Data science has revolutionized the philanthropic sector and how social impact work is tackled. It can help structure unstructured data and form data driven decisions that have far-reaching implications. To help learn more about this concept, three data scientists-Antonio Campello of Wellcome Trust, Jonathan Hertel of the Impact Genome Project®, and Andrew Spott of Submittable-recently shared their insights in a partnered with Chantal Forster and the Technology Association of Grantmakers.
Antonio Campello of Wellcome Trust is a data scientist experienced in handling epidemics, complex diseases and population health. Wellcome Trust is a global charitable foundation that exists to improve health, globally, by investing in science, population health, and public engagement. Jonathan Hertel of the Impact Genome Project® is a data scientist who is expanding the science of impact measurement. This project’s mission is to not only foster better understanding of how interventions work, but to improve results through optimized engagement in social sector organizations. Lastly, Andrew Spott of Submittable is a data scientist who works with a digital platform to streamline communications between grants programs, social charities and their partners.
Through tracing the insights of their webinar and other research, nine ways for organizations to use data science and accelerates their social impact work have been identified. Firstly, data science can help organizations to focus on effective interventions by providing valid and reliable evidence on program impact. Secondly, it also improves predictive capabilities to further use machine learning techniques to forecast possible scenarios while evaluating the community’s scenario at a large scale. Thirdly, data science can help analyze data from many sources at once, while providing meaningful insights and indicators. Fourthly, data science can also help to detect social patterns, such as patterns of donor behavior or change in demand for certain services. Fifthly, data science enables organizations to identify and address issues on a larger and more diverse scale, thanks to the analytical capabilities offered by data science. Sixthly, data science can help to speed up data preparation and provide data-driven decisions about research and resource allocation. Seventh, data science can also improve evaluation processes and impact reports, such as comparing different communities or approaches. Eighth, data science tools can help to measure the success of a project or initiative, enabling organizations to track progress, measure impact, and pinpoint areas for improvement. Lastly, data science can help to improve collaboration between different stakeholders, by linking them, enabling them to access data, and to improve collaboration and performance.
These nine ways of using data science to boost social impact work discussed previously provide a great starting point for organizations to implement data science into their operations. Scientific evidence has become a necessary and important part of developing and running social projects and data science has made understanding the impact of projects much easier and accessible.
