data.org, with generous support from the Mastercard Center for Inclusive Growth and The Rockefeller Foundation, issued a $10M Inclusive Growth and Recovery Challenge. The Challenge solicited proposals for scalable and sustainable data science solutions from and for every part of the world, with themes of Jobs for Tomorrow, Access to Capital, and Cities & Towns, as well as an open track.
Our global outreach yielded 1,263 applications. We received a wide range of proposals at different stages of development, from a budding idea to an established methodology seeking international replication. The diverse group of applicants—researchers, entrepreneurs, doctors, and government representatives— included and reflected levels of experience from newcomer to household name. Applications addressed many important topics, such as reimagining credit scoring, providing better farming knowledge, and preparing urban landscapes for extreme weather.
A pool of expert and over 400 volunteer judges, coordinated by technical partner DataKind, evaluated applications based on the Challenge’s five principal criteria: their potential impact, replicability, scalability, practicality, and breakthrough ideas. After 3,500 reviews, we selected eight outstanding awardees:
- Aalborg University, Department of the Built Environment (BUILD) – Denmark
- Basel Agency for Sustainable Energy (BASE) – Switzerland, India
- Community Lattice – USA
- Fundación Capital – Panamá, Mozambique
- GiveDirectly & Center for Effective Global Action – USA, Togo
- Solar Sister – USA, Nigeria, Tanzania
- University of Chicago, Center for Data and Computing (CDAC) – USA
- Women’s World Banking – USA and Switzerland, with partners in Mexico, Nigeria, and India
Identifying and lifting up these exceptional awardees as an ongoing cohort was the primary Challenge goal. But, as this report reveals, a significant secondary benefit is the unique snapshot of organizations using data science for social impact around the globe. A few of the key insights:
Six prevalent topics emerged.
After an expansive review of proposals and analysis of the application trends, data.org and DataKind identified six prevalent topics that are critical to inclusive growth and recovery and that have tremendously exciting applications of data science. Each of these topics addresses a form of inequality, and underscores that inclusive growth issues are shared by different individuals, groups, and communities worldwide – and merit continued exploration.
- Smallholder farmers and agriculture
- Affordable housing and neighborhoods
- Micro, small, and medium enterprises and entrepreneurship
- Gender inequality
- Urbanization and sustainable development
- Youth unemployment
Capacity is unevenly distributed.
Anecdotally, individuals and organizations seeking to achieve social impact with data science frequently identify capacity as an obstacle. In order to learn more about strengths and needs, we reviewed over 100 applicants that scored highest in their data science assessment to understand their capacity for data, talent, technology, and partnerships. We learned that applicants rarely held all the key ingredients to deliver impact. A common thread across university applicants, for example, was higher data science capacity and lower partnership capacity: stronger resources for theoretical approaches than for fully-fleshed out plans. While the sample size evaluated is too small for sweeping generalizations, it did reveal that even high functioning data organizations have uneven areas of capacity, showing the need for tools like data maturity assessments and talent evaluation to know where to double down and where to shore up efforts. This capacity benchmarking, and potential remediation and partnerships, will ensure potentially strong players are not hampered by capacity gaps.
Economic growth – and particularly inclusive economic growth – is multifaceted and tied to all sectors.
When launching a global inclusive growth and recovery challenge, we anticipated applications that sought to tackle issues related to economic development. While the largest sector represented was economic development – at one-third of all applications – we also saw data science applied to related social issues. For example, we saw applications of AI to support case workers in the child welfare system – where early intervention can fundamentally shift the life trajectories and economic outcomes of young people. We reviewed proposals to digitize and map the informal transportation sector, which a large percentage of the world depends on in order to access better job opportunities, yet ride times, reliability, and user experience remain a data black hole. We learned about organizations using data science for waste disposal and sanitation in informal settlements – with solutions that could impact health, the environment, and future investment in communities that have been left behind.
Alignment with United Nations’ Sustainable Development Goals (SDGs) reflected this breadth of solution. Each Challenge application touched on one or several of the SDGs, particularly those regarding the amelioration of poverty and income inequality (i.e., SDG 1, 68%; SDG 8, 74%; SDG 10, 77%).
We ultimately were expansive in our interpretation of inclusive growth – supporting more traditional inclusive growth strategies, like reimagining credit scoring, alongside structural issues like the digital divide, which too many people are experiencing acutely during COVID-19. The applications received and topics covered furthered our understanding that economic growth is inextricable from many other social issues.
There is appetite and incentive for cross-sector collaboration.
Finally, as we built interest in the Challenge, we saw an outpouring of support from organizations offering technical assistance. Partners across the non-profit and private sectors are providing technical assistance, from pro bono data consulting to the donation of cloud computing credits, to awardees and a number of high-potential projects. Private sector partners recognize the importance of leveling up the use of data for social impact, and the fact that economic growth underpinning business stability relies on healthy, stable communities. The Challenge demonstrates the power of partnerships, and that cross-sector, interdisciplinary collaboration is essential for building the field of data science for social impact.
We are grateful to our partners, the Mastercard Center for Inclusive Growth, The Rockefeller Foundation, and DataKind, for their intellectual engagement, hands-on collaboration, and willingness to extract and share these insights from the Challenge. This report is the first of many – part of our commitment to bring back to the community what we are privileged to see from our vantage point as a neutral platform for partnerships. We hope what we have shared here will inform our collective work of building the field of data science for social impact.