Dynamic scheduling: integrating schedule risk analysis with earned value management

The topic of this paper is dynamic project scheduling to illustrate that project scheduling is a dynamic process that involves a continuous stream of changes and is a never ending process to support decisions that need to be made along the life of the project. The focus of this paper lies on three crucial dimensions of dynamic scheduling which can be briefly outlined along the following lines: (i) Baseline scheduling to construct a timetable that provides a start and end date for each project activity, taking activity relations, resource constraints and other project characteristics into account, and aiming to reach a certain scheduling objective, (ii) risk analysis to analyze the strengths and weaknesses of your project schedule in order to obtain information about the schedule sensitivity and the possible changes that undoubtedly occur during project progress and (iii) project control to measure the (time and cost) performance of a project during its progress and use the information obtained during the scheduling and risk analysis steps to monitor and update the project and to take corrective actions in case of problems. The focus of the current paper is on the importance and crucial role of the baseline scheduling component for the two other components, and the integration of the schedule risk and project control component in order to support a better corrective action decision making when the project is in trouble

On the use of schedule risk analysis for project management

The purpose of this paper is to give an overview on the existing literature and recent developments on the research on Schedule Risk Analysis (SRA) in Project Management (PM) to measure the sensitivity of activities and resources in the project network. SRA is a technique that relies on Monte-Carlo simulation runs to analyze the impact of changes in activity durations and costs on the overall project time and cost objectives. First, the paper gives an overview of the most commonly known sensitivity metrics from literature that are widely used by PM software tools to measure the time and cost sensitivity of activities as well as sensitivity for project resources. Second, the relevance of these metrics in an integrated project control setting is discussed based on some recent research studies. Finally, a short discussion on the challenges for future research is given. All sections in this paper are based on research studies done in the past for which references will be given throughout the manuscript

Adding value to earned value analysis

The non-repetitive nature of projects leads to uncertainty that is present to some degree in every project. Our limited ability to accurately forecast future values of parameters that are used as input to plan projects affect every project. Due to uncertainty and the resulting risk, project planning is in fact a starting point in the project management process that consists of planning, monitoring and control. Risk management techniques are also used in project management for the very same reason. Understanding the dynamic, stochastic nature of projects and the tools and techniques that can help us cope with this environment is the focus of this paper. In this paper we discuss some ideas, tools and techniques that may help project managers cope with uncertainty. We focus our discussion on two new ways to teach students and practitioners the Earned Value concept, which is discussed in the PMBOK and is supported by many of the commercial project management software packages: the Project Team Builder (PTB) and ProTrack’s Assistant. PTB is a training tool that won the PMI product of the year award for 2008. ProTrack’s Assistant is an automatic tool added on the ProTrack software tool that integrates lessons learned from an Earned Value research study awarded by the IPMA research 2008 award

A New Schedule Estimation Technique for Construction Projects

Allen studied hundreds of construction projects and developed an accu-rate, practically useful model of their labor profiles. We combine Al-len’s labor profile with standard Earned Value Management (EVM) techniques and derive a simple, practical formula that estimates the fi-nal schedule from early project data. The schedule estimation formula is exact; it requires no approximations. The estimate is also surprisingly accurate and available early enough in the project for the project manager to be able to take appropriate actions. We use one of Allen’s real-world construction data sets to calibrate and validate our theoreti-cal model. Early estimates of the final schedule are remarkably accu-rate, and available early enough to be used to effect management changes. We also explain why a current schedule estimation method, Earned Schedule (ES), has a poor theoretical foundation and show that our model is superior to ES in predicting construction schedule delays. The model should provide warning of schedule delays early enough for project managers to take corrective actions

