International Construction Specialty Conference of the Canadian Society for Civil Engineering (ICSC) (5th : 2015)

Identifying influential factors for capital construction project planning strategies Safa, Mahdi; MacGillivray, Sandra; Davidson, Mike; Kaczmarczy, Kevin; Haas, Carl T.; Gibson, G. Edward Jun 30, 2015

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5th International/11th Construction Specialty Conference 5e International/11e Conférence spécialisée sur la construction    Vancouver, British Columbia June 8 to June 10, 2015 / 8 juin au 10 juin 2015   IDENTIFYING INFLUENTIAL FACTORS FOR CAPITAL CONSTRUCTION PROJECT PLANNING STRATEGIES Mahdi Safa1,2,5, Sandra MacGillivray2, Mike Davidson3, Kevin Kaczmarczyk3, Carl T. Haas1,and G. Edward Gibson, Jr. 4 1 Department of Civil and Environmental Engineering, University of Waterloo, Canada 2 Valency Inc., Canada 3 Ontario Power Generation, Canada 4 School of Sustainable Engineering and the Built Environment, Arizona State University, US 5 msafa@uwaterloo.ca Abstract: Construction companies devote significant resources to front end planning (FEP). The potential substantial benefits of the strategic implementation of FEP practices across an entire portfolio have made FEP evaluation an important issue for both project leaders and scholars. The primary objective of this study is the use of multiple regression analysis for the identification of factors for use in predicting the gaps in project definition and for evaluating the FEP. FEP data from 59 North American capital construction projects from the same industry segment have been examined in order to establish such indicators and to enable the monitoring of project resources throughout the project lifecycle. When employed as a proactive approach during FEP, the results of this analysis have the potential to guide project managers in their search for important potential project definition gaps, and to prioritize there definition efforts. Its contribution to the body of knowledge is a methodology for understanding how to focus project definition efforts most effectively.    1 INTRODUCTION   Long-term strategies associated with a large capital project are established during front end planning (FEP), a process that is influenced by a number of risks and constraints, such as resource limitations, changes in government regulations, environmental restrictions, and financial and economic crises (Safa et al. 2013, Gibson 2005). A review of studies in this area reveals adequate FEP to be an essential component in the overall success of a project David Grau et al. 2012, George et al. 2008, Gibson et al. 1995, Hartman and Ashrafi 2004, Smith  2000, Webster 2004). The potential for acquiring substantial benefits from FEP and the opportunity to address problems encountered during the planning process have thus made the evaluation of the FEP phase of construction capital projects an important concern for both scholars and industry practitioners. With a focus on construction firms that have implemented a Project Definition Rating Index (PDRI) as a standardized tool across their capital project portfolios, the research presented in this paper has identified the most important influential factors for FEP assessment. Also included are the results of an investigation of key PDRI elements, including the statistical analysis method used, an evaluation of its effectiveness with respect to predicting gaps during the strategic phase of a project, details of potential uses of the indicators, and a synopsis of the benefits available for the construction industry. Recent construction research has been directed at the establishment of a common set of construction phase metrics and their corresponding definitions (Park et al. 2005, Beatham et al. 2004, Rankin et al. 56-1 2008, Willis and Rankin 2012). Large capital construction projects are fraught with significant risk, with cost and schedule remaining key areas of scrutiny because failure to exploit opportunities for improving project value and decreasing risks could lead to the undervaluation of such projects (Ford 2002). Acquiring an in-depth understanding of this type of risk during the FEP phase is challenging because neither spending nor delivery has technically begun during this phase. A proven leading risk indicator employed during FEP is the PDRI. In current use as a widely adopted FEP standard, the PDRI stipulates key project elements suitable for representing the project team’s own assignment of scope definition ratings. The PDRI provides a framework for these ratings that allows project stakeholders to contribute important content and helps them acquire an understanding of the cross-functional impact of any risks identified.  