Projects within the context of product development are temporary, divine, unique, and transient. Irrespective of the different latitude of goal requirement for any organisation, either to conduct organisational change or to create competitiveness from product innovation, the gravity of the challenges encountered was inevitable and attributable to the consequences of diversity, uncertainty (risk), complexity, urgency and integration of the project. To cope with these, much of the established theory and practices emanates from the conventional methodology of PM which was used as a framework of reference. This method is driven to be linear, analytic, reductionistic, deterministic, goal-oriented or waterfall approach. The presumption of this conventional approach is defined by a set of related reductionism of activities (such as work breakdown structure (WBS), cost breakdown structure (CBS), product breakdown structure (PBS) and et cetera) and sequential procedures in which were claimed to be adequately predicted the success rate of projects. Conversely, in most cases, especially complicated, uncertain and complex projects, the conventional PM method consistently exhibits high levels in failure rate in a project-oriented company such as Li & Fung (LF). Against this background, an overview of the LF’s projects in the context of product development processes that was underpinned by the conventional PM framework was undertaken. An example of an obscure, uncertain and complex project which demonstrated failure in achieving the project goal was presented. This lead to a universal consensus that another new approach has to be deployed in order to achieve high levels of success rate.
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Align with this setting, evidence can be seen in the development of a holistic and systemic PM in the context of product development such as complex adaptive system (CAS). CAS is characterised by apparent complex behaviour that come to light as a result of non-linear property, spatio-temporal interaction among a large number of component system at different levels of the organisation. CAS also exhibits dynamic properties that could evolve, adapt to the environment. Together, these attributes and characteristic can be associated and established as a valuable construct in the defining, managing and understanding of the project development practices and can help projects be more successful. Ultimately, a conclusion can be drawn that CAS could be beneficial and it can provide the flexibility in managing complexity and uncertainty in product development more successful. The findings also suggest a limitation on the application of the CAS to the context of product development projects.
From the evolution to the revolution of the project management (PM) (Morris, PWG, 2013), projects are considered the ubiquitous driving force of organisations to improve its performance regardless of tangible or intangible value (Geraldi J, et.al., 2011; McCarthy P.et.al.,2006). Nonetheless, projects within the context of product developments (PD) in a product-oriented company are imperative to create differentiation and core competency from its competitors. Such importance stimulates the development of a plethora of frameworks and practices (Anderson, et.al, 2005) in order to improve our understanding of PD projects, processes and the management. To support such notion, there are two well-known frameworks which are claimed to be ‘the best practices’ – Bodies of Knowledge (Project Management Institute (PMI), APM, 2008) as well as the UK’s Office of Government Commerce standard (PRINCE2) (Aritua B, et.al., 2008). Collectively, these cascade a universal framework for organisational practices in term of the method, techniques and tools as remedies for implementing successful projects (Geraldi J, et.al, 2011; Vidal LA, et.al., 2008). Conversely, a paucity of success rate can be observed on projects by adopting the conventional PM method (Atkinson R, 1999) and performance improvement is perceived to be elusive (Geraldi J, et. al, 2011).
According to the Bodies of Knowledge (PMI, 2008), a project is defined as ‘a temporary endeavour undertaken to create a unique product, service or result’. Consequently, it represents an effort to explore a new horizon. Due to the characteristics of projects – unique, divine, novelty, finite, transient, multi-disciplinary, complex, dynamic and high risk, (PMI, 2008) has delineated a structural dimension with two components of approaches – the product life cycles (PLC) and the management process. The PLC consists of five-step processes ranging from inception stage, feasibility, design, execution and completion stage (waterfall approach). At each stage of the project, it is required to follow a management process which comprises planning, control, organise and implement the process (PMBOK® Guide, 4th Ed 2008, p. 78). Predominantly, these methodologies are analytic, systematic, descriptive, linear, structured, sequential approach (Aritua B, et. al, 2007; McCarthy IP, et. al, 2006). Due to the linearity property of the frameworks, the conventional PM can be conceived as an ordered, sequential and relative predictable predetermined sets of activities and dependencies (Bonner, et.al, 2002; Levardy V, et.al, 2009). Additionally, the conventional approach also makes an insidious assumption about the goal of a PD project that is known and fixed (Levardy V, et. al., 2009). By contrast, in most cases of the PD’s goals and destination are rarely distinguishable, obscure and undetermined. Above and beyond, some complex factors such as elements of flexibility, uncertainty (risk), informality, feedback (interdependency and interrelationship) and autonomy might influence the project have been discounted (McCarthy IP, et. al, 2006, p. 438). These restraints may inhibit the project’s ability to reach a goal. And yet, these methods are fairly well-suited to managing an isolated single project (Aritua B, et.al, 2007) and lower level of uncertainty (Kapsali M, 2011). To encapsulate, the conventional methods of PM in term of PD deliver less value in defining, understanding, and managing complex, multi-disciplinary, ambiguous, uncertain and complicated projects.
