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

Development of an operational excellence model to improve safety for construction organizations Liu, Huang; Jazayeri, Elyas; Dadi, Gabriel B.; Maloney, William F.; Cravey, Kristopher J. 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   DEVELOPMENT OF AN OPERATIONAL EXCELLENCE MODEL TO IMPROVE SAFETY FOR CONSTRUCTION ORGANIZATIONS Huang Liu1,3, Elyas Jazayeri1, Gabriel B. Dadi1, William F. Maloney1, and Kristopher J. Cravey2 1 Department of Civil Engineering, Univ. of Kentucky, Lexington, KY, USA 2 Business Services, Day & Zimmermann, Lancaster, PA, USA  3 huang.liu@uky.edu Abstract: Construction incidents have numerous root causes, but one of the most frequent is worker behavior. Therefore, construction safety management systems should be designed to maximize the number of safe behaviors by workers, and focus on the execution of construction safety management to achieve excellent safety performance. Operational excellence, a safety concept from the chemical processing industry, is defined as doing the right thing, the right way, every time – even when no one is watching. Good operational excellence results in effective reinforcement of appropriate safety systems, and significantly reduces the rate of unsafe behaviors. Researchers managed to embed the concept of operational excellence into construction safety management. Through an extensive literature review, discussions with industry experts on the topic, and subject matter expert validation, the researchers have developed an operational excellence model designed to evaluate and improve safety performance for construction organizations. This paper describes the model development process and the key elements included in the Operational Excellence Model (OEM). The primary contribution to the overall body of knowledge is developing a practical operational excellence model for practitioners to assess and improve safety performance through behavioral and cultural elements. 1 INTRODUCTION Despite significant reductions of incidents on construction sites in the past several decades, the injuries and fatality rates for construction workers are still higher than other industry sectors (Bureau of Labor Statistics, 2011). Many safety researchers hold a perception that inherent reasons must exist in the construction industry, which are responsible for the poor safety situation on the jobsite (Davies and Tomasin, 1990). Unsafe behavior during the execution of work is considered as an inherent reason, which causes a majority of construction incidents (Tariq et al, 2000; D.-C. Seo, 2005). Many statistical analyses of incident reports conducted in multiple countries found that almost 90% of the incidents can be attributed to unsafe behaviors or human errors (Salminen and Tallberg, 1996; Williamson and Feyer, 1990; Lutness, 1987; D. Chen and H. Tian, 2012). A conclusion can be made that unsafe behavior is the primary direct cause for the construction incidents. However, other researchers go further to explore the inherent reason behind unsafe behavior. Many unsafe behaviors can be attributed to poor construction safety culture. This idea is widely supported by many researchers (Brown et al., 2000; Oliver et al., 2002; Petersen, 1988; Tomas et al., 1999). 096-1 Poor safety culture and unsafe behaviors are both drivers of poor safety performance. Operational excellence involves cultural and behavioral constructs. Operational excellence is a concept proposed by the chemical processing industry, which is based on the philosophy that excellent operation leads to excellent safety performance. Operational excellence is defined as doing the right thing, the right way, every time – even when no one is watching. Good operational excellence results in effective reinforcement of appropriate safety systems, and significantly reduces the rate of unsafe behaviors. To achieve operational excellence, a culture dedicated to excellence must be established. Culture exists as an implicit concept that drives tangible safe behaviors. Safe behaviors generate an authentic and lasting effect on the organization, which in turn sustains and promotes the safety culture.  The primary purpose of this research is to develop a safety model involving both cultural and behavioral elements. Operational excellence is the outcome of the model, which in turn, should improve safety performance. The essence of the model is that culture drives behavior and behavior sustains culture (Maloney, 1989). Through an extensive literature review, discussions with industry experts on the topic, and subject matter expert validation, the researchers have developed an operational excellence model designed to evaluate and improve safety performance for construction organizations. This paper describes the model development process and the key elements included in the Operational Excellence Model (OEM). The primary contribution to the overall body of knowledge is developing a practical operational excellence model for practitioners to assess and improve safety performance through behavioral and cultural elements.   2 OPERATIONAL EXCELLENCE 2.1 Definition of Operational Excellence Operational excellence is a buzzword that is commonly used across various industries when addressing improvements in production, safety, quality, and cost performance, yet it is often ill defined. The fundamental idea of operational excellence is that perfect operations lead to perfect results.  Operational Performance Systems (OPS), a management consulting company, defines operational excellence as “the performance of tasks according to written expectations, policies and procedures in a safe and professional manner” (Philip, 2013). In other words, operational excellence is about creating a written standard and applying that standard rigorously and consistently across the organization. Another view is that operational excellence should be separated into organizational level and individual level components. The definition of organizational level operational excellence is “the deeply rooted dedication and commitment by every member of an organization to carrying out each task the right way, each time” (Klein et al., 2011). The definition of the individual level is “commitment to working safely by doing every task, the right way, every time” (Klein et al., 2011). In other words, there is commitment by the members collectively as an organization to do it the right way, every time and individually in their own work practices. Based on these definitions, the aim of operational excellence is to achieve exceptional performance through the engagement of all members in the organization to do the right thing, the right way, every time – even when no one is watching. Hence, determining the “right thing” and the “right way” is imperative, and those are the elements that are identified and validated in this paper. 2.2 Previous Operational Excellence Research Prior researchers utilize characteristics to describe and embody the makeup of operational excellence. Dennis Johnson (2005) compiled a set of 10 characteristics to represent operational excellence in the context of the oil industry. Brian D. Rains (2012) identified a set of 11 characteristics. James A. Klein and Bruce K. Vaughen (2008) set up an operational excellence framework consisting of 11 characteristics. Both of these models were developed for the safety improvement of chemical processing industry. Robert J. Walter (2002) proposed a more comprehensive version consisting of 15 characteristics. However, it is also designed for the chemical processing industry and the oil exploration and refining industry. 