Risk Allocation by Law—Cumulative Impact of Change Orders

Change, defined as any event that results in a modification of the original scope, execution time, or cost of work, is inevitable on most construction projects due to the uniqueness of each project and the limited resources of time and money available for planning. There are many factors that may cause a change such as design errors, design changes, additions to the scope, or unknown conditions in the field. For each change, contractors are entitled to an equitable adjustment to the base contract price and schedule for all productivity impacts associated with the change. The focus of this paper is to outline the types of changes that can occur on a construction project and also to spell out the financial recovery possibilities that exist for the contractor for each type of change. There are many historical and current court decisions that shape the outcomes of such claims and determine who holds the risks associated with various project changes. Also, an effective cumulative impact claim contains certain vital elements upon which the final outcome will be determined by the legal system. Last, there are certain actions that a contractor and owner can do to either enhance or mitigate the effectiveness of a potential cumulative impact claim.     

Quantitative Impacts of Project Change: Size Issues

Change has a tremendous effect on the performance of a construction project. Research that focuses on the quantitative impact is limited, incomplete, and in some cases questionable. The goals of this study were to quantify the nature and impacts of project change and develop recommended practices so that owners and contractors can manage change better. The focus was on project change during detailed design and construction, in particular the size of change and its impact on the project. These results show that the amount of change is negatively correlated with productivity and total installed project cost, whether within the design phase or construction phase, or between them. The greater the amount of change the more productivity and costs are degraded. Recommendations are also offered here on how to mitigate the impact of project change.     

Cumulative Effect of Project Changes for Electrical and Mechanical Construction

Change is inevitable on construction projects, primarily because of the uniqueness of each project and the limited resources of time and money that can be spent on planning, executing, and delivering the project. Change clauses, which authorize the owner to alter work performed by the contractor, are included in most construction contracts and provide a mechanism for equitable adjustment to the contract price and duration. Even so, owners and contractors do not always agree on the adjusted contract price or the time it will take to incorporate the change. What is needed is a method to quantify the impact that the adjustments required by the change will have on the changed and unchanged work. Owners and our legal system recognize that contractors have a right to an adjustment in contract price for owner changes, including the cost associated with materials, labor, lost profit, and increased overhead due to changes. However, the actions of a contractor can impact a project just as easily as those of an owner. A more complex issue is that of determining the cumulative impact that single or multiple change orders may have over the life of a project. This paper presents a method to quantify the cumulative impact on labor productivity for mechanical and electrical construction resulting from changes in the project. Statistical hypothesis testing and correlation analysis were made to identify factors that affect productivity loss resulting from change orders. A multiple regression model was developed to estimate the cumulative impact of change orders. The model includes six significant factors, namely: Percent change, change order processing time, overmanning, percentage of time the project manager spent on the project, percentage of the changes initiated by the owner, and whether the contractor tracks productivity or not. Sensitivity analysis was performed on the model to study the impact of one factor on the productivity loss (%delta). The model can be used proactively to determine the impacts that management decisions will have on the overall project productivity. They may also be used at the conclusion of the project as a dispute resolution tool. It should be noted that every project is unique, so these tools need to be applied with caution.     

Impact of Change Orders on Labor Efficiency for Electrical Construction

Change orders are a source of many disputes in today's construction industry. The issue at hand is whether or not the execution of change orders work has a negative impact on overall labor efficiency on a construction project. Previous literature demonstrates evidence that change orders affect labor efficiency. Attempts have been made to quantify these impacts by many researchers, with limited success. Using the electrical construction industry, a research study has been conducted to quantify the impacts of change orders on labor efficiency. In this paper, results of hypothesis testing and regression analysis are presented. A linear regression model that estimates the loss of efficiency, based on a number of independent variables, is also presented. The independent variables used in this model are (1) qualitative and quantitative criteria used to determine whether projects are impacted by changes or not; (2) the estimate of change order hours for the project as a percentage of the original estimate of work hours; (3) the estimate of change order hours for the project; and (4) the total number of years that the project manager had worked in the construction industry. Additional projects were used to validate the model, with an average error rate of 5%. The results of this research study are useful for owners, construction managers, general contractors, and electrical specialty contractors, because they provide a means to estimate the impact of a change order under certain project conditions. This research also identifies factors, which, when understood and effectively managed, may be used to mitigate the impact of a change order on project costs and efficiency.     