Welcome to OR&S! Where students, academics and professionals come together

In this manuscript, an overview is given of the activities done at the Operations Research and Scheduling (OR&S) research group of the faculty of Economics and Business Administration of Ghent University. Unlike the book published by [1] that gives a summary of all academic and professional activities done in the field of Project Management in collaboration with the OR&S group, the focus of the current manuscript lies on academic publications and the integration of these published results in teaching activities. An overview is given of the publications from the very beginning till today, and some of the topics that have led to publications are discussed in somewhat more detail. Moreover, it is shown how the research results have been used in the classroom to actively involve students in our research activities

Project regularity : development and evaluation of a new project characteristic

The ability to accurately characterize projects is essential to good project management. Therefore, a novel project characteristic is developed that reflects the value accrue within a project. This characteristic, called project regularity, is expressed in terms of the newly introduced regular/irregular-indicator RI. The widely accepted management system of earned value management (EVM) forms the basis for evaluation of the new characteristic. More concretely, the influence of project regularity on EVM forecasting accuracy is assessed, and is shown to be significant for both time and cost forecasting. Moreover, this effect appears to be stronger than that of the widely used characteristic of project seriality expressed by the serial/parallel-indicator SP. Therefore, project regularity could also be useful as an input parameter for project network generators. Furthermore, the introduction of project regularity can provide project managers with a more accurate indication of the time and cost forecasting accuracy that is to be expected for a certain project and, correspondingly, of how a project should be built up in order to obtain more reliable forecasts during project control

Valor Ganado : aplicación en el sector de la construcción

Partiendo de la idea de definir y explicar el método de valor ganado como sistema de control de la programación, se pretende profundizar en el tema de la planificación, y especialmente en cuanto a construcción. Para ello se expone el sistema, y una vez captada la idea, se procede a ver las diferentes maneras existentes en cuanto a planificación, parte esencial del Valor GanadoMolla Romero, D. (2011). Valor Ganado : aplicación en el sector de la construcción. http://hdl.handle.net/10251/12392.Archivo delegad

Predicting Performance Measurement of Residential Buildings Using an Artificial Neural Network

Application Earned Value Management (EVM) as a construction project control technique is not very common in the Republic of Iraq, in spite of the benefit from EVA to the schedule control and cost control of construction projects. One of the goals of the present study is the employment machine intelligence techniques in the estimation of earned value; also this study contributes to extend the cognitive content of study fields associated with the earned value, and the results of this study are considered a robust incentive to try and do complementary studies, or to simulate a similar study in alternative new technologies. This paper is aiming at introducing a novel and alternative method of applying Artificial Intelligence Techniques (AIT) for earned value management of the construction projects through using Artificial Neural Networks (ANN) to build mathematical models to be used to estimate the Schedule Performance Index (SPI), Cost Performance Index (CPI) and to Complete Cost Performance Indicator (TCPI) in Iraqi residential buildings before and at execution stage through using web-based software to perform the calculations in the estimation quickly, accurately and without effort. ANN technique was utilized to produce new prediction models by applying the Backpropagation algorithm through Neuframe software. Finally, the results showed that the ANN technique shows excellent results of estimation when it is compared with MLR techniques. The results were interpreted in terms of Average Accuracy (AA%) equal to 83.09, 90.83, and 82.88%, also, correlation coefficient (R) equal to 90.95, 93.00, and 92.30% for SPI, CPI and TCPI respectively. Doi: 10.28991/cej-2021-03091666 Full Text: PD

Project scheduling and forecasting by laws of physical movement

Measuring actual project progress and comparing it with the planned time schedule is essential in controlling of a project. The outcome of the latter follows the s-curve diagram, which compares actual progress with the planned amount and finally analyzing any gap between them to draw directions for project scheduling. However, final duration of the project cannot be either estimated or predicted through conventional methods. The new method, using Rules of kinematics, can calculate the final duration of the project. This novel approach is successfully implemented on a construction project. The first objective in new method is forecasting final duration of the project, finding equation path and draw a new s-curve diagram for actual status during the execution process. The second objective is to evaluate schedule performance of the project and report the status of the project at each period which is a useful tool for managers