discussion

Instructions

DQ 3.1:  Risk Software Simulation and the Modeling of Risk Variables:  a 2 point discussion of the case of your choice.As we explore the many tools and quantitative analysis processes available to Project Managers, probability analysis and calculating risks becomes paramount. The field of Risk Analysis emerged from the insurance industry, which utilized probabilities for over a century to calculate risks over populations, demographic sectors, and categories of accidents, project risk conditions, etc.  This week, you will be introduced to @Risk software and review one case on the company website.  You do not need this software, only to analyze one case of your choice:  http://www.palisade.com/cases/?caseNav=byIndustry Please click on one of the 'Case Studies by Industry' tab and read a case that you select carefully. Then post your 2-paragraph discussion on how such a tool might be utilized in the 'sector' of your professional industry (construction; IT; defense; environmental; academic; manufacturing; transportation, etc.) to aide in calculating or forecasting risk factors. Do not 'cut and paste' from the web site: review the methods in your own words. DQ 3.2: In order to provide you practice with actually performing a Monte Carlo analysis, we have made Crystal Ball software available to you. (See Access to Microsoft Project and Crystal Ball link under Table of Contents in Content.)  Click here for a video that shows you in eight simple steps how to access this software and complete the Monte Carlo analysis for the case study whose link is below.Click here for the short case study that you should complete as part of this discussion.The case study is based on construction project risks which are identified in the Mitigation of Risk in Construction: Strategies for Reducing Risk and Maximizing Profitability (McGraw-Hill, 2011) reading listed under Session 3. Your discussion response should explain how you arrived at the conclusion referred to in the case and should include the cumulative probability distribution chart (or screenshot of it).

Answer