Data for Development | OECD Development Co-operation Report 2017

Data are a prerequisite for delivering the United Nations (UN) 2030 Agenda for Sustainable Development and ensuring that no one is left behind. The Development Co‑operation Report 2017 focuses on data for development because quality, timely and disaggregated data are crucial for achieving the ultimate goal of development: improving the welfare of people and fighting poverty.

There is, however, a major risk that the continued scarcity of basic data in developing countries about people and the planet, and weak incentives and capacity to fill these gaps, will hold back success.

The Sustainable Development Goals (SDGs) are putting high demands on national statistical systems the world over. Most countries, including many OECD countries, have not yet started collecting data for many indicators in the UN global SDG indicators framework. The challenges are even more critical for many developing countries with low statistical capabilities. For example, 77 developing countries have inadequate poverty data. Only 56% of countries worldwide have birth registration data that are 90% complete, with just 15% of countries in sub‑Saharan Africa having these data, 33% in Southern Asia and 36% in Southeast Asia. Only 37 countries have national statistical legislation that complies with the UN’s Fundamental Principles of Official Statistics. Serious methodological and strategic challenges still need to be met, including the need to strike a balance between producing the data for global monitoring, on the one hand, and for national policy making on the other.

The report analyses how developing countries and their development co‑operation partners can bridge the data divide by seizing the unprecedented opportunity – and mitigate the risks – presented by the convergence of the power of technology with the most ambitious development plan to date: the 2030 Agenda. New technology and the so‑called data revolution make it easier, faster and cheaper to produce data that decision makers need to make informed choices on policies and priorities. However, simply producing more data is not enough: data must be transformed, analysed and used to be useful for policy making, monitoring and accountability.

The data revolution offers governments and national statistical offices a welcome opportunity to produce more useful data by generating data from new sources, which can complement and strengthen, though not replace, official statistics. Some developing countries are already embarking on the data revolution with positive results. Ethiopia, South Africa, Sri Lanka and Uganda have improved the efficiency and accuracy of census and survey data collection by using computer assisted personal interview devices, such as computer tablets or other handheld devices. Geospatial data are helping national statistical systems monitor socio‑economic and environmental conditions, enabling geographic disaggregation and making geo‑located data more dynamic.

This report identifies ways to bridge the data divide for sustainable development. There is a need for strong political leadership in developing countries to ensure that data enable development. This involves promoting the cause of data for development while making certain that data are produced to high‑quality standards, protecting privacy and confidentiality. The Development Co‑operation Report 2017 recommends six concrete actions to make the most of the power of data for sustainable development.

Data action 1. Make statistical laws, regulations and standards fit for evolving data needs.

To build inclusive data ecosystems that benefit global development and individual citizens, institutional and legal frameworks need to be fit for purpose. The growing number of public, private, and civil society actors and institutions involved in the production and use of data make the need for clear legal, ethical, and quality standards and protocols even more urgent. These should regulate the use of traditional and new sources of data, fostering the trust that is needed to inform good policies and development results.

Data action 2. Improve the quantity and quality of financing for data.

Investing in statistical systems must become a strategic priority for developing countries and their development co‑operation partners alike. Budgets need to grow if national statistical systems are to respond to the growing demand for more and better data. By making data a cross‑cutting priority for development co‑operation, providers can start to recognise it as part of the essential infrastructure for delivering on national, regional and global development commitments.

Data action 3. Boost statistical capacity and data literacy through new approaches.

New, more comprehensive approaches to statistical capacity development need to be developed and piloted that go beyond building capacity to collect data, to building the capacity of national statistical offices to play an evolving and multifunctional role in the data ecosystem, and to improve the institutional and enabling environment for data and statistics.

Data action 4. Increase efficiency and impact through “data compacts” or other co‑ordinated, country‑led approaches.

Developing countries should better align incentives for producing data for national policy making and global monitoring through mutually accountable inclusive partnerships among data producers and users. The establishment of data compacts for co‑ordinating and harmonising investment in data and support for statistical systems is a promising approach; it should be tested further to ensure that it meets the needs of all actors and fosters mutual accountability for delivering on joint, performance‑based action plans.

Data action 5. Invest in and use country‑led results data to monitor progress towards the Sustainable Development Goals.

International development actors must break with the business‑as‑usual approach; rather than collecting and using data to meet their own reporting and accountability pressures, they need to support country‑led strategies and data ecosystems. This requires clear vision and pragmatism in dealing with the pressure to attribute results to every aid dollar. It also means ensuring that results from any independent data collection efforts are accessible to all development actors and co ordinated with the statistical objectives of developing country governments.

Data action 6. Produce and use better data to help understand the overall state of SDG financing.

Data on development finance also need to improve. This means producing a comprehensive financing picture by increasing the availability and transparency of quality development finance data and improving methodologies and standards with the objective of equipping developing countries to plan and budget their national development strategies and priorities.

Read the full book on: 10.1787/dcr-2017-en