Choosing the SDG Indicators

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SDG Indicator Framework

The UN Statistical Commission has stressed the importance of developing high quality indicators for monitoring Sustainable Development Goal progress, of which they appointed an Inter-Agency Expert Group (IAEG) to create, provide technical support, review development, and recommend implementation strategies. This task calls for a data revolution—“an inspiring vision of a world of fast growing data deployed for the public good, and of citizens and governments excited and empowered by the possibilities this creates” (UN Data Revolution, 2016).

Tracking SDG progress is of the upmost importance. It offers an opportunity to increase resources and innovation to fill existing and new data gaps. Gaps in data create disparities in many vulnerable and marginalized communities and social groups, a reason for the UN’s “leave no one behind” mission for the 2030 Agenda. Filling these gaps is priority, as the data can be used to improve lives and increase the power and control citizens have over their destinies. Failing to create adequate indicators will undermine implementation of the programs needed to do so[1].

What is the IAEG?[2]

Those responsible for determining the indicators for SDG progress monitoring are a UN appointed group comprising of 28 representatives from national statistics offices of member states as well as regional and international agencies as “observers”. Together they will provide a proposal of a global indicator framework for consideration by the Statistical Commission in March 2016. This indicator taskforce is otherwise known as the “Inter-Agency and Expert Group” (IAEG). The group will meet twice a year and report annually to the Statistical Commission who oversee whether the proposed indicators are relevant, methodologically sound, measurable, easy to communicate and access, and are limited in number with focused outcome at the global level.

How were indicators chosen?

A total of three meetings occurred between members of the IAEG and the observers in order to finalize a framework for review by the UN Statistics Commission (UNSC), and in July of 2016, the UNSC approved of a framework consisting of 230 indicators. In order to ensure targets can be met worldwide, stress was placed on capacity building in all countries as well as proper disaggregation of the data collected.

Disaggregated data (or stratified into smaller dimensions), is incredibly important to the mission of leaving no one behind, a central objective to the SDGs. Breaking data up into specific dimensions ensures that all social groups are represented and are more likely to receive the help that they need.

In order to do so, the IAEG is responsible for upholding the following criteria when deciding each indicator for each of the 17 targets[3]:  

  • Clear levels of disaggregation for relevant SDG indicators
  • Set of indicators specifically reflecting inequalities that are not captured by disaggregation of other indicators
  • Capacity gaps and investments requirements of national statistical systems of countries to disaggregate indicators with requisite level of detail and showcase them to the international community

The specific dimensions upon which the indicators were to be disaggregated included:

  • Sex and gender
  • Age
  • Income quintiles/deciles
  • Location or spatial varieties (urban, rural, metropolitan, districts etc.)
  • Disability
  • Ethnicity and indigenous status
  • Economic activity
  • Migrant status

Not all of the selected indicators provide the same level of reliability. For this, the IAEG and observers agreed on three tiers to categorize each target indicator[4]:

  • Tier 1: indicators for which methodology and data exist
  • Tier 2: indicators for which methodology exists but data is unavailable
  • Tier 3 indicators for which methodology requires further work and no data is available

Challenges:

The challenges in data collection alone are large, not to mention the ability to break up that data into the aforementioned dimensions. Collection on sensitive issues such as sexual orientation, religion, ethnicity or disability is especially difficult due to various cultural and social norms at community, regional, and national levels. Additionally, much of the relevant data are obtained through household surveys, where the number of questions increases by a multitude of respondents and where development standards to ensure survey data are not always observed under the same definition (i.e. there is no clear definition of what an “urban area” is). Problems also arise when obtaining a large enough sample size to yield statistically significant results. Comparability of data between countries also requires the necessary capacity for quality data to be collected, making comparison between developed and developing countries a challenge regardless of the targets set in order to mitigate this barrier.

Specific challenges apply in light of SDG target data; risks of multi-purpose data becoming too reductive; the complexity of organizing the overlapping, interrelated or potentially contradictory goals/target data (see Figure 1), omitted benchmarks, and the isolated nature of publically and privately collected data.

Integrated Nature of SDGs (Figure)

Image result for integrated nature of SDGs

 

 

The Data Revolution[5]:

In light of the aforementioned challenges with everyday data collection and those specific to the SDGs, the UN has called for a data revolution: increased data for everyone, for now and for the future. This empowers people at all levels, to make informed decisions and encourages the development of data as a shared resource, which promotes transparency, integrity and responsibility. Investing in a data revolution today will enable the innovations required to meet the challenges of tomorrow.

