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

Measuring high-level project productivity for Alberta capital projects Yun, Sungmin; Mulva, Stephen P.; Kim, Dae Y. 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   MEASURING HIGH-LEVEL PROJECT PRODUCTIVITY FOR ALBERTA CAPITAL PROJECTS Sungmin Yun1,3, Stephen P. Mulva1 , Dae Y. Kim2 1 Construction Industry Institute, University of Texas at Austin, USA 2 Department of Architectural Engineering, Dong-Eui University, South Korea 3 smyun@utexas.edu Abstract: This paper contemplates the development of a single high-level productivity metric for Alberta capital projects in order to represent overall improvement over time. The Industry Leaders Roundtable would use this metric to challenge the status quo, and formulate “out of the box” thinking to improve Alberta Megaproject productivity. The measure would be most relevant for the owner; however, owners and industry need to be supportive to make it successful. For this purpose, the proposed study includes comparisons with data held by the Construction Industry Institute (CII) such as COAA (Construction Owner’s Association of Alberta) and CII Performance Assessment Database. This paper establishes selection criteria for input/output variables for the high-level productivity metrics based on the comprehensive review of existing productivity metrics and create a high-level productivity metric.  Data are collected from COAA and CII Performance Assessment Database. Descriptive and statistical inferential analyses are conducted for comparison of high-level project productivity between Alberta and U.S. capital projects. The results of this study are anticipated to provide a single high-level productivity metrics with informative quantitative analyses for Alberta projects. 1 INTRODUCTION Construction industry has been a significant role in Alberta’s as well as Canada’s economy. In 2013, the construction sector represents 10.9% of $338.2 billion (CND) of total gross domestic product in Alberta (Alberta Government, 2015). Over the two decades, the construction industry in Alberta increases from $4.5 billion (CND) to $36.8 billion (CND). Especially, oil sands industry is a big portion of the construction sector in Alberta and more than $102 Billion (CDN) was spent on construction and operation capital necessary to develop oil sands resources (COAA, 2009). While the size of construction industry increases, the productivity performance and improvement in Alberta’s construction industry have been declining. This decline in Alberta is consistent with the decline of construction productivity in North America region over the past three decades (Jergeas, 2009).     For improving performance of construction productivity, academic researchers and industry practitioners have tried to provide effective productivity measurements. In usual, construction labor productivity is measured in actual work-hours per installed quantity. This measurement has been widely adopted in existing productivity studies (Yi and Chan, 2014). However, this productivity measurement focused on micro-level measurement for construction productivity depending on disciplines and workers. In spite of outstanding contributions from the previous studies, a high-level project productivity measurement has been demanding to capture overall improvement of project productivity for capital projects over time. The 239-1 Industry Leaders Roundtable in Alberta seeks a comprehensive measurement of high-level project productivity to challenge the status quo, and formulate “out of the box” thinking to improve Alberta capital project productivity.   This paper contemplates and presents possible measurement of high-level project productivity for Alberta capital projects. This paper aims to identify the most appropriate single, high-level project productivity metric for Alberta’s capital projects in order to gauge overall status and trends across the industry based on pros and cons of each measurement. This paper also compares Alberta capital projects’ project productivity with those of U.S. capital projects as a benchmark. 2 RESEARCH BACKGROUND 2.1 COAA-CII Performance Assessment Initiative As the principal industry association for capital projects in Alberta, the Construction Owners Association of Alberta (COAA) strives to provide leadership to enable its owner members to be successful in their drive for safe, effective and productive project execution. Since 2005, COAA and CII have had a collaborative partnership for the purpose of benchmarking capital projects in Alberta. Building on the collective expertise of COAA and CII, the COAA Benchmarking program has provided a comprehensive performance assessment system comprised of a customized questionnaire, a dedicated database, and a suite of individualized reports for each company submitting project data as shown in Figure 1. This program was funded by COAA with assistance from Alberta Finance and Enterprise, a component of the provincial government of Alberta, and operated by University of Calgary Performance Assessment Lab.      