Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2

Earned Value Management Related Abstracts

2 Cost Overruns in Mega Projects: Project Progress Prediction with Probabilistic Methods

Authors: Yasaman Ashrafi, Stephen Kajewski, Annastiina Silvennoinen, Madhav Nepal


Mega projects either in construction, urban development or energy sectors are one of the key drivers that build the foundation of wealth and modern civilizations in regions and nations. Such projects require economic justification and substantial capital investment, often derived from individual and corporate investors as well as governments. Cost overruns and time delays in these mega projects demands a new approach to more accurately predict project costs and establish realistic financial plans. The significance of this paper is that the cost efficiency of megaprojects will improve and decrease cost overruns. This research will assist Project Managers (PMs) to make timely and appropriate decisions about both cost and outcomes of ongoing projects. This research, therefore, examines the oil and gas industry where most mega projects apply the classic methods of Cost Performance Index (CPI) and Schedule Performance Index (SPI) and rely on project data to forecast cost and time. Because these projects are always overrun in cost and time even at the early phase of the project, the probabilistic methods of Monte Carlo Simulation (MCS) and Bayesian Adaptive Forecasting method were used to predict project cost at completion of projects. The current theoretical and mathematical models which forecast the total expected cost and project completion date, during the execution phase of an ongoing project will be evaluated. Earned Value Management (EVM) method is unable to predict cost at completion of a project accurately due to the lack of enough detailed project information especially in the early phase of the project. During the project execution phase, the Bayesian adaptive forecasting method incorporates predictions into the actual performance data from earned value management and revises pre-project cost estimates, making full use of the available information. The outcome of this research is to improve the accuracy of both cost prediction and final duration. This research will provide a warning method to identify when current project performance deviates from planned performance and crates an unacceptable gap between preliminary planning and actual performance. This warning method will support project managers to take corrective actions on time.

Keywords: Simulation, Project Management, risk analysis, Earned Value Management, Cost Forecasting, Project Control

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1 Empirical Study of Correlation between the Cost Performance Index Stability and the Project Cost Forecast Accuracy in Construction Projects

Authors: Amin AminiKhafri, James M. Dawson-Edwards, Ryan M. Simpson, Simaan M. AbouRizk


Earned value management (EVM) has been introduced as an integrated method to combine schedule, budget, and work breakdown structure (WBS). EVM provides various indices to demonstrate project performance including the cost performance index (CPI). CPI is also used to forecast final project cost at completion based on the cost performance during the project execution. Knowing the final project cost during execution can initiate corrective actions, which can enhance project outputs. CPI, however, is not constant during the project, and calculating the final project cost using a variable index is an inaccurate and challenging task for practitioners. Since CPI is based on the cumulative progress values and because of the learning curve effect, CPI variation dampens and stabilizes as project progress. Although various definitions for the CPI stability have been proposed in literature, many scholars have agreed upon the definition that considers a project as stable if the CPI at 20% completion varies less than 0.1 from the final CPI. While 20% completion point is recognized as the stability point for military development projects, construction projects stability have not been studied. In the current study, an empirical study was first conducted using construction project data to determine the stability point for construction projects. Early findings have demonstrated that a majority of construction projects stabilize towards completion (i.e., after 70% completion point). To investigate the effect of CPI stability on cost forecast accuracy, the correlation between CPI stability and project cost at completion forecast accuracy was also investigated. It was determined that as projects progress closer towards completion, variation of the CPI decreases and final project cost forecast accuracy increases. Most projects were found to have 90% accuracy in the final cost forecast at 70% completion point, which is inlined with findings from the CPI stability findings. It can be concluded that early stabilization of the project CPI results in more accurate cost at completion forecasts.

Keywords: Earned Value Management, empirical study, cost performance index, final project cost

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