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.     

Effect of Preconstruction Planning Effort on Sheet Metal Project Performance

The complexity of construction industry requires the identification of work tasks and the coordination of interactions among them. As a result, construction planning is considered to be one of the most critical steps toward success and is the main focus of past research. Consequently, little research has been performed regarding the preconstruction planning, which is the planning completed by the contractor in the period between project award and project execution. This paper focuses on sheet metal preconstruction planning, primarily that of mechanical and heating ventilations and air conditioning contractors. The research was completed in three phases: phase one gathered data on the current state of preconstruction planning, phase two developed a model sheet metal preconstruction planning process to be used by sheet metal contractors, and phase three validated the model preconstruction planning process. Based on project data collected for this research, projects that used a planning process similar to the model process performed more successfully—they achieved an average profit margin of 23% while projects that were poorly planned experienced an average profit margin of ?3%.     

Labor Performance Analysis for Microtunneling Projects

Microtunneling projects have special process characteristics. The production time of microtunneling projects is needed for project estimating and scheduling. The production time has three basic components: (1) preparation times for pipe segments; (2) preparation times; and (3) delay times. Real project data were collected from 35 projects to predict the time needed for pipe segment preparation. A probabilistic distribution technique was used to predict the preparation times for pipe segments. Various numbers of probabilistic distributions were tested against the data. A log-logistic distribution was selected to represent the preparation time’s probability for a pipe in microtunneling projects. Preparation times for high, medium, and low performance contractors were predicted. By enhancing the estimation process of the microtunneling projects, contractors can use this paper in predicting the preparation time for pipe segments, which represents the crew (or crew’s) productivity.     

Optimum Planning of Highway Construction under A + B Bidding Method

In recent years, many departments of transportation in the United States have started to apply the A + B bidding method in highway projects in order to reduce construction time and minimize its associated traffic congestion and adverse impact on local economies. The application of this method places an increased pressure on contractors to minimize both the time and cost of highway construction. This paper presents a practical model for optimizing resource utilization in highway projects that utilize the A + B bidding method. The model is designed to minimize the total combined bid by identifying the optimum crew formation and the optimum level of crew work continuity for each activity in the project. The model is developed using a dynamic programming formulation and is incorporated in a Windows application that provides a user-friendly interface to facilitate the optimization analysis. An application example of a highway project is analyzed to illustrate the use of the model and to demonstrate its capabilities.     

Conceptual Planning Process for Electrical Construction

The competitive nature of the construction industry has motivated many specialty contractors to search for ways to improve efficiency by increasing their quality and decreasing their costs in order to strengthen their market share. As a result, contractors are turning to “better planning” as a method for improving their efficiency and, consequently, increasing their profitability. In fact, a consensus exists in the construction industry that more formalized preconstruction planning is necessary to remain successful in an increasingly competitive industry. This paper presents a model electrical preconstruction planning process that was crafted from outstanding processes used on several successful electrical projects. Furthermore, a method to evaluate the effectiveness of planning, by comparing actual planning to the model process, is briefly introduced. From this assessment, “effective planning” was correlated to project outcome, and evidence is provided that better planning is, indeed, related to successful performance.     

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.     

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.     

WorkPlan: Constraint-Based Database for Work Package Scheduling

A database program called WorkPlan has been created to systematically develop weekly work plans. Such work plans are used by crew foremen in scheduling work packages and allocating available labor and equipment resources. WorkPlan adopts the Last Planner methodology, which implements several lean construction techniques. A week prior to conducting work, WorkPlan guides the user step by step through the process of spelling out work packages, identifying constraints, checking constraint satisfaction, releasing work packages, and allocating resources; then at the end of the week, collecting field progress data and reasons for plan failure. This systematic approach helps the user create quality work plans and learn from understanding reasons for failure. The lean planning philosophy underlying WorkPlan and the functionality of the computer program implementation are detailed in this paper. Various ways of displaying work package data are illustrated. WorkPlan's job-shop scheduling view complements the view traditionally adopted by project management, as is reflected in scheduling tools using the critical-path method.     

