Variability in project scheduling and the impact of team type Maryam Mirzaei, Victoria J. Mabin School of Management Victoria University of Wellington
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Abstract One important challenge of project scheduling models is the management of the harmful impacts of variability. The vast majority of research on project schedule variability uses network analysis and focuses on enhancing the scheduling models by adding mathematical rigour into the planning process. However, the problem of variability in execution is not yet well addressed. Since projects are carried out largely by human resources, a project’s execution depends on the modus operandi and interactions between its human resources. This paper based on a multi-case study research re-examines the assumptions of network analysis on human resource arrangement and their interactions. Ten cases, from various industries including construction, software, service, policy making, and filmmaking, provided insights into the diversity of project execution processes. Empirical data revealed that projects exhibit two distinct scenarios with challenges related to variability depending on their team type. Projects that used non-dedicated teams were more vulnerable to variability while projects executed by a dedicated team absorbed variability. Key words: variability, team, network scheduling, execution, human resources
Background “Projects are undertakings to realize an idea” (Morris, 2013, p. 12) or more precisely temporary undertakings that create a final product, service or result. The product or the result could be “a building, a software system, a new service or business function, a document such as a research report, or a new process such as one that could benefit society” (Project Management Institute, 2008, p. 6). ‘Project’ in its broad definition has always been a big part of what people do. ‘Project management’ as a discipline however, is thought to have arisen no earlier than 1952, when the US Air Force invented the role, project manager, for the first time (Morris, 2013, p. 27). Since then project management has evolved into a whole new discipline with many theories, schools of thoughts, methods and accreditations, all dedicated to describing or prescribing what happens or should happen to make an idea a reality. Some of the most exciting ideas of the twentieth century have been the incubator for project management. Founders of this new discipline invented the so-called traditional project management techniques to facilitate the realisation of mankind’s dreams in the last century. Many existing project management techniques and concepts arose from military research and product development projects (Morris, 2013). A ‘Project Office’ first appeared in 1956 for the Polaris project that successfully developed the Polaris Submarine weapon system and Fleet Ballistic Missile capability in the USA. One of the first network scheduling techniques, PERT (Program Evaluation and Review Technique) was also developed in 1957–1958 for the same
project. Such an ambitious plan encountered high complexity, uncertainty and ambiguity, and PERT’s event-oriented schedule was designed to accommodate uncertainty and manage stakeholder expectations (Morris, 2013, p. 18). At the same time, in 1957–1959, the Critical Path Method (CPM) was developed. CPM is also a network scheduling method that was invented for construction projects (Morris, 2013; Stretton, 2007). CPM is activity-oriented and corresponds to the linear and measureable world of construction. Both PERT and CPM were iconic techniques of project management for years and are still used today. Another scheduling method based on network analysis is Critical Chain, regarded as the application of TOC to project management (Goldratt, 1997; Leach, 1999; Newbold, 1998). Critical Chain attempts to direct the focus of management to the core constraint for a project, defined as the longest chain of activities. Critical Chain was invented as a response to persistent problems that caused project failure. Pittman (1994) listed several reasons for project failure based on an extensive literature review at that time. These reasons related to an inability to manage variability at convergence points, the effect of uncertainty and consequent changes to the schedule, and lack of a decision support system during execution. Scholars continue to report similar problems such as vulnerability to uncertainties (Bożejko et al., 2011; Chua & Shen, 2005; Kishira, 2006; Piotr & Biruk, 2011; Shu-Shun & Shih, 2009; Xiaokang & Mei, 2010), instability in schedules (Bożejko et al., 2011; Xiaokang & Mei, 2010), and incompetency of traditional approaches for dealing with interdependencies and project complexity (Chua & Shen, 2005; González et al., 2006; Henrich et al., 2005; Ning & Yeo, 2000; Shu-Shun & Shih, 2009; Xiaokang & Mei, 2010). In response to some of the problems discussed above, several scholars argued that practical problems were beyond scheduling solutions (Morris, 2013, p. 49; Sculli & Wong, 1985, p. 239) and even perhaps beyond systems thinking (Johnson, 2001; Sayles & Chandler, 1971). However, Pittman (1994) conducted extensive simulation analyses that clearly demonstrated the effect of assumptions made during planning CPM and PERT on the execution process. Pittman (1994) concluded that many project problems listed here are the result of wrong assumptions in existing scheduling methods. A specific example is static