1 NOTICE: This is the authors’ version of a work that was accepted for publication in the ASCE Journal of Management in Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published and can be accessed via the following link: http://ascelibrary.org/meo/resource/1/jmenea/v27/i3/p170_s1 PLEASE REFER TO THE RESEARCH IN THIS MANUSCRIPT, IF CITED, AS FOLLOWS: Chinowsky, P., Taylor, J., and Di Marco, M. (2011). “Project Network Interdependency Alignment: New Approach to Assessing Project Effectiveness,” ASCE Journal of Management in Engineering, 27(3): 170-178.
PROJECT NETWORK INTERDEPENDENCY ALIGNMENT: A NEW APPROACH TO ASSESSING PROJECT EFFECTIVENESS Paul Chinowsky 1, John E. Taylor 2, and Melissa Di Marco 3 ABSTRACT The engineering and construction industry has evolved to a task-centric approach to evaluating the effectiveness of projects. However, a narrow task-based view of project network logic neglects the coordination of communication and knowledge exchanges across the project organizational network. This paper departs from traditional approaches to introduce a new approach to assessing project effectiveness that focuses on alignment of actual knowledge exchanges with knowledge exchange requirements across task-organization network dyads. We introduce a new modeling approach which we term as Project Network Interdependency Alignment.
Project Network Interdependency Alignment identifies potentially excessive or
insufficient communication and knowledge exchanges which can make projects ineffective. We introduce the modeling approach and retrospectively validate it using a building renovation construction project.
The case study demonstrates that the approach can provide project
managers with the capacity to analyze task and organizational network interdependence on projects and the critical capability to identify misalignments that impede project effectiveness. Keywords: Interdependence; Organizational Issues; Project Networks; Social Network Analysis; Task Networks
1
Associate Professor, University of Colorado at Boulder, Department of Civil, Environmental and Architectural Engineering, Boulder, CO 80309-0428;
[email protected]. 2 Assistant Professor, Columbia University, Civil Engineering and Engineering Mechanics Department, New York, NY 10027 USA;
[email protected]. 3 Graduate Student, Dept of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027 USA;
[email protected].
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INTRODUCTION The latter half of the 20th Century was witness to the expansive growth of information-centered technologies. The development of the Internet, distributed databases, and n-dimensional graphics are all manifestations of the information-centered society. The engineering-construction industry energized its collective resources around this development to transform project information processing to include web-based project extranets, 4-Dimensional CAD visualization and modeling, and enhanced control processing. These information-centered project management techniques emerged as advances to traditional critical path method (CPM) based control strategies. Although these techniques were advances in information processing capacity, they emphasized a narrow, task-based view of improving information flow efficiency.
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perspective may have diverted project managers from a central element of project management, the coordination of knowledge in the project organizational network to enhance project effectiveness. In this context, project effectiveness is the ability of project stakeholders to develop solutions which meet or exceed expectations through innovation, learning, greater understanding of client requirements, and an overall understanding of the long-term implications of the project. At the core of this effectiveness is the ability of project stakeholders to spend the appropriate amount of time coordinating tasks and organizational exchange requirements. In this paper we define project effectiveness as achieving the right amount of communications and knowledge exchange required to successfully achieve a set of tasks on a project. Projects become ineffective if there is too much or too little communication and knowledge exchange occurring. This paper introduces a new approach to assessing project effectiveness by focusing on the alignment of actual stakeholder knowledge exchange with knowledge exchange requirements defined by task relationships. We describe this new approach as Project Network Interdependency Alignment.
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Project Network Interdependency Alignment (PNIA) has its roots in social network and task network approaches to network theory. The underlying emphasis of these approaches is to build upon the capacity of the stakeholders within an organizational network to adapt to the demands of a changing environment and adopt an interaction modality that is appropriate and fits the environmental context. The fundamental assumption is that individuals or firms within the network strive to achieve a collective outcome that benefits the whole, not the sub-optimization of a few stakeholders. This assumption may hold true for projects involving one firm or a small number of firms. However, in complex projects today there are often dozens of firms involved which may have competing interests. Moreover, projects today are temporary organizations with shifting participation from one project to the next. This relational instability makes achieving collective alignment at the interdependent boundary between tasks and organizations extremely challenging. Project network interdependency includes both task interdependency within the project task network and organization interdependency within the project participant network. At the junction of these two interdependencies is the communication and knowledge exchange requirements for effective project execution.
