Event chain methodology

Event chain methodology is an extension of quantitative project risk analysis with Monte Carlo simulations.

[1] Event chain methodology tries to mitigate the effect of motivational and cognitive biases in estimating and scheduling.

[3] Event chain methodology is an extension of traditional Monte Carlo simulation of project schedules where uncertainties in task duration and costs are defined by statistical distribution.

[4][5][6] For example, task duration can be defined by three point estimates: low, base, and high.

Defining uncertainties using statistical distribution provide accurate results if there is a reliable historical data about duration and cost of similar tasks in previous projects.

[7][8] Information about probabilities and impact of such events is easier to elicit, which improves accuracy of analysis.

This moment, when an event occurs, in most cases is probabilistic and can be defined using statistical distribution.

[11][12] The simplest way to represent these chains is to depict them as arrows associated with certain tasks or time intervals on the Gantt chart.

[13] Probabilities and impacts of risks assigned to activities are used as input data for Monte Carlo simulation of the project schedule.

[14] In most projects it is necessary to supplement the event based variance with uncertainties as distributions related to duration, start time, cost, and other parameters.

In Event chain methodology, risk can not only affect schedule and cost, but also other parameters such as safety, security, performance, technology, quality, and other objectives.

Monte Carlo simulation provides the capability, through sensitivity analysis, to identify single or chains of events.

During the course of the project, the probability and time of the events can be recalculated based on actual data.

Event chain methodology reduces the risk probability and impact automatically based on the percent of work completed.

Risk response plans execution are triggered by events, which occur if an activity is in an excited state.

Reallocation of resources can also occur when activity duration reaches a certain deadline or the cost exceeds a certain value.

Events can be used to model different situations with resources, e.g. temporary leave, illness, vacations, etc.