By Molly Anders, 23 January 2017 - Following the first ever United Nations World Data Forum in Cape Town, South Africa, last week, an emerging group of donors led by the U.K.’s Department for International Development and the World Bank is calling for greater data disaggregation — a breakdown of development figures based on characteristics such as gender and geography.
The more profound level of detail is needed to ensure that pockets of neediness are not overlooked in examining average progress toward the Sustainable Development Goals, advocates say.
Disaggregation is “what’s going to tell us what’s actually going on as opposed to how averages are performing,” Dominic Haslam, director of policy and strategy at Sightsavers told Devex.
Timed with the Forum, DfID released ambitious plans to disaggregate program data collection based on sex, age, disability status and geography. The department will concentrate on these four variables initially and re-evaluate what further criteria might be needed in 2020, according to the Data Disaggregation Action Plan.
For its part, the World Bank pledged to support 78 IDA countries to implement a multi-topic household survey every three years, as well as support capacity for gender statistics, among other areas.
The forum’s Cape Town Global Action Plan for Sustainable Development Data also calls for donors to “Improve the production of high-quality, accessible, timely, reliable and disaggregated data by all characteristics relevant in national contexts to ensure that no one is left behind.”
The plan, a “to-do list” for policymakers, sets out objectives for generating and using data to achieve the Sustainable Development Goals. It calls for strengthening national statistics systems and modernizing collection tools, improving dissemination, and stronger partnerships and data sharing, among other objectives. Advocates told Devex they had hoped for an even stronger call for disaggregation in the final document.
Statisticians and aid practitioners are eager to see an upgrade in methodologies for gathering and using data, aligning with the level of detail included in indicators for the SDGs. Some experts argue that short of better disaggregation across the U.N. system, disabled and other marginalized groups are still in danger of being left behind.
The U.K.’s Data Disaggregation Action Plan, the first of its kind by a top donor, outlines its strategy to disaggregate project data beginning with “trailblazer” initiatives in Bangladesh, Nepal, Rwanda and Zimbabwe. DfID will disaggregate its own data as well as work with each of the host governments to include similar data in national statistic collection. DfID aims to fully disaggregate data “for all social groups under the Global Goals,” by 2030.
“Going forward it would be good to see others setting out commitments to disaggregate their work,” a DfID spokesperson told Devex. “To meet the target set out in the Global Goals to leave no one behind we need to raise the standards of data disaggregation.”
By DfID’s own admission, disaggregation will be challenging. Its limited start is intentional, the document says, “knowing there will be challenges... in the shorter term.” The document continues, “By starting with these the aim is to create an incentive for culture change, recognising this will take some years to embed across the organisation.”
The department is “the first to admit they’re just starting the process,” Haslam said. He told Devex he is encouraged by the U.K.’s whole of government approach to the venture, noting that the Office of National Statistics has also been involved.
“They want to make sure they take on things which they can deliver, so rather than saying we’re going to disaggregate everything immediately and make all of our projects inclusive right now, none of which is reasonable, they’re taking what I think is a really valid and sensible step, which is to say we’re going to do these core things, we’ll learn from them and then see where we’re at, and in general the disability sector has been very supportive of that.”
The U.N. Action Plan on the other hand could go further, Haslam said. While the U.N. document is “quite strong” in places, he argues it doesn’t go far enough to bridge existing gaps in disability data and doesn’t specifically call for the U.N. — an essential piece of the data picture for measuring development impact — to improve its own data systems.