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There are many potential measures of performance for evaluating the success of a construction project. All address performance in three key areas: scope, schedule and budget. In a performance measurement framework where senior management wishes to minimise the numberof performance measures it employs, while ensuring maximal coverage or visibility into the programme, having a tool that captures each of the three areas would be ideal. Project managers have used Earned Value Management (EVM) for over 40 years to track actual schedule progress and actual costs against project plans. Earned Value Management has traditionally been applied to individual projects on which the manager is accountable for both schedule and cost variances. This paper proposes methods to apply EVM principles to allow: (1) analysis of portfolios of construction projects; (2) incorporation of the analysis into an innovative pay‐for‐performance human resources practice; and (3) use of regression analysis to develop baseline earned value curves. These extensions fit the needs of many government managers, who oversee a range of projects by multiple contractors, and whose cost risk is primarily due to schedule slips and change orders. Earned Value Management is described in the context of project oversight, and a dashboard system of performance measures is proposed for quickly assessing individual projects and portfolios. A method of generating standardised planned value curves is then specified, based on data from previous and ongoing projects. The paper concludes by showing how the US General Services Administration’s Public Buildings Service is using these methods to analyse and oversee its portfolio of new construction and major repair and alteration projects.

The Ariba Implementation at MED-X case is designed to teach students how to analyze a program that is experiencing problems and recommend solutions. Specifically, the case introduces students to earned value analysis and program oversight for an e-procurement technology program. The case centers on MED-X's need to quickly discover why the company's e-procurement implementation project was not going according to plan. Once a cause has been discovered, students will need to make a recommendation to fix the problem. Data for the simplified program, consisting of two concurrent projects, is given to students, who should in turn analyze the project using earned value analysis. The case is an easy introduction to program management and oversight for executives and MBA students, and teaches the essentials of earned value project management.

Students will learn how to control and act in oversight of large complex programs, as well as how to apply earned value metrics to analyze a simplified program consisting of two projects. Analyzing the project enables students to learn the strengths and pitfalls of the earned value approach. From a management decision perspective, the case gives students the tools to succinctly answer the questions: How much will the project cost? How long will it take? What is wrong with the project?

Sets out to examine earned value management (EVM), a project management technique that relates resource planning to schedules, technical costs and schedule requirements.

Provides an example of how EVM can be implemented in a data warehouse project and how it can be used as a tool to diagnose and solve problems.

EVM is based on the belief that the value of the project increases as tasks are completed and therefore the earned value of a project is a measure of the real progress of that project.

Offers a significant analysis of EVM, its benefits and pitfalls.

This study aims to review earned value management (EVM)-relative methods, including the original EVM, earned schedule method (ESM) and earned duration management (EDM(t)). This study then proposes a general implementation procedure and some basic principles for the selection of EVM-relative methods.

After completing an intensive literature review, this study conducts a case study to examine the forecasting performance of project duration using the EVM, ESM and EDM(t) methods.

When the project is expected to finish on time, ESM with a performance factor equal to 1 is the recommended method. EDM(t) would be the most reliable method during a project's entire lifetime if EDM(t) is expected to be delayed based on past experience.

As this research conducts a case study with only one building construction project, the results might not hold true for all types of construction projects.

EVM, ESM and EDM(t) are simple and data-accessible methods. With the help of a general implementation procedure, applying all three methods would be better. The power of the three methods is definitely larger than that of choosing only one for complex construction projects.

Previous studies have discussed the advantages and disadvantages of EVM, ESM and EDM(t). This study amends the available outcomes. Thus, for schedulers or researchers interested in implementing EVM, ESM and EDM(t), this study can provide more constructive instructions.

There is growing recognition that effective project control systems (PCS) are critical to the success of projects. The relationship between the individual elements of PCS and successfully achieving project objectives has yet to be explored. This research investigates the enablers and barriers that influence the elements of PCS success and drive project objectives.

This study adopts a mixed approach of descriptive analysis and regression models to explore the impact of six PCS elements on project outcomes. Petroleum and chemical projects in Saudi Arabia were selected as a case study to validate the research model.

Data from a survey of 400 project managers in Saudi’s petroleum and chemical industry reveal that successful PCS are the key to achieving all project outcomes, but they are particularly critical for meeting project cost objectives. Project Governance was identified as the most important of the six PCS elements for meeting project objectives. A lack of standard processes emerged as the most significant barrier to achieving effective project governance, while having skilled and experienced project team members was the most significant enabler for implementing earned value.

The study offers a direction for implementing and developing PCS as a strategic tool and focuses on the PCS elements that can improve project outcomes.

