@RISK

6_RE

@RISK

845£

@RISK is used to analyze risk and uncertainty in a wide variety of industries. From the financial to the scientific, anyone who faces uncertainty in their quantitative analyses can benefit from @RISK.


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Wouldn’t you like to know the chances of making money – or taking a loss — on your next venture? Or the likelihood that your project will finish on time and within budget? How about the probabilities of finding oil or gas, and in what amounts?  
Everyone would like answers to these types of questions. Armed with that kind of information, you could take a lot of guesswork out of big decisions and plan strategies with confidence. With @RISK, you can answer these questions and more – right in your Excel spreadsheet.
@RISK (pronounced “at risk”) performs risk analysis using Monte Carlo simulation to show you many possible outcomes in your spreadsheet model—and tells you how likely they are to occur. It mathematically and objectively computes and tracks many different possible future scenarios, then tells you the probabilities and risks associated with each different one. This means you can judge which risks to take and which ones to avoid, allowing for the best decision making under uncertainty.
@RISK also helps you plan the best risk management strategies through the integration of RISKOptimizer, which combines Monte Carlo simulation with the latest solving technology to optimize any spreadsheet with uncertain values.  Using genetic algorithms or OptQuest, along with @RISK functions, RISKOptimizer can determine the best allocation of resources, the optimal asset allocation, the most efficient schedule, and much more.
How @RISK Works
Running an analysis with @RISK involves three simple steps:
1. Set Up Your Model. Start by replacing uncertain values in your spreadsheet with @RISK probability distribution functions, like Normal, Uniform, or over 35 others. These @RISK functions simply represent a range of different possible values that a cell could take instead of limiting it to just one case. Choose your distribution from a graphical gallery, or define distributions using historical data for a given input. Even combine distributions with @RISK’s Compound function. Share specific distribution functions with others using the @RISK Library, or swap out @RISK functions for colleagues who don’t have @RISK.
Next, select your outputs—the "bottom line" cells whose values interest you. This could be potential profits, ROI, insurance claims payout, disease recovery rate, or anything at all.
Define Uncertainty with Ease @RISK comes with 40 distribution functions. These are true Excel functions, behaving the same way as Excel’s native functions and giving you total modeling flexibility. Choosing which @RISK distribution function to use is easy because @RISK comes with a graphical distribution gallery that lets you preview and compare various distributions before selecting them. You can even set up your distributions using percentiles as well as standard parameters, and overlay different distribution graphs for comparison. You can use historical or industry data and @RISK’s integrated data fitting tool to select the best distribution function and the right parameters. You can select the type of data to be fit (e.g. continuous. discrete, or cumulative), filter the data, specify distribution types to be fit and specify Chi-Squared binning to be used. Fitted distributions are ranked based on three statistical tests, and may be compared graphically. You can even overlay graphs of multiple fitted distributions. Fit results can be linked to @RISK functions, so the functions will update automatically when input data changes.
Input distributions may be correlated with one another, individually or in a time series. Correlations are quickly defined in matrices that pop up over Excel, and a Correlated Time Series can be added in a single click. A Correlated Time Series is created from a multi-period range that contains a set of similar distributions in each time period.
All @RISK functions and correlations in your model are summarized—with thumbnail graphs—in the dashboard-style @RISK Model window, and you can watch distribution graphs pop up as you browse through cells in your spreadsheet.