Functioning as a multifaceted front end planning tool, a PDRI operates as a vehicle for the facilitation of strategic decision making through the evaluation of scope readiness as a means of measuring project risk. PDRIs are tailored to meet the specific needs of the building, industrial, and infrastructure sectors of the construction industry (Dumont et al. 1997, Weerasinghe et al. 2007, Gibson et al. 2010, Nasir et al. 2012). The correlation between a PDRI and risk factors related to project performance is based on published analyses of data from many hundreds of projects. The opportunity now exists to employ those historical project data sets at a portfolio level as a means of mining the powerful constituent elements of the index in order to develop methods that can support construction firms as they form proactive planning strategies for the execution of each new capital project.  Such strategies encompass the use of influential factors, information technology systems, and common knowledge gaps that have been identified in the companies.   Since PDRIs are available in a variety of versions that vary according to the unique characteristics of each project, the authors have carefully considered each set of individual project features while developing the proposed analysis method for FEP risk assessment. The contribution of this study to the existing body of knowledge is to employ the data from 59 actual capital industrial projects from the same industry segment as a means of demonstrating the influential factors for analyzing and assessing the entire FEP process. The names of the projects and companies have been kept confidential. In accordance with the terms of the confidentiality agreement, because all materials related to these projects are also strictly confidential, including the designs, plans, specifications, models, reports, and other documents, their publication is not permitted. The results of this study have the potential to serve as a measureable process for aligning the owner and contractor with respect to complete scope definition for one or several projects as each is being defined.  2 PROJECT DEFINITION RATING INDEX The primary deliverable of the FEP phase is an adequate level of design that enables the project team to prepare cost and schedule estimates, to make strategic decisions, and to identify risk (Dobler and Burt 1996, Safa et al. 2014). Once project funding has been approved, the FEP design deliverables become the primary input for the next phases in the project life cycle: procurement and detailed design. The FEP gates, four PDRI potential application points, and other life cycle project phases are illustrated in Figure 1. A gate is defined as the existence of the discrete information and definitions required for a decision to be made that determines whether to proceed.    56-2 1. These elements can be used consistently only across an entire portfolio of projects for a specific construction industry sector (e.g. oil and gas).  2. These powerful influential factors cannot be used to replace the PDRI process.  3. The elements selected can vary from one construction industry sector to another (e.g. oil and gas and commercial buildings).  Regression analysis can indicate only how or to what extent variables are associated with one another. The results can therefore not be considered as establishing precise cause-and-effect relationships, which means that any conclusions about the relationships should be based on the judgment of project managers and experts. In fact, the use of expert intuition represents one method of model validation, and was the method performed by the authors in this case. In practice, a project management team embodies a combination of domain expertise and operational experience. Therefore, on September 18, 2014, the authors met with two experts who had been involved with some of the projects included in the study in order to gain insight and to benefit from the unique opportunity to influence the direction of this research. The experts validated and confirmed the accuracy of the results obtained from the statistical analysis. This type of analysis offers a number benefits for a company:  1. It enables a determination of whether PDRI scores are a reliable leading indicator of performance when a PDRI is implemented as a strategic tool and is used consistently across an entire portfolio of projects.  2. Given the positive correlation between PDRI scores and improved project performance across an entire portfolio, a construction company can use these results as a means of validating their process and their commitment to using best practices in project management in order to maximize the financial return on their capital investments.  3. PDRI data analysis will provide a formal framework for FEP evaluation, thereby enhancing the quality of project management, facilitating management succession, and forming the basis for the long-term educational value of the FEP process.  4. With respect to performance over both the short and long term, this analysis will add to the impressive body of studies related to the evaluation of FEP results.  5. These results can contribute to an analysis of trends or common gaps in FEP data to be used as indicators of the organizational effectiveness of a project because they provide a benchmark at the element level of baseline conditions that are related to project success.   