CRYSTALL BALL

Training Syllabus:

CRYSTALL BALL

OVERVIEW:

In this course, you will learn to perform spreadsheet modeling and analysis using Crystal Ball Standard Edition. You will learn the basics of Monte Carlo simulation, tornado analysis, and steps to develop Crystal Ball models. A strong emphasis is placed on gaining insight from simulation results and understanding the best ways to present findings to peers, management, or clients. You will learn to develop advanced Crystal Ball models, expedite the model-building process, and apply the analytical tools of Crystal Ball Professional Edition. You will cover advanced topics, including optimization and time-series forecasting, advanced assumptions, forecast options, and precision controls. The emphasis in the second half of this course is on learning to make optimal decisions by using the combined power of Crystal Ball.

WHAT YOU’LL LEARN:

• Modeling and simulations
• Start Crystal Ball and access resources
• Crystal Ball probability distributions
• Define assumptions
• Correlate assumptions
• Analyze and present simulation results
• Analyze data with Crystal Ball tools
• Set advanced options for assumptions and forecasts
• Manipulate simulation controls
• Optimize decisions with OptQuest and analyze solutions
• Perform time series forecasting with Predictor

WHO SHOULD ATTEND THIS TRAINIG?:

Business analysts and end users

TRAINING MATERIAL OUTLINE:

1. Modeling and Simulation

• Oracle’s Enterprise Performance Management System
• Model Basics
• Simulation Basics
• Monte Carlo Simulations
• Crystal Ball
• Model Development Process

2. Getting Started with Crystal Ball

• Setting Crystal Ball Start Preferences
• Welcome Dialog Box
• Basic Crystal Ball Terminology
• Crystal Ball Ribbon
• Additional Resources for Crystal Ball

3. Examining Probability Distributions

• Probability Distributions
• Basic Distribution Statistics
• Viewing Distribution Types in the Distribution Gallery
• Properties of Crystal Ball Distributions
• Commonly Used Crystal Ball Distributions

4. Assumptions

• Data-Based Assumptions through Distribution Fittings
• Data-Based Assumptions with Custom Distributions
• Expert-Based Assumptions
• Referencing Cells for Parameter Values

5. Forecasts, Running Simulations, and Analyzing Results

• Forecasts
• Running Simulations
• Analyzing Forecast Charts
• Viewing Other Charts with Forecast Data
• Saving and Loading Forecast Results
• Editing Crystal Ball Data

6. Correlating Assumptions

• Importance of Correlating Assumptions
• Rank Correlation Method
• Crystal Ball Options for Correlating Assumptions
• Defining Correlations by Modifying Assumption Definitions
• Adjusting Correlation Coefficients During Simulations

7. Creating Reports

• Crystal Ball Reports
• Generating Reports
• Extracting Data to Excel

8. Determining Assumptions with Tornado and Spider Charts

• Considering Assumptions
• Tornado and Spider Charts
• Tornado Charts Versus Sensitivity Charts
• Creating Tornado and Spider Charts
• Examining Tornado Charts
• Examining Spider Charts

9. Working with Multiple Assumptions

• Batch Fitting Probability Distributions
• Correlating Multiple Assumptions with Correlation Matrices

10. Setting Advanced Options for Assumptions

• Building Distributions with Alternate Parameters
• Truncating Assumption Distributions
• Creating Distribution Functions
• Publishing and Subscribing to Distributions
• Customizing the Distribution Gallery

11. Setting Advanced Options for Forecasts

• Automatically Extracting Forecast Statistics
• Adding Marker Lines to Forecast Charts
• Fitting Distributions to Forecast Charts
• Filtering Forecast Results

12. Working with Simulation Controls

• Setting Precision Control Preferences
• Setting Sampling Preferences
• Setting Run Mode Preferences
• Selecting Options for Simulation Statistics

13. Optimizing Decisions with OptQuest

• Optimization
• OptQuest
• Optimizing Decision Variables
• Analyzing OptQuest Results
• OptQuest Performance Best Practices
• Performing Efficient Frontier Analysis

14. Forecasting with Predictor

• Crystal Ball Predictor
• Creating Time Series Forecasts
• Performing Linear Regressions

VENUE : Kagum Group Hotel Bandung (Golden Flower, Banana Inn, Serela, Gino Feruci), Amaroossa Hotel, Noor Hotel, Grand Setiabudi Hotel, dll

TRAINING DURATION :  3 days

TRAINING TIME :

INVESTMENT PRICE/PERSON :

1. Rp. 6.500.000/person (full fare) or
2. Rp. 6.250.000/person (early bird, payment 1 week before training) or
3. Rp. 5.950.000/person (if there are 3 persons or more from the same company)

FACILITIES FOR PARTICIPANTS :

1. Training Module
2. Flash Disk contains training material
3. Certificate
4. Stationeries: NoteBook and Ballpoint
5. T-Shirt
6. Backpack
7. Training Photo
8. Training room with full AC facilities and multimedia
9. Lunch and twice coffeebreak everyday of training
10. Qualified instructor

Recommendation: Participants should bring a laptop for practice session.