FROM INSIGHTS TO IMPACT: STATISTICAL AND TECHNOLOGICAL APPROACHES FOR ACHIEVING THE SUSTAINABLE DEVELOPMENT GOALS (International Journal of Humanities, Commerce and Education, 2026)
The 2030 Agenda for Sustainable Development, adopted by the United Nations in 2015, presents 17 interconnected Sustainable Development Goals (SDGs) as a universal framework to eradicate poverty, protect the planet, and ensure prosperity. As the deadline approaches, many nations face challenges in measuring progress, designing effective interventions, and evaluating outcomes. This paper argues that the integration of recent advances in science and technology with innovative statistical techniques is essential for accelerating SDG achievement.The review synthesizes conceptual and empirical insights from global data sources, including UN reports, World Bank datasets, FAO, WHO, ILO, IEA, and OECD. For each of the 17 SDGs, the study highlights recent technological developments (such as AI, IoT, remote sensing, and blockchain) and statistical approaches (including regression modelling, Bayesian inference, time-series forecasting, life-cycle assessment, and simulation). Global-level data anchors illustrate progress and persistent gaps, demonstrating how quantitative analysis contributes to evidence-based policy design.Findings indicate that statistical innovations serve three critical functions: improving measurement precision, enhancing predictive capacity, and ensuring accountability in SDG implementation. Yet disparities in data quality, unequal access to technology, and limited statistical capacity in developing regions threaten inclusivity. The paper concludes with a call for investments in statistical infrastructure, open data ecosystems, and interdisciplinary collaboration to ensure that science, technology, and statistical techniques collectively drive sustainable development.