The Addis Ababa Action Agenda commits to increase the availability and use of high-quality, timely and reliable disaggregated data. Statistical products maximise their impact when they are standardized, i.e. they measure things the same way across time and across geographic locations.
The Addis Agenda specifically:
- Seeks to increase and use high-quality, timely and reliable data disaggregated by sex, age, geography, income, race, ethnicity, migratory status, disability, and other characteristics relevant in national contexts
- Requests the Statistical Commission, working with relevant international statistical services and forums, to regularly assess and report on the adequacy of international statistics related to implementing the sustainable development agenda
- Calls on relevant public and private actors to put forward proposals to achieve a significant increase in global data literacy, accessibility and use, in support of the 2030 Agenda
- Commits to support efforts to make data standards interoperable
Latest developments
During 2019, the Inter-agency Expert Group on SDG Indicators (IAEG-SDGs) undertook a comprehensive review of the global indicator framework and proposed 36 major changes for review by the United Nations Statistical Commission in March 2020. The proposed changes aim to (i) enhance the target-indicator mapping; (ii) ensure that all critical aspects of a target or goal are covered by an indicator; and (iii) ensure that all indicators have an established methodology.
An increasing share of projects on statistical capacity development contain components that target gender statistics. Between 2015 and 2017, approximately 11 per cent of commitments to statistics from bilateral donors targeted gender data, up from three per cent between 2010 and 2012. However, despite this positive trend, additional efforts are needed, as many of the 54 gender-specific SDG indicators are not currently produced with sufficient regularity to meet the SDG monitoring requirements.
Read more on the progress in strengthening data frameworks, measurements and data collection here.