The results of this study can also be employed at pre-meetings held by PDRI facilitators before they conduct PDRI sessions to analyze project documents with key project stakeholders. Critical powerful indicators are also useful for enhancing the speedy evaluation of FEP phases; the periodic evaluation and prediction of common gaps in projects, portfolios, and the organization; and the assessment of small projects, organizational strategic issues, and contingency planning. 5 CONCLUSION More rigorously analyzed PDRI data can substantially improve the level of project managers’ understanding in this area. The primary contribution of this study is the identification of influential factors for FEP evaluation. The potential exists for construction companies to optimize their current use of such best practices and to integrate this new knowledge into their existing FEP. Data from 59 industrial projects have been evaluated and the results reported. It should be noted that the analysis and case projects all belong to the industry sector, which means that the results are not applicable for other sectors; however, the same methodology could be employed in additional construction industry sectors. Given the complexity of many construction capital projects, significant value accrues to the engineering and construction industry if the proposed method could be effectively utilized to enhance risk assessment for construction projects. Approaches to risk mitigation could then be more accurate and better focused, with fewer wasted resources. Other benefits include increased construction time and cost savings resulting from effective planning, which can further increase the success of risk avoidance procedures. PDRI users will have the opportunity to be at the forefront of the development, implementation, and exploitation of this crucial new method. The methodological limitations identified in these empirical studies (e.g. regression analysis constraints) suggest several avenues for future research in other construction industry sectors. As additional data become available, the results of this study will also be more broadly 56-8 applicable for use with further discoveries, such as operational excellence management, for which project risk management reporting represents a constant challenge for capital project teams and owners. References Beatham S., Anumba C. and Thorpe T. 2004. KPIs: A Critical Appraisal of Their Use in Construction. Benchmarking: International Journal, 11(1): 93-117. Chatterjee, S. and Hadi, A. S. 2013. Regression Analysis by Example. John Wiley & Sons.  Construction Industry Institute (CII) 2010. Project Definition Rating Index for Infrastructure Projects. Implementation Resource 268-2, First Edition, Austin, TX. Dobler, D.W. and Burt, D.N. 1996. Purchasing and Supply Management: Text and Cases. New York, NY: McGraw-Hill. Dumont, P. R., Gibson, G. E. and Fish, J. R. 1997. Scope Management Using Project Definition Rating Index. Journal of Management in Engineering, 13(5): 54-60.  Ford, D., Lander, D. and Voyer, J. 2002. A real options approach to valuing strategic flexibility in uncertain construction projects. Construction Management & Economics, 20(4): 343-351. George, R., Bell, L. and Edward Back, W. 2008. Journal of Management in Engineering, 24(2): 66-74. Gibson, G. E. 2005. Alignment During Pre-Project Planning: A Key To Project Success: Implementation Resource 113-3. Austine. TX: Construction Industry Institute. Gibson, G. E. and Dumont, P. R. 1996. Project definition rating index (PDRI) for industrial projects. Construction Industry Institute, Implementation Resource, 113-2. Gibson Jr, G. E., Kaczmarowski, J. H., and Lore, H. E. 1995. Preproject-planning process for capital facilities. Journal of construction engineering and management, 121(3), 312–318. Gibson, G.E., Bingham, E. and Stogner, C. 2010. Front End Planning for Infrastructure Projects. In Proceedings of Construction Research Congress 2010, ASCE, Banff, Alberta, Canada, pp. 1125-1135. Grau, D., Back, W. and Prince, J. 2012. Benefits of On-Site Design to Project Performance Measures. Journal of Management in Engineering, 28(3), 232–242. Hartman, F. and Ashrafi, R. 2004. Development of the SMART™ project planning framework. International Journal of Project Management, 22(6), 499–510. Nasir, H., Haas, C., Rankin, J., Fayek, A., Forgues, D. and Ruwanpura, J. 2012. Development and implementation of a benchmarking and metrics program for construction performance and productivity improvement. Canadian Journal of Civil Engineering, 39(9), 957-967.  