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This lesson focuses on performing quantitative risk analysis. This deals with numbers: risk, cost and possible impact. [toggle_content title="Transcript"] The next process is perform quantitative risk analysis. Quantitative deals with numbers. Perform quantitative risk analysis creates project updates. The inputs are the risk management plan, cost management plan, schedule management plan, risk register, enterprise environmental factors and organizational process assets. Once again the risk management plan is going to tell you the methods and how to do quantitative risk analysis. Cost management plan is going to assess the risk dealing with numbers so the cost. Schedule management plan is going to provide you with schedule so you are going to be looking at risks that apply to time, your risk register has all your known risks, once again enterprise environmental factors and organizational process assets. The tools that are used are representation and data gathering techniques. You are going to be conducting interviews and you are going to try to figure out costs and time data by interviewing people to determine what those risks are and the impact on cost and time. Then you are going to try to model that data. Quantitative Risk Analysis and Modeling Techniques so it's going to be like be like Montecarlo. You are providing information to a computer software program that is going to run scenarios to figure out what the risk and cost impacts are and expert judgement. Quantitative risk analysis let's look at a Decision Tree Analysis, which is another way of doing it. This example is a decision to make a product locally or outsource. If you make it locally, it's going to cost the company, $500,000. If you outsource it, it is going to cost the company, $100,000. There is risk associated with that. If you make it locally there is a 90 percent that it is going to meet the quality needs to if you want to sell it. There is a 10 percent chance that it fails quality and you will be able to sell it at a reduced cost of $600,000. If its a success, its a million dollars in revenue. If it fails, its $600,000 dollars in revenue. Outsourcing its going to cost $100,000. There is a 50 percent chance that it succeeds and meets quality, and there is a 50 percent chance that it fails to meet quality. In this scenario, if it meets quality, your revenue will be a million dollars. If it fails, to meet the quality, it is $200,000. What does this information give us? If you notice there is four categories, and we are going to figure out what the profit is. Am taking a million dollars in revenue, and am subtracting what it cost so $500,000. That gives me $500, 000. I am multiplying it by 90 percent which is probability that will occur and am coming up with $450, 000. Price decision is also ten percent so am taking $600,000 which is revenue subtracting $500,000 which gives me $100,000 and am multiplying by ten percent. That will give me 10,000. If I add those two together, I get $460,000. That is my profit with the decision tree if I make it locally. That's the number I am looking at. Now if I am trying to determine if I should outsource, do the same thing down here. So am taking a million dollars which is revenue, I am subtracting 100,000 which is what it cost me. So I'm coming up with $900,000 and am multiplying it by fifty percent. This gives me $450,000. If it fails to meet quality, I can still sell it for $200,000 gives me 100,000 in profit multiplying that by fifty percent. That gives me $50,000 dollars. If I outsource, I come up with $500,000 potential revenue. That's how you use a decision tree. Do I make it locally or outsource. So running these numbers with what I have provided for percentage revenue and costs to give me profit, I will outsource cause this gives me $500,000 versus this gives me $460,000. [/toggle_content]