Integrating Risk Assessment and Actual Performance for Probabilistic Project Cost Forecasting: A Second Moment Bayesian Model

被引:21
作者
Kim, Byung-Cheol [1 ]
机构
[1] Ohio Univ, Dept Civil Engn, Athens, OH 45701 USA
关键词
Bayesian; cost forecasting; cost risk; earned value management (EVM); project management;
D O I
10.1109/TEM.2015.2404935
中图分类号
F [经济];
学科分类号
02 ;
摘要
Forecasting the actual cost to complete a project is a critical challenge of project management, particularly for data-driven decision making in contingency control, cash flow analysis, and timely project financing. This paper presents a Bayesian project cost forecasting model that adaptively integrates preproject cost risk assessment and actual performance data into a range of possible project costs at a chosen confidence level. The second moment Bayesian (SMB) model brings more realism into project cost forecasting by explicitly accounting for inherent variability of cost performance, correlation between aggregated past and future performance, and the fraction of project completed at the time of forecasting. Functionally, the SMB model fully encompasses, as restrictive cases, two most commonly used index-based cost forecasting techniques in earned value management. The SMB model provides computationally efficient algebraic formulas to conduct robust probabilistic forecasting without additional burden of data collection or sophisticated statistical analysis. Numerical examples and simulation experiments are presented to demonstrate the predictive efficacy and practical applicability of the SMB in real project environments.
引用
收藏
页码:158 / 170
页数:13
相关论文
共 26 条
[1]  
Alshibani Adel, 2012, Proceedings of the 2012 Construction Research Congress, P545
[2]  
Anbari F.T., 2003, Project Management Journal, V34, P12, DOI [DOI 10.1177/875697280303400403, 10.1109/EMR.2004.25113]
[3]  
[Anonymous], 2003, Bayesian Data Analysis
[4]  
[Anonymous], 2011, PRACT STAND EARN VAL
[5]   Probabilistic forecasting of project performance using stochastic S curves [J].
Barraza, GA ;
Back, WE ;
Mata, F .
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2004, 130 (01) :25-32
[6]   A Bayesian Approach to Improve Estimate at Completion in Earned Value Management [J].
Caron, Franco ;
Ruggeri, Fabrizio ;
Merli, Alessandro .
PROJECT MANAGEMENT JOURNAL, 2013, 44 (01) :3-16
[7]  
Christensen D., 1993, Project Management Journal, V24, P37
[8]  
Fleming Q.W., 2010, Earned value project management, V4th
[9]  
GAO, 2009, GAO COST EST ASS GUI
[10]   A probabilistic framework for Bayesian adaptive forecasting of project progress [J].
Gardoni, Paolo ;
Reinschmidt, Kenneth F. ;
Kumar, Ramesh .
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2007, 22 (03) :182-196