An op-ed by Mahmoud Mohieldin and Haishan Fu emphasizes the need to built trust throughout the “data value chain” and in the decisions that such data support.
Disaggregating data at the national and sub-national levels by various factors can help identify those lagging behind and determine by how much.
The authors also underscore the need for greater and more predictable financing to achieve the SDGs.
30 January 2019: Two Wold Bank Group officials addressed ways to track progress on the SDGs, even while about two-thirds of the global indicators “have no data.” The op-ed by Mahmoud Mohieldin, Senior Vice President for the 2030 Development Agenda, UN Relations and Partnerships, and Haishan Fu, Director, Development Economics Data Group, was published in the United Arab Emirates (UAE) newspaper the National.
The authors acknowledge serious data challenges in tracking the SDGs, but describe a number of promising trends towards overcoming such challenges. These include:
- A recognition of the importance of a social contract regarding statistics and people;
- A recognition of the need for disaggregated data in policymaking; and
- The potential for the transformational role of new technologies in the development data space.
Mohieldin and Fu emphasize the need for building and sustaining trust throughout the “data value chain” and in the decisions that such data support. The authors report that over the last five years, both public and private sector entities, including the Bill and Melinda Gates Foundation, Unilever and the US National Aeronautics and Space Administration (NASA), have implemented data-sharing policies that promote the free use and reuse of data and improved accessibility through open data portals. They also note the World Bank Group’s (WBG) prioritization of data access.
The authors predict that national statistics offices (NSOs) will play a more dynamic role in partnering with citizens and civil society involved in the production and use of sustainable development data, building trust and tapping into new data sources. They recommend disaggregating data at the national and sub-national levels by age, gender, socioeconomic position and migration status, among others, which can help to identify those lagging behind and determine by how much, as well as to target policies to address their challenges. While in some countries, such as Peru and India, NSOs have been publishing disaggregated data, many countries still lack the capacity to do so. According to the Identification for Development (ID4D) initiative, the authors add, 1.1 billion people worldwide cannot officially prove their identity; half of these are children whose births were not registered.
The authors also explain that new technologies are helping governments “reimagine” solutions and improve service delivery to achieve the SDGs. For example, in Haiti, mobile phones are being used to connect urban residents to jobs, services and economic opportunities. In the Philippines, governments are using GPS data from taxis to reduce accidents and improve emergency services. They also note that WBG projects are using big data and artificial intelligence to help governments better monitor policies to achieve the SDGs. The op-ed does, however, acknowledge concerns and risks associated with big data, including privacy risks.
Finally, Fu and Mohieldin underscore the need for greater and more predictable financing to achieve the SDGs, including domestic and international investments in data innovation, data interoperability and reproducibility, and strengthening systemic statistical capacity. They point to the Dubai Declaration agreed at the second UN World Data Forum in October 2018, which seeks to encourage countries to plan for predictable financing in their national data and statistical efforts. [Op-ed on SDG Data Challenges]