Transform your Microsoft Excel spreadsheets to get a credible picture of risk, create accurate predictive models, search for the best solution and maximise appreciation of the risks that you are facing. From Monte Carlo simulation to forecasting and optimisation, Crystal Ball software tools deliver. Crystal Ball is the industry-standard for oil, gas and mining company executives to analyse the uncertainties in their spreadsheet models.

Industry Example - Mining

The rapidly fluctuating price of minerals, increasing competition and volatile financial markets have placed the mining industry in a position of ever-increasing risk.

Crystal Ball

Crystal Ball is the easiest way to perform fast risk analysis and optimisation in your own spreadsheets. With one integrated toolset, you can use your own historical data to build accurate models, automate "what if" analysis to understand the effect of underlying uncertainty and search for the best solution or project mix.

Oracle Crystal Ball is the leading spreadsheet-based application for predictive modeling, forecasting, simulation, and optimization. It gives you unparalleled insight into the critical factors affecting risk. With Crystal Ball, you can make the right tactical decisions to reach your objectives and gain a competitive edge under even the most uncertain market conditions.

New Features in v11.1.2.2

Grouped Assumptions in Sensitivity Charts

You can group assumptions in a sensitivity chart to combine similar assumptions, such as grouping Monthly assumptions into a single Year assumption group. Use the Sensitivity menu in a sensitivity chart window.

Data Filtering When Fitting Distributions

When fitting distributions for assumptions, you can filter historical data to use only data values that fall within specified value ranges. Unused values are not permanently deleted, only discarded for the purpose of distribution fitting. Once used, filter settings are saved as global preferences and are used each time you select Filter data in the Fit Distribution dialog until you change the settings.

Parameter Edits When Fitting Distributions

A new setting in the Comparison Chart window enables you to edit parameters for assumptions created by distribution fitting. By default, a distribution of the accepted type with default parameters is created in the selected cell. If you select Edit after Accept, the Assumption dialog opens with the parameter entries taken from the chosen distribution. You can change the distribution parameters and save the modified assumption.

Expanded Distribution Parameters

The maximum number of trials allowed for binomial distributions and the maximum rate allowed for Poisson distributions have both been expanded to 1e9.

Predictor Parallelization

Predictor now uses multiple cores (CPUs) to process all the time series in historical data. Calculations are shared between all available cores, run in parallel, and the results are displayed much faster than before.

Localization into Additional Languages

The Crystal Ball user interface is now translated into French, German, Japanese, Portuguese, and Spanish. Documentation is not translated.


Crystal Ball Screenshot

Adding Probability to Risk Calculations

What is the likelihood of reaching a particular goal? What are the critical factors affecting risk? The answer to these and other common "what-if" scenarios can be determined by assigning probability to unknown variables. Excel can't handle the complexity of probability analysis, so you need a better tool: Crystal Ball.

Crystal Ball automates the cumbersome "what-if" process using Monte Carlo simulation, by applying a range of values or a probability distribution to each uncertain variable.

The program generates random values from within the defined probability ranges, and then recalculates the model literally hundreds or thousands of times, storing the results of each "what-if" scenario. This timesaving process alleviates having to manually enter different scenarios over and over again.

Monte Carlo Simulation
Calculates multiple scenarios of a spreadsheet model automatically. Frees users from the constraints of estimates and best-guess values.

Distribution Gallery
Provides an intuitive interface for selecting model input variables; includes 16 discrete and continuous distributions plus custom distribution. Simplifies the quantifying of risk, means you don't have to enter the distribution formula into Excel.

Categories of Distributions
Create predefined distributions, modify your existing distributions and organize them using custom categories. Create your own library of distributions, organized in categories. Re-use distributions from one project to the next.

Publish and Subscribe Feature for Categories
Publish categories and share with many users. Work as a team sharing models and data to get your work done faster.

Process Capability Features
Define spec limits (LSL, USL and Target) in your forecasts, calculate capability metrics and view simulation results and metrics together in one split-view chart. With capability metrics in Crystal Ball you simplify your workflow and better integrate simulation into your Six Sigma and Quality methodology.

Forecast Charts
Graphically display simulation results and statistics. Allows users to track and analyze thousands of possible outcomes; charts are interactive.

Split-View charts
View forecast charts, descriptive statistics and capability metrics side-by-side on the same chart. Enable up to 6 charts and tables in one view. One chart tells the whole story.

Sensitivity and Tornado Analyses
Two separate methods for identifying the most critical model input variables. Enable users to focus on high-risk model input variables.

Distribution Fitting
Uses historical data for defining assumptions. Can fit to continuous and discrete distributions. Allows users to customize model input variables based on real-world results.

Models dependencies between uncertain input variables. Provides more accurate modeling and forecasting.

