Counting What Counts: Using Big Data To Drive Social Impact
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As data accumulates and the world becomes increasingly interconnected, the resulting “big data” that is generated offers potential for applying this information towards social change. The private sector has been successful in utilizing big data analytics for driving innovation and economic growth. Gradually, the social sector is adopting these practices and taking advantage of the vast amount of data available to tackle complex societal problems and assist underserved populations. By incorporating data-driven analysis into efforts aimed at driving social impact, organizations across sectors can facilitate the development of innovative solutions to the problems society needs answers to. Despite this potential, numerous challenges stand in the way that have prevented the social sector from making all these possibilities a reality, as this type of work requires a collaborative model given the dynamic nature of social problems and the complexity of their solutions. What is needed in order to accelerate the use of big data solutions towards social innovation? This thesis explores the current state of big data in the social sector, examining case studies of successful organizations that have used big data in addressing the most pressing issues in society, and the impediments that have prevented similar data-driven solutions from becoming more widespread. This thesis aims to provide direction in guiding efforts going forward to expand the use of big data in driving social impact, offering suggested strategies to develop sustainable solutions in light of the obstacles impeding such efforts.