Managing Teams for Integrated Design Solutions

Managing Teams for Integrated Design Solutions Vishal Singh, Kathryn von Treuer and Kerry London¹ Deakin Univsersity, Australia ¹RMIT University, Australia Abstract: Key words: Design integration in the architecture, engineering and construction sector requires a multiplicity of skills, knowledge and experience. Design practice requires management tools and skills besides the design skills and the domain knowledge. Teams and design teams have been extensively studied, and it is widely accepted that the team management practices are contingent on the nature of collaboration. This research specifically investigates the critical success factors for managing teams for integrated design and delivery solutions (IDDS), which aims to involve virtual collaborative environments and various stakeholders and supply chain players such as architects, consultants, contractors, and suppliers across the project lifecycle. Since IDDS is a recent development, the associated teamwork factors and challenges are not currently well understood, especially for the design development phases. Therefore, there is an immediate need to investigate the teamwork requirements and challenges for successfully meeting the IDDS objectives. This paper reports the preliminary findings from an ongoing research that investigates this gap. This investigation builds on the rich literature on teamwork and organizational studies, design management and construction supply chain integration to identify the critical success factors necessary for an IDDS team. For teams to be efficient, team members need to have well developed mental models of each other, as well as the mental models for the task, process, context, and competence of the team. In particular, our question is what are the critical task, process, context and competence factors specific to the IDDS teams that involve multiple players representing the construction supply chain? How can the early identification of these factors help better team managment and enhance team efficiency? This research adopts an interdisciplinary approach to investigate these questions. The findings reported in this paper are part of an ongoing research that aims to develop a framework for teamwork in IDDS teams, based on the constructs of mental models. The framework is intended to form the basis for a computer simulation tool, which can support team management decisions and formation of IDDS teams in large construction projects. The research plans and objectives are presented in the paper. Teamwork, mental models, construction supply chain, integrated design and delivery solutions, 1. INTRODUCTION The construction industry globally is increasingly realizing the cost of inefficient processes and wastage that occurs with the traditional design delivery practice. It is widely recognized that the lack of integrated design and delivery across the construction supply chain and inefficient manpower management across the project lifecycle costs billions of dollars in waste (ACIF, 2010). Hence, there is a greater push for approaches such as Integrated Design Delivery Solutions (IDDS) that aim to create more productive environments through collaborative work processes involving information systems, enhanced skills, and integrated data across the entire project lifecycle (CIB, 2010).

2 CIB-W096 2011 Vienna Effective IDDS implementation involving integration of elements within the supply chain may reduce the waste by decreasing duplicity and increasing efficiency (King & Meyer, 2005). However, full service and process integration is challenging and many such at attempts at integration fail because of the varying effectiveness of the change management strategies and people engagement processes within larger teams and organizations (Glendinning, 2003). For teams to be efficient, team members need to have well developed mental models of each other and that of the task, process, context and competence of the team (Badke-Schaub et al., 2007; Druskat & Pescosolido, 2002; Klimoski & Mohammed, 1994; Langan-Fox et al., 2004; Lim & Klein, 2006). Mental models are the internal representation of the external world (Smyth et al., 1994). Team members develop various mental models as they interact with and observe each other (Cannon- Bowers and Salas 1997). Well developed mental models allow team members to coordinate their roles and responsibilities with the rest of the team, and create a shared understanding of the team s overall goals and objectives, which also facilitates the change management process. Well developed mental models of the team members can significantly improve the cost, schedule, and quality measures, especially in complex projects (Rouse et al. 1992), which is often the case with construction projects. However despite the importance of teamwork and the evident push for approaches such as IDDS that aim to integrate the teams across the construction supply chain, there is little research and understanding of the teamwork management issues with construction project supply chain teams. In an extensive literature review, London (2008) highlighted that the focus of past construction supply research can be organised into four key themes; logistics, construction production, strategic procurement and industrial organisation economics. Significantly there is little focussed research of the task, process, context, competence and team factors that constitute the mental models of the members of the construction project supply chain teams. Unless the various factors affecting the mental models are identified and understood, and unless corresponding team management and change management strategies are developed, it may not be possible to effectively achieve the objectives of the IDDS approaches. This