@RISK Fights Avian Flu in
Scientific Computing World
The August/September issue of Scientific Computing World includes the feature “Academics Tackle Epidemics” by David Robson on how modeling software is used to monitor the spread of global disease. The article highlights London’s Royal Veterinary College use of @RISK to determine chances of bird flu reaching Britain. Referring to his @RISK analysis, Professor Dirk Pfeiffer, leader of the RVC’s Population Biology and Disease program states, “In-depth knowledge…enables us to take a rational approach to situations that, at a surface level, have the potential to spread out of control.” Palisade Senior Consultant Dr. Michael Rees is also quoted in the article.

Excerpt:
“Scientists like to use tools they are already familiar with, and Palisade’s @RISK software allows Monte Carlo analysis, a technique frequently used in disease epidemiology, to be performed in the comfort of Microsoft Excel. When studying a disease, the software would then analyze [different factors] to find the likelihoods of an outbreak depending on different circumstances.”

» Read the full article
» Download the full article (PDF)

Palisade User Conference
North America Draws Record
Global Delegation
Palisade Corporation marked another attendance milestone at its 2nd Annual User Conference North America. Held in Miami Beach October 25th and 26th, 2007, the event attracted scores of delegates from across North America as well as Australia, France, Uruguay, Finland, and Russia.

Sam McLafferty, President, Palisade Corporation noted, “I was impressed with the dynamic energy of this conference. The attendees engaged our staff and the presenters with a vigor I have seldom seen.”

The 2007 event was sponsored by QUALITY Magazine, Foresight Magazine, and Oil & Gas Financial Journal.

“Overall, I found the conference to be an excellent use of time.  The Palisade staff was extremely helpful in answering my questions and educating me on the software.  I look forward to working with the new [@RISK 5.0] version.”
Isaac Espinoza, Greenlight Reinsurance

“The dinner / networking was an invaluable part of conference!”
Ed Kuligowski, PTS

“Great experience, will definitely return in the future.”
Jason Mewis, ENGCOM Engineering & Computing
Professionals, Inc.

Free Live Webcast:
The DecisionTools Suite at Unilever
"Software is Only Part of the Solution..."
Thursday, 8 November 2007 @ 11:00am ET
For the last three years Unilever’s Finance Academy has been rolling out and embedding its Decision Making Under Uncertainty (DMUU) program to its finance managers, project leaders and key decision makers. The key aim of this program is to create a culture where high-quality decisions and probabilistic analysis are the norm. Palisade’s DecisionTools Suite provides the analytical engine which enables the analysts to develop clear insights and gain commitment to action. By building a collaborative relationship with Palisade, Unilever has developed joint courses focused on Unilever-specific requirements and armed over 200 people with the software tools they need to analyze complex decisions. This presentation will share the experiences and learnings Unilever has gained from the past three years.

» Register now for FREE Live Webcast:
"The DecisionTools Suite at Unilever:
Software is Only Part of the Solution..."
Thursday, 8 November 2007, 11:00am - 12:00pm ET /
4:00 - 5:00 pm GMT

Risk Register, Monte Carlo Simulation, Decision Trees and Force Field Analysis have been integrated to facilitate the decision-making process. This system has been used and applied to Suncor Bitumen Selection Strategy, and the case study proved to be successful. In addition, the result of this case study, along with further research work, may have potential commercial values. If the processes are properly generalized, theorized, and formalized; it will be valuable to Suncor and to any other energy company which desires a proven methodology for their future major capital project selection decisions.

» Download the conference presentation
» Download the white paper

Value at Risk (VAR)

This example was taken from Chapter 45 of Financial Models using Simulation and Optimization by Wayne Winston, published by Palisade Corporation, where a detailed, step-by-step explanation can be found. It is also explained further in the @RISK User's Guide.

» Example model: Var.xls

Discounted Cash Flow (DCF)
Discounted cash flow (DCF) calculations are a frequent example of the use of @RISK. In the example model, the sources of risk are the revenue growth rate and the variable costs as a percentage of sales.  After taking into account the assumed investment, and applying a discount factor, the DCF is derived.  Following the simulation, the average (mean) of the DCF is known as the net present value (NPV).  In this example, the results show that the average DCF is positive (about 40), whereas the probability of a negative DCF is about 15%. The decision as to whether to proceed or not with this project will therefore depend on the risk perspective or tolerance of the decision-maker.