Transaction-Cost-Based Selection of Appropriate General Contractor-Subcontractor Relationship Type

Relationships between general contractors and subcontractors are generally formed on a project-by-project basis. However, because of the competitive nature of the construction industry, this traditional arrangement can result in adversarial relationships between general contractors and subcontractors, which can jeopardize potential or ongoing collaborative construction plans. To avoid this problem, close, long-term relationships between general contractors and subcontractors, as in strategic partnerships, must be established. Unfortunately, forming and sustaining such relationships can be time-consuming and cost-intensive. Furthermore, this type of relationship does not necessarily enhance cooperation or work performance. For contractors to successfully establish effective partnerships with their subcontractors, they must select the appropriate relationship by considering the different characteristics of the subcontracted work involved. Based on transaction cost theory, the findings of this study show that transaction costs incurred by general contractors and subcontractors vary according to the type of relationship established. Therefore, for the purpose of comparing transaction costs incurred in both competitive and partnership relationships, transaction-cost-based profit models for both general contractors and subcontractors are developed, respectively, for each relationship type. As well, by applying different strategies to maximize profits in each relationship, and by simulating the parameters affecting the nature of the subcontracted work, the conditions and relationships under which general contractors’ profits are optimized have been determined. Finally, based on simulation, practical guidelines for choosing the most appropriate relationship type are proposed.     

Stochastic Modeling for Pavement Warranty Cost Estimation

This paper presents a cost estimation model for long-term pavement warranties with multiple distress indicators. One application area for such warranties involves performance-based specifications (PBSs). In contrast to traditional approaches, PBS gives contractors the flexibility to select construction methods, materials, and even design. However, the contractors then must warrant the performance of their work for a specified period of time. Therefore, an accurate estimation of the risks associated with the warranty is a significant cost issue for any contractor to cover potential risks while still being competitive in bidding. Quantitative evaluation of the cost of risk incurred by the warranty has several difficulties. The deterioration of a highway project is a complex process, which is affected by pavement structure, material, traffic load, and weather conditions. Based on a probabilistic risk analysis of failures of performance indicators, the resulting model can estimate the warranty cost at a detailed level. The application of the model has been demonstrated via a numerical case study using long-term pavement performance data.     

Proposed Subcontractor-Based Employee Motivational Model

The intent of this research was to identify the factors that promote positive motivational behavior in construction subcontractor crews. The factors affecting motivation, goal-setting, workforce needs, and incentives were investigated to determine the attributes for a subcontractor employee motivational model. A survey addressing these four categories was distributed to subcontractor foremen and supervisors to establish a list of motivational factors. The statistical analysis of the survey results aided in the final development of the proposed subcontractor based employee motivational model, which includes such components as confidence and competence as being reinforced by quality of work, incentives, safe performance, praise, and a sense of belonging. The proposed model provides industry practitioners with another level of understanding of the motivation sequence of the subcontractor’s labor force. Perhaps the most interesting finding was related to the attributes found in relation to workforce needs. A common link “feeling of being a member of the team/crew” was discovered between “praise” and “job security.” It was surmised that essentially a worker must first receive praise before they feel as if they are a member of the team/crew and once they feel like a member of the team, they then begin to acquire feelings of job security. The results of this study further reinforce the findings of several previous behavioral studies. Future research should attempt to validate the model using a larger sample size incorporating multiple general contractors.     

Labor Productivity Drivers and Opportunities in the Construction Industry

The study of labor productivity in the construction industry is gaining increasing attention as the industry faces multiple problems related to its workforce. This paper presents the results of a survey instrument applied to determine the relative level of relevance of construction labor productivity drivers and opportunities. Owners, general contractors, electrical contractors, mechanical contractors, consultants, and others participated in this survey. Management skills and manpower issues were identified as the two areas with the greatest potential to affect productivity according to survey respondents. Surprisingly, external factors, which are often cited as a major cause for reduced productivity in the construction industry, were considered to be one of the least relevant productivity drivers. These results suggest that respondents consider the improvement of labor productivity within their reach and control rather than determined by external conditions.     

Quantitative Definition of Projects Impacted by 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. Change may occur on a project for a number of reasons, such as design errors, design changes, additions to the scope, or unknown conditions. 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. Changes may or may not have an impact on labor productivity. Existing literature uses subjective evaluation to determine whether the project is impacted. Projects impacted by change cause the contractor to achieve a lower productivity level than planned. The focus of this paper is to quantify whether an electrical or mechanical project is impacted by a change order. Through statistical hypothesis testing, groups of factors that correlate with whether a project is impacted by change orders were identified and used to develop a quantitative definition of impact. Logistic regression techniques were used to develop models that predict the probability of a project being impacted. The results of this research show that percent change, type of trade, estimated and actual peak manpower, processing time of change, overtime, overmanning, and percent change related to design issues are the main factors contributing to the project impact.     