Park, H., Thomas, S., and Tucker, R. 2005. Benchmarking of Construction Productivity. Journal of Construction Engineering and Management, 131(7), 772–778. Rankin, J., Robinson, A., Meade, G., Haas C. and Manseaue, A. 2008. Initial metrics and pilot program results for measuring the performance of the Canadian construction industry. Canadian Journal of Civil Engineering, 35(9): 894-907, 10.1139/L08-018. Safa, M., Haas, T. C., Gray, J. and Hipel, W. K. 2013. Electronic Process Management System based Front End Planning Tool (FEPT). Journal of Construction Engineering and Project Management, ISSN 2233-9582. Safa, M., Shahi, A., Haas, C. T. and Hipel, K. W. 2014. Supplier selection process in an integrated construction materials management model. Automation in Construction, 48, 64-73. Smith, C. C. 2000. Improved project definition ensures value-added performance. Part 1. Hydrocarbon Process, 79(8), 4. Wang, Y. R., and Gibson Jr, G. E. 2010. A study of preproject planning and project success using ANNs and regression models. Automation in Construction, 19(3), 341-346. Webster, J. 2004. Project planning: Getting it right the first time. IEEE Aerospace Conference Proceedings, Big Sky, Mont., 6: 3924–3930. Weerasinghe, G. K. S., Ruwanpura, J.  and Horman, M. 2007. LEED-PDRI Framework for Pre-Project Planning of Sustainable Building Projects. Journal of Green Building, 2:123-143.  Willis, C. and Rankin, J. 2012. Demonstrating a linkage between construction industry maturity and performance: a case study of Guyana and New Brunswick. Canadian Journal of Civil Engineering, 39(5), 565-578.  Zou, G. 2004. A modified poisson regression approach to prospective studies with binary data. American journal of epidemiology, 159(7), 702-706. 56-9  5th International/11th Construction Specialty Conference 5e International/11e Conférence spécialisée sur la construction    Vancouver, British Columbia June 8 to June 10, 2015 / 8 juin au 10 juin 2015   IDENTIFYING INFLUENTIAL FACTORS FOR CAPITAL CONSTRUCTION PROJECT PLANNING STRATEGIES Mahdi Safa1,2,5, Sandra MacGillivray2, Mike Davidson3, Kevin Kaczmarczyk3, Carl T. Haas1,and G. Edward Gibson, Jr. 4 1 Department of Civil and Environmental Engineering, University of Waterloo, Canada 2 Valency Inc., Canada 3 Ontario Power Generation, Canada 4 School of Sustainable Engineering and the Built Environment, Arizona State University, US 5 msafa@uwaterloo.ca Abstract: Construction companies devote significant resources to front end planning (FEP). The potential substantial benefits of the strategic implementation of FEP practices across an entire portfolio have made FEP evaluation an important issue for both project leaders and scholars. The primary objective of this study is the use of multiple regression analysis for the identification of factors for use in predicting the gaps in project definition and for evaluating the FEP. FEP data from 59 North American capital construction projects from the same industry segment have been examined in order to establish such indicators and to enable the monitoring of project resources throughout the project lifecycle. When employed as a proactive approach during FEP, the results of this analysis have the potential to guide project managers in their search for important potential project definition gaps, and to prioritize there definition efforts. Its contribution to the body of knowledge is a methodology for understanding how to focus project definition efforts most effectively.    1 INTRODUCTION   Long-term strategies associated with a large capital project are established during front end planning (FEP), a process that is influenced by a number of risks and constraints, such as resource limitations, changes in government regulations, environmental restrictions, and financial and economic crises (Safa et al. 2013, Gibson 2005). A review of studies in this area reveals adequate FEP to be an essential component in the overall success of a project David Grau et al. 2012, George et al. 2008, Gibson et al. 1995, Hartman and Ashrafi 2004, Smith  2000, Webster 2004). The potential for acquiring substantial benefits from FEP and the opportunity to address problems encountered during the planning process have thus made the evaluation of the FEP phase of construction capital projects an important concern for both scholars and industry practitioners. With a focus on construction firms that have implemented a Project Definition Rating Index (PDRI) as a standardized tool across their capital project portfolios, the research presented in this paper has identified the most important influential factors for FEP assessment. Also included are the results of an investigation of key PDRI elements, including the statistical analysis method used, an evaluation of its effectiveness with respect to predicting gaps during the strategic phase of a project, details of potential uses of the indicators, and a synopsis of the benefits available for the construction industry. Recent construction research has been directed at the establishment of a common set of construction phase metrics and their corresponding definitions (Park et al. 2005, Beatham et al. 2004, Rankin et al. 56-1 2008, Willis and Rankin 2012). Large capital construction projects are fraught with significant risk, with cost and schedule remaining key areas of scrutiny because failure to exploit opportunities for improving project value and decreasing risks could lead to the undervaluation of such projects (Ford 2002). Acquiring an in-depth understanding of this type of risk during the FEP phase is challenging because neither spending nor delivery has technically begun during this phase. A proven leading risk indicator employed during FEP is the PDRI. In current use as a widely adopted FEP standard, the PDRI stipulates key project elements suitable for representing the project team’s own assignment of scope definition ratings. The PDRI provides a framework for these ratings that allows project stakeholders to contribute important content and helps them acquire an understanding of the cross-functional impact of any risks identified.  