MSCI 609
MSCI 609
QUANTITATIVE DATA ANALYSIS
PROJECT PROPOSAL
Submitted by,
Sumithra Pandiaraj(20540918)
Syed Ibrahim(20520662)
Ekta Dua(20527454)
Risks and uncertainties are inherent in construction projects and if neglected these risks often lead to project cost and time overruns. To enable successful projects, companies follow a structured risk management process. The high complexity of the project demands for computer based tools. We will be examining and evaluating how contractor experts manage risks during the tendering process for large scale infrastructural projects. Our aim is to provide information that will aid to improve risk management support tool in the studied company. The improvements are based on an analysis of behavioral practices and attitudes in a project tendering team and by performing a detailed risk management study of one major infrastructural contractor. The methodology is based on a broad literature review of risk management in construction and the company’s internal documents and policies. By using the Monte Carlo simulation technique, simulation of risks in completed infrastructural projects will be performed.
This project will involve the performance of Monte Carlo simulations on two accomplished infrastructural projects. A Monte Carlo simulation is a problem solving technique used to approximate the probability of certain outcomes by running multiple trial runs, called simulations, using random variables. The simulation will generate both a probability and a range of the outcome. Two projects were selected to increase the reliability by minimizing random errors (increasing sample size). The input data used in the simulation will be collected in two methods. In the first method, data will be collected directly from the documented risk budget. In the second simulation, the accessible data from the risk budget will be complemented by estimations by the two people involved in the specific project.
Here’s an
QUANTITATIVE DATA ANALYSIS
PROJECT PROPOSAL
Submitted by,
Sumithra Pandiaraj(20540918)
Syed Ibrahim(20520662)
Ekta Dua(20527454)
Risks and uncertainties are inherent in construction projects and if neglected these risks often lead to project cost and time overruns. To enable successful projects, companies follow a structured risk management process. The high complexity of the project demands for computer based tools. We will be examining and evaluating how contractor experts manage risks during the tendering process for large scale infrastructural projects. Our aim is to provide information that will aid to improve risk management support tool in the studied company. The improvements are based on an analysis of behavioral practices and attitudes in a project tendering team and by performing a detailed risk management study of one major infrastructural contractor. The methodology is based on a broad literature review of risk management in construction and the company’s internal documents and policies. By using the Monte Carlo simulation technique, simulation of risks in completed infrastructural projects will be performed.
This project will involve the performance of Monte Carlo simulations on two accomplished infrastructural projects. A Monte Carlo simulation is a problem solving technique used to approximate the probability of certain outcomes by running multiple trial runs, called simulations, using random variables. The simulation will generate both a probability and a range of the outcome. Two projects were selected to increase the reliability by minimizing random errors (increasing sample size). The input data used in the simulation will be collected in two methods. In the first method, data will be collected directly from the documented risk budget. In the second simulation, the accessible data from the risk budget will be complemented by estimations by the two people involved in the specific project.
Here’s an