Four ways data can help society’s most vulnerable

By Alteryx

Interview with Jordan Barker, Director of Sales Engineering, Asia Pacific and Japan, Alteryx.

Anthropologist Margaret Mead once said that the first sign of civilisation was compassion, demonstrated in a healed femur. The femur is the longest bone in the body. Without modern medicine, it would have taken a long time and dedicated caregiving to heal.

Today, governments play a big role in helping the vulnerable get back up on their feet. Many have turned to analytics to find those who have fallen through the cracks and design targeted interventions.

Jordan Barker, Director of Sales Engineering, Asia Pacific and Japan at analytics company Alteryx, shares four ways governments use data to help citizens in need.

1. Improve location planning

Geospatial mapping and analytics can help authorities find the best locations for social support facilities. For instance, a Canada-based health data science company used demographic data to improve food bank locations.

The company used Alteryx’s platform to look at citizens’ age, gender, and income. It then pulled in data on road networks and the overlapping support systems that already exist. This allowed it to place food banks right where the greatest needs were.

This service could be helpful in Singapore. A 2019 hunger report from The Food Bank Singapore reported that 3000 people rely on food bank services, Barker says. “I can only imagine during the pandemic that this number has risen due to unemployment and economic downturn,” he adds.

One food bank, run by Jamiyah Singapore, saw a sharp rise in the number of families seeking assistance in the pandemic. This trend will likely continue even as the economy begins to recover, as families will need time to find jobs, The Straits Times reported.

The gaps in Singapore’s food support network have led to food waste and inefficiencies, but data can help. The country doesn’t yet have a central database to track who is receiving food from support groups, CNA revealed last year. Some households get multiple meals, while others barely receive enough.

Authorities could use analytics to plan for aged care facilities as well. They could choose to set them up in areas with a higher density of elderly, while taking into account transportation routes, Barker notes.

2. Map malaria hotspots

As we’ve learned in the past year, data is crucial when tackling public health crises. Barker points to the success of analytics in reigning in the spread of malaria, a “longer term public health crisis the world has learned to deal with”.

Zambia has used Alteryx’s services to better understand the spread of malaria in the country. The disease is the leading cause of death in young children in Africa.

Health authorities worked with PATH, a global health nonprofit, to track transmissions between people and locations in near to real time. “The geospatial capabilities within Alteryx allowed them to connect the dots between those people,” he explains.

Authorities could monitor where infection rates were increasing, automatically predict malaria cases and roll out counter measures at a community level.

3. Financial assistance for job seekers

Saudi Arabia uses data to match job seekers to financial assistance more efficiently. Alteryx’s Analytic Process Automation platform combs through millions of data points each month and identifies the individuals who need help. This has sped up the process by 90 per cent, Barker shares.

Alteryx has also allowed the government to provide schemes that would be most helpful. Public officials can evaluate different schemes based on the duration of financial aid or the target demographics to find the most suitable programmes for each citizen.

4. Manage employee stress

Public servants face immense pressure in a pandemic to bring the nation out of the clutches of the crisis. Governments need to monitor their employees’ well-being and stress levels to provide support where needed.

Alteryx offers analytic tools that can help with this. Employers can map employee schedules, shifts and workloads with a risk score to predict employees most at risk for quitting. They can then design targeted training or support programmes.

Governments work to serve even the most vulnerable. Analytics can help officials find and reach those who are most in need.