Applied Decision Making Essay Example
Decision Making Free Essay Example
Descriptive Models seeks to describe the relationships between phenomena and provide the information that can be used for their further evaluation while prescriptive models seek to determine an optimal policy.
Data tables gives a summary of the impacts of one or two inputs on a specific output while the excel scenario manager allows one to create scenarios. Scenarios are set of values that are normally saved and can be automatically substituted on the worksheet. One may also require to use goal seek in cases where the result that is needed from a formula is known but one is not sure on the input vale that the formula needs to get the known result.
In cases where an optimal solutions are needed to optimization formulated as spreadsheet models the solver can be used. It is also possible to incorporate certain uncertainties into the decision models by specifying the probability distributions fro uncontrollable inputs by generating random variants using samples from the probability distributions.
Risk analysis can be described as an approachfor developing a comprehensiveunderstanding and awareness of the risk associated with any particular variable of interest. Such variables can be in the form of payoff measure, cash flow profile or a macro economic forecast. Monte Carlo contribution of “Monte Carlo Simulation” is a process that allows the repeated generation of inputs to a decision model based on sampling from their assumed probability distributions. The outputs are then calculated and the results analyzed. The distributions of the output variables are normally used to determine the likelihood of achieving certain output values. With a better understanding of such distributions, one is able to assess risks in the process of decision making.
To develop a spreadsheet one therefore needs to define the assumptions for certain variables which give the probability distribution that describe the uncertainty. One then proceeds to identify the output focus of interest/forecast cells. This if followed by setting the number of trials and other run preferences. The simulation can consequently be run and the results interpreted.
Note that in Crystal ball, the decision variables are the variables that are normally specified and can be changed by the user while the focus cells are the output variables of interest. Assumptions are the uncertain inputs.