As the degree of interdependency increases
between tasks or organizations, greater levels of communication and knowledge exchange are required from the participants to ensure that both the intentions of the participants are met and the specific requirements of the task are achieved. This paper introduces Project Network Interdependency Alignment as a means of identifying omitted and potentially excessive or ineffective exchanges on projects. This network interdependency focus is a significant departure from traditional project management in that we introduce the impact of organizational dependence on achieving project effectiveness. The paper begins with a description of the
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building blocks upon which this approach has been developed. Given this background, we then describe the details of the PNIA approach and how it departs from a traditional task-centric approach. We then illustrate and retrospectively validate the PNIA approach on a building renovation construction project. The case study demonstrates that PNIA can provide project managers with the capacity to analyze task and organizational network interdependence on projects and, more importantly, the critical capability to identify misalignments that create project vulnerability and impede project effectiveness.
BACKGROUND Researchers in construction project management have achieved a relative consensus on the importance of human factors or ‘people’ for successful project outcomes (Lechler, 2000). The ‘discovery’ that human and social capital is a key project success factor is of particular interest to the current research focus based on its emphasis of network teams. Specifically, research into the role that communication plays in project success is a precursor to the current research effort into interdependency (Thomas, et al 1998).
Additionally, research into the role that creating an
environment in which project participants can succeed as a foundation for the overall project success provides a basis for analyzing the role that project networks play in project success (Newell et al, 2002). The project network interdependency alignment approach builds upon this focus on human capital by integrating two distinct research areas; social network analysis and task network analysis.
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Social Network Analysis Social Network Analysis (SNA) has been an instrumental tool for researchers focusing on the interactions of groups since the concept was introduced by Moreno in 1934 (Moreno 1960). At the center of the concept is the basis that individuals or organizations exchange information during the performance of any activity (Scott 1991; Haythornthwaite 1996). Given the premise that any activity requires a transfer of information, the extension of this foundation is that these exchanges can be mapped based on a graph format where actors and information exchange become nodes and arcs within a graph (Wasserman and Faust 1994). The translation of these interactions to a mathematical basis is the strength and validity of the network approach to analyzing social interactions, communication and knowledge exchanges, and a range of interactional phenomena. The ability to apply mathematical analysis to network information exchange provides the researcher with established measurements for analyzing the effectiveness and weaknesses of the group being studied (Alba 1982). The social network concepts of cohesion, density, distances and relationships are currently being applied by researchers in many diverse and distinct domains. Classic SNA research focuses on sociological networks involving individuals in the workplace and their exchange of information to complete tasks (Krebs 2004). Additional studies are focusing on international relationships in areas such as research coordination and international investment (Krebs 2004). Construction engineering and management researchers have utilized network analysis to examine issues such as the emergence of cultural boundary spanners in global engineering services networks (Di Marco et al. 2009) and the structure and relationships within project organizations (Chinowsky et al. 2008).
Within these studies, the ability to map
participant relationships within a structure that can be visualized using network analysis software
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is a significant benefit to network researchers. Specifically, work in network visualization techniques is providing researchers with the ability to isolate relationships, visualize network principles such as dominance, centrality, and egocentricity, and graphically present results that were previously limited to mathematical matrices (Hanneman and Riddle 2005). In the project management domain, the use of social network analysis has emphasized project communications and the role communications can play in assisting coordination functions (Pryke and Smyth 2006). However, communication is only one factor that can be modeled with SNA tools and methods.
As outlined in the Social Network Model for
Construction, human dynamics factors including reliance, trust, and values augment traditional communication analysis when elevating the project analysis to include knowledge sharing and high performance outcomes (Chinowsky, Diekmann, and Galotti 2008). Knowledge sharing has significant importance to research into the multi-faceted coordination requirements of complex engineering design and construction work. communication may be insufficient.
In complex engineering task coordination,
We need to understand the extent to which actual
knowledge is being exchanged at each task interdependent organizational dyad on the project. The understanding of communication and knowledge exchange elements within a given project network provide the capacity to identify coordination misalignments between organizations on the project and their interdependent task assignment.
