For example:the future cost of raw materialsfuture interest ratesfuture number of employees in a firmexpected product demandDecisions made using uncertain information often involve risk. Mgmt.Dealing with RandomnessMost real-world business situations today are probabilistic, but the decision models used to deal with them are deterministic.How to deal with randomness?Ignore itSimplify problem to make it analytically tractable, get solution, then ignore real-life complicationsFind a way to obtain an approximate solution to real-world problemsMonte Carlo SimulationMonte Carlo simulation is a method by which approximate solutions are obtained to realistic (and therefore complicated) problemsThis is in contrast to analytical methods, which obtain exact solutions to highly stylized problemsTradeoff between rigor and relevanceIntroduction to SimulationWhat is this? Y = f(X1, X2, …, Xk)Often, the values for one or more 'input' cells are unknown or uncertain This creates uncertainty about the value of the 'output' cellSimulation can be used to analyze these types of modelsRandom Variables & RiskA random variable is any variable whose value cannot be predicted or set with certainty.Many “input cells” in spreadsheet models are actually random variables. Project ManagementSession 9Crystal BallOPIM 5270Session 9 GoalsUnderstand why risk must be analyzedKnow pros / cons for three ways to analyze riskIdentify random variables in modelsKnow the four steps of a simulation processGenerate random numbers with Crystal BallUse the four steps of a simulation processExplain how Crystal Ball supports Proj.

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