TY  - CONF
TI  - Enhancing Earned Value Analysis With Instrinsic Schedule Performance Metrics
AU  - Bosché, Frédéric
AU  - Larabi-Tchalaia, Kat
AD  - Reader, School of Engineering, The University of Edinburgh, Edinburgh, UK, f.bosche@ed.ac.uk,  orcid.org/0000-0002-4064-8982
AD  - Civil Engineer, Assystem UK Ltd, Bristol UK, klarabitchalaia@assystem.com, orcid.org/0000-0002-8078-4743
PY  - 2023
DA  - 2023/06/26
T2  - Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31)
C3  - Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31)
CY  - Lille, France
SP  - 1116
EP  - 1126
DO  - 10.24928/2023/0109
SN  - 2789-0015 (ISSN)
AB  - The Earned Value Analysis (EVA) is a well-known, widely taught and used project monitoring method in both public and private sectors. It nonetheless has some limitations that have led to the emergence of complementary methods like the Earned Schedule (ES) or the Earned Duration Method (EDM). In this paper, another method is proposed that aims to address the limitations of EVA in terms of schedule performance assessment. This method introduces intrinsic schedule performance metrics that (1) ensure that the schedule performance of the overall project and that of individual work packages (WPs) can be measured reliably and independently from the performance of preceding WPs; and (2) do not converge to neutral values at the end of the project or WP (e.g. schedule variance converging to zero). This means that not only are project managers provided with reliable data throughout the entire project, but it also allows to record the real schedule performance of past projects for benchmarking and future planning. The proposed metrics and their application are demonstrated using simulations illustrating their benefits, or complementarity with current EVA metrics.
KW  - Earned value analysis
KW  - project
KW  - schedule
KW  - performance
KW  - monitoring
L1  - https://www.iglc.net/papers/details/2053/pdf
UR  - https://www.iglc.net/papers/details/2053
DB  - IGLC.net
LA  - English
N1  - Export date: 04 October 2026
ER  -