A new United Nations-backed on timely Sustainable Development Goal data has people talking about the world’s natural resource in shortest supply—time.
How would you feel about studying for a degree where you get no feedback on your performance until after your graduation date? How about signing a lease on a new apartment before knowing the cost of the rent? Or having to decide where to send 100,000 yellow fever vaccines before you have information on the location of the latest outbreaks? The latter is a common problem, and in this and many other ways, data lags cause needless suffering and waste scarce resources daily. Data is knowledge, and knowledge is power—the power to effect change before it’s too late.
Most countries do not regularly collect data for more than half of the Sustainable Development Goal (SDG)?global indicators.1 A United Nations survey in Africa and Asia found that, on average, data for only 20 per cent of the indicators is currently available,2 and poverty data on two thirds of the population of sub-Saharan Africa is based on surveys that were done before the SDGs were adopted in 2015.3 For policymakers with a sense of urgency, it’s maddening that much of the data being used to monitor the SDGs was?collected before the SDGs were even agreed upon.
Timeliness—the most important of the five facets of quality data?
There are five facets of robust data: completeness, consistency, accuracy, validity and timeliness. Improving the timeliness of the data could arguably stand to make the greatest positive impact. The first two months of this decade-long countdown to 2030 have already seen a coronavirus (COVID-19) emerge and rapidly spread, Australia burn and Jakarta flood. More than ever, it feels that time is the most precious of all resources.
Timeliness is one reason people get excited about big data such as mobile phone metadata, and social media, satellite and remote sensing data. Others are excited by the prospect of going beyond real-time data into forecasting or predictive models. Yet big data enthusiasts sometimes forget to remind the development community of the increasing importance of validated data, both in its own right and as a training tool for machine learning.4 This is starkly evident in agriculture, as noted by Stanford University professor David Lobell.5
“It’s usually not practical or affordable to get highly granular data with extremely high frequency,” says Claire Melamed, CEO of the Global Partnership for Sustainable Development Data. “But non-traditional data is much more useful with solid foundational systems. Where you can get both together—for example, detailed agricultural surveys and weekly satellite data—then you get a multiplier effect. In those cases, it’s now possible to do things we couldn’t have dreamed of 10 years ago, like estimate crop yield down to the half-meter or intervene in illegal logging sites before an entire forest is decimated.”6
The battle for governments and multilateral institutions to understand the importance of data has now largely been won.
The promise of the data revolution has not been oversold, but the investment needed to build robust, validated models tends to be glossed over. This in turn can lead to a “peak of inflated expectations” and a?“trough of disillusionment”, as explained by researchers from the Gartner technology company.7
Aligning data and decision-making
How timely should data for SDG-related decision-making be? The acceptable interval between data points depends on the robustness of methodologies, anticipated speed of change over time and how frequently inputs are needed for decision-making.
In the development data community, the buzzwords of “real-time data” and “nowcasting”, so popular five years ago, have been replaced by an emphasis on aligning the frequency of data supply with the frequency of data-led decision-making. Planning for an adequate number of places for students enrolling in school is a once-a-year decision process, and crop harvests require seasonal interventions, whereas health crises may evolve week to week.
“In the field of health, timely data can be very useful in resource allocation, especially for vaccines. We have cases where we have a lot of stock in vaccines. And we have shortages in some areas and excesses in others, so timely data, especially for those that need vaccines, is very important for proper resource allocation”, says Yusuf Murangwa, Director General of the National Institute of Statistics of Rwanda. “With satellite data we can now tell if a crop has failed in 2-3 weeks, giving us valuable time to either intervene or plan for supporting a population that may be suffering from a poor harvest”, he explained.
A bad case of ‘pilot-itis’
The battle for governments and multilateral institutions to understand the importance of data has now largely been won. The world’s most successful private companies are now powered by real-time data about us, our habits, history and preferences. Governments looking to formalize their economies, boost tax revenue and reduce wastage in public services know they cannot do so without data. Despite this cultural shift, most national data systems remain chronically underfunded, and a critical mass of methods leveraging non-traditional data sources have failed to go to scale.