Against this background, a new holistic approach known as Complexity Adaptive System (CAS) has caught the momentary attention and it has been increasingly used as a lens to understand the complexity of the project development (Levardy V, et.al., 2009) especially in the realm of product development (PD) (McCarthy IP, et.al., 2006). In brief, Complex Adaptive System (CAS) defines to a complex system with an adaptive element that displays complex behaviour.
With this introduction, the structure of this article is as follows. First, it provides an overview of the project-oriented organisation – Li & Fung (LF)’s projects setting within the context of the organisational setting in project development. An illustration of a project called Battery-operated maker was outlined. Then, in the literature review, both Linear and CAS framework will be defined and elucidated in detail. Comparison between both will be delineated. Next, the recommendation to be provided. Finally, the article concludes by encapsulating the findings.
Different business organisation-specific proposition will influence the multi-variant of project activities. Correspondingly, Li & Fung (LF) is a global supply chain organisation that commend one stop supply-chain solutions for product design development, material sourcing, factory evaluation, production, manufacturing and quality control, as well as inbound and outbound global logistic (LF.com.hk, 2017). PM essentially is the lynchpin of the organisation to innovate and to change in accordance with the contemporary business need and the ever-changing market environment. Archetypally, the most salient characteristic of LF project complexity superimposed with Baccarini (1996) definition in term of organisational complexity (related to organisational hierarchical structure, levels, specialization et cetera) and technology complexity (associated with the operation, characteristic of material and knowledge). Herein the elements of complexity invariably induce complexes and complicatedness on the project.
Against this setting, LF typified a PM methodology in which underpinned primarily on the conventional PMBOK® Guide (PMI, 2008) with a set of theories, principles, and practices as a frame of reference. In essence, the methodology encapsulated project cycle, budgeting, risk and manage each phase of the projects. This approach deeply rooted in current management practice. A centralized project organisational structure was established to translate proper instruction and management to the operation of the project. This was thought could efficiently and effectively facilitated projects within the organisation.
In the similar vein, LF collaborated with Creative Memories (CM) to develop a project called Battery-Operated Maker (BO). The project goal was to develop a new revolutionary product which could attain the key stakeholders (CM) business and market demand. Project success was associated with achieving the project goals in which linked to the Iron Triangle – Cost, Time and Quality (Atkinson R, 1999, p. 337). In another elucidation, the BO’s project scouted for product differentiation, performance and functionality from any available product in the market. Due to the uniqueness of the project, it required a significant degree of technological complexity. As cited by Baccarini (2008), technology is a multi-dimensional and can be categorized into three aspects – operational (equipping and sequencing of activities), characteristics of materials as well as utilization of knowledge and skills (Baccarini D, 2008). Pertaining to this discernment, evidence can be seen that BO project required identification of risk, development of the implementation of risk management, detail product planning, process control over the activities, and a formalized communication process. Naturally, the project depended on the role of the project manager (actors or agent) who entrusted on the goals of the projects. The project manager was requested to develop stable and predictable work processes and then improved those work processes over time through increased quality, reduced costs, and shorter delivery times. Habitually, the project undertook typical multiple process phases from the initial processing phase, Planning Process Phase till Execution Process Phase. In each of the phases, a series of predetermined activities have been determined.
Not surprisingly, a major discrepancy and the deficiency were discovered during the execution stage, despite a systematic implementation steps and phases of the product cycle had been undertaken. Technically, the BO Maker could not fulfil the basic product functionality requirement or specification. Evidently, the non-systemic techniques including risk evaluation and management were incapable to encapsulate what need to be managed. Additionally, the conventional PM was solely focused narrowly on individual functions and tasks. In the end, the project ended with customer termination. The failure epitomized the concern and triggered a consensus that the current non-systemic, linear and reductionistic method had stretched to the limit, and another approach and perspective in understanding and managing the complexity of projects has to be instigated.