Share Your Model with Others @RISK functions can be stored in the @RISK Library, a SQL database for sharing with other @RISK users. @RISK functions may also be removed with the Function Swap feature, enabling your models be to shared with colleagues who don’t have @RISK installed. @RISK will keep track of any changes that occur in the spreadsheet while the @RISK functions were “swapped out.” You can control how @RISK should update formulas when it finds changes in the model. In addition, you can have @RISK automatically swap out functions when a workbook is saved and closed and automatically swap in if necessary when a workbook is opened. 
2. Run the Simulation. Click the Simulate button and watch. @RISK recalculates your spreadsheet model thousands of times. Each time, @RISK samples random values from the @RISK functions you entered, places them in your model, and records the resulting outcome. Explain the process to others by running your simulation in Demo Mode, with graphs and reports updating live as the simulation runs.
3. Understand Your Risks. The result of a simulation is a look at a whole range of possible outcomes, including the probabilities they will occur. Graph your results with histograms, Scatter Plots, cumulative curves, Box Plots, and more. Identify critical factors with Tornado charts and sensitivity analysis. Paste results into Excel, Word, or PowerPoint, or place them in the @RISK Library for other @RISK users. You can even save results and charts right inside your Excel workbook.
Clear, Easy-to-Understand Results @RISK provides a wide range of graphs for interpreting and presenting your results to others. Histograms and cumulative curves show the probability of different outcomes occurring. Use overlay graphs to compare multiple results, and summary graphs and Box Plots to see risk and trends over time or over ranges. Right-click menus and handy toolbars make navigation a snap. All graphs are fully customizable—including titles, axes, scaling, colors, and more—and ready for export to Excel, Word, or PowerPoint. You can watch results graphs pop up as you browse through cells in your spreadsheet.
@RISK provides you with sensitivity and scenario analyses to determine the critical factors in your models. Use sensitivity analysis to rank the distribution functions in your model according to the impact they have on your outputs. See the results clearly with an easy-to-interpret Tornado diagram, or uncover relationships with Scatter Plots. Sensitivity analysis pre-screens all inputs based on their precedence in formulas to outputs in your model, thus reducing irrelevant data. In addition, you can use @RISK’s Make Input function to select a formula whose value will be treated as an @RISK input for sensitivity analysis. In this way, multiple distributions can be combined into a single input, streamlining your sensitivity reports.
All simulation results for both outputs and inputs are summarized—with thumbnail graphs—in the dashboard-style @RISK Results Summary window. Simulation results may be saved directly in your Excel workbook, and also placed in the @RISK Library to for sharing with other @RISK users.
New in Version 6.0 – Improvements for Project Management & More
New @RISK version 6.0 includes a wide range of improvements, including powerful new integration with Microsoft Project that allows you to perform risk analysis and Monte Carlo simulation on your Microsoft Project schedules – all from the @RISK for Excel platform! Other new features include easier-to-understand tornado charts, better graphing options, improved distribution fitting, new distribution functions, and much more. The Industrial edition now adds the OptQuest solving engine to RISKOptimizer, and features simulation of time-series forecasts.
Integration with Microsoft Project The new version of @RISK for Excel integrates with Microsoft Project, allowing you to perform all your risk modeling from the more flexible Excel environment. @RISK now imports your Project schedules into Excel so that you can use all of Excel’s formulas, and @RISK’s features, on your Project models. Excel becomes a front-end for your Microsoft Project schedule, linking directly to the underlying .MPP(X) file. Changes made in either Project or Excel are reflected in the other. When it’s time to run your Monte Carlo simulation, Microsoft Project’s scheduling engine is used for the calculations, ensuring accuracy.
Time Series Simulation @RISK now offers a new set of functions for simulating time series processes, or values that change over time. Any future projection of time series values has inherent uncertainty, and @RISK now lets you account for that uncertainty by looking at the whole range of possible time series projections in your model. This is particularly useful in financial modeling and portfolio simulation.

