Palisade User Conference Americas Big Success

From Tacoma, Washington to Bucaramanga, Colombia, scores of risk management

professionals from all corners of the globe descended on Miami, Florida for the 2006

Palisade User Conference: Americas on

November 13-14.

continue below

From Tacoma, Washington to Bucaramanga, Colombia, scores of risk management

professionals from all corners of the globe descended on Miami, Florida for the 2006

Palisade User Conference: Americas on

November 13-14.

continue below

Seminar Schedule

:: Regional Seminars

Risk and Decision Assessment using @RISK and the DecisionTools Suite

December 4-5, Chicago

December 11-12, Houston

January 8-9, San Diego

January 15-16, Atlanta

January 29-30, San Juan

Risk Assessment:

Oil & Gas Focus

December 14-15, Houston

Project Risk Assessment

Using @RISK for Project

January 17-18, Atlanta

:: Regional Seminars

Risk and Decision Assessment using @RISK and the DecisionTools Suite

December 4-5, Chicago

December 11-12, Houston

January 8-9, San Diego

January 15-16, Atlanta

January 29-30, San Juan

Risk Assessment:

Oil & Gas Focus

December 14-15, Houston

Project Risk Assessment

Using @RISK for Project

January 17-18, Atlanta

:: Live Web Training

Risk and Decision Assessment using @RISK, Part I

December 14-15

January 22-23

Risk and Decision Assessment using @RISK, Part II

December 18-19

January 25-26

full schedule and registration

Free Live Webcasts

Overview of @RISK for Project

December 14

Selecting the Right Distribution

December 20

Data Collection with

@RISK for Project

January 9

Ask Amy

Expert Answers to

Technical Questions

n is the number of iterations needed.

S is the estimated standard deviation of the output.

D is the desired width of the confidence interval (in this case, 10 units).

Expert Answers to

Technical Questions

Dear Amy,

Can I determine how many iterations I need to run in my simulation so that the estimate of the mean is calculated within a specific confidence interval?

— J.H.

Dear J.H.,

Yes you can. In the example here, let’s suppose that we want to use simulation to estimate the mean of the output in cell B11 and be accurate within 10 units 95% of the time. The number of iterations needed to meet these requirements can be calculated using the following formula:

n=[z_{a/2}S/D]^{2}

n is the number of iterations needed.

S is the estimated standard deviation of the output.

D is the desired width of the confidence interval (in this case, 10 units).

Palisade Announces Free Live Webcasts

Palisade is pleased to announce a new way to get more from your investment in @RISK and DecisionTools software: Free Live Webcasts. Webcasts are seminars given online free of charge to further learning in risk, decision, and data analysis. The sessions are 30 to 60 minutes in length, include question-and-answer, and are presented on a variety of topics. Webcasts will include a variety of different presentation formats, including:

- Industry applications showing how to approach issues

in areas like project management or real options. - Best practice discussions on how to address common modeling issues.
- Industry case studies from software users demonstrating

how they tackled their risk analysis problems. - Demonstrations of innovative software and how it can be used in a general way.

December Webcast offerings include:

In this session, we explain uncertainty and show how estimates and forecasts can be dramatically ‘tightened up’ within existing risk management procedures using @RISK for Project.

How often have you looked at the palette of distributions in @RISK and related tools and wondered which one you should use? This session will explain, in simple terms and illustrated with example models, the thinking behind the most powerful distributions, what they model, and how they can be put to use in your risk analyses.

view full schedule and register

Case Study:

@RISK Helps Budget for Social Services

To control costs, state governments are increasingly moving toward the privatization of social services. How much should a state pay its private vendors for providing those services? This is always a tricky question, and its answer hinges on ever-changing uncertainties. Dr. Anthony Broskowski’s consulting firm, Pareto Solutions, helps state governments plan the privatization process for mental health and child welfare services. Dr. Broskowski advises state governments on vendors’ administrative cost structures, the mix of appropriate services, and the long-range costs they can expect to pay for those services as well as traditional services. For more than a decade, he has relied on @RISK to make his budget projections.

