Data Innovations for the Public Good

The second assumption was that the holistic, integrated SDG framework would provide both the political impetus for innovations in data use (to design successful policies and programs to achieve the goals), and the financial means for statistical agencies to be able to measure public and civil-society progress.

A World that Counts assumed that the global adoption of the SDGs in 2015 would be the principal driver of increased investments in data that would underpin policy design by tracking developmental progress. We believe the authors made this assumption on the basis of three factors: (1) the impact that the Millennium Development Goals (MDGs) had on strengthening investments in data; (2) the potential for new technologies to mobilize cross-sector innovation and data-sharing; and (3) the MDGs’ demonstrated ability to withstand major global shocks.

The MDGs, launched in 2000, paved the way for greater political attention and investment in development and data. In 2004, the  Marrakech Action Plan for Statistics  was endorsed by the  UN Statistical Commission , who recognized the centrality of official statistics in measuring development results to support the “Monterrey Consensus,” which had aligned increased levels of development financing with the MDGs. Through the Marrakech Plan, the  Partnership in Statistics for Development in the 21st Century (PARIS21)  provided support for developing national statistics strategies. The Marrakech Action Plan spurred global initiatives to facilitate a 2010 round of population censuses, improved planning for household surveys, and the creation of specialized trust funds to provide financial support to these and related initiatives. International efforts under the Plan also bore fruit, leading the global community to recommit to this effort in 2011 under the  Busan Action Plan for Statistics , which focused on three themes: (1) fully integrating statistics in decision-making; (2) promoting open access to statistics; and (3) increasing resources for statistical systems.

A World that Counts emphasized that the SDGs would require data on a broader range of topics and from a greater range of sources than the MDGs: “more data on more topics.” This reflected the SDG agenda’s integrated approach to addressing social, environmental, and economic challenges, which would necessitate expanding the data sources required to track performance in real-time at localized levels (to include big data, citizen-generated data, and administrative data held by governments, businesses, and civil society). The report also recommended strengthening collaborations between public and civil institutions and the private sector to leverage new technologies and ways of using data through platforms and visualization tools. These collaborations were also expected to increase data sharing between private-sector entities for the development of public policy.

The third expectation was that technological advances driving wider applications of data for development within the momentum of the global development agenda would remain largely resistant to major shocks. This belief was based on the relatively limited impact of the 2008 global financial crisis on the development data agenda (apart from some small exceptions, such as the  2013 G20 Data Gaps Initiative , which had been planned to improve global financial stability). 

The SDGs provide a common indicator framework for cross-country comparisons of progress, and there have been clear improvements in developing data standards to support SDG monitoring. One key action was the creation of the  United Nations Inter-agency and Expert Group on SDG Indicators (IAEG-SDGs ), consisting of 30 members representing all regions of the globe. Launched in 2015 and working under the auspices of the  UN Statistical Commission , the IAEG-SDGs developed the global indicator framework for the goals and targets of the SDG agenda. They identified and defined 231 indicators, for which 219 had data by  October 2020 , as well as a refinement mechanism to systematically correct units of measurement and clarify terminology. The IEAG-SDGs was supported by four working groups, with many multilateral agencies contributing to develop guidance in specific areas and track indicator development. For example, through its global gender data program,  Women Count ,  UN Women  promotes the production of gender statistics on a regular basis, including by providing financial and technical assistance to improve data collection for SDG monitoring.

The creation of the SDG indicators and their accompanying guidelines on how to produce and collect data to construct the indicators, are innovations in the global statistical architecture. However, the SDGs’ impact on how governments formulate policies has been limited. This is not surprising, for two reasons. First, processes to formulate policies at the national and global levels were established long before the launch of the SDGs. Second, the data requirements for the design and testing of specific policies are more difficult to standardize for cross-country applications. For global governance, studies suggest that global summits, such as the High-level Political Forum on Sustainable Development, serve primarily as a platform for voluntary reviews and peer learning (Beisheim and Bernstein, 2020). Yet there is no robust evidence that such peer learning has steered governments towards structural and transformative change (Amanuma et al., 2019). While there is some evidence at the national and local levels that both state and non-state actors have started to formulate policies based on the SDGs (see, for example, Biermann et al. 2022), national governments primarily used the SDGs to report on their existing priorities (Tosun and Leininger, 2017). And the SDGs have not changed public budgets or financial allocation mechanisms in any important ways, with some exceptions at the local level (Valencia et al. 2019), where cities are more progressive than central governments in building coalitions for SDG implementation (Hickmann, 2021).

Unlike advances in indicators to monitor policy impact, improvements in data to support policy design and testing have remained largely invisible since A World that Counts was released. As such, it is difficult to assess whether the SDG framework actually triggered substantial investments in data for policy design, relative to the investments made in improving data for SDG monitoring. Especially as progress on the SDGs primarily reflects prior government priorities, it is unlikely that the 2030 Agenda triggered much of an increase in new forms of data for policy design.

By contrast, the impact of the COVID-19 pandemic has been a greater catalyst for data innovation to support policy formulation in three ways. 

Overall, the evidence suggests that the COVID-19 pandemic strengthened the policy pathway linking innovations in data supply to more effective public-sector actions. However, experts are divided on whether this pathway, post-COVID, will ever again exhibit the coherence and integration that it did when it was guided by the SDGs (Biermann et al. 2022). Returning to multi-year, coordinated policy pathways will require political leadership to renounce the transactional and reactive techniques embodied in their COVID-19 response. 

In terms of monitoring social outcomes, a number of initiatives inspired by the SDG indicator agenda were leveraged during the pandemic to improve data accessibility and public participation in policy assessment and advocacy. 

The pandemic helped increase public data availability and interest in data, building on the successes of open data initiatives, dashboards, and mapping that had been inspired by the SDG agenda (Gurin, et al. 2015; Pirlea, et al. 2023). Capitalizing on these advances gave a large share of the world’s population access to visual-friendly evidence of the pandemic’s progress, updated in near real-time. The  Johns Hopkins dashboard  was considered a “springboard” that encouraged similar presentations (Koch, 2021). Additionally, while datasets on the prevalence of viruses had been available before, the scale and potential to further analyze viral progression expanded quickly. These initiatives also provided opportunities to improve media coverage of the pandemic’s evolution, as journalists and researchers were able to better analyze local and regional outbreaks and the demographics that drove these outbreaks.

The adoption of the SDGs marked a pivotal moment that would inspire new investments in data to inform policy design and to monitor progress towards the global targets. Since the publication of A World that Counts, however, the COVID-19 pandemic has surpassed the SDGs in spurring data innovation for policy design, even while pandemic responses leveraged SDG-inspired efforts to improve data access, visualizations, and mapping. As such, future research might assess the prospects of sustaining these innovations in data collection, data partnerships, and data-based decision-making in a post-pandemic world.

●      What are the key lessons learned from the COVID-19 pandemic regarding the integration of data-driven approaches into public policy formulation and implementation?

●      What are the challenges and opportunities that the COVID-19 pandemic revealed in terms of data governance, privacy, and the ethical use of data in public decision-making, and how can these challenges be addressed?

●      To what extent has the policy pathway connecting innovations in data supply to effective public sector interventions been reinforced by the pandemic, and what challenges exist in sustaining this pathway post-COVID?

These research questions aim to explore the multifaceted relationship between data innovations, policy design, and how they are affected by external shocks, such as the COVID-19 pandemic.