Her response: Increase the ‘reward’ in high-risk scenarios

Posted on 27. Sep, 2013 by in Academic Departments, Annual Report, Industrial and Systems Engineering, Issues, People, Research

Laura McLay in front of a fire station

Laura McLay. Photo: David Nevala

Industrial and Systems Engineering Associate Professor Laura McLay’s research canvas is massive data—banks of millions of emergency 911 calls, commercial
airline flights and ship cargo deliveries—which she uses to tease out the risk factors in these high-stakes endeavors.

As a data challenge, it might seem like searching for the proverbial needle in the haystack, but McLay is quick to clarify her goal. “You actually never find the needle,” she says. “You just make a better haystack.”

McLay is an expert in operations research, which she defines as “the discipline of applying advanced analytical methods to help make better decisions.” Operations research received a major awareness boost after the September 11 attacks, as an important tool in improving airline screening and security and combating terrorist threats.

McLay works to develop mathematical models to identify how to design risk-based passenger screening methods given that the “haystack” of data can be used as a type of passenger risk assessment tool. “You’re really trying to weed out all of the low-risk events and be able to focus on maybe the 5 percent you really need to worry about,” she says. “A lot of times operations research is exactly the right tool to use, because it answers the question, ‘How do we best utilize limited resources and imperfect data?’”

McLay found a robust new research target after the 2010 “Snowmageddon,” a storm that dumped more than 3 feet of snow on parts of the Washington, D.C., region. In the aftermath, there were controversies over poorly managed emergency resources, response times and decisions.

This was a perfect research storm for McLay, who married her longtime work in analysis of emergency response times with data on severe weather. Her analysis of the Snowmaggedon response, compared against more typical weather days, revealed importance differences that could improve decision-making and prioritizing calls during future weather emergencies.
Emergency responders develop notoriously good instincts in reducing their response times, but McLay hopes her work bolsters those instincts with hard data on managing calls during high-volume or high-risk periods.

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