Task Network Analysis Research on the analysis of tasks in a construction project as a network of activities began with the development of arrow diagramming methods (Kelley 1961) and precedence diagramming methods (Fondahl 1961) in the 1950s. These methods were developed as a response to the
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increasing complexity of the projects that were being scheduled and introduced logic relating to the dependency of a network of activities on each other (Archibald and Villoria 1967). The calculations involved with each task network analysis method resulted in the identification of the critical path. Much of the focus of research over the ensuing two decades focused on efforts to develop heuristic methods to improve the accuracy and algorithms of critical path prediction (Elmaghraby 1964), to include resources in task networks to understand and optimize time-cost trade-offs (Clark 1961, Davis and Heidorn 1971), and to develop project control approaches (Pilcher 1973). Although research in these areas continues to draw attention from scholars, the last two decades have been witness to a significant amount of research on project task network scheduling using computerized systems. Research in these areas has been augmented with information processing capacity to enable the application of fuzzy logic (Ayyub and Haldar 1984, Lorterapong and Moselhi 1996), integration with geographic information systems (Poku and Arditi 2006) and three-dimensional computer aided design models (McKinney and Fischer 1998), and Monte Carlo simulation approaches (Lee 2005) in task network analysis research. This research is critical to developing more accurate approaches to modeling and making inferences from task networks. Yet, researchers have commented that an overly task-centric approach to the management of projects neglects the important interface management function of project management (Morris 1994). Managing interfaces becomes increasingly important as the number of tasks in the project increase and researchers have shown that schedules managed by construction project managers have larger numbers of activities than projects in other fields (Liberatore et al. 2001).
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PROJECT NETWORK INTERDEPENDENCY ALIGNMENT The Project Network Interdependency Alignment approach entails three steps. In this section we first describe how we integrate task and organizational interdependence. We then describe the first step of the modeling process which centers on the collection of communication and knowledge exchange frequency data from project stakeholders. This technique is based on the Social Network Model for construction (Chinowsky, Diekmann, and Galotti 2008). The second modeling step focuses on evaluating the degree of interdependency for each pair of tasks in the project schedule, referred to as task dyads. Each task dyad in the network is evaluated based on the level of knowledge exchange required between the project stakeholders responsible for the task dyad. This integrated task and organizational network diagram is referred to as the Project Network Interdependency Alignment model. The final step involves evaluating the alignment between the Social Network Model of actual communication and knowledge exchanges and the Project Network Interdependency Alignment model of required communication and knowledge exchanges on the project. We present the Project Network Interdependency Alignment approach in parallel with a description of the case project we studied to validate the feasibility and accuracy of the approach.
Integrating Task and Organization Coordination As described in the previous sections, the current work defines interdependency coordination requirements as dependent on two factors, task coordination scope and organizational coordination scope. Task coordination scope refers to the level of interdependency that exists between each pair of tasks, or task dyad, in a project schedule. Organizational coordination scope refers to the relationship between stakeholders executing each task dyad. The levels of
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this interdependency derive from the work of Thompson (1967). The first of these levels, pooled interdependency, represents tasks that can be completed at any time between the start and finish node of a project. These tasks are relatively rare in complex design and construction projects as most tasks depend on other tasks. The next level, sequential interdependence, indicates tasks that are dependent on other tasks being completed before they can begin work. This allows coordination processes to occur such that a delay in a precedent task can be communicated before the next task begins. The third, and most complex level, is reciprocal interdependency where tasks are completed simultaneously and are dependent on each other for both intermediate and final results. Many construction projects today are “fast-tracked” which often involves forcing some activities to be executed concurrently. Coordination processes are significantly more difficult in this level as issues that arise during construction related one task may adversely impact activities being concurrently executed. Coordination requirements rise in complexity as the states evolve from pooled to reciprocal interdependency. Coordination moves from having limited inter-task requirements in a pooled interdependency state to sequential coordination, and finally to requiring concurrent reciprocal coordination. At the core of this coordination requirement is the need for individuals to extend beyond communications and information exchange to a focus on knowledge exchange. Firms must collaborate to examine solution alternatives that effectively meet the demands of the coordination requirements and ensure mutual benefits for each party. This level of exchange requires the parties to exchange both explicit and tacit knowledge to explore solutions to intertask coordination issues as they arise. The difficulty with these exchanges is that in a relationally unstable industry there is often insufficient past working interactions to support effective collaborative task execution. Rather, teams focus on building a communication network that is
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efficient to meet project needs, but may be lacking in the items that are required to label the network as effective. The PNIA approach is designed to determine whether the appropriate task-organization alignment is in place to enable efficient exchanges and, hence, effective project execution. Utilizing the underlying concepts described previously, PNIA determines if the appropriate level of communication and knowledge exchange is occurring between the responsible participants in tasks that are vulnerable to coordination misalignment. Utilizing an alignment measurement, PNIA has the capacity to identify the potential areas where task-organization misalignment may occur and where projects become vulnerable to collective coordination misalignment.
