Completing Projects on Time and Budget: A Study on the Analysis of Project Monitoring Practices Using Real Data

Tekin Kose, Tuba Bakici* (Corresponding Author), Öncü Hazır

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This article analyzes the relationship between project cost and time performance indicators and monitoring activities, namely, tracking frequency and regularity with real project data. The existing literature on project monitoring and control remains scant, mainly based on self-reported, simulation-based artificial data for a single project, and somewhat inconclusive. Data from 60 projects managed in Belgium between 2011 and 2019 with different project duration and sizes were first used to reveal associations of regular monitoring with project performance with linear probability models; then, to dissect nonlinear associations between monitoring frequency and project performance indicators using random effects models. Earned value management technique with performance indicators is adopted to assess the project performance. Empirical findings indicate that regularly tracked projects are less likely to be late. Tracking frequency displays a U-shaped association with the likelihood of late completion. Moreover, tracking frequency has inverted U-shaped relationships with cost performance and schedule performance indexes. Moving beyond the direct effects, this article is the first to analyze a nonlinear relationship between monitoring and project performance. Our results also validate prior studies' findings on regular and frequent tracking effects using real-life multiple-project data and assess the EVM metrics and their behavior in project management.
Original languageEnglish
Number of pages12
JournalIEEE Transactions on Engineering Management
Early online date21 Dec 2022
DOIs
Publication statusE-pub ahead of print - 21 Dec 2022

Bibliographical note

Acknowledgement
The authors would like to thank K. Avcioglu for her assistance with data organization.

Keywords

  • Earned value analysis
  • nonlinear relationship
  • panel data
  • project management
  • project monitoring
  • regression analysis

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