paper reports on the preliminary findings from a research study that aims to identify the critical factors affecting the formation of mental models in construction project supply chain teams, especially in view of the IDDS objectives. In particular we seek to explore such questions as: What are the critical task, process, context and competence factors specific to the integrated design and delivery teams involving members from various stakeholder groups of the construction supply chain? How can the identification of these factors early on in the project help better team managment and enhance team efficiency? Can we identify the potential bottlenecks and conflicts in the mental models of the team members at the different phases of the project so that effective resource allocation and monitoring plans can be devised? How do the project conditions influence mental models, for example, how does the formation of mental models vary across distributed and collocated teams? London et al (2005) have shown that the investment in human, cultural and social capital, which are constructs closely related to team mental models is critical to the success of construction projects and the development of the organization s economic capital. This research will also analyse the task, process, context and competence factors from the inclusion of investment as a construct that provides potentially useful indicator and measure of individual and organizational motivation (von Treuer et al, 2009). This paper details the research plan. The paper also reports preliminary findings based on focus group interviews (FGIs) with representatives from Australian AEC sector on the potential challenges to integrated design delivery practice using a collaboration platform, with Building Information Model (BIM) at the core of data exchange. Thus, while the objectives of IDDS are broader than

Managing Teams for Integrated Design Solutions 3 achieving an integrated BIM delivery for the project, these discussions provide an insight into the potential challenges in managing the teamwork issues for an IDDS approach, which unlike the traditional design and delivery practice envisages including the client as an integral part of the information supply chain. Furthermore, the challenges to IDDS implementation are likely to be greater for a fully integrated construction supply chain team, integrated across the entire project lifecycle, which will be investigated in future FGIs, interviews and surveys. 2. BACKGROUND Inspired by the successful implementation of supply chain management in the manufacturing sector and their ability to integrate the design and delivery services, the construction industry policymakers have supported the adoption of the concept by construction industry participants (CIB, 2010; London, 2004). However there has been a general lack of widescale implementation in civil, residential and commercial sectors. The emphasis of management decisions in the manufacturing sector is on the modelling of volume production (Azambuja and O Brien, 2009). The construction industry, however, has a very different structural organisation. The behavioural characteristics and the industrial organisation of the supply chains within the construction sector can differ markedly (London, 2008; London, 2004). The success from the supply chain management and integrated design and delivery services in the manufacturing sector cannot be directly translated to the construction commercial sector. There are similar characteristics in the residential sector with the volume housebuilders. However, even in that sector there are limitations as the larger players are still not as significant in being able to make widescale change to the sector on their own. Coupled with this is that each tier in the supply chain has diverse players who have unique business environments and different work practices and mindsets. Therefore new research is required to understand these challenges and our project is precisely to carry this out. In the construction industry, from commercial organisations to government agencies, it has been widely acknowledged that there is a need for more efficient and easy to use decision support methods to enable coordination and control of all parties involved in the construction supply chain network (Love et al, 2009). Figure 1 provides an indication of a generic supply chain including the various actors. This representation however belies the complexity of the construction supply chain and the complex interdependencies that arise as different supply chains form for different projects. Integration of key players in the supply chain is considered to be an important part of project success. As each player pursues its own contractual objectives, it is suspected that a lack of integration and teamwork has resulted in low productivity and low innovation. Figure 1. Construction Supply Chain Economics (London, 2008)

4 CIB-W096 2011 Vienna Such challenges are likely to impede the IDDS initiatives envisioned by the construction industry as the design and delivery practice of the future. One of the biggest challenges for managers and organizations involved in the design and construction supply chain is to understand, and deal with, a distributed project team with diverse task, process, context, and team member mental models, resulting from the diversity in social, operational and functional backgrounds of the team members at individual as well as organizational level. The diverse backgrounds may result in different beliefs, cultures, goals, objectives, skills, norms, standards, and other factors that may result in syntactic as well as semantic conflicts (Druskat & Pescosolido, 2002; Langan-Fox et al., 2004; Lim & Klein, 2006). Formation of mental models has been studied across