The consultation has ended and comments are closed.
The Millennium Development Goals, agreed by world leaders at the turn of the century, have been hugely successful in galvanising focus and resources to help eradicate poverty, reduce child mortality, combat diseases and more. They also encouraged investments in data, as national governments and international organisations tracked progress on agreed indicators.
For a government to plan and monitor the impact of its policies, it must be able to benchmark data and see year on year progress. Comparing progress across countries is important – shared indicators and statistical frameworks help countries see how they are doing in comparison to others. As the 2015 deadline for the MDGs approaches, the international community has started to work on a new development framework of ‘Sustainable Development Goals’ (SDGs)
Tracking progress on new goals will increase the demands on often hard-pressed National Statistical Offices to collect and analyse data in new areas. This in turn will require increasing resources for the statistical system and building statistical capacity, with the support of the international community.
A new set of goals offers an opportunity to increase resources and innovate to fill new data gaps. The Independent Expert Advisory Group will make recommendations that will support agile and effective analysis of data on Sustainable Development Goals. The Group welcomes input on innovative monitoring of the Sustainable Development Goals. This might include participatory methods; monitoring inequalities, eliciting citizen feedback on performance of service providers; perceptions data; tracking progress in any of the new areas likely to be covered in the SDGs; citizen generated data.
We welcome inputs on:
- Specific ideas for new technologies or approaches that can be used to fill data gaps likely to arise from new goals.
- How participatory and qualitative methods of data collection can be used together with new and existing quantitative approaches to enhance understanding and improve policy and accountability.
- Ways of collecting and communicating disaggregated data to ensure that the inequalities which hamper progress for particular groups are better known and understood.
- Examples of how new information technologies and existing data infrastructure can be brought together or used in parallel to produce improved development data.
- A critical assessment of what worked and what did not work in measuring progress on Millennium Development Goals, especially focusing on the bottlenecks and how to overcome them.
- Means of implementation and funding to fill critical gaps in the production, dissemination and use of statistics, including introduction of new forms of data and methodologies
- Suggestions on future-proofing SDG measurement to ensure that the system can respond to emerging technology and data sources