096-2 The extensive literature suggests that a lack of research on operational excellence exists, especially in the context of the construction industry.  Due to limited resources, developing OEM will take a great effort to identify, categorize and examine elements associated with the construction industry. 3 METHODOLOGY The critical elements of OEM are identified through an extensive literature review. Efforts mainly focus on previous research and professional guidance by industry association. To verify these elements, subject matter expert validation is conducted through questionnaire survey and statistical analysis. 3.1 Framework of OEM As aforementioned, this research aims at developing a model that can be used by practitioners to assess and improve safety performance through behavioral and cultural elements. However, the previous characteristics of operational excellence were compiled by other industries, and therefore have limited applicability to this OEM designed for construction projects. After discussion by the research team, the Critical to Quality (CTQ) tree was chosen as the tool to develop measurable characteristics, which arise from the six sigma methodology (Aristide et al., 2013).  CTQ trees are used to decompose broad research objectives into more easily quantified elements.  The OEM must be developed into clear, specific, quantitative requirements, so that it can be used by practitioners as an effective and practical tool. In the context of construction safety, these quantitative requirements are called Critical to Safety characteristics (CTSs). CTSs are the measurable safety characteristics that are considered important to sustain and promote construction safety. The model was structured as a Critical to Safety Tree. The model has four levels: Safety Driver (SD), Critical to Safety (CTS), Critical to Expectations (CTX, X indicates various expectations), and Specification/Measurement (S/M). SD indicates the factor that will be used to evaluate the performance of the safety program. CTS indicates elements of the driver, which corresponds to “the right thing” in the definition of operational excellence. CTX indicates behaviors and/or processes used to provide the elements, which corresponds to “the right way” in the definition of operational excellence. S/M indicates a quantitative measurement of the CTX, which corresponds to “every time” in the definition of operational excellence. Generally speaking, the four levels model represents the essence of the operational excellence: focus on doing the right thing, the right way, every time – even when no one is watching. However, the important piece of the “even when no one is watching” is not directly measured. The approach to this issue is to embed safety culture into the whole model. Culture drives behavior and behavior sustains culture. Through the rigid execution of operational excellence, the number of unsafe behaviors will be reduced and the safety culture will be reinforced. Once the safety culture is embedded into every member’s mind, the goal of “even when no one is watching” will be achieved. Consequently, CTS trees based on operational excellence will serve as the framework for the OEM. 3.2 Identifying and Categorizing the Elements of OEM  To identify and categorize the elements on each level, the research team employed three main resources: • Previous relevant research; • Documentation from industry associations and government; and • The expertise of the research team. A preliminary list of SDs was developed by the use of documentation from past research and publications, which constitutes the first level of OEM. Starting from these SDs, further development of CTSs, CTXs and S/M were conducted, and a complete and detailed list was developed. However, the original version was roughly categorized, which causes the overlapping between different characteristics. 096-3 During multiple meetings, research team members rigorously examined and refined the list through brainstorming and nominal group technique. Finally, an improved list of OEM was developed. It has 13 SDs, and each of those SDs represents a major aspect of construction safety (see Table 2 Column 2). From these 13 SDs, 75 CTSs that may have a bearing on operational excellence are identified (see Table 2 Column 2). And then 256 CTXs, and 293 S/Ms were also developed. For CTSs and CTXs, they are listed as a complete phrase or sentence, which ensure consistency of the understanding. S/Ms are ways to quantifiably measure a level of performance.  The thrust of the research team is to conceptually validate the OEM at the SD and CTS level. Therefore, the validation results that follow focus on those two levels. Future research efforts will collect data against the entirety of the model. 3.3 Validating the SDs and CTSs  Subject matter expert validation of the SDs mainly focused on determining the relative degree of significant contribution that each SD makes to operational excellence in construction safety. Researchers also obtained professional views on whether each CTS is suitable to its corresponding SD. Validation was conducted through a questionnaire survey.  For each of the SDs, participants are asked to evaluate their level of agreement with the statement that this SD is significant to operational excellence. Detailed descriptions are attached to each SD to help ensure participants’ understanding of the SD under review. The average value will be computed as the final score for each SD. Respondents are required to rate significance of contribution on a 5-point scale where 1=Disagree, 2=Neither Agree nor Disagree. 3=Slightly Agree, 4=Agree, and 5=Strongly Agree. In the case of CTSs, participants are asked to evaluate the importance of each CTS to developing and understanding of its SD. The average value will be computed as the final score for each CTS. Respondents were requested to rate importance on a 5-point scale where 1=No importance, 2=Little importance, 3=Some importance, 4=Moderate importance, and 5=Great importance. This Likert scale is skewed intentionally. The researchers had a concern that a traditional Likert scale would not show variability in the responses, since many of the items are based on previous literature and unlikely to have high levels of disagreement. 4 DATA ANALYSIS Data collection is performed through the use of Select Survey’s server-based software. Most of the participants are experienced practitioners. This online survey system is designed to provide researchers credible data and facilitate research. A total of 92 surveys were initiated, but not all were completed. Each question had a minimum of 60 responses. All responses for each question were included.  4.1 Characteristics of the Organizations Respondents were asked to provide demographic information on their organizations. Organization characteristics are shown in Table 1. Most companies have participated in national or even international projects and conducted construction-related work. Types of projects they participate in cover almost all construction sectors.   