Impact of Change Orders on Labor Efficiency for Mechanical Construction

Change orders have become an everyday occurrence in construction. It is widely accepted by both owners and contractors that change orders have an effect on the labor efficiency, but these effects are difficult to quantify and frequently lead to disputes. Data from 61 mechanical construction projects were collected to develop a statistical model that estimates the actual amount of labor efficiency lost due to the change orders. The input variables needed in the model are as follows: (1) The original estimated labor hours; (2) impact classification; (3) total estimated change hours; (4) number of change orders; and (5) the timing of changes. The results of this study show that impacted projects have a larger decrease in labor efficiency than unimpacted projects. Additionally, the later a change order occurs in the life of a project the more impact it will have on the labor efficiency. The results appear to be consistent with the intuition of experienced professionals. Although each project has unique characteristics, the resultant model provides owners and contractors with a baseline measure of lost labor efficiency.     

Impact of Change Orders on Small Labor-Intensive Projects

In today’s construction, small projects can be just as important if not more important than the larger projects. However, small projects are usually fast track projects, which often involve overlapping design and construction time. Subsequent modifications may be required for the sections that are already under construction. These disruptions to the ongoing project are labeled as change orders. The impact due to changes has been described as the adverse effect upon the unchanged work due to changes in the contract. For this study, 34 projects were selected to develop a statistical model that estimates the amount of labor efficiency lost due to change orders for small projects. The variables in the final model are percent design related changes, percent owner initiated changes, the ratio of actual peak labor to estimated peak labor, the ratio of actual project duration to estimated project duration, and project manager’s percent time on the project. The results of this paper are of value to owners, electrical and mechanical contractors, and construction managers. The model quantifies the impact of change orders by introducing the most important variables that bring the largest disruptions.     

Quantifying Engineering Project Scope for Productivity Modeling

A poor scope definition in an engineering design project disrupts project rhythm, causes rework, increases project time and cost, and lowers the productivity and morale of the workforce. A quantitative measurement of the project scope is the basis for productivity modeling that involves the measurement, estimation, control, and evaluation of productivity. This paper proposes a conceptual model, the quantitative engineering project scope definition (QEPSD), to standardize the measurement of engineering project scope in construction projects, within a computer aided design environment. The QEPSD quantitatively measures engineering project scope, in terms of the complexity of design items by defining design categories and complexity functions appropriate to the particular discipline. The proposed method was originally verified and implemented specifically for steel drafting projects. Actual data was analyzed and used to demonstrate the benefits of historical data prepared using QEPSD for project scope definition. It was found that the new method led to increased utilization of previously untapped values in historical data, improving the accuracy of project scope definition, and productivity modeling. The paper concludes with a discussion of the potential benefits of adopting the QEPSD method, and its implications upon various project management functions.     

Frequency of Change Orders in Highway Construction Using Alternate Count-Data Modeling Methods

A common problem at state transportation agencies is the inability to complete projects within the original scope of work. Change orders, which are contractual documents issued to accommodate the additional work in a contract, are generally due to root causes such as design errors, unexpected site conditions, and weather conditions, and intermediate causes such as bidding characteristics. At the preaward phase of project management, an improved understanding of the factors that are associated with change orders will be of value and also can serve as a basis for taking steps to reduce concomitant contractual aberrations such as time delay and cost overruns. Recognizing that the occurrence of change orders is a count variable, this paper analyzes the frequency of change orders using a variety of count-modeling methods including the negative binomial, Poisson, zero-inflated negative binomial, and zero-inflated Poisson. Using 5 years of contract data from Indiana highway projects, appropriate models are estimated to assess the influence of project type, contract type, project duration, and project cost on the frequency of change orders.     

Can Design Improve Construction Safety?: Assessing the Impact of a Collaborative Safety-in-Design Process

This paper analyzes the impact of a large-scale safety-in-design initiative during the design and construction of a semiconductor manufacturing facility in the Pacific Northwest of the United States. Drawing on multiple data sources including individual interviews, group interviews, construction documentation, and an expert panel involved in the initiative, the writers identify 26 potential design changes on the project and assess the importance of timing, trade contractor involvement, and the type of design change in determining whether a proposed design change was ultimately integrated into the final construction plans. The writers further consider whether adopted design changes would have occurred in the absence of the safety-in-design initiative and whether the accepted design changes ultimately impacted construction site safety on the project. This analysis of a full-scale safety-in-design initiative provides important insights into how injury prevention efforts in the construction industry can begin upstream by involving designers, engineers, and trade contractors in preconstruction processes.     

