Qualitative vs Quantitative Risk Analysis

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The Qualitative Risk Analysis process prioritizes the identified risks evaluating the probability/likelihood that the events may occur, and their impact if these events occur, taking under consideration the response timeframe and the degree of risk tolerance. The results of the analysis can be illustrated in matrix where in one dimension a number of probability levels are classified based on likelihood, for example to “low-medium-high” categories, and a second dimension where a number of impact levels based on severity to “very low-low-medium-high-very high”; fifteen cells occur in this example from the possible combinations of probability-impact. Risks that score high in probability and impact will be prioritized; while the risks that rank medium in scale are to be monitored and the ones that score very low can be ignored and accepted (Meredith & Mantel, 2012; PMBOK,2013).

Qualitative risk analysis is an iterative process that should be repeated according to the project requirements. It also sets the base for further process of risks through Quantitative Analysis.

Strengths: Requires less time and fewer resources (cost effective) than the Quantitative Risk Analysis and directs focus on high-priority risks, reducing uncertainty levels.

Weaknesses: Low quality of risk information data (estimates) can produce invalid results. The risk information data collection can be more time-consuming and costly than estimated.

In the Quantitative Risk Analysis, critical and generally considerable risks are being assessed for numerical and more accurate results against project objectives. Methods employed to develop a probabilistic analysis of the project are:

• the FMEA (Failure Mode and Effect Analysis) where numerical values 1-10 are given to each of the risk measures -Severity, Likelihood and inability to Detect the risk- and the result of their multiplication gives the Risk Priority Number. In general, risks that score high are considered critical. FMEA limitations of results: In some cases where The Severity is high (10), Likelihood is low (1) and Inability to Detect is high (10), the low score can be overlooked.

• the “Sensitivity Analysis”, usually illustrated in tornado diagram, presents the risks with the most potential impact.

• -the “Decision Tree Analysis”, used to illustrate sequential events that may or not happen.

• the “Expected Monetary Value analysis”, calculates average result of possible scenarios that may or not happen, for example:

Employer A has a 50% probability in two years to promote and earn 50000$, a 30% probability of staying at the same position earn 28000$ and a 20% probability of demotion and earn salary 20000$.

EMV=(50%*50000)+(30%*28000)+(20%*20000)=25000+8400+4000=37400$

Employer B has a 10% probability in two years to promote and earn 90000$, a 65% probability to promote me and earn 34000$ and a 25% probability of demotion and earn salary 25000$.

EMV=(10%*90000)+(65%*34000)+(25%*25000)=9000+22100+6250=37350$

Based on the EMV, Employer A is a better choice than Employer B.

Strengths: Facilitates decision making, effective risk responses and contingency reserves. Prioritizes risks and allows identification of trends. Lessens uncertainty.

Weaknesses: Low quality of risk information data (estimates) can produce invalid results. Requires time and resources.

References

Meredith, J.R. & Mantel, S.J. (2012). “Project management: a managerial approach”. 8th ed. Hoboken, NJ: John Wiley & Sons, Inc.

Project Management Institute. (2013). “A guide to the project management book of knowledge (PMBOK® Guide)”. 5th ed. Newton Square, PA: Project Management Institute.