096-4 Table 1: Organization Characteristics Work Area Percentage (%) Respondent’s Organization Percentage (%) Primary Construction Sector(s) Percentage (%) Regionally 20.69 Owner 37.39 Industrial 57.03 Nationally 34.48 Designer 0.87 Commercial 23.44 Internationally 22.99 Constructor 56.52 Infrastructure/Heavy Civil 8.59 All 21.84 Other 5.22 Residential 1.56     Other 9.38 4.2 Results of the SDs and the CTSs Two criteria are developed to examine the subjective opinions from experts. The first criterion is a threshold value of 3.50 for all mean values. Three from the 5-point scale means “some importance” or “slightly agree”, a mean value higher than 3.50 indicates that experts agree with the importance of the item to the construction project safety. The second criterion is comparing the percentage of responses higher than 3 with 80%. If the percentage is higher than 80%, it means more than 80% of experts agree that this item is important to the construction project safety. Mean values are given in column 3, and the percentage of response higher than 3 is presented in column 4. The results of the survey can be seen in Tables 2-14 for each safety driver. Table 2: Survey Results for Recognition and Reward SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 1 Recognition & Reward 4.07 84.13% CTS 1.1 Recognize performance of required behaviors 4.46 88.89% CTS 1.2 Reward performance of discretionary behaviors 4.63 90.48% CTS 1.3 Celebrating group achievement of safety results 4.27 82.26% Table 3: Survey Results for Employee Engagement SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 2 Employee Engagement 4.67 98.21% CTS 2.1 Development and review of safety and health policy 4.49 89.09% CTS 2.2 Conducting risk assessments 4.55 96.36% CTS 2.3 Organizing for safety and health activities 4.18 83.64% CTS 2.4 Implementing the safety plan 4.66 96.23% CTS 2.5 Measuring safety and health performance 4.39 89.09% CTS 2.6 Investigating incidents, accidents, and near misses 4.65 89.09% CTS 2.7 Develop lessons learned from the investigations and review 4.69 94.55% 096-5 Table 4: Survey Results for Subcontractor Management SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 3 Subcontractor Management 4.60 100.00% CTS 3.1 Prequalification and selection of subcontractors 4.69 96.30% CTS 3.2 Require subcontractors to develop a project site-specific safety plan 4.51 90.91% CTS 3.3 Prime contractor/subcontractor safety meetings 4.67 96.36% CTS 3.4 Subcontractor compliance with requirements 4.55 90.91% CTS 3.5 Site safety orientation 4.54 88.89% CTS 3.6 Managerial emphasis on the importance of safety 4.73 96.36% Table 5: Survey Results for Training and Competence SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 4 Training & Competence 4.70 100.00% CTS 4.1 Identification of required safety specific competencies 4.67 94.44% CTS 4.2 Assessment of competencies held by employees 4.43 90.74% CTS 4.3 Gap analysis to determine training needs 4.24 90.74% CTS 4.4 Development of training programs to provide required competencies 4.57 96.30% CTS 4.5 Conduct training programs 4.60 94.34% CTS 4.6 Assess training programs to determine how effectively knowledge and skills have been acquired 4.40 90.74% CTS 4.7 Assess safety performance to identify needs for remedial, refresher, and new training programs 4.44 94.44% Table 6: Survey Results for Risk Awareness, Management, and Tolerance SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 5 Risk Awareness, Management & Tolerance 4.63 98.08% CTS 5.1 Considering safety and risk evaluation in all aspects of personnel planning 4.63 94.23% CTS 5.2 Evaluating daily construction risk 4.77 96.15% CTS 5.3 Considering safety and risk evaluation in the project budget development process 4.33 90.38% CTS 5.4 Reviewing safety programs and safety performance periodically by the business (Above project level) 4.42 90.38% CTS 5.5 Reducing risk tolerance of workers 4.67 96.15% 096-6 Table 7: Survey Results for Learning Organization SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 6 Learning Organization 4.35 94.12% CTS 6.1 Formal approaches 4.27 90.20% CTS 6.2 Informal approaches 4.27 88.24%  Table 8: Survey Results for Human Performance SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 7 Human Performance 4.58 94.00% CTS 7.1 Reducing errors 4.68 96.00% CTS 7.2 Managing defenses or controls: 4.65 98.00% Table 9: Survey Results for Transformational Leadership SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 8 Transformational Leadership 4.45 93.88% CTS 8.1 Challenging the process 4.39 92.00% CTS 8.2 Inspiring a shared vision 4.60 92.00% CTS 8.3 Modeling the way 4.48 91.84% CTS 8.4 Enabling others to act 4.64 94.00% CTS 8.5 Encouraging the heart 4.50 92.00% Table 10: Survey Results for Shared Values, Beliefs, and Assumptions SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 9 Shared Values, Beliefs, and Assumptions 4.46 95.83% CTS 9.1 Routines 4.45 87.76% CTS 9.2 Rituals 4.22 81.63% CTS 9.3 Stories 4.32 85.71% CTS 9.4 Symbols 3.86 69.39% CTS 9.5 Power 4.49 83.67% CTS 9.6 Safety structures 4.52 89.80% CTS 9.7 Safety controls 4.47 91.84% CTS 9.8 Underlying assumptions 4.18 81.63% 096-7 Table 11: Survey Results for Strategic Safety Communication SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 10 Strategic Safety Communication 4.40 93.75% CTS 10.1 Developing project communication program 4.50 91.84% CTS 10.2 Providing training in communication skills 4.18 83.33% CTS 10.3 Engaging in safety conversations with project personnel 4.74 97.96% CTS 10.4 Utilizing posters and newsletters 3.81 61.22% CTS 10.5 Employing visual management techniques to communicate safety performance metrics 4.24 81.25% CTS 10.6 Evaluating safety information flow 4.06 69.39% CTS 10.7 Coaching 4.64 91.84% Table 12: Survey Results for Just & Fair Practices and Procedures SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 11 Just & Fair Practices and Procedures 4.35 89.80% CTS 11.1 Developing Just & Fair policy 4.32 85.71% CTS 11.2 Developing an incident reporting system 4.53 89.80% CTS 11.3 Implementing policy & reporting system 4.29 87.76% CTS 11.4 Recognizing, rewarding, and reinforcing incident reporting 4.28 81.25% CTS 11.5 Providing feedback on incident reports 4.34 85.71% CTS 11.6 Maintaining incident reporting system 4.38 83.67% CTS 11.7 Maintaining policy and system integrity 4.46 89.58% CTS 11.8 Employee perception of safety culture 4.63 93.88% Table 13: Survey Results for Worksite Organization SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 12 Worksite Organization 4.51 93.88% CTS 12.1 Sorting 4.45 89.58% CTS 12.2 Straightening/Setting in order 4.43 91.84% CTS 12.3 Shining 4.27 81.63% CTS 12.4 Standardizing 4.32 91.84% CTS 12.5 Sustaining 4.54 91.84% 096-8 Table 14: Survey Results for Owner’s Role SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 13 Owner's Role 4.55 95.74% CTS 13.1 Establishing and communicating attitudes toward safety 4.65 95.92% CTS 13.2 Selection of contractor 4.69 95.92% CTS 13.3 Contractual safety management 4.47 93.88% CTS 13.4 Owner's involvement in safety pre-construction 4.49 91.84% CTS 13.5 Monitoring contractor safety compliance 4.54 93.75% CTS 13.6 Measuring and analyzing safety results 4.45 93.88% CTS 13.7 Participation in behavior observation surveys (BOS) 4.17 74.47% CTS 13.8 Participation in incident investigations 4.28 81.63% CTS 13.9 Providing assistance 4.44 85.71% CTS 13.10 Participation in safety training 4.33 87.76% 5 DISCUSSION Every SD has a mean value higher than 3.50 and a percentage higher 80%. This result means most experts agree that those SDs significantly contribute to the operational excellence in construction project safety. The validation of the SDs lays a solid foundation for the development of CTSs. Each of the CTSs have a mean value higher than 3.50. Most of CTSs have a percentage higher than 80%, except symbols (69.39%), utilizing posters and newsletters (61.22%), evaluating safety information flow (69.39%), and participation in behavior observation surveys (BOS) (74.47%).   