“The World We Want” for Data: Articulating Clear, Compelling Goals on Data for Development

Written by Jessica Espey

At the end of January 2019 in Bern, Switzerland, a group of bilateral and multilateral donors, as well as data technicians, came together to discuss the funding for data landscape at a gathering hosted by the Government of Switzerland. The scenario painted was grim. Current resources allocated to data and statistics are woefully inadequate to ensure all countries have the systems in place to track progress on sustainable development and achieve the SDGs.

In 2015, the Sustainable Development Solutions Network (SDSN) and partners provided a conservative estimate of the data financing gap of at least US$ 500 million per annum, with US$ 200 million of this being provided by the international community. This year, PARIS21 and Overseas Development Institute (ODI) have recalculated these figures to include additional investments in statistical capacity (among other things), and now estimate the international community needs to provide more than double that amount – and ideally an additional US$ 700 million per annum.

The Sustainable Development Goals (SDGs) place high importance on using data to monitor and ultimately achieve sustainable development, and include such commitments as disaggregating data by income, gender, age, race, ethnicity, migratory status, disability, and geographic location to ensure we leave no one behind (see Target 17.18). The SDGs also include specific targets to increase availability of data for management and monitoring of sustainable development, and to build the capacity of countries to use it (17.18 and 17.19).

But in spite of these compelling objectives, the international community has been reluctant to increase funding for data and statistics. At the meeting in Bern, participants reflected on why this might be so: lack of appetite for systems funding, increased attention on humanitarian crises, declining support for official development assistance. But for me, one excuse rang above the rest: We, the international data community, have not provided a short and compelling pitch for why data is so crucial for international development.

The problem with this is that the international data community, including governments and their national statistical offices, don’t want one thing; national data systems are complex, comprised of a broad range of tools, all for different purposes, each with different ministry partners, each with different technical requirements. Furthermore, the “data revolution” means many of our traditional approaches are being turned on their heads or are being forced to modernize. It is in the context of this topsy-turvy environment that donors are being asked to cough up, and it’s hard for them to know how best to do so.

The Cape Town Global Action Plan (CTGAP), agreed in January 2017, marks an important consensus on how best to modernize data systems for sustainable development but it, too, feels like something of a laundry list. If we are going to get people’s attention, we need clear and compelling advocacy messages, like investing in data will save x people’s lives, or will generate cost efficiencies of y.

These “sales techniques” may seem crude but (1) they work (as shown by the campaigns of Save the Children, UNICEF and others to successfully fund advances in maternal and child health), and (2) we have the evidence to ensure they are factually correct. There are a host of compelling case studies on the economic and social returns from investing in data, as per a recent series of TReNDS and the Global Partnership for Sustainable Development Data that highlighted the cost-saving impacts of transparent budgetary data in Nigeria, the life-saving potential of innovation health tracking systems in Bangladeshi slums, and the US$ 2 billion global economic benefit of the US government launching and investing in the Landsat earth observation program, among other cases. These examples should be used in a coordinated, strategic effort to win the attention and investment of international and domestic financiers. 

In addition to a coordinated advocacy campaign, the data community may do well to consider some more quantifiable, public goals that help the global community to track progress in building national data systems – a useful suggestion raised by Haishan Fu, the Director of the World Bank’s Development Data Group, in Bern.

It has been said that the Millennium Development Goals (the predecessors of the SDGs) “broke new ground […] catching the attention of millions of policy makers at national and international level [sic],” due to their simplicity and ability to focus resource investments (Erna Solberg 2016).  This is what we need for data.

The High-Level Group for Partnership, Coordination and Capacity-Building for Statistics for the 2030 Agenda for Sustainable Development (trust statisticians to come up with such a precise and unwieldy name!) is perhaps best placed to devise such a list, given that it is comprised of a representative group of Member States and has representation from regional and international agencies. They should attempt to whittle down a short-list of 8 to 10 clear, compelling goals that draw upon the CTGAP, the targets already featured in the SDGs, and priorities articulated by countries through the UN Statistical Commission, such as:

  • Leaving no one behind through investments in the census (e.g. Increase investments in the 2020 Census and support to all countries to improve their interim population estimates, using new methodological approaches – as per those identified by the POPGRID consortium), and improvements in disaggregated data (e.g. SDG Target 17.18: "By 2020 increase significantly the availability of high-quality, timely and reliable data disaggregated by income, gender, age, race, ethnicity, migratory status, disability, geographic location and other characteristics relevant in national contexts);

  • Advances in civil registration and vital statistics (CRVS) system coverage (e.g. Increase investments in the 100 low- and middle-income countries that lack functional CRVS systems and under-record or completely fail to record vital events of specific populations);  

  • Advances in data openness and transparency (e.g. via a measure of the Open Data Inventory ODIN);

  • New data partnerships for innovation (e.g. x countries have established multi-stakeholder partnerships to fill key data gaps in national statistics, either for SDG monitoring or high-frequency data for policy- and decision-making, drawing upon new data sources such as big data and telecommunications data);

  • The widespread utilization of geospatial imagery (e.g. All countries are utilizing geospatial imagery and other earth observation data for improved environmental monitoring and geographic disaggregation, in partnership with national earth observation agencies and teams);

  • Supportive governance frameworks (e.g. All countries have a governance framework or statistical law that enables the utilization of third-party data, including that provided by private companies and academic institutions), and so on.

Such goals would not only make it easier for us to communicate what we want to donors, but also to our own governments, as well as making it easier for the disparate global data community to pull in the same direction. As John F. Kennedy once said, “By defining our goal more clearly, by making it seem more manageable and less remote, we help all people to see it, to draw hope from it, and to move irresistibly towards it.” (John F. Kennedy Presidential Library and Museum)