If controlling cost is a high priority, then the impact would be severe. Impact scales can be a bit more problematic since adverse risks affect project objectives differently.įor example, a component failure may cause only a slight delay in project schedule but a major increase in project cost. Whereas another project may use more precise numerical probabilities (e.g., 0.1, 0.3, 0.5) These definitions vary and should be tailored to the specific nature and needs of the project.įor example, a relatively simple scale ranging from “very unlikely” to “almost certainly” may suffice for one project. ![]() The quality and credibility of the risk assessment process requires that different levels of risk probabilities and impacts be defined. If so, then it would be wise for that organization to be proactive and mitigate this risk by developing incentive schemes for retaining specialists and/or engaging in cross-training to reduce the impact of turnover. The risk a project manager being struck by lightning at a work site would have major negative impact on the project, but the likelihood is so low it is not worthy of consideration.Ĭonversely, people do change jobs, so an event like the loss of key project personnel would have not only an adverse impact but also a high likelihood of occurring in some organizations. It is important to consider such consequences when setting contingencies since, as would be expected, low probability, high impact risks require greater contingency than likely, low impact risks.Simply stated, risks need to be evaluated in terms of the likelihood the event is going to occur and the impact or consequences of its occurrence. Indeed, the effect of low probability, high-impact risks will be quite different from that of high probability, low-impact risks, even though individually the risks can the same product term (impact x probability). The correct treatment of risk requires both the impact and probability dimensions to be considered, and that focusing attention on those risks ranked as ‘riskiest’ by a multiplied figure of these two dimensions is dangerous. Unfortunately much risk analysis involves going through the motions to assign numbers without actually doing much thinking about what lies under the hood. Some advise caution, concluding risk matrices do not necessarily support good (e.g., better-than-random) risk management decisions, while others have described the PIM approach as hiding more than it reveals and that it can be a dangerous waste of time. While risk matrices are viewed by some as useful for ranking risk in order of significance (the bigger the number, the greater the risk), it can be irrational when applied blindly. A risk rating such ‘15’ will have no absolute meaning, (it would be inappropriate to conclude that such a rating is fifteen times more important than rating of 1). The example shows a risk that has been assessed as ‘medium probability’, ‘medium cost impact’, generating a ‘risk score’ of 15. Probability impact matrix with risk score The most common such measure is to multiply your measure of probability of the risk with your measure of the impact of the risk as shown below: ![]() Risk Managers are assumed to be at the leading edge of their profession if they provide quantitative measures of both probability and impact, and combine them to give an overall measure of risk.
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