planning that overlooks the dynamic nature of projects. This was echoed by Leach (2005). He demonstrated that such problems were resolvable by implementing a more realistic schedule and a systems approach that connects plan and schedule with real-world projects and their practical problems. These are addressed by Critical Chain. Numerous simulation studies have demonstrated CCPM’s advantages over CPM (Budd & Cooper, 2004, 2005; Huang & Yang, 2009; Huang, Chen & Tsai, 2012; Pittman, 1994; Yang, 2007). While Critical Chain questions several CPM and PERT assumptions and corrects them, it too has been criticised for some of its assumptions and lack of applicability to a wide range of projects (Mckay & Morton, 1998; Morris, 2013; Raz et al., 2003). In practice, projects exhibit different characteristics (Dvir, Lipovetsky, Shenhar, & Tishler, 1998; Shenhar, 2001), but Critical Chain proposes a universal solution for all projects. It is similar to CPM and PERT in many ways, particularly, in that it portrays a project as a network of activities. The widespread use of network analysis (White & Fortune, 2002) in project management reflects the assumption that actions in projects are performed in a sequence of tasks governed by precedence dependencies. Network analysis also treats planning and execution as separate undertakings that are performed by management and human resources respectively, which according to Koskela and Howell (2002) argue is influenced by ‘job dispatching theory’. This theory consists of deciding and communicating the assignment to the job station which implies that decision making and acting upon a decision are distinct undertakings performed by
different actors. Since projects are carried out largely by human resources, a project’s execution depends on the modus operandi and interactions between its human resources. This paper therefore, re-examines the assumptions of network analysis on human resource arrangement and their interactions.
Methodology The paper presents the findings of a multi-case study research. Cases were all small projects that are executed in large and mature organizations. Small projects often follow the processes that are predominantly invented for large projects. Therefore, investigating small projects, while being more manageable to study, can be very insightful when exploring the role of assumptions behind project management methods as they are being adapted and tailored to different contexts. Purposeful sampling (Patton, 2005) was used and was focused on maximum variation and attempted to capture diversity of projects by including as many different types of projects as was possible. A summary of the cases, their type and sector, and sources of information for each case is provided in Table 1. Cases are from a diverse range of industries, and consist of a balanced mixture of for-profit (commercial) and not-for-profit (government and education sector) projects. Table 1: Cases and sources of information Code Name ‘Case 1’ ‘Case 2’ ‘Case 3’ ‘Case 4’ ‘Case 5’ ‘Case 6’ ‘Case 7’ ‘Case 8’
Type-Sector ServiceGovernment ImprovementEducation ConstructionCommercial ServiceGovernment Documentary film Not-for-profit SoftwareCommercial Policy advisoryGovernment SoftwareCommercial
‘Case 9’
SoftwareserviceEducation
‘Case 10’
ConstructionCommercial
Role of interviewees and codes Project manager (PM) Project manager (PM)
Sources of information 2 interviews, 3 organization level meetings, the firm’s website 2 interviews, 1 organization-level two upper managers prior to the official case study, the firm’s website, project documents 1 interviews, Online material suggested by the interviewee 1 interviews, The firm’s website
General manager (GM) Project manager (PM) Director and 2 interviews, Materials suggested and provided producer (DP) by the interviewee
Project manager (PM 5 interviews, The firm’s website (PM 2) Scrum master (SM) Project manager 3 interviews, 2 meetings, 2 workshops, the (PM) firm’s website, project manager’s website, online material suggested by the interviewee Project manager 5 interviews, Observation (of the software used) (PM), Lead The firm’s website consultant (LC) Scrum master (SM) 6 interviews, Project documents, the firm’s Associate director website, observation of a full day planning (AD) session and one daily stand-up and some Product Owners materials used in the project (PO1 and PO2) Project manager 4 interviews, The firm’s website, project (PM), Site manager documents (SM)
The broader research underpinning this paper first and foremost is inspired by Goldratt’s quest for questioning assumptions. “Progress in understanding requires that we challenge basic assumptions about how the world is and why it is that way” (Goldratt & Cox, 1984). In project management several project management scholars have called for rethinking existing concepts and assumptions (Ahlemann et al., 2012; Koskela & Howell, 2002; Packendorff, 1995; Turner & Muller, 2003; Winter, Smith, Morris, & Cicmil, 2006). However, after investigating how researchers in project management construct research questions, Hallgren (2012) identified a “lack of assumption-challenging research” which, he argued, “may hinder project research's development” particularly because in project management “many contributions tend to be based on long-lost principles” (Hallgren, 2012, p. 812). This paper follows this quest of rethinking concepts in project management and attempts to identify the impact of variability in different projects.
