New OECD Report outlines six data actions for sustainable development
Whether filling data gaps on indigenous populations to leave no one behind or harnessing satellite imagery to combat climate change, achieving the Sustainable Development Goals hinges on our ability to harness evidence, technology, and data science. However, we know producing and providing more data alone will not be enough. Data must be transformed, analyzed, and most importantly, used for policy making, monitoring, and accountability. Data must be a catalyst for change.
The OECD just released the timely, highly relevant Development Co-operation Report 2017: Data for Development. The report provides a holistic view of data-driven development and identifies concrete actions to advance the job of improving the quality of data and statistics. The report highlights six concrete actions that international development partners, civil society, and the private sector can take to support the priorities and efforts of governments and national statistical systems to bridge the data divide. The release of the report is accompanied by highlights in development aid trends and allocations and profiles of providers of official development assistance.
Harnessing data for development is a topic that runs deep within the ethos of Open Data Watch. Working on the report with PARIS21 and OECD provided an opportunity for us to contribute our experience and learn from our partners and our own research.
We believe the national statistical systems (NSSs) can take advantage of the data revolution to build a sustainable data ecosystem. In chapter 3, we explore the opportunities, enablers, and challenges national statistical offices face in using big data and other new sources and methods. We review country capacity, gaps and strategies for putting in place the right data. As the chart below displays, additional work is needed to ensure NSSs are operating at high-capacity to provide the fundamental statistics. We dug deep to find out more about countries’ capacity to deliver fundamental statistics and understand variations in statistical capacity among different countries. The chapter sets out what needs to happen to build capable statistical systems: ensure better leadership and governance; strengthen core statistical programs; modernize national statistical systems through innovation; and focus more on disseminating and using statistics.
But as Martine Durand noted (and we agree) statisticians – especially those in developing countries – cannot do this work alone. Increasing the capacity of national statistical offices (NSOs) will require the support of the entire government, donors, international organizations, and private sector. The data ecosystem is expanding and we need all hands on deck. The chapter tackles issues such as how to rethink the support of old actors and how to integrate the participation of new actors in capacity building efforts.
More financial resources are needed to build statistical capacity as the recently released PRESS 2017 demonstrates. Despite the reputation data have gained as the catalyst for sustainable development, statistical systems remain under-resourced and under-staffed. As those inside and outside the statistical community push for more funding for statistics, such calls should be coupled with a better understanding of how to most effectively use additional funds. The chapter seeks to identify those priority items – leading us on a path to demand-driven, holistic approach to strengthening statistical systems.
Building on the work of PARIS21’s Capacity Development 4.0, the chapter calls for a revitalization of donor support for statistics. As we shift away from traditional approached, with their heavy reliance on technical assistance and a focus on the supply side and donors’ priorities, we are adopting new approaches that emphasize partnerships, support aligned with national statistical plans, and a focus on the use and the users of data. The chart below, taken from chapter 4 of the report, compares these two approaches and sets the stage for the detailed priorities described in the chapter.
The Development Co-operation Report is not limited to these two topics alone. The remaining chapters discuss the value of data, making better use of results data, and how to improve development finance data. Improving sustainable development is a monstrous task for all actors. Political leadership, in a supportive institutional framework together with financial, technical and human resources, public-private partnerships and a user-focus are crucial if data are to drive and enable development. Stefan Schweinfest says it best in his “In my view” piece of the report – we need a global data architecture for sustainable development.
In closing, a wealth of knowledge is presented in Development Co-operation Report. It presents an opportunity not to be missed by all stakeholders to take actions. The findings and recommendations of the report will provide valuable knowledge on the latest in the status of countries in meeting the data for development demand. And the options provided will help policy makers to build on the opportunities presented to make data work for sustainable development.
Read the full report here: