Sustainable Development Governance

The COVID-19 crisis served as a wake-up call about the urgent need for solid and reliable data systems at the national, regional and global level. The pandemic has tested the ability of governments and public health stakeholders to implement coordinated and effective measures to track the spread of the virus and to set up appropriate containment and treatment responses. Therefore, it is essential to have all necessary information at hand to manage the crisis with informed decisions and evidence-based political leadership.

Since the start of the COVID-19 crisis, we have seen a sharp increase in funding for health-related data and statistics – rising from a 10% share to more than a third of all funding for data and statistics. At the same time, however, funding for other sectors such as social infrastructure and protection have fallen precipitously, from 20% to 7%.^[1] The example of health-related data and statistics as an essential need during a health crisis also demonstrates for the fundamental need for solid data-based information systems for the design and monitoring of crisis recovery interventions in general.

The 2030 Agenda has set ambitious and cross-cutting goals for sustainable development that provide a strategic framework for coordinating of national and global development efforts towards a sustainable future. Regular measurement of progress, combined with open and transparent access to data and statistics, will be vital to keeping governments on track to meet their SDG targets and consequently to set up Recover Forward policies and interventions.

Given the breadth and complexity of the SDGs, many different types of data are required with varying levels of coverage and disaggregation. This has led to increased demand on the partner side for capacities in order to meet the SDG monitoring challenge.

The Need to Broaden the Data Ecosystem Landscape for SDG Monitoring

A growing demand for data and statistics along with a rapidly expanding landscape of data producers and users call for a redefined understanding of capacity development for data. It is therefore essential to first gain a better understanding of the various dimensions of challenges that countries are facing and how best to address them.

Experiences from the VNRs show that most countries lack data to measure the progress of all the relevant SDG indicators. One of the crucial concerns is the lack of timely disaggregated data on the populations that are at risk of being left behind. However, countries noted that national statistical offices (NSOs) could benefit from data and analysis produced by other stakeholders. Collaboration between NSOs and other potential data producers can accelerate the availability of data and help to close data gaps for measuring the progress of the 2030 Agenda in areas that are relevant and a priority for countries.

Alternative Data for SDG Monitoring

To address effectively and efficiently the breadth and depth of the SDGs, governments are increasingly adopting alternative or non-traditional data sources and methods to fill data gaps and complement traditional data. The key alternative data sources and approaches to be highlighted are geospatial data, citizen-generated data, administrative data, big data and open data. A more detailed insight into the different kind of alternative data and their potential use is illustrated in the 2030 Agenda’s data challenge report.

SDG Interlinkages and its Implications

With the 2030 Agenda covering all kind of aspects for sustainable development, there is of course the phenomenon that there are many interlinkages among the different targets. This is not only the case at the domestic level – it is also true at the cross-national level when it comes to global spill-over effects, such as consumption patterns in one part of the world causing serious damage along the value chain in other parts of the world.

Integrated Recover Forward interventions need coordinated action from various stakeholders. Therefore, it is clearly essential to have solid, timely and granular information available in terms of data and statistics that allow for profound analysis of SDG interactions, for simulation and forecasting of different recover forward scenarios – and then of course for tracking progress.

For data-based integrated policymaking (statistical) indicators can act as useful communication and coordination devices between different interest groups, helping to raise the salience of different issues, identify performance gaps, and mobilize efforts. This potential communicative function and “framing role” of indicators can operate between policymakers in various ministries of national governments and thus foster policy coherence.