Probabilistic Approach for Budgeting in Portfolio of Projects

This paper presents a mathematical model for calculating the budgetary impact of increasing the required confidence level in a probabilistic risk assessment for a portfolio of projects. The model provides a rational approach for establishing a probabilistic budget for an individual project in such a way that the budget for a portfolio of projects will meet a required confidence level. The use of probabilistic risk assessment in major infrastructure projects is increasing to cope with major cost overruns and schedule delays. The outcome of the probabilistic risk assessment is often a distribution for project costs. The question is at what level of confidence (i.e., the probability that budget would be sufficient given the cost distribution) should be used for establishing the budget. The proposed method looks at a portfolio of such projects being funded by the same owner. The owner can establish a target probability with respect to its annual budget. The model can help the owner establish confidence level for individual projects and also examine the effect of changing the confidence level of the portfolio budget on the budget and the confidence level of individual projects. The paper is relevant to practitioners because it provides a methodology for establishing confidence levels by the owner agencies in the emerging field of cost risk assessment for infrastructure projects. A numerical example is provided using actual transit project data to demonstrate the model application.     

Estimation of Cost Contingency for Air Force Construction Projects

Risk and associated cost overruns are critical problems for construction projects, yet the most common practice for dealing with them is the assignment of an arbitrary flat percentage of the construction budget as a contingency fund. Therefore, our goal was to identify significant variables that may influence, or serve as indicators of, potential cost overruns. We analyzed data from 203 Air Force construction projects over a full range of project types and scopes using multiple linear regression to develop a model to predict the amount of required contingency funds. The proposed model uses only data that would be available prior to the award of a construction contract. The variables in the model were categorized as project characteristics, design performance metrics, and contract award process influences. Based on the performance metric used, the model captures 44% of actual cost overruns versus the 20% captured by the current practice. Furthermore, application of the model reduces the average contingency budgeting error from 11.2 to only 0.3%.     

Three-Stage Least-Squares Analysis of Time and Cost Overruns in Construction Contracts

Construction cost overrun and time overrun (delay) are a significant problem in highway-construction project delivery. Previous research studies have provided insight into the factors that affect overruns; however the findings may have been limited because they do not explicitly consider the simultaneous relationship between cost and time overruns. In this paper, we use data from Indiana highway projects to provide empirical evidence that a simultaneous relationship exists between cost and time overruns and that analysis of these two contractual outputs need to take due cognizance of such simultaneity. Using the three-stage least-squares technique, we identify a number of factors that significantly affect cost overrun and time overrun and we show how the effect of these variables vary by attributes such as project type and results of the bidding process. The models developed in this paper can help agencies enhance the estimation of the expected overruns of final cost and the delay in completion time for their planned projects.     

Isolated Collapsed But-For Delay Analysis Methodology

Schedule delays are common in construction projects. Although many methods have been developed for analyzing and measuring schedule delays for construction projects, each method has functional limitations and use prerequisites. No one method is acceptable for all project participants under all circumstances. This study presents the isolated collapsed but-for (ICBF) method, an innovative delay analysis method for construction projects. During analysis, the ICBF method requires as-planned and as-built schedules as well as identified liability documents with key delay events to perform its analysis approach. Based on its application to an illustrative case and comparisons with other methods, the ICBF method is effective for delay analysis. Results provided by the proposed method can be easily traced to the actual case in an as-built schedule.     

Fuzzy Logic Approach for Activity Delay Analysis and Schedule Updating

This paper presents a fuzzy logic model that integrates daily site reporting of activity progress and delays, with a schedule updating and forecasting system for construction project monitoring and control. The model developed assists in the analysis of the effects of delays on a project’s completion date and consists of several components: An as-built database integrated with project scheduling; a list of potential causes for delays; a procedure to categorize delays; a method of estimating delay durations utilizing fuzzy logic; a procedure that updates the schedule; and, a procedure that evaluates the effects and likely consequences of delays on activity progress. This model is of relevance to researchers since it makes a contribution in project scheduling by developing a complete approach for handling the uncertainty inherent in schedule updating and activity delay analysis. It also advances the application of fuzzy logic in construction. It is of relevance to construction industry practitioners since it provides them with a useful technique for incorporating as-built data into the schedule, assessing the impact of delays on the schedule, and updating the schedule to reflect the consequences of delays and corrective actions taken. The use of fuzzy logic in the model allows linguistic and subjective assessments to be made, and thereby suits the actual practices commonly used in industry.     