Timely data on whether a population is getting what it needs—such as better hospital waiting times, doctor ratios, school results and air pollution figures—are a powerful tool for assessing progress and fostering swift accountability. Yet the public are not clamoring for widespread investment in data systems; the media is full of stories about how data can be used to harm citizens, rarely balanced by reporting on how data can be used to improve lives.
Thankfully, the 2030 Agenda for Sustainable Development is a powerful accountability mechanism, and for countries that are committed to achieving the SDGs and want solid data to monitor progress the outlook is promising.
First, although data financing remains pressing, many are now grasping the value of investing in data systems and capacity-building. The 2020 United Nations , to be held in Bern, Switzerland, from 18 to 21 October, could be an opportunity to signal cooperation and progress in this regard.
Second, with so many data solutions readily available, the challenge is not “can this be measured on a timely basis?” but rather “how do we adopt new methods and make them stick?”.
Third, when it comes to timely data, the wisdom of the crowd has never been more critical: exchanging best practices on data protection and privacy, legal frameworks and quality assurance for non-traditional actors from civil society and the private sector are just a few of the areas where international dialogue and cooperation yields rapid progress.
Data for Now
A new initiative called , led by the United Nations Department of Economic and Social Affairs, the Global Partnership for Sustainable Development Data, the Sustainable Development Solutions Network and the World Bank, was announced by Deputy Secretary-General Amina J. Mohammed during the seventy-fourth session of the United Nations General Assembly in September 2019. It is aimed at curing the bad case of ‘pilot-itis’ afflicting the international data community. Eight Governments have signed on as ‘trailblazer countries’: Bangladesh, Colombia, Ghana, Mongolia, Nepal, Paraguay, Rwanda and Senegal. In a kickoff workshop in November 2019, those Governments, along with 60 experts from United Nations agencies, technology companies and NGOs, worked through areas in which National Statistical Offices have identified data lags as particularly harmful or wasteful, including agriculture, disaster management, education, forestry, migration, poverty-mapping, transport, urban planning and water. By narrowing in on specific pathways and approaches to common problems, the countries hope to adopt established methodologies and unlock resources for institutionalizing change. As expectations mount for a “decade of delivery” on the SDGs, the hope is that momentum will build over the course of this year.
In every country striving to achieve the SDGs, data lags prevent us from truly understanding who is being helped or harmed before it is too late to course-correct. Fighting for timely data will supercharge progress for the planet and its people.
Click for a closer look at the Data for Now initiative and how Rwanda is using timely data.
Notes
1. United Nations, Department of Economic and Social Affairs, “The Sustainable Development Goals Report 2019”, (New York, 2019), p. 3. Available from .
2. United Nations, Department of Economic and Social Affairs, “The Sustainable Development Goals Report 2018”, (New York, 2018), p. 16. Available from .
3. World Bank, “Research”, PovcalNet. Available at (accessed 08 January 2020).
4. Claire Melamed, “The race to innovate for development should not leave foundational data systems behind”, 缅北禁地Chronicle, vol. LV, Nos. 3 and 4 (December 2018), pp. 58-60. Available at /en/chronicle/article/race-innovate-development-should-not-leave-foundational-data-systems-behind.
5. David Lobell, “Big data has transformed agriculture—in some places, anyway”, Scientific American, 18 April 2019. Available at .
6. Claire Melamed, Statement at Data for Now inception workshop, National Institute of Statistics Rwanda, Kigali, Rwanda, 13 November 2019.
7. Gartner, “Gartner Hype Cycle”. Available at (accessed 08 January 2020).
?
The 缅北禁地Chronicle is not an official record. It is privileged to host senior United Nations officials as well as distinguished contributors from outside the United Nations system whose views are not necessarily those of the United Nations. Similarly, the boundaries and names shown, and the designations used, in maps or articles do not necessarily imply endorsement or acceptance by the United Nations.
