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Event chain methodology is an uncertainty modeling and schedule network analysis technique that is focused on identifying and managing events and event chains that affect project schedules. Event chain methodology is the next advance beyond critical path method and critical chain project management.
An activity (task) in most real life processes is not a continuous uniform procedure. Tasks are affected by external events, which transform an activity from one state to another.
One of the important properties of an event is the moment when an event occurs during the course of an activity. This moment, when an event occurs, in most cases is probabilistic and can be defined using statistical distribution.
Events can cause other events, which will create event chains. These event chains can significantly affect the course of the project. For example, requirement changes can cause an activity to be delayed. To accelerate the activity, the project manager allocates a resource from another activity, which then leads to a missed deadline. Eventually, this can lead to the failure of the project.
Once events and event chains are defined, quantitative analysis using Monte Carlo simulation can be performed to quantify the cumulative effect of the events. Probabilities and effects of risks are used as input data for Monte Carlo simulation of the project schedule. In most real life projects, it is necessary to supplement the information regarding the uncertainties expressed as an event, with distributions related to duration, start time, cost, and other parameters.
The single events or the event chains that have the most potential to affect the projects are the “critical events” or “critical chains of events.” By identifying critical events or critical chains of events, we can mitigate their negative effects. These critical chains of events can be identified by analyzing the correlations between the main project parameters, such as project duration or cost, and the event chains.
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