In decision making process ambiguity, variability and uncertainty are often faced. For this reason Risk Analysis is always part of any decision making process. Even if the access to information is unprecedented even then future can’t be predicted accurately. For this reason Monte Carlo simulation is used which provides all the possible outcomes of decisions, access the impacts of risks and allow better decision making under uncertain situations.
It is a computerized mathematical technique based on broad class of computer algorithms which allow people and organisations to calculate risks and hence helps in better decision making.
Monte Carlo Simulation can also be termed as a problem solving technique to calculate probability of outcomes by using random variables and multiple trials which are termed as simulations (Berg, 2004). Monte Carlo Simulation is used by professionals in engineering, medicine, physics, chemists, project management, manufacturing, research and development, environmental specialists, oil and gas and several business functions. This is a reflective report in which case study of Fennel Design Project of Laura Watson company is used to predict the demand of greeting cards.
The aim of the report is to speculate the situation of the Fennel Design project and also to provide a base for the companies experiencing these situations.
This report uses discrete data of continuous range In this report discrete data of continuous range is used. Example of discrete data is when a coin flips in air, it have two possibilities either head or tail. Whereas, a running engine might have many temperature changes at different time intervals which is an example of continuous data.
Laura Watson is a new company and so can also face these uncertainties as they don’t have any idea of when to produce, when to produce, supply and demand analysis and the situation which drives these factors. For this reason Monte Carlo Simulation is used to calculate predicted demand, risk analysis in order to provide company with useful information which then can be utilized to make timely decision making. This report is divided into three main parts.
In Monte Carlo Simulation we can take as many amounts of trials to get an accurate answer. But, in the given casestudy, business manager’s Alex and Laura took one thousand trials. Number of trials increases the profit probabilities and helps in getting close results and reduces the chances of risks. In this question we have to calculate the price of the cards and for this we used Descriptive Analysis Function in Microsoft Excel. This Function automatically calculates all statistical data like mean, median, mode and standard deviation. Whereas, in task two WHAT IF analysis helps us in getting the results within the given number of trials. It creates thee situations or results which are base case scenario, best case scenario and worst case scenario.
When the values of these situations are changed answer automatically changes. It is very helpful for managers in decision making. In task three risk simulation function and random functions are used which makes a balance between mean and standard deviation given in the projected demand. Rand command is used to calculate the cost of parts, random discreet method is used to. Variance Reduction is used to minimize non accurate profits. These all function enables to calculate price and predict risk. In this report every function is calculated independently to make the process easy to understand and clear. By using Monte Carlo Simulation we have calculated all the possible parameters required in the case study and also predicted the risk. It helps the managers to make quick and accurate decisions.
Bibliography
Berg, A. B. (2004). Markov Chain Monte Carlo Simulation and their Statistical Analysis. New Jersey: World Scientific.
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