Oracle Crystal Ball Suite (Decision Optimizer Edition)

Oracle Crystal Ball is the easiest way to perform Monte Carlo simulations in your own Excel spreadsheets and models. Crystal Ball automatically calculates thousands of different "what if" cases, revealing the range of possible outcomes, their probability

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Products specifications
Min. OS RequirementWindows XP
Language7 languages (EN, FR, JP, DE, ES, CN, KR)
Add-InRequires Excel
Available for MacNo, requires Parallels Emulation
Price includes 1st year maintenanceNo
Requires other Software?Requires Microsoft Excel to run
Scripting SupportBuilt In
SimulationMonte Carlo
VBA SupportBuilt In
CSV SupportYes
XML SupportYes
Distribution FittingBuilt In
User Defined DistributionsYes
Distribution Gallery22 Base distributions + Advanced Custom Parameters
Monte Carlo SamplingYes
Latin HyperCube SamplingYes
Process Capability (6 Sigma)Yes
Sensitivity AnalysisYes
Tornado AnalysisYes
Precision ControlYes
Probability calculations functionsYes
Correlation MethodsNormal Copula Only (Iman- Conover)
SIP Math SupportCrystal Ball is SIPMath compatible because it allows for sequential sampling of datasets (SIPs). SIP Libraries can be exported using a 3rd Party Macro.
Decision TreesWe recommend : Palisade PrecisionTree
Stats Tools3rd party option. We recommend Minitab, Analyse-it and Palisade StatsTools
MS Project SupportRequires free Crystal Ball Project Macro to be installed
ChartingBuilt In
Charts can be customizedYes
Automated ReportingYes
Multi-Core SupportYes
Developper KitYes
Example ModelsYes
Network Licensing AvailableNo
Data Base Integration30+ Data Sources with CDATA Connectors
Supported DBsStandard ODBC sources from Excel + 3rd party connectors
User Defined Distribution LibraryDistributions can be generated and saved to shared network drive and can be made available to other Crystal Ball users on the network
Linear Optimization MethodsYes
Non-Linear Optimization MethodsYes
Requirements / Soft Constraintsyes
Max RequirementsUnlimited
Max Decision VariablesUnlimited
PSI supportyes
Solution Filteringyes
Efficient Frontieryes
Scenario Analysis SupportAbility to create stochastic decision matrices using Decision Optimizer
Convergence Testingyes
Genetic Algorithimsyes
Ranges for Decision Variablesyes
Main Solver EngineOptQuest
Optimize multiple statisticsOptimization can be done on 11 different statisics (Mean, Variance, Standard Deviation, Skewness, Kurtosis, Percentile, Min/Max, Mode, Range, Coef. Variation, Probability, Certainty ) + 15 SigSigma Capability Metrics
Optimization Goal TypesMinimize, Maximize & Set Target
Static Optimization Supportyes
Dynamic Optimization Supportno
Stochastic Optimization Supportyes
Time Series as distributionsYes
Time Series FittingYes
Time Series Methods5 Non-Seasonal Methods + 6 Seasonal Methods, Complete ARIMA (1500 Models) and Stochastic Multiple Linear Regression
Multiple Linear RegressionStochastic Linear Regression (Forecast Independent Variables and recombine into a simulated dependant variable using the regression equation)
Seasonal MethodsSeasonal Multiplicative, Seasonal Additive, Holt-Winter's Additive, Holt-Winter's Multiplicative, Damped Trend Additive, Damped Trend Multiplicative
Non-Seasonal MethodsDouble Moving Average, Single Exponential Smoothing, Double Exponential Smoothing, Single Moving Average, Damped Trend
GBM SupportNo
Cubic SplineFor Outlier Adjustments. Option can be set to neighbour interpolation also
Heteroscedastic ModelsNo
ARIMA SupportYes, Full ARIMA Model (1331 Non-Seasonal + 27 Seasonal Methods)
Data SensoringOutlier Detection Methods: Mean and Standard Deviation, Median Absolute Deviations, Interquartile Deviation
Time-Series Event SupportYes
Define Time SeriesNo
Markov ChainsNo
Automatic Data TransformYes
Manual Data Transform MethodsNo
Manual DeseasonalizationNo
Manual DetrendingNo
Visualize Simulated OutputYes
Exception ReportingYes
Time Series Scenario AnalysisNo
Error MeasuresRMSE, MSE, MAD, MAPE, Theil's U, Durbin-Watson
Time Series Fit CriteriaBIC, AIC, RMSE, MSE, MAD, MAPE, Theil's U, Durbin-Watson
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