So here are some ideas in short form that consider all kinds of data - trend, legitimacy, performance, outcome, digital exhaust - and how they can change philanthropy:
- Pattern finding - aggregated revenue and organization giving, coded by strategy or outcome, would allow us to see patterns. Find strengths, networks, gaps.
- Mash with other data - giving data mapped against health disparities, census, income, educational levels, second home ownership - you name it
- Turn online platforms into instruments for understanding - use online platforms as instruments to understand donor motivation, not just assume we understand their actions - bring persuasive tech, A/B testing, and behavior change knowledge to these platforms
- Network mapping - aggregate digital giving data to see networks of support, find influencers
- Predictive - does "flash mob" giving tell us anything?
- Predictive - which data on organizations actually influence donors? Which influence organizations?
- Predictive - non c3 actions and networks - which ones matter?
- Follow all money - a single dataset (or common taxonomy at least) of CSR, government contracts and grants, foundation dollars, development aid - real revenue understanding
- New revenue - data on impact investing, actual money flows would allow us to see if this is real, hype, or bubble. If real, code it all so Impact Investing data can be seen in light of bullet above
- Use geo-location data with volunteers to see who, what, how, where
- Use organizational information to improve program services (see datadives from DataKind)
- Create applications and software that improve sectors such as human rights work or disability services (see Benetech, TopCoder and SocialCoding4Good)
- Protect an open internet - see the Mozilla Foundation, Wikimedia
- Create fluid networks of activists - see SOPA/PIPA fight, #PDF12 for complete catalogue
- Open proposal applications - propose once, reach many (similar to Awesome Foundation structure)
- New forms of public service and geek volunteering - see CodeForAmerica, CrisisCommons, etc.
- "Liquid philanthropy" - mash up monitoring information from a PWX with feedback mechanisms such as "liquid feedback" to drive global engagement around water issues
- Form new forms - data backbone on an issue, used by shared communities of activists and donors - create 21c century organizations
- Video.
- Use funding platforms (everything from DonorsChoose to Kickstarter to SpaceHive) as "community assessments" - what are communities asking for? Same with foundation proposal processes.
- Find how (if) people move on a ladder of data engagement - from legitimacy to performance to outcomes
- Seed baseline repository of outcome data so can answer questions about organizational form and revenue mix by outcomes (down the road)
- Data communities, such as communitycommons.org
- Data as a public good - in the "next great natural resource race" over corporate/government ownership and personal privacy what is in the Digital Public Good commons?
- More coming on Wednesday on Data Philanthropy
- Add your ideas in the comments...
7 comments:
Getting closer to measuring impact: very hard to measure outcomes/impact/causality of a single nonprofit, especially a small one; but looking a whole set (say a portfolio of grantees) may get closer to determining if the money is moving the needle, especially when mashed with civic data.
Lucy, is that all you could think of?
This is a really great post and the telegraphic way in which you have delineated an enormous data agenda is really powerful. I really appreciate the challenge to the field to think far beyond the narrow focus on outcomes. The only real danger I see is that donors will send the people and organizations in whom they invest on endless data collection errands without, first, deciding what it is they want and need to know. But you are really pointing to something much larger than the investor-investee relationship: more like a social ecosystem, the life blood of which is data.
Brad
Well I only had 15 minutes to write the post so I may have left some ideas out. Really though - tomorrow comes the big ideas.
Your caution is KEY - if funders use data as yet another time-sucking errand in the funding power dynamic - what a waste.
Had an interesting conversation with Washington Post reporter about all this and was also reminded of the "digital divide" nature inherent in what's possible, who can afford it, who has skills. Also very important part of developing a "data agenda" for the field.
Thanks
Lucy
Exciting list, Lucy. Am not seeing any explicit "data derived from listening to beneficiaries" or something along those lines. The use of that kind of feedback/feedforward data -- not only evaluative, but prescriptive -- could be transformative. Might be assumed in many of the types you listed, but considering the number of stakeholder types that are called out (volunteers, organizations, donors, etc.) it seems an oversight to not call out "those on whose behalf the philanthropic action is being taken."
Christine
I am applying "hand to forehead" - thanks for noting this as an explicit addition. I agree completely -
Lucy
Hi Lucy, awesome post. Gaia Marcus from the RSA and I are developing software and social practices for network mapping and are incredibly excited about the value of making it possible to incorporate relationships into service delivery and the measured values of organisations.
http://civic.mit.edu/blog/natematias/social-mirror-tablet-tech-for-social-checkups
References:
"Power Lines" provides an overview of the RSA's thinking on networks and the Big Society: http://www.thersa.org/projects/connected-communities/power-lines
"India's HIV Orphans and Vulnerable Children" applies network analysis to assessment of regional health delivery: http://www.bu.edu/cghd/files/2012/02/IndiaOVCreport-100212-copy1.pdf
--Nathan Matias, MIT Media Lab Center for Civic Media
Where are data gathered or analyzed about the issues for the purpose of educating the public and policy debate on the nature and scope of the issues philanthropy works on? Doesn't the sector spends billions of dollars a year on this sort of thing?
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