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Predictive Analytics Used to Determine Hospital Bed Capacity
Hospital bed availability changes daily, especially during COVID-19, as patients are admitted and discharged. @RISK gives staff a real-time look at data as it evolves, so they can develop models from different variables. … The probabilistic or stochastic models, such as @RISK, examine a wider range of possibilities and how likely each one is ...
Det Norske Veritas (DNV) uses @RISK to Model ROI on Energy Systems Investments
Global risk management consulting company DNV specializes in helping companies in the energy, maritime, healthcare and other industries identify, assess, and manage risks of all kinds.
DNV uses probabilistic Monte Carlo modeling with @RISK to illustrate factors affecting the return on investment of energy systems. @RISK is used for a range ...
How to Create a Custom Application for Stock Portfolio Optimization, Right in Your Spreadsheet
This is an example of the use of @RISK automation applied to stock portfolio optimization. It is a custom application written by Palisade Custom Development using @RISK’s XDK in Excel.
The steps outlined in the Stock Portfolio Optimization example include:
Obtain Price & Weight Data
The user will first define a portfolio of ...
The Paradox of Knowledge: Using Correlations
Modeling from empirical data takes observed information and attempts to replicate that information in a set of calculations. There are a number of relationships to account for when incorporating those data in a model. These relationships include dependencies and/or correlations. Correlations are often omitted for a variety of reasons, which ...
Struggling with Your NCAA Bracket? Try Monte Carlo Simulation, with Help from the Pros
Each March, office productivity is greatly impacted by the NCAA Men’s Basketball Tournament. Just about everyone—regardless of their passion for college basketball—fills out a bracket in hopes of winning their respective pool (or pools). Some rely strictly on their knowledge of the teams involved, while others choose winners based on uniform ...
Uses of the Uniform Continuous Distribution
The continuous uniform distribution represents a situation where all outcomes in a range between a minimum and maximum value are equally likely.
From a theoretical perspective, this distribution is a key one in risk analysis; many Monte Carlo software algorithms use a sample from this distribution (between zero and one) to generate random ...
Cpk in Six Sigma: What is its “Capability?”
In Six Sigma analyses, there seems to be some low level confusion about Cpk and Ppk and what they actually represent. Very basically, Cpk is short term “noiseless” process capability where Ppk is long term “noisy” process capability. Some of the confusion regarding these two metrics may be because the automotive industry had at one time used ...
Contingency Calculation in Cost Risk Analysis
When performing a cost risk analysis study, one of the key results is the amount of extra monetary resources that is to be added to the project cost baseline to guarantee that the budget is not exceeded at a certain confidence level. Good project risk management strategies must take this into account.
After defining the uncertain variables ...
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 ...
Key Project Management & Decision Analysis Text Expands on DecisionTools in New Edition
What are the characteristics of successful managers? Surveys consistently show decision-making ability at or near the top of the lists. Perhaps no management activity is more important. Risk and Decision Analysis in Projects by John R. Schuyler presents the approach and principal techniques of decision analysis to help the reader realize ...
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 ...
International Monetary Fund uses Monte Carlo Simulation for Stress Testing
An IMF working paper this month contemplates the effectiveness of lending arrangements the institution makes to various countries around the world. The paper, “Assessing IMF Lending: A Model of Sample Selection,” seeks to identify and understand common factors that make programs effective – or not. Using Monte Carlo simulation to assess the ...