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Identifying Early Indicators of Manageable Rework Causes and Selecting Their Mitigating Construction Best Practices

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Elnaz Safapour, S.M.ASCE1 and Sharareh Kermanshachi, Ph.D., P.E., M.ASCE2

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Ph.D. Student, Department of Civil Engineering, University of Texas at Arlington, 425 Nedderman Hall, 416 Yates Street, Arlington, TX 76019. E-mail: [email protected]

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(Corresponding author) Assistant Professor, Department of Civil Engineering, University of Texas at Arlington, 425 Nedderman Hall, 416 Yates Street, Box 19308, Arlington, TX 76019. E-mail: [email protected]

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ABSTRACT

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Many large-scale construction projects suffer from the issuance of rework that ultimately leads to

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substantial cost overruns and major scheduling delays. Scholars and practitioners worldwide have

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assessed the impact of these changes and the critical causes behind them, and found it difficult to

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mitigate after the rework has occurred. Thus, it is important to identify the early indicators of

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manageable rework causes and implement the appropriate mitigating strategies prior to their

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occurrence. Therefore, the aim of this study is to identify indicators of manageable rework causes

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(IMRCs) and select the appropriate construction Best Practices (BPs) in order to reduce the value

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of manageable and controllable rework. To fulfill the objectives of this study, 51 manageable

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causes of rework were identified through a comprehensive literature review. According to the

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nature of BPs, the identified IMRCs were classified into three main categories: organization,

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project, and people. Then, 44 case study projects were collected and analyzed. As information

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regarding other aspects of the projects was required for this study, a questionnaire survey was

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developed and conducted to collect data from the construction projects. For this purpose, a

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representative from each stated project was selected and asked to fill out the survey. Finally, 32

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significant IMRCs, belonging to 13 attributes, were determined. The project management team

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(PMT) is commonly responsible for preparing the plan, building an effective team, and monitoring

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the process; therefore, the experience of the PMT in the design and/or construction phase, and

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number of PMTs who work in a construction project are the most important indicators and record

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the highest weights in deriving rework. Next, all of the identified BPs by Construction Industry

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Institute (CII) were investigated and among them, 10 BPs were found significantly beneficial to

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decrease the value of rework associated with IMRCs. The implementation of Front-End Planning

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determines the feasibility of a project and evaluation of the conceptual scope during the

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preplanning phase; thus, the design errors that are due to challenges regarding finance and scope

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attributes can be decreased. The outcomes of this study will help stakeholders and project

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managers (PMs) identify the indicators of rework early in construction projects and select the

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appropriate BPs, thereby reducing the extra cost of rework and improving the project time and cost

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performance.

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INTRODUCTION

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Change orders due to design errors and modifications are common and almost inevitable in all

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types of construction projects (Li and Taylor 2014). They affect the cost of a project, create

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scheduling delays, and decrease productivity (Love 2002; Arashpour et al. 2014; Li and Taylor

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2014). Therefore, rework plays an important role in a project’s success or failure. Because of the

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uniqueness of the budget and schedule estimation of each construction project, as well as the

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availability of resources for planning, such as time, money and work force, change orders and

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rework vary significantly from project to project. Taylor and Ford (2006) defined rework as “work

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discovered to require change (either through errors, omissions, or regulation changes).”According

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to the Love’s and Facade’s studies, the total values of rework in civil infrastructure projects were

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found to be 10.29% (Love et al. 2010), and 16.5% (Forcada et al. 2017a) of the contract value.

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Hence, it is critical to identify the root causes of rework and manage them to reduce their

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unfavorable impact on the execution of construction projects (Love and Smith 2003; Zhang et al.

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2012; Palaneeswaran et al. 2014; Dehghan and Ruwnapura 2014).

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Best practice strategies can improve the performance of construction projects and can assist in

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effectively managing large-scale projects (CII 2012). The Construction Industry Institute (CII)

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explained BP as “a process or method that leads to enhanced project performance, when executed

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effectively.” CII (2012) defined and introduced the following fourteen BPs: Front-End Planning,

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Alignment, Constructability, Materials Management, Planning for Start-up, Team Building,

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Partnering, Quality Management, Lessons Learned, Benchmarking and Metrics, Change

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Management, Dispute Prevention and Resolution, Project Risk Assessment, and Zero Accidents

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and Techniques. As the Planning for Start-Up strategy is commonly implemented when a project

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is almost completed (CII 2012), it does not significantly contribute to the management and

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reduction of the rework workload and was not included in this study. In addition, as the purpose

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of implementing the Benchmarking and Metrics strategy is to measure the utilization of CII best

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practices according to the measured project performance (CII 2012), it does not help with the

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management and reduction of the rework workload according to the presented IMRCs in a project,

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and was therefore excluded from this study. Change Management was likewise excluded because

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its implementation directly affects all aspects of change orders and rework. In summary, all of the

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BPs, which could potentially reduce the value of rework, were investigated to determine their

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impact on the reduction of the value of manageable design changes in construction projects.

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In this study, through a comprehensive literature review, 51 manageable causes of rework were

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identified according to the studies of Hsieh et al. (2004); Kean et al. (2010); Love et al. (2012),

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Forcada et al. (2014); Karthick et al. (2015); Ye et al. (2015). Based on the CII comprehensive

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research (CII 2012), among the identified manageable causes of rework, 35 were found

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manageable by implementing BPs during the execution of a construction project. The remaining

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causes of rework were mostly out of control (e.g. weather condition), and need more resources and

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allocations to be managed (e.g. owner’s change of schedule due to financial problems).

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According to the research conducted by the Construction Industry Institute (CII 2012), the

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implementation of BPs assists in the management of characteristics associated with organizations,

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projects, and team members. Inspired by works of Love et al. (2012) and Forcada et al. (2014), the

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prepared list of manageable causes of rework was classified into three main categories:

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organization, project, and people.

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As the overall goal of this study is to determine IMRCs, and investigate how implementation of

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appropriate best practices reduces value of rework associated with challenges of IMRCs in

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construction projects; therefore, this study seeks to answer the following questions:

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Q1. What are the early indicators of manageable rework causes?

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Q2. What are the appropriate best practices to reduce the value of rework associated with

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indicators of manageable rework causes?

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The following objectives were formulated to answer the research questions:(1) identify potential

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IMRCs through existing literature;(2) classify the identified IMRCs based on the previous

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studies;(3) determine significant IMRCs using statistical methods;(4) investigate the benefits of

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implementing each best practice in addressing the issues of IMRCs; and (5) calculate how much

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each BP contribute to the reduction in the value of rework.