Figure 1: COAA Major Performance Assessment System  Since 2005, the collective effort of COAA and CII has focused on exploring the performance and productivity concerning the execution of capital projects in Alberta. This collaboration was premised on the extensive experience of CII in researching and benchmarking industrial facilities in the United States and around the world. Extending CII’s reach into Alberta permitted tremendous understanding of the performance of these projects, especially when compared with similar projects in the United States. In the line of this efforts, this study develops a high-level project productivity metric for Alberta capital projects. 239-2 3 METHODOLOGY 3.1 High-Level Project Productivity Metrics  To develop high-level project productivity measurement, the reasonable input and output need to be defined to meet the purpose of measurement. This study adopts two approaches for exploring high-level productivity measurement in Alberta capital projects.   First, a quantity-based approach is applied which aggregates construction productivity in major construction disciplines including concrete, structure steel, piping, equipment, electrical, insulation, and instrumentation. Construction productivity of each discipline is measured based on actual work-hours per installed quantity. When using this manner, lower productivity values indicate better productivity performance. Using this quantity-based approach, the CII developed project-level engineering and construction productivity metrics to measure high-level project productivity of capital projects. This approach was applied to measure project-level productivity through standardization and aggregation of productivity metrics of engineering and construction disciplines (Liao, 2012; Chanmeka, 2012). Similarly, the project-level construction productivity metric was calculated through the following procedures: • Transformation: For calculating project-level productivity metric, the productivity data first needs to be assessed on normality of the distribution because the standardization is conducted based on the assumption of normal distribution of the data. This study checked the normality and skewedness on the distribution of productivity values and applied natural log transformation to transform the skewed productivity data for standardization.  • Standardization: The transformed productivity values of the disciplines were standardized to z-score which standard score which means the number of standard deviations. In practice, the absolute value of this metric represents the distance between the productivity value of one project and the population mean of the productivity values in units of the standards deviation. A value is negative when the productivity is below the average, positive when above.   iz = iiijpσµ−=  where: iz =  z score of thi construction discipline’s productivity; ip = the transformed productivity metric value of thi  construction discipline’s thj  project; iµ = mean value of  the transformed productivity metric value of thi  construction discipline; iσ = standard deviation of the transformed productivity metric value of thi  construction discipline.  • Aggregation: Through the standardization of the productivity values, the variability of productivity values in different disciplines was neutralized and calibrated in the same scale suitable for aggregation. The standardized productivity values of construction disciplines are aggregated using work-hours as the weights because work-hours is usually considered as a common parameter amongst different disciplines (Liao, 2012). The standardized productivity values in different disciplines are aggregated using the following equation:  Project Level Productivity Metric ∑∑==×=niiniiiWHzWH11)( 239-4 where: iz = z score of thi  construction discipline’s productivity; iWH = work hours of the thi construction discipline. Second, a cost-based approach is also used which considers costs for construction activities as an output. Total site work-hours is considered as hours worked in construction field. All costs have been normalized in terms of currency, location, and time. The normalized cost are value in 2013 Chicago. Similarly, this approach is applied to high-level productivity measurement. The following costs were considered as output.  • The total constructed cost includes all costs, direct and indirect, inherent in converting a design plan for material and equipment into a project ready for start-up or commissioning, but not in production operation; the sum of field labor, supervision, administration, tools, field office expense, materials, equipment, and subcontracts. Therefore, this study uses sum of procurement and construction cost as total constructed cost.   • The construction phase cost includes the costs of construction activities from commencement of foundation or driving piles to mechanical completion. The costs include construction project management, construction labor, and also equipment and supplies costs that are used to support construction operations and removed after commissioning. The CII defined construction direct and indirect costs for detail of typical cost elements in construction phase.  • The equipment cost is the total cost of major equipment. The major equipment is commonly used interchangeably with engineered equipment. It is generally defined as tagged/numbered process or mechanical equipment including drivers.   When using this cost-based approach, larger productivity values indicate better productivity performance because the costs indicate amount of construction works that have been done as output. For calculating cost-based productivity metrics, the following simple equation is applied.  Project Productivity Metric = Cost for construction activities Work-hours  In addition to that, the ratio of construction phase cost to procurement cost is also considered as a high-level productivity metric. This metric indicates that how much construction cost is larger than procurement cost considering major equipment and large modularization. If major equipment or modularization is larger, the value of this metric would be smaller.   Based on these two approaches for measuring high-level project productivity, this study investigates the following five candidate as high-level project productivity measurement. 1. Project Level Construction Productivity 2. Total Constructed Cost/Total Site Work-hours 3. (Total Constructed Cost – Equipment Cost)/Total Site Work-hours 4. Construction Phase Cost/Total Site Work-hours 5. Construction Phase Cost/Procurement Cost 3.2 Data Sources and Collection This paper uses the data extracted from CII Performance Assessment Database and COAA Major Project Benchmarking Database. The CII Performance Assessment has collected capital projects data into its database through the collaboration with more than 130 industrial partners including leading construction owners and contractors around world. As of 2014, CII Performance Assessment Database suppressed 2,300 projects in its database, exceeding over $300 Billion (USD) of cumulative capital project investment since 1995 (CII, 2014).   By 2014, 60 Alberta capital project data has been collected in the COAA Major Project Benchmarking system which mainly consisted of oil sands projects including oil sands SAGD, oil sands upgrading, oil sands mining/extraction, oil and gas exploration, pipeline, and so on. The project data were extracted in 239-5 • (Total Constructed Cost – Equipment Cost)/Total Site Work-hours: The project productivity metric “(Total Constructed Cost-Equipment Cost)/Total Site Work-hours” means that the total constructed cost excluding major equipment cost per one hour worked in a capital project. The mean value of the project productivity of Alberta projects was US $157.47 per hour while that of U.S. projects was US $157.21 per hour. Thus, the Alberta projects’ productivity was slightly better than that of U.S. projects but the t-test results shows that there was no significant difference between Alberta and U.S. projects (p-value=0.989).   • Construction Phase Cost/Total Site Work-hours: The project productivity metric “Construction Phase Cost/Total Site Work-hours” means that the amount of construction phase cost per one hour worked in a capital project. The mean value of the project productivity of Alberta projects was US $161.75 per hour while that of U.S. projects was US $174.28 per hour. Thus, the U.S. projects’ productivity was slightly better than that of Alberta projects but the t-test results shows that there was no significant different between Alberta and U.S. projects (p-value=0.526).   • Construction Phase Cost/Procurement Cost: The project productivity metric “Construction Phase Cost/Procurement Cost” means that the ratio of construction phase cost to procurement cost for a capital project. The mean value of the project productivity of Alberta projects was 2.99 while that of U.S. projects was US 2.94. The value of Alberta projects (2.99) means that the construction phase cost is about three times more than procurement cost. The larger metric value indicate that the project spent smaller amount of procurement cost including equipment cost compared to other projects. Alberta project procures engineered modules Thus, the Alberta projects’ productivity was slightly better than that of U.S. projects but the t-test results shows that there was no significant different between Alberta and U.S. projects (p-value=0.793).    5 CONCLUSIONS AND PATH FORWARD This study contemplates a high-level project productivity metrics that can be used for achieving stable planning and engineering to provide the baseline estimates of planned performance. Five measurements for high-level project productivity were developed and investigated through comparison between Alberta and U.S. projects. These metrics can be used to fill the gap between country- and industry- level labor productivity calculated by government and activity- and discipline-level productivity. As the results from the t-test analysis of the productivity between Alberta and U.S. projects, Alberta projects’ project productivity tends to be lower than that of U.S. projects and can be more improved. The relatively lower productivity of Alberta’s capital projects, especially large oil and gas construction projects causes various factors such as the apparent management deficiency in management scope, time, quality, cost, productivity tools, scaffold, equipment, materials, and lack of leadership, and others (Jergeas, 2009).   