Benchmarking Productivity Indicators for Electrical/Mechanical Projects

Labor-intensive industries such as the electrical and mechanical trades are considered high risk due to the high percentage of labor costs. Because of this high risk, it is important for contractors in these industries to closely track labor costs on projects and compare these costs to industry benchmarks. In this paper, benchmark indicators for these industries are established on the basis of actual project data. These benchmarks include the relationship between the percent complete or percent time and cumulative work hours or cost, project size and duration, project size and average man power, project size and peak man power, and average versus peak man power. These relationships were developed using regression analysis. Man power loading charts and the related S-curves were developed from actual project data. The man power loading charts and the related S-curves are useful for resource planning and for tracking progress on a construction project. They can be used to show the cause-and-effect relationship between projects impacted by outside factors and normal labor productivity.     

Decision Tree Approach to Classify and Quantify Cumulative Impact of Change Orders on Productivity

Multiple or unusual change orders often cause productivity losses through a “ripple effect” or “cumulative impact” of changes. Many courts and administrative boards recognize that there is cumulative impact above and beyond the change itself. However, determination of the impact and its cost is difficult due to the interconnected nature of construction work and the difficulty in isolating causal factors and their effects. As a result, it is very difficult for owners and contractors to agree on equitable adjustments for the cumulative impact. What is needed is a reliable method (model) to identify and quantify the loss of productivity caused by the cumulative impact of change orders. A number of studies have attempted to quantify the impact of change orders on the project costs and schedule. Many of these attempted to develop regression models to quantify the loss. However, traditional regression analysis has shortcomings in dealing with highly correlated multivariable data. Moreover, regression analysis has shown limited success when dealing with many qualitative or noisy input factors. Classification and regression tree methods have the ability to deal with these complex multifactor modeling problems. This study develops decision tree models to classify and quantify the labor productivity losses that are caused by the cumulative impact of change orders for electrical and mechanical projects. The results show that decision tree models give significantly improved results for classification and quantification compared to traditional statistical methods in the field of construction productivity data analysis, which is characterized by noisiness and uncertainty.     

Impact of Change’s Timing on Labor Productivity

There are many types of construction changes and each type can have an effect on labor productivity. To a certain extent though the specific type of change is not as important as the mere presence of the change and, as analyzed in this paper, the timing of that change. The research reported in this paper reaffirms that project change is disruptive and detrimental to labor productivity. Data from 162 construction projects were statistically analyzed and a series of three curves are presented in this paper, representing the impact that change has on the labor productivity for early, normal, and late timing situations. The projects are a representative sample of the industry, involving a wide range of sizes, different delivery systems, and industry sectors. Late change is more disruptive of project productivity than early change, all other things being equal. The implications and benefits of this research are clear: if changes are necessary, they should be recognized and incorporated as early as possible. Practitioners can use these data and curves for either forward pricing or retrospective pricing of changes. Other researchers can use these findings to test their own findings and to explore timing issues in further detail.     

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.     

Improved Measured Mile Analysis Technique

Quantifying lost labor productivity on construction projects is difficult and sometimes subjective. A widely accepted way to quantify losses is the “measured mile” approach. It compares periods of a project that have been impacted by change to those that have not been impacted. As currently practiced the measured mile relies on subjectively identifying that reference period. In this paper the measured mile and a variant, the baseline method, are analyzed and compared to a new, proposed statistical clustering method. This new approach is advocated because it determines its reference period using objective criteria. A case study is included to show how the three methods work, and advantages and disadvantages of each method are presented in this paper.     

Model for Quantifying the Impact of Change Orders on Project Cost for U.S. Roadwork Construction

Change orders are very common in almost every construction project nowadays, often resulting in increases of 5–10% in the contract price. Understanding the consequences of such trends, several studies have attempted to quantify the impact of change orders on the project cost. Most of the studies aimed at the quantification of the change orders were sponsored by contractors’ organizations, where statistical models used to quantify the impact of the change orders on the project cost were based on data supplied by the contractors; a situation that can lead to owner-contractor disagreements related to the quantification method used. In addition, most of the studies tackled commercial and electromechanical work, and very rare studies tackled the field of heavy construction; a field that suffers from change orders because of errors and omissions, scope of work changes, or changes because of unforeseen conditions. This study addresses the need for a statistical model to quantify the increase of the contract price due to change orders in heavy construction projects in Florida. The model is based on data collected from 16 Florida DOT projects with contract values that ranged between $10–$25 million, and that encountered an increase in the contract price from 0.01 to 15%. Eleven variables were analyzed to test their impact on the cost of the change orders. The study concluded that most significant variables that impact the value of the change order, which are (1) the timing of the change order and (2) when the reason for issuing the change order is unforeseen conditions. Two regression models are developed and validated as follows: (1) a model to quantify the percentage increase in the contract price due to the change orders that increase the contract price from 0.01 to 5% and (2) a model to quantify the percentage increase in the contract price due to the change orders that increase the contract price from 5 to 15%. Those models will provide the owner with a retrospective or forward pricing of the change orders, and hence, allow the owner to estimate and utilize contingency amounts.     

