Schedule updating and project control

Forecasting represents a core project management process.Estimates at completion in terms of cost and schedule provide essential data and advice to the project team in order to lead and control the project and implement suitable corrective measures.Project management can be seen as a process that starts from the definition of project scope and objectives and ends with the fulfillment of project requirements.As the Project Management Institute (2008) stated, the main phases involved in project management are: initiating, planning, executing, monitoring and controlling, and closing.In order to improve the forecasting process, a Bayesian model has been developed within the earned value management framework aiming to calculate a confidence interval for the estimates of both cost and schedule at the completion of the project.

Although the data records are related to the past, experts’ knowledge may help to forecast the future, in particular regarding the overall WR.In the following, the generic indices CPI and SPI(t) will be referred to the overall WC, while CPI will be referred to the overall WR.The process of calculating an estimate at completion is usually based on a deterministic approach that is suited to projects with a low uncertainty level (Fleming, 1992).The application of a statistical approach to EVM was first proposed by Lipke (2002b), who suggested applying control charts to project performance so as to determine upper and lower limits for estimate at completion (an analogous property was investigated by Christensen [1996]) as a way to improve project planning and control processes.A further study (Lipke, 2002a) demonstrated that the monthly values CPI are log-normally distributed.

The model has been tested in an oil and gas project.

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Schedule updating and project control introduction

Schedule updating and project control

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