@RISK Professional

Designed for professional-grade problems in any industry, @RISK Professional is perfect for most commercial uses. It provides a balance of advanced analysis and point-and-click ease of use, and includes:
  • @RISK Library: A SQL database for storing and sharing with others @RISK distribution functions, model components, and simulation results.
  • Integrated distribution fitting: Defines distribution functions for you based on historical or industry data.
  • Excel Developer Kit (XDK): Automate and customize @RISK for Excel through a complete library of commands and functions that let you control every aspect of @RISK in your spreadsheet. Add @RISK for Excel to any custom application.
  • Stress Analysis: Lets you control the range that is sampled from a distribution function, enabling you to see how different scenarios affect your bottom line without changing your model.
  • Advanced Sensitivity Analysis: Lets you see how changes in any input—distributions or regular values—affect simulation results.
  • @RISK Goal Seek: Uses multiple simulations to find an input value that achieves a target simulation result you specify. 

 @RISK Industrial

Designed for your largest, most complex models, @RISK Industrial includes everything in @RISK Professional, plus the following:
  • RISKOptimizer: Combines Monte Carlo simulation with sophisticated optimization techniques to find the best combination of factors that lead to a desired result under uncertain conditions.  Use RISKOptimizer for resource allocation, scheduling, investment, route planning, and other types of tricky problems where you need to determine the best combination of inputs to maximize a return, minimize a cost, or achieve a specific target.  RISKOptimizer uses genetic algorithms and Optquest solving methods so you’ll be sure to have the right engine for any type of problem.
  • Simulation of Time-series Forecasts:  @RISK offers a set of functions for simulating time series processes, or values that change over time. Any future projection of time series values has inherent uncertainty, and @RISK lets you account for that uncertainty by looking at the whole range of possible time series projections in your model. This is particularly useful in financial modeling and portfolio simulation. There are functions available for 17 different statistical time series models, including ARMA, GBM, GARCH, and others. These functions are entered as array functions in Excel. @RISK also provides new windows for fitting historical time series data to these new functions. The results can be animated to show the behavior of your time series during simulation. All this is integrated into the existing @RISK interface.
  • Full Multi-CPU support: Speed up simulations with parallel processing by using all multi-core processors and available CPUs within a single machine. 

How RISKOptimizer Works

Standard optimization programs are good at finding the best combination of values to maximize or minimize the outcome of a spreadsheet model given certain constraints. However, these programs are not set up to handle “uncontrolled” uncertainty, and require static values for any factor that is not being adjusted by the optimization. This forces modelers into making decisions based on overly simplistic or inaccurate results.
Add Simulation to Optimization Suppose you have several factories and want to find the best locations to manufacture different products to meet demand in nearby cities. You want to maximize profits and minimize shipping costs. This is a straightforward optimization problem where you want to assign manufacturing volume, by product, to different factories. But key factors out of your control are uncertain: shipping costs, demand, etc. Traditionally you would have had to guess at the uncertain factors and hope for the best. With RISKOptimizer, those uncertain factors are represented with probability distribution functions (like Normal, Triang, etc.) so that a Monte Carlo simulation can be run for each trial allocation of manufacturing volume. In this way, you can maximize the mean of the simulated output – say profits – an account for risk during optimization.
Add Optimization to Simulation
@RISK uses Monte Carlo simulation to account for the uncertainty in models and determine the probability of various outcomes occurring. But Monte Carlo simulation does not deal with decision variables whose values you can control. It handles random, uncertain values at a single state of those decision variables.