Symbols do not convey detailed information, compared to other CTSs under Shared Values, Beliefs, and Assumptions. This is the reason for its low importance. Utilizing posters and newsletters is not specifically-targeted, and employees lack incentives to check things not exclusively delivered to them. This is why experts assign a lower grade to it. Evaluating safety information flow has a relatively higher mean value of 4.06, but a relatively low percentage of 69.39%. That indicates that there is a diverging opinion among experts. Safety information flow is a foreign concept for construction industry. Experts with a lack of knowledge of this concept would tend to reduce its value. Participation in behavior observation surveys (BOS) also has a relatively higher mean value and a relatively low percentage. The divergence of expert opinions exists. Some experts think BOS is not the owner’s work, others think it is. The disagreement on the owner’s role in safety management leads to the lower percentage. The CTSs that did not meet the criteria were deleted from the model. Thus, the remaining contents describe a conceptually validated model of operational excellence for construction project safety. Future work will collect data to measure the impact that operational excellence has on construction project safety. 6 CONCLUSION This study investigated the concept of operational excellence in the context of construction project safety, and developed a practical operational excellence model for practitioners to assess and improve safety performance through behavioral and cultural elements. 13 SDs and 75 CTSs were identified through an extensive and thorough literature review. To validate the applicability of the SDs and the CTSs, a subject 096-9 matter expert validation process was conducted through an online survey. Results of the SDs shows that each of the SDs has a mean value higher than 3.5, and more than 80% of experts score them with 4 or 5. This proves that experts significantly agree the contributions made by the SDs. Each of the CTSs have a mean value higher than 3.50. Except for 4 CTSs, the remainders have a percentage greater than 80%. This proves that experts significantly regard the CTSs as important for the development of the SDs. The subject matter expert validation results provide solid evidence for the validity of the OEM.  Acknowledgements This research study was made possible by the Construction Industry Institute (CII) and its members through Research Team 317. The authors wish to thank CII and the industry partners on RT 317 for the support and expertise. References Brown, K.A., Willis, P. G. and Prussia, G. E. 2000. Predicting Safe Employee Behavior in the Steel Industry: Development and Test of a Sociotechnical Model. Journal of Operations Management, 18: 445–465. Bureau of Labor Statistics 2011. Census of Fatal Occupational Injuries and Industry Injury and Illness Data. Chen, D. and Tian, H. 2012. Behavior based safety for accidents prevention and positive study in China construction project. Procedia Engineering, 43: 528–534. Davies, W.S. and Tomasin, K. 1990. Construction Safety Handbook. Thomas Telford, London. Johnson, D. 2005. Operational Discipline Workshop. AIGA 2005 Meeting. Klein, J.A. and Vaughen, B.K. 2008. A Revised Program for Operational Discipline. Process Safety Progress, 27(1): 58-65. Klein, J.A. and Vaughen, B.K. 2011. Implement an Operational Discipline Program to Improve Plant Process Safety. CEP MAGAZINE, AIChE, 48-52. Lutness, J. 1987. Measuring up: Assessing Safety with Climate Surveys. Occupational Health and Safety, 56: 20–26. Maloney, W. F. 1989. Organisational Culture: Implication for Management. Journal of Management in Engineering, 5(2), 125-138. Petersen, D. 1988. Safety Management: A Human Approach. Aloray, Inc., Goshen, NY. Rains, B.D. (2012). Driving Operational Discipline through Quality Written Procedures. 2012 Spring Meeting & 8th Global Congress on Process Safety, AIChE, Houston, TX. Salminen, S. and Tallberg, T. 1996. Human Errors in Fatal and Serious Occupational Accidents in Finland. Ergonomics, 39(7): 980–988. Seo, D-C. 2005. An Explicative Model of Unsafe Work Behaviour. Safety Science 43: 187–211. Tomas, J.M., Melia, J.L. and Oliver, A. 1999. A Cross-Validation of a Structural Equation Model of Accidents: Organizational and Psychological Variables as Predictors of Work Safety. Work and Stress, 13(1): 49–58. Walter, R.J. 2002. Discovering Operational Discipline: Principles, Attitudes, and Values That Enhance Quality, Safety, Environmental Responsibility, and Profitability. Human Resource Development Press, Amherst, MA. Williamson, A.M. and Feyer, A.-M. 1990. Behavioral Epidemiology as a Tool for Accident Research. Journal of Occupational Accidents, 12: 207–222.  096-10  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   DEVELOPMENT OF AN OPERATIONAL EXCELLENCE MODEL TO IMPROVE SAFETY FOR CONSTRUCTION ORGANIZATIONS Huang Liu1,3, Elyas Jazayeri1, Gabriel B. Dadi1, William F. Maloney1, and Kristopher J. Cravey2 1 Department of Civil Engineering, Univ. of Kentucky, Lexington, KY, USA 2 Business Services, Day & Zimmermann, Lancaster, PA, USA  3 huang.liu@uky.edu Abstract: Construction incidents have numerous root causes, but one of the most frequent is worker behavior. Therefore, construction safety management systems should be designed to maximize the number of safe behaviors by workers, and focus on the execution of construction safety management to achieve excellent safety performance. Operational excellence, a safety concept from the chemical processing industry, is defined as doing the right thing, the right way, every time – even when no one is watching. Good operational excellence results in effective reinforcement of appropriate safety systems, and significantly reduces the rate of unsafe behaviors. Researchers managed to embed the concept of operational excellence into construction safety management. Through an extensive literature review, discussions with industry experts on the topic, and subject matter expert validation, the researchers have developed an operational excellence model designed to evaluate and improve safety performance for construction organizations. This paper describes the model development process and the key elements included in the Operational Excellence Model (OEM). The primary contribution to the overall body of knowledge is developing a practical operational excellence model for practitioners to assess and improve safety performance through behavioral and cultural elements. 1 INTRODUCTION Despite significant reductions of incidents on construction sites in the past several decades, the injuries and fatality rates for construction workers are still higher than other industry sectors (Bureau of Labor Statistics, 2011). Many safety researchers hold a perception that inherent reasons must exist in the construction industry, which are responsible for the poor safety situation on the jobsite (Davies and Tomasin, 1990). Unsafe behavior during the execution of work is considered as an inherent reason, which causes a majority of construction incidents (Tariq et al, 2000; D.-C. Seo, 2005). Many statistical analyses of incident reports conducted in multiple countries found that almost 90% of the incidents can be attributed to unsafe behaviors or human errors (Salminen and Tallberg, 1996; Williamson and Feyer, 1990; Lutness, 1987; D. Chen and H. Tian, 2012). A conclusion can be made that unsafe behavior is the primary direct cause for the construction incidents. However, other researchers go further to explore the inherent reason behind unsafe behavior. Many unsafe behaviors can be attributed to poor construction safety culture. This idea is widely supported by many researchers (Brown et al., 2000; Oliver et al., 2002; Petersen, 1988; Tomas et al., 1999). 