Vital efficiency: Kai Huang is using data analytics to study humanitarian aid

Izabela Szydlo, DeGroote Research Writer | Hamilton | November 15, 2017

Santa Fe,Bantayan,Philippines – December 18, 2013: Humanitarian aid workers loading ShelterBox emergency aid onto trucks after Typhoon Haiyan in the Philippines

Asia-Pacific is the world’s most disaster-prone region, and a recent United Nations report warns that disasters could become more destructive in the area. Meanwhile, in developing nations such as Kenya, under-nutrition is a leading cause of death among children under five in the arid and semi-arid areas that make up 80 per cent of the country.

Such alarming realities are part of what makes DeGroote Associate Professor Kai Huang‘s research not only timely, but vital. Huang examines the effectiveness and efficiency of humanitarian aid with the help of data analytics. “Disaster response in the past has been very spontaneous. People just try to help people. That’s the basic idea,” Huang begins.

“In a typical scenario, organizations try to help by sending various items to the affected areas. However, because this isn’t done in a scientific way, they may be sending the wrong items that people don’t actually need. We need a more efficient way to help people, and the research we’re conducting could help develop a disaster information system for the humanitarian sector.”

Canadian Forces DART – Nepal Earthquake 2015

Along with fellow DeGroote Professor Yufei Yuan, Computing and Software Associate Professor Rong Zheng, and several graduate students, Huang is working on a project entitled Assessing the Effectiveness and Efficiency of Humanitarian Aid Operations via Data Analytics. It’s funded by the Social Sciences and Humanities Research Council (SSHRC) Partnership Development Grant program, and research is being conducted in partnership with World Vision Canada (WVC).

The team’s work aims to assess the performance of humanitarian operations in terms of allocation and distribution, with a long-term goal of introducing more analytical models to the humanitarian sector. These models can eventually be incorporated through software systems. To date, Huang has undertaken research based on data related to several humanitarian projects, including Kenyan food aid, Nepali earthquake relief, and Iraqi refugee camps.

“Previously, when we talked about humanitarian operations, we didn’t have the data because it wasn’t kept — aside from, maybe, monetary donation data,” he says. “But World Vision has invented software called Last Mile Mobile Solutions, which combines software applications with hardware to digitize beneficiary registration, verification, distribution planning and management, monitoring, and reporting. Now that we have the data, we want to help them interpret it, through data mining techniques, to inform humanitarian aid practices.”

Kai Huang, Associate Professor, Operations Management

Kai Huang, Associate Professor, Operations Management

Last Mile Mobile Solutions, a Canadian-made product, is currently being used by various organizations to improve remote data collection, help manage aid recipients, enable faster and fairer aid distributions, and deliver rapid reporting to aid workers.

However, the humanitarian sector still has a long way to go, Huang says. Some of the successful theories in operations management, such as the coordination mechanisms in organization interaction, have not yet been widely accepted. Instead, many organizations are still relying on carrying out operations instinctively. He hopes his research can help to shift this view.

“In business supply chain, people have invented many efficient models and theories. But in the humanitarian side, we see that people don’t depend on theory, but they should,” he says. “So first we talk with organizations, and we try to convince them we can help implement change that will have a positive impact on humanitarian aid operations.”

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