For capturing high-level project productivity, the measurement requires to be easily understandable and accepted as a measure of macro-efficiency of construction execution, dis-aggregatable to figure out causes, and practical to tract and record. Based on these requirements against high-level project productivity metric, only project-level construction project productivity metric developed at CII can be dis-aggregatable. So, it can be used for the high-level productivity measurement for Alberta capital projects. However, the high level productivity measurement needs to more elaborated and improved for capturing impact of off-site costs and module costs that are very significant component of capital projects. Although the COAA-CII collective efforts lead about 60 Alberta’s projects in the COAA Large Major Benchmarking System, the number of the submitted projects is not enough to create time series trend over the time with statistical significance. Therefore, the more data collection of Alberta’s projects may be required to develop better productivity measurements.  239-8 References Alberta Government, 2014. Trends in Labour Productivity in Alberta. http://www.albertacanada.com/ business/statistics/productivity-trends.aspx Chanmeka, A., Thomas, S.R., Caldas, C.H., and Mulva, S.P. 2012. Assessing key factors impacting the performance and productivity of oil and gas project in Alberta. Canadian Journal of Civil Engineering. 39: 259-270 Construction Industry Institute (CII). 2009. The Alberta Report: COAA Major Project Benchmarking Summary. Alberta Finance and Enterprise, Alberta Energy and Construction Owners Association of Alberta. Calgary. Alberta. Canada. Construction Industry Institute (CII). 2014. CII 2013 Annual Report. Construction Industry Institute. Austin. TX. Jergeas, G. 2009. Improving Construction Productivity on Alberta Oil and Gas Capital Projects. University of Calgary. Alberta. Canada. Liao, P.C., Thomas, S.R., O’Brien, W.J. Dai, J. Mulva. S.P., and Kim, I. 2012. Benchmarking Project Level Engineering Productivity. Journal of Civil Engineering and Management. 18(2): 235-244 Statistics Canada. 2015. Table 383-0029 - Labour productivity and related variables by business sector industry, consistent with the North American Industry Classification System (NAICS) and the System of National Accounts (SNA), provinces and territories, annual (accessed: January 19, 2015) Yi, W. and Chan, A.P.C. 2014. Critical Review of Labor Productivity Research in Construction Journals. Journal of Management in Engineering, ASCE, 30(2): 214-225.    239-9  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   MEASURING HIGH-LEVEL PROJECT PRODUCTIVITY FOR ALBERTA CAPITAL PROJECTS Sungmin Yun1,3, Stephen P. Mulva1 , Dae Y. Kim2 1 Construction Industry Institute, University of Texas at Austin, USA 2 Department of Architectural Engineering, Dong-Eui University, South Korea 3 smyun@utexas.edu Abstract: This paper contemplates the development of a single high-level productivity metric for Alberta capital projects in order to represent overall improvement over time. The Industry Leaders Roundtable would use this metric to challenge the status quo, and formulate “out of the box” thinking to improve Alberta Megaproject productivity. The measure would be most relevant for the owner; however, owners and industry need to be supportive to make it successful. For this purpose, the proposed study includes comparisons with data held by the Construction Industry Institute (CII) such as COAA (Construction Owner’s Association of Alberta) and CII Performance Assessment Database. This paper establishes selection criteria for input/output variables for the high-level productivity metrics based on the comprehensive review of existing productivity metrics and create a high-level productivity metric.  Data are collected from COAA and CII Performance Assessment Database. Descriptive and statistical inferential analyses are conducted for comparison of high-level project productivity between Alberta and U.S. capital projects. The results of this study are anticipated to provide a single high-level productivity metrics with informative quantitative analyses for Alberta projects. 