Earned value project management: Improving the predictive power of planned value

Abstract Earned value project management (EVPM) is an effective tool for managing project performance. However, most studies on extensions and applications of EVPM concentrate on improving final cost and duration estimates rather than improving upon the use of planned value (PV) to predict earned value (EV) and actual cost value (AC). This study proposes a straightforward modeling method for improving the predictive power of PV before executing a project. By using this modeling method, this study develops EV and AC forecasting models for four case projects. Out-of-sample forecasting validation using mean absolute percentage error (MAPE) demonstrates that the proposed method improves forecasting accuracy by an average of 23.66% and 17.39%, respectively, for EV and AC. This improvement on PV's predictive power prior to project execution provides management with more reliable predictive information about EV and AC performance, allowing for effective proactive action to ensure favorable performance outcomes.

[1]  Jennifer A. Farris,et al.  Evaluating the Relative Performance of Engineering Design Projects: A Case Study Using Data Envelopment Analysis , 2006, IEEE Transactions on Engineering Management.

[2]  David S. Christensen.  Value Cost Management Report to Evaluate the Contractor's Estimate at Completion , 1999 .

[3]  Byung-Cheol Kim.  Dynamic Control Thresholds for Consistent Earned Value Analysis and Reliable Early Warning , 2015 .

[4]  W. Duncan.  A GUIDE TO THE PROJECT MANAGEMENT BODY OF KNOWLEDGE , 1996 .

[5]  Hung-Ming Chen,et al.  Visualized EVM system for assessing project performance , 2010 .

[6]  Denis F. Cioffi,et al.  Designing project management: A scientific notation and an improved formalism for earned value calculations , 2004 .

[7]  Mario Vanhoucke,et al.  A simulation and evaluation of earned value metrics to forecast the project duration , 2005, J. Oper. Res. Soc..

[8]  Michael R. Duffey,et al.  A model for effective implementation of Earned Value Management methodology , 2003 .

[9]  Christophe Bredillet,et al.  Earned value management insights using inferential statistics , 2008 .

[10]  William M. K. Trochim,et al.  An introduction to concept mapping for planning and evaluation. , 1989 .

[11]  L. M. Naeni,et al.  A fuzzy approach for the earned value management , 2011 .

[12]  Mario Vanhoucke,et al.  On the use of multivariate regression methods for longest path calculations from earned value management observations , 2016 .

[13]  Kym Henderson.  Earned Schedule: A Breakthrough Extension to Earned Value Theory? A Retrospective Analysis of Rea , 2003 .

[14]  F.T. Anbari,et al.  Earned Value Project Management Method and Extensions , 2003, IEEE Engineering Management Review.

[15]  Christine Nadel,et al.  Case Study Research Design And Methods , 2016 .

[16]  Ofer Zwikael,et al.  Prediction of project outcome The Application of statistical methods to earned value management and earned schedule performance indexes , 2009 .

[17]  Hrishikesh D. Vinod,et al.  “Generalization of the durbin-watson statistic for higher order autoregressive processes , 1973 .

[18]  Ding Yi,et al.  Time series analysis and its application , 2008, 2008 Chinese Control and Decision Conference.

[19]  Daniel M. Brandon.  Implementing Earned Value Easily and Effectively , 1998 .

[20]  Hong Long Chen,et al.  Logit models for early warning of distressed capital projects , 2013 .

[21]  José Manuel Galán,et al.  Stochastic earned value analysis using Monte Carlo simulation and statistical learning techniques , 2015 .

[22]  Hong Long Chen.  Improving Forecasting Accuracy of Project Earned Value Metrics: Linear Modeling Approach , 2014 .

[23]  Denis F. Cioffi.  A tool for managing projects: an analytic parameterization of the S-curve , 2005 .

[24]  H. Chen,et al.  Using Financial and Macroeconomic Indicators to Forecast Sales of Large Development and Construction Firms , 2010 .

[25]  Raafat Elshaer,et al.  Impact of sensitivity information on the prediction of project's duration using earned schedule method , 2013 .

[26]  Awad S. Hanna.  Using the Earned Value Management System to Improve Electrical Project Control , 2012 .

[27]  Mario Vanhoucke,et al.  Evaluation of deterministic state-of-the-art forecasting approaches for project duration based on earned value management , 2015 .

[28]  roBErt A. MArSHALL,et al.  The Contribution of Earned Value Management to Project Success on Contracted Efforts , 2007 .

[29]  Mario Vanhoucke,et al.  Setting tolerance limits for statistical project control using earned value management , 2014 .

[30]  David S. Christensen.  The Costs and Benefits of the Earned Value Management Process , 1998 .

[31]  David S. Christensen,et al.  Using Earned Value for Performance Measurement on Software Development Projects , 1995 .

[32]  Alberto De Marco,et al.  An Earned Schedule-based regression model to improve cost estimate at completion , 2014 .

[33]  Mario Vanhoucke,et al.  A comparison of different project duration forecasting methods using earned value metrics , 2006 .

[34]  Denis F. Cioffi.  Completing projects according to plans: an earned-value improvement index , 2006, J. Oper. Res. Soc..

[35]  Mark Keil,et al.  Why software projects escalate: the importance of project management constructs , 2003, IEEE Trans. Engineering Management.