diverse domains such as defence, psychology, information technology and so on (Badke-Schaub et al., 2007, Mohammed and Dumbville, 2001). It is well established that effective teamwork requires various kinds of competencies that can be discussed in terms of the knowledge, skills and attitudes that are specific or generic to the task, and specific or generic to the team (Ancona & Caldwell, 2007; Cannon-Bowers et al., 1993; Cohen & Bailey, 1997). Hence, well developed mental models for the task, process, context, competence and the team members are critical to effective team performance (Badke-Schaub et al., 2007; Druskat & Pescosolido, 2002; Klimoski & Mohammed, 1994; Langan-Fox et al., 2004; Lim & Klein, 2006). These findings suggest that organizational contingency theories (Lawrence and Lorsch, 1967; Donaldson, 2001; Levitt et al, 1999) also apply to formation of mental models in teams. Therefore, while general patterns and critical parameters related to the formation of mental models in teams can be identified, the results may vary according to the specifics of the industry and the project, i.e., which of these parameters are applicable, and what are their values in the given industry and the project, Figure 2. TASK e.g. What is this? What comes next? PROCESS e.g. How to do this? TEAM MEMBERS e.g. Who knows what? CONTEXT e.g. What to do in this situation? COMPETENCE e.g. Can we do this? Do we have the capability? Figure 2. Mental models that team members need to develop for effective team performance The capability to predict the likely effects of pre-developed mental models of team members, based on the actual data related to their prior experience and existing mental models, and the specific project data, can significantly enhance project decision making. Such efforts are found to be useful in forming effective small project teams, where the scale of the project and the personnel data is manageable using a manual process. For example, Wilde (2007) reports how they use psychometric data and personality tests to consistently form high performing student design teams at Stanford University. However, in real world construction projects, the complexity of the supply chain, and, hence, the number of variables and the amount of data to analyze can be expected to be much higher. Personality assessments and psychometric tests are not uncommon in staffing and recruiting processes, but this approach is rarely applied to project team formation within and across the organizations. In large team sizes such as in construction projects, such tests may be useful in matching people not only based on their availability and expertise but also on their potential to collectively work together towards the project goals. However, while there is enough technical support to conduct tests for the individual s fit to the project and the organization, there is little

Managing Teams for Integrated Design Solutions 5 support to analyze how the numerous individuals, selected through this process, will work together, in different phases of the project. Hence, this research aims to address some of the related issues. Methodologically, one of the major areas of development will be to move from a static analysis approach to dynamic analysis, based on the likely emergent scenarios and interactions of personnel and project-specific data. The critical success factors pertaining to the teamwork in IDDS teams in construction projects identified from this research will be mapped to develop a framework that is intended to form the basis for a computer simulation based tool, which can support management and analysis of large data sets. The developed tool can be used to conduct predictive longitudinal simulations of how the construction project, and the project-related mental models, may evolve over time as a result of the diverse mental models of the team members at the start of the project. The simulation tool will build on the prior research on computational modelling of individuals and societies (Carley and Newell, 1994; Levitt et al 1999; Macy and Willer, 2002). 3. RESEARCH DESIGN AND ANALYSIS This research will initially utilise a grounded theory approach (Martin & Turner, 1986) where data is collected from several sources (interviews, focus groups, surveys) in order to indentify the variables which are critical to measure in the decision framework. A case study will also be conducted and will validate and refine the framework. Participants will include various members of a construction supply chain project team. This research can be categorized in the following stages, Figure 3: Interviews, FGIs and surveys Case Study Final FGIs Development of simulation tool Critical factors, preliminary framework Refined framework Validated / formalized computational framework Multiple stages: implementation, testing, model validation Figure 3. Research design; stages in development of the computational framework 3.1 Framework creation The initial framework creation will be based on the identification of the critical factors that emerge from literature review, interviews, FGIs and the survey. FGIs will include representatives from each tier and discipline of the construction supply chain. Two FGIs will be conducted for preliminary data collection. The interviews and FGIs will be recorded on tape and later transcribed. The survey questionnaire design and measures for identification of critical success factors will build on similar surveys used in assessment of integrated delivery services in other disciplines such as healthcare (vontreuer et al, 2009). Online surveys are also planned such that a larger sample size can be obtained to validate the findings from a smaller group of participants, accessed through industry networks within the Australian construction sector.