1 INTRODUCTION Construction industry has been a significant role in Alberta’s as well as Canada’s economy. In 2013, the construction sector represents 10.9% of $338.2 billion (CND) of total gross domestic product in Alberta (Alberta Government, 2015). Over the two decades, the construction industry in Alberta increases from $4.5 billion (CND) to $36.8 billion (CND). Especially, oil sands industry is a big portion of the construction sector in Alberta and more than $102 Billion (CDN) was spent on construction and operation capital necessary to develop oil sands resources (COAA, 2009). While the size of construction industry increases, the productivity performance and improvement in Alberta’s construction industry have been declining. This decline in Alberta is consistent with the decline of construction productivity in North America region over the past three decades (Jergeas, 2009).     For improving performance of construction productivity, academic researchers and industry practitioners have tried to provide effective productivity measurements. In usual, construction labor productivity is measured in actual work-hours per installed quantity. This measurement has been widely adopted in existing productivity studies (Yi and Chan, 2014). However, this productivity measurement focused on micro-level measurement for construction productivity depending on disciplines and workers. In spite of outstanding contributions from the previous studies, a high-level project productivity measurement has been demanding to capture overall improvement of project productivity for capital projects over time. The 239-1 Industry Leaders Roundtable in Alberta seeks a comprehensive measurement of high-level project productivity to challenge the status quo, and formulate “out of the box” thinking to improve Alberta capital project productivity.   This paper contemplates and presents possible measurement of high-level project productivity for Alberta capital projects. This paper aims to identify the most appropriate single, high-level project productivity metric for Alberta’s capital projects in order to gauge overall status and trends across the industry based on pros and cons of each measurement. This paper also compares Alberta capital projects’ project productivity with those of U.S. capital projects as a benchmark. 2 RESEARCH BACKGROUND 2.1 COAA-CII Performance Assessment Initiative As the principal industry association for capital projects in Alberta, the Construction Owners Association of Alberta (COAA) strives to provide leadership to enable its owner members to be successful in their drive for safe, effective and productive project execution. Since 2005, COAA and CII have had a collaborative partnership for the purpose of benchmarking capital projects in Alberta. Building on the collective expertise of COAA and CII, the COAA Benchmarking program has provided a comprehensive performance assessment system comprised of a customized questionnaire, a dedicated database, and a suite of individualized reports for each company submitting project data as shown in Figure 1. This program was funded by COAA with assistance from Alberta Finance and Enterprise, a component of the provincial government of Alberta, and operated by University of Calgary Performance Assessment Lab.      Figure 1: COAA Major Performance Assessment System  Since 2005, the collective effort of COAA and CII has focused on exploring the performance and productivity concerning the execution of capital projects in Alberta. This collaboration was premised on the extensive experience of CII in researching and benchmarking industrial facilities in the United States and around the world. Extending CII’s reach into Alberta permitted tremendous understanding of the performance of these projects, especially when compared with similar projects in the United States. In the line of this efforts, this study develops a high-level project productivity metric for Alberta capital projects. 239-2 3 METHODOLOGY 3.1 High-Level Project Productivity Metrics  To develop high-level project productivity measurement, the reasonable input and output need to be defined to meet the purpose of measurement. This study adopts two approaches for exploring high-level productivity measurement in Alberta capital projects.   First, a quantity-based approach is applied which aggregates construction productivity in major construction disciplines including concrete, structure steel, piping, equipment, electrical, insulation, and instrumentation. Construction productivity of each discipline is measured based on actual work-hours per installed quantity. When using this manner, lower productivity values indicate better productivity performance. Using this quantity-based approach, the CII developed project-level engineering and construction productivity metrics to measure high-level project productivity of capital projects. This approach was applied to measure project-level productivity through standardization and aggregation of productivity metrics of engineering and construction disciplines (Liao, 2012; Chanmeka, 2012). Similarly, the project-level construction productivity metric was calculated through the following procedures: • Transformation: For calculating project-level productivity metric, the productivity data first needs to be assessed on normality of the distribution because the standardization is conducted based on the assumption of normal distribution of the data. This study checked the normality and skewedness on the distribution of productivity values and applied natural log transformation to transform the skewed productivity data for standardization.  • Standardization: The transformed productivity values of the disciplines were standardized to z-score which standard score which means the number of standard deviations. In practice, the absolute value of this metric represents the distance between the productivity value of one project and the population mean of the productivity values in units of the standards deviation. A value is negative when the productivity is below the average, positive when above.   iz = iiijpσµ−=  where: iz =  z score of thi construction discipline’s productivity; ip = the transformed productivity metric value of thi  construction discipline’s thj  project; iµ = mean value of  the transformed productivity metric value of thi  construction discipline; iσ = standard deviation of the transformed productivity metric value of thi  construction discipline.  • Aggregation: Through the standardization of the productivity values, the variability of productivity values in different disciplines was neutralized and calibrated in the same scale suitable for aggregation. The standardized productivity values of construction disciplines are aggregated using work-hours as the weights because work-hours is usually considered as a common parameter amongst different disciplines (Liao, 2012). The standardized productivity values in different disciplines are aggregated using the following equation:  Project Level Productivity Metric ∑∑==×=niiniiiWHzWH11)( 239-4 where: iz = z score of thi  construction discipline’s productivity; iWH = work hours of the thi construction discipline. Second, a cost-based approach is also used which considers costs for construction activities as an output. Total site work-hours is considered as hours worked in construction field. All costs have been normalized in terms of currency, location, and time. The normalized cost are value in 2013 Chicago. Similarly, this approach is applied to high-level productivity measurement. The following costs were considered as output.  • The total constructed cost includes all costs, direct and indirect, inherent in converting a design plan for material and equipment into a project ready for start-up or commissioning, but not in production operation; the sum of field labor, supervision, administration, tools, field office expense, materials, equipment, and subcontracts. Therefore, this study uses sum of procurement and construction cost as total constructed cost.   • The construction phase cost includes the costs of construction activities from commencement of foundation or driving piles to mechanical completion. The costs include construction project management, construction labor, and also equipment and supplies costs that are used to support construction operations and removed after commissioning. The CII defined construction direct and indirect costs for detail of typical cost elements in construction phase.  • The equipment cost is the total cost of major equipment. The major equipment is commonly used interchangeably with engineered equipment. It is generally defined as tagged/numbered process or mechanical equipment including drivers.   When using this cost-based approach, larger productivity values indicate better productivity performance because the costs indicate amount of construction works that have been done as output. For calculating cost-based productivity metrics, the following simple equation is applied.  Project Productivity Metric = Cost for construction activities Work-hours  In addition to that, the ratio of construction phase cost to procurement cost is also considered as a high-level productivity metric. This metric indicates that how much construction cost is larger than procurement cost considering major equipment and large modularization. If major equipment or modularization is larger, the value of this metric would be smaller.   Based on these two approaches for measuring high-level project productivity, this study investigates the following five candidate as high-level project productivity measurement. 1. Project Level Construction Productivity 2. Total Constructed Cost/Total Site Work-hours 3. (Total Constructed Cost – Equipment Cost)/Total Site Work-hours 4. Construction Phase Cost/Total Site Work-hours 5. Construction Phase Cost/Procurement Cost 3.2 Data Sources and Collection This paper uses the data extracted from CII Performance Assessment Database and COAA Major Project Benchmarking Database. The CII Performance Assessment has collected capital projects data into its database through the collaboration with more than 130 industrial partners including leading construction owners and contractors around world. As of 2014, CII Performance Assessment Database suppressed 2,300 projects in its database, exceeding over $300 Billion (USD) of cumulative capital project investment since 1995 (CII, 2014).   