Enhancing Financial Success Among Electrical Contractors

This paper provides electrical contractors with significant information related to enhancing company financial performance. The methodology involves understanding the determinants of contractor financial success through: (1) an extensive literature review; (2) collection of financial- and management-related data from electrical contractors; and (3) analysis of data to identify management trends that are more prevalent in profitable firms. Ninety-six usable responses were collected from small, medium, and larger electrical contracting companies. General trends reveal that more profitable firms place greater emphasis in the areas of certain management initiatives (higher lines of credit and supporting continuing education), marketing initiatives (involvement in formal alliances and partnering), and technology initiatives related to spending more capital resources on computers and software. Significant differences are revealed with financial ratios as well. A Financial Success Scorecard is created for firms to compare their management inputs to those of successful firms. Findings from this study could provide helpful guidelines for nonelectrical contracting firms. Recommendations for achieving future financial success are also provided.     

Optimal Planning and Scheduling for Repetitive Construction Projects

This paper presents a multiobjective optimization model for the planning and scheduling of repetitive construction projects. The model enables construction planners to generate and evaluate optimal construction plans that minimize project duration and maximize crew work continuity, simultaneously. The computations in the present model are organized in three major modules: scheduling, optimization, and ranking modules. First, the scheduling module uses a resource-driven scheduling algorithm to develop practical schedules for repetitive construction projects. Second, the optimization module utilizes multiobjective genetic algorithms to search for and identify feasible construction plans that establish optimal tradeoffs between project duration and crew work continuity. Third, the ranking module uses multiattribute utility theory to rank the generated plans in order to facilitate the selection and execution of the best overall plan for the project being considered. An application example is analyzed to illustrate the use of the model demonstrate its new capabilities in optimizing the planning and scheduling of repetitive construction projects.     

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.     

Model for Predicting the Performance of Project Managers at the Construction Phase of Mass House Building Projects

The need to match project managers’ (PMs) performance measures onto projects of both unique and similar characteristics has long since been acknowledged by researchers. The need for these measures to reflect the various phases of the project life cycle has also been contended in the recent past. Here, a competency-based multidimensional conceptual model is proposed for mass house building projects (MHBPs). The model reflects both performance behaviors and outcome in predicting the PMs’ performances at the conceptual, planning, design, tender, construction, and operational phases of the project life cycle. Adopting a positivist approach, data elicited for the construction phase is analyzed using multiple regression techniques (stepwise selection). Out of a broad range of behavioral metrics identified as the independent variables, the findings suggest the best predictors of PMs’ performances in MHBPs at the construction phase are: job knowledge in site layout techniques for repetitive construction works; dedication in helping works contractors achieve works schedule; job knowledge of appropriate technology transfer for repetitive construction works; effective time management practices on house units; ability to provide effective solution to conflicts, simultaneously maintaining good relationships; ease with which works contractors are able to approach the PM and volunteering to help works contractors solve personal problems. ANOVA, multicollineriality, Durbin–Watson, and residual analysis, confirm the goodness of fit. Validation of the model also reflected reasonably high predictive accuracy suggesting the findings could be generalized. These results indicate that the model can be a reliable tool for predicting the performance of PMs in MHBPs.     

Parade Game: Impact of Work Flow Variability on Trade Performance

The Parade Game illustrates the impact work flow variability has on the performance of construction trades and their successors. The game consists of simulating a construction process in which resources produced by one trade are prerequisite to work performed by the next trade. Production-level detail, describing resources being passed from one trade to the next, illustrates that throughput will be reduced, project completion delayed, and waste increased by variations in flow. The game shows that it is possible to reduce waste and shorten project duration by reducing the variability in work flow between trades. Basic production management concepts are thus applied to construction management. They highlight two shortcomings of using the critical-path method for field-level planning: The critical-path method makes modeling the dependence of ongoing activities between trades or with operations unwieldy and it does not explicitly represent variability. The Parade Game can be played in a classroom setting either by hand or using a computer. Computer simulation enables students to experiment with numerous alternatives to sharpen their intuition regarding variability, process throughput, buffers, productivity, and crew sizing. Managers interested in schedule compression will benefit from understanding work flow variability's impact on succeeding trade performance.     

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.