Revisiting the Data Revolution:
A Pathway to Sustainable Development Goals
By Shaida Badiee
21 July 2025
I served as co-chair of the Sustainable Development Solutions Network (SDSN) Thematic Research Network on Data and Statistics (TReNDS) from 2015 until its closure in late 2024. Before concluding our work, we made a concerted effort to document the network’s key lessons and achievements, which we published in a final report. I reflected on this journey in a subsequent blog, highlighting TReNDS’ impact in fostering collaboration across a wide range of stakeholders. Building on this foundation, we partnered with several members of the network to critically examine the underlying assumptions of the data revolution. In the blog, I summarize the most important takeaways for guiding future investments in data, drawing on insights from a recently published paper led by Alex Fischer.
Understanding the Data Revolution
In recent years, the term “data revolution” has gained popularity as a transformative force for tackling global challenges. With the rise of big data, advanced analytics, and widespread connectivity, data has become recognized as a crucial element in achieving the United Nations’ Sustainable Development Goals (SDGs). However, as we explore this topic further, it is vital to critically examine the assumptions behind the data revolution and how they shape our approach to sustainable development.
The data revolution involves the rapid increase in data creation, collection, and analysis driven by technological progress. Today, data is more plentiful and accessible than ever, allowing policymakers, researchers, and organizations to make decisions based on real-time information. The concept is simple: by leveraging this wealth of data, we can craft more effective policies, improve service delivery, and ultimately make progress toward reaching the SDGs.
The SDGs, a collection of 17 global targets designed to address social, economic, and environmental issues, rely heavily on data to track progress and guide strategies. From eliminating poverty to advancing gender equality and encouraging sustainable economic growth, the potential for data to speed up these efforts is enormous.
Assumptions Behind the Data Revolution
Despite the promising outlook of the data revolution, several key assumptions deserve scrutiny:
1. More Data Equals Better Decisions:
A common belief is that having more data results in better decision-making. Yet, data quality and relevance are essential. Without accurate and contextually appropriate data, decisions may be misguided or ineffective.
2. Universal Data Accessibility:
Another assumption is that data is accessible and usable everywhere. In reality, disparities exist in data access, especially between developed and developing regions. This divide can worsen existing inequalities, leaving marginalized communities further behind
3. Equity and Inclusivity:
It is often believed that data-driven methods are inherently fair. However, relying on data can ignore the voices and needs of those not represented in the data collection process, leading to policies that may not serve all groups.
Challenging These Assumptions
These assumptions can cause serious problems. For example, focusing solely on quantitative data can overlook the crucial qualitative insights necessary for understanding complex social issues. Additionally, ethical issues related to data privacy and ownership must be addressed to foster trust and cooperation among stakeholders.
Furthermore, case studies from various regions demonstrate both successes and failures in utilizing data to achieve the SDGs. Some projects have effectively used data to influence policy, while others have faced backlash due to perceived bias or lack of representation in data collection.
Recommendations for a Stronger Data Strategy
To handle these challenges, we need a more nuanced and inclusive approach to data:
Building Data Literacy:
Educating communities about data can connect data producers and users, making sure everyone can participate meaningfully in the data revolution.
Promoting Multi-Stakeholder Collaboration:
Working together—governments, civil society, and the private sector—can ensure diverse perspectives are included in data efforts.
Maintaining an Intersectional Approach and Setting Ethical Standards:
Aiming for better data to reflect individual experiences while covering multiple forms of identities, such as race, age, disability, etc., and creating ethical frameworks for data collection and use which is key to protecting rights and fostering trust.
The Future of the Data Revolution and SDGs
As technology advances, new opportunities and issues will emerge. Developments such as artificial intelligence and machine learning can enhance data analysis and decision-making. Still, we must use these tools with caution, ethically and inclusively.
Looking ahead, the future of the data revolution in support of the SDGs depends on our ability to adapt and innovate. By critically examining our assumptions, promoting inclusivity, and establishing robust ethical practices, we can leverage data to build a more sustainable and fairer world.
While the data revolution presents unparalleled opportunities to advance sustainable development, it must be approached with a critical mindset. By reevaluating the assumptions underlying data-driven efforts, we can gain a deeper understanding of complex challenges and develop more effective solutions.
Please read the full paper here.