Evaluating Cost Overruns of Asphalt Paving Project Using Statistical Process Control Methods

While some projects will experience changes to the contracted cost by deduction or additions, construction cost overruns are becoming a common problem in the construction industry. Steps need to be taken to minimize cost overrun through cost and quality control techniques. This paper presents a study conducted to evaluate construction cost overruns of asphalt paving operations performed by the Illinois Department of Transportation (IDOT). The main objective is to analyze the main causes of cost overruns and evaluate the amount of cost overrun of asphalt paving operations, using statistical process control (SPC) techniques. Real data from projects in the year 2000 were collected from IDOT. These data contain cost information of 219 projects. The results indicate that the average cost overrun for the sample collected was 4% above the bid price. Reasons for cost overruns are analyzed and a Pareto chart and a cause and effect diagram are constructed. Individuals and Moving Range (MR) control charts are developed and their interpretation and use are discussed. Furthermore, the benefits and limitations of using the individuals and MR chart in cost control applications are pointed out. It is recommended that SPC analysis be an integral part in managing and controlling project costs.     

Probabilistic Forecasting of Project Duration Using Kalman Filter and the Earned Value Method

The earned value method (EVM) is recognized as a viable method for evaluating and forecasting project cost performance. However, its application to schedule performance forecasting has been limited due to poor accuracy in predicting project durations. Recently, several EVM-based schedule forecasting methods were introduced. However, these are still deterministic and have large prediction errors early in the project due to small sample size. In this paper, a new forecasting method is developed based on Kalman filter and the earned schedule method. The Kalman filter forecasting method (KFFM) provides probabilistic predictions of project duration at completion and can be used from the beginning of a project without significant loss of accuracy. KFFM has been programmed in an add-in for Microsoft Excel and it can be implemented on all kinds of projects monitored by EVM or any other S-curve approach. Applications on two real projects are presented here to demonstrate the advantages of KFFM in extracting additional information from data about the status, trend, and future project schedule performance and associated risks.     

Web-Enabled System Dynamics Model for Error and Change Management on Concurrent Design and Construction Projects

Construction projects are uncertain and complex in nature often because of iterative cycles caused by errors and changes. These errors and changes impair project performance and, consequently, cause schedule and cost overruns to be prevalent. Iterative cycles are more detrimental when design and construction are concurrent and often force activities to proceed without complete information. In an effort to address this issue, this paper presents the information technology aspect of the dynamic planning and control methodology (DPM), which provides a mechanism that will analyze the impact of negative iterative cycles on construction performance. In order to guarantee a smooth application of this method to real-world projects, DPM has been developed by integrating several existing methods around a core system dynamic model for quality and change management and then implementing these methods into a web-based collaborative environment. A case project, applying the developed web-based DPM, shows great potential in facilitating on-site decision making by virtue of its support of data analysis as well as real-time information sharing.     

Modeling Cost Escalation in Large Infrastructure Projects

Cost overruns in large infrastructure projects have been commonplace in the past decades. Budgeting for cost escalation is a major issue in the planning phase of these projects. In this paper, we first review various methods of forecasting escalation factor and study the changes in construction costs in the past 25 years by analyzing movements of a cost index. We then introduce a system for modeling the escalation uncertainty in large multiyear construction projects. The system uses a Monte Carlo simulation approach and considers variability of project component durations and the uncertainty of escalation factor during the project lifetime and calculates the distribution for the cost. System application is demonstrated using a numerical example. The system can be used by planners and cost estimators for budgeting the effect of cost escalation in large projects with multiyear schedules.     

Strategic-Operational Construction Management: Hybrid System Dynamics and Discrete Event Approach

A significant number of large-scale civil infrastructure projects experience cost overruns and schedule delays. To minimize these disastrous consequences, management actions need to be carefully examined at both the strategic and operational levels, as their effectiveness is mainly dependent on how well strategic perspectives and operational details of a project are balanced. However, current construction project management approaches have treated the strategic and operational issues separately, and consequently introduced a potential conflict between strategic and operational analyses. To address this issue, a hybrid simulation model is presented in this paper. This hybrid model combines system dynamics and discrete event simulation which have mainly been utilized to analyze the strategic and operational issues in isolation, respectively. As an application example, a nontypical repetitive earthmoving process is selected and simulated. The simulation results demonstrate that a systematic integration of strategic perspective and operational details is helpful to enhance the process performance by enabling construction managers to identify potential process improvement areas that traditional approaches may miss. Based on the simulation results, it is concluded that the proposed hybrid simulation model has great potential to support both the strategic and operational aspects of construction project management and to ultimately help increase project performance.     