Simulating Learning Dynamics in Project Networks

In this paper we develop a multiagent simulation model to explore the impact of learning dynamics on the productive implementation of innovations in project networks comprised of designers and contractors. Though researchers generally agree that when firms form into networks they will gain access to new knowledge, the question of learning beyond the firm at the boundaries between firms or at the level of the project network itself remain less explored. We simulate the impact of task interdependence and relational instability on learning in project networks comprised of multiple specialist firms. We find that relational instability in project networks slows learning and task interdependence moderates the impact of increasing relational instability on network productivity rates. The findings have significant implications for interorganizational learning theory. The simulation results provide insights into appropriate firm-level and project network-level strategies for change.     

Causes of Variation in Construction Project Task Starting Times and Duration

In this research, variation is defined as the time difference between what was planned and what actually happened in terms of task starting times and duration. Variation in construction tasks is important as it can impact productivity performance. Construction projects consist of a large number of interdependent tasks. When the starting time and/or duration of one task varies, it can affect other downstream tasks and result in disruptions to the schedule and/or decreased productivity. The construction process is complex and involves numerous people with different levels of responsibility, which makes identifying the root causes of the variation difficult. A nationwide survey was administered to workers, foremen, and project managers to identify the most prevalent causes and magnitude of both starting time and task duration variation. Fifty individual causes of variation were divided into eight categories: prerequisite work, detailed design/working method, labor force, tools and equipment, material and components, work/job site conditions, management/supervision/information flow, and weather or external conditions. This research examined the similarities and differences in perceptions between craft workers, foremen, and project managers in terms of starting time and task duration variation. The top eight causes of starting time variation and top nine causes of task duration variation were identified. The research also quantitatively analyzed the underlying structure of the causes of variation using factor analysis. This was done by grouping the 50 individual causes into nine orthogonal factors that represent the underlying structure of the affecting causes. The findings will help construction project managers and field managers focus on the root causes of variation during planning in order to develop effective strategies to reduce variation and improve project productivity performance.     

Contractor Prebid Planning Principles

Planning is an essential function of project management. Yet, many small- and medium-sized contractors do a relatively poor job of operational planning. Better prebid plans will reduce costs, shorten schedules, and improve labor productivity. Unfortunately, the published literature offers little guidance for smaller contractors on what constitutes effective planning. Most papers describe planning as a macrolevel process for owners. Most emphasize scope definition for industrial projects. This paper describes a microlevel planning process for contractors. It consists of eight steps which are: (1) assess contract risks; (2) develop a preliminary execution plan; (3) develop site layout plans; (4) identify the sequences that are essential-to-success; (5) develop detailed operational plans; (6) develop proactive strategies to assure construction input into design; (7) revise the preliminary plan; and (8) communicate and enforce the plan. The entire process is illustrated with a case study project and is fully illustrated with figures which show how to integrate the work of multiple contractors, keep key resources (crews or equipment) fully engaged with no downtime, provide time buffers so the work of follow on crews can be efficiently done, expedite the schedule using multiple work stations and concurrent work, ways to communicate the work plan to the superintendent and foremen, and how to assess the feasibility of various work methods. The steps are easy to understand and implement. They will yield immediate positive results.     

Here Comes the Judge—Duties and Responsibilities of Design Professionals When Deciding Disputes

Frequently during the progression of a construction project, the design professional is forced into the role of a judge of project disputes between the owner and contractor. These disputes generally involve substantial claims for extra compensation or extra time and have significant impact on the owner and contractor’s financial position on the project. The architect or engineer will be pressured by the owner, who controls whether the design professional gets paid. The contractor, however, may threaten to pursue legal claims against design professionals if they make the contractor’s job more expensive or fail to give it the appropriate time extension. In many cases, design professionals must admit or deny whether their services were defective in some nature. In addition to these pressures, the design professional is not necessarily trained or comfortable with acting as a judge and interpreting the meaning of contract terms. Generally, when an architect or engineer performs this judicial function, they are immune from any liability for the results of decisions. However, the design professional must make the decision in good faith and with impartiality. In addition, design professionals must only decide those matters that their contract obligates design professionals to decide. This paper will address the nature of the designer’s role as judge and the limits of the designer’s immunity with respect to the designer’s contract obligations and good faith and impartiality requirements.