Suppose you are developing a new product and want to determine whether or not this venture will pay off in the long run. You build a standard spreadsheet model to calculate the profit, replacing uncertain factors like demand and material costs with @RISK functions. Then you realize that some of your assumptions are based on using specific vendors and production methods to construct your product. There may be other vendors and methods available to you that could save money. It's also possible that some production methods may make shipping costs unattractive. With @RISK alone, you could run multiple simulations and compare results - but did you try every possible combination of inputs? With RISKOptimizer, you can try different combinations of vendors and methods to maximize your profits.
Using RISKOptimizer involves three simple steps:
1. Set Up Your Model. The RISKOptimizer Model window provides one-stop setup for all optimization problems. Here you specify the target cell and statistic, identify cells to adjust, and define constraints. Adjustable cells and constraints support cell ranges for easy setup and changes, while target cells can be maximized, minimized, or approach a specific goal.
Defining Ranges and Stopping Conditions 
When defining adjustable cells, you can specify the maximum and minimum boundaries of ranges of cells directly in Excel, greatly simplifying setup and making changes easy. For example, you can tell RISKOptimizer to adjust cells B1:B5, with a minimum value for each in A1:A5, and a maximum value for each in C1:C5. Multiple groups of cells may be specified, with multiple ranges in each group.
You must also define constraints in your model. For example, there may be limited resources which must be modeled. When defining constraints (hard or soft), you can also specify minimums and maximums with cell ranges.
Finally, set stopping conditions for your optimization, telling RISKOptimizer when to stop each simulation and when to halt the optimization as a whole.
Solving Methods RISKOptimizer uses six different solving methods that you can specify to find the optimal combination of adjustable cells. Different methods are used to solve different types of problems. The six methods are:
  • Recipe - a set of variables which can change independently.
  • Grouping - a collection of elements to be placed into groups.
  • Order - an ordered list of elements.
  • Budget - recipe algorithm, but total is kept constant.
  • Project - order algorithm, but some elements precede others.
  • Schedule - group algorithm, but assign elements to blocks of time while meeting constraints.
In your spreadsheet itself, you need to add probability distribution functions to describe uncertain factors beyond your control. For more on probability distribution functions, see @RISK.
RISKOptimizer also allows a great degree of control over how it performs the optimization itself. You can set optimization and simulation parameters, runtime settings, control macros, and more in the RISKOptimizer Settings dialog.
2. Run the Optimization. Click the Start icon to start the optimization. RISKOptimizer will start generating trial solutions, and running Monte Carlo simulations on each one, in an effort to achieve the target set in Step 1. The summary RISKOptimizer Progress window appears, showing simulation status and best answer achieved thus far. This window lets you pause, stop, and run the optimization using playback controls. You can also monitor progress in detail with the RISKOptimizer Watcher. Tabbed reports show real-time updates on best answers achieved, all solutions tried, the diversity of solutions being tried, and more.
What Optimization Does During an optimization, RISKOptimizer generates a number of trial solutions and uses genetic algorithms to continually improve results of each trial. For each trial solution, a Monte Carlo simulation is run, sampling probability distribution functions and generating a new value for the target cell - over and over again. The result for each trial solution is the statistic that you wish to minimize or maximize for the output distribution of the target cell (mean, standard deviation, etc.). For each new trial solution, another simulation is run and another value for the target statistic is generated.
3. View Optimization Results. After optimization, RISKOptimizer can display the results of the original, best, and last solution on your entire model, updating it with each scenario in a single click. This makes it easy to decide the best course of action. You can also generate reports directly in Excel for an optimization summary, log of all simulations, and log of progress steps.