The Renovation Case Study Coordinating the often divergent requirements of individual constituencies together with the project plan is a core requirement of any project. However, moving beyond coordination to project effectiveness is the challenge that the PNIA concept is addressing. In this context, renovation projects often bring an additional set of coordination issues, and thus challenges to effectiveness, as new design requirements are integrated with existing structures. Concurrent with these coordination issues is the need to balance schedule pressures with the need to validate existing conditions within the structure. Because of the complex coordination issues involved with a large renovation project, we selected such a case to examine and retrospectively validate the PNIA concept. The case study was coordinated with a national multi-sector builder (The Builder) who was given the responsibility to renovate four dormitories on a university campus in a design-build delivery option. The total project budget was $58.3 million and each of the four dormitory renovations represented approximately one-quarter of the total budget. Each of the
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four projects was scheduled to be completed in 14 months. The specific context for the case study was the second of four dormitory renovation projects (The Project). The scope of The Project consisted of a complete renovation of the dormitory mechanical systems and electrical systems as well as installing high speed internet lines. Additionally, the project included a focus on sustainability where new windows, ventilation, and mechanical controls were included in the project. A similar scope was established for each of the four projects. The Builder created a core team of primary subcontractors and project management staff that would complete and oversee all four projects. The first of the renovations served as a trial project where the team focused on establishing efficient processes and team-building for the entire set of four projects. Given this context, we obtained a copy of the project schedule for The Project as well as a list from the Builder of the primary personnel for each of the project stakeholders. The list of participants for the project included 28 individuals and covered the design, construction, and owner stakeholder teams.
The combination of the personnel list and the project schedule
provided the basis for the PNIA analysis detailed in the following sections.
Collecting Data on Organization Network Exchanges The first step in the PNIA approach is to collect organizational network data from project stakeholders.
For the case study project, this was enabled through the deployment of an
electronic, Web-based format of the Social Network Model survey to the project participants. The survey contained questions that map to the levels in the Social Network Model. The intent of the survey was to obtain data that corresponds to the perspectives of each individual in regards to communication and knowledge exchange occurring between them and every other stakeholder
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in the network. The 28 project personnel provided by the organization were each notified of the survey and were given the opportunity to confidentially complete the survey. Twenty-six of the twenty-eight project personnel completed the survey in its entirety; the remaining two completed a portion of the survey which was sufficient to include them in the PNIA case study and retrospective validation. The study focused on two specific types of networks; communication exchange networks (weekly, monthly and quarterly) (communication network is graphed in Figure 1) and knowledge exchange networks (weekly, monthly and quarterly) (knowledge network is graphed in Figure 2). Revisiting the network discussion earlier in this paper, the communication exchange network reflects the current communication that exists between project stakeholders and the frequency in which those communications occur. Similarly, the knowledge exchange network reflects the current knowledge exchange that exists between project stakeholders and the frequency in which that knowledge exchange occurs. These exchanges are reflected in the graphs as lines between the individual nodes. The size of the node indicates the relative number of individuals who indicated that they communicate or exchange knowledge with that individual. Table 1 provides a listing of each individual in the network and their role in the project. These networks thus provide the insight into the continuity of exchanges occurring on the project. To construct these networks, the 28 project participants were surveyed to determine which of the other participants they interacted with on a weekly basis for communication and knowledge exchange purposes. As detailed in the Social Network Model (Chinowsky, Diekmann, and Galotti 2008), the weekly threshold is the timeframe in which communications can be considered continuous, which is the requirement for establishing free and open knowledge exchange. This
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analysis provided an overall network and density measurement for each of the variables as well as an individual set of communication dyads for use in the task interdependency analysis.
