Project risk management

Within project management, risk management refers to activities for minimizing project risks, and thereby ensuring that a project is completed within time and budget, as well as fulfilling its goals. Risk management activities are applied to project management. Project risk is defined by the Project Management Institute (PMI) as, "an uncertain event or condition that, if it occurs, has a positive or negative effect on a project’s objectives." Within disciplines such as operational risk, financial risk and underwriting risk management, the concepts of risk, risk management and individual risks are nearly interchangeable; being either personnel or monetary impacts respectively. However, impacts in project risk management are more diverse, overlapping monetary, schedule, capability, quality and engineering disciplines. For this reason it is necessary in project risk management to specify the differences (paraphrased from the U.S. "Department of Defense Risk, Issue, and Opportunity Management Guide for Defense Acquisition Programs"): Risk management: Organizational policy for optimizing investments and (individual) risks to minimize the possibility of failure. Risk: The likelihood that a project will fail to meet its objectives. A risk: A single action, event or hardware component that contributes to an effort's risk. An improvement on the PMI's PMBOK definition of risk management is to add a future date to the definition of a risk. Mathematically, this is expressed as a probability multiplied by an impact, with the inclusion of a future impact date and critical dates. This addition of future dates allows predictive approaches. Good project risk management depends on supporting organizational factors, having clear roles and responsibilities, and technical analysis. Chronologically, project risk management may begin in recognizing a threat, or by examining an opportunity. For example, these may be competitor developments or novel products. Due to lack of definition, this is frequently performed qualitatively, or semi-quantitatively, using product or averaging models.