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In summary, the ability to predict design changes early in construction projects offers significant

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benefits to industry practitioners, specifically stakeholders (i.e., owners, engineers, and

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contractors) and project managers. Furthermore, implementing the appropriate best practices at the

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right time assists in the management of undesired consequences and enables the reduction of the

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dollar value of the rework. For instance, the scope of a large-scale project is commonly complex,

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and precise clarification of the project’s scope occurs in the construction phase. Therefore, owner

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entities can allocate sufficient funds in the preplanning phase to implement the appropriate

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strategy. Implementing a suitable strategy results in early clarification of a project’s scope and

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helps reduce the rework of a project. As another example, when designers lack sufficient skills in

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new technology, implementing an appropriate strategy might be beneficial for the prevention of

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design errors.

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The paper is organized as follows. First, a literature review is presented. The research approach

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for this study is then described, with a detailed description of case studies and data collection from

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44 construction projects. Then, the process and result of the descriptive data analysis is described.

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The procedure of how significant IMRCs were determined is discussed and presented. Next,

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research findings are discussed to depict how implementation of best practices manages the value

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of rework associated with IMRCs. Lastly, verification of the outcomes of this study is described.

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LITERATURE REVIEW

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There are several definitions and interpretations of rework in existing literature in the area of

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construction management (Love 2002). CII (2001) characterized rework in the construction phase

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as activities that have to be done more than once, or activities that remove previous work installed

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as part of a project. Similarly, Josephson at al. (2002) defined rework as useless output that

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commonly occurs due to mistake through execution of a construction project.

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Investigation of root causes of rework assists in managing them effectively (Hwang et al. 2009).

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Many studies have been conducted worldwide to investigate the root causes of rework and their

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unfavorable consequences on construction projects (Hwang et al. 2009; Love et al. 2010, 2016a;

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Ye et al. 2015, Forcada et al. 2017b). According to the previous studies, the causes of rework were

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mainly classified as constructability (Feng 2009); material supply (Hwang and Ho 2012; London

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and Singh 2013); project management team (Arashpour et al. 2012); skill (Arashpour and

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Arashpour 2011); and project scope (Tuholski 2008). Love et al. (2012) and Forcada et al. (2014)

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concluded that there are potential latent problems inherent in project systems, such as

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organizational issues (e.g. lack of quality management), project issues (e.g. definition of scope),

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and individual issues (e.g. work experience of staff). The mentioned authors also found that these

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issues could set the stage for designers to make mistakes. Love et al. (2012) labeled the established

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orthodoxy as people, organization, and project systems. These nomenclatures highlighted the

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process that enables the mapping of dependencies that affect error prevention. This mapping aids

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prevention of design errors.

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The procedure of rework assessment and management are usually time consuming and leading

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cost overruns if it is not well organized at the appropriate time. As complexity in modern

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construction projects increases, the stricter rework assessment and management are required in

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order to minimize schedule delays and cost overruns. (Love et al. 2015; Love et al. 2016a, 2016b).

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Zaneldin (2000) explained that through the early stage of a design phase, change orders (rework)

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might be issued with minimum cost overruns. Lack of familiarity with ways to manage change

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orders (rework) appropriately often leads to serious schedule delays and cost overruns (Alnuaimi

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et al. 2010). Therefore, change orders (rework) are easier to manage during the earlier phases,

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because, to put it simply, they make it possible to avoid modifications (Arain and Pheng 2007;

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Love et al. 2015; Du et al. 2016). Palaneeswaran et al. (2014) stated that a systematic design audit

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for construction projects would be most effective for reducing the number of reworks. Zhang et al.

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(2012) generated a model to reduce rework that focused on managing a continuous improvement

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loop in four main stages: (1) rework tracking and cause classification, (2) evaluation of rework

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and its causes, (3) corrective action planning, and (4) integration of changes into the total

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management system.

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Furthermore, as mentioned earlier, several strategies have been introduced by CII to practitioners

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and scholars to enhance project performance and reduce change orders. In this regard, many

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significant studies have been conducted to investigate the impact of implementing single or

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multiple BPs in order to improve the management of construction projects (CII 2012; Akpan et al.

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2014; Du et al. 2016; and Safapour et al. 2017). Although implementation of all best practices is

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beneficial for enhancing project performance, it is not feasible (Safapour et al. 2017). There is a

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gap of information pertaining to how to select the appropriate strategies based on the indicators of

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manageable rework causes in construction projects. Therefore, a thorough investigation and

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analysis of how to utilize the construction best practices in construction projects is needed.

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Thus, the focus of this study is to determine IMRCs, and to define the benefits of adoption of BPs

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in decreasing the value of rework due to challenges associated with IMRCs. For this purpose, as

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stated earlier, the appropriate and related best practices for mitigating IMRCs were selected. The

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definitions of these BPs were stated in Table 1.

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Table 1. List of Construction Best Practices with Their Definition

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RESEARCH METHODOLOGY

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To fulfill the objectives of this study, a seven-step research methodology was developed and

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implemented, as shown in Fig. 1. This study was initiated with a comprehensive review of

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literature to identify potential indicators of rework causes (IMRCs) that can be managed through

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implementation of the construction best practices. These early indicators were then classified

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according to the previous studies. In the third step, 44 case studies of construction projects were

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collected. As information regarding other aspects of the projects was needed for this study, a

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structured questionnaire was developed to collect the required information (e.g., dollar value of 7

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rework, implementing level of best practice strategies) from the stated projects. A descriptive data

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analysis was conducted in the next step. In step 5, quantitative analyses were performed to

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determine the IMRCs.

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Fig. 1. Research methodology approach

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Depending on the type of data that was collected from the survey, different statistical tests were

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utilized. Table 2 summarizes the basic formal statistical methods that were used for the quantitative

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analysis in this study. In the last step, the appropriate BPs were investigated and determined. The

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weight of each early indicator of manageable rework causes was then identified, using Cohen’s d

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method.

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Cohen’s d parameter (Cohen 1988) was applied to investigate the extent of each manageable

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rework indicator. Cohen’s d yields information about the difference in the means of two sample

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groups, divided by standard deviations. The raw data for the two sample groups was used to

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formulate the following equation for the two-sample t-test: M2 −M1

Cohen′ s d =

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SDpooled

(1)

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where M1 and M2 are the mean difference of two sample groups (dollar value of rework which is

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associated with significant manageable rework indicators by two-sample t-test), respectively, and

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the denominator is pooled standard deviation. SDpooled = √

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(n1 −1)SD21 +(n2 −1)SD22 n1 +n2 −2

(2)

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According to equation (2), SD1 and SD2 correspond to standard deviation of the first and second

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groups, respectively. In addition, n1 and n2 are related to the first and second sample sizes,

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respectively.

