All projects, no matter how meticulously planned, are exposed to the effects of risk. While you may not be able to predict the future with total certainty, there is a framework you can build to mollify any nasty surprises you might face during a project.
We are pleased to introduce Safran Risk 7.2, which introduces a range of new features and changes to our powerful project risk analysis software.
Safran Risk has chosen a fundamentally different approach to measuring uncertainty and has created a program with the capability to capture multiple levels of uncertainty and risk for individual projects and gain key insight into the impact of each individual factor. This gives project managers confidence in their assessment of projects with various risk factors and enables them to present accurate estimates of a projected project. Watch the video below to see examples of a real life project with various uncertainties using the risk register in Safran Risk.
Schedule Risk Analysis has developed over many years into a mature discipline with its own set of tools and techniques. However, projects still fail to meet their objectives despite the principle that schedule risk analysis should contribute to success. Adequately modeling risk and uncertainty is a task project teams face every day, often without the right processes to measure both with confidence.
In project intensive organizations, such as EMAS, work is fluid and dynamic – introducing a need for higher emphasis on readiness no matter the situation. Jamie Marzonie, a Senior Risk Specialist at EMAS AMC, discusses the importance of managing schedules and quantities of risk, and how Safran’s Integrated Risk Modeling can ensure projects are delivered on time and on budget.
All projects experience unexpected events that can impact their objectives in the form of loss or gain, and the extent of uncertainties and risks vary according to the size and complexity of projects. Uncertainty, however, is an abstract concept and many project managers lack the suitable tool to accurately define uncertainty for effective analysis.