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DecisionTools Suite - Industrial Edition

SKU: PAL10ESL

The DecisionTools Suite Industrial includes @RISK for Monte Carlo simulation, PrecisionTree for decision trees, and TopRank for “what if” sensitivity analysis. In addition, the DecisionTools Suite comes with StatTools for statistical analysis and forecasting, NeuralTools for predictive neural networks, and Evolver and RISKOptimizer for optimization.

$3,395.00
$3,225.25
Products specifications
Min. OS Requirement Windows XP
Language 6 languages (EN, FR, JP, ES, CN, KR)
Add-In Requires Excel
Available for Mac No, requires Parallels Emulation
Price includes 1st year maintenance
Requires other Software? Requires Microsoft Excel to run
Scripting Support Built In
Simulation Monte Carlo
VBA Support Built In
CSV Support
XML Support
Distribution Fitting Built In
User Defined Distributions
Distribution Gallery 48 base distributions (38 Continuous + 10 Discrete) with 20 that can have alternate parameters
Monte Carlo Sampling
Latin HyperCube Sampling
Process Capability (6 Sigma)
Sensitivity Analysis
Tornado Analysis
Precision Control
Probability calculations functions
Correlation
Correlation Methods Normal + Non-Normal Copulas
SIP Math Support
Decision Trees Comes bundled with PrecisionTree
Stats Tools Comes bundled with Palisade StatsTools
MS Project Support
Charting Built In
Charts can be customized
Automated Reporting
Multi-Core Support
Developper Kit
Example Models
Network Licensing Available
Data Base Integration 30+ Data Sources with CDATA Connectors
Integration with other tools Includes Palisade @RISK, PrecisionTree, TopRank, NeuralTools, StatsTools, BigPicture, Evolver and RiskOptimizer
Supported DBs Standard ODBC sources from Excel + 3rd party connectors
User Defined Distribution Library Distributions can be generated and saved to an SQL or SQL Express DB and can be made available to other @RISK users who have access to the repository
Linear Optimization Methods
Non-Linear Optimization Methods
Requirements / Soft Constraints Requires Evolver
Max Requirements Unlimited
Max Decision Variables Unlimited
PSI support
Solution Filtering
Efficient Frontier
Scenario Analysis Support Must be setup as separate submodels using functions. Functions exist to support multiple scenarios and to track results separately
Convergence Testing
Genetic Algorithims
Ranges for Decision Variables
Main Solver Engine RiskOptimizer
Optimize multiple statistics Optimization can be done on 11 different statisics (Mean, Variance, Standard Deviation, Skewness, Kurtosis, Percentile, Min/Max, Mode and Range)
Optimization Goal Types Minimize, Maximize & Set Target
Static Optimization Support
Dynamic Optimization Support
Stochastic Optimization Support
Time Series as distributions
Time Series Fitting
Time Series Methods 11 Methods (AutoRegression, GBM, Moving Average)
Multiple Linear Regression Provided using Palisade StatTools
Seasonal Methods Seasonal ARMA & GBM
Non-Seasonal Methods AR(1&2), MA(1&2)
GBM Support Univariate, Multivariate and Seasonal
Cubic Spline
Heteroscedastic Models ARCH, GARCH11, EGARCH11 and APARCH11
ARIMA Support Partial Support for ARMA
AutoARIMA
Data Sensoring Automatic
Time-Series Event Support
Define Time Series All available methods can be configured manually using parameters
Markov Chains
Automatic Data Transform
Manual Data Transform Methods
Manual Deseasonalization
Manual Detrending
Visualize Simulated Output
Exception Reporting
Time Series Scenario Analysis
Error Measures
Time Series Fit Criteria Akaike and Baysean Information Criteria
Product description

The DecisionTools Suite


The DecisionTools Suite is a complete risk analysis for Excel that includes optimization, decision tree analysis and advanced statistical tools. The DecisionTools Suite means you can judge which  risks to take and which ones to avoid, allowing for the best decision making under uncertainty.

Greater Than the Sum of its Parts

Each component of the DecisionTools Suite can perform a powerful analysis. When you combine these products, you can achieve more complete results than any single program can provide.

New in DecisionTools Suite 6.0

New DecisionTools Suite version 6.0 includes a wide range of improvements, including powerful new integration of @RISK 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! @RISK also adds simulation of time series models, easier-to-understand tornado charts to identify risk drivers, better graphing options, improved distribution fitting, and new distribution functions.

But there’s more to DecisionTools Suite 6.0 than just @RISK. PrecisionTree 6.0 adds powerful Bayesian revision and the ability to insert nodes anywhere in a tree. RISKOptimizer and Evolver 6.0 now include the OptQuest solving engine for even faster solutions on many types of models. RISKOptimizer, which has always shared functions with @RISK, is now even more tightly integrated with @RISK for seamless modeling. And StatTools and NeuralTools have added improvements to scatter plots and sensitivity analysis to the testing of neural nets.

Why go for the DecisionTools Suite?

