Using AI to forecast resource supplies in natural disasters

Natural disaster
© iStock/Angela Schmidt

Scientists have formed a partnership to create a predictive analytics model that identifies and forecasts supply and demand of resources in the case of natural disasters.

A leading technology provider and data-driven consulting organisation, and the Schulich School of Business at York University have announced a partnership to create a predictive analytics model that identifies and forecasts supply and demand of necessary resources in a disaster-related emergency.

The model evaluates existing wildfire data points and feeds into an ad hoc trading platform which key stakeholders can use to option the right amount of services and supplies in the most cost-effective manner. The project aims to bring together local governments, insurers and medical supplies providers to collaborate and plan proactively for optimal disaster management. Available in June 2020, the platform is the first in a series of analytics tools that the Schulich School of Business and Exigent will develop to deliver on their core focus: turning data into actionable business intelligence and community-centric analytics products.

The collaboration is part of the Masters in Business Analytics Program (MBAN) at Schulich. Students are working alongside Exigent’s data and business analysts to build a model that identifies the environmental, social and economic impact of wildfires in Canada, and subsequently the United States. Artificial intelligence is at the core of the team’s efforts to create their predictive tool, which will absorb and structure data, find and evaluate patterns, calculate impact and feed into a bespoke analytics tool.

The Exigent-Schulich project aims to predict with a high degree of accuracy the supplies and services needed for effective disaster response, for example, the number of medical supplies or number of medical professionals needed in the event of a wildfire in a specific area with particular weather patterns. The highly reliable predictive models feed data into a shared trading platform, where stakeholders can opt to acquire supplies at the best time with regard to price and preparedness. The predictive analytics model, coupled with the trading platform, will allow insurance companies to calculate the best premium, suppliers to accurately forecast medical supplies and local authorities to purchase the right amount of supplies at the best price. Should the disaster not strike a particular province or state, options can be then traded to those affected.  The option structure will keep prices low and incentivize suppliers to build inventory.

Based on data from the Canadian Interagency Forest Fire Centre, more than 6,000 fires occur (on average) each year and destroy over 2.7 million hectares (6.7 million acres) of land. in 2018, in the Province of Ontario alone, the Canadian government spent $212 million in combating forest fires.  The infamous 2016 fire that burned much of Fort McMurray in northern Alberta cost insurance companies $3.58 billion. On the other side of the border, fires in the US burnt a massive 3.5 million hectare (8.8 million acres) in 2018, with the California Department of Insurance stating that, as of April 2019, insurance claims from the Camp, Hill and Woolsey Fires in November 2018 have exceeded $12 billion. The Exigent trading platform is estimated to cut costs by 20% and drive down premiums. More importantly, having an inventory of medical supplies available, and with improved predictive analytics, this tool also aims to reduce fire related injuries and resulting deaths, which have been rising in recent years.

“The numbers are staggering and sadly we are reminded of the tragedy that wildfires cause more and more often, like in California just now, where entire communities face uncertainty and loss, both physical and emotional,” said David Holme, CEO of Exigent. “It’s shocking that collectively we are not using the huge amount of data available to make a difference, both on a social and business level. With Schulich, we are trying to shift attitudes towards data and provide a tangible platform for change for all stakeholders involved. From our own experience as data evangelists in the legal industry and with corporations, we know that demonstrating how data can save money–and lives in this case– is key to getting people on board. We are building a tool that gives incontrovertible proof of that.”

Murat Kristal, Program Director of Schulich’s MBAN Program and an Associate Professor of Operations Management & Information Systems, added: “We’re very excited to give our students the opportunity to learn from industry leaders how to tangibly make a difference through data. Hands-on guidance from a company that handles global organizations’ complex data across departments and turns it into bottom-line results is invaluable.”

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