A COMPARATIVE MODEL OF EVM AND PROJECT’S SCHEDULE RISK ANALYSIS USING MONTE CARLO SIMULATION

International Journal of Information, Security and Systems Management

مقاله 6، دوره 2، شماره 2، شهریور 2013، صفحه 219-225   

نوع مقاله: Research Paper

نویسندگان

Bahar Mojabi¹؛ Reza Radfar²؛ Jamshid Nazemi³

¹M.A. Graduated of IT Management, Science & Research Branch, Islamic Azad University, Tehran, Iran

²Associated Prof. of Industrial Management, Science & Research Branch, Islamic Azad University, Tehran, Iran

³Faculty Member of Engineering Department, Science & Research Branch, Islamic Azad University, Tehran, Iran

چکیده

The issue of successful project management and control is of vital importance in today’s world. Although the time and cost of any project is determined in advance, paying less attention to an appropriate control and revision will result in a small chance of reaching those goals. The earned value management method that shows deviation of projects schedules and costs is of the good method for this problem however, it does not consider risks and uncertainties. Risk is defined as uncertainty of projects from internal and external environment. Identification and analysis of these risks with an appropriate and effective method is important. As regards conditions that risk imposes on project, the project will be deviated through its life cycle and managers should try to reduce deviations using corrective actions. However risk analysis is widely used in projects today, but this risk analysis is highly futuristic. The purpose of this research is designing a comparative model of earned value management and project schedule risk analysis that uses best corrective actions to improve the condition of the project. In this paper, earned value management indicators are calculated and analyzed and project completion time and delay factors are obtained by using a real project data. Also the project completion time and delay are investigated using project risk analysis and estimating activities completion time by doing Monte Carlo simulations. Finally by comparison of these two methods, a solution is proposed to improve the project condition.