096-1 Poor safety culture and unsafe behaviors are both drivers of poor safety performance. Operational excellence involves cultural and behavioral constructs. Operational excellence is a concept proposed by the chemical processing industry, which is based on the philosophy that excellent operation leads to excellent safety performance. Operational excellence is defined as doing the right thing, the right way, every time – even when no one is watching. Good operational excellence results in effective reinforcement of appropriate safety systems, and significantly reduces the rate of unsafe behaviors. To achieve operational excellence, a culture dedicated to excellence must be established. Culture exists as an implicit concept that drives tangible safe behaviors. Safe behaviors generate an authentic and lasting effect on the organization, which in turn sustains and promotes the safety culture.  The primary purpose of this research is to develop a safety model involving both cultural and behavioral elements. Operational excellence is the outcome of the model, which in turn, should improve safety performance. The essence of the model is that culture drives behavior and behavior sustains culture (Maloney, 1989). Through an extensive literature review, discussions with industry experts on the topic, and subject matter expert validation, the researchers have developed an operational excellence model designed to evaluate and improve safety performance for construction organizations. This paper describes the model development process and the key elements included in the Operational Excellence Model (OEM). The primary contribution to the overall body of knowledge is developing a practical operational excellence model for practitioners to assess and improve safety performance through behavioral and cultural elements.   2 OPERATIONAL EXCELLENCE 2.1 Definition of Operational Excellence Operational excellence is a buzzword that is commonly used across various industries when addressing improvements in production, safety, quality, and cost performance, yet it is often ill defined. The fundamental idea of operational excellence is that perfect operations lead to perfect results.  Operational Performance Systems (OPS), a management consulting company, defines operational excellence as “the performance of tasks according to written expectations, policies and procedures in a safe and professional manner” (Philip, 2013). In other words, operational excellence is about creating a written standard and applying that standard rigorously and consistently across the organization. Another view is that operational excellence should be separated into organizational level and individual level components. The definition of organizational level operational excellence is “the deeply rooted dedication and commitment by every member of an organization to carrying out each task the right way, each time” (Klein et al., 2011). The definition of the individual level is “commitment to working safely by doing every task, the right way, every time” (Klein et al., 2011). In other words, there is commitment by the members collectively as an organization to do it the right way, every time and individually in their own work practices. Based on these definitions, the aim of operational excellence is to achieve exceptional performance through the engagement of all members in the organization to do the right thing, the right way, every time – even when no one is watching. Hence, determining the “right thing” and the “right way” is imperative, and those are the elements that are identified and validated in this paper. 2.2 Previous Operational Excellence Research Prior researchers utilize characteristics to describe and embody the makeup of operational excellence. Dennis Johnson (2005) compiled a set of 10 characteristics to represent operational excellence in the context of the oil industry. Brian D. Rains (2012) identified a set of 11 characteristics. James A. Klein and Bruce K. Vaughen (2008) set up an operational excellence framework consisting of 11 characteristics. Both of these models were developed for the safety improvement of chemical processing industry. Robert J. Walter (2002) proposed a more comprehensive version consisting of 15 characteristics. However, it is also designed for the chemical processing industry and the oil exploration and refining industry. 096-2 The extensive literature suggests that a lack of research on operational excellence exists, especially in the context of the construction industry.  Due to limited resources, developing OEM will take a great effort to identify, categorize and examine elements associated with the construction industry. 3 METHODOLOGY The critical elements of OEM are identified through an extensive literature review. Efforts mainly focus on previous research and professional guidance by industry association. To verify these elements, subject matter expert validation is conducted through questionnaire survey and statistical analysis. 3.1 Framework of OEM As aforementioned, this research aims at developing a model that can be used by practitioners to assess and improve safety performance through behavioral and cultural elements. However, the previous characteristics of operational excellence were compiled by other industries, and therefore have limited applicability to this OEM designed for construction projects. After discussion by the research team, the Critical to Quality (CTQ) tree was chosen as the tool to develop measurable characteristics, which arise from the six sigma methodology (Aristide et al., 2013).  CTQ trees are used to decompose broad research objectives into more easily quantified elements.  The OEM must be developed into clear, specific, quantitative requirements, so that it can be used by practitioners as an effective and practical tool. In the context of construction safety, these quantitative requirements are called Critical to Safety characteristics (CTSs). CTSs are the measurable safety characteristics that are considered important to sustain and promote construction safety. The model was structured as a Critical to Safety Tree. The model has four levels: Safety Driver (SD), Critical to Safety (CTS), Critical to Expectations (CTX, X indicates various expectations), and Specification/Measurement (S/M). SD indicates the factor that will be used to evaluate the performance of the safety program. CTS indicates elements of the driver, which corresponds to “the right thing” in the definition of operational excellence. CTX indicates behaviors and/or processes used to provide the elements, which corresponds to “the right way” in the definition of operational excellence. S/M indicates a quantitative measurement of the CTX, which corresponds to “every time” in the definition of operational excellence. Generally speaking, the four levels model represents the essence of the operational excellence: focus on doing the right thing, the right way, every time – even when no one is watching. However, the important piece of the “even when no one is watching” is not directly measured. The approach to this issue is to embed safety culture into the whole model. Culture drives behavior and behavior sustains culture. Through the rigid execution of operational excellence, the number of unsafe behaviors will be reduced and the safety culture will be reinforced. Once the safety culture is embedded into every member’s mind, the goal of “even when no one is watching” will be achieved. Consequently, CTS trees based on operational excellence will serve as the framework for the OEM. 3.2 Identifying and Categorizing the Elements of OEM  To identify and categorize the elements on each level, the research team employed three main resources: • Previous relevant research; • Documentation from industry associations and government; and • The expertise of the research team. A preliminary list of SDs was developed by the use of documentation from past research and publications, which constitutes the first level of OEM. Starting from these SDs, further development of CTSs, CTXs and S/M were conducted, and a complete and detailed list was developed. However, the original version was roughly categorized, which causes the overlapping between different characteristics. 