Prediction System for Change Management in Construction Project

Changes are the main causes of delays and cost overruns in construction projects. Various change management systems have been developed to minimize the impacts of changes and to facilitate good project management. This paper presents a change prediction system using activity-based dependency structure matrix (DSM) to facilitate change management. DSM is used to model the process that may occur as a result of changes. Consequently changes can be predicted by setting the change criteria for each activity in the form of rework scope. Furthermore, Monte Carlo simulation is introduced to analyze the change probability of activities involved in construction projects. The effectiveness of the prediction system is verified by applying this system to an office building project. This study provides a useful tool for project management teams to manage changes proactively and efficiently.     

Float Consumption Impact on Cost and Schedule in the Construction Industry

Quantifying and minimizing the risks associated with delays in the construction industry are the main challenges for all parties involved. Float loss impact in noncritical activities is one of the complicated delays to assess on a project’s duration and cost. This is due to the fact that the deterministic critical path method cannot cope with such delays unless they exceed the total float values. Further, stochastic analysis, which is used in this research to assess the impact of such delays, is perceived by many planners to be complicated and time consuming. This paper presents a method to control the risks associated with float loss in construction projects. The method uses a recently developed multiple simulation analysis technique that combines the results of cost range estimates and stochastic scheduling, using Monte Carlo simulation. The proposed method quantifies the float loss impact on project duration and cost. Least-squares nonlinear regression is used to convert the stochastic results into a polynomial function that quantifies the float loss impact by relating directly the float loss value to project duration and cost at a specified confidence level.     

Discriminant Analysis for Predicting Ranges of Cost Variance in International Construction Projects

Unanticipated market conditions as well as project-related risks can easily lead to cost overruns in international construction projects. For a contractor to be financially successful in international projects, a careful examination of the project is a prerequisite to understanding the cost variance characteristics. Based on the reasonably accurate characterization of the cost performance, the markup or contingency amount is determined to ensure both a decent level of profit and a good chance of winning the contract. This paper presents a classification model to categorize international construction projects, particularly faced by Korean contractors, into five cost-variation classes: extreme cost overrun, moderate cost overrun, neutral, moderate cost saving, and extreme cost saving. The model is able to characterize an international project for its cost performance prediction in comparison to the contractor’s initial cost estimate. A linear discriminant analysis is utilized to develop the predictive classification model with the support of the bootstrap method. Tests show that the proposed model is able to help cost estimators determine a proper level of cost contingency before bidding on an international project.     

Cost Information Model for Managing Multiple Projects

Construction companies must deal with several projects at once, but a system to manage multiple projects is not fully developed yet. The first step towards developing such system is to design an information model that is suitable for managing multiple projects. This paper presents the cost-based project modeling (CBPM) method in contrast to the traditional activity-based project modeling methods. The CBPM uses cost as a core of the model along with other project information organized around it. The CBPM serves as a platform for integrating project information from multiple projects. Various types of construction costs are hierarchically modeled to generate corporate-wide information such as project performances, cash flows, and other predictive indicators. Based on the information model, an object-oriented database was developed to contain cost data across several projects. In the model, a module that connects to external systems is built into the model to enhance interactivity with the legacy systems and the industry standards. A prototype system was developed and tested with actual project data to validate the information processing capabilities of the model. The findings from the test indicate construction cost can be an excellent medium that can organize various types of information of multiple projects.     

Project Performance Control in Reconstruction Projects

Cost, schedule, and quality are the main indicators of performance in construction projects. These indicators are highly interrelated and require some balance and trade-off among them to achieve efficient overall control over project performance. Focusing on these performance indicators, the primary objective of this study is to investigate the use of conventional control techniques in projects involving reconstruction of occupied buildings. To facilitate this analysis, performance data have been collected, using a questionnaire survey, from 25 reconstruction and 15 new construction projects. The survey was followed by structured interviews with construction practitioners and project participants to elicit success-related factors and to identify some of the unique problems affecting the control of reconstruction projects. Using the collected data, performance comparison was conducted between new and reconstruction projects along with a detailed analysis of the suitability of existing techniques for the control of the cost, schedule, and quality in reconstruction projects.     

