Sense Making in the New Data-Scape

An edited version of this post is available on the SSIR Opinion Blog. The version below is unedited.

Some things are so obvious they are hard to see. For example, why do we make change organizations go looking for funders instead of having funders go look for change organizations? Now, wait just a minute, I hear you saying, funders do go looking for change organizations. Foundations hire professionals to do this. When they develop strategies and write papers, hire consultants to do environmental scans and needs assessments, post guidelines, accept applications and do site visits, that is exactly what all those folks are doing - looking for organizations to fund. And you’re right, that is what all those people are doing.

On the other hand, individual donors, small and large (and some foundations) go online, type in search terms on any one of a variety of sites and can find loans to make (Kiva), actions to volunteer for (allforgood), petitions to sign (Care2), projects to fund (NetworkForGood, GlobalGiving), teachers to support (DonorsChoose), grants to match (PowerPhilanthropy, DonorEdge), social entrepreneurs to support (socialenterprise API, coming soon) or all of the above (socialactions). In these cases organizations, enterprises, entrepreneurs, teachers, activists have filled out a form, tagged it correctly, the information has been vetted, and is posted for anyone interested to search for and find.

In the foundation case, many of the same steps are being taken, but the information is done in a series of “one-offs.” Foundation A does research, develops a strategy, posts guidelines, seeks applicants, rejects many, and funds a few. File. Revise. Rinse. Repeat.

With very few exceptions, Foundations B and C and D, individual donors X and Y, donor advisers Q and W, and corporate funders E, F, G – all of whom are interested in the same issues and goals as Foundation A each repeat some variation on the same work that Foundation A did. And the organizations within this sphere of work revise and re-calibrate their applications as best they can guess for A, B, C, D, E, F, G, Q, W, X, and Y.

This might have made some sense 95 years ago when foundations first structured themselves. But now we have multiple databases of information – GuideStar, the TechSoup International Exempt Equivalent Repository (needs a new name!), NFG, GlobalGiving, GreatNonprofits, Cultural Data Project, GFEM Media database, the Foundation Center, the IRS, the Urban Institute, as well as the internal grants databases of every foundation and countless public agencies. Together these resources hold information on just about every organization and enterprise, every project and funded entrepreneur, and every strategy.

We have a long way to go before these get pulled together and are cross searchable, but progress is moving quickly on that front. National networked databases of comparable information on projects and organizations will soon exist if DonorEdge gets launched through every community foundation, if Blackbaud’s nonprofit central tools take off, if GuideStar’s partnership with GreatNonprofits reaches its promise, if some of the government2.0 public data access movement is successful in opening up the IRS database of exempt organizations, if sites like MIX Market and GreaterGood South Africa and MyC4 keep growing, and MissionMarkets.com or SocialMarkets.org takes off, and/or if the socialentrepreneur API gets public traction. The groundwork is in place that makes it easy to imagine a time when publicly accessible, comparable, searchable data on fundable enterprises, programs and people is readily (and cheaply) available.

So then what? How will donors access and organize and synthesize that information? Might foundations use algorithms instead of (in addition to?) program officers? Might donors rely on crowd sourced recommendations? Might they search first for co-funders, then for organizational partners, and then develop large, leveraged strategies? Might there be connections between well-researched, evidence-based and independently evaluated strategies for change and the multiple organizations that carry out that work?

There are a lot of possibilities out there. Given how soon the landscape of information sources will change we still don’t know much about how the landscape of information-users will change. Data on change organizations is becoming centrally available, at low cost, in comparable searchable ways. We know what this change in data availability did for how colleges are selected and applied to (commonapp), insurance is sold (esurance), how restaurants are reviewed (yelp), how services are purchased (elance), bank accounts are set up (smartypig), apartments are rented (craigslist), stocks are traded (scottrade), friends are found (facebook), coupons are used (cellfire) and textbooks acquired (chegg).

We’ve seen how new organizations, products, tools and services emerge to help us find and maybe make sense of ubiquitous data (Google, WolframAlpha, gapminder). We’ve also seen how the organizations that used to do the sense making for us have struggled to keep up (see newspapers, book publishing, record companies, phone books for examples). What we are also seeing, in the development of universal applications for funding (commonuse), data on outcomes for large-scale donors (pulse), standard reporting systems and metrics (IRIS and GIIRS) crowd-sourcing, and even some of the prize platforms are early sightings of emerging organizational forms for sense-making around social sector data. We’ll see more because with all these data shifts being able to make sense just makes sense.

Tags: philanthropy, data