Functioning as a multifaceted front end planning tool, a PDRI operates as a vehicle for the facilitation of strategic decision making through the evaluation of scope readiness as a means of measuring project risk. PDRIs are tailored to meet the specific needs of the building, industrial, and infrastructure sectors of the construction industry (Dumont et al. 1997, Weerasinghe et al. 2007, Gibson et al. 2010, Nasir et al. 2012). The correlation between a PDRI and risk factors related to project performance is based on published analyses of data from many hundreds of projects. The opportunity now exists to employ those historical project data sets at a portfolio level as a means of mining the powerful constituent elements of the index in order to develop methods that can support construction firms as they form proactive planning strategies for the execution of each new capital project.  Such strategies encompass the use of influential factors, information technology systems, and common knowledge gaps that have been identified in the companies.   Since PDRIs are available in a variety of versions that vary according to the unique characteristics of each project, the authors have carefully considered each set of individual project features while developing the proposed analysis method for FEP risk assessment. The contribution of this study to the existing body of knowledge is to employ the data from 59 actual capital industrial projects from the same industry segment as a means of demonstrating the influential factors for analyzing and assessing the entire FEP process. The names of the projects and companies have been kept confidential. In accordance with the terms of the confidentiality agreement, because all materials related to these projects are also strictly confidential, including the designs, plans, specifications, models, reports, and other documents, their publication is not permitted. The results of this study have the potential to serve as a measureable process for aligning the owner and contractor with respect to complete scope definition for one or several projects as each is being defined.  2 PROJECT DEFINITION RATING INDEX The primary deliverable of the FEP phase is an adequate level of design that enables the project team to prepare cost and schedule estimates, to make strategic decisions, and to identify risk (Dobler and Burt 1996, Safa et al. 2014). Once project funding has been approved, the FEP design deliverables become the primary input for the next phases in the project life cycle: procurement and detailed design. The FEP gates, four PDRI potential application points, and other life cycle project phases are illustrated in Figure 1. A gate is defined as the existence of the discrete information and definitions required for a decision to be made that determines whether to proceed.    56-2 1. These elements can be used consistently only across an entire portfolio of projects for a specific construction industry sector (e.g. oil and gas).  2. These powerful influential factors cannot be used to replace the PDRI process.  3. The elements selected can vary from one construction industry sector to another (e.g. oil and gas and commercial buildings).  Regression analysis can indicate only how or to what extent variables are associated with one another. The results can therefore not be considered as establishing precise cause-and-effect relationships, which means that any conclusions about the relationships should be based on the judgment of project managers and experts. In fact, the use of expert intuition represents one method of model validation, and was the method performed by the authors in this case. In practice, a project management team embodies a combination of domain expertise and operational experience. Therefore, on September 18, 2014, the authors met with two experts who had been involved with some of the projects included in the study in order to gain insight and to benefit from the unique opportunity to influence the direction of this research. The experts validated and confirmed the accuracy of the results obtained from the statistical analysis. This type of analysis offers a number benefits for a company:  1. It enables a determination of whether PDRI scores are a reliable leading indicator of performance when a PDRI is implemented as a strategic tool and is used consistently across an entire portfolio of projects.  