Causes, Effects, Benefits, and Remedies of Change Orders on Public Construction Projects in Oman

Change orders are usually issued to cover variations in scope of work, material quantities, design errors, and unit rate changes. This paper discusses variations in public construction projects in Oman by investigating causes of variations, studying their effects on the project, identifying the beneficial parties, and suggesting remedies to alleviate related problems. Tasks included an analysis of four actual case studies and conducting a field survey via a questionnaire. It was determined that the client’s additional works and modifications to design were the most important factors causing change orders, followed by the nonavailability of construction manuals and procedures. The most important effects of change orders on the project were found to be the schedule delays, disputes, and cost overruns. The contractor was found to be the party most benefiting from the change orders followed by the consultant and then the client. A set of remedial actions were suggested and respondents viewed that the revision of registration of consulting offices would be the most important action followed by establishing standard documents for design procedures and building a national database about soil conditions and services.     

Statistical Analysis on the Cost and Duration of Public Building Projects

A probabilistic model is proposed to predict the risk effects on time and cost of public building projects. The research goal is to utilize a real history data in estimating project cost and duration. The model results can be used to adjust floats and budgets of the planning schedule before project commencement. Statistical regression models and sample tests are developed using real data of 113 public projects. The model outputs can be used by project managers in the planning phase to validate the schedule critical path time and project budget. The comparison of means analysis for project cost and time performance indicated that the sample projects tend to finish over budget and almost on schedule. Regression models were developed to model project cost and time. The regression analysis showed that the project budgeted cost and planned project duration provide a good basis for estimating the cost and duration. The regression model results were validated by estimating the prediction error in percent and through conducting out-of-sample tests. In conclusion, the models were validated at a probability of 95%, at which the proposed models predict the project cost and duration at an error margin of ±0.035% of the actual cost and time.     

Predicting Cost Deviation in Reconstruction Projects: Artificial Neural Networks versus Regression

This paper investigates the challenging environment of reconstruction projects and describes the development of a predictive model of cost deviation in such high-risk projects. Based on a survey of construction professionals, information was obtained on the reasons behind cost overruns and poor quality from 50 reconstruction projects. For each project, the specific techniques used for project control were reported along with the actual cost deviation from planned values. Two indicators of cost deviation are used in this study: cost overrun to the owner, and the cost of rework to the contractor. Based on the information obtained, 36 factors were identified as having direct impact on the cost performance of reconstruction projects. Two techniques were then used to develop models for predicting cost deviation: statistical analysis, and artificial neural networks (ANNs). While both models had similar accuracy, the ANN model is more sensitive to a larger number of variables. Overall, this study contributes to a better understanding of the reasons for cost deviation in reconstruction projects and provides a decision support tool to quantify that deviation.     

Evaluation of Risk Factors Leading to Cost Overrun in Delivery of Highway Construction Projects

Accurate owner budget estimates are critical to the initial decision-to-build process for highway construction projects. However, transportation projects have historically experienced significant construction cost overruns from the time the decision to build has been taken by the owner. This paper addresses the problem of why highway projects overrun their predicted costs. It identifies the owner risk variables that contribute to significant cost overrun and then uses factor analysis, expert elicitation, and the nominal group technique to establish groups of importance ranked owner risks. Stepwise multivariate regression analysis is also used to investigate any correlation of the percentage of cost overrun with risks, together with attributes such as highway project type, indexed cost, geographic location, and project delivery method. The research results indicate a correlation between the reciprocal of project budget size and percentage cost overrun. This can be useful for owners in determining more realistic decision-to-build highway budget estimates by taking into account the economies of scale associated with larger projects.     

Impact of Optimism Bias Regarding Organizational Dynamics on Project Planning and Control

Schedule delays and cost overruns in large-scale construction projects are caused by a variety of reasons including unrealistic expectations at the planning stage. This paper examines, through computer simulation, the phenomenon of optimism bias regarding organizational dynamics as a potential cause for unrealistic expectations on schedules and budgets. A theoretical framework is introduced to examine how optimism bias regarding organizational dynamics can affect the performance of construction processes. A variety of “what-if” scenarios is tested, and based on our results, we claim that managers who maintain an unbiased attitude during project planning tend to outperform those having either an optimistic or a conservative approach. Therefore, we argue that developing an explicit method for analyzing and taking into account organizational dynamics would be a stepping stone toward adding more realism to construction planning and control practice.