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How Data Analysis Can Save Lives

The following is an excerpt from a GovLoop and SAS report, Government Workforce in Focus: Closing the Data Skills Gap. The report includes a survey of 283 public-sector professionals, which provides insights on the challenges in closing the data skills gap.

The International Organization of Migration (IOM) is an intergovernmental agency that provides humanitarian assistance to migrants in need and relies on a highly skilled data workforce to meet its mission. Through its work, IOM provides relief after natural disasters, managing and coordinating efforts for displaced citizens. This includes managing temporary shelters, schools and evacuation centers.

In November 2013, IOM was an essential part of the relief efforts as Super Typhoon Haiyan barreled through the Philippines. “[During Typhoon Haiyan] one of the IOM’s jobs was to focus vital resources for first responders,” Terrell said. “One division of IOM was using spreadsheets, intuition and human analysis to take a look at where they should be sending their resources to fix the problem.”

IOM had to manage thousands of data points — from tracking clusters of individuals and water and sanitation needs to collecting information from government and non-governmental organizations partners, such as the Philippine Department of Health, World Health Organization and UNICEF.

To share the SAS analyses effectively, IOM used its Displacement Tracking Matrix (DTM), a management tool that tracks relief efforts and assesses individuals’ needs. “By adopting easy-to-use technology, combined with intuition and knowledge that workers had, they were able to get actionable data and trends within 30 seconds,” Terrell said. Through DTM, IOM workers knew where services were needed and provided.

One area Haiyan hit particularly hard was the city of Guiuan, which has a population of roughly 50,000. Using an SAS text mining analysis tool, more than 10,000 ere analyzed, providing important details about the relief efforts’ current status. The social data also told IOM workers that the Red Cross and an Australian emergency medical team were in Guiuan already providing support. Finally, the tool provided information about what resources, such as antibiotics and generators, were most desperately needed.

“This information would have been unavailable to IOM if they did not have a way to look at social media in a way that was useful and actionable to them,” Terrell said. “So in this case, they were able to pivot and send resources where they were most needed.”

The IOM case study shows how the combination of cutting-edge technology and talented teams who understand data can make a real impact on service delivery — and save lives in the process.

 

 

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