Findings and discussion Empirical data revealed that there are two important aspects in investigating the role of human resources in project process: the human resource acquisition, and team type. When project managers describe their teams, some project managers are very specific and address their team members by their names, while others address their team members by their roles. These differences became more obvious with further clarification on how they chose resources for their project. Project managers exhibited different levels of flexibility in the way they made decisions in this regard. Some projects required a specific person to complete the entire project, while other projects were more flexible. In addition to acquisition of human resources, case projects also exhibited a difference in how they assigned work to project team members. At one extreme, specific people were assigned to do specific jobs. At the other extreme, every task could be performed by a range of people, and members of the team could perform a range of tasks. A more interesting divide that impacted project vulnerability to variability was the team type with non-dedicated skill-based teams at one extreme and dedicated cross-functional teams at the other extreme. Examples below showcase such differences. Two construction cases used non-dedicated skill-based teams. Perhaps a characteristic of construction projects is that different tasks are conducted by different trades. The schedule played an important role in coordinating multiple trades. CPM was used in both construction cases. Synchronisation points and the sequence of activities were indeed very important for these projects. Each trade worked on multiple projects and took responsibility in the case project temporarily as per the schedule. The schedule determined and estimated their availability. The project exhibited a high reliance on the schedule for coordinating human resources. For example if carpenters arrived at the site and the preceding task was not yet completed, they could only wait or return at a later date. If the preceding work was completed earlier, time was wasted. Another project that depicted a similar workflow in one of its phases was a filmmaking project. This project had three phases: pre-production, production, and post-production. Phase 3 exhibited a sequential workflow. This phase included video editing, editing the soundtrack, colour correction and sound design. Each of these tasks required a different specialty and was conducted by different professional groups. However, at the end there was a merging point where all of this had to work together. Therefore, the post-production phase had a sequential process with a non-dedicated team similar to the above projects. Another example was a
software development project that used Critical Chain: in this project also team members entered and left the project. “[A person] is required for a portion of the project; they are not required across the whole length of it. So they come in, do their bit and then they hand over to whoever is the next person.” (PM, Case 8) The common team characteristics in all the above non-dedicated skill-based teams are:
Each task was performed by individuals or groups who specialised in performing that particular task
These individuals or groups were engaged in multiple projects and attended to the particular project temporarily at the specific time.
In contrast, in another software development case, the project had moved from a waterfall method to an Agile method. Initially, they described their workflow as a linear process as follows: Analysis
Development
Test
Release
In a waterfall approach, the whole process of analysis happened before development started. Similarly, testing was done after completion of development. This meant a few months of analysis and then a few months of development, followed by testing. Such a process, first and foremost, increased the chance of human resources waiting idle. “There is always waiting in IT,... we might have just people waiting …sometimes there is a week delay between this person finishing and the next person finishing” (PM, Case 6) They then moved to using Agile which recommends small batches. The above process changed to be more like this:
While this method improves flow of work dramatically, it does not eliminate queueing and waiting time. This is because if each person in the team only works according to their specialty as in the past, long queues would be commonly observed before the most constrained resource, for two reasons. First, because there is always uncertainty and variability. Second, because in a dedicated team, each of these activities requires an integer number of team members, but the work itself if calculated accurately will rarely be an integer number. This was explained by the project manager as follows: “If you have a much larger group of people, like 100, you might be able to find a ratio, but when you are working with smaller groups, even if the analysts are working 20% under-utilized, that doesn’t mean you can take one away. If you have 2 analysts, taking
away 1 person is taking away 50% of their capacity. With a small group of people you cannot really optimize to that extent.” (PM, Case 6) However, the dedicated team in this case exhibited an interesting phenomenon: variability and uncertainty was absorbed by team members interchanging roles and helping each othe as needed: “The daily stand ups allow very quick response to those sort of things, … [so when some work is delayed, another team member would say] Ok, I will help you in such and such.” (PM, Case 6) Another case used a dedicated team throughout the project. The case was a policy advisory project in a government department. The team members were engaged in this project throughout its duration. No member of the team disengaged from the project at any stage.This team also exhibited interchanging roles: “Someone else will pick the work from the Kanban board and move the work forward.” (PM, Case 7) The above findings indicate at one extreme there are projects with a non-dedicated skill-based team, in which contractor tradespersons or skilled workers were involved in the process of the project briefly to perform