on key issues, trends and progress

Page 9: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

A few tips for making best use of these sources:• Think of the key types of comparison that would be most useful to you

e.g. by turnover, venue/non-venue, art form, location etc

• Decide whether any of these are mutually exclusive (if so you’ll need more than one comparison group)

• Come up with a list of the best sources for information on these topics or companies

• Come up with a list of key organisations to compare yourself to

• Pull together the data on these topics and organisations into a single spreadsheet …. If you don’t then the different definitions and layout of the information will hinder analysis

• Report on the findings to your staff and Board at least once a year, quarterly if the data changes more frequently or is a live issue.

Page 10: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

West Midlands vs. M’chester, N’castle & London (2010 data,

in the arts)

Page 11: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

Sample Size:Income Source (as % of income)

London <£5m t/o

West Midlands Newcastle Manchester

No. orgs in data set 43 25 11 8

Average revenue turnover £989k £3.56m £4.08m £1.75m

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Grant Income:Income Source (as % of income)

London <£5m t/o

West Midlands Newcastle Manchester

ACE RFO/NPO 49.7 43.3 41.8 39.8

ACE funding 9.3 7.8 4.1 8.8

Trusts & Foundations 13.6 6.9 3.5 4.6

Local Authorities 10.1 14.6 4.7 12.2

Grant in Aid 9.1 0 0 44

Other Gov’t Grants 26.4 4.7 35.8 30.9

Total Grant Income 63.9 59.1 52.6 61.6

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Earned Income - Venue:Income Source (as % of income)

London <£5m t/o

West Midlands Newcastle Manchester

Ticket Sales 17.4 29.5 35.6 24.4

Shop & Retail 15.1 8.0 9.8 4.7

Café & catering 5.1 2.8 3.7 5.5

Space Hire 12.4 2.5 21.1 4.4

Total venue based income 23.4 29.0 49.4 29.6

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Earned Income - Non-Venue:Income Source (as % of income)

London <£5m t/o

West Midlands Newcastle Manchester

Corporate Sponsorship 5.6 1.2 1.2 1.7

Private Donations 4.3 0.5 2.2 0.8

Other sponsorship & donations 7.1 5.5 0.7 1.3

Royalties 0 1.2 0 2.0

Product Sales 11.3 2.9 10.5 0.1

Services & consultancy 10.4 6.6 1.0 18.4

Ticket Sales (other venues) 18.7 20.3 1.3 8.9

Subscriptions & membership 5.2 0.3 0.5 4.0

Contracts 10.7 25.5 0 0

Total non-Venue, non-grant income

27.6 31.8 15.8 20.0

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Costs:Costs London

<£5m t/oWest Midlands Newcastle Manchester

Total Direct Costs 40.4 38.8 45.9 30.2

Total Salaries (ex NIC & Pensions 33.9 39.1 30.4 44.2

Pensions 1.3 2.7 1.6 3.3

Marketing 3.6 3.7 6.8 2.9

Total Revenue Expenditure 98.3 103.0 104.2 104.3

Surplus/Deficit 4.0 -3.0 -4.8 -4.3

Page 16: How pooling our data can build our collective intelligence Ways to have your cake and eat it!

Who else is interested in benchmarking in the third sector?• NCVO, Charity Finance Group• Big Society Capital, Big Issue Invest and other social investors• Paul Hamlyn Foundation and other trusts & foundations• Core Cities group & assorted Local Authorities• Various Arts Councils and Creative Scotland