096-3 During multiple meetings, research team members rigorously examined and refined the list through brainstorming and nominal group technique. Finally, an improved list of OEM was developed. It has 13 SDs, and each of those SDs represents a major aspect of construction safety (see Table 2 Column 2). From these 13 SDs, 75 CTSs that may have a bearing on operational excellence are identified (see Table 2 Column 2). And then 256 CTXs, and 293 S/Ms were also developed. For CTSs and CTXs, they are listed as a complete phrase or sentence, which ensure consistency of the understanding. S/Ms are ways to quantifiably measure a level of performance.  The thrust of the research team is to conceptually validate the OEM at the SD and CTS level. Therefore, the validation results that follow focus on those two levels. Future research efforts will collect data against the entirety of the model. 3.3 Validating the SDs and CTSs  Subject matter expert validation of the SDs mainly focused on determining the relative degree of significant contribution that each SD makes to operational excellence in construction safety. Researchers also obtained professional views on whether each CTS is suitable to its corresponding SD. Validation was conducted through a questionnaire survey.  For each of the SDs, participants are asked to evaluate their level of agreement with the statement that this SD is significant to operational excellence. Detailed descriptions are attached to each SD to help ensure participants’ understanding of the SD under review. The average value will be computed as the final score for each SD. Respondents are required to rate significance of contribution on a 5-point scale where 1=Disagree, 2=Neither Agree nor Disagree. 3=Slightly Agree, 4=Agree, and 5=Strongly Agree. In the case of CTSs, participants are asked to evaluate the importance of each CTS to developing and understanding of its SD. The average value will be computed as the final score for each CTS. Respondents were requested to rate importance on a 5-point scale where 1=No importance, 2=Little importance, 3=Some importance, 4=Moderate importance, and 5=Great importance. This Likert scale is skewed intentionally. The researchers had a concern that a traditional Likert scale would not show variability in the responses, since many of the items are based on previous literature and unlikely to have high levels of disagreement. 4 DATA ANALYSIS Data collection is performed through the use of Select Survey’s server-based software. Most of the participants are experienced practitioners. This online survey system is designed to provide researchers credible data and facilitate research. A total of 92 surveys were initiated, but not all were completed. Each question had a minimum of 60 responses. All responses for each question were included.  4.1 Characteristics of the Organizations Respondents were asked to provide demographic information on their organizations. Organization characteristics are shown in Table 1. Most companies have participated in national or even international projects and conducted construction-related work. Types of projects they participate in cover almost all construction sectors.   096-4 Table 1: Organization Characteristics Work Area Percentage (%) Respondent’s Organization Percentage (%) Primary Construction Sector(s) Percentage (%) Regionally 20.69 Owner 37.39 Industrial 57.03 Nationally 34.48 Designer 0.87 Commercial 23.44 Internationally 22.99 Constructor 56.52 Infrastructure/Heavy Civil 8.59 All 21.84 Other 5.22 Residential 1.56     Other 9.38 4.2 Results of the SDs and the CTSs Two criteria are developed to examine the subjective opinions from experts. The first criterion is a threshold value of 3.50 for all mean values. Three from the 5-point scale means “some importance” or “slightly agree”, a mean value higher than 3.50 indicates that experts agree with the importance of the item to the construction project safety. The second criterion is comparing the percentage of responses higher than 3 with 80%. If the percentage is higher than 80%, it means more than 80% of experts agree that this item is important to the construction project safety. Mean values are given in column 3, and the percentage of response higher than 3 is presented in column 4. The results of the survey can be seen in Tables 2-14 for each safety driver. Table 2: Survey Results for Recognition and Reward SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 1 Recognition & Reward 4.07 84.13% CTS 1.1 Recognize performance of required behaviors 4.46 88.89% CTS 1.2 Reward performance of discretionary behaviors 4.63 90.48% CTS 1.3 Celebrating group achievement of safety results 4.27 82.26% Table 3: Survey Results for Employee Engagement SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 2 Employee Engagement 4.67 98.21% CTS 2.1 Development and review of safety and health policy 4.49 89.09% CTS 2.2 Conducting risk assessments 4.55 96.36% CTS 2.3 Organizing for safety and health activities 4.18 83.64% CTS 2.4 Implementing the safety plan 4.66 96.23% CTS 2.5 Measuring safety and health performance 4.39 89.09% CTS 2.6 Investigating incidents, accidents, and near misses 4.65 89.09% CTS 2.7 Develop lessons learned from the investigations and review 4.69 94.55% 096-5 Table 4: Survey Results for Subcontractor Management SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 3 Subcontractor Management 4.60 100.00% CTS 3.1 Prequalification and selection of subcontractors 4.69 96.30% CTS 3.2 Require subcontractors to develop a project site-specific safety plan 4.51 90.91% CTS 3.3 Prime contractor/subcontractor safety meetings 4.67 96.36% CTS 3.4 Subcontractor compliance with requirements 4.55 90.91% CTS 3.5 Site safety orientation 4.54 88.89% CTS 3.6 Managerial emphasis on the importance of safety 4.73 96.36% Table 5: Survey Results for Training and Competence SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 4 Training & Competence 4.70 100.00% CTS 4.1 Identification of required safety specific competencies 4.67 94.44% CTS 4.2 Assessment of competencies held by employees 4.43 90.74% CTS 4.3 Gap analysis to determine training needs 4.24 90.74% CTS 4.4 Development of training programs to provide required competencies 4.57 96.30% CTS 4.5 Conduct training programs 4.60 94.34% CTS 4.6 Assess training programs to determine how effectively knowledge and skills have been acquired 4.40 90.74% CTS 4.7 Assess safety performance to identify needs for remedial, refresher, and new training programs 4.44 94.44% Table 6: Survey Results for Risk Awareness, Management, and Tolerance SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 5 Risk Awareness, Management & Tolerance 4.63 98.08% CTS 5.1 Considering safety and risk evaluation in all aspects of personnel planning 4.63 94.23% CTS 5.2 Evaluating daily construction risk 4.77 