Figure 1: Communication Exchange Network for Case Project
Figure 2: Knowledge Exchange Network for Case Project
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Assessing Organizational Network Exchange Requirements at Task Network Dyads The goal of the second portion of the analysis was to develop a Project Network Interdependency Alignment model. This involved determining the extent to which each organizational network dyad, defined as two project team members who need to communicate and exchange knowledge to execute the scheduled tasks they are responsible for, should be communicating and exchanging knowledge based on their assigned tasks. We assumed that those organizational network dyads responsible for tasks that are highly interdependent require the most significant amount of communication and knowledge exchange. To determine the specific levels of interdependence, a logical scheme was developed using network graphs. First, the tasks in the case project were combined into all possible task dyad pairs, defined as two tasks that have a defined relationship in the project schedule. A total of 428 task dyads were identified. These were then each evaluated utilizing three task network interdependency criteria: 1) their actual task interdependence derived from the schedule precedence logic; 2) their time-space interdependence; and 3) their criticality determined from whether the tasks were on the schedule critical path. Figure 3 shows the tasks in a network diagram including the links indicating where task interdependency relationships existed. The criticality of the tasks is illustrated by the size of nodes indicating their placement on the critical path; the larger nodes are those tasks that if not completed would impact the completion of subsequent tasks. For example, the plumbing rough-in and the fan coil installation tasks are indicated with larger nodes as they both are on the critical path. The two nodes are also connected with a link as they are indicated as having logical precedence dependency in the project schedule.
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For the first task network interdependency criterion we assumed a value of 0 for pooled interdependence, 1 for sequential interdependence, and 2 for reciprocal interdependence for each task dyad. This underestimates the additional coordination difficulty imposed by reciprocal interdependence, however, for the purposes of assessing whether we could establish a project network interdependency alignment model it is sufficient. For the second criterion, we attributed a value of 1 if the activities would be completed in the same time and space since this requires knowledge exchange even if the tasks themselves are not interdependent in terms of precedence logic. If the activities did not occur at the same time and in the same space we attributed a value of 0 to the task dyad on this criterion. The last criterion we considered was the criticality of the tasks. A value of 1 was attributed if both of the activities were on the critical path for the project and a value of 0 was attributed otherwise. We then added up the values across the three criteria to arrive at the knowledge exchange requirement for each task dyad. Returning to the plumbing rough-in to fan-coil example, the tasks have reciprocal dependency, task-space dependency, and are both on the critical path, thus giving this relationship the maximum score of 4 points. We then developed a task dyad matrix which was used to create the task dyad communication and knowledge exchange requirement network diagram contained in Figure 4.
The communication and knowledge exchange
requirement level is indicated through the tie strength (line thickness) of the connecting links between the task dyads. The thicker the lines, the more interdependent the tasks are. Once again, the example is reflected with a strong tie between the plumbing rough-in and fan coil tasks in the network.
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Figure 3: Task Dyad Network for Case Project with Critical Path
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Figure 4: Task Dyad Communication and Knowledge Exchange Requirements on Case Project
Assessing Project Network Interdependency Alignment In order to complete the project network interdependency analysis, we linked the organizational network dyads with the task dyads to determine the level of knowledge exchange required. In the plumbing rough-in to fan coil example, the responsible parties are p2 and p22 respectively. For every task dyad with a knowledge exchange requirement value of at least 1, we determined the organizational stakeholders, or dyad,responsible for the two tasks. We then extracted the knowledge exchange requirement values for that task dyad and associated it with the organizational network dyad responsible for completing the interdependent tasks. However, in many cases the same organizational network dyad was responsible for multiple task dyads. In this case, we summed the knowledge requirement values in order to assess an overall level of knowledge exchange required by the individuals in the organizational network dyad.
