Advocacy Evaluation and Being ‘Data-Informed’

I wrote a post not too long ago about ‘data-driven cultures’. And then I read Measuring the Networked Nonprofit, and, in just a chapter, Beth Kanter and her co-author changed, somewhat, how I talk about the role of data in nonprofit organizations.

Social services aren’t ever going to be totally ‘data-driven’. There are a lot of factors that impact our decisions and our programming.

And that’s how it should be.

Rather than trying to make social workers slaves to spreadsheets, or pretending that we can make rational every factor that influences our operations, we need to become data-informed organizations, embracing both the power of data and its limits.

As Kanter advises, we need to spend a lot more time thinking about the data we collect than we do collecting it. As I see in the advocacy evaluation collaborative of which I’m a part, we need to find ways to unobtrusively gather data–weaving that into the work as much as possible–so that we have time to sit around and talk about what this means (which, in some cases, is how we ‘analyze’).

We need to resist the temptation to dump data on someone’s desk, thinking that our work is done when the report is published. I ask my clients, from the very beginning, what it is that they hope to learn from a given evaluation effort, what questions we need to ask to figure that out, and with whom they need to share the answers they glean. We plan for usefulness from the start.

It makes me think about an organization I have worked with over the past 18 months or so, which has a Quality Improvement Department–staffed with just a few full-time employees, whose job it is to cull through the organization’s data, looking for patterns and making sense of what they see, and also to systematically share information with others within the organization, so that, together, they can ask the most important question:

“So what?”

But this distinction between being data-driven and data-informed has special importance in advocacy, I think. We’re always exhorted, in advocacy, to have ‘hard facts’, as though the stories we share about policy impact are somehow too soft and squishy to be meaningful.

But the best nonprofit advocates already know that the most powerful advocacy comes from weaving data and narrative, from analyzing numbers to answer hard questions, and from relying on all kinds of knowledge to inform our decisions.

In advocacy, we know that being ‘data-driven’ can lead to outcomes that don’t work for individuals who don’t fit a typical pattern. We know that data don’t change hearts and minds, and that developing power requires creating spaces for people’s voices.

We know that we must be data-informed.

And driven by a vision.

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