Part 2: Project Management Methodologies

As mentioned above, PM involves a series of systematic procedures undertaken to achieve a goal. In the project management realm, a methodology is defined as a system of practices, techniques, procedures, and rules used by those who work in a discipline (Joslin & Mu00fcller, 2014). There are several project management methodologies (PMM) usable either solitarily or in a combination of two or more methods to realize the program goals. The types include agile, waterfall, critical path, scrum, Lean Six Sigma, and PRINCE2.

Agile

Agile is a PM approach that aims at increasing organizational flexibility. White observes that although the traditional project management (TPM) has been successful in projects whose solutions can be relatively defined, scoped, and estimated, in terms of cost and time, todayu2019s business ventures are likely to have high degrees of unforeseen uncertainties (White, 2008). To this end, TPM, which is focused on centralized decision-making and control within a hierarchical organizational structure, may not be feasible given the speed of economic dynamics. Hence, according to White, agile is an approach that deals with the reality of continuous change or incorporates discovery learning throughout the project life cycle (White, 2008). The agile method is based on some socio-technical principles, as discussed below.

The first agile principle emphasizes precision and is called minimal critical specification. According to this principle, system requirements should be precise about what has to be done and that the use of standards, rules, and predefined procedures should be kept to the absolute minimum (Dyba et al., 2014). The second principle is the principle of the autonomous team. Basing on the premise that self-managed teams are a prerequisite for the success of innovative projects, this aspect underscores that autonomous teams offer potential advantages over traditionally managed teams because they bring decision making authority to the level of operational problems and uncertainties and thus improve accuracy and speed of problem-solving (Dyba et al., 2014). Lastly, the redundancy principle is concerned with the overlap in an individualu2019s knowledge and skills to create common references for further innovation (Dyba et al., 2014). These concepts enable the applicability of the agile method on projects that have a high level of complexity or uncertainty.

Scrum

Scrum is one of the project management approaches but under the umbrella of agile. By definition, scrum is an agile method of iterative and incremental product delivery that uses frequent feedback and collaborative decision making (Michele Sliger, 2011). Sliger notes that some scholars such as Schwaber regard scrum as a framework, not a methodology, since scrum provides a structure for delivery but is not explicit on how to do specific practices (Michele Sliger, 2011). The scrum basic framework is as shown in the figure below.

Figure 2

The basic scrum framework

Waterfallu00a0

Waterfall project management, often used in software development, is a structured, sequential process to bring a project through a series of phases to the completion. The waterfall approach to systems analysis and design was the first established modern approach to building systems (Bogdan et al., 2019). The model consists of five phases, namely requirements, design, coding, testing, and operations. The requirements phase involves analyzing business needs and extensive documentation of all features (Bogdan et al., 2019). In the IT field, the design stage includes selecting the relevant technology and planning the full software infrastructure interaction. Coding entails solving all problems, optimizing solutions, and implementing each aspect described in the requirements level, based on the diagrams and blueprints from the design phase. A meticulous, extensive evaluation of all the implemented features at the testing stage enables the project management team to identify loopholes and intervene appropriately. The last phase, operations, involves deployment to a production environment. This model’s underlying assumption is that mobilizing all the requirements guarantees an obstructed road that the stakeholders will follow to complete the project (Bogdan et al., 2019). However, the latter does not always hold in real-life situations due to the dynamics of consumer tastes and preferences. In most cases, the phases may not be re-evaluated. The following diagram is an illustration of the waterfall model.

u00a0

Figure 3

Waterfall Process Model

Critical Pathu00a0

Simply put, the critical path methodology (CPM) defines project tasks based on the duration each step would take, hence the possibility of affecting the project deadlines. As mentioned earlier in this course, every project is conducted within three fundamental constraints: time, cost, and scope. The critical path approach is concerned with the project schedule. Kramer and Jenkins articulate that schedules are used as management tools to communicate activity sequence, dictate the start and finish time of work, and track progress in most endeavors (Kramer & Jenkins, 2006). Moreover, the duo observes that managers can get lost in the plethora of information provided in the project schedule (Kramer & Jenkins, 2006). Therefore, the CPM technique enables planning by scheduling and controlling project time and cost by recording their interdependence in a diagrammatic form that enables each identified problem to be tackled separately (Aliyu, 2012). This method relies on mathematical concepts in manipulating variables and determining predicting results. However, manual calculations may be rigorous and time-consuming, especially for vast data. The technological advancements have enabled access to computer-generated schedules, as shown below.

Figure 4

Example of a computer-generated CPM schedule

Lean Six Sigma

The Six Sigma management approach underscores better comprehension of customer needs, improving the organizational structure, and enhancing the firmu2019s financial performances. Like the critical path, Six Sigma integrates profound knowledge of mathematics, engineering, process, and project management (Anbari, 2002). Furthermore, Anbari argues that the Six Sigma methodology is more comprehensive than the other quality initiatives like the Total Quality Management (TQM) and the Continuous Quality Improvement (CQI) u00a0(Anbari, 2002). u00a0TQM and CQI tools are heavily oriented towards brainstorming and simple data analysis, as shown in Figure 5 below.

Figure 5

Data analysis as used in TQM and CQI

The Six Sigma blends the data analysis tools used in TQM and CQI with advanced techniques such as quality function deployment (QFD), design of experiments (DOE), failure mode and effect analysis (FMEA), and regression analysis to understand customer concerns and analyze problems adequately. Anbari summarizes the Six Sigma dimension as follows.

Six Sigma = TQM ( or CQI) + stronger customer focus + additional data analysis tools + financial management + project management.

Notably, the combination of better analytic tools and appropriate projection selection and evaluation techniques makes the Six Sigma method ideal for achieving project objectives.

PRINCE2.

PRINCE2 is the standard UK convention for Projects IN Controlled Environments. The methodology is process-based and structured, highlighting how understanding and manipulating eight particular variables can significantly reduce risk in all project types (Siegelaub, 2004). That said, the PRINCE2 technique is understandably comparable to PMBOK^u00ae.Siegelaub observes that the PMBOK^u00aeGuide loose, general approach to integrating knowledge areas, while PRINCE2 suggests an effective way to organize them (Siegelaub, 2004). Accordingly, the following table shows the comparison between the PMBOK^u00aeareas of knowledge and PRINCE2.

Figure 6

Comparison of PMBOK^u00ae^u00a0areas of knowledge and PRINCE2.

Back to Lesson