The Return of Henry Yennie–and Gustav

Now that Hurricane Gustav has blown out of the picture, it’s time to catch up with Henry Yennie, of the Louisiana State Department of Mental Health.  I reported earlier on Henry’s decision evaluation study of evacuation plans for the City of New Orleans.  The questions he was trying to answer with Palisade Corporation’s Monte Carlo […]

SixSigmaIn demonstrates how Monte Carlo Simulation is used in Tolerance analysis

Recently, Franco Anzani of SixSigmaIn Team and Marco Manara of Casappa S.p.A. worked together on a Six Sigma tolerance analysis project where they used Palisade Corporation’s @RISK 5.0. The model represents a tolerance analysis study performed to solve a potential assembly issue in a gear pump typically used in forklifts and low noise emission machines. The […]

Lessons Learned from Crises in the Financial Markets: Impoved Regard for Risk Management Systems

The Director of the European Offices of the International Monetary Fund, Saleh M. Nsouli, recently gave an address that examined some of the lessons that can be learned from the crisis in today’s world financial market. In both the private and public sectors, Nsouli advises taking a harder look at the risk management sector. For […]

What are Real Options?

Real options are the flexibilities that are inherent in general business or other decision situations. In general, a real option is present in any decision situation involving a decision-chance-decision sequence; the possibility to (at the second decision) select from a range of different decision possibilities after the occurrence of the chance event may alter the […]

Just Say No When Business Gets Too Risky

At the annual rendezvous of reinsurers in Monte Carlo earlier this month, risk assessment and, in particular, risk analysis were hot topics.  Reinsurers buy up risk assumed by other insurers, and they have met in Monte Carlo every fall since 1957.  Understandably this industry has been hard hit by the upheaval in the financial markets, […]

Oil & Gas: Exponential Decline Model

The risk analysis model below examines the familiar production forecasting model for oil and gas wells, the exponential decline curve. The standard equation, q = qie-at (3.3), can be used with random variables for both qi (the initial production rate, sometimes called IP) and a (the constant decline rate). Here the model has an additional […]

Using a Risk Factor Approach to Model Project Risks

When building a Monte Carlo simulation model in @RISK for project risk analysis, we can incorporate a risk register through risk factors. Risk factors are more concrete abstractions of risk and define situations that can be individually assessed with a limited amount of information. Risk factors affect a project through the occurrence of events that […]