6 CIB-W096 2011 Vienna 3.2 Framework development Once the critical factors and their interdependencies have been mapped to create the framework, a case study will be conducted to refine the framework. The case study will map the mental models of the various members of a single IDDS team that is involved in distributed design and delivery. The selection of the case study will be based on the following criteria: (1) two different project teams from the same parent organization will be studied such that there is only partial overlap of members across the two teams; and (2) while project team members may be part of multiple projects at least some of the team must have committed 50% of their work hours to the current project. 3.3 Framework validation The refined framework will be presented to industry experts and representatives of various disciplines in the construction supply chain to validate the findings. Follow-up FGIs are planned where these experts can collectively provide feedback and critic the framework. The refined framework will be formalized using an object-oriented approach to form the basis for a computational model that can be used as simulation tool. 3.4 Development of simulation tool The most critical parameters related to the task, process, context and team member mental models will be computationally modelled and implemented as a simulation tool. The simulation tool will build on the prior research on computational modelling of individuals and societies (Carley and Newell, 1994, Macy and Willer, 2002). Tools such as the Virtual Design Team (VDT) (Kunz et al., 1998) are widely used and recognized as useful simulation tools for advanced project management and decision making. Singh (2010) has demonstrated that computer simulations are useful in studying the formation of team member mental models. Real world case studies and other measures of model validation will be conducted to ensure usability of the simulation tool. 4. PRELIMINARY RESEARCH DATA The findings reported in this paper are based on data from FGIs conducted with representatives from various stakeholder groups in the construction supply chain that typically form an IDDS team. This includes architects, engineers, consultants, contractors, facility managers and collaboration platform service providers for construction projects. Representatives from large contracting firms and government organizations, who often work as clients in construction projects also participated in the workshop. The FGI discussions revolved around the potential challenges to integrated design delivery practice using a collaboration platform, with BIM at the core of data exchange. The FGI participants were encouraged to discuss the challenges to using an integrated information system and Building Information Models for managing the information supply chain across the project lifecycle. The FGI discussions were recorded on tape and transcribed by the researchers to categorize the discussions across the issues relating to task, process, context, competence and team member mental models.

Managing Teams for Integrated Design Solutions 7 5. RESEARCH FINDINGS Verbal protocol analysis technique was be used to analyse the data and identify the underlying patterns and trends across the identified themes, i.e., task, process, context, competence and team. Protocol analysis is a rigorous methodology for eliciting verbal reports of thought sequences as a valid source of data on thinking (Ericsson, 2001). FGI discussions primarily revolved around the challenges in developing and using an integrated Building Information Model in a project, and the issues with managing the information supply chain. FGI discussions indicate that even at the outset of a project the different stakeholders are likely to start with conflicting mental models and apprehensions about each other s beliefs and level of engagement in the project. Table 1 lists of the key factors associated with the task, process, context, and competence and team member mental models. Table 1. Key factors associated with different mental models Themes Factors and description Task (creating an Purpose of the model: In creating an integrated BIM for the project members need a shared integrated BIM for understanding of the purpose of the model, which also determines how the task is shared and the project) distributed among the team members. Level of detail: Team members need clarity on the level of detail expected in the model. The level of detail in the model is contingent on the project requirements and the purpose of the model. Related aspects of task or model development where shared understanding is needed includes model types and sub-models, accuracy and completeness, as-built data for facilities management, and documentation and communication tasks. Process (Process needed to manage an in Integrated BIM project) Context (team situation, culture and practices) Team members need shared understanding of the processes for managing the integrated BIM project development. This includes agreed protocols and practices for business processes, collaboration and information exchange, and interaction with the model. Mutual agreement and processes are critical for the following: Design review and clash detection: Team members need agreed practices for conducting design review using BIM models and tools that allow clash detection. Participants reported resistance among some stakeholder groups to change design review norms which are currently based on document sign-offs and approvals. Version management: Concerns were raised