SIMULATION USING CRYSTAL BALL. WHAT CRYSTAL BALL DOES? Crystal ball extends the forecasting capabilities of spreadsheet model and provide the information.

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Presentation transcript:

SIMULATION USING CRYSTAL BALL

WHAT CRYSTAL BALL DOES? Crystal ball extends the forecasting capabilities of spreadsheet model and provide the information that needs to become a more accurate, efficient, and confident decision maker. There are two main limitations in any spreadsheet analysis: 1.You can change only one spreadsheet cell at a time. As a result, exploring the entire range of possible outcomes is next to impossible; you cannot determine the amount of risk that impacts. 2.“What if” analysis always results in single-point estimates which do not indicate the likelihood of achieving any particular outcome. While single point estimate might tell you what is possible, but not what is probable.

Crystal ball overcomes both of these limitations: 1.We can describe a range of possible values for each uncertain cell in the spread sheet. Everything that is known about each assumption is expressed all at a once. 2.Using the process called Monte Carlo Simulation, crystal ball displays results in a forecast chart that shows the entire range of possible outcome and the likelihood of achieving each of them.

CRYSTAL BALL TOOLS Crystal ball tools are Visual Basic Program that extends the functionality of the program. They are: 1.Batch Fit – Automatically fits selected continuous probability distributions to multiple data series. 2.Bootstrap - Address the reliability and accuracy of forecast statistics. 3.Correlation Matrix Tool – Rapidly defines and automates correlations of assumptions.

4.Decision Table – Evaluates the effects of alternate decisions in a simulation model. 5.Tornado Chart – individually analyzes the impact of each model variable on a target outcome. 6.Two dimensional Simulation – Independently addresses uncertainty and variability using two – dimensional simulation.

When the values of two variables depend on each other in any way, then it is to be correlated in order to increase the accuracy of the simulation forecast results. There are two types of correlations: Positive correlations: Indicates that two assumptions increases or decreases together. Negative correlations: Indicates that an increase in one assumption results in a decrease in the other assumption. Correlation Matrix Tool