96.15% CTS 5.3 Considering safety and risk evaluation in the project budget development process 4.33 90.38% CTS 5.4 Reviewing safety programs and safety performance periodically by the business (Above project level) 4.42 90.38% CTS 5.5 Reducing risk tolerance of workers 4.67 96.15% 096-6 Table 7: Survey Results for Learning Organization SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 6 Learning Organization 4.35 94.12% CTS 6.1 Formal approaches 4.27 90.20% CTS 6.2 Informal approaches 4.27 88.24%  Table 8: Survey Results for Human Performance SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 7 Human Performance 4.58 94.00% CTS 7.1 Reducing errors 4.68 96.00% CTS 7.2 Managing defenses or controls: 4.65 98.00% Table 9: Survey Results for Transformational Leadership SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 8 Transformational Leadership 4.45 93.88% CTS 8.1 Challenging the process 4.39 92.00% CTS 8.2 Inspiring a shared vision 4.60 92.00% CTS 8.3 Modeling the way 4.48 91.84% CTS 8.4 Enabling others to act 4.64 94.00% CTS 8.5 Encouraging the heart 4.50 92.00% Table 10: Survey Results for Shared Values, Beliefs, and Assumptions SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 9 Shared Values, Beliefs, and Assumptions 4.46 95.83% CTS 9.1 Routines 4.45 87.76% CTS 9.2 Rituals 4.22 81.63% CTS 9.3 Stories 4.32 85.71% CTS 9.4 Symbols 3.86 69.39% CTS 9.5 Power 4.49 83.67% CTS 9.6 Safety structures 4.52 89.80% CTS 9.7 Safety controls 4.47 91.84% CTS 9.8 Underlying assumptions 4.18 81.63% 096-7 Table 11: Survey Results for Strategic Safety Communication SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 10 Strategic Safety Communication 4.40 93.75% CTS 10.1 Developing project communication program 4.50 91.84% CTS 10.2 Providing training in communication skills 4.18 83.33% CTS 10.3 Engaging in safety conversations with project personnel 4.74 97.96% CTS 10.4 Utilizing posters and newsletters 3.81 61.22% CTS 10.5 Employing visual management techniques to communicate safety performance metrics 4.24 81.25% CTS 10.6 Evaluating safety information flow 4.06 69.39% CTS 10.7 Coaching 4.64 91.84% Table 12: Survey Results for Just & Fair Practices and Procedures SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 11 Just & Fair Practices and Procedures 4.35 89.80% CTS 11.1 Developing Just & Fair policy 4.32 85.71% CTS 11.2 Developing an incident reporting system 4.53 89.80% CTS 11.3 Implementing policy & reporting system 4.29 87.76% CTS 11.4 Recognizing, rewarding, and reinforcing incident reporting 4.28 81.25% CTS 11.5 Providing feedback on incident reports 4.34 85.71% CTS 11.6 Maintaining incident reporting system 4.38 83.67% CTS 11.7 Maintaining policy and system integrity 4.46 89.58% CTS 11.8 Employee perception of safety culture 4.63 93.88% Table 13: Survey Results for Worksite Organization SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 12 Worksite Organization 4.51 93.88% CTS 12.1 Sorting 4.45 89.58% CTS 12.2 Straightening/Setting in order 4.43 91.84% CTS 12.3 Shining 4.27 81.63% CTS 12.4 Standardizing 4.32 91.84% CTS 12.5 Sustaining 4.54 91.84% 096-8 Table 14: Survey Results for Owner’s Role SD Model Element ID Safety Drivers and Critical to Safety Elements Mean Percentage of response higher than 3 1 2 3 4 SD 13 Owner's Role 4.55 95.74% CTS 13.1 Establishing and communicating attitudes toward safety 4.65 95.92% CTS 13.2 Selection of contractor 4.69 95.92% CTS 13.3 Contractual safety management 4.47 93.88% CTS 13.4 Owner's involvement in safety pre-construction 4.49 91.84% CTS 13.5 Monitoring contractor safety compliance 4.54 93.75% CTS 13.6 Measuring and analyzing safety results 4.45 93.88% CTS 13.7 Participation in behavior observation surveys (BOS) 4.17 74.47% CTS 13.8 Participation in incident investigations 4.28 81.63% CTS 13.9 Providing assistance 4.44 85.71% CTS 13.10 Participation in safety training 4.33 87.76% 5 DISCUSSION Every SD has a mean value higher than 3.50 and a percentage higher 80%. This result means most experts agree that those SDs significantly contribute to the operational excellence in construction project safety. The validation of the SDs lays a solid foundation for the development of CTSs. Each of the CTSs have a mean value higher than 3.50. Most of CTSs have a percentage higher than 80%, except symbols (69.39%), utilizing posters and newsletters (61.22%), evaluating safety information flow (69.39%), and participation in behavior observation surveys (BOS) (74.47%).   Symbols do not convey detailed information, compared to other CTSs under Shared Values, Beliefs, and Assumptions. This is the reason for its low importance. Utilizing posters and newsletters is not specifically-targeted, and employees lack incentives to check things not exclusively delivered to them. This is why experts assign a lower grade to it. Evaluating safety information flow has a relatively higher mean value of 4.06, but a relatively low percentage of 69.39%. That indicates that there is a diverging opinion among experts. Safety information flow is a foreign concept for construction industry. Experts with a lack of knowledge of this concept would tend to reduce its value. Participation in behavior observation surveys (BOS) also has a relatively higher mean value and a relatively low percentage. The divergence of expert opinions exists. Some experts think BOS is not the owner’s work, others think it is. The disagreement on the owner’s role in safety management leads to the lower percentage. The CTSs that did not meet the criteria were deleted from the model. Thus, the remaining contents describe a conceptually validated model of operational excellence for construction project safety. Future work will collect data to measure the impact that operational excellence has on construction project safety. 6 CONCLUSION This study investigated the concept of operational excellence in the context of construction project safety, and developed a practical operational excellence model for practitioners to assess and improve safety performance through behavioral and cultural elements. 13 SDs and 75 CTSs were identified through an extensive and thorough literature review. To validate the applicability of the SDs and the CTSs, a subject 096-9 matter expert validation process was conducted through an online survey. Results of the SDs shows that each of the SDs has a mean value higher than 3.5, and more than 80% of experts score them with 4 or 5. This proves that experts significantly agree the contributions made by the SDs. Each of the CTSs have a mean value higher than 3.50. Except for 4 CTSs, the remainders have a percentage greater than 80%. This proves that experts significantly regard the CTSs as important for the development of the SDs. The subject matter expert validation results provide solid evidence for the validity of the OEM.  Acknowledgements This research study was made possible by the Construction Industry Institute (CII) and its members through Research Team 317. The authors wish to thank CII and the industry partners on RT 317 for the support and expertise. References Brown, K.A., Willis, P. G. and Prussia, G. E. 2000. Predicting Safe Employee Behavior in the Steel Industry: Development and Test of a Sociotechnical Model. Journal of Operations Management, 18: 445–465. Bureau of Labor Statistics 2011. Census of Fatal Occupational Injuries and Industry Injury and Illness Data. Chen, D. and Tian, H. 2012. Behavior based safety for accidents prevention and positive study in China construction project. Procedia Engineering, 43: 528–534. Davies, W.S. and Tomasin, K. 1990. Construction Safety Handbook. Thomas Telford, London. Johnson, D. 2005. Operational Discipline Workshop. AIGA 2005 Meeting. Klein, J.A. and Vaughen, B.K. 2008. A Revised Program for Operational Discipline. Process Safety Progress, 27(1): 58-65. Klein, J.A. and Vaughen, B.K. 2011. Implement an Operational Discipline Program to Improve Plant Process Safety. CEP MAGAZINE, AIChE, 48-52. Lutness, J. 1987. Measuring up: Assessing Safety with Climate Surveys. Occupational Health and Safety, 56: 20–26. Maloney, W. F. 1989. Organisational Culture: Implication for Management. Journal of Management in Engineering, 5(2), 125-138. Petersen, D. 1988. Safety Management: A Human Approach. Aloray, Inc., Goshen, NY. Rains, B.D. (2012). Driving Operational Discipline through Quality Written Procedures. 