Implementing Agenda 2030: Unpacking the Data Revolution at Country Level

This final report from the Post-2015 Data Test initiative offers research-based reflections on how the 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDGs) can be effectively and universally applied, as well as measured, across countries with different sustainable development challenges and priorities. The report seeks to provide clear guidance on where and how country-level investments in the data revolution could be made, particularly with the Global Partnership for Sustainable Development Data now underway. It gives prominence to the issue of data quality and, through a set of case studies, tests out a methodology to assess, in a comparative way, how well countries are doing in providing the kind of data needed to review and follow up on their commitments toward selected goals and targets. Findings are expected to be particularly useful for countries that are exploring ways of mainstreaming SDGs into their national plans and policies, as well as measuring and reporting on progress. The emphasis in this volume is on what national statistical offices (NSOs) have to do and how others can help. In a world in which "big data" is a phrase practitioners hear often, this is a reminder that the main providers of development data will likely continue to be national government offices. But NSOs need help in the form of better use of technology and partnerships.

The Post-2015 Data Test initiative is jointly led by the Center for Policy Dialogue (CPD) in Bangladesh and the Norman Patterson School of International Affairs at Carleton University in Canada, and is being carried out in partnership with a network of 48 think tanks across Africa, Asia, and Latin America called Southern Voice. (Both CPD and Southern Voice receive institutional support through the International Development Research Centre (IDRC)'s Think Tank Initiative (TTI).) These collaborators share a conviction that better development data will allow for far more rapid progress on development outcomes, the kind of departure from business-as-usual that is needed to meet the SDGs. To take just one example, Agenda 2030 issued a call to leave no one behind. But most of the data used for monitoring the Millennium Development Goals (MDGs) could not be disaggregated by gender, geography, income, disability, or other categories. Several countries were deemed to have met the goals even though inequality was rapidly increasing and sizeable parts of the population were not benefiting. Policymakers and civil society organisations need to know what is going on in their countries, and around the world, in much more detail, and in a much more timely fashion, so that data becomes actionable. Development data constitute, on this conception, not a historical record of the past but, instead, a current review of what is happening now in order to inform the follow-up of what needs to change in the future.

The volume synthesises key findings from local research carried out by think tanks in 7 low-, middle-, and high-income countries: Bangladesh, Canada, Peru, Senegal, Sierra Leone, Tanzania, and Turkey (click here for access to individual country studies). Over a 2-year period, researchers tested a set of SDGs within their countries by identifying priorities and accompanying indicators that are appropriate to their particular country contexts, and then examining the availability and quality of data for tracking progress.

The following excerpt from the report captures some of the main recommendations from the research:

"A Universal Framework Fit for Purpose

Universality works but national priorities matter
The SDGs resonate across countries with different sustainable development contexts and it is possible to apply and measure a global framework across countries with different sustainable development challenges. However, allowing countries space to identify national priorities is critical to ensuring the utility of a universal framework and robust adoption at the national level...

Take a differentiated approach to global monitoring
...the global monitoring framework should be applied using a differentiated approach that accounts for the relevance of particular targets and indicators across countries. High-income countries should not be asked to report on extreme poverty, as measured by proportion of a population living on less than US$1.25 (purchasing power parity) per day, and low-income countries should not report on all aspects of global partnership...

Keep the global SDG structure light
...There is less need for a top heavy global architecture to facilitate efforts. Rather, the global architecture should enable the flow of resources and capacities to where needs exist through follow-up and review processes. Implementation and monitoring of the SDGs should be country-led, carried out by institutions in country.

Focus more on national priorities and less on international comparability
...Countries should have space to monitor SDG implementation and beyond according to national priorities. This means the use of additional indicators that reflect their context for sustainable development, many of which may already be identified through national planning processes...

Assess the utility of SDG targets and indicators before investing finite resources in them
Finite resources available for data generation are to be invested only after the SDG targets and indicators have been aligned with national priorities and possibilities...For example, tracking the use of modern cooking fuels does not make sense in high-income countries.

Recognise that zero targets will need resourcing to be measured and achieved
It is not feasible to reach zero targets or global minimum standards in many low-income countries without dedicated international financing for both implementation and measurement...

Measure global partnership at the country level
...While the global framework will concentrate more on monitoring the delivery of global commitments (global public goods) at an aggregate level, it will be necessary to measure individual country contributions to global partnership, and as such, hold individual countries accountable for their contributions.

Broaden the conversation on implementation at the country level
...[A]ction must move from New York to national and provincial capitals, and from foreign ministries to central ministries to make sure that the right stakeholders, including the private sector and other non-state actors, are engaged in SDG delivery and its assessment.

Investing in More and Better Data to Drive SDG Progress

Take stock of existing data as a first step to investing in the data revolution at the country level
...[A]ll countries will have to do a data inventory to assess the availability of data to have an adequate national benchmark for the relevant SDGs.

