Too often, risk managers take solace in the failure of enterprise risk management by citing the occurrence of black swans or perfect storms -- expressions used to describe unthinkable or extremely unlikely events.
"Most of the risks we see in life are somewhere in between," said Elisabeth Paté-Cornell, a professor of management science and engineering at Stanford University.
But the expressions are heard often enough, and that's because "they are lame excuses for bad risk management," said Paté-Cornell. "This idea that something that happened could never have been envisioned before is often absurd."
"In reality," she wrote in a paper recently published by the Society for Risk Analysis, "there are often precursors to such events."
But those precursors were either unknown, ignored or downplayed, Paté-Cornell said.
A recent example, she said, was the Fukushima tsunami and nuclear accident in Japan in 2011. Even though the combination of tsunami and seismic activity had not occurred in recent times, it had been recorded at least twice in history, she said.
Engineering risk analysis -- which is most often used in the development of new systems, such as when nuclear power plants were first constructed -- can help support effective risk management, she said.
Ordinary risk analysis, which focuses on the use of statistics alone, is generally insufficient, she said, noting that systemic risk management requires an in-depth analysis of a system, its subsystems, functions and redundancies.
"These measures," she wrote, "involve monitoring of signals, precursors and near-misses, as well as reinforcement of the system, improvement of its management and a thoughtful response strategy. It also involves careful examination of organizational factors such as incentives, which shape human performance and affect the risk of errors."
Such an analysis, Paté-Cornell said, will support effective risk management instead of leaving an organization facing the disastrous results of poor planning after an event.
--By Anne Freedman
March 1, 2013
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