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Table 2. Statistical Analysis Methods

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Step 6 of this study was divided into two sub-steps: Step 6a and Step 6b. In Step 6a, the significant

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best practices were determined to reduce the dollar value of design changes and/or modifications.

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In Step 6b, the total weight of each best practice associated with attributes of indicators of

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manageable rework causes were recorded and presented. In the last step, two case study projects

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were utilized to measure the reduction in the value of rework by implementing BPs.

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STEP 2: IDENTIFY AND CLASSIFY POTENTIAL MANAGEABLE REWORK INDICATORS

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Fifty-one (51) manageable causes of rework were identified from previous studies, as mentioned

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earlier. According to the study of CII (2012), among these causes, 35 were found to be manageable

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by implementing the best practices. Then, the IMRCs were classified into three main categories

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(organization, project, and people). These nomenclatures were selected based on the nature of the

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BPs to manage a project’s characteristics associated with organization, project, and team members

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that were thoroughly described in CII research (2012) and inspired by studies conducted by Love

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et al. (2012), and Forcada et al. (2014).

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Next, inspired by previous studies (Hsieh et al. 2004; Love et al. 2008, Sun and Meng 2009; Love

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et al. 2012; Ye et al. 2015), the three mentioned categories were classified into thirteen attributes,

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as shown in Fig. 2. These classifications and attributes led to substantial progress in understanding

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IMRCs. Consequently, this clarification assists in the prevention of design errors.

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Fig. 2. Classification of indicators of manageable rework causes

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As illustrated in Fig. 2, the IMRCs in the organization category were classified into bureaucracy,

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participant, and communication attributes. Similarly, the IMRCs in the project category were

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classified into management team, location, design and technology, material resources, scope,

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partnership, and finance attributes. The indicators in the category of people were classified into

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skill, field craft experience, and socio-culture attributes. As stated earlier, the purpose of selecting

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an appropriate terminology for the attributes was to make the IMRCs more understandable in order 9

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to facilitate greater reduction in the value of rework. For instance, the terminology of design and

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technology was selected because design and technology management is an important factor

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influencing rework in construction projects (Hwang et al. 2009). The other attribute is socio-

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culture, corresponding to cross-cultural differences and conflicts between team members. As an

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example, the IRMC-32, percentage of craft labor sourced locally, was associated with the socio-

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culture attribute because the participation of a construction project’s team members who are from

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different locations or countries may result in challenges associated with different cultures.

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STEP 3: PERFORM DATA COLLECTION

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After identification and classification of potential IMRCs, 44 construction case study projects were

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collected. The research team then developed a structured questionnaire to collect data

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comprehensively associated with the same projects, as stated earlier.

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The survey questions were categorized into three groups: (1) general project description, (2)

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potential indicators of manageable rework, and (3) level of implementation of best practices. Fig.

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3 shows two examples of questions included in the survey. As shown in this figure, collected

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responses were in two forms: continuous number and seven-point Likert scale. The first section of

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the survey consisted of 20 questions associated with general information and project

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characteristics. The second section consisted of 35 questions that were related to the potential

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manageable causes of rework. In the third section, ten questions addressed the level of

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implementation of the most applicable rework best practices.

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Fig. 3. Two example questions of the survey

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To avoid respondents’ confusion and collect consistent data, the definitions of best practices were

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included at the beginning of the questionnaire. The pilot test was administered to four experienced

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practitioners from industry to examine the clarity of each question. After the questionnaire was

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validated, it was finalized and distributed among experienced industry professionals. The survey 10

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process was entirely set up and managed through an online system. After sending two follow-up

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emails, 44 completed surveys gathering more data related to the case studies were collected.

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The demographic information of survey respondents is shown in Table 3. As illustrated in this

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table, the current role of 69% of the survey respondents was project manager. The purpose of

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selecting the most upper-level respondents was to collect reliable and valid data corresponding to

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construction projects.

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Table 3. Respondents’ Demographic Information

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STEP 4: PERFORM DESCRIPTIVE DATA ANALYSIS

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Information from 44 case study projects is shown in Table 4. Among the projects, 31 (71%) of

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them were heavy industrial projects, and the remaining 13 (29%) were light industrial,

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infrastructure, and building projects. This table shows that 33 projects (75%) were located in the

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USA, and the rest (25%) were in Canada, China, Prue, Senegal, Indonesia, Saudi Arabia, Brazil,

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and the Netherlands. The maximum project size of the collected case studies was $5 billion for a

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heavy industrial project located in Saudi Arabia with a 42-month baseline schedule.

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Table 4. Information of Case Study Projects

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Descriptive data analyses associated with baseline and actual budgets and schedules, as well as

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rework dollar values corresponding to 44 construction projects, are shown in Table 5.

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Table 5. Descriptive Data Analysis of Collected Data in Construction Phase

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To avoid any bias created by larger projects on the results, the values of the issued rework were

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normalized based on the size of the projects. To calculate the normalized value of rework for any

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project, the value of rework was divided by the value of baseline budget for the construction phase.

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These values were recorded and used for the rest of the analyses conducted in this study.

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STEP 5: DETERMINE SIGNIFICANT IMRCs

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The P-Values corresponding to the significant IMRCs are shown in Table 6. As there were two

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types of data (continuous and seven-point Likert scale) collected from the survey, the two-sample

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t-test and Kruskal-Wallis test were performed. As stated earlier, 51 manageable causes of rework

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were initially found through existing literature. Among these causes, 35 were found manageable

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by implementing the BPs. Finally, 32 significant IMRCs were determined, as shown in Table 6.

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In the first, second, and third columns of Table 6, the names of the three main categories of

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attributes (organization, project, and people) and a list of significant IMRCs are presented,

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respectively. The fourth column contains a list of causes of rework, based on previous studies. In

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other words, Column 4 portrays the origination of each IMRC through existing literature.

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Abbreviations of indicators of manageable rework causes and their associated numbers (e.g.

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IMRC-2) were used. Column 5 shows the results of the statistical data analyses. As presented in

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Table 6, this study initially conducted the statistical analysis at the 0.05 significance level, and

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then raised it to 0.1 to include more indicators of manageable rework causes.

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Considering IMRC-10, reaching an agreement, which belongs to the organization category and

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communication attribute, can be very time consuming due to conflicts between designers.

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Consequently, the process of decision making by designer entities takes a lot of time and the

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possibility of design changes increases.