For
example, p2 and p22 are responsible for multiple plumbing and fan coil tasks as well as other
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task relationships such as plumbing and fire sprinkler installation. This multiple responsibility scenario results in a cumulative effect on the knowledge exchange requirements. We then graphed a Project Network Interdependency Alignment model (see Figure 5 and Table 1) that normalizes and compares actual and required communication and knowledge exchange patterns for the project network. To determine whether coordination was appropriate, too little, or too much, the model incorporates a quantitative process as follows: 1. The amount of actual coordination between each person dyad is normalized on a scale of 0 to 1 based on the amount of quarterly, monthly and weekly communication and knowledge exchange that is identified in the SNA networks. 2. The amount of required coordination is normalized on a scale of 0 to 1 based on the interdependency points described above. 3. The difference between the required and actual coordination amounts is then calculated as the variance for each task-organization dyad. 4. The mean of the variances is then calculated together with the standard deviation to determine the acceptable variation from the mean. 5. Acceptable coordination is then determined based on the rule that variance within one standard deviation from the mean of the variances is considered appropriate, greater than one standard deviation is excessive, and less than one standard deviation is too little.
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Table 1: The roles of each stakeholder included in the interaction network diagrams Designation p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12 p13 p14 p15 p16 p17 p18 p19 p20 p21 p22 p23 p24 p25 p26 p27 p28
Project Role Job Sponsor Superintendent Field Engineer Project Manager Project Engineer Sr. Estimator Principal Job Captain Project Manager Designer Life Safety Code Official Electrical Owner's Rep Planner Division Manager Division Director Deputy Director Assistant Director Mechanical VP Sales HVAC Engineer Project Manager Engineer Project Manager Consultant Consultant Engineer
Organization The Builder The Builder The Builder The Builder The Builder The Builder The Architect The Architect The Architect The Architect The Owner The Owner The Owner The Owner The Owner The Owner The Owner The Owner The Owner The Owner Mechanical Mechanical Mechanical Electrical Electrical LEED LEED Fire
Figures 5a, 5b, and 5c illustrate the results of this analysis for the case study. The thickness of the link connecting each stakeholder in the network indicates the relative amount of actual versus required communication and knowledge exchange.
Figure 5a illustrates coordination
relationships that are appropriate for the project. These are the coordination links that are within one standard deviation from the mean of the variances and are thus considered appropriate levels of actual coordination in relation to the required coordination. Figure 5b illustrates the links
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where there is relatively too much communication and knowledge exchange and, hence, ineffective communication and knowledge exchange may be occurring. These links are those where the actual minus the required was greater than one standard deviation from the mean of the variances. Finally and most importantly, Figure 5c illustrates the linkages where there was relatively too little communication and knowledge exchange. In this case the actual minus the required was more than one standard deviation less than the mean of the variances. In other words the actual communication and knowledge exchange was much less than was required by the tasks for which the stakeholder pairs were responsible.
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5a: Links indicating which relationships have satisfactory exchange levels.
5b: Links indicating which relationships have exchange levels that are too high compared to requirements.
5c: Links indicating which relationships have exchange levels that are too low compared to requirements.
Figure 5: Project Network Interdependency Alignment Model
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CASE STUDY RETROSPECTIVE VALIDATION In order to retrospectively validate the above findings of the PNIA model and explore the underlying influences behind the observed patterns of variance, we conducted interviews with the Project Manager for The Builder. These interviews provided the opportunity to have an external validation of the misalignment findings and obtain an insight as to why certain patterns have taken shape in the coalition of the project. The initial question put to the Project Manager concerned the overall performance of the Project. The Project Manager believed that the overall project was going well, but two issues were of significant concern going forward for the next two projects as identified in the following quotes: •
“We have not had a close relationship with The Mechanical Engineer resulting in a number of extra meetings to clarify work that was already decided upon,” and
•
“The Owner representatives on the team are a significant bottleneck to progress. A significant amount of time is spent updating the owner, but significant delays occur waiting for responses to important issues.”
