Risk management is a broad term, the application of which can vary in the extreme depending on the field in question. For instance, many of the tales told about the 2008 financial disaster reference disenfranchised or disemboweled risk departments within organizations such as AIG and Merrill Lynch.
The field of international relations has its own take on risk management. Does anyone else remember long, languid afternoons in the summertime playing RISK?
In the world of project management, risk is one of the process areas considered for every project. This is captured in the PMBOK, the most accessible text, and the one that comes closest to the risk management applied in construction management. Last year, I did a presentation with some of PMA’s construction risk experts and Steve Farkus, P.E, PMP, of the U.S. Army Corps of Engineers, for some of the thousands of project managers employed by the Corps. Our goal was to give an overview of the application of qualitative and quantitative risk analysis in construction. Typically, this takes the form of a qualitative gathering and ranking of risks, which leads to a quantitative analysis of the riskier risks in the risk register (to put it rather alliteratively). Here is a copy of the PowerPoint we presented in Long Beach.
For construction projects, the quantitative portion of risk is usually broken into cost and schedule analysis. The process is similar for both. I’ll focus on schedule risk analysis, since that is the area in which I have more familiarity.
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Having identified the most potentially disruptive risks through the qualitative risk process, now we want to start assigning some numbers to the potential risks to determine what impact they could have on the duration of the deterministic schedule. We go through a process of “ranging” individual activities on the schedule that might be impacted by a risk. The ranging process is usually done in collaboration with subject matter experts and the project team. We talk about how a risk might extend the duration of an activity if it becomes active. In a schedule where logical ties enforce relationships, a change in the duration of one activity can have a ripple effect throughout the schedule. The typical approach would be to add an Optimistic, Pessimistic, and most likely, Duration assessment for each activity we want to risk on the schedule.
Having created a logically-tied deterministic schedule with ranging for activities, now we can perform a statistical modeling process against the schedule in order to determine the statistical probability of completing the schedule on any given date. The process is most commonly done with aMonte Carloanalysis, although recently, Latin Hypercube has also been applied. Each of these methods relies on using statistics to generate “realizations” of the schedule. The process randomly selects a duration for each activity in the network based on the previous ranging exercise. Each realization is, in essence, a snapshot of a potential outcome for the schedule if certain risks activate and others do not. After many realizations (around 1000 for most of the schedules we work with), we achieve convergence. Convergence is the point at which the realizations have reached the full potential of distributions and at which further realizations will typically duplicate previous outcomes.
It is a source of continuous amazement to me that this works, which is to say that, when properly performed, the project team can really produce an accurate probability forecast for the project finishing on the deterministic date. It kind of reminds me of what it’s like to watch an airliner take off. Intellectually, I understand the physics of lift, and how the plane takes off, but it still amazes me every time I see it happen.