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Risk-adjusted Earned Value and Earned Duration Management models for project performance forecasting
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Project control is essential to ensure that the investment on a project is providing the intended benefits and is valuable to the customers. Previous methods offer project performance monitoring and forecasting tools, but they lack accuracy and the associated techniques omit the project financial risk (any unplanned event that has an impact on schedule and budget); the main factor of project failure. Poor project execution, and particularly failure to control and accurately forecast the project performance, may lead to increased costs, upset customers and eventually loss of market share. These gaps have been filled in this study by the development of novel models that use statistical analysis of the previous project performance, including risk evaluation techniques. The proposed models succeeded in providing remarkably improved forecasts in three project dimensions: duration, cost and resources. The robustness of the models has been verified by testing them on real projects. The results show superiority in terms of accuracy and easy application compared to any existing method, proving that the risk inclusion provides improvement compared to previous studies. The most important features of the models are: risk-based adjustment of the forecasted values, periodic and completion forecasts, statistical processing and holistic approach. The greatest advancements have been made in the cost forecast, for which the risk adjustment inclusion is examined for the first time. The resources (man-hours) forecast is another pioneer element of the proposed models. All the above provide a complete image of the project status and paint the picture of future performance. The models results are fed in a Decision Support System, which highlights the overperforming and underperforming areas of the project. This confirms the proposition that the model results can be used to initiate restorative action. The contribution of this study to the project management field is easy-to-use and accurate models, which include the financial risk and facilitate the project manager’s decisions and actions. Anticipation of the project performance, by considering the risk, can result to significant time and cost savings, crucial for project success.   

Place, publisher, year, edition, pages
2019. , p. 77
Keywords [en]
Project monitoring, Project forecasting, Financial risk, Earned Value Management, Earned Duration Management, Schedule Performance Index, Duration Performance Index, Cost performance Index, Program Performance Index, Risk Coefficient, Risk-adjusted Schedule Model, Risk-adjusted Cost Model, Risk-adjusted Man-hours Model, Statistical Analysis, Decision Support System
National Category
Other Engineering and Technologies not elsewhere specified
Identifiers
URN: urn:nbn:se:bth-18965OAI: oai:DiVA.org:bth-18965DiVA, id: diva2:1373119
Subject / course
IY2594 Magisterarbete MBA
Educational program
IYABA MBA programme
Supervisors
Examiners
Available from: 2019-11-27 Created: 2019-11-26 Last updated: 2019-11-27Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Output format
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