Democracy, Equity and the Pursuit of Data

January 22, 2015 4 Comments

“If you bring the appropriate people together in constructive ways with good information, they will create authentic visions and strategies for addressing the shared concerns of the organization and community.”

David Chrislip

Image from r2hox

In our work at IISC, we occasionally reference David Chrislip’s “collaborative premise” (see above) as a way of orienting people to some of the key components of effective collective and net work. Given our emphasis on effective stakeholder engagement and process design, we generally focus on the first two elements more so than the last around good information, which does not mean we think it doesn’t matter. In fact, recently I’ve been observing some interesting dynamics around the data conversation in various network building and collective impact projects that we support.

Invariably, it seems that there are those who are quite concerned about ensuring that a given collective effort has the “right data” and that people are being “rigorous” in their approach to problem/opportunity analysis and solution generation. While understanding the need to have and use good data, we also think that it’s important to ask the question – Data for what? People often say they want data to ensure that they are not making uninformed and overly subjective judgments. Understandable. Furthermore it is sensible to want to seek out a baseline to be able to measure progress as a change effort moves forward. This said, I see a number of pitfalls in what can sometimes become the drumbeat for data.

First of all, as we have found out in various initiatives, people can get stuck in an endless pursuit of gathering data. “Just how much data is enough?” becomes a critical question. Furthermore, it is important to remember that data does not speak for itself. It is human analysis and meaning making of data that speaks. Therefore it is critical to ask about the sources of the data, who interprets it, and how.

In given instances the rigorous pursuit of data can marginalize certain perspectives on a situation or system, which begs the question – What do we mean by “data”? Otherwise, lived experience and anecdotal evidence may be too easily dismissed along with the traditionally under-represented voices and stories of those most (negatively) impacted by the issues an effort may say it is trying to address. This is why I like to ask at the outset of a collective change effort – What constitutes legitimate ways of knowing?

It is also part of the reason why at IISC, we are pursuing an approach to place-based engagement around social and environmental issues that we call Big Democracy, to bring balance to some of the ardent pushes around “big data.” At the end of the day we believe that we must put (or keep) a human face on the systems that we are trying to change and also to ensure that those who are most often left out and/or are on the margins are at the center of the conversation.

In this same vein, it is interesting to read these words from theoretical/computational astrophysicist and occasional NPR commentator Adam Frank about the dangers of Big Data (also see his full blog post).

“From credit to health insurance to national security, the technologies of Big Data raise real concerns about far more than just privacy (though those privacy concerns are real, legitimate and pretty scary). The debate opening up before us is an essential one for a culture dominated by science and technology. Who decides how we go forward? Who determines if a technology is adopted? Who determines when and how it will be deployed? Who has the rights to your data? Who speaks for us? How do we speak for ourselves?”

The systems thinking pioneer Donella Meadows once talked about the need to surface our assumptions about any situation. She understood that any map that we create of our reality is just that – a map, a model. She encouraged us to bring to the table those models, to be explicit about them, and to allow others to look at and question them. Which brings us back to the two other components of Chrislip’s collaborative premise. Who is at the table and how those people at the table are engaged matters. Data matters, yes, and it matters in context, and with the understanding that it must serve us and the larger purposes (of democracy, of equity) and not the reverse.

How are you thinking about and using data in your change effort? What and who is this serving?


  • very helpful! And thoughtful. I think it’s also important to watch out for the embedded code in the request for data and rigor, it is often a set up to uphold a particular kind of “expert,” usually the most privileged kind.

    • Charlie Jones says:

      Ditto Gibran’s comment!

      Also – I recently heard a piece on Radio Lab or the TED Hour (cannot remember which) where it was suggested (and backed up by strong evidence) that much of what a person thinks directly supports what that person believes. That, in fact, most people are patently incapable of thinking in ways that do NOT support what they believe. If this is true, I’d say this is even more dangerous than bad data…

  • Curtis Ogden says:


    Smiling because the very words out of my mouth the other day with a client were, “Sometimes when we say ‘we need data,’ it is code for something else. What question are you trying to answer with data?”


  • Cynthia Silva Parker says:

    This gives more flesh to the mantra that narrative trumps numbers. The studies that produce the data are also built around a set of assumptions and beliefs. A large part of science (physical and social) is about testing those assumptions (and ideally demonstrating that they are true). It takes a mountain of disconfirming data to cause people to question their assumptions and stories about how the world works.

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