about potential conflicts that may arise from multiple files and versions of the model that are generated across the team. Besides the management of the different versions of the model concerns were raised about the software versions as well. In general, it was agreed that versions management requires measures such as standard file nomenclature system and notifications and flagging on model updates. Data organization and management: In an integrated BIM project the amount of data generated can multiply significantly. At the same time, different disciplinary and functional groups may be working on parallel models that need to be integrated. Ideally it will be useful to have all the generated data across the entire project lifecycle stored for archiving and history tractability for legal reasons. But that may lead to data explosion. Hence, mutually agreed data management processes are required for decision making such as data pruning. Work culture and practice: Project teams and organizations may vary significantly in their culture and work practice. Further, adopting IDDS approach will require adopting new work culture and news ways of working. The change in work practices often requires shifting organizational cultures from a focus on separate services to a focus on operating within a fully integrated service system. Cultural change refers to the establishment of norms, attitudes, and interpersonal relationships that will foster cohesive use of that system by all the team members. Project phase: Team members need to have clear understanding of their roles, responsibilities and contributions to the integrated BIM model at different phases of the project. This includes clarity on the scope of the model and its usage across the different phases of the project. Regulations and standards: Building regulations and standards vary across states and countries. Hence, team members need to be alert about these conditions when working on projects or teams distributed across boundaries. Project requirements: How the team is organized, how the task is coordinated and what processes

8 CIB-W096 2011 Vienna Themes Competence (Capabilities of the team and tools) Team member (about the team and team members) Factors and description are adopted will vary according to the project requirements. Hence, team members need a shared understanding of the project requirements and the scope and objectives of the integrated design delivery approach specific to the project. FGI participants agreed that even though some of these requirements and project context will evolve midway through the project, considerable improvements can be obtained by discussing the project upfront with all the project holders. Discussions suggest that it may be useful to mutually develop and create measures that will help identification and agreement on emergent project requirements. Such measures and agreements will reduce the likely misunderstandings and disagreements that may arise out of unforseen project conditions, which often occur in most projects. BIM readiness and technical competence of project partners is a critical factor in determining the teamwork efficiency. Project managers need structured approaches and checklists to identify potential clashes that may arise due to the use of incompatible tools and technologies. Potential users need to be aware of the competencies and skills required to use the various applications and at the same time they need to be aware of the capabilities and limitations of the tools at the outset of the project. Issues of data format and import/ export capabilities of the softwares need to considered at the project planning stage itself. Due consideration must be given to the variable ability of the team members to learn new tools and processes, and their existing skills and specialities. Capabilities of the information systems and the collaboration platform may also determine the nature of collaboration and the opportunity for social learning and team building. FGI participants also raised concerns over the other capabilities of the information systems that include security; bandwidth; server capacity; visualization capabilities; integration capabilities; querying and archiving; usability and interface. FGI discussions revealed a concern over the tendency of some functional groups and disciplines to work in isolation. Lack of trust in accuracy and completeness of the information and models created by members of other disciplines was a concern. FGI discussions emphasised that roles and responsibilities need to be clearly defined, which often becomes a contentious issue, especially in changing team environments. Issues such as data authorship and access rights remain a concern. Some disciplinary groups expressed a fear of additional work, showing resistance to change. FGI participants discussed a range of strategies for dealing with the resistance to change including motivations and initiatives for the different user groups to adopt new ways of working, government and regulatory measures that will drive this change as a necessary condition, creation of communities of practice that can encourage and train the members of the various communities, and identification of the change leaders. The discussions suggested that willingness of the team members to learn and adapt to the project requirements reflects a measure of investment and the expected return on investment. Some of the factors that individuals and firms in multi-organizational collaboration consider as part of their assessment of the return on investment