The UN General Assembly (UNGA) Open Working Group (OWG) on Sustainable Development Goals (SDGs) held an informal meeting on 'Measuring Progress' with Member States, stakeholders, and experts from the international statistical community.
Participants discussed the role that data and statistics will play in the SDGs, and how to craft targets with measurable indicators.
The meeting took place on 17 December 2013, in New York, US.
17 December 2013: The UN General Assembly (UNGA) Open Working Group (OWG) on Sustainable Development Goals (SDGs) held an informal meeting on ‘Measuring Progress’ with Member States, stakeholders, and experts from the international statistical community. Participants discussed the role that data and statistics will play in the SDGs, and how to craft targets with measurable indicators. The meeting took place on 17 December 2013, in New York, US.
Opening the meeting, OWG Co-Chair Csaba Kőrösi spoke of the OWG’s need to “tap the experience of the statistical community” in order to better understand how to monitor and report on an integrated set of SDGs, and the relationship between goals, targets, and indicators. He asked experts to “help us design goals and targets to ensure their measurability,” and specifically to explore questions of: what should be measured on national, regional and international levels; what capabilities for measuring SDGs still need to be developed; how to differentiate goals and targets for the specific needs and priorities of different countries; how to ensure transparency of measurement; and how the ‘data revolution’ will change statistical needs.
Keynote speaker Walter Radermacher, Director General of Eurostat, said the SDGs should choose indicators before the goals and targets have been fixed. Discussing the need for evidence-based decision-making, Radermacher said good statistics and indicators will aid policy-makers and “inspire us to improve.” He said that the possibilities offered by the data revolution, including the prominence of ‘big data,’ will offer great opportunities in the coming years, but the global community must develop capabilities and understanding around new forms of data.
The first panel discussion, on ‘Lessons learned from the monitoring of the Millennium Development Goals (MDGs) and Sustainable Development indicators (SDIs),’ discussed experiences in the implementation of both global and national development initiatives. Philippe Cuneo, INSEE France, said inconsistencies in the MDGs could have been reduced had their numerical targets been better designed from the start. Enrique Ordaz, National Institute of Statistics and Geography (Mexico), said MDG statistics are used to communicate facts with society, and data should be used for all people to understand the dynamics of their country.
In the second panel, ‘Review of existing proposals and their statistical requirements,’ panelists explored proposals of goals put forward this year by the UN Secretary-General’s High-level Panel on the Post-2015 Development Agenda (HLP) and the Sustainable Development Solutions Network (SDSN), in terms of their measurability. Peter Harper, ABS Australia, said “significant work” will be needed to provide and develop the data that different SDG proposals are calling for, especially in the areas of social, environmental, and governance quality measurements. For most of the ambitious targets proposed by the HLP, he said, “the statistics are quite a way off” from being able to measure them. Rutger Hoekstra, CBS Netherlands, said measuring institutions is one important area in which to improve, especially in the context of new SDG proposals.
In the third panel, ‘Road-map for measurement,’ panelists explored the way forward for interaction between statistics and the crafting of the SDGs. Jose Ramon Albert, NCSB Phillippines, discussed the need for “sustainable statistics,” while Pali Lehola, SSA South Africa, said statistics should allow a country to question what it values. Johannes Jutting, PARIS21, said data are an important tool for holding governments and stakeholders accountable, and the specific data challenges of poor countries must be looked at in particular.