• A buffer control method for top-down project control

      Martens, Annelies; Vanhoucke, Mario (European Journal of Operational Research, 2017)
      Timely 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 multivariate approach for top-down project control using earned value management

      Colin, Jeroen; Martens, Annelies; Vanhoucke, Mario; Wauters, Mathieu (Decision Support Systems, 2015)
      Project monitoring and the related decision to proceed to corrective action are crucial components of an integrated project management and control decision support system (DSS). Earned value management/earned schedule (EVM/ES) is a project control methodology that is typically applied for top-down project schedule control. However, traditional models do not correctly account for the multivariate nature of the EVM/ES measurement system. We therefore propose a multivariate model for EVM/ES, which implements a principal component analysis (PCA) on a simulated schedule control reference. During project progress, the real EVM/ES observations can then be projected onto these principal components. This allows for two new multivariate schedule control metrics (T2 and SPE) to be calculated, which can be dynamically monitored on project control charts. Using a computational experiment, we show that these multivariate schedule control metrics lead to performance improvements and practical advantages in comparison with traditional univariate EVM/ES models.
    • An empirical validation of the performance of project control tolerance limits

      Martens, Annelies; Vanhoucke, Mario (Automation in Construction, 2018)
      The 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 a limited budget on the corrective action taking process

      Song, Jie; Martens, Annelies; Vanhoucke, Mario (European Journal of Operational Research, 2020)
      The main goal of project control is to identify the deviations between the baseline schedule and the actual progress of the project by measuring the project performance in progress and using the project control methodologies to generate warning signals that act as triggers for corrective actions to bring the project back on track. To that purpose, tolerance limits are set on the required project performance, such that if the warning signals exceed these limits, they should result in appropriate corrective actions. In this paper, the Earned Value Management (EVM) control method and its extensions are used to test their abilities in taking corrective actions under a budget constraint. More precisely, four different approaches are proposed for allocating the limited budget along the different project phases, and whether a proper allocation of the budget results in an increase of the expected project outcome is measured. A large computational experiment is conducted on a set of artificial projects to assess the efficiency and effectiveness of the budget allocation models. Results show that simply allocating budget according to the time accrue of projects performs better than methods that take cost, time/cost or risk information into account. Moreover, results indicate that allocating a budget that increases in later stages of the project is beneficial for the outcome.
    • The impact of applying effort to reduce activity variability on the project time and cost performance

      Martens, Annelies; Vanhoucke, Mario (European Journal of Operational Research, 2019)
      During 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.
    • Integrating corrective actions in project time forecasting using exponential smoothing

      Martens, Annelies; Vanhoucke, Mario (Journal of Management in Engineering, 2020)
      Earned value management (EVM) and earned duration management (EDM) are established methodologies to monitor the project performance during execution. These methods serve as a basis to forecast the final project duration and/or project cost. The aim of this paper is to improve the accuracy of project time forecasting by extending exponential smoothing for project time forecasting using EVM and EDM with the integration of corrective actions that are taken during project progress. In order to evaluate the forecasting accuracy of this approach, eight projects conducted in recent years have been followed up in real time. Based on the nature of the observed corrective actions, six distinct categories of corrective actions are identified. The empirical experiment showed that explicitly integrating the occurrence of corrective actions into the forecasting process improves the forecasting accuracy of traditional forecasting methods and forecasting methods using standard exponential smoothing, especially for the middle and late phases of projects. Consequently, by including corrective actions in the forecasting process, project managers can predict the final project duration more accurately.
    • The integration of constrained resources into top-down project control

      Martens, Annelies; Vanhoucke, Mario (Computers & Industrial Engineering, 2017)
      The timely completion of a project is one of its main factors for success. During the scheduling phase, a project buffer can be installed to protect the project deadline. During the execution phase, tolerance limits that generate warning signals when the project deadline is endangered should be constructed to monitor the buffer consumption. These tolerance limits will be constructed for the dynamic progress data provided by the Earned Value Management/Earned schedule methodology (EVM/ES). In this paper, we incorporate information on the availability of scarce resources into the construction of analytical tolerance limits for EVM/ES, in order to improve the efficiency and reliability of these tolerance limits. In order to review the performance of the limits, a computational experiment has been carried out in which they are compared to analytical tolerance limits that disregard the availability of resources. Results have shown that the performance of analytical tolerance limits can be significantly enhanced by incorporating the available resource information.
    • Using earned value management and schedule risk analysis with resource constraints for project control

