Schedule Network Analysis Techniques

Schedule Network Analysis Techniques

Schedule Network Analysis Techniques

Schedule Network Analysis Techniques are used to produce Schedule. There are many Schedule Network Analysis techniques.

The first technique is called PERT. PERT stands for Program Evaluation and Review Technique. This is based on three time estimate for an activity. These three estimates are Optimistic estimate, Most Likely estimate and Pessimistic Estimate. For example, the Optimistic estimate to finish an activity can be say 10 days, where as the pessimistic estimate can be 20 days, meaning in any case, the activity would not take more than 20 days. The most likely estimate would be 15 days. This is the most probable days to finish the activity.

There are some other Network Analysis Techniques as well, which are used from time to time.

In Scenario Analysis technique, questions like What if a particular thing is changed on the project, would that produce a shorter schedule? are asked to produce a realistic schedule.

Another technique is Monte Carlo Analysis. In this method of estimating, a computer is used to simulate the outcome of a project, making use of the three point estimates. The three point estimates are optimistic, pessimistic and most likely estimate.

Some time Resource leveling is also used to produce a resource limited schedule. Resource leveling results is more stable no of resources used in the project.

Critical Chain Method is another technique to develop the Project Schedule that takes into account, both the activity and resource dependencies.

Critical chain method refers to a specific project management technique in which a schedule network analysis is used for the purposes of modifying an already determined and set project schedule to account for more limited than expected project financial resources. The critical chain method takes into a count a number of factors when being used in analysis. These factors primarily include those of deterministic probabilities as well as probabilistic approaches to schedule network analysis.

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