The fundamentals of such a revolution, according to the UN Data Revolution Report A World That Counts, are broken down into 9 principles[6]:

  1. Data quality and integrity: high quality data are according to clear standards and should be classified using commonly agreed criteria and quality benchmarks
  2. Data disaggregation: data broken up into many dimensions so that no one is left behind or hidden within national averages to promote evidence based policy making at every level
  3. Data timeliness: the time between collection and publication is minimized to ensure a steady flow of high-quality and relevant data—the data cycle much match the decision cycle
  4. Data transparency and openness: data concerning specific individuals, groups, communities, nations that are being used to determine public decisions should be accessible to those respective parties—data should be technically and legally open, so that it can be processed individually and/or formatted for commercial and non-commercial reuse
  5. Data usability and organization: developing necessary tools to translate raw data into information for a broader constituency of non-technical potential users and enable citizens and other data users to provide feedback
  6. Data protection and privacy: clear international norms and robust national policy and legal frameworks to regulate data collection and storage functions. They enable citizens to better understand and control their own data—people’s rights to freedom of expression using data should be protected
  7. Data governance and independence: lack of sufficient capacity and funding leave many national statistics offices (NSOs) vulnerable to political and interest group influence—data quality and integrity should be protected and improved by strengthening national statistics offices and ensuring that they are functionally autonomous
  8. Data resources and capacity: national capacity for data science must be developed to leverage opportunities in big data for the public good.
  9. Data rights: have the protection of human rights as a core part of activities

Next Steps:

With the indicator framework approved, the IAEG is tasked with providing the strategic leadership for the implementation of SDGs concerning monitoring, reporting, and harnessing the opportunities of the data revolution to support the implementation process. The initial steps in launching SDG progress tracking rely on the ability of the IAEG, UNSC, and NSOs to establish country baselines and develop further guidance on the issue of data disaggregation of current data for measures of comparability over the course of the 2030 agenda’s implementation. [7]

Between March 2016 and March 2017 the IAEG will carry out…

  • An agreed global reporting mechanism including identifying those responsible for compiling data for global reporting on individual indicators
  • A continued discussion on the inter-linkages across goals and targets and on the use of multi-purpose indicators
  • Review data availability of tier I and II indicators and develop a plan for increasing the data coverage of tier II indicators
  • Establish a work plan for further development of tier III indicators
  • Review progress on all aforementioned points at the second IAEG review in the fall of 2016

Over the course of the 2030 Agenda implementation period, the IAEG will be responsible for[8]

  • Providing technical support for the implementation of the indicator and monitoring framework over the 15 year period
  • Regularly review methodological developments and issues related to the indicators and their metadata
  • Report on progress at bi-annual meetings regarding the goals and targets
  • Regularly review capacity-building activities in statistical areas relevant to sustainable development goal monitoring and make recommendations to be considered by UNSC and other important institutions involved in SDG progress monitoring
  • Review and support work by the Secretariat for the development of a SDG data-user forum, tools for data analysis and an open dashboard on the state of the SDGs

 

 

References:

[1] SDG Group Discussing Indicator Selection, Way Forward. (2015, June 2). Retrieved August 25, 2016, from http://sd.iisd.org/news/sdg-group-discusses-indicator-selection-way-forward/

[2] IAEG-SDGs. (n.d.). Retrieved August 25, 2016, from http://unstats.un.org/sdgs/iaeg-sdgs/

[3] Leaving No One Behind: Disaggregating Indicators for the SDGs. (2015, October 26). Retrieved August 25, 2016, from http://unsdsn.org/wp-content/uploads/2015/10/151026-Leaving-No-One-Behind-Disaggregation-Briefing-for-IAEG-SDG.pdf

[5] Sustainable Development Goals: Measuring progress on new indicators and for all groups - UN Data Revolution. (n.d.). Retrieved August 25, 2016, from http://www.undatarevolution.org/measuring-sustainable-development/

[6] Data Revolution Report - UN Data Revolution. (n.d.). Retrieved August 25, 2016, from http://www.undatarevolution.org/report/

[7] UN Statistical Commission endorses global indicator framework. (n.d.). Retrieved August 25, 2016.

[8] Report of the Inter-Agency and Expert Group on Sustainable Development Goal Indicators (Rep.). (2016). Retrieved August 25, 2016, from http://unstats.un.org/unsd/statcom/47th-session/documents/2016-2-SDGs-Rev1-E.pdf