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In the case of IMRC-19, which belongs to the project category and design and technology

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attribute, if the design of a system is complex, an increased number of errors is more probable due

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to deficiencies in the designers’ knowledge and/or experience. Ultimately, these errors will cause

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design changes and modifications during the construction phase. Poor quality of materials (IMRC-

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25, belonging to the project category and material resources attribute) leads to replacement of the

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materials and results in modifications of the design. As shown in Table 6, if the designers lack

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skills in working with new technologies in the design phase (i.e. IMRC-29, belonging to the people

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category and skill attribute), the probability of design errors in a complex project increases.

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Table 6. Significant Indicators of Manageable Rework Causes and Corresponding P-Value

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STEP 6a: DETERMINE BEST PRACTICES THAT REDUCE VALUE OF REWORK ASSOCIATED WITH IMRCs

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In this section, the selection of suitable BPs to reduce the value of rework corresponding to issues

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related to IMRCs, was investigated, and the results of the P-Values are shown in Table 7. Because

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the implementation level of BPs was asked in a survey as a seven-point Likert scale question, the

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Kruskal-Wallis test was utilized to investigate whether a significant difference existed between the

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median values of the best practices implementation level associated with IMRCs.

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As depicted in Table 7, implementation of Front-End Planning is effective in managing the

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challenges related to bureaucracy in an organization. Bureaucracy is a time-consuming systematic

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structure that handles the business of an organization. Therefore, with implementation of Front-

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End Planning that allocates appropriate functions, rework associated with bureaucracy can be

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reduced.

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Adoption of the Team Building strategy results in clear expectations and improved commitment

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among team members. In addition, this strategy promotes trust and accountability among members

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of an entity. Consequently, utilization of Team Building reduces the value of rework due to

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communication challenges within owner stakeholders, and designer and contractor entities.

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Utilization of the Constructability strategy assists in the development of plans and specifications.

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For instance, through implementation of this BP, a technical software such as the Building

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Information Modeling Technique for Coordination is used to review architectural and engineering

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disciplines for proper coordination. Thus, it was perceived that when the PMT has insufficient

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work experience and/or the design of a project is complex, the adoption of Constructability would

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be beneficial to reduce the value of rework.

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The implementation of Quality Management results in regular audits and analyses of historical

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data to identify design errors. Furthermore, this strategy performs root cause analyses and takes

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corrective actions at the right time. As a result, when there are several locations and/or countries

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involved in the design phase, the adoption of Quality Management is beneficial to decrease the

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number of design errors.

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It is important to mention that all 44 case studies implemented the Safety strategy in their projects,

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and it is impossible to determine whether implementing this strategy significantly reduces the

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challenges associated with manageable causes of rework. Therefore, it was concluded that

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investigation of this strategy would not assist in determining whether the adoption of Safety would

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reduce the dollar value of rework associated with IMRCs, so it was excluded from the prepared

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list of BPs.

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As depicted in Table 7, implementation of Front-End Planning is effective for manage the

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challenges related to the bureaucracy in an organization. Bureaucracy is a time-consuming,

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systematic structure that handles the business of an organization. Therefore, with implementation

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of Front-End Planning, which allocates appropriate functions, rework associated with bureaucracy

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can be reduced.

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Utilization of the Constructability strategy assists in the development of plans and specifications.

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For instance, through implementation of this BP, a technical software, such as the Building

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Information Modeling Technique for coordination can be used to review architectural and

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engineering disciplines for proper coordination. Thus, when the PMT has insufficient work

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experience and/or the design of a project is complex, the adoption of Constructability would be

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beneficial to reducing the value of rework.

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Implementation of Quality Management regular audits and analyses of historical data to identify

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design errors. Furthermore, this strategy performs root cause analyses and takes corrective actions

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at the right time. As a result, when there are several locations and/or countries involved in the

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design phase, the adoption of Quality Management would be beneficial to decrease the number of

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design errors.

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Table 7. Result of Kruskal-Wallis Test of BPs to Reduce the Value of Rework Associated with IMRCs

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STEP 6b: CALCULATE ATTRIBUTES

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The value of effect sizes corresponding to IMRCs, as listed in Table 8, were calculated by using

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Cohen’s d method. Then, the values of the effect sizes were normalized, as indicated in Table 8.

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These normalized values were calculated based on the value of effect size associated with each

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IMRC, divided by the summation of all values of effect sizes. The maximum normalized weight

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(6.06%) of IMRCs corresponds to the experience of the project manager in the construction phase

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(IMRC-15). As shown in Table 8, the normalized weight of the number of PMTs who participated

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in the project (IMRC-12), and the experience of the PM in the design phase (IMRC-14) were

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recorded as 5.87% and 5.68%, respectively. The PMT commonly has two important tasks: to direct

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a project to achieve objectives quickly, and to improve relations in the organization to attain higher

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efficiency. Therefore, the highest normalized weights that were recorded corresponded to the

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PMT.

WEIGHT

OF

BEST

PRACTICES

FOR

REWORK

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Table 8. Weight of Early Indicators of Manageable Rework Causes

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The weights of the BPs for managing rework attributes were calculated and are shown in Table 9.

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The results of this table show that for reduction in the value of rework corresponding to the 15

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participant attribute (i.e., owner, designer, and contractor stakeholders) Front-End Planning and

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Dispute Prevention produced the greatest support. Weights corresponding to Front-End planning

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and Dispute Prevention were similarly recorded as 0.0416. For more clarification as to how these

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weights were recorded, consider Front-End and Dispute Prevention in Table 7, corresponding to

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participant attribute. As can be seen, IMRC-6 (number of owner organizations) was significant in

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this attribute for both mentioned strategies. Table 8 illustrates that the weight of IMRC-6 was

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calculated as 0.0416. Therefore, as shown in Table 9, weights for both Front-End Planning and

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Dispute Prevention associated with the participant attribute were recorded as 0.0416. Team

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Building promotes trust and accountability among project participants and creates shared goals

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among stakeholders, thereby reducing potential time-consuming disagreements and conflicts.

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Furthermore, adoption of Dispute Prevention is important for early recognition of the indicators of

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conflicts among participants and for forming a strong commitment to avoid them.

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In case of Team Building, this strategy promotes trust and accountability among project

365

participants and creates shared goals between stakeholders; therefore, reducing potential time-

366

consuming disagreements and conflicts will occur. Furthermore, adoption of Dispute Prevention

367

is important to recognize the indicators of conflicts early among participants and form of a strong

368

commitment to avoid them.