      Song, Jie; Martens, Annelies; Vanhoucke, Mario (European Journal of Operational Research, 2021)
      The main goal of project control is to measure the actual project progress such that the deviations from the plan can be identified and corrective actions can be taken to bring the project back on track. However, in resource-constrained projects, disrupted activities affect their successors due to precedence relations and the other activities due to resource constraints, both of which will result in deviations during project progress. Since the project control approaches solely focus on the deviations based on the network analysis, they do not accurately reflect the progress of resource-constrained projects. This paper extends project control approaches for resource-constrained projects to measure and evaluate whether the project progress is acceptable. Moreover, we design three scenarios considering possible resource conflicts to take corrective actions when needed. In the computational experiment, this project control process is applied to a large set of projects with different characteristics and further validated on real-life project data. The results show that the proposed scenarios and different project control approaches are efficient and reliable, but their use depends on project network structure and resource scarceness.
    • Using real project schedule data to compare earned schedule and earned duration management project time forecasting capabilities

      André de Andrade, Paulo; Martens, Annelies; Vanhoucke, Mario (Automation in Construction, 2019)
      Since project control involves taking decisions that affect the future, the ability to accurately forecast the final duration and cost of projects is of major importance. In this paper, we focus on improving the accuracy of project duration forecasting by introducing a forecasting approach for Earned Value Management (EVM) and Earned Duration Management (EDM) that combines the schedule performance and schedule adherence of the project in progress. As the schedule adherence has not yet been defined formally for EDM, we extend the EVM-based measure of schedule adherence, the p-factor, to EDM and refer to this measure as the c-factor. Moreover, we aim to improve the ability to indicate the expected forecasting accuracy for a project by extending the EVM concept of project regularity to EDM. The introduced forecasting approach and the EDM project regularity indicator are applied to a large number of real-life projects, mainly situated in the construction sector. The conducted empirical experiment shows that the project duration forecasting accuracy can be increased by focusing on both the schedule performance and schedule adherence. Further, this study shows that the EDM project regularity indicator is indeed a more reliable indicator of forecasting accuracy.
    • Using schedule risk analysis with resource constraints for project control

      Song, Jie; Martens, Annelies; Vanhoucke, Mario (European Journal of Operational Research, 2021)
      Schedule Risk Analysis (SRA) has shown to provide reliable activity sensitivity information for taking corrective actions during project control. More precisely, by selecting a small subset of activities with high sensitivity values for taking corrective actions, the project outcome can be improved. In resource constrained projects, disrupted activities can affect both their successors as well as other activities when resource conflicts are induced. Since SRA focuses solely on the project network to determine the sensitivity of activities, the traditional SRA metrics do not accurately reflect the activity sensitivity for resource constrained projects. In this paper, the traditional SRA metrics are extended for resource constrained projects, and a novel resource-based sensitivity metric is introduced (RC-SRA metrics). A computational experiment is conducted to investigate the ability of the RC-SRA metrics to identify activities with higher sensitivity values. In addition, two activity selection strategies, defined as the normal strategy and sequential strategy, are designed to select activities for taking corrective actions. Further, two types of corrective actions are proposed to reduce the activity duration or resource demand in case of delays, respectively. Finally, the impact of dynamically updating the RC-SRA metrics during project execution is examined. The computational results show that the normal activity selection strategy is recommended for serial projects, while the sequential strategy is preferred for parallel projects. The results also indicate that reducing the activity durations performs better than reducing the resource demand of activities. Finally, it is shown that updating the RC-SRA metrics dynamically during project execution improves the efficiency of the corrective action taking process.