Browsing Articles by Subject "Schedule Control"
Now showing items 1-4 of 4
A buffer control method for top-down project controlTimely completion of projects is an important factor for project success. However, projects often exceed their predefined deadline, which results in a late project delivery and an increase in the total project cost. In order to increase the probability of timely completion, a project buffer can be planned at the end of a project. During project execution, an assessment of the total buffer consumption at the project completion date can be made in order to periodically monitor the project progress. When the expected buffer consumption is higher than 100%, the project deadline is expected to be exceeded and the project manager should take corrective actions to get the project back on track. In this paper, a new buffer monitoring approach is introduced, which sets tolerance limits for Earned Value Management/Earned Schedule (EVM/ES) schedule performance metrics by allocating the project buffer over the different project phases. The purpose of these tolerance limits is to provide the project manager with accurate and reliable information on the expected project outcome during the project execution. A computational study is carried out to assess the performance of the proposed approach and to compare its performance with traditional buffer consumption monitoring procedures. Additionally, existing performance metrics for tolerance limits have been put into a hypothesis testing framework, and new metrics have been developed in order to fill the detected gaps in performance measurement. Results have shown that the proposed tolerance limits improve the performance of the monitoring phase, especially for parallel projects. Consequently, the underperformance of EVM/ES for parallel projects is mitigated by these limits.
A comparison of the performance of various project control methods using earned value management systemsRecent literature on project management has emphasised the effort which is spent by the management team during the project control process. Based on this effort, a functional distinction can be made between a top down and a bottom up project control approach. A top down control approach refers to the use of a project control system that generates project based performance metrics to give a general overview of the project performance. Actions are triggered based on these general performance metrics, which need further investigation to detect problems at the activity level. A bottom up project control system refers to a system in which detailed activity information needs to be available constantly during the project control process, which requires more effort. In this research, we propose two new project control approaches, which combines elements of both top down and bottom up control. To this end, we integrate the earned value management/earned schedule (EVM/ES) method with multiple control points inspired by critical chain/buffer management (CC/BM). We show how the EVM/ES control approach is complementary with the concept of buffers and how they can improve the project control process when cleverly combined. These combined top down approaches overcome some of the drawbacks of traditional EVM/ES mentioned in the literature, while minimally increasing the effort spent by the project manager. A large computational experiment is set up to test the approach against other control procedures within a broad range of simulated dynamic project progress situations.
An empirical validation of the performance of project control tolerance limitsThe goal of project control is monitoring the project progress during project execution to detect potential problems and taking corrective actions when necessary. Tolerance limits are a tool to assess whether the project progress is acceptable or not, and generate warnings signals that act as triggers for corrective action to the project manager. In this paper, three distinct types of tolerance limits that have been proposed in literature are validated on a large and diverse set of real-life projects mainly situated in the construction sector. Moreover, a novel approach to construct tolerance limits that integrate the project risk information into the monitoring process is introduced. The results of the empirical experiment have shown that integrating project-specific information into the construction of the tolerance limits results in a higher efficiency of the monitoring process. More specifically, while including cost information increases the efficiency only marginally, incorporating the available resource information substantially improves the efficiency of the monitoring process. Furthermore, when projects are not restricted by scarce resources, the efficiency can be enhanced by integrating the available project risk information.
The impact of applying effort to reduce activity variability on the project time and cost performanceDuring project execution, deviations from the baseline schedule are inevitable due to the presence of uncertainty and variability. To assure successful project completion, the project’s progress should be monitored and corrective actions should be taken to get the project back on track. This paper presents an integrated project control procedure for measuring the project’s progress and taking corrective actions when necessary. We apply corrective actions that reduce the activity variability to improve the project outcome. Therefore, we quantify the relation between the applied managerial effort and the reduction in activity variability. Moreover, we define three distinct control strategies to take corrective actions on activities, i.e. an interventive strategy, a preventive strategy and a hybrid strategy. A computational experiment is conducted to evaluate the performance of these strategies. The results of this experiment show that different strategies are preferred depending on the topological network structure of projects. More specifically, the interventive strategy and hybrid strategy are preferred for parallel projects, while the preventive strategy is preferred for serial projects.