This research contributes to project management knowledge and differs from previous attempts in two ways. Firstly, it investigates the elements of PCS that are critical to achieving project scope, schedule and cost objectives; secondly, enablers and barriers of PCS success are examined to see how they influence each element independently.

Earned value management systems (EVMS), also called integrated project and program management systems, have been greatly examined in the literature, which has typically focused on their technical aspects rather than social. This study aims to hypothesize that improving both the technical maturity of EVMS and the social environment elements of EVMS applications together will significantly impact project performance outcomes. For the first time, empirical evidence supports a strong relationship between EVMS maturity and environment.

Data was collected from 35 projects through four workshops, attended by 31 industry practitioners with an average of 19 years of EVMS experience. These experts, representing 23 organizations, provided over 2,800 data points on sociotechnical integration and performance outcomes, covering projects totaling $21.8 billion. Statistical analyses were performed to derive findings on the impact of technical maturity and social environment on project success.

The results show statistically significant differences in cost growth, compliance, meeting project objectives and business drivers and customer satisfaction, between projects with high EVMS maturity and environment and projects with poor EVMS maturity and environment. Moreover, the technical and social dimensions were found to be significantly correlated.

Key contributions include a novel and tested performance-driven framework to support integrated project management using EVMS. The adoption of this detailed assessment framework by government and industry is driving a paradigm shift in project management of some of the largest and most complex projects in the U.S.; specifically transitioning from a project assessment based upon a binary approach for EVMS technical maturity (i.e. compliant/noncompliant to standards) to a wide-ranging scale (i.e. 0–1,000) across two dimensions.

Delineating where stability occurs in a contract provides the window of opportunity for procurement officials to positively affect cost and schedule outcomes. While the concept of a Cost Performance Index (CPI) "stability rule" has been routinely cited by Earned Value Management (EVM) authors since the early 1990's, more recent research questions the veracity of this stability rule. This paper resolves the controversy by demonstrating that the definition of stability matters. We find a morphing of the stability definition over time, with three separate definitions permeating the literature. Next, an analysis of Department of Defense contracts for both cost and schedule stability properties finds that the veracity of the stability rule is intricately tied to the definition used.

The purpose of this paper is to contribute to the diffusion of earned value management (EVM) as a practicable methodology to monitor facility construction and renovation projects in the context of the European industry.

First, a review of the literature reveals how EVM evolved as a tool for facility construction project monitoring together with specific concerns for its application. Then, a review of EVM practice and trends in Europe is provided and finally, applicability and viability of the method is proved through a case demonstration.

EVM practice in the European construction industry is found to be lagging behind other experienced countries and industries, despite EVM having been found to be applicable, adaptable, and predictive of integrated final cost and schedule of facility construction projects. In particular, cost estimate at completion is forecasted by a simple cost performance index (CPI), while for the time estimate at completion, the earned schedule concept is revealed as an accurate predictor.

The paper urges the need for research of a European standard as a primary factor for successful diffusion of EVM usage in architecture, engineering and construction projects.

This paper helps practitioners to understand the adaptability of EVM practice in the European construction industry and to apply EV tools for effective monitoring of the performance of their projects.

Current trends of EVM practice in the European construction context are presented and suggestions for sustaining the diffusion of EVM are given.

Earned Value Management (EVM) is widely used as a project performance measurement and forecasting technique. Nonetheless, it has not been fully explored in Pakistani construction industry; where conventional progress reporting methodology (CPRM) is being followed having certain confines. It reports only the financial progress of a project, expresses feeble association between the duration and cost of activities, and forecasts flawed schedule and completion cost. This research implements EVM on under-construction building projects in Pakistan, and compares its upshots with the projects' actual records and with the outcomes of CPRM.

To assess the implementation of EVM on building projects, a set of specific criteria was established. Work Breakdown Structure, Organization Breakdown Structure and Control Points were established. The study has compared the EVM metrics with CPRM outcomes on three under-study building projects, and has deliberated on their mutual differences as well as their relationship with actual cost and schedule performance. Monthly figures of actual spending and completed activities were periodically recorded and compared with planned values for status indication. The graphs were generated to observe the correlation between the results of EVM and CPRM. The data was then extrapolated to forecast the schedule and cost values at completion.

The study discovered that trends of EVM in quantifying the project's cost and schedule performance were strongly correlated and were closer to the actual progress. It has also verified the EVM's soundness in forecasting the cost and schedule, required for project's completion. Contrarily, CPRM metrics could not precisely visualize the current and future, cost and schedule performance.

The case study concludes that EVM's incorporation in progress reporting regime can revolutionize the assessment procedures in Pakistan by rightly indicating the project's current status as well as visualizing the future performance. The study's methodology can also be extrapolated in other countries having similar work environment and economic conditions.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.