“Contracting for social services is a risk-reward corridor that both government and vendors must travel through,” says Dr. Broskowski. Recently, the city of Washington, D.C., wanted to privatize the foster-care component of its child welfare program, under a system in which a vendor would receive a prepaid allotment for every child needing a foster care placement. Under this system, the vendor would assume the costs and the risks of cost fluctuations until the child could be reunited with his or her family or attains some other permanency status, such as adoption. To compensate for assuming these risks, the vendor would retain any portion of the government’s payment left over after expenses, within a range of plus or minus 85% of the expected total costs. Dr. Broskowski says that to figure out a fair rate to pay the service provider, “You can’t use a simple formula like: number of children x number of days of care x price per unit.” There are too many other factors, such as local population trends, the case-mix of children by age and reason for removal from the home, and many more.

**:: Big Decisions, Big Models
**Dr. Broskowski’s models are big simulations spun out over long time spans. Having first used @RISK in the early ‘90s for applying managed care principles to carving out mental health insurance benefits for top corporations like Federal Express and Chrysler, he has come to rely on its ease of use for even the largest models. In fact, although he now frequently trains his clients in the use of @RISK, he confesses that for many years he made little mention of his use of Palisade’s software. “I didn’t want those other guys—my competitors—to find out how easy it is to use.”

**:: Balancing Risk
**“With @RISK,” Dr. Broskowski says, “the real challenge isn’t the modeling. The real challenge is getting the folks in government to accept their role in risk sharing. Here again, @RISK is so intuitive it makes it easy to show people how to balance the risks with the opportunities and come to some kind of equilibrium.”

read the full case study

learn more about @RISK

Product Spotlight:

** NeuralTools, Evolver and Solver ****
**NeuralTools is Palisade’s Neural Networks add-in for Microsoft Excel that features the innovative Live Prediction function. Neural Networks are a rapidly-expanding approach to data analysis and prediction, but one that has been implemented primarily by analysts with an advanced understanding of data analysis and artificial intelligence. NeuralTools offers the power of sophisticated analysis, as well as instant updating with Palisade’s proprietary Live Prediction, to the everyday spreadsheet user.

:: Live Prediction a Standout

Live Prediction is the feature that makes NeuralTools a standout among all Neural Networks software. When new data are entered into an analysis, Live Prediction updates predictions instantly. This is a time-saver and is particularly valuable when combined with Excel’s Solver add-in or other optimization software such as Palisade’s Evolver.

Using Solver or Evolver, users can set a desired target prediction—for example, timely repayments of a bank loan with 90 percent certainty. Under a typical scenario, the optimizer would vary input variables such as loan amount until it achieved a 90 percent certainty of loan repayment. But with NeuralTools Live Prediction, the optimizer can vary loan amount, loan term, and other variables, and run that information through NeuralTools in real time. Thus as the optimization proceeds, NeuralTools continually updates its repayment predictions. Users can set the optimizer to continually change the model until the desired NeuralTools prediction is achieved. This is a far more accurate way of analyzing and optimizing predictive problems.

When coupled with Evolver, you can solve complicated, non-linear predictive problems. Combine Evolver’s genetic algorithms with NeuralTools’ predictive capabilities for unprecedented solving power.

The use of Neural Networks spans a variety of industry sectors as wide as the use of Excel—from banking to biology, defense to finance, and medicine to manufacturing. Designed for the many nonspecialists in all enterprises who want access to Neural Networks technology, NeuralTools has innumerable applications, including loan underwriting, credit card fraud detection, airline security analysis, medical diagnoses, financial investment prediction, and many more.

