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@RISK Helps Monitor Air Pollution in Kuwait
Indeed, wind conditions and production output from industrial sources can contribute to a high concentration of pollution in an area. When the weather changes, so can pollution concentration. @RISK became an integral part of the inventory process, allowing for more detailed information, “As part of the analysis, we needed to provide input parameters into complex air dispersion models,” said Freeman. “These parameters included physical dimensions such as stack heights and diameters that were easy to identify. The more important parameters were independent variables such as release rates, temperature, and flow rates. This was where Palisade’s @RISK was particularly helpful. We were able to model the worst-case to best-case scenarios for each parameter in our models to show long-term exposure, as well as contributions from individual sources.”
UNDP now employs @RISK to correlate local industries’ impact on air quality in Kuwait. Using Monte Carlo simulation, UNDP looks at potential ranges of impacts. The analyses can show quite conclusively, for instance, that a particular area with specific companies may not be the sole contributors to poor air quality, and contribute significantly less than initially considered. Freeman concluded, “The ongoing work with KEPA has meant Palisade’s products are a very integral part of the success of this program. Pretty much if we don’t use @RISK at least once a day, it means we’re on vacation.”
The ongoing work with KEPA has meant
Brian Freeman, Team Leader for Air Regulatory
Mind Mapping Software Blog Gives
Frey investigates BigPicture's many key features, such as its diagram-building capabilities (“Very cool! This is a capability that you won’t find in any dedicated mind mapping or diagramming program.”); data mapping (“If your eyes glaze over when you look at a large number of columns and rows of data in Excel like I do, you’ll immediately appreciate this aspect of BigPicture."); and its org chart functions (“This promises to be a big time-saver for human resources managers!").
After exploring these flexible features, Frey concludes: "If you’re looking for an affordable, easy-to-use diagramming and mind mapping tool and you already use Excel, then you owe it to yourself to check out BigPicture. I think you’ll be very impressed with its excellent toolset and ease of use. This is backed up by a help file and videos that actually do an excellent job of explaining how to perform common tasks. That’s all too rare today!"
Palisade Client Discusses Project
Laurits Søgaard Nielsen, CEO at Visual Reporting, believes Monte Carlo simulation used within @RISK was integral to the solution that Visual Reporting implemented for the Danish Government, and he discussed that success in the January 2015 issue of Economia, which covers technical accountancy content, business, economics, management and finance. In the piece, Why do IT projects fail?, Nielsen gives his insight:
“The main reason large IT projects fail is that they grow in complexity, and humans are very poor at handling complex tasks,” says Laurits Søgaard Nielsen, CEO of Virtual Reporting. “But often the creation of a business case does not follow best practice and can be severely affected by managers wanting to influence the process of project approval. ‘I want this project to happen’ often outweighs the poor business case.”
With Palisade’s risk and decision analysis tools, complex tasks and projects can be handled with confidence.
Munich: 18 June – Register NowOur Annual 2-Day Risk Conference will be held in New Orleans, November 11-12, at the Hilton New Orleans Riverside. Register now for our biggest event, with multiple tracks of software training and industry presentations.
» See the global list of conferences for 2015
In some instances you may wish to have @RISK draw random numbers from a particular distribution that is not in the Define Distributions dialog. If this holds true for your situation, @RISK does give you the ability to use a formula for the inverse CDF (Cumulative Distribution Function), if a closed form exists. The input to that formula is a RiskUniform(0,1) which provides a randomly selected cumulative probability; then your inverse CDF formula converts that to an x value. Click on the link below to learn more.
Introduction to Risk and Decision Analysis using
Introduction to Risk Analysis using @RISK
Oil and Gas Applications of @RISK and DecisionTools Suite
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