369

Table 9 illustrates that Constructability offers the greatest support for reduction in design errors

370

related to attributes of management team and design and technology. As shown in Table 8, the

371

weights of Constructability corresponding to management team and design and technology

372

attributes were calculated as 0.0568 and 0.0416, respectively. For more clarification of how the

373

weight of design and technology (0.0416) was calculated, consider Constructability in Table 7,

374

which is related to the design and technology attribute. As shown in this table, IMRC-19 (difficulty

16

375

in system design) and IMRC-20 (design completion before construction phase) were determined

376

as significant for Constructability related to the design and technology attribute. Table 8 illustrates

377

that weights of IMRC-19 and IMRC-20 were calculated as 0.0170 and 0.0246, respectively. As a

378

result, the weight of Constructability for the design and technology attribute is recorded as 0.0416

379

(the summation of 0.0170 and 0.0246). This strategy benefits design quality control and clash

380

checking and decreases design errors that are due to the design management team’s lack of

381

experience in working with new technologies during the design phase.

382

Table 9. Weight of Each Best Practice for Manageable Rework Attributes

383

As indicated in Table 9, the adoption of Front-End Planning leads to early clarification of the

384

project’s goal to ensure that the scope and technical specifications are well defined and

385

documented, and results in the reduction of late design changes of the scope attribute. This strategy

386

creates finance strategy that makes project cost and schedule targets more reliable. Therefore, this

387

strategy strongly supports the finance attribute.

388

Table 9 shows that the utilization of Risk Assessment is highly recommended when team members

389

have insufficient required skills. This strategy provides a foundation on which to build the

390

compliance program with training, monitoring, and auditing; thus, this BP reduces the number of

391

issued design modifications in a construction project. In addition, it was perceived that when

392

different locations and/or countries are involved in the design and/or construction phase, the

393

adoption of Risk Assessment can be beneficial to establishing structured and disciplined regular

394

audits.

395

As shown in Table 9, the implementation of Front-End Planning and Alignment strategies are

396

highly suggested to support partnership challenges. These strategies adopt a standard template for

397

stakeholders to communicate about project goals and scope in order to achieve the success of a

17

398

project. Moreover, these strategies lead to performing required analyses to align requirements and

399

expectations of stakeholders.

400

Since communication within and between multicultural teams has a strong impact on the project’s

401

performance, the implementation of Lesson Learned will enhance a project’s cost and schedule

402

performance when participating craft laborers in a project are from different cultures (i.e. socio

403

culture attribute). The Lesson Learned strategy benefits the utilization of knowledge regarding the

404

cultural differences to supervise effectively the execution of a project.

405

STEP 7: IMPLEMENT THE RESULTS

406

Two heavy-industrial case study projects were selected to verify the results of the present study.

407

As illustrated in Table 10, the baseline budget of the construction phase of each of the two projects

408

was around $5 million. To obtain the results quickly, the case studies with short construction phase

409

durations were purposely selected. This table shows that the baseline schedules of the construction

410

phase for the first and the second projects were 8 and 7 months, respectively.

411

As illustrated in Table 10, thirteen, and ten IMRCs were presented in the first and second projects,

412

respectively. Five BPs (Constructability, Material Management, Quality Management, Lesson

413

Learned, and Risk Assessment) were implemented in the first project, and the value of rework was

414

approximately $ 1.2 million. For the second project, only Material Management, Lesson Learned,

415

and Risk Assessment were implemented. The value of the derived rework for the second project

416

was around $1.7 million. The results demonstrated that the implementation of Constructability and

417

Quality Management led to a reduction in the value of the rework of approximately $600 thousand

418

for two industrial projects with similar construction phase baseline budgets and schedules.

419 420

Table 10. Breakdown of Information for Two Case Study Projects Used for Implementation of Results

18

421

As shown in Table 10, indicators of rework associated with the management team attribute (i.e.

422

IMRC-14, low PM experience in design phase) and design and technology attribute (i.e. IMRC-

423

19, complex system design) were presented in the first and the second projects. As shown in Table

424

9, adoption of Constructability in the first project reduced the dollar value of rework associated

425

with the management team and design and technology attributes. Furthermore, Table 10 illustrates

426

that the indicators of rework associated with the management team (i.e., IMRC-14: low PM

427

experience in design phase) and (i.e., IMRC-15: Low PM experience in construction phase) were

428

present in both projects. The indicators of the location attribute (i.e., IMRC-16, several execution

429

locations in design phase) and (i.e. IMRC-17, two countries involved in design phase) were

430

likewise presented in the first and second projects. Thus, as shown in Table 9, implementation of

431

Quality Management assisted within reducing the dollar value of rework due to challenges

432

associated with the management team and location in the first project. As a result, adoption of

433

Constructability and Quality Management led to a lower dollar value of rework in the first project.

434

CONCLUSION

435

This research has two goals: (1) to determine the early indicators of manageable rework causes;

436

(2) to select the appropriate best practice strategies in order to reduce dollar value of rework

437

associated with manageable rework attributes. In this regard, 32 significant indicators were

438

identified belonging to three main categories and thirteen attributes. Furthermore, 10 appropriate

439

best practices were selected in order to reduce the dollar value of rework associated with rework

440

attributes.

441

Since the PMT commonly is responsible for the planning, execution, and closing of any

442

construction project, the experience of the PMT in the design and construction phases (i.e., IMRC-

443

15, IMRC-14) and the number of project management staff who work on the project (i.e. IMRC-

19

444

12) were determined to be the three important indicators with the highest weights in construction

445

projects. This study also concluded that implementation of Alignment and Front-End Planning

446

assist in the effective management of challenges that are due to bureaucracy in a construction

447

project. Adoption of the mentioned strategies forms an organized framework in which to establish

448

businesslike communication within an organization system, which reduces the number of design

449

changes throughout a construction project. In addition, this study demonstrated that Quality

450

Management benefits when several countries are participating in the design and/or construction

451

phase, because regular audits and analysis of the collected data are conducted to prevent potential

452

design errors. It is believed that the outcomes of this study will assist stakeholders and

453

corresponding project managers in early identification of manageable rework causes and timely

454

implementation of appropriate best practices to attain minimum design modifications throughout

455

the execution of construction projects.

456

ACKNOWLEDGMENTS

457

The authors would like to appreciate the editor of this journal and three anonymous reviewers for

458

their constructive comments that contributed in adding to the value of the manuscript.

459

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24

Table

Click here to access/download;Table;Tables.docx

Table 1. List of Construction Best Practices with Their Definition Best Practice

BPs Explanation

Previous Studies

Partnering

Companies may collaborate in order to achieve specific business objectives by maximizing the effectiveness of each participant’s resources.

Du et al. (2016) Wang et al. (2016)

Alignment

The condition where appropriate project participants are working within acceptable tolerances to develop and meet a uniformly defined and understood set of project priorities.”

Griffith and Gibson (2001)

Front End Planning

The process through which owners develop sufficient strategic information to address risk and commit resources in order to maximize project success.