**:: **How NeuralTools Works

NeuralTools uses advanced statistical analysis techniques to reveal the structure of a data set. It “learns” existing data and then uses the knowledge and patterns it discovers to make predictions from new, unanalyzed data. All this happens “behind the scenes,” so the user need not be involved in setting the parameters of each algorithm. The software can perform both numeric and categorical prediction.

learn more about NeuralTools

learn more about Evolver

User Conference Big Success continued from above

The event drew professionals from all industries and featured two days of real-world case studies, workshops, networking, and a preview of the all-new @RISK 5.0 and DecisionTools Suite 5.0.

“The feedback we’ve received from the conference delegates has been overwhelmingly positive,” noted Sam McLafferty, President and CEO of Palisade Corporation. “Attendees expressed excitement about the new versions of @RISK and the DecisionTools Suite, and appreciated learning new applications from each other.”

:: @RISK 5.0 and Keynote Among Highlights

Considered by many a high point of the conference was Mr. McLafferty’s unveiling of @RISK 5.0 and the DecisionTools Suite 5.0. Spontaneous declarations of approval were heard as he explained feature after feature of the new versions, including: a more robust graphics engine, direct integration with the spreadsheet, @RISK Libraries for sharing distributions and simulation results, and the ability to share @RISK models with non-@RISK users.

Another highlight was keynote speaker David Apgar’s address presenting an interesting proposition about risk intelligence. Mr. Apgar is the author of the just-published book *Risk Intelligence: Learning to Manage What We Don’t Know* from Harvard Business School Press. He asserted that business risks are learnable, and not simply random, thereby allowing organizations to better manage the unknown. He provided a scorecard to help businesses quantify their risk intelligence, and suggested from there building a “risk pipeline” to constantly monitor organizational risks.

:: Diverse Delegation; Diverse Locations

A cross-section of customers participating in Palisade’s inaugural annual user conference included: S.C. Johnson & Son, Inc., Kimberly-Clark, Cummins Inc., McKinsey and Co., Capital One, WorleyParsons Komex, Boeing, General Dynamics, Banco Nacional de Costa Rica, Detroit Public Schools, Sumitomo Mitui Banking Corp. Group, United States Military Academy at West Point, ISA Colombia, Ontario Power Authority, and INCAE Business School.

The now annual Palisade User Conference: Americas was the finale in a global user conference series that began in London, England in June, and moved on to Sydney, Australia. The 2007 Palisade User Conference: Europe is already set for April 23rd and 24th in London, while dates are being planned for events in Australia, Latin America, and North America as well.

**:: **Presentations Available

Sessions were presented from a variety of industries on applications ranging from asset retirement to sports betting to Six Sigma manufacturing control. Many of the presentations from the Palisade User Conference: Americas, including the keynote address, are now available for free download from the Palisade web site.

more about the Palisade User Conference: Americas

view abstracts and presentations

more testimonials

Ask Amy continued from above

z_{a/2} is the number that satisfies P(Z>z_{a/2}) = a/2, where Z follows a normal distribution with mean 0 and standard deviation 1. In words, z_{a/2} is the z value such that the area of the right-hand tail is a/2. a/2 can be found by setting the desired confidence level equal to 100(1−a) and solving for a.

In this example (a 95% confidence level):

95 = 100(1−a)

Then a is 0.05 and a/2 is 0.025. To compute z_{a/2} in Excel, use the NORMSINV function and enter =NORMSINV(1−a/2, 0, 1). Cell E13 of the attached example shows a Z value of approximately 1.96 for a 95% confidence interval.

To obtain an estimate for the standard deviation of the output, the @RISK statistics function RiskStdDev was placed in cell B14 and a simulation was run with just 100 iterations. This gave us a standard deviation of approximately 58.7. If we plug the above information into our formula we get

n = [ 1.96 × 58.7 / 10 ] ² = 133

Thus, at least 133 iterations should be run to be 95% sure that our estimate of the mean of the output in cell B11 is accurate within 10 units.

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©2006 Palisade Corporation, 798 Cascadilla Street, Ithaca, NY 14850 USA

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E-mail comments or suggestions to: sales@palisade.com

©2006 Palisade Corporation, 798 Cascadilla Street, Ithaca, NY 14850 USA

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