2. Given the positive correlation between PDRI scores and improved project performance across an entire portfolio, a construction company can use these results as a means of validating their process and their commitment to using best practices in project management in order to maximize the financial return on their capital investments.  3. PDRI data analysis will provide a formal framework for FEP evaluation, thereby enhancing the quality of project management, facilitating management succession, and forming the basis for the long-term educational value of the FEP process.  4. With respect to performance over both the short and long term, this analysis will add to the impressive body of studies related to the evaluation of FEP results.  5. These results can contribute to an analysis of trends or common gaps in FEP data to be used as indicators of the organizational effectiveness of a project because they provide a benchmark at the element level of baseline conditions that are related to project success.   The results of this study can also be employed at pre-meetings held by PDRI facilitators before they conduct PDRI sessions to analyze project documents with key project stakeholders. Critical powerful indicators are also useful for enhancing the speedy evaluation of FEP phases; the periodic evaluation and prediction of common gaps in projects, portfolios, and the organization; and the assessment of small projects, organizational strategic issues, and contingency planning. 5 CONCLUSION More rigorously analyzed PDRI data can substantially improve the level of project managers’ understanding in this area. The primary contribution of this study is the identification of influential factors for FEP evaluation. The potential exists for construction companies to optimize their current use of such best practices and to integrate this new knowledge into their existing FEP. Data from 59 industrial projects have been evaluated and the results reported. It should be noted that the analysis and case projects all belong to the industry sector, which means that the results are not applicable for other sectors; however, the same methodology could be employed in additional construction industry sectors. Given the complexity of many construction capital projects, significant value accrues to the engineering and construction industry if the proposed method could be effectively utilized to enhance risk assessment for construction projects. Approaches to risk mitigation could then be more accurate and better focused, with fewer wasted resources. Other benefits include increased construction time and cost savings resulting from effective planning, which can further increase the success of risk avoidance procedures. PDRI users will have the opportunity to be at the forefront of the development, implementation, and exploitation of this crucial new method. The methodological limitations identified in these empirical studies (e.g. regression analysis constraints) suggest several avenues for future research in other construction industry sectors. As additional data become available, the results of this study will also be more broadly 56-8 applicable for use with further discoveries, such as operational excellence management, for which project risk management reporting represents a constant challenge for capital project teams and owners. References Beatham S., Anumba C. and Thorpe T. 2004. KPIs: A Critical Appraisal of Their Use in Construction. Benchmarking: International Journal, 11(1): 93-117. Chatterjee, S. and Hadi, A. S. 2013. Regression Analysis by Example. John Wiley & Sons.  Construction Industry Institute (CII) 2010. Project Definition Rating Index for Infrastructure Projects. Implementation Resource 268-2, First Edition, Austin, TX. Dobler, D.W. and Burt, D.N. 1996. Purchasing and Supply Management: Text and Cases. New York, NY: McGraw-Hill. Dumont, P. R., Gibson, G. E. and Fish, J. R. 1997. Scope Management Using Project Definition Rating Index. Journal of Management in Engineering, 13(5): 54-60.  Ford, D., Lander, D. and Voyer, J. 2002. A real options approach to valuing strategic flexibility in uncertain construction projects. Construction Management & Economics, 20(4): 343-351. George, R., Bell, L. and Edward Back, W. 2008. Journal of Management in Engineering, 24(2): 66-74. Gibson, G. E. 2005. Alignment During Pre-Project Planning: A Key To Project Success: Implementation Resource 113-3. Austine. TX: Construction Industry Institute. Gibson, G. E. and Dumont, P. R. 1996. Project definition rating index (PDRI) for industrial projects. Construction Industry Institute, Implementation Resource, 113-2. Gibson Jr, G. E., Kaczmarowski, J. H., and Lore, H. E. 1995. Preproject-planning process for capital facilities. Journal of construction engineering and management, 121(3), 312–318. Gibson, G.E., Bingham, E. and Stogner, C. 2010. Front End Planning for Infrastructure Projects. In Proceedings of Construction Research Congress 2010, ASCE, Banff, Alberta, Canada, pp. 1125-1135. Grau, D., Back, W. and Prince, J. 2012. Benefits of On-Site Design to Project Performance Measures. Journal of Management in Engineering, 28(3), 232–242. Hartman, F. and Ashrafi, R. 2004. Development of the SMART™ project planning framework. International Journal of Project Management, 22(6), 499–510. Nasir, H., Haas, C., Rankin, J., Fayek, A., Forgues, D. and Ruwanpura, J. 2012. Development and implementation of a benchmarking and metrics program for construction performance and productivity improvement. Canadian Journal of Civil Engineering, 39(9), 957-967.  