2012 Spring Meeting & 8th Global Congress on Process Safety, AIChE, Houston, TX. Salminen, S. and Tallberg, T. 1996. Human Errors in Fatal and Serious Occupational Accidents in Finland. Ergonomics, 39(7): 980–988. Seo, D-C. 2005. An Explicative Model of Unsafe Work Behaviour. Safety Science 43: 187–211. Tomas, J.M., Melia, J.L. and Oliver, A. 1999. A Cross-Validation of a Structural Equation Model of Accidents: Organizational and Psychological Variables as Predictors of Work Safety. Work and Stress, 13(1): 49–58. Walter, R.J. 2002. Discovering Operational Discipline: Principles, Attitudes, and Values That Enhance Quality, Safety, Environmental Responsibility, and Profitability. Human Resource Development Press, Amherst, MA. Williamson, A.M. and Feyer, A.-M. 1990. Behavioral Epidemiology as a Tool for Accident Research. Journal of Occupational Accidents, 12: 207–222.  096-10  Development of an Operational Excellence Model to Improve Safety for Construction OrganizationsHuang Liu1, Elyas Jazayeri2, Gabriel B. Dadi, Ph.D., P.E.3, William F. Maloney, Ph.D.4, Kristopher J. Cravey, Ph.D.51 Ph.D. Candidate, Univ. of Kentucky, 2 Ph.D. Student, Univ. of Kentucky, 3Assistant Professor, Univ. of Kentucky, 4Raymond-Shaver Professor, Univ. of Kentucky, 5 Vice President, Day & ZimmermannResearch Question• Can a sustainable step change in safety performance be achieved through an enhanced culture of rigorous operational discipline, also known as performance excellence?– How and what key elements are required to produce the improved safety performance?RT 317 - Safety Performance through Operational ExcellenceResearch Phases• Develop Operational Excellence Model• Conceptually validate the modelYears1 & 2• Identify relationship between OE adherence and safety performanceYears3 & 4CompletedIn Progress3Objectives for Phases 1• Define Operational Excellence (OE) in the context of construction project safety• Develop a model framework for OE• Create model structure• Formulate model within the research team• Validate model with subject matter expertsFormulate modelDevelop frameworkCreate modelDefine OEValidate model4Formulate modelDevelop frameworkCreate modelDefine OEValidate model4DefinitionOperational ExcellenceDoing the Right thing, the Right way, Every time, even when no one is watching5Formulate modelDevelop frameworkCreate modelDefine OEValidate model5Sustained Improvement through Behavior and CultureDeJoy ModelCultureBehavior6Formulate modelDevelop frameworkCreate modelDefine OEValidate model6How do you quantify an excellent cup of coffee?7Formulate modelDevelop frameworkCreate modelDefine OEValidate model7RT 317’s Operational Excellence Model FrameworkOperationalExcellenceDriver (OED)Critical toSafetyElement (CTS)Critical toSafetyExpectation (CTX)Specification/Measurement(S/M)8Formulate modelDevelop frameworkCreate modelDefine OEValidate model8RT 317 OE Model9Formulate modelDevelop frameworkCreate modelDefine OEValidate modelZero InjuriesEmployee EngagementRecognition and RewardSubcontractor ManagementTraining and CompetenceRisk Awareness, Management, and ToleranceLearning OrganizationHuman PerformanceStrategic Safety CommunicationWorksite OrganizationOwner’s Role in SafetyTransformational LeadershipShared Values, Beliefs, and AssumptionsJust and Fair Practices and ProceduresCustomerRequirementSafetyDrivers**BehavioralCultural9Significant Information Sources• DuPont – series of publications on operational discipline• Zurich - Management Safety Culture Assessment• CII’s Owner’s Role in Safety, Leadership, and Subcontractor Management literature• CURT Owner’s Safety Blueprint, Contractor Safety Prequalification, Improving Safety Programs, Managing Safety Performance• Institute of Nuclear Power Operations• Toyota Production System10Formulate modelDevelop frameworkCreate modelDefine OEValidate model10Formulation of the Model• Internal formulation– The team reviewed and edited the model through 4 face to face meetings and 4 web meetings• External formulation– The PIs discussed the model with CURT’s safety committee on several occasions– Portions of the model were reviewed by subject matter experts in the area• Charlie Soczek and Brian Rains, DuPont• Richard Boutwell, PhD, Consultant to DuPont• Dominic Cooper, PhD., Consultant on Safety Culture• Chris Garrabrant, PhD., Zurich11Formulate modelDevelop frameworkCreate modelDefine OEValidate model11Peer Validation Process• Sent out survey to CII and CURT member companies• Survey focused on validating the inclusion of the safety drivers and CTSs– How important is each safety driver and CTS?– 80% agreed or strongly agreed and >3.5 were kept in the model123453.512Formulate modelDevelop frameworkCreate modelDefine OEValidate model12Survey Demographics38%57%5%Respondent MixOwner ContractorOther57%23%9%2% 9%Respondents by Construction SectorIndustrial CommercialInfrastructure ResidentialOther13Formulate modelDevelop frameworkCreate modelDefine OEValidate model13Survey Results• 92 individuals completed at least a portion of the survey– 3 CTSs met the elimination criteria– Additional comments were supportive of the effort “Plan your work and work your plan…or plan to fail”“Safety is not just a culture, it is a way of life”“Leadership importance cannot be overstated”“Collectively all of these adds to the culture of safety”“Coaching is the key component of improving safety culture”14Formulate modelDevelop frameworkCreate modelDefine OEValidate model14Final Conceptual ModelBenefits of Model• Identify what is being done and what is not being done– Identify gaps • Identify what is being done informally and what is being done formally• Identify how well a process is being performed• Identify areas of opportunity for improvementModel Outcomes• Develops the gold standard for Operational Excellence in construction project safety– Identifies those  processes that must be undertaken to achieve operational excellence in construction safety– Identifies the elements of each of those processes – Assesses the extent to which each of the elements is performed • Supports the culture change necessary to drive behavior and decision making in the organizationNext Steps (1/2)• Conduct a Delphi panel to weight the drivers– Expert based iterative process– Assigns weights to identify significance• Review & refine the model based on outcomes of the Delphi panel• Operationalize the model– Converts model from conceptual to functionalNext Steps (2/2)• Develop self-assessment tool– Converts operationalized model to a formal assessment tool• Collect data on the extent to which firms adhere to the model using organization and project level data• Identify the relationship between safety performance and adherence to the model as measured by the Operational Excellence index• Detailed implementation strategies to achieve the gold standard 

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