Part of the DecisionTools Suite

@RISK is available by itself or as part of the DecisionTools Suite, Palisade’s complete risk and decision analysis toolkit. The DecisionTools Suite includes PrecisionTree for decision trees, TopRank for what-if analysis, NeuralTools andStatTools for data analysis, and more. @RISK is fully compatible with all DecisionTools programs and can be combined with them for greater insight and analysis.
» More about The DecisionTools Suite - Save Over 50% When You Buy the Suite
When you buy the DecisionTools Suite, you save over 50% versus buying all components individually. The best analyses at a great price—with the DecisionTools Suite.
Stand-alone Licenses
Stand-alone licenses are intended for use by one person on one computer. They may not be run from a server. Every stand-alone license comes with its own serial number and activation ID which unlocks the software for perpetual use. Software activation can be done with a single click over the Internet or manually via e-mail. Stand-alone licenses may be transferred from one computer to another once every 90 days, but may never be used one more than one computer at a time.
 View the Stand-Alone License Agreement 
Concurrent Network Licenses
Concurrent network licenses are intended to serve multiple users from a network server. The software is installed on a single server, but may also be installed on an unlimited number of client computers. The restriction is placed on the number of users who can access the software at the same time, i.e., concurrently. Concurrent network licenses are a very cost-effective way to serve many people who need to use the software occasionally and “log off” when finished. Concurrent network licenses utilize FLEXnet technology and come with one serial number and activation ID, regardless of the number of users. Software activation is only required for the server license, not the client installations. Activation can be done with a single click over the Internet or manually via e-mail. The same installer may be used on all client computers, so scripting is very straightforward. In addition, concurrent network licenses support Terminal Services and Citrix environments. The server license may be transferred from one server to another once every 90 days, but may never be used on more than one server at a time.
Concurrent network licenses also allow “borrowing,” or temporarily taking one license off the network server and putting it on the client computer. This lets someone use the software even if their computer is disconnected from the server (e.g., taking a laptop on a trip). When a license is borrowed, an expiration date must be set by the user. At expiration, the license is automatically returned to the server license pool and ceases to function on the disconnected client.
 View the Concurrent Network License Agreement 
Enterprise Activation Server
 Enterprise Activation Server licenses use FLEXnet technology to allow you to grant and manage stand-alone licenses of Palisade software from your own server instead of the Palisade license server. Rather than requiring every stand-alone user to contact the Palisade license server to activate their software, each user would instead contact your own server once to activate. A single activation ID may be used for all license installations. You can expand the number of users on the license by purchasing additional users for the same server without having to use a new activation ID. If users wish to transfer licenses from one computer to another, the deactivation and reactivation of licenses can be managed on your local server as well. Enterprise Activation Servers are a great option for companies with strict firewall or security protocols, and make license management easy.
 View the Enterprise Activation License Agreement 
Corporate Licenses 
The Most Cost-Effective Solution Palisade corporate licenses are purchasing options that enable you to get the most software for your money, deployed in the most efficient manner possible. Using the concurrent network or Enterprise Activation methods (though they may be customized however you wish) and are structured according to your organizational needs and volume.
Investing in a Palisade corporate license is the most cost-effective path to better decisions enterprise-wide. By switching from haphazardly purchasing individual copies to adopting a corporate license, many companies have found that the return on their software investment dramatically improved. Not only was their investment outlay reduced compared to buying individual copies, but widespread access to the software encouraged better decision-making throughout the organization.There are two kinds of Palisade corporate licenses:
Site Licenses – Provide software access to everyone at a particular physical location. 
Enterprise Licenses – Provide access to the software throughout an organization or division regardless of physical location.
Benefits of corporate licenses include:
The latest software version - for everyone. With current maintenance, all users work with the same current version, and upgrades are handled on the same corporate level to maintain this consistency and avoid compatibility issues.
Encourages better decisions throughout the organization. Corporate licenses encourage experimentation with powerful Palisade software by all employees. The more people performing quantitative decision analysis, the better your decision will become.
Elimination of IT compliance issues. A corporate license relieves IT personnel of having to monitor software usage to ensure compliance with software license agreements.
Streamlined procurement process eliminates red tape. By procuring software through a single purchasing contract, you can avoid departmental budget constraints, differing purchasing procedures, and other administrative hurdles.