This example has also been extended to calculate the distribution of bonus payments on the assumption that a bonus is paid whenever the net DCF is larger than a fixed amount (such as 50).  It also uses some of the @RISK Statistics functions RiskMean, RiskTarget, and RiskTargetD to work out the average net DCF, the probability that the net DCF is negative and the probability that a bonus is paid.

» Example model: CashFlow.xls

Agriculture

» Delayed cultivation on set-aside land benefits wildlife
Technique: Decision Trees   » see PrecisionTree
Source: FarmersWeekly, 11 October 2007

Delaying cultivating or spraying off rotational fallow land for as long as possible are the keys to managing it most successfully for environmental benefit, according to a new decision tree produced by The Farming and Wildlife Advisory Group and The Game and Wildlife Conservation Trust

Child Development

» Intelligent Playgrounds
Technique: Neural networks   » see NeuralTools
Source: CNN International, 26 September 2007

The team at the University of Southern Denmark developed the technology by first studying children in a playground. They categorized the behavior of children, comparing those who played in a disruptive manner with those who played in a continuous way. When they brought a new set of children to the playground, the neural network they had programmed had learnt to recognize different children's abilities.

Computer Gaming

» Using Genetic Programming to Evolve Soccer Teams
Technique: Decision Trees   » see PrecisionTree
Source: Gamasutra, 27 September 2007

In this article, a decision tree process was used to create the best, or optimal, soccer team. The goal was to develop a decision tree to each one of the team’s players.

Credit Card Fraud

» Credit Card Fraud: Solving the Crime with Math
Technique: Neural networks   » see NeuralTools
Source: Earth and Sky, 2 November 2007

Credit card companies have turned to sophisticated computer programs called “neural networks” to fight fraud. A computerized neural network needs to undergo a process of “training” to decide whether a transaction is legitimate. One of the great advantages of neural networks is the sheer scope of data they can analyze to discern patterns.

Emergency Treatment

» Online Resource To Help Medical Responders
During Radiation...
Technique: Decision Trees   » see PrecisionTree
Source: Medical News Today, 30 September 2007

Plans to counter one of the most menacing threats - radiation contamination by nuclear explosion, "dirty" bomb, or some other device - have been developed. Part of a solution to this challenge is a series of decision-tree algorithms for the nonexpert physician to follow at the scene....

Global Warming

» Urjit R Patel: The Heat is On
Technique: Monte Carlo simulation  » see @RISK
Source: The Business Standard, 15 October 2007

Cost estimates of global warming based on IAMs underscore the need for a modelling approach based on probabilities (deploying Monte Carlo simulation), which means that a scenario is run many times (as many as 1,000 times), each time choosing a set of uncertain parameters randomly from pre-determined ranges of possible values.

Medical Screening

» Neonatal Screening for Metabolic Disorder
Deemed Cost-effective
Technique: Monte Carlo simulation  » see @RISK
Source: Medicexchange.com, 28 September 2007

A Monte Carlo simulation was used to assess the incremental cost-effectiveness ratio (ICER) of screening vs. not screening for medium chain acyl-CoA dehydrogenase (MCAD) deficiency, a recessive disease.

Oil & Gas

» An Oil & Gas Shangri-la in the Arctic?
Technique: Monte Carlo simulation  » see @RISK
Source: Energy Bulletin, 10 October 2007

Undiscovered oil and gas resources in each of 24 plays (assessment units) within the Alaska Central North Slope were estimated using a deposit simulation analysis. Sizes of oil and gas accumulations were simulated using a Monte Carlo algorithm.

Semiconductor Manufacturing

» Improving Yield through Parametric
Variability Characterization and Modeling
Technique: Monte Carlo simulation  » see @RISK
Source: Solid State Technology, 2 November 2007

Random and systematic process variations reduce parametric yields significantly at the leading 65nm and 45nm CMOS process technologies. Local distribution and correlation models of circuit modeling parameters supply statistical circuit analysis engines using Monte Carlo sampling techniques.