Geaorge et al. (2008), Hwang and Ho (2012)

Constructability

The optimal use of construction knowledge and experience in planning, design, procurement, and field operations to achieve overall project objectives.

Kifokeris and Xenidis (2017), Nascimento et al. (2017)

A project-focused process that builds and develops shared goals, interdependence, trust and commitment, and accountability among team members. The process used to identify, assess, and manage risk. The project team evaluates risk exposure for potential project impact to provide focus for mitigation strategies. An integrated process for planning and controlling all necessary efforts to make certain that the quality and quantity of materials and equipment are appropriately specified in a timely manner, are obtained at a reasonable cost, and are available when needed. Use of a dispute review board as an alternative to litigation. The Dispute Review Board technique provides a process for addressing disputes in their early stages before the dispute affects the progress of the work, creates adversarial positions, and leads to litigation. This strategy incorporates all activities conducted to improve the efficiency, contract compliance and cost effectiveness of design, engineering, procurement, QA/QC, construction, and startup elements of construction projects.

Spatz (2000), Mohammadi et al. (2016) Zavadskas et al. (2010)

Team Building

Risk Assessment

Material Management

Dispute Prevention

Quality Management

Lesson Learned

Knowledge gained from experience, successful or otherwise, for improving future performance.

Thomas et al. (2005), Donyavi and Flanagan (2009) Barry and Leite (2015)

Sullivan (2011)

Carrillo et al. (2013), Shokri-Ghasabeh and Chilesha (2014)

Table 2. Statistical Analysis Methods Statistical Test

Assumptions

Two-sample t-test (adjusted R2): This test was used • The two groups follow a normal distribution. where the response is a count or numerical value. • Each Project was independent from other projects. Kruskal-Wallis: This test was used for Likert scale questions (ordinal seven-point scale), where it could not necessarily be assumed that the data follows a normal distribution.

• The two groups follow an identically scaled distribution. • Each Project was independent from other projects. • The distribution of two groups are the same.

Table 3. Respondents’ Demographic Information Years of Experience 0-10 11-20 21-30 31-40 Above 40

Number 4 12 14 12 2

Percentage (%) 9 27 32 27 5

Current Role in the Company Program Director Project Manager Engineer

Number 10 30 4

Percentage (%) 22 69 9

Table 4. Information of Case Study Projects Project

Project Type

Project Location

Baseline Budget ($)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

Heavy Industrial Heavy Industrial Infrastructure Heavy Industrial Buildings Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Buildings Infrastructure Light Industrial Heavy Industrial Light Industrial Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Buildings Heavy Industrial Buildings Infrastructure Heavy Industrial Heavy Industrial Heavy Industrial Light Industrial Heavy Industrial Buildings Heavy Industrial Heavy Industrial Buildings Buildings Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial Heavy Industrial

USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA Senegal Indonesia Saudi Arabia Brazil Netherlands Canada Peru Indonesia Alaska Canada China

$21,450,000 $45,000,000 $4,882,621 $5,900,000 $19,999,000 $43,500,000 $575,000,000 $11,053,269 $17,400,000 $13,500,000 $17,003,722 $81,800,000 $77,000,000 $166,333,047 $77,000,000 $273,550,000 $217,250,000 $111,818,500 $11,000,000 $448,864,480 $376,433,800 $273,550,000 $7,000,000 $425,000 $1,600,000 $18,300,000 $9,250,000 $125,000,000 $11,000,000 $25,700,000 $639,326 $39,754,613 $560,000 $203,638,000 $273,550,000 $5,000,000,000 $450,000,000 $30,000,000 $550,000,000 $166,333,047 $1,443,000,000 $639,326 $273,550,000 $4,290,000

Actual Cost ($) $18,980,000 $42,957,344 $5,276,921.35 $6,200,000 $19,999,000 $43,500,000 $650,000,000 $9,015,969 $17,800,000 $13,888,000 $14,039,249 $79,500,000 $83,249,000 $192,884,724 $90,000,000 $295,037,296 $214,600,000 $105,041,153 $13,600,000 $666,347,825 $319,660,518 $295,037,296 $5,910,365 $418,293 $1,259,000 $15,260,000 $7,706,000 $138,000,000 $10,700,000 $42,700,000 $698,056 $29,364,523 $560,000 $190,083,306 $295,037,296 $5,600,000,000 $490,000,000 $30,500,000 $575,000,000 $192,884,724 $1,563,340,000 $698,056 $295,037,296 $4,648,000

Baseline Schedule (months) 30 30 24 8 12 16 39 24 24 15 27 47 16 24 22 22 30 24 30 26 26 22 30 24 24 19.4 16.5 24 17.5 22 10 54 10 36 22 42 42 21 22 26 33 10 22 8

Actual Schedule (months) 36 36 34 8 12 20 52 30 24 17 34 70 21 36 23 24 36 22 36 35 35 24 31 26 26 19.1 18 30 16.6 24 12 55 11 31 24 44 45 23 25 35 36 12 24 9

Table 5. Descriptive Data Analysis of Collected Data in Construction Phase

Cost

Schedule Change Orders

Construction Phase Baseline Budget Actual Cost Baseline Schedule Actual Schedule Rework

Standard Deviation

Variance

134,588,433

$1.8E+16

Minimum

Mean

Maximum

$337,721

$87,279,265

$740,100,000

$327,000

$151,578,590

$2,500,000,000

393,970,564

$1.5E+17

4 Months

16 Months

40 Months

9.6 Months

93.7 Months

3 Months

17.5 Months

46 Months

10.5 Months

110.1 Months

$21,000

$2,068,557

$9,350,000

$2,081,929

$4.3E+12

Category

Table 6. Significant Indicators of Manageable Rework Causes and Corresponding P-Values Attribute

Organization

Bureaucracy

Participants

Communication

Management Team

Project

Location

Design & Technology Material Resources Scope Partnership Finance

People

Skill Field Craft Experience Socio-Culture

Indicators of Manageable Rework Causes (IMRCs) IMRC-1- Difficulty in obtaining design approval IMRC-2- Number of financial approval authority threshold IMRC-3- Number of external entities required to approve the design IMRC-4- Number of active Internal stakeholders in decision making process IMRC-5- Alignment quality of internal stakeholders IMRC-6- Number of owner organizations IMRC-7- Number of designer organizations IMRC-8- Number of contractor organizations IMRC-9- Communication effectiveness within owners IMRC-10- Communication effectiveness within designers IMRC-11- Communication effectiveness within contractors IMRC-12-Percentage of actual project management staff IMRC-13-Number of executive oversight entities above the PM IMRC-14- PMT experience in design phase IMRC-15- PMT experience in construction phase IMRC-16-Number of execution locations on this project during detailed design phase IMRC-17-Number of countries involved in design phase IMRC-18- Number of countries involved in construction phase IMRC-19-Difficulty in system design IMRC-20- Percentage of design at the start of construction IMRC-21- RFI leads to design changes IMRC-22- Number of new systems tied into existing systems IMRC-23- Delay in delivery of permanent facility equipment IMRC-24- Permanent equipment quality issues IMRC-25-Quality of bulk materials

