From the BlogSubscribe Now

Improving the predictive power of planned value

Access to new resource related to Earned Value Management added to PMWL



Resource provided by Balzhan Khamitova

12 May 2022 – Almaty, Kazakhstan – Access to a new resource has been added to the PM World Library (PMWL) related to Earned Value Management. The new resource titled “Earned value project management: Improving the predictive power of planned value” is a paper by Hing Long Chen, Wei Tong Chen and Ying Lien Lin published in the International Journal of Project Management in 2016.

The aim of this study was to provide a straightforward modeling method for improving the predictive power of Planned value before project execution. Furthermore, the authors developed forecasting models for Earned value and Actual cost for different cases.

To answer the main question of this study: “How can we enhance the predictive power of PV prior to project execution?”, the authors provided two-fold methodologies. The first one is Logarithm Linear transformation (LLT) and the second one is a mathematical model that combines time-series and regression analysis.

As a result, the authors used Mean Absolute Percentage Error as evaluation criterion, by which the authors provided the conclusion and made comparisons between case studies. The authors identified some limitations in this study as generalizing claims based on results would require further empirical testing and that project managers and/or engineers may still find it difficult to apply this method in practice.

To access this new resource, go to the Applications and Hot Topics section of the library at scroll down to “Basic P/PM Topics”, and click on “Earned Value Management (EVM)”, scroll down to resource. Must be a registered member and logged-in to access. If not yet registered, please consider the FREE 30-day Trial Membership.

This new resource provided through the PMWL university research internship program; to learn more, click here