Here's How Data Science Can Help Solve Global Crises | News Direct

Here's How Data Science Can Help Solve Global Crises By Shamina Singh

News release by The Mastercard Center for Inclusive Growth

facebook icon linkedin icon twitter icon pinterest icon email icon Northampton, MA | May 27, 2022 02:01 PM Eastern Daylight Time

Image courtesy of Mastercard
Image courtesy of Mastercard

Across the world, local officials and NGO workers are heroically responding to overlapping, complex crises – whether they’re battling new waves of the COVID-19 pandemic or delivering aid after natural disasters. The energy and determination of these frontline organizations is unmatched, but their technical capacity can fall short in crucial ways.

In particular, many lack the tools, teams and resources to effectively harness the power of data science. For cutting-edge companies that incorporate data science into all levels of their operations, this is an opportunity to help. For example, Eastern European governments have worked rapidly to welcome a historic exodus of Ukrainians fleeing the Russian invasion. One Polish city turned to Mastercard for help in planning for the influx of the new arrivals. Within a matter of days, our team analyzed regional spending patterns to provide near real-time insights that helped city officials better prepare to meet the needs of exhausted, traumatized families.

But one-off partnerships shouldn’t be our goal. If the private sector and other funders, including foundations and development organizations, work together, we can help NGOs and under-resourced governments build more sophisticated data science infrastructure of their own – strengthening their ability to battle crises and bolstering global resiliency.

That’s why the Mastercard Center for Inclusive Growth, which I run, makes impact data science a top priority. Two years ago at Davos, alongside The Rockefeller Foundation, Mastercard launched data.org, a growing platform that works with organizations across the world to infuse data science into social sector decision making.

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