Here are some ways that data science can help in the resolution of global issues | Education

Here are some ways that data science can help in the resolution of global issues | Education
Here are some ways that data science can help in the resolution of global issues 

Here are several ways in which data science can help in the resolution of global issues 

Global disruptions are becoming more complex, taxing the abilities of social impact organizations and governments on the front lines.

Innovative companies use data science to improve every aspect of their operations, but those sophisticated tools are not available to many organizations and governments.

Together, companies, funders and global institutions can help organizations and governments build a robust data science infrastructure to navigate future crises more equitably.

Around the world, local authorities and NGO workers are bravely responding to overlapping, complex crises – whether they are 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 capability can fall short in significant 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 acted swiftly to welcome the historic exodus of Ukrainians who escaped Russian aggression. One Polish city turned to MasterCard to help plan the influx of new arrivals. In just a few days, our team analyzed regional spending patterns to provide near-real-time insights that helped city officials better prepare to meet the needs of weary, grieving families.

But one-off partnership should not be our goal. If the private sector and other funds, including foundations and development organizations, work together, we can help NGOs and low-resource governments build more sophisticated data science infrastructure of their own Strengthening their ability to fight and strengthen global resilience.

This is why the Mastercard Center for Inclusive Growth, which I run, makes impact data science a top priority. Two years ago in Davos, along with The Rockefeller Foundation, Mastercard launched data.org, a growing platform that works with organizations around the world to incorporate data science into social sector decision-making.

Impact data science can enhance frontline crisis response

Building technical capacity in small NGOs or remote government offices is not an easy task. But three recent examples underscore why this matters.

First, look at Community Solutions, an organization that combats homelessness in the United States. Even before the pandemic, homelessness was rising across the country and resources were scarce. To improve efficiency, Community Solutions worked with experts to enhance their data analysis capabilities. That work paid off when the pandemic hit, and it was able to help identify individuals in shelters at high risk for COVID-19 and move them to safer settings.


As the pandemic spread to the other side of the world, the Togolese government also turned to data science. Togo's Ministry of Digital Economy and GiveDirectly, a nonprofit that sends cash to people facing poverty, launched a pilot program to quickly distribute cash aid to the country's lowest-income residents. He worked with the Center for Effective Global Action to use machine learning and survey data to identify residents and provide support. This method has reached more and more needy people of the country and so far this program has given about 10 million dollars to about 137,000 people.

The third example illustrates how front-end investing in impact data science can pay dividends in the face of a crisis. In India, nearly a third of farmers' produce is wasted, as it is difficult to determine how long to store particular products and how to extend shelf life. Experts in Switzerland developed an app to help solve both problems, equipping farmers with modeling to help them keep more food fresh for longer. Six months ago, helping rural Indian farmers access data science tools was hardly a global priority. But now, as Russia's invasion of Ukraine causes grain shortages that lead to a serious food crisis, we can clearly see how such investments can make a big difference.

Governments and NGOs struggle to integrate data science

Unfortunately, those examples are the exception. Too often, organizations and support personnel on the ground face a lack of data, and the equipment and personnel to analyze and deploy it.

Many governments and NGOs are not able to recruit enough data scientists. An upcoming report from the McGovern Foundation and data.org estimates that the social sector alone needs 3.5 million more data scientists over the next 10 years. Mastercard announced a $4.6 million grant to help train one million data scientists with a focus on diversifying the field, but we need to do more.

The lack of analytical tools and internal structure is also a problem – even for organizations that have a lot of data. In contrast, many corporations have spent years developing data and analytics strategies, investing in interconnected, user-friendly platforms, building teams with deep expertise, and cultivating a data-literate culture.

Companies, funders impact can help build capacity to deploy data science

Companies and funders can help bridge this "data science gap" facing governments and NGOs by dedicating attention, technical skills, and funding. We know that because organizations like Datakind successfully connect volunteer data scientists to social organizations, helping them unlock the power of data in ethical and responsible ways.

The challenge is moving towards building impact data science as a field through individual involvement and selfless efforts - at the scale required. Last fall, at the request of G7 governments, data.org began calling on the private, public and non-profit sectors to create Epiverse – an open digital infrastructure that aggregates data from around the world to help prevent the next pandemic. will analyze the streams.

The overarching goal is to strengthen collaboration across sectors so that we can use data science to systematically address other societal challenges, prioritizing privacy and security concerns.

No initiative will help frontline respondents build the teams and tools to use data science fluently and effectively as most well-funded private sector companies. But we can and should increase our investment. Companies can start by adopting data responsibility principles, which include security and privacy as well as innovation and social impact, and then join Mastercard to build data.org into an even stronger platform for data science partnerships. steps can be taken.

The work may not grab headlines, but it will help the world navigate the crises of tomorrow more equitably and effectively.