Park, H., Thomas, S., and Tucker, R. 2005. Benchmarking of Construction Productivity. Journal of Construction Engineering and Management, 131(7), 772–778. Rankin, J., Robinson, A., Meade, G., Haas C. and Manseaue, A. 2008. Initial metrics and pilot program results for measuring the performance of the Canadian construction industry. Canadian Journal of Civil Engineering, 35(9): 894-907, 10.1139/L08-018. Safa, M., Haas, T. C., Gray, J. and Hipel, W. K. 2013. Electronic Process Management System based Front End Planning Tool (FEPT). Journal of Construction Engineering and Project Management, ISSN 2233-9582. Safa, M., Shahi, A., Haas, C. T. and Hipel, K. W. 2014. Supplier selection process in an integrated construction materials management model. Automation in Construction, 48, 64-73. Smith, C. C. 2000. Improved project definition ensures value-added performance. Part 1. Hydrocarbon Process, 79(8), 4. Wang, Y. R., and Gibson Jr, G. E. 2010. A study of preproject planning and project success using ANNs and regression models. Automation in Construction, 19(3), 341-346. Webster, J. 2004. Project planning: Getting it right the first time. IEEE Aerospace Conference Proceedings, Big Sky, Mont., 6: 3924–3930. Weerasinghe, G. K. S., Ruwanpura, J.  and Horman, M. 2007. LEED-PDRI Framework for Pre-Project Planning of Sustainable Building Projects. Journal of Green Building, 2:123-143.  Willis, C. and Rankin, J. 2012. Demonstrating a linkage between construction industry maturity and performance: a case study of Guyana and New Brunswick. Canadian Journal of Civil Engineering, 39(5), 565-578.  Zou, G. 2004. A modified poisson regression approach to prospective studies with binary data. American journal of epidemiology, 159(7), 702-706. 56-9  Faculty of EngineeringDepartment of Civil and Environmental EngineeringIDENTIFYING INFLUENTIAL FACTORS FOR CAPITAL CONSTRUCTION PROJECT PLANNING STRATEGIESMahdi SafaSandra MacGillivrayMike Davidson Kevin KaczmarczykCarl T. HaasG. Edward Gibson, Jr.June, 2015Outline of Presentation• Introduction and Needs• Front End Planning• Project Definition Rating Index• Identifying Influential Factors• Analysis and Results2What is Front End Planning?“The essential process of developing sufficient strategic information with which owners can address risk and make decisions to commit resources in order to maximize the potential for a successful project.”3Why FEP is Important?• Most important process in construction project• FEP increases the likelihood for a successful project• Poor scope definition during FEP process is the leading cause of capital project cost • Alignment recognized as an important factor during successful front end planning process4• A methodology to measure the level of scope definition– Comprehensive review– Identify gaps– Take appropriate action– Reduce risk in front end planning5Project Definition Rating IndexWhat is PDRI?• An Acronym– Project Definition Rating Index• An Index– Score along a continuum representing the level of scope definition• A Risk Management Tool– Incorporates risk factors relating to new construction (Greenfield) and renovation and revamp projectsBenefits of PDRI• Proven method to quantify the level of scope development during front end planning• Promotes alignment between owners and design contractors – Highlighting poorly defined areas in scope definition package• Provides input into the risk assessment7When to use PDRI?1 2 3Early Review2iFinal ReviewIdentifying Influential Factors• Project managers can concentrate their efforts on the more difficult aspects of projects. • Consistent deficiency predictions are provided. • The nature of the relationships between variables can be quantified. • The time saved allows project managers to focus greater time and energy on the contingency aspects of projects.9PDRI Hierarchy 10Regression Analysis Output Sample at the Category Level 11Analysis• (A1) Reliability Philosophy • (A2)  Maintenance Philosophy, as well as one• (P2)  Engineering/Construction Plan & Approach12Analysis• These elements can be used consistently only across an entire portfolio of projects for a specific construction industry sector. • These powerful influential factors cannot be used to replace the PDRI process. • The elements selected can vary from one construction industry sector to another. 13Analysis• Determining PDRI scores are a reliable leading indicator across an entire portfolio of projects • validating the process and commitment to using best practices • Facilitating management succession, and forming the basis for the long-term educational value of the FEP process• Contributing to an analysis of trends or common gaps in FEP data14Thank you!

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