If you have been following the Sustainable Development Goal (SDG) process, you’ll know the numbers. 17 SDGs, 169 targets and 230 indicators. One question naturally arises: How the hell are countries going to monitor them all?
According to the wonks, data is only regularly available at the moment for 100 of the 230; 82 indicators have weak data and 44 do not even have an agreed monitoring methodology.
That is why the “data revolution” needs to look at new ways to fill stark data gaps, and one option receiving a lot of interest at the moment is more involvement from sub-national and local level partners.
Filling the gaps
That is exactly what TReNDS partner Cepei is trying to do. According to Colombia’s National Administrative Department of Statistics (known as DANE), high-quality information is only available for 54 percent of the SDG indicators in the country. But every city in Colombia has a Chamber of Commerce that holds information that could be useful, e.g. number of commercial bank branches (SDG indicator 8.10) and manufacturing employment as a proportion of total employment (9.2).
So Cepei did something quite bold: It put DANE in touch with the Bogotá Chamber of Commerce, a sub-national, private entity. Philipp Schönrock, Director of CEPEI, told me that it was a process of “co-creation.”
In Bogotá, Cepei brought together Colombia’s national statistics office and the private sector to explore data reconciliation. Learn more about this work in their process brief.
“The private sector is still not providing much data for the SDGs,” he said, “and procedural issues hinder sub-national data from being integrated nationally. This is just a pilot but we are trying to build something robust that can be maintained over time.”
There were, of course, challenges, both technical (e.g. ensuring that different data sets were reconcilable, and that data is clear and cleaned) and political (building interest and trust). Schönrock said there is “no magical solution,” but that gradually, a “stronger ecosystem of SDG data” could emerge.
But while local data is important for filling data gaps, that is not its only value. It is also crucial if we are to have a chance to comply with the SDG’s best-known slogan: leave no one behind.
Leaving no one behind
As the mountains of data assessing the impact of the Millennium Development Goals (MDGs) came in, a dominant story began to emerge: progress in aggregate did not mean progress for all. And one of the most important predictors of disadvantage is geography. Just as all countries have their own contexts that require specific tailored policies, so, too, do regions within those countries have their own unique terrains, culture, history, and politics.
National aggregates hid the reality of intra-national inequality; local data can reveal it. And with context-specific information, more context-specific policy responses can be developed.
So, no, local data action is not just about funneling local data up into some grand dataset held by a nerd in New York.
In fact, it is the other way around.
The whole SDG edifice could be a mechanism for furthering national and sub-national objectives. As well as filling gaps in someone else’s dataset, a focus on local data could do two other things: encourage evidence-based policymaking at the local level and engage local people in making change happen.
Encouraging context-specific policies
That is why SDSN established the Local Data Action Solutions Initiative, which is encouraging the development of and distribution of good, replicable technical methods for sub-national SDG monitoring that facilitate local action in support of the “leave no one behind” principle.” One of the grants it has made is to the Community Systems Foundation’s OpenCities Institute to work with Patiala, a city in the state of Punjab in India. Their aim is to localize the SDGs by using them to frame development priorities in the city as the first step towards a full-scale SDG observatory, helping make planning more effective. Local data, leading to better local planning.
A white paper by TReNDS’ Jessica Espey and the Indian Institute for Human Settlements’ Aromar Revi discusses evidence-based urban policymaking.
Meanwhile, evidence for better urban policies is a focus of the U20, 25 leading cities committed to exemplifying sustainable development. A paper by TReNDS director Jessica Espey and Aromar Revi of the Indian Institute for Human Settlements argued that “a new interdisciplinary urban science” should be the basis of “building the right knowledge and policy infrastructure to support local sustainable development” in a context of rapid urbanization.
The U20 paper also emphasized inclusivity. Because as well as filling gaps and encouraging better policies, a focus on local data can inspire local activism.
Inspiring local activism
As the message of the SDGs is communicated more widely, including the idea that this time no one, however remote, will be left behind, communities and their representatives are more likely to organize, to demand better. And their demands will be backed up with evidence, which they can use to hold the powerful to account.
Furthermore, the very process of collecting local data can become a vehicle for advocacy and information-sharing, fomenting local activism and empowering marginalized communities well beyond capital cities.
The how is as important as the what.
Too often data collection has been about taking, rather than giving. But this empowers the researcher, not the researched. After all, “knowledge is power.”
This time around, actively including communities can transform the process of data gathering into a dynamic process, leaving behind a knowledge infrastructure managed by capacitated communities that would continue collecting and managing data about their own communities long after the SDG excitement has died down.
BudgIT’s open data approach to Nigeria’s federal budget reached 2.5 million Nigerians via online and offline platforms and engaged 25,000 citizens in the review process.
For example, the ONE campaign has compiled a set of examples of communities that have used data to follow public money and concretely improve their communities, including busting “ghost” projects and teachers, doubling mining revenues and exposing dodgy datasets. Another example is BudgIT, which opened up federal budget documents in Nigeria for citizen review, resulting in exposés of mismanaged spending and changes to the federal budget allocations.
People are tired of being talked at by experts, even experts armed with datasets. They feel that they are the experts on their own lives, and they are right. The researcher Indrajit Roy tells the story of a community of “untouchable” agricultural labourer households in Bihar that refuses offers of better housing – not because they prefer their squalid conditions, but because “complying with elite diktats is an affront to their dignity.” They insisted on being involved in the analysis and the decision-making process.
This is not just about gathering numbers – it is about empowering people to monitor their own circumstances, and listening to their conclusions. People deserve to be engaged and inspired. If there is to be a real “data revolution,” local data doesn’t just need activating. It needs activism, too.