Understanding quantitative risk analysis

Question 1

What is quantitative risk analysis?

Answer 1

Quantitative risk analysis is the process of numerically estimating the impacts of risks on a project, allowing project managers to calculate contingency reserves.

Question 2

What is the key output of quantitative risk analysis?

Answer 2

The key output is the calculation of contingency funds or reserves needed to address potential risks.

Question 3

What technique is used for the reserve analysis?

Answer 3

Expected Monetary Value (EMV)

Question 4

What is the expected monetary value (EMV)?

Answer 4

EMV is a calculation that combines the probability of a risk occurring with its potential impact, expressed in monetary terms.

Question 5

How is EMV calculated?

Answer 5

EMV is calculated by multiplying the probability of occurrence (as a decimal) by the impact (in dollars).

EMV= Probability x impact

Question 6

What does a negative EMV indicate?

Answer 6

A negative EMV indicates a potential loss associated with a risk.

Postive (+) is a gain

Question 7

What is a decision tree in the context of risk analysis?

Quantitative analysis

Answer 7

A decision tree is a visual tool used to analyze decisions by mapping out different choices and their potential outcomes.

Question 8

When is it appropriate to use a decision tree?

Answer 8

A decision tree is appropriate when there are multiple options to consider, each with different probabilities and impacts.

Question 9

What are decision nodes in a decision tree?

Answer 9

Decision nodes represent points where a choice must be made between different options.

Question 10

How do you calculate the total impact for existing tools?

Answer 10

The total impact is calculated by adding the investment cost to the expected returns from different growth scenarios, weighted by their probabilities.

Question 11

What should project managers consider when using decision trees?

Answer 11

Project managers should consider the reliability of the probabilities and the complexity of the decision tree as more options are added.