Photo: World Bank
Photo: World Bank

“The achievement of the SDGs hinges on delivering economic growth that benefits everyone, empowering women and achieving gender equality, and taking ambitious action on climate change. We have a responsibility to future generations to not only achieve these goals, but to do so in a way that leaves no one behind.”

Justin Trudeau, Prime Minister of Canada

As countries and development actors ensure that no one is left behind, the call for bridging the data divide has become a principal issue of the 2030 Agenda. Data and statistics are essential to inform policy decisions and the adoption of the Sustainable Development Goals (SDGs) has further cemented the importance of reliable, high-quality, and timely data. Still, the continued lack of basic data and weak statistical systems remain a challenge in the developing world. Nearly two-thirds of the 232 SDG indicators adopted by the UN Statistical Commission have no sound statistical basis, and one-third often lack an agreed methodology for measurement.

To bring the development and improvement of statistics to the forefront of the development agenda, the OECD worked in close collaboration with PARIS21 to produce the 2017 Development Co-operation Report (DCR) on “Data for Development”. Every year, the flagship report addresses an important challenge for the international development community and provides practical guidance and recommendations. This 55th edition of the DCR provides a comprehensive analysis on the data constraints faced by developing countries today, and the policy options to compile better statistics for sustainable development. 

There is a worrying data divide…

A global data divide persists today in developing countries. This divide is characterized by the scarcity of basic data about people and the planet, and the weak incentives and capacity to fill these gaps.

Good data for development is lacking

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Source: OECD Development Co-operation Report 2017

…but opportunities are emerging with the data revolution

At the same time, we observe a surge in new data sources and types of data enabled by digital technologies. This June, Canada will be hosting “Big Data Toronto”, a conference and exposition that will focus on the technical and practical cases of big data such as predictive analytics, data governance, privacy, and cybersecurity. Big data has been a driving force in Canada’s innovative business sector, but its use in developing countries is only  emerging now.  However, just as M-Pesa, a mobile banking application created in Kenya in 2007, enabled the African continent to address financial inclusion, a mobile phone powered data revolution could help developing countries address long-standing data gaps. Developing countries have an incredible opportunity to leverage the power of big data to transform various government operations. Social media, mobile telephone records, sensors, web scraping, and satellite imagery represent some of the new information sources offering an opportunity for better data. In Sri Lanka and Côte d’Ivoire, governments are using mobile records to inform urban planning challenges, enable disease surveillance, and even undertake poverty mapping in cost effective ways. In Bangladesh, Haiti, Kenya, Nigeria, and Tanzania, governments are starting to use geospatial information to understand socio-economic phenomena including educational outcomes (e.g. literacy, numeracy) and access to contraceptives. In Egypt, crowd-sourced data is collected to better understand and combat sexual harassment and violence

Canada’s “data for development” agenda

Canada is devoting significant efforts to improve the data agenda in its development policy. First, through its Feminist International Assistance Policy, Canada is improving public-sector institutional capacity and building a strong base of evidence to support gender equality actions in the countries that Canada supports. Today, integrating gender statistics into national statistical plans and improving the reporting and use of gender-related data remains a challenge in several countries. Second, Canada’s efforts to improve statistics in developing countries through partnerships with private data providers are noticeable. Canada is supporting better birth registration systems in Tanzania, DRC, Sudan, Ethiopia, and Mali, where the needs for improving civil registration is critical. Only 13% of new births are registered in Tanzania. This work culminated in a newly-established Centre of Excellence for Civil Registration and Vital Statistics Systems, hosted by Canada’s International Development Research Centre (IDRC) and supported by Global Affairs Canada. This global knowledge hub is working to improve access to information and expertise, including global standards, tools, research evidence, and good practice. Its purpose is to help countries develop, strengthen, and scale-up their civil registration and vital statistics systems. These programs will allow governments in the future to have better data for designing early childhood policies, and to better allocate education and health expenditure.

Third, promoting inclusive governance and accountability is another area where Canada’s development agenda overlaps with the gloal data agenda. From a data perspective, this involves working together with governments and civil society actors to improve citizen participation (both in data generation and data use) and accountability. To enable these agendas, Canada hosts the Open Data for Development (OD4D) program. Established in 2015, OD4D is a multi-donor initiative funded by IDRC, the World Bank, Global Affairs Canada, and the UK’s Department for International Development, that leverages a global network of partners to use open data in generating greater accountability and transparency, local innovation, and better delivery of key public services such as education and health.

Concrete actions to bridge the data divide

The DCR identifies six key data actions to make the most of the power of data for sustainable development. Each action will require strong political leadership in developing countries to ensure that the abundance of data actually enables development. This involves promoting the case of data for development, while ensuring that statistics are produced according to high-quality standards, while also protecting privacy and confidentiality.

Six concrete data actions to bridge the data divide

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Source: OECD Development Co-operation Report 2017

Data action 1. Make statistical laws, regulations, and standards fit for evolving data needs. To build inclusive data ecosystems, institutional and legal frameworks need to be fit for purpose. The growing number of actors and institutions involved in data production stress the need for clear legal and quality standards. Immediate actions in this direction are proposed: developing and updating statistical and open statistical laws, authorizing national statistics offices to adopt new modes of data collection, new forms of partnership, and data dissemination.

Data action 2. Improve the quantity and quality of financing for data. Investing in statistical systems must be a priority for developing countries and their development co-operation partners alike. To achieve this, financing has to increase and then stabilize if national statistical systems are to respond to the growing data demand. Innovative mechanisms for domestic resource mobilization for statistics, public-private partnerships, and data philanthropy should be developed.

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. These should go beyond building capacity to collect data. Taking three distinct features into account — people, organizations, and the enabling environment — a new capacity development 4.0 should become best practice for national statistics offices. This will entail emphasizing soft skills including leadership, change management, strategic thinking, and advocacy, and taking the user’s perspective into account.

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 harmonizing investment in data and support for statistical systems is a promising approach. For this, aligning incentives for producing data for national strategies will be essential.

Data action 5. Invest in and use country-led results data to monitor progress towards the SDGs.

External actors need to support country-led strategies and data ecosystems. This requires clear vision and pragmatism in dealing with results-based frameworks. It also means ensuring that results from independent data collection efforts are made accessible to development actors to avoid unnecessary duplication.

Data action 6. Produce and use better data to help understand the overall state of SDG financing. Better data on development finance is needed to gain a more comprehensive financing picture and to allow developing countries to better plan and budget their national development strategies.

Improving statistics for sustainable development is a task for all — developing countries cannot do this job alone. They need political and financial support to develop the statistics and analytical tools that will show how agreed national and global objectives can be met. For this, development co-operation providers such as Canada need to continue to provide efficient and consistent financial and technical support to guarantee long-lasting improvements in the provision of quality statistics.


By Johannes Jütting, Manager, PARIS21 and Jean Lebel, President, Canada’s International Development Research Centre (IDRC)

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