Five Ideas: Predictive Modeling
What's the deal with Monte Carlo and Oracle Crystal Ball?
June 2009
“[Oracle’s] Crystal Ball can run 10,000 different Monte Carlo simulations within two or three minutes and give business managers the probabilities of the success of different scenarios for maximizing profits or customer service. Companies can pick the scenario that represents the least risk and the biggest payoff." —Harry Ghuman, Oracle’s group vice president for the Oracle Insight program and industry strategy
“With the Monte Carlo method, you use a computer to generate many thousands of random scenarios. It calculates thousands of possible outcomes, adds them all up, and gives a spread of all the possible outcomes and their respective probabilities in a histogram. Of course, as with any model, Monte Carlo simulations depend on the inputs. You have to keep checking against reality...but...Monte Carlo simulations, when tested scientifically against real-life observation, consistently outperform alternative methods of risk assessment."—Douglas Hubbard, CEO of Hubbard Decision Research and author of How to Measure Anything: Finding the Value of Intangibles in Business
“Most products take users only to the point of being able to see the possibilities of a given situation. They might refine things to the point of a best-case, worst-case, and most likely scenario, but that's as far as they get. These methods give you possibilities but not probabilities. Crystal Ball takes you much farther forward, allowing you to refine scenarios to the point of making educated decisions." —Jim Franklin, vice president and general manager of Oracle's Crystal Ball
“One of the biggest benefits of building a simulation model is that you have to study the inputs so carefully and understand the problem so well you may not even have to run the model." —John Charnels. senior vice president in Enterprise Stress Testing at Bank of America and author of Financial Modeling with Crystal Ball and Excel
“When a Monte Carlo tool runs a simulation, it also analyzes the relationships between inputs and outputs to determine which inputs have the greatest impact on performance. This sensitivity analysis tool can help manufacturers to identify and understand which process steps are most critical to achieving the desired level of quality in the final product, such as cycle time and defects letting them know where to insert the desired controls."—John Danese, director of Life Sciences Product Strategy and Fred Ciochette, solutions specialist, Oracle
