@RISK Modeling Tips
» Mumbai 13 January
Project Risk Assessment
Meeting schedule milestones in a timely manner is paramount in any industry, but particularly important in those working with the United States Department of Defense, where deliverables can be a matter of national safety, and where program delays can become very expensive. A major aerospace company was contracted by the U.S. Navy to build defensive missiles, and was required to provide accurate estimations of their timeline and deliverables. Jim Aksel, (Principal) at ProjectPMO, helped the aerospace company deal with schedule risk analysis for their project. Thanks to using @RISK in conjunction with Microsoft Project, Aksel was able to provide the company a rock-solid model proving that their schedule estimation was reliable.
Previously the company used an outdated schedule risk analysis method. "They didn’t have a Monte Carlo simulation tool," says Aksel. "They were adding duration margins to many tasks without knowing if that amount of time was correct or to the correct tasks. It was simply a guesstimation." By cutting out the ‘junk’ tasks in the project schedule, and using @RISK to more accurately determine the durations between milestones, Aksel and his team were able to identify estimates that were six to eight weeks later than they needed to be and shorten them when appropriate.
Aksel describes his favorite feature of @RISK—the fact that the formulas, data, and models are all accessible and viewable in one place. "It lets me see what’s going on where," he says. "I’m able to see everything in going on in one place, so there’s less mystery. I showed the team the inputs and made sure there was consensus from everyone on all the inputs. For this particular project, Aksel explains, the model matched fairly closely to the engineering team’s original estimates with only a few exceptions. "It helped solidify that we had true belief in our logic," says Aksel. "That’s the best success we could ask for!"With Great Power Comes Great Responsibility: @RISK plays a part in finance analysis for SpiderMan 2 and other movie favorites
Movies such as SpiderMan 2, The Interview, and 22 Jump Street have all benefitted from @RISK’s quantitative risk analysis—thanks to Benjamin Waisbren. Waisbren, a partner at the law firm Winston & Strawn, is also the President and a shareholder of LSC Film Corporation, which funds major film productions—such as V for Vendetta, Blood Diamond, and 300. In his role as a film financier, Waisbren uses @RISK in all his negotiations.
Last year, Waisbren relied on @RISK to navigate a $200 million co-financing deal with Sony. The deal gave Waisbren’s team, LStar Capital, a stake in nearly all of Sony’s movies. Waisbren says the success was in part thanks to Palisade’s risk analysis software: "I am happy to say that @RISK played a very significant part in my work on that deal," he says. "I did the modeling behind it, and because of @RISK, we did not hire any outside advisor or consultant." Additionally, because of the risk modeling tool, "our closing costs were about 20 million dollars lower than other deals." After closing the agreement, Waisbren was then asked to be manager of the new film fund for LStar Capital.
Since then, Waisbren has continued to use @RISK to do statistical analysis and risk quantification on the volatility of the motion picture industry. For example, the software has helped him to make uncannily accurate predictions around how much a film will make on its opening day or weekend—or, it can help him predict how much money a film production will burn through in a certain number of months. In short, it’s proven itself invaluable: "I’m really grateful for this product—it has provided a substantial competitive advantage in this business," he says. "I’m a huge believer in this tool."
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Palisade's new mind mapping, data exploration, and diagramming software, BigPicture, is available free of cost during the Beta testing period which is set to expire on June 1st.
Use BigPicture in the beginning stages of your modeling to create strategic maps to help grasp the relationships between your variables before implementing your @RISK model. Group your data by creating a data map in BigPicture to help you see interesting concepts without having to scroll through columns of data. Report findings of your @RISK models to upper level management through BigPicture's slide show capabilities, that allows you to walk your audience through the steps you took to come up with your end results.
Try BigPicture today to see how you can incorporate it into your current modeling routines!
Projecting oil prices under conditions of uncertainty has always been and will always remain a challenge. What makes this more of a challenge is the acceptance that the oil and possibly other commodity and stock markets do not behave in a random fashion generating normal distribution patterns. In this example, a partially manipulated/partially random model for oil prices incorporating uncertainty generates U-shaped distributions. These are difficult to model with a single best fitting distribution. Download the example model and step-by-step instructions to learn a methodology for modeling a U-shaped distribution by creating three segments and obtaining the best fitting distribution for each segment using @RISK.
Introduction to BigPicture
Introduction to Risk and Decision Analysis using
Introduction to Risk Analysis using @RISK
Introducción al análisis de riesgo y
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