By 2014, 60 Alberta capital project data has been collected in the COAA Major Project Benchmarking system which mainly consisted of oil sands projects including oil sands SAGD, oil sands upgrading, oil sands mining/extraction, oil and gas exploration, pipeline, and so on. The project data were extracted in 239-5 • (Total Constructed Cost – Equipment Cost)/Total Site Work-hours: The project productivity metric “(Total Constructed Cost-Equipment Cost)/Total Site Work-hours” means that the total constructed cost excluding major equipment cost per one hour worked in a capital project. The mean value of the project productivity of Alberta projects was US $157.47 per hour while that of U.S. projects was US $157.21 per hour. Thus, the Alberta projects’ productivity was slightly better than that of U.S. projects but the t-test results shows that there was no significant difference between Alberta and U.S. projects (p-value=0.989).   • Construction Phase Cost/Total Site Work-hours: The project productivity metric “Construction Phase Cost/Total Site Work-hours” means that the amount of construction phase cost per one hour worked in a capital project. The mean value of the project productivity of Alberta projects was US $161.75 per hour while that of U.S. projects was US $174.28 per hour. Thus, the U.S. projects’ productivity was slightly better than that of Alberta projects but the t-test results shows that there was no significant different between Alberta and U.S. projects (p-value=0.526).   • Construction Phase Cost/Procurement Cost: The project productivity metric “Construction Phase Cost/Procurement Cost” means that the ratio of construction phase cost to procurement cost for a capital project. The mean value of the project productivity of Alberta projects was 2.99 while that of U.S. projects was US 2.94. The value of Alberta projects (2.99) means that the construction phase cost is about three times more than procurement cost. The larger metric value indicate that the project spent smaller amount of procurement cost including equipment cost compared to other projects. Alberta project procures engineered modules Thus, the Alberta projects’ productivity was slightly better than that of U.S. projects but the t-test results shows that there was no significant different between Alberta and U.S. projects (p-value=0.793).    5 CONCLUSIONS AND PATH FORWARD This study contemplates a high-level project productivity metrics that can be used for achieving stable planning and engineering to provide the baseline estimates of planned performance. Five measurements for high-level project productivity were developed and investigated through comparison between Alberta and U.S. projects. These metrics can be used to fill the gap between country- and industry- level labor productivity calculated by government and activity- and discipline-level productivity. As the results from the t-test analysis of the productivity between Alberta and U.S. projects, Alberta projects’ project productivity tends to be lower than that of U.S. projects and can be more improved. The relatively lower productivity of Alberta’s capital projects, especially large oil and gas construction projects causes various factors such as the apparent management deficiency in management scope, time, quality, cost, productivity tools, scaffold, equipment, materials, and lack of leadership, and others (Jergeas, 2009).   For capturing high-level project productivity, the measurement requires to be easily understandable and accepted as a measure of macro-efficiency of construction execution, dis-aggregatable to figure out causes, and practical to tract and record. Based on these requirements against high-level project productivity metric, only project-level construction project productivity metric developed at CII can be dis-aggregatable. So, it can be used for the high-level productivity measurement for Alberta capital projects. However, the high level productivity measurement needs to more elaborated and improved for capturing impact of off-site costs and module costs that are very significant component of capital projects. Although the COAA-CII collective efforts lead about 60 Alberta’s projects in the COAA Large Major Benchmarking System, the number of the submitted projects is not enough to create time series trend over the time with statistical significance. Therefore, the more data collection of Alberta’s projects may be required to develop better productivity measurements.  239-8 References Alberta Government, 2014. Trends in Labour Productivity in Alberta. http://www.albertacanada.com/ business/statistics/productivity-trends.aspx Chanmeka, A., Thomas, S.R., Caldas, C.H., and Mulva, S.P. 2012. Assessing key factors impacting the performance and productivity of oil and gas project in Alberta. Canadian Journal of Civil Engineering. 39: 259-270 Construction Industry Institute (CII). 2009. The Alberta Report: COAA Major Project Benchmarking Summary. Alberta Finance and Enterprise, Alberta Energy and Construction Owners Association of Alberta. Calgary. Alberta. Canada. Construction Industry Institute (CII). 