Monte Carlo Simulation and Human Risk [Risk Management]

Many industries - reinsurance finance and commercial development, for example - rely on risk analysis technology that utilize Monte Carlo simulation. To bail down the likelihood of success ot failure of any given project, the simula' rjon process considere a series of random events, or risks and calculates thousands of scenarios io project die probability of difierent outcomes occurring.

For the aforementioned industries, the risks often;, deal with insurance decisions, expected shorrfalls in capital or supply chain disruptions. While important issues, they are not life threatening.

However, Monte Culo simulation, which was created by scientists attempting to determine radiation shielding, has assisted in rhe assessment of risk that impacts more than just the bottom line, In many instances, it has helped save lives and guide decision makers in rimes of disaster.

While the basic premise and procedures of Monte Carlo simulation remain constane, the technology used has continued eo evolve. In turn, mort industries have discovered unique ways - with remarkable results - to extend its urility beyond the business world.

Hurricane Katrina Call Center

When Hurricane Katrina struck New Orleans in 2005, Louisiana officials created a family crisis phone center to help callers locate family members and collect information regarding missing persons. Given the expecred influx of calls, Monte Carlo simulation helped officials quickly determine the call load the center should expect and create a staffing schedule to manage the activity. Crinen] data points, such as timing of calls, duration of calls and number of deaths were used co predict potential call load. As new data became available, the schedule was adjusted io anticipate necessary schedule changes.

The call center helped reunite 8.000 of the 11,000 people reponed raasing in Louisiana and identify 900 of the estimated 1,100 people who died as the result of the devastating hurricane.

Guatemala Volcano Evacuation

Volcan de Fuego is an active volcano located in a relatively populated area of Guatemala. While the volcano's activity typically poses little risk to dtose living nearby, it has the potential to be destructive. Recently, Guatemala's National Infunile for Seismology, Vbkanology, Meteorology and Hydrology worked with the University of Bristol to create a risk assessment of potential volca nic-related evacuation tisks, The study considered the likelihood of a successful evacuation by inputting several variables, such as the time between a possible eruption and a posible hazard hitting a location, along with communication times from authorities and evacuation times.

These variables were each modeled by experts using probability distributions. In September 2012, after its Largest eruption since 1999, more than 35,000 people within 11 miles of the volcano were evacuated.

Pandemic Preparation

In 2008, the New Yotk City Health Emergency Preparedness Program examined the ability of the city's 64 hospitals to properly staff nurses in the event of a pandemic, By using Monte Carlo simulation, it was possible co ascertain a scries of probabilities regarding nursing shortages during a future pandemic. Officials identified a 26,5% chance that shortages would exist, a 10% chance that the would be shortage of at least 46 nurses and a 1% chance of a shortage of more than 102 nurses.

The Simulation took into account variables such as the number of hospital beds, the maximum number of shifts a nurse can perform in a week and the total number of shifts available in a week. Nurse absenteeism, due to taking care of family members also suffering from the pandemic and nurses' desire to protect themselves from being exposed, was also factored into the simulation.

Randy Heffernan is vice president at Palisade Corporation, a provider of risk and decision analysis software.