Invest in disaggregated data so we know we are leaving no one behind
...While disaggregation is often possible by sex, age and sub-region, other forms of disaggregation - particularly in terms of income and minority groups - are often not available....Greater use of existing data and expanding and facilitating links between data sources could help...

Be guided by measuring what matters - not what data exists
...[T]he inclusion of new priorities for which data gaps exist reflects their importance as part of a new agenda for sustainable development and can drive resourcing and effort - including around data collection.

Data consistency and compatibility are important
At the country-level, assessments of existing data production should be encouraged before launching new survey instruments....In the longer term, NSOs will need to establish procedures for ensuring outputs are internally coherent and provide information on comparability between sources. Efforts will also be needed to facilitate the use of common standards and definitions across statistical outputs, periodically assessed against international standards...

Invest in harnessing existing data
Data is more readily available to monitor poverty, education and employment-related SDGs....[T]he key challenge will be working with NSOs and line ministries to prepare and make available statistics and accompanying analysis...

Collect data more often and release results more quickly
...A key challenge is ensuring that NSOs are adequately resourced to collect, analyse and disseminate data in a timely manner. Addressing this challenge will require long-term efforts and commitment by governments, development partners and data producers. In the short-term, the provision of information on data releases, including when any divergence from advance release times occur, should be encouraged. In the longer term, there is a need for data producers to establish and update data release policies in accordance with international standards, provide a calendar for releases and establish procedures to monitor punctuality and provide formal explanations in the event of delays.

Use unofficial data strategically, but not at the expense of official data
Unofficial data sources (e.g. research institutions, think tanks and non-governmental organisations) should be harnessed to fill data gaps and complement official data sources. Systems have to be put in place so that unofficial data are more acceptable to NSOs from methodological perspectives. Governance is an area where unofficial data will be particularly powerful...

Put NSOs in the lead and invest in national priorities, systems and institutions
...Efforts to support the data revolution at country level should be grounded in national priorities and establishing statistical building blocks. This requires country leadership and coordination...

Providing autonomy and legal protection to NSOs
For NSOs to play their desired roles, they have to be given statutory protection so that they can function professionally and without political interference.

Be predictable with financing and commitments
...Commit resources, according to national plans, over the long-term...

Consult with data users to improve data relevance
...A number of steps could be taken to improve engagement with data users. In the short-term, ad hoc, periodic user consultations may be a simple way to begin improving the relevance of data collected. In the longer term, countries will need to develop policies and systems for user consultation, which may include the establishment of advisory committees or other more formalised mechanisms of user consultation. Policies and procedures should also include a system for collating ongoing feedback.

Coordinate data efforts across government more effectively
...Significant efforts will be needed to ensure effective monitoring of goals related to energy and infrastructure, governance, and the environment. Importantly, for these goal areas, line ministries have a critical role to play. Efforts to generate good quality data will need to incorporate NSOs as well as responsible ministries for these goal areas and support better coordination across government. Ensuring the relevance of data also requires better coordination between data producers to reduce duplication of efforts and ensure that data collection, across ministries, meets various user needs...

Integrate data quality policies and systems across government
...There is a need to ensure all data produced by the government...is accompanied by metadata, particularly information on sampling and non-sampling errors, preliminary and revised data, methodology, and data quality available....A number of studies also noted that policies for data revision are unavailable. Establishing such policies and providing access to them would contribute to improving data quality.

Engage with Southern research institutions
Scarce technical capacities for data generation, quality assessment and analytical use in developing countries are located in their research institutes and think tanks. These institutions should be extensively engaged by the national governments, regional entities and global community to address data challenges emanating from the operationalisation of data revolution at country level.

Adopt technologies suited to country context
...The integration of new technologies should be understood within the context of existing physical and ICT [information and communication technology] infrastructure constraints at the country level. Many of the challenges related to accessibility relate to the need for greater use of technology and electronic formats in the collection, presentation, and dissemination of data.

Develop and integrate consistent standards for data production and dissemination
...In the short-term, space could be created for greater cooperation and exchange between statistical providers and programmes to improve coherence and comparability, particularly in terms of the adoption of shared expectations, policies and procedures. NSOs could take a leading role in such discussions. Improving dissemination of data is also a critical challenge. In the short-term and particularly in the case of low-income countries, there is a need to make greater use of electronic dissemination, including the provision of data, metadata and microdata where possible. Websites will need to be updated to enable users to easily access and download data in usable forms. Longer term, the establishment of a data dissemination policy...should be encouraged. It should be clear to users how, and under what terms, they can access data....It will also be important to ensure that users have access to up-to-date methodological documents, ideally according to an established policy for consistent procedures and presentation of metadata."