Measurements for project team performance

PMBOK (Project Management Institute, 2013) proposes monitoring and controlling as one of the project management process groups which classifies project performance into three elements: work performance data (e.g. task completion percentage, number of change request, number of defects); work performance information (e.g. status of corrective action and implementation, forecasts of project cost and schedule, status of project risks); and work performance reports (e.g. project progress reports, risk registers, issue reports). Traditional measurements for project performance have been within the dimension of schedule and cost.

One of the techniques for managing project costs and schedules is the earned value technique introduced by the US Department of Defence in the 1960s to manage defence contracts. However, Christensen (1998) argued that the technique was inadequate without the intervention of control mechanisms, and proposed the Earned Value Management Systems (EVMS) comprising five

categories — organisation, planning and budgeting, accounting, analysis and revisions — to measure project performance. The mechanism was further developed into what is now available as the EVM technique (Kim & Ballard, 2010; Lipke, Zwikael, Henderson, & Anbari, 2009; Anbari, 2003;). The Project Management Institute, USA, has also published its own practice standard of the EVM (Project Management Institute, 2011). While acceptance of the EVM technique has generally been low, research by E. Kim, Wells, and Duffey (2003) indicates that the take-up is increasing. Although the metrics used in EVM can be a predicator for project team performance, it alone is insufficient to assess team performance.

In the context of virtual project environment, risks can be significant and may impact project team performance. Reed and Knight (2010) identified seven risks that affect both co-located and virtual teams — (1) inexperience with processes within organisations, (2) lack of project team cohesion, (3) diversity in language and cultural backgrounds, (4) insufficient technical resources, (5) inadequate knowledge transfer, (6) poor ethics (hidden agendas), and (7) loss of key resources. Such factors can contribute to project team performance. Hence, this research will investigate the aspects of

65 performance as echoed by Lin et al. (2008) who proposed that social capital factors play a critical role and need to be considered early, well before the team formation stage.

Straub, Fevig, Casler, and Yadav (2013) analysed the risk of using students in a spacecraft project and classified the effects into a number of areas affecting the project’s success. They ascertained that a student’s inexperience allowed them to accept changes to the scope, resulting in scope creep. This in turn magnified errors in the schedule and cost estimation which resulted in cost and schedule creep. Variation in performance is not only attributed to the knowledge and skill levels of a team member but also depends on their social interaction capability (Sawyer, Guinan, & Cooprider, 2010). Jawadi and Bonet-Fernandez (2013) presented a study that stressed the importance of high-quality

relationships among team members in order to achieve high team performance. They argued that project team performance was more dependent on interaction and dialogue between team members. However, in order to increase team performance, project manager leadership and trust among team members is paramount (Anantatmula, 2010; P. Lee, Gillespie, Mann, & Wearing, 2010). Greater information exchange between team members facilitates higher team performance (Liu, Keller, & Shih, 2011). Diversity in the experiences of team members can also impact project team performance (Saji, 2004).

In an effort to develop a key performance indicator (KPI) dashboard to assess the performance of a pharmaceutical capital project, Suk, Hwang, Dai, Caldas, and Mulva (2011) identified the following key indicators: cost, schedule, dimension (space utilisation) and quality. Scope, schedule and cost are traditional measures of project performance; however, these are rapidly becoming integrated with factors such as resource usage efficiency, stakeholder satisfaction, conflict and dispute reduction and safety as new project performance measures (Ogunlana, 2010). While these latter factors are useful high-level measures at the project level, when measuring performance at the project team level, more specific detailed KPIs are required. In an IT outsourcing software development project, Narayanan, Balasubramanian and Swaminathan (2011) used the key factors of project planning capability, communication effectiveness, team stability and customer satisfaction to measure project

performance. They propose that performance has to be measured in totality, direct and indirect. The premise that project planning is important for project performance is compounded by effective communication and team stability. Higher project performance results in improved customer satisfaction.

Project performance can be attributed to project effectiveness and efficiency. Effectiveness of the project is the degree to which project managers use tools and techniques to improve the efficiency of project execution (Marques, Gourc, & Lauras, 2011), while efficiency is the degree by which the project can transform inputs into outputs in the most economical way (Swink, Talluri, & Pandejpong,

66 2006). Geraldi and Adlbrecht (2008) state that analysis and coordination of a high volume of

information that is directly linked to the number of people and entities or organisations involved in the project increases the complexity of the project. Marques et al. (2011) suggested that when the

complexity is too great (due to size of the project, the number of stakeholders, the location or the form of the contract), there is a possibility for the interrelations within the project team to become

incoherent, which then necessitates the use of appropriate skills and tools. Swink et al. (2006) argued that efficiency can be increased by significant process change, which may include a fundamental change in the technology used to transform inputs into outputs. This research aims to take this notion a step further by exploring whether SM can be used as the technology platform to bring about some form of efficiency to the project.

In their research, Brettel, Heinemann, Engelen, and Neubauer (2011) analysed the impact of integration between various departments (research and development (R&D), marketing and manufacturing), on the effectiveness and efficiency of new product development projects. Their findings indicate that integration between R&D and marketing has a positive impact on efficiency but not on effectiveness, and will depend on the process stage and the degree of innovativeness. A significant impact is seen for efficiency in the development phase between R&D and manufacturing. These findings prove that the degree of efficiency and effectiveness varies, depending on the stage or phase of the project lifecycle.

Samset (2009) proposed five criteria to measure project performance: effectiveness, efficiency, relevance, impact and sustainability. T Williams and Samset (2010) state that project effectiveness and efficiency is both achieved and driven through the overall project strategy that defines the value of the project in terms of cost, schedule and quality. PMBOK (Project Management Institute, 2013) underlines that project performance will depend on scope, cost, schedule and quality. The inclusion of quality in the equation opens the floodgate to consider the rest of the knowledge areas of PMBOK. For this research, project performance is defined as:

 effectiveness from the perspective of scope, quality, risk and talent (human resources)  efficiency from the perspective of schedule, cost and quality.

This research fills this gap from the perspective of analysing the effects of SM on project team performance. To this effect, this research attempts to link the contribution of SM to virtual teams and the social capital of project teams, and the impact on project team performance.

The next section focuses on process and maturity models that can be used to assess the robustness of business processes for the use of SM in projects or organisations.

67