particular tasks. This group often mentioned synchronization problems. When team members left the project and attended to other projects, their involvement in the project was coordinated via a schedule. At the other extreme, the team consisted of permanent members who were constantly involved in the same project until its completion. It was observed that the schedule’s role as a coordination mechanism was replaced/augmented by other means such as daily stand-up, Kanban boards, and mutual adjustments, and team members were constantly informed about progress in the project. Such teams, while they still had members with specific skills, were more open to learning and taking roles outside their expertise when required. The findings above indicate that dedicated teams and non-dedicated teams are fundamentally different in the way they operate. It has been observed that in a dedicated team, members are willing to learn what they do not know and perform what they have never performed before as they help each other. As a result, they appear to be cross-functional. On the other hand, members of non-dedicated teams represent trades or personnel with particular skills or responsibilities, and only do those tasks that are their particular specialties. This emphasis on skills relies on the assumption that the tradesperson (for example, a particular contractor, with a crew of construction workers) or other skilled personnel have done similar work many times before. These skilled workers are expected to have statistical information on the task duration related to their area of expertise, as indicated in the following quote from Case 8: “I presume that you’re a professional at producing this…then I say you have developed things like this before… [and] if you have done 30 or 40 of these things [before], you know what the probable range is.” (LD, Case 8) A dedicated team can be equally specialised and skilled; however, since they are constantly working together, and do not leave the project when they have completed their own tasks, they also performed tasks outside their area of expertise when they finish their own tasks. . This reduces variability. However, in contrast, this research found that variability is reinforced by working with a non-dedicated team. Figure 1 provides an explanation (using TOC’s cause-
effect mapping protocols) of how variability is increased as a result of non-dedicated team members working on multiple projects. It is worth noting that it is not possible or recommended in all projects to use a dedicated team. However, dedicated teams can eliminate the problems of variability in the project schedule as explained in Figure 2. Increased variability in the project schedule Required human resources varies in action from what is planned
There is variability in other projects
Schedule is used to coordinate people and tasks There is variability in performing individual tasks
The team members work on other projects before and after their turn in the project
It is expensive to keep team members waiting idle for their turn in the project Project uses a non-dedicated team
Team members are not continuously needed on the project
Tasks are designed to be carried out sequentially
Figure 1. Non-dedicated team increases variability in project schedule (Mirzaei et al., 2015)
Reduced variability in the project schedule
If a task is not completed by the assigned member, their coworkers will help to complete it
Project is isolated from variability of other projects
There is variability in performing individual tasks Schedule may be used to coordinate people and tasks
It is expensive to keep team members waiting idle for their turn in the project Project uses a dedicated team
The team members take up tasks outside their assigned tasks when they are free Team members are not continuously needed on the project
Tasks are not designed to be carried out sequentially
Figure 2. A dedicated team reduces variability in project schedule (Mirzaei et al., 2015)
Conclusion “Modern project management had originated, as we’ve seen, with an interest in scheduling and cost control techniques but then developed as a means of coordination.” Morris (2013, p. 57) Similarly, this research started with exploring the assumptions behind the prevailing use of network scheduling methods such as CPM, PERT, and CCPM, but then sought to develop an understanding of the role of sequential and non-sequential dependencies and their coordination requirements. The findings suggest assuming sequential dependency is not true in all projects. Sequential dependency of human resources is only one of several dependencies identified in organisation research. Thompson (1967, pp. 54-65), for example, classifies processes into ‘independent’ to ‘sequential’ and to ‘reciprocal’. He suggests ‘sequential’ processes can be coordinated via planning and scheduling while ‘reciprocal’ processes require various mutual adjustment mechanisms. This study indicates that non-dedicated skill-based teams often adopt ‘sequential’ processes while dedicated teams exhibit ‘reciprocal’ processes. It seems that a dedicated team and non-dedicated team are fundamentally different in the way they operate. While non-dedicated teams were found to be vulnerable to inadequacies in their scheduling, dedicated teams took advantage of mutual adjustment in organising themselves and were less vulnerable to variability.
Limitations and future research This study is limited by its practical reach in obtaining data and thereby the choice of cases may not accurately reflect the full diversity of various industries using project management. Moreover, the research was exploratory in nature and was primarily focused on small projects within large organizations. Therefore, further research is required to investigate whether the results hold in other types of projects. This study indicates that project managers learn from practices in other industries, at least through existing normative guidebooks; however, they might use similar concepts for very different purposes. Therefore, it is recommended that more cross-industry analyses be conducted to gain a deeper understanding of such differences/similarities.
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