include: Financial investment in technology: Is it worth investing in a new technology unless the returns from the project cover it? Even if the returns in the current project are low will it provide long term advantages in future projects? Effort and time invested in creating a shared protocol for working with the team and other project partners: Am I likely to work with the same group in future or not? Is the project long enough or worthy enough to invest time and effort in creating a project specific protocols and culture? Investing in new skills and specialities: Adopting news ways of working or new technical skills requires commitment and time. Some project stakeholders who are recognized for their expertise and experience in their existing skills and capabilities, and have built a strong reputation for it, are reluctant to venture into developing new skills and specialities. The inherent uncertainties and lack of experience acts a deterrent to investing in the new skills and specialities, especially for people who have spent decades working and mastering a particular skill and expertise. Though the factors have been classified within one category often one factor is associated with multiple mental models such that the task, process, context, competence and team member mental models are closely interrelated and affect each other. For example, model validation is not only about

Managing Teams for Integrated Design Solutions 9 the task but also the process involved in conducting that task. Similarly, skills acquisition is not only about the competence but also about what the individuals think of the team, and their roles and responsibilities towards the team. Further research is needed to build on this mapping and develop a dependency model that provides the framework for a computational application. 6. CONCLUSION This paper discusses an ongoing research that aims to investigate teamwork challenges and opportunities in construction supply chain networks, especially with respect to the objectives of integrated design delivery solutions. The paper details the research plans and the steps towards achieving the research objective of creating the basis for a computational simulation tool as a decision support system for team selection and resource allocation for efficient management of teams engaged in integrated design delivery and solutions practice. This research adopts the construct of mental models as the basis for establishing the parameters of team work. Findings from the preliminary focus group interviews with representatives of various stakeholder groups are analysed and categorised into issues related to task, process, context, competence and team member mental models. The focus group discussions suggest that there are overlaps across the different mental models and the key issues concerning efficient teamwork and project management. Among other issues it is evident that team members have a sense of measuring their investment in the project and the returns on the investment. This investment involves multiple parameters such as time, effort, money, and reputation. Further research is planned to investigate these issues and develop the framework. 7. REFERENCES ACIF - Australian Construction Industry Forum, 2010, Construction Forecasting. URL: http://www.acif.com.au/construction-forecasting/, Accessed on May 15 th 2010. Ancona, D. G., and Caldwell, D., 2007, Improving the Performance of New Product Teams. Engineering Management Review, IEEE, 35(4), 45. Azambuja,M. and O Brien,W., 2009, Construction Supply Chain Modelling : Issues and Perspectives- chapter 2 ( in) Construction Supply Chain Management Handbook, Taylor and Frances USA. pp1.13-43. ISBN13-978-1-4200-4745-5. 2009. Badke-Schaub, P., Neumann, A., Lauche, K. and Mohammed S., 2007, Mental models in design teams: a valid approach to performance in design collaboration? CoDesign, 3: 5-20. Cannon-Bowers, J. A., and Salas E., 1997, Teamwork competencies, The interaction of team member knowledge skills and attitudes, p. 151-174. In O. F. O'Neil (ed.), Workforce readiness, Competencies and assessment. Erlbaum, Hillsdale, NJ. Carley, K. M., and Newell, A., 1994, The Nature of the Social Agent, Journal of Mathematical Sociology 19:221-262. CIB, 2010, CIB White Paper on IDDS Integrated Design and Delivery Solutions, CIB Publication 328 ISBN: 978-90-6363-060-7. Cohen, S. G., and Bailey, D. E., 1997, What Makes Teams Work: Group Effectiveness Research from the Shop Floor to the Executive Suite, Journal of Management, 23(3), 239-290. Donaldson, L. 2001. The Contingency Theory of Organizations. Sage Publications, Thousand Oaks, CA. Druskat, V. U., and Pescosolido, A. T., 2002, The Content of Effective Teamwork Mental Models in Self-Managing Teams: Ownership, Learning and Heedful Interrelating. Human Relations, 55(3), 283-314. Ericsson, K. A., 2001, Protocol analysis in psychology. In N. Smelser & P. Baltes (Eds.), International Encyclopedia of the Social and Behavioral Sciences, Oxford, UK: Elsevier, p. 12256 12262. Glendinning, C., 2003, Breaking down barriers: Integrating health and care services for older people in England, Health Policy, 65, 139-151. King, G., and Meyer, K., 2005, Service integration and co-ordination: A framework of approaches for the delivery of coordinated care to children with disabilities and their families, Child: Care, Health, and Development, 32, 477-492. Klimoski, R., and Mohammed, S., 1994, Team Mental Model: Construct or Metaphor? Journal of Management, 20(2), 403-437.

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