Risk Management & Resilience – Identifying and Monitoring Low Probability/High Impact Risks – Hine and Rewey

As P/PMs we have been taught to identify and track High Probability/High Impact risks, which is absolutely the correct thing to do. However, many of us have been excluding similarly impactful risks from regular review simply due to an estimated low probability of occurrence. What if the probability estimate is incorrect? What if, as improbable as it was, the impact of such a risk becomes a reality? What is your get-well plan? Look for another job?

In this session we will discuss the importance and practical application of monitoring all risks, not just those considered High Probability and High Impact.

PMI Talent Triangle: Technical Project Management (Ways of Working)

Using data you (probably) already have to predict program risks – Kwame

The traditional way to manage risks on projects calls for the project team to (1) identify risks, (2) log them, (3) analyze them to determine their likelihood and impact to the project, and (4) formulate the appropriate responses. In this presentation, I will attempt to show a better approach to addressing steps 3 and 4. I will show how we can apply the binomial distribution function to data collected and correctly categorized in a risk & issue database to predict which risks are likely to occur, and subsequently, how to setup appropriate contingency using normal distribution functions (or where sample sizes are too small, unified scheduling method or estimation by analogy). I will also show some important applications of these concepts including using calculated project risk scores to determine project “riskiness” and how to apply appropriate management based on this.

PMI Talent Triangle: Technical Project Management (Ways of Working)