Abstract

In the past few years, there has been an increasing interest in developing project control systems. The primary purpose of such systems is to indicate whether the actual performance is consistent with the baseline and to produce a signal in the case of non-compliance. Recently, researchers have shown an increased interest in monitoring project’s performance indicators, by plotting them on the Shewhart-type control charts over time. However, these control charts are fundamentally designed for processes and ignore project-specific dynamics, which can lead to weak results and misleading interpretations. By paying close attention to the project baseline schedule and using statistical foundations, this paper proposes a new ex ante control chart which discriminates between acceptable (as-planned) and non-acceptable (not-as-planned) variations of the project’s schedule performance. Such control chart enables project managers to set more realistic thresholds leading to a better decision making for taking corrective and/or preventive actions. For the sake of clarity, an illustrative example has been presented to show how the ex ante control chart is constructed in practice. Furthermore, an experimental investigation has been set up to analyze the performance of the proposed control chart. As expected, the results confirm that, when a project starts to deflect significantly from the project’s baseline schedule, the ex ante control chart shows a respectable ability to detect and report right signals while avoiding false alarms.

Highlights

  • According to the project management body of knowledge (PMBOK), performance measurement baseline (PMB) is an approved integrated cost-schedule plan for the project work, against which project execution and all future measurements are compared to monitor and control performance (Project Management Institute 2013)

  • Project performance needs to be monitored during its execution to ensure that the actual performance follows the planning

  • One way to do this is the use of statistical control charts in which the project performance indicators are plotted over time

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Summary

Introduction

The practical use of EDM is often faced with some challenges that make it inefficient To overcome this drawback and to discern acceptable (as-planned) variabilities from non-acceptable (not-asplanned) variations, statistical process control (SPC) techniques have been recently applied for project’s performance monitoring (Colin 2015). In such techniques, when the gap between planning and actual performance becomes significantly large, an early-warning signal is issued to take corrective/preventive actions, and as a result getting the project back on track. The last section includes a discussion of the implications of the findings for future research opportunities and provides our concluding remarks

Literature review
Findings
Conclusions and future research avenues
Full Text
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