FEATURES BENEFITS
See all possible outcomes with Monte Carlo simulation Avoid pitfalls and identify opportunities in @RISK or PrecisionTree models
Map out decisions with decision trees and influence diagrams Identify and illustrate the best alternative
Works in Excel No need to learn new applications from scratch
Genetic algorithms and OptQuest optimization methods Solve complex, nonlinear problems involving uncertainty
Linear Programming solving methods Solve linear problems – both large and small – quickly and accurately
Sensitivity or What-If Analysis Identify the most important variables in @RISK or PrecisionTree models
Distribution viewing and fitting Accurate description of uncertainty
Presentation-quality graphs and reports Easily explain results and recommendations to others
Full integration between programs Easily install and migrate between component tools; apply analyses from one tool to another tool’s model for greater insight
Parallel processing Speed up large Monte Carlo simulations by using available CPUs within a single machine
Bundle pricing Save money compared to buying products separately

 

New in @RISK 6.0

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. Univariate and Multivariate Time Series Fitting and 10 New Methods, Including:

  • Auto Regressive Models
  • Moving Averages
  • ARMA
  • Geometric Brownian Motion
  • BMMR
  • GBMJD
  • BMMRJD
  • ARCH
  • GARCH

64Bit Compatible

@RISK 6.0 is fully compatible with 64-bit Excel 2010. 64-bit technology enables Excel and @RISK to access much more computer memory than ever before. This allows for vastly larger models and greater computational power. In addition, @RISK has been fully translated into Spanish, German, French, Portuguese, Japanese and Chinese.

@RISK for Six Sigma

 

A key application of @RISK is Six Sigma and quality analysis. Industries ranging from engine manufacturing to precious metals to airlines and consumer goods are using @RISK every day to improve their processes, enhance the quality of their products and services, and save money.

Whether it’s in DMAIC, Design for Six Sigma (DFSS), Lean projects, Design of Experiments (DOE), or other areas, uncertainty and variability lie at the core of any Six Sigma analysis. @RISK uses Monte Carlo simulation to identify, measure, and root out the causes of variability in your production and service processes and designs.

Six Sigma Capability Metrics in @RISK

@RISK analyzes thousands of different possible outcomes, showing you the likelihood of each occurring. Uncertain factors are defined using over 35 probability distribution functions, which accurate describe the possible range of values your inputs could take. @RISK allows you to define Upper and Lower Specification Limits and Target values for each output, and comes complete with a wide range of Six Sigma statistics and capability metrics on those outputs, like Cpk, Cp, Cpm, and much more. These metrics can be placed directly in your spreadsheet model, or appear in the @RISK Results Summary window. Output graphs show markers for LSL, USL, and Target values. The Industrial edition of @RISK adds RISKOptimizer to your Six Sigma analyses for optimization of project selection, resource allocation, and more.

Additional information
Products specifications
Min. OS Requirement Windows XP
Language 6 languages (EN, FR, JP, ES, CN, KR)
Add-In Requires Excel
Available for Mac No, requires Parallels Emulation
Price includes 1st year maintenance
Requires other Software? Requires Microsoft Excel to run
Scripting Support Built In
Simulation Monte Carlo
VBA Support Built In
CSV Support
XML Support
Distribution Fitting Built In
User Defined Distributions
Distribution Gallery 48 base distributions (38 Continuous + 10 Discrete) with 20 that can have alternate parameters
Monte Carlo Sampling
Latin HyperCube Sampling
Process Capability (6 Sigma)
Sensitivity Analysis
Tornado Analysis
Precision Control
Probability calculations functions
Correlation
Correlation Methods Normal + Non-Normal Copulas
SIP Math Support
Decision Trees Comes bundled with PrecisionTree
Stats Tools Comes bundled with Palisade StatsTools
MS Project Support
Charting Built In
Charts can be customized
Automated Reporting
Multi-Core Support
Developper Kit
Example Models
Network Licensing Available
Data Base Integration 30+ Data Sources with CDATA Connectors
Integration with other tools Includes Palisade @RISK, PrecisionTree, TopRank, NeuralTools, StatsTools, BigPicture, Evolver and RiskOptimizer
Supported DBs Standard ODBC sources from Excel + 3rd party connectors
User Defined Distribution Library Distributions can be generated and saved to an SQL or SQL Express DB and can be made available to other @RISK users who have access to the repository
Linear Optimization Methods
Non-Linear Optimization Methods
Requirements / Soft Constraints Requires Evolver
Max Requirements Unlimited
Max Decision Variables Unlimited
PSI support
Solution Filtering
Efficient Frontier
Scenario Analysis Support Must be setup as separate submodels using functions. Functions exist to support multiple scenarios and to track results separately
Convergence Testing
Genetic Algorithims
Ranges for Decision Variables
Main Solver Engine RiskOptimizer
Optimize multiple statistics Optimization can be done on 11 different statisics (Mean, Variance, Standard Deviation, Skewness, Kurtosis, Percentile, Min/Max, Mode and Range)
Optimization Goal Types Minimize, Maximize & Set Target
Static Optimization Support
Dynamic Optimization Support
Stochastic Optimization Support
Time Series as distributions
Time Series Fitting
Time Series Methods 11 Methods (AutoRegression, GBM, Moving Average)
Multiple Linear Regression Provided using Palisade StatTools
Seasonal Methods Seasonal ARMA & GBM
Non-Seasonal Methods AR(1&2), MA(1&2)
GBM Support Univariate, Multivariate and Seasonal
Cubic Spline
Heteroscedastic Models ARCH, GARCH11, EGARCH11 and APARCH11
ARIMA Support Partial Support for ARMA
AutoARIMA
Data Sensoring Automatic
Time-Series Event Support
Define Time Series All available methods can be configured manually using parameters
Markov Chains
Automatic Data Transform
Manual Data Transform Methods
Manual Deseasonalization
Manual Detrending
Visualize Simulated Output
Exception Reporting
Time Series Scenario Analysis
Error Measures
Time Series Fit Criteria Akaike and Baysean Information Criteria