Two years after their formal adoption, there is an urgent need to mobilize the “Data Revolution” in general, and its core component Big Data in particular, to reach the Sustainable Development Goals (SDGs). The hope is that the (Big) Data Revolution will reshape and upgrade current power dynamics and decision-making systems for the better. That this revolution will move us towards a world where public interventions are designed and evaluated against evidence, discussions and decisions are more firmly grounded in facts and shared experiences, and more voices are heard and considered. That it will serve development and democracy in the age of post-truth politics. The fear is that data can be and indeed has been used to entrench power dynamics and decision-making systems that fuel adverse outcomes (deprivation, violence, pollution, congestion, waste, wars, distrust, disdain, etc.) That data will be used to impede progress towards the goals. Thus, the question is: What can and should be done to seed and support a virtuous data-enabled process of social transformation through innovation and inclusion – a transformation in which the SDGs are much more systematically monitored and promoted?
This overarching question raises two more. First, what is the theory of societal change explicitly or implicitly put forth by the strongest advocates of the SDGs? And how valid is that theory? In other words: what are we saying or selling about the causal impact of measurement and evidence more largely? When we measure the height of our young kids and put a mark on the wall, is it to check if they have grown according to plans? So as to feed them better if they haven’t? Of course not. This isn’t to say there is no instrumental value in the outcome of measurement, but rather to stress the role of the process itself.
Secondly, how can the instrumental role of measurement—via greater accountability and efficiency—be materialized, and magnified? For all the talk about the importance of measuring the SDGs to get closer to achieving them, surprisingly little has been done towards that objective. Despite the hope that Big Data could help fill “data gaps” and perhaps even fix the “statistical tragedy” in the poorest countries, there is, as of now, no body of stable, scalable methodologies to ‘leverage’ Big Data to make a significant contribution to measuring the SDGs in the next decade. Even after 10 years following the emergence of Big Data as a socio-technological phenomenon and ecosystem. Even after publication of dozens of case studies and academic papers confirming their potential. Why is that? Can this be changed and if so how?
These are some of the questions this talk will address in proposing a theoretical and methodological framework for monitoring and promoting the SDGs through the (Big) Data Revolution – a framework based on the work and vision of Data-Pop Alliance.
