CoolData blog

22 April 2010

Introducing the nonprofit data collective

Filed under: Non-university settings — Tags: , , — kevinmacdonell @ 8:20 am

Yesterday I gave a conference presentation to a group of fundraisers, all but one of whom work for non-university nonprofits. Many have databases that are small, do not capture the right kinds of information to develop a model, or are unfit in any number of ways. But this group seemed highly attentive to what I was talking about, understood the concepts, and a few were eager to improve the quality of their data – and from there get into data mining someday.

The questions were all spot-on. One person asked how many database records one needed as a minimum for predictive modeling. I don’t know if there’s a pat answer for that one, but in any case I think my answer was discouraging. If you’re below a certain size threshold, you may not have any need for modeling at all. But the fact is, if you want to model mass behaviour, you need a lot of data.

So here’s a thought. What if a bunch of small- to mid-sized charities were to somehow get together and agree to submit their data to a centralized database? Before you object, hear me out.

Each charity would fund part of the salary of a database administrator and data-entry person, according to the proportion of the donor base they occupy in the data pool. The first benefit is that data would be entered and stored according to strict quality-control guidelines. Any time a charity required an address file for a particular mailing according to certain selection criteria, they’d just ask for it. The charity could focus on the delivery of their mission, not mucking around with a database they don’t fully know how to use.

The next benefit is scale. The records of donors to charities with related missions can be pooled for the purpose of building stronger predictive models than any one charity could hope to do on its own. Certain costs, such as list acquisition, could be shared and the benefits apportioned out. Some cross-promotion between causes could also occur, if charities found that to have a net benefit.

Maybe charities would not choose to cede control of their data. Maybe there are donor privacy concerns that I’m overlooking. It’s just an idea. My knowledge of the nonprofit sector outside of universities is limited – does anyone know of an example of this idea in use today?

P.S. (18 Feb 2011): This post by Jim Berigan on the Step by Step Fundraising blog is a step in the right direction: 5 Reasons You Should Collaborate with Another Non-profit in 2011.

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