Data & Analytics

Data and analytics are increasingly recognized as fundamental elements in achieving the Sustainable Development Goals (SDGs). These 17 goals, adopted by the United Nations in 2015, aim to address global challenges such as poverty, inequality, climate change, environmental degradation, peace, and justice. Each goal is interconnected, requiring a holistic approach to achieve sustainable development by 2030. Within this framework, SDG 17, "Partnerships for the Goals," is particularly crucial as it highlights the need for high-quality, timely, and reliable data to drive progress across all goals.

The importance of data and analytics in realizing the SDGs cannot be overstated. Accurate and insightful data is necessary for several key aspects: assessing current progress, identifying existing gaps, informing policy-making, and guiding the allocation of resources. For instance, in addressing SDG 1, "No Poverty," data helps in understanding the demographics of poverty, allowing for targeted interventions. Similarly, for SDG 3, "Good Health and Well-being," data analytics play a crucial role in tracking disease outbreaks, understanding health trends, and improving healthcare delivery.

In the education sector, under SDG 4, "Quality Education," data can inform about areas where educational resources are lacking or where dropout rates are high, guiding efforts to enhance education systems. Additionally, for SDG 13, "Climate Action," data is indispensable for understanding climate patterns, predicting future scenarios, and formulating strategies to mitigate and adapt to climate change.

Advancements in data collection and analytics methods have opened up new possibilities. Mobile technology, for example, has revolutionized data collection, enabling real-time gathering and dissemination of information even in remote areas. Remote sensing technologies, such as satellite imagery, provide critical data on environmental changes, agricultural patterns, and urban development. These methods not only expand the scope of data collection but also enhance its accuracy and timeliness.

However, challenges remain in harnessing the full potential of data for the SDGs. These include issues related to data availability, quality, accessibility, and interoperability. In many parts of the world, especially in developing countries, there is a significant data deficit. This gap hinders the ability to make informed decisions and effectively address the SDGs. Moreover, data collected must be reliable and relevant to be useful in policy formulation and implementation.

To overcome these challenges, partnerships between governments, private sector, academia, and civil society are vital. These collaborations can foster innovation in data collection and analytics, ensure data sharing, and build capacities for data analysis. Furthermore, there is a need for a global framework to standardize data collection and reporting methods, which will facilitate comparison and aggregation of data across regions and countries.

Leaders require new tools to make better strategic decisions in an increasingly complex and uncertain environment. The World Economic Forum offers Strategic Intelligence as an engagement option to help you understand the global forces at play and make informed decisions that will have a positive impact on your organisation. The platform contributes to a range of SDGs, including Goals 9 and 17.
Furthering SDGs 5 and 10, this report aims to better understand the role gender plays in the global research enterprise and inspire evidence-based policy driven by powerful data. It examines research participation, career progression and perceptions across the European Union and 15 countries globally in 26 subject areas. The report concludes that while the participation of women in research is increasing overall, inequality remains across geographies and subject areas in terms of publication outputs, citations, awarded grants and collaborations.
The latest analysis of SDG-supporting research focusses on SDG 11: Sustainable Cities and Communities. This graphic shows key metrics for research into Sustainable Cities.
The cost-effectiveness and reliability of waste collection services in informal settlements can be difficult to optimize given the geospatial and temporal variability of latrine use. Daily servicing to avoid overflow events is inefficient, but dynamic scheduling of latrine servicing could reduce costs by providing just-in-time servicing for latrines. This study used cellular-connected motion sensors and machine learning to dynamically predict when daily latrine servicing could be skipped with a low risk of overflow.

The Lancet Global Health, Volume 8, January 2020

An Article in support of SDGs 2 and 12, analysing the affordability of the EAT–Lancet benchmark diets using food price and household income data for 744 foods in 159 countries, collected under the International Comparison Program.
National statistics are an essential component of policy making. Yet many national statistical systems face challenges in collecting, producing, analysing and disseminating the data required for sustainable development. Furthering SDGs 10 and 15. This report introduce a pioneering approach to capacity development – Capacity Development 4.0 – that brings together new data stakeholders, does more to involve users and promotes a holistic view of statistical capacity development.
Detailed information on research and development (R&D) spending of the private sector is very limited, particularly when the interest is on small and medium enterprises or focuses on companies active in multiple technology areas. This lack of data poses challenges on the robustness of quantitative analyses and, as a consequence, on the reliability of evidences needed, for example, to support policy-makers in policy design. This paper proposes a patent-based method to estimate R&D expenditure in the private sector.
This case study shows the contribution of the Global Partnership for Sustainable Development Data to the Open Algorithms Initiative. It addresses how to unlock the potential of private sector data for public good purposed in a safe ethical, scalable and sustainable manner furthering goals 9 and 17.
This case study uses survey and satellite data to help better protect those working in agriculture in Kenya and Tanzania against drought and climate change, helping to advance SDG 2 and 13.

United Nations University, November 2019.

Contributing to SDG 10 (Reduced Inequalities) and SDG 16 (Peace, Justice and Strong Institutions), this research prioritized engaging with young people as research partners in order to examine the needs of children exiting violent armed groups.