This preview shows page 1. Sign up to view the full content.
Unformatted text preview: tend to have more uncertainty. .5 Data precision. Precision describes the extent to which a risk is known and understood. It measures the extent of data available, as well as the reliability of data. The source of the data that was used to identify the risk must be evaluated. .6 Scales of probability and impact. These scales, as described in Section 126.96.36.199, are to be used in assessing the two key dimensions of risk, described in Section 188.8.131.52. .7 Assumptions. Assumptions identified during the risk identification process are evaluated as potential risks (see Sections 184.108.40.206 and 220.127.116.11). 11.3.2 Tools and Techniques for Qualitative Risk Analysis .1 Risk probability and impact. Risk probability and risk consequences may be described in qualitative terms such as very high, high, moderate, low, and very low. Risk probability is the likelihood that a risk will occur. Risk consequences is the effect on project objectives if the risk event occurs. These two dimensions of risk are applied to specific risk events, not to the overall project. Analysis of risks using probability and consequences helps identify those risks that should be managed aggressively. 134 NAVIGATION LINKS ACROYMNS LIST ACRONYMS LIST ACROYMNS LIST A Guide to the Project Management Body of Knowledge (PMBOK Guide) 2000 Edition 2000 Project Management Institute, Four Campus Boulevard, Newtown Square, PA 19073-3299 USA Chapter 11--Project Risk Management .2 Probability/impact risk rating matrix. A matrix may be constructed that assigns risk ratings (very low, low, moderate, high, and very high) to risks or conditions based on combining probability and impact scales. Risks with high probability and high impact are likely to require further analysis, including quantification, and aggressive risk management. The risk rating is accomplished using a matrix and risk scales for each risk. A risk's probability scale naturally falls between 0.0 (no probability) and 1.0 (certainty). Assessing risk probability may be difficult because expert judgment is used, often without benefit of historical data. An ordinal scale, representing relative probability values from very unlikely to almost certain, could be used. Alternatively, specific probabilities could be assigned by using a general scale (e.g., .1 / .3 / .5 / .7 / .9). The risk's impact scale reflects the severity of its effect on the project objective. Impact can be ordinal or cardinal, depending upon the culture of the organization conducting the analysis. Ordinal scales are simply rank-ordered values, such as very low, low, moderate, high, and very high. Cardinal scales assign values to these impacts. These values are usually linear (e.g., .1 / .3 / .5 / .7 / .9), but are often nonlinear (e.g., .05 / .1 / .2 / .4 / .8), reflecting the organization's desire to avoid high-impact risks. The intent of both approaches is to assign a relative value to the impact on project objectives if the risk in question occurs. Well-defined scales, whether or...
View Full Document
- Fall '13
- The American