Charting and Reporting
Automates report generation, includes the ability to overlay forecasts and to project trends through time. Creates clear analysis and presentation of all forecasts, improves communication with colleagues, management, and clients.

Precision Control
Provides advanced simulation capabilities. Increases simulation accuracy and flexibility; saves time.

Latin Hypercube Sampling
Alternative simulation method to Monte Carlo. Samples regularly across distribution, excellent for simulations with restriction on number of trials.

Data extraction
Exports data from Crystal Ball memory. Allows users to examine individual simulation results and transfer results to other software programs.

CB Tools
Macro-driven tools that use Crystal Ball; Includes scenario analysis, decision table, data analysis, tornado chart, correlation matrices, 2D-simulation, batch fit, and boot strap. Automates modeling processes with effortless and powerful tools.

CB Predictor
CB Predictor uses established forecasting methods to help identify and extrapolate the trends in your historical data. CB Predictor analyzes your data and produces insightful and accurate forecasts.

Crystal Ball and CB Predictor Developer Kits
The Crystal Ball and CB Predictor Developer Kits bring complete automation and control to these tools from within a Visual Basic for Applications (VBA) program or any other language outside of Excel that supports OLE 2 automation.

Microsoft Certification
Certified Excel macro provider. Eliminates security concerns.

Industry Examples of Crystal Ball

There are many industries that use Crystal Ball software. Crystal Ball is the tool chosen by more than 85% of the Fortune 500 companies. Like in the United States, Crystal Ball is the most popular choice in Australia and New Zealand to help improve spreadsheet modelling and risk analysis.

Mining Applications

The rapidly fluctuating price of minerals, increasing competition and volatile financial markets have placed the mining industry in a position of ever-increasing risk.

Oil & Gas Applications

Oil & Gas exploration deals with many unknowns, with high risk and uncertainty an inherent part of the oil and gas industry. The management of risk in oil and gas exploration has always been difficult.

Six Sigma and Process Improvement

Six Sigma is a set of practices originally developed by Motorola to systematically improve processes by eliminating defects. Motorola uses Crystal Ball in its Six Sigma Program.

Environmental Research

Crystal Ball is for anyone who uses spreadsheets and needs to forecast uncertain results. Environmental geologists, cost engineers, environmental scientists, hydrogeologists and project managers all rely on Crystal Ball.

Banking and Finance

To ignore the effects of uncertainty in your financial and business analyses means to potentially expose your organisation to unnecessary risk and potential failure.


Crystal Ball E-Newsletter - Freezing cells from simulation runs

The Freeze command lets you see the that effect certain cells have on the model while holding other assumptions to their spreadsheet values.

Crystal Ball E-Newsletter - How to obtain forecast value corresponding to a percentile directly

This edition focuses on the CB.GetForePercent Crystal Ball function. Instead of having to go to the Forecast Chart, you can now view the corresponding forecast value directly on the spreadsheet.

Crystal Ball Seminar - Example Models

All the exmaples models from the July 2012 Seminar Series around Australia

Mining, Oil and Gas - Drill Bit Replacement - Example Model

When drilling wells in certain types of terrain, the performance of a drill bit erodes with time because of wear. The problem is to determine the optimum replacement policy; that is, the drilling cycle between replacements.

Mining, Oil and Gas - Mine Project Valuation Using Monte Carlo Analysis - Example Model

A mining corporation is evaluating a small underground gold mining project containing an estimated one million ounces of gold.

Mining, Oil and Gas - Optimising the Growth Portfolio of Kumba Resources

The application and benefits of Monte Carlo simulation in optimising the growth portfolio of Kumba Resources, a diversified mining company based in South Africa.

Mining, Oil and Gas - Portfolio Optimisation applied to Acquisition Evaluation

This paper describes some of the lessons learnt in building a portfolio model of petroleum assets. The example is based on the evaluation of an acquisition opportunity, a setting which imposed its own constraints on the methodology.

Mining, Oil and Gas - Process Operating Costs with Applications in Mine Planning and Risk Analysis

This paper discusses techniques for estimating treatment plant operating costs, including identification of high impact cost areas and expected key cost variations year by year.

Six Sigma - Applying Crystal Ball to Transaction Process Analysis

Crystal Ball can be utilised to evaluate process steps for their full range of variation and assess the impacts of binary events. Results from the analysis provide better assessments cycle time variation than an average approach.

Six Sigma - Monte Carlo Simulation as Process Control Aid

Statistically designed experiments (DOEs) have become an essential tool in many fields of research because they can lead to rapid learning and optimisation in less time and with less cost.

Six Sigma - The Use of Monte Carlo Simulation in Production Modeling

Example of how Lockheed Martin uses Crystal Ball

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