In terms of the former quote, this conflict is revealed in the PNIA network through the lack of sufficient knowledge exchange between p5 (The Project Engineer) and p22 (The HVAC Engineer). This is illustrated as a thick line connecting p5 and p22 in Figure 5c. The thickness of the line in this network diagram indicates a strong need for more communication and knowledge exchange between these individuals. This coincides with the quote obtained from the Project Manager. In terms of the latter quote, the PNIA networks reveal that p20 (The Owner representative for mechanical issues) and p14 (The Owner representative for the users) do not
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have the required levels of coordination with the Project Engineer (p5), the HVAC Engineer (p22), or the Architectural Designer (p10). As with the previous example, these are indicated by three lines connecting p14 and p20 to other nodes in Figure 5c. This insufficient communication and knowledge exchange has a direct result in the project experiencing both information delays and requirements for additional meetings by the Builder with project stakeholders to provide the information that is not emerging from the owner representatives. The Project Manager suggested that one reason for this may be the reluctance of the owner to get involved with project issues due to contractual concerns. Additional issues include the control of project execution and internal conflicts within the overall owner organization. These instances highlight the misalignment that can occur in task and organizational network alignment. In each case, required interactions are missing due to misalignment between network members in terms of; 1) actual and required communications, and 2) actual and required knowledge exchanges. This misalignment is affecting individual tasks such as plumbing and code approval since the organizational network dyads are not providing the knowledge required to enable effective project execution. The PNIA model was able to accurately identify these key communication and knowledge exchange misalignment issues that were occurring. Although this is a single case study, the strong degree of agreement with the PNIA model results was sufficient to retrospectively validate that a PNIA modeling approach can identify key project network interdependency misalignments that affect project execution.
LIMITATIONS Although the findings from the PNIA model were retrospectively validated with the renovation case study, the approach does have several limitations that should be addressed in future
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research. First, the PNIA modeling approach outlined in this paper includes communication and knowledge exchanges between dyads in the network. The model identifies misalignments when too little communication is occurring. However, in situations where organizational dyads have significant amounts of trust or have worked together on similar tasks in the past, less communication and knowledge exchanges may be needed to work together effectively. Future research should consider the amount of trust and previous working experience at organizational network dyads. Although not described in detail in the case validation section, there was one organizational network pair the PNIA model indicated was coordinating less than the model predicted was necessary and yet the tasks were completed effectively on the case project. The project manager indicated that there was a long track record of the pair working together on projects. Hence, examining the strength of trust and learning across organizations may be required for to develop a comprehensive PNIA modeling approach. Another limitation of the PNIA model is that it is based on normalized actual and required coordination and, as such, can only indicate whether there is relatively more or less variance between actual and required. Future research should endeavor to develop scales for actual and required communications such that the value derived from the variances is directly interpretable.
A third limitation that future research should address is the impact of an
organizational boundary being crossed at an organizational dyad. The current PNIA model does not weight the amount of communication and knowledge exchange requirement to be greater when the pair of stakeholders is from two separate organizations. Considering the additional coordination required to work across organizational boundaries may represent an important calibration for the PNIA model and should be considered in future research.
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CONCLUSION The PNIA approach to managing interdependency is an evolutionary step forward in project management. The approach reintroduces the critical role that organizational networks play in successful project execution.
The PNIA approach provides a methodology to apply a
quantitative analysis of a project schedule and integrate the coordination connections that exist within the stakeholder network. This integration of communication and knowledge exchanges with project task interdependencies addresses the central requirement that effective project execution requires striking the right balance in communications and knowledge exchanges for each organization and task pairing in the project network.
This paper presents the PNIA
approach applied to a case study for a building renovation project. The paper illustrated how the PNIA approach can be used to analyze a project schedule and identify potential disconnects between project stakeholders in terms of coordination. The case study illustrated how the lack of appropriate coordination can result in potential project delays and miscommunications. As the case study identified the same set of ineffective task-organization dyads as the PNIA approach, we were able to use the case study to retrospectively validate the approach. The PNIA approach has important strategic implications to the profession.
Project
managers currently learn about ineffective communications and knowledge exchanges on projects after insufficient exchanges lead to errors and omissions or too much information and knowledge exchange leads to excessive costs. With the PNIA approach a project manager can monitor the impact of ongoing communications and knowledge exchanges during a project to identify ineffective exchanges. When ineffective exchanges are identified, the project manager can proactively address them through interventions such as additional coordination meetings between specific project team members.
To achieve these benefits additional research is
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required to refine, scale and further validate the PNIA modeling approach. However, the initial evidence suggests that the project network interdependency alignment modeling approach is a valuable line of inquiry to understand and improve project effectiveness.
ACKNOWLEDGMENTS This material is based in part upon work supported by the National Science Foundation under Grant No. 0729253. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors also wish to thank the unnamed company and company representatives who gave up their valuable time to participate in this research investigation.
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