Causes of Rework based on Previous Studies

P-Value

Long waiting time for approval (Chan & Kumaraswamy 1997) Long-lead procurement (Fisk 1997)

0.015** 0.001**

Occurrence of conflicts and disputes (Wu et al. 2005)

0.034**

Impediment of prompt decision-making (Sanvido et al.1992)

0.043**

Poor coordination (Arain and Pheng 2005) Impediment of prompt decision-making (Sanvido et al. 1992) Poor coordination ( Arain and Pheng 2005) Poor site management (Sunday 2010) Owner fail to make decision right time (Jadhav & Bhirud 2015) Failure by consultant to supervise effectively (Jadhav & Bhirud 2015) Poor project management by contractor (Ye et al. 2015) Poor site management and supervision (Ye et al. 2015) Low speed of decision making (Chan & Kumaraswamy 1997) Lack of experience ( Arain and Pheng 2005) Lack of experience ( Arain and Pheng 2005)

0.020** 0.003** 0.055* 0.016** 0.006** 0.001** 0.001** 0.023** 0.035** 0.001** 0.001**

Inappropriate linking all design team (Chan & Kumaraswamy 1997)

0.051* 0.057* 0.081* 0.038* 0.031* 0.018* 0.035** 0.003** 0.047** 0.043**

IMRC-27-Total number of joint-venture partners in a project IMRC-28-Number of funding phases IMRC-29-Degree of familiarity with technologies in design IMRC-30- familiarity with technologies in construction phase

Socio-cultural factors (O’Brien 1998) Socio-cultural factors (O’Brien 1998) Mistake and defect in design (Hsieh et al. 2004) Incomplete design information (Jadhav & Bhirud 2015) Changes in design ( Arain and Pheng 2005) Lack of experience ( Arain and Pheng 2005) Unavailability of equipment (O’Brian 1998) Low productivity of equipment (Assaf and Al-Hejji 2006) Replacement of material (Karthick et al. 2015) The owner may make changes to achieve certain milestones within a given time frame (Wu et al. 2005) Low speed of decision making (Chan & Kumaraswamy 1997) Delay in payment (Karthick et al. 2015) Defect in design (Hsieh et al. 2004) Changes in construction method(Wu et al. 2005)

IMRC-31- Field craft labor quality issue

Skill Shortage ( Arain and Pheng 2005)

0.069*

IMRC-32- Percentage of craft labor sourced locally

Socio-cultural factors (O’Brien 1998)

0.011**

IMRC-26- Clarity of owner’s project goals and objectives

** denotes significant differences with 95% confidence; * denotes significant differences with 90% confidence

0.039** 0.042** 0.044** 0.082* 0.063*

Skill Field Craft Experience Socio-Culture

Lesson Learned

People

Scope Partnership Finance

Dispute Prevention

Material Resources

Quality Management

Design & Technology

Material Management

Project

Location

Risk Assessment

Management Team

Front End Planning

Communication

Partnering

Participants

Alignment

Organization

Bureaucracy

Team Building

Attribute

Constructability

Category

Table 7. Result of Kruskal-Wallis Test of BPs to Reduce the Value of Rework Associated with IMRCs

IMRC-1 IMRC-2 IMRC-3 IMRC-4 IMRC-5 IMRC-6 IMRC-7 IMRC-8 IMRC-9 IMRC-10 IMRC-11 IMRC-12 IMRC-13 IMRC-14 IMRC-15 IMRC-16 IMRC-17 IMRC-18 IMRC-19 IMRC-20 IMRC-21 IMRC-22 IMRC-23 IMRC-24 IMRC-25 IMRC-26 IMRC-27 IMRC-28 IMRC-29 IMRC-30

0.198 0.825 0.475 0.285 0.175 0.497 0.112 0.458 0.423 0.108 0.477 0.365 0.185 0.001** 0.252 0.395 0.425 0.202 0.047** 0.025** 0.285 0.412 0.202 0.202 0.285 0.202 0.333 0.475 0.117 0.414

0.258 0.321 0.147 0.415 0.284 0.617 0.085 0.058 0.064* 0.081* 0.052* 0.394 0.852 0.174 0.256 0.354 0.052* 0.235 0.684 0.196 0.555 0.396 0.145 0.112 0.312 0.112 0.125 0.485 0.157 0.158

0.051* 0.285 0.025** 0.698 0.035** 0.188 0.321 0.0741* 0.147 0.120 0.346 0.168 0.096* 0.146 0.344 0.687 0.145 0.362 0.456 0.387 0.456 0.550 0.265 0.352 0.256 0.625 0.170 0.685 0.145 0.325

0.111 0.174 0.285 0.012** 0.321 0.222 0.312 0.297 0.374 0.321 0.354 0.116 0.174 0.375 0.303 0.489 0.203 0.132 0.114 0135 0.394 0.465 0.665 0.363 0.110 0.285 0.015** 0.185 0.325 0.374

0.369 0.074* 0.352 0.526 0.354 0.014** 0.483 0.743 0.345 0.147 0.466 0.016** 0.196 0.159 0.055* 0.156 0.361 0.144 0.178 0.112 0.415 0.394 0.209 0.564 0.393 0.059* 0.041** 0.018** 0.486 0.315

0.875 0.241 0.178 0.369 0.147 0.444 0.397 0.645 0.456 0.145 0.117 0.746 0.285 0.525 0.354 0.131 0.220 0.085* 0.568 0.189 0.285 0.745 0.406 0.550 0.282 0.145 0.695 0.396 0.545 0.084*

0.663 0.440 0.685 0.357 0.158 0.266 0.199 0.196 0.625 0.652 0.284 0.373 0.221 0.424 0.074* 0.208 0.334 0.068* 0.248 0.684 0.341 0.195 0.063* 0.008** 0.035** 0.465 0.375 0.358 0.357 0.458

0.660 0.446 0.358 0.359 0.169 0.442 0.174 0.456 0.412 0.354 0.365 0.191 0.356 0.075* 0.064* 0.058* 0.035** 0.346 0.863 0.374 0.396 0.375 0.175 0.065* 0.044** 0.368 0.674 0.425 0.303 0.417

