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Development 2.0: Give me less information and more data!

OK, the title is deliberatively provocative. But I found a coincidence of two blog posts last week to be quite powerful. Last week we had a blog post from Dave Snowden that challenged the "data to information, information to knowledge and wisdom" continuum that has informed so many of the knowledge management efforts in the non-profit and public sector:

For the best part of a century we have been trying to move data into information. Some people have then tried to make information into knowledge and a few charlatans have attempted a transformation to wisdom, thus marking themselves out as the antithesis of the wise. With the capability of modern technology to augment human intelligence (but not replace it), we are increasingly moving in the other direction. Breaking up information into its source data and allowing messy, but coherent real time assembly in the context of need. Information carries too many assumptions to allow it to be context free, while data has more fluidity and adaptability. This is a huge change, partly enabled, heralded and driven by the rise of social computing but it is far more than that. It changes the way we think about the world, increases the focus on concrete, embodied knowledge that was achieved through apprentice systems such as the knowledge boys in the London Taxi service.

And in the very same week, a post from Aleem Walji on the DM blog called developers "the new infomediaries." The sheer act of juxtaposing and visualizing sets of data that were previously unavailable to the public can prompt us to ask whole new sets of questions about development, its governance and impact:

For instance, what is the relationship between GDP per capita and health as expressed by life expectancy? Why is it that some countries achieve good progress in reducing infant mortality rates despite low incomes while others grow their economies but fail to make progress in reducing child deaths? These are the sort of questions that arise when good data meets good information architects and master visualizers.

Of course, we will always need experts and their "concrete, embodied knowledge" to answer such questions.

However, the trend in the development sector away from information and toward data (and not vice versa) and data’s “coherent real time assembly in context of need” is, it seems to me, undeniable. What better examples than crisiscommons.org or ushahidi.org and their real time collection of data during a crisis?  The impressive statistics from the first few weeks of the World Bank’s Open Data Initiative also speak of a great appetite for raw data, without necessarily a superimposed layer of “official” interpretation. And what about recent plans to build a social investment data engine to help investors determine the potential social impacts of their investments?

This is consistent with the trend that I identified before of a demand for greater traceability of donations to the development sector. In that context too, the public seems increasingly interested in seeing the numbers and hearing it “from the lion’s (ie. the recipient’s) mouth”, as it were, without any intermediation.  See this recent example from Canada for some striking results.

What are the implications of the trend towards data for development organizations? I can think of at least a few:

  • If resources are limited, focus your efforts on making your data open rather than in producing generic “lessons learned” documents (or other knowledge management products) that have little contextual value for practitioners on the ground. In a world where SMS makes it possible to connect with affected communities even in rural areas, those products will sound increasingly hollow.
  • Be transparent about your assumptions. If you are producing an analysis or releasing a report, make the raw data available as a matter of practice. Don’t shy away from providing your interpretation and offer your take, but make sure that your assumptions are clearly spelled out.
  • Be prepared to answer (and engage with) new questions: as more and more data will be made accessible by the new "infomediaries" for anyone to query and analyse, new questions will arise that will challenge well established development conventions and paradigms.
  • Make low-cost efforts to capture data an integral part of your processes. I am thinking, for example, of ways to make all projects geo-tagged from inception (it was great to learn from Aleem that the Bank is thinking very much along those lines). Or see this great case of SMS data gathering ingenuity from FINO to keep track of their banking agents.
  • Make your experts accessible "in the context of need." Just like with London’s taxi drivers and their knowledge of the local streets in Dave’s example, development organizations have fantastic knowledge embodied in their practitioners. They can perhaps do a better job at making them easily available when the context requires it (here again, social media can play a great role).

What else should be added to the list?