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» Decision-Making and Uncertainty for Project Managers
Interdisciplinary Solutions executed the quantitative side of this year-long public health project using @RISK and its Panálysis model which projects healthcare demands during a pandemic to include critical product requirements and staffing needs. This epidemiologic model integrates Palisade’s risk and decision analysis software @RISK and RISKOptimizer in order to account for uncertainty. @RISK was used to assess nursing capacity, and RISKOptimizer analyzed possible resource shortages.
This case was originally presented at the 2009 Palisade Risk Conference.
“@RISK is a risk analysis tool that is particularly easy to use. …[It has] extremely fast calculation times, parallel use of multiple processors, dynamic output charts, regression scatter plots, shared function libraries, extended product range and so on.”
“@RISK and Six Sigma are excellent bedfellows, providing the means to dynamically analyze both starting data and the ongoing improvements being made to the process so as to provide even more insight to the true causes of variability.”
Palisade Quoted in Chartered Institute for IT:
Any new approaches – involving models, tools, staff, and ways of thinking – must not be limited to the financial sector. Regardless of business sector, the disciplines of QRM (quantitative risk management) and DMUU (decision making under uncertainty) must be approached with new attitudes and new commitment.
Managing and Measuring Diversification Effect
Palisade Blog Headlines
Taking the guesswork out of water pipe replacement,
Construction time is of crucial importance when it comes to utilizing the production factors in an effective and efficient way. Construction periods that are too short usually result in higher cost, poorer quality and a larger number of disputes. This presentation sets out to demonstrate the calculation of construction time and cost whilst considering key construction management parameters. Beyond a simple, deterministic method, other options for calculation are shown that rely on probability using Monte Carlo simulation in @RISK for Excel. The approaches described to determine construction time and cost are illustrated by a high-rise building project example.
Did you know the @RISK Library allows you to store specific, customized probability distribution functions for use by other @RISK users? You can also store simulation results for later auditing, and for use as inputs in subsequent simulations. You can use the Library just for yourself, or on a server for a group of @RISK users. The @RISK Library helps ensure consistency of inputs and common modeling practices.
Engineers from Yale University have developed a supercomputer that uses neural network technology to mimic the mammalian visual system.
In the U.K., car shoppers can use a new decision tree application to sort out the increasing number of energy efficiency choices and settle on the model that will work best for them.
Scientists from Johannes Guternberg University Mainz used Monte Carlo simulation to test the potential of a number of ways to improve the performance of thin-film solar cells.
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