0.741 0.528 0.355 0.745 0.645 0.028** 0.633 0.045 0.312 0.295 0.475 0.711 0.341 0.324 0.654 0.158 0.330 0.365 0.148 0.198 0.645 0.684 0.556 0.333 0.355 0.756 0.312 0.484 0.119 0.636

0.396 0.547 0.187 0.658 0.586 0.333 0.063* 0.697 0.387 0.274 0.145 0.623 0.285 0.303 0.666 0.302 0.357 0.145 0.351 0.257 0.036** 0.045** 0.145 0.145 0.268 0.642 0.202 0.356 0.022** 0.063*

IMRC-31

0.185

0.195

0.174

0.525

0.505

0.110

0.151

0.015**

0.147

0.417

IMRC-32

0.452

0.302

0.415

0.405

0.220

0.111

0.325

0.369

0.101

0.002**

IMRC

Table 8. Weight of Early Indicators of Manageable Rework Causes Indicators of Manageable Rework Causes (IMRCs)

Weight

IMRC-15- PM experience in construction IMRC-12- Number of PM staff IMRC-14- PM experience in design

0.0606 0.0587 0.0568

IMRC-13- No. of entities above PM

0.0549

IMRC-2- No. of financial approval authority

0.0530

IMRC-3- No. of entities for design approval

0.0511

IMRC-9- Communication within owners IMRC-10- Communication within designers IMRC-23- Delay in delivery of facility IMRC-11- Communication within contractors IMRC-6- No. of owner organizations IMRC-29- Familiarity with design tech. IMRC-7- No. of designer organizations

00378

IMRC-8- No. of contractor organizations IMRC-5- Alignment of internal entities

0.0359 0.0340

IMRC-16- No. of locations in design

0.0321

Indicators of Manageable Rework Causes (IMRCs)

Weight 0.0303 0.0284 0.0265

0.0492 0.0473 0.0454

IMRC-1- Difficulty in design approval IMRC-32- percentage of local craft staff IMRC-22- No. of new systems IMRC-20- Design completion before construction phase IMRC-21- RFI leads to design changes IMRC-18- No. of countries in construction IMRC-31- Field craft labor quality issues IMRC-19- Difficulty in system design IMRC-24- Equipment quality issues

0.0435

IMRC-4- No. of active internal entities

0.0132

0.0416 0.0397

IMRC-25- Quality of bulk materials IMRC-28- No. of funding phases IMRC-30- Familiarity with construction technology IMRC-26- Clarity of owner goals IMRC-27- No. of joint-venture partners IMRC-17- No. of countries in design phase

0.0113 0.0094

0.0246 0.0227 0.0208 0.0189 0.0170 0.0151

0.0075 0.0056 0.0037 0.0018

People

Project

0.0814

Participant

0.0699

Communication Management Team Location Design & Technology Material Resources Scope Partnership Finance Skill Field Craft Experience Socio- Culture

Quality Management

Material Management

Risk Assessment

Front End Planning

Lesson Learned

Bureaucracy

Partnering

Alignment

Team Building

Constructability

Attribute

Dispute Prevention

Organization

Category

Table 9. Weight of Each Best Practice for Manageable Rework Attributes

0.0416

0.0378

0.0530 0.0132

0.0416

0.140 0.0568

0.0549

0.1193

0.0018

0.0208

0.0606

0.1174

0.0208

0.0339

0.0416

0.0492 0.0718

0.0264

0.0056 0.0037

0.0037 0.0094 0.0075

0.0472 0.0189 0.0284

Table 10. Breakdown of Information for Two Case Study Projects Used for Implementation of Results Project 1 2 Project

1

2

Baseline Budget Baseline Schedule Construction Phase Construction Phase Heavy Industrial $5,022,000 8 Months Heavy Industrial $5,000,000 7 Months Existing IMRCs in the Project IMRC-3: High no. of external entities required to approve design IMRC-4: High no. of active internal stakeholders in decision making process IMRC-12: Low percentage of PM staff IMRC-13: High no. of executive oversight entities IMRC-16: Several no. of execution locations in design phase IMRC-17: Two countries involved in design phase IMRC-19: Complex system design IMRC-21: RFIs drive serious project changes IMRC-22: Several new systems were tied into existing systems IMRC-23: Several weeks delay in the delivery of permanent facility equipment IMRC-28:Two no. of funding phases IMRC-8: Several no. of contractor organizations IMRC-14: Low PM experience in design phase IMRC-15: Low PM experience in construction phase IMRC-16: Several no. of execution locations in design phase IMRC-17: Two countries involved in design phase IMRC-18: Six no. of countries involved in construction phase IMRC-22: Several new systems were tied into existing systems IMRC-23: Several weeks delay in the delivery of permanent facility equipment IMRC-26: Low clarity of owner’s project goal IMRC-28:Three no. of funding phases IMRC-32: Between 60% and 80% of craft labors were not sourced locally Type of Project

Rework $1,239,831 $1,667,500 Implementation of BPs Constructability: Yes Team Building: No Alignment: No Partnering: No Front End Planning: No Material Management: Yes Quality Management: Yes Lesson Learned: Yes Risk Assessment: Yes Dispute Prevention: No

Constructability: No Team Building: No Alignment: No Partnering: No Front End Planning: No Material Management: Yes Quality Management: No Lesson Learned: Yes Risk Assessment: Yes Dispute Prevention: No

Figure

Click here to access/download;Figure;Fig.1.pdf

Step 1

Review Existing Literature

Step 2

Identify and Classify Potential IMRCs* Perform Data Collection

Step 3

Step 4

Case Study

Survey

Perform Descriptive Data Analysis 1st Study Outcome

Step 5

Determine Significant IMRCs 2nd Study Outcome

Step 6a

Determine Best Practices that Reduce the Value of Rework Associated with IMRCs

Step 6b

Calculate Weight of Best Practices for Rework Attributes

Step 7

Implement the Results

Fig. 1. Research methodology approach (IMRC*= Indicators of Manageable Rework Causes)

Figure

Click here to access/download;Figure;Fig.2.pdf

Organization •Bureaucracy •Participants •Communication

Project •Management Team •Location •Design & Technology •Material Resources •Scope •Partnership •Finance

People •Skill •Field Craft Experience •Socio-Culture

Fig. 2. Classification of indicators of manageable rework causes

Figure

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Question 23. Were there joint-venture partners in this project? If yes, how many? Question 39. Please indicate the impact of external agencies on the project execution plan. No Impact on Meeting the Execution Plan 1 2

Moderate 3

4

5

Substantial Impact on Meeting the Execution Plan 6 7

Fig. 3. Two example questions of the survey