Steve Hunt, LSSBB

Whether in DMAIC, Design for Six Sigma (DFSS), Lean projects, or Design of Experiments (DOE), uncertainty and variability lie at the core of any Six Sigma analysis. I’m interested in how Monte Carlo simulation can be used to identify, measure, and root out the causes of variability in production and service processes and designs.

Actuaries Tune Risk Analysis to Improve Decision Making under Uncertainty

Actuaries are more risk-averse than you and I because they advise insurers and pension funds that have a lot at risk.  So they need to be better at decision making under uncertainty.   When they calculate requirements for pension fund investment, life insurance, or long-term care they try to account not only for the uncertainties–say, growth […]

Holly Bailey

Public Relations Representative for Palisade I specialize in communications for technical and scientific companies. During my work for Palisade Corporation over the past decade I have kept a close eye on trends in quantitative decision-making techniques.  I’m keeping this blog to report where and how I find these techniques–such as risk analysis, risk optimization, decision […]

Risk Analysis in Clinical Practice

As medical practice has become more and more “evidence-based,” the role of risk analysis and Monte Carlo simulation has expanded rapidly.  Nowhere is this more evident than in recent software introductions that incorporate Monte Carlo software to calculate dosages with extreme precision.  If “dosage” brings to mind a teaspoon and a bottle of cough syrup, […]