2014. CII 2013 Annual Report. Construction Industry Institute. Austin. TX. Jergeas, G. 2009. Improving Construction Productivity on Alberta Oil and Gas Capital Projects. University of Calgary. Alberta. Canada. Liao, P.C., Thomas, S.R., O’Brien, W.J. Dai, J. Mulva. S.P., and Kim, I. 2012. Benchmarking Project Level Engineering Productivity. Journal of Civil Engineering and Management. 18(2): 235-244 Statistics Canada. 2015. Table 383-0029 - Labour productivity and related variables by business sector industry, consistent with the North American Industry Classification System (NAICS) and the System of National Accounts (SNA), provinces and territories, annual (accessed: January 19, 2015) Yi, W. and Chan, A.P.C. 2014. Critical Review of Labor Productivity Research in Construction Journals. Journal of Management in Engineering, ASCE, 30(2): 214-225.    239-9  International Construction Specialty Conference 2015Measuring High-Level Project Productivity for Alberta Capital ProjectsSungmin Yun*, Stephen P. Mulva, Dae Y. KimSungmin Yun, Ph.D.Construction Industry InstituteThe University of Texas at Austin1Outline• Introduction• Macroeconomic Productivity Trends• High Level Productivity Measurement Quantity-Based Approach• CII Project Level Construction Productivity Cost-Based Approach• Total Constructed Cost / Direct Field Labor Hours• (Total Constructed Cost – Equipment Cost) / Direct Field Labor Hours• Total Direct Field Cost / Direct Field Labor Hours• Total Field Cost / Procurement Cost• Conclusions2IntroductionObjectives• To identify the most appropriate single, high-level project productivity metric for Alberta’s capital projects in order to gauge overall status and trends across the industry• To compare high-level project productivity between Alberta and U.S. projectsWhat is the most appropriate metric for measuring high-level project productivity, if you choose only one?3IntroductionMetric Requirements:• Provide a single, “high level” Productivity Metric. • To challenge the status quo, and formulate “out of the box” thinking to improve Alberta Megaproject productivity. • The output measure would enable trending over time.• Owners and Contractors need to be supportive to make it successful.4Introduction• Data Sources– CII General Benchmarking Database– COAA Major Project Benchmarking Database• Scope– Projects with midpoint of construction since 2001 (2001~2013)– Capital Projects in North America (U.S. and Canada)5Macroeconomic Productivity TrendsLabor Productivity =Real Gross Domestic ProductHours WorkedStatistics Canada (2015)6Approaches for Project Level Productivity MeasuresProject-Level Construction Productivity MetricsProject Level Productivity =Cost for Construction ActivitiesHours Worked Quantity-Based Approach Cost-Based ApproachProject Level Productivity =Construction CostProcurement CostOption 1:Option 2:Discipline-Level Productivity =Work-HoursInstalled Quantity*z= z score of transformed discipline-level productivityProject-Level Construction Productivity DISCIPLINE-LEVEL PRODUCTIVITYPROJECT-LEVEL CONSTRUCTION PRODUCTIVITYConcrete Field ProductivityStructural Steel Field ProductivityElectrical Field ProductivityPiping Field ProductivityInstrumentation Field ProductivityEquipment Field ProductivityInsulation Field ProductivityTransformation (Log Transformation)Standardization (Z-score)Aggregation (Weighted Z-score)Project Level Productivity Measurement Scales Note: Ward, A. W., Murray-Ward, M. (1999). Assessment in the Classroom. Belmont, CA: Wadsworth9Interpretation of Project Level Productivity ScoreProject Level Productivity ScorePercentileRank3.50 99.98%3.25 99.94%3.00 99.87%2.75 99.70%2.50 99.38%2.25 98.78%2.00 97.72%1.75 95.99%1.50 93.32%1.25 89.44%1.00 84.13%0.75 77.34%0.50 69.15%0.25 59.87%0.00 50.00%-0.25 40.13%-0.50 30.85%-0.75 22.66%-1.00 15.87%-1.25 10.56%-1.50 6.68%-1.75 4.01%-2.00 2.28%-2.25 1.22%-2.50 0.62%-2.75 0.30%-3.00 0.13%-3.25 0.06%-3.50 0.02%Example:If a project’s project level productivity score is -1, the percentile rank of the project will 15.9% from the best. This indicates that the project has better productivity than 84.1% of sample projects.WorseBetter10USAAlberta2.01.51.00.50.0-0.5-1.0-1.5-0.030.30CII Project Level Construction ProductivityAnalysis Results(N=30)                                                      (N=97)p-value = 0.021*   WorseBetterNorth America Median• Quantity-Based Project Productivity Metric26.6%11Analysis ResultsBetterWorse• Cost-Based Project Productivity Metrics12Conclusions• Quantity-based project productivity metric meets the requirements for dis-aggregatable measurement and shows statistically significance• Relatively lower productivity in Alberta’ capital projects causes various factors such as management deficiency in scope, time, quality, cost, productivity tools, scaffold, equipment, materials, and lack of leadership, etc. (Jergeas 2009)• High-level project productivity metric needs to be more elaborated and improved for capturing impacts of off-site construction, use of modularization, indirect labors and works, quality of engineering deliverables, owner’s inputs, etc.13

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