@RISK Standard

@RISK Professional

@RISK Industrial

£845.00

£1,095.00

£1,550.00
Volume licensing is available, please contact us at: sales@unitedaddins.com .
Oil and Gas Corporations
Amoco
Anadarko Petroleum
BHP
BP
Blade Energy 
CDX Gas
ChevronTexaco
Cinergy 
Conoco
Duke Energy
ExxonMobil
Fluor Daniel 
IHS Energy 
National Oilwell Varco
NIPSCO 
RiskAdvisory (Canada) 
Petrobras (Brasil)
PetroCanada
Phillips Petroleum
Schlumberger
Shell
StatOil
Teikoku Oil Co, Ltd. (Japan)
Unocal
Insurance/Actuarial Customers
ACE Bermuda Insurance Co. Ltd.
ACE USA
AEGIS Insurance Services, Inc
Aetna Chile Seguros de Vida
AFLAC
Allianz Insurance Company
Allstate Insurance Company
American Re-Insurance Company
American Family Insurance
Aon Non-Marine Reinsurance Ltd
Aon Re Ireland
Aon Risk Services Japan Ltd.
Arab-Malaysian Assurance Berhad 
Arkwright Mutual Insurance
Aspinall & Associates 
Chaucer Insurance Plc (UK)
C.G.U. Insurance S.A. (South Africa)
CNA Reinsurance Europe Ltd
Colonial Insurance (Bermuda)
Erc Frankona Reinsurance AS 
General Reinsurance
G.I. Actuarial (UK)
ING Reinsurance Co Intl Ltd
Kemper Insurance
K.L.P. Insurance (Norway)
PMA Re
London Life & Casualty
Manulife Financial
Maritime Life Insurance
MMI Insurance (Australia)
NAC Reinsurance
National Grange Mutual Ins. 
New York Life
North Carolina Department of Insurance
Northwestern MutualLife
Partner Reinsurance Company
Pearl Assurance Plc (UK)
Penn National Insurance Co.
PMA Re
Progressive
Renaissance Reinsurance 
St. Paul Reinsurance Co. Ltd
State Farm Insurance
Standard & Poor's Insurance
Swiss Reinsurance 
Texas Builders Insurance, Co.
Renaissance Reinsurance
Transatlantic Reinsurance Comp 
Willis Faber
Zurich Insurance Group (Switzerland)
Other Customers
Abacus Technology
ADM
AMD
AT&T
Bank of America
Bankers Trust
BC Hydro
Bechtel
Becton Dickinson
Black and Decker
Blue Cross Blue Shield of Florida
Boeing
Bombardier
Borden Foods Co.
Borg Warner
Bristol-Myers Squibb
Center for Disease Control
Centre for Traffic and Transport
Chase Manhattan Bank
Cinergy 
Citibank
Coca-Cola
Colgate Palmolive
Coopers & Lybrand
Corning
Corus 
Cummins Engine Corp. 
CVRD Brasil
Deloitte Tohmatsu Corp. Finance Co. (Japan)
Dow Chemical
Eastman Chemical
eBay
Employer's Reinsurance Corp.
Ernst & Young
Facebook 
Federal Highway Administration 
Fluor Daniel 
Ford Motor Company
Gannett Fleming 
Gap
GEICO
General Electric                                      
Goodyear
GRE Insurance Group
Halcrow Group Ltd 
Harley-Davidson
Hatch Associates
Her Majesty’s Prison Service  
Hewlett-Packard
Hitachi
Honeywell International
Hospital Clinic Barcelona 
Hughes Aircraft
IBM
Impex Corporation (Japan)
ING - Equitable Life
IHS Energy 
Istria Ltd 
Japan Food Research Labs 
John Deere
Johnson & Johnson
Katrina Disaster Response 
Kennecott Utah Copper 
Kirin Brewery Company, Ltd. 
KPMG Peat Marwick
Logion (Netherlands)  
Los Alamos National Lab.
Louis Berger Group
Lucent Technologies
Marsh Japan Inc.
McKinsey & Co.
Met-Mex Peñoles (Mexico) 
Mettler Consulting 
Mercantile Co. Ltd (Japan)
Merck 
Microsoft’s Treasury Department 
Mitsubishi Heavy Industries Ltd. 
NASA
National Reconnaissance 
Group (Virginia) 
New Balance Athletic Shoe
NIPSCO 
Northrop Grumman
Disney
Ontario Hydro
Oracle
Owens Corning
Pantektor AB 
Pareto Solutions 
PepsiCo
PCA Life (Japan)
Pfizer
Post Denmark 
Price Waterhouse Coopers
Procter & Gamble  
Raytheon
RiskAdvisory (Canada) 
SAIC
Sara Lee
Shimadzu Corporation
Starbucks
Sumisho Electronics Co., Ltd. 
Sun Life Reinsurance Group
Society of Actuaries / Casualty 
TAP Pharmaceuticals
Thales 
Tillinghast Towers & Perrin
Toyota
Triangle Economic Research 
TRW
TVA (Tennessee Valley Authority)
UK Ministry of Defence 
Unilever
US Dept. of Agriculture
US Army Corps of Engineers
US Steel
Verizon
Western Australia Department of Agriculture 
Wal-Mart Stores
Westinghouse
The World Bank
World Conservation Union 
Whirlpool
Xerox
 PDF depicting U.S. Government departments with Palisade software licenses