Debates over the achievement of the Millennium Development Goals (MDGs) over its several years of effort led to a renewed and broader agreement about sustainability, and then led to the endorsement of the Sustainable Development Goals. These goals are not only built on the MDGs, but also supplant them, as of course, a greater awareness of the need for broader engagement to achieve the change that societally and economically is needed to shape our world into the world we want. The adoption of the SDGs by the United Nations, renewed understanding of how the major challenges that the world is facing are interdependent. No country can really expect to be its own island, whether in its need for food, water, energy, or jobs. The SDGs are a foundational platform that all countries are challenged with the adoption and the endorsement by the United Nations to consider how to address the challenges.
The SDGs provide a new vision for development, a vision that does not assume Development is isolated, but understands and admits that it is changing the role of women and youth; bringing access to ICTs to small farmers and midwives in developing countries; advancing access to information and education for children that have not school rooms, or limited access to books in their language to help them learn.
In response to growing awareness about the importance of sustainable development initiatives and activities and to meet what has been established as necessary goals for the world, the SDGs offer the potential guidelines to move the world toward a sustainable future.
Looking back at the MDGs, this session proposes to look at the learning of the MDGs very much like a prologue to what must be done now. In fact, the SDGs are already finding ways to gain supporting implementation initiatives. In addition, to take into account lessons learned about lack of data, and lack of focused reporting on achievements.
In order to know where we are, we need data. We cannot plan how we move toward achieving the SDGS unless we have better understanding. As a wise sage once said: If you do not know where you are going, any road will get you there. In addition, another study the past to know the future. Many reports are published by businesses, NGOs, and think tanks. Reports are published annually by UN agencies. However, it is very difficult to determine what is factual from all these reports, and who provides the input to the studies, so it is difficult to determine where “we” are.
The implementation of the 17 UN SDGs in developing countries is only a fortnight away, and as it looks, the UN could be up against more than it really understood. Creating a form of standardized reporting is very challenging for developing countries, unless there is a sort of “road-map” that is built on their present status in terms of data gathering mechanisms and analysis.
According to World Bank Report (Poverty Global Practices Group and Development Data Group April 2015), a significant number of developing and least developed nations across Asia and Africa lack sufficient data to be used by business and policymakers in making estimates.
Lack of data and why the need for sufficient data:
Data helps experts weigh the feasibility of goals, provides clarity on the nature of the problem and facilitates statistic-based supervision and evaluation of development progress. It is paramount in intermediate outcome tracking and determination of whether the paths predicts that a country or the UN will achieve or miss on an SDG and its targets. Most developing countries lack data even in priority areas and that has come as one of the most pressing challenges the 2030 Agenda is likely to face. As has been suggested, a little under 30 of the world’s poorest countries have extremely limited data to measure the trend of SDGs indicators.
Mechanisms for gathering data:
One fundamental data collection method is through conducting household surveys, which will provide important data for evaluation and analysis of individual wellbeing in terms of health and education statuses, agriculture, energy and consumption levels. Another reliable method is the use of administrative records, which can provide statistics on demographic changes and trends, for instance, to aid in the formulation of health, education and social protection policies.
However, we must be realistic that developing countries often lack resources to conduct the aforementioned surveys; some have poor and unreliable registration systems, which may force analysts to rely solely on non-statistical estimates. To add to the challenges, one SDG target requires that legal identity, including birth registration, be provided for all by 2030. Relying only on telecom operators/mobile operators to report on connectivity, for instance, is a very flawed measurement, as has been demonstrated by Lirne Asia’s research.
Data measurement mechanisms that are suitable for developing and developed countries need updating. Moreover, this needs to happen quickly. It may be that grants and training programs for developing countries will be needed to help strengthen the organizations at the national levels so that they can enhance their ability to gather reliable data and be more comprehensive with what they provide to the UN registry bodies if SDGs are to be met.
The workshop on “Data for sustainable development road-maps” session will bring together a diverse set of UN Agency representatives responsible for gathering statistics; other kinds of data producers, business professionals and users, as well as innovators in the field (national and international experts) to discuss the way forward, including exploring how new technologies and approaches that can be used to strengthen the data ecosystem globally.
The session would be organized around five themes aiming to achieving the following outcomes:
Theme 1: Addressing data gaps and financing
● present the current situation for countries to produce SDG indicators and
highlight data gaps.
● discuss opportunities to strengthen census and survey regimes.
● discuss opportunities to further develop the administrative data system with the
view of ensuring harmonization, comparability, and quality of data.
● present possibilities for using new data/ technology to address identified data
gaps and engage new actors.
● to determine how alignment with national and regional agendas will impact data
collection in developing countries and indicator production and reporting.
- Identify possible approaches for addressing the funding gap (both in terms of
mobilizing additional resources and using those available more effectively)
Theme 2: Encouraging data use
● have an open dialogue with key users on how data/ statistics produced can
better meet their needs.
● Identify ways to harness the opportunity of the momentum around data for the
SDGs to strengthen the sharing, accessibility and presentation of data.
● raise the profile of data production and use with key stakeholders including
policy- makers to encourage the use of improved data for evidence-based decision-making and accountability.
Theme 3: Strengthening the Data Ecosystem
● solidify the multi-stakeholder approach to achieving and measuring the SDGs,
and create new data communities.
● Identify and discuss solutions to major funding gaps.
● Identify and discuss solutions to major capacity gaps.
● Provide an opportunity for country-to-country learning in the SDG indicator
● ensure high-level political and policy-maker buy-in for the Roadmap process.
● Identify key issues for the policy and enabling environment for the data
Theme 4: Improving Systems
- How can the promotion of transparent data support the implementation of the SDGs at both the national and global levels?
- What kind of data regime is needed for the most effective and robust system for the implementation of SDGs?
- To what extent would data availability contribute to delivery of national and global goals?
- Learning from home grown and other non-traditional systems of information management in developing countries.
Theme 5: Policy and enabling environment
This theme will focus on the necessary policy initiatives in relation to data production, sharing and use as well as the enabling environment to ensure data quality, interoperability, security and protection.