Thus far, there are commonly a handful types of frameworks that were encapsulated with the aim of interpreting and understanding PD – Linear, Recursive, Chaotic and CAS (McCarthy IP, et. al., 2006). In this section, due to the scope of the review, the restriction is given to Linear and CAS framework.
Linear PD framework originates from the conventional PM methodology that emphases on a series of steps, phases and multifunctional activities which are sequential and discrete (McCarthy I.P, et. al., 2006). Best known linear PD framework is Project Management Book of Knowledge (PMBOK). PMBOK® Guide (PMI, 2008) outlines a set of theories, principles, efficiency and control practices as a frame of reference which navigate throughout the project cycle and manages by coordinating each phase of the projects. The processes were determined by the communication, cooperation and coordination of the teams that participated in the PD process (PMI, 2008). The critical assumption of the linear PD framework is that through a predetermined set of activities and dependence, the goal of the PD can be achieved effectively (Bonner, et.al, 2002; Levardy V, et.al, 2009). However, as per stated in the definition of a project, it represents an attempt to achieve a project’s goal that is still uncertain, complex and ambiguous. In the main, the conventional theories and practices incapable to distinguish all of the disparate risk and uncertainty surrounding projects (Steward R, et.al, 1995). As such, this resonates with negative perspective that why so many projects failed. A survey conducted by KPMG Canada 1997 (calleam.com, Aug 2016) shows a staggering statistic of 61% surveyed organisations have suffered an unsuccessful failure rate. Even though linear framework can reveal any inappropriate process structure can deteriorate or even jeopardise any PD project, however, this reductionist technique inclined to disregard other contributing factors such as elements of interaction between disparate risk (Steward, R, et.al, 1995), flexibility, informality, feedback and autonomy (McCarthy IP, et. al., 2006).
On the other side of spectrum, in response to the uncertainty, ambiguous, complexity of a new PD as well as unclear path to a project’s designated goal and objective, this has triggered the consensus that the current conventional methodologies of the project development (PD) is insufficient and inappropriate to cope and adapt to the ever-changing environment pace (Vidal AL, et. al, 2008). Profoundly, PD is a non-linear and iterative sequence process (Levardy, et.al., 2009). According to numerous works of literature, a project can be considered as systems (Vidal A.L, et. al, 2008; Baccarini, 1996). A system is a perceived whole whose elements interconnected together because they continually affect each other over time and operate towards common purposes (Senge P, et.al, 2011).
Alternatively, Vidal Ludovic (2008) contended that ‘project complexity is the property of a project which makes it difficult to understand, foresee and keep under control its overall behaviour even when given a complete information about the project system. Its drivers are factors related to project size, project variety, project interdependence and project context.’ (Vidal A.L, et.al, 2008) Whereas, David Baccarini competed that their complexity is defined as ‘consisting of many varied interrelated parts’ and can be operationalized in terms of differentiation and interdependence through the concept of organisational and technological complexity (Baccarini D, 1996).
Not surprisingly, the above interpretation of complexity mirrors systems theory and it shares a lot of commonalities. Systems that exhibit the characteristic of complexity theory is known as a complex adaptive system (CAS) (Aritua et. al, 2009, p. 76). In another elucidation, in accordance to Plsek and Greenhalgh (2001, p.625), a CAS is ‘a collection of individual agents with the freedom to act in ways that are not always totally predictable, and whose action are interconnected so that one agent’s action changes the context for other agents’. In numerous kinds of literature (Aritua et al (2009), Dooley K (1997) and Lansing J.S (2003)), it is distinguishable that the attributes and the characteristic of a CAS can be summarised in Table 3.1.
Table 3.1 Attributes and characteristics of CAS
Hence, in an organisational context, the major antecedent in a CAS model is the individual agents which are the interaction of all the stakeholders – customers, project manager, suppliers, internal team members as well as the external market environment. And yet, adaptation or emergence is the major consequence (Holden, 2005). Emergence is referred to as global patterns of organisation behaviour which are established out from the local self-organisation as a consequence due to the interactions of the systems as opposed to predetermined or deterministic (Levardy V, et.al, 2009; Dooley K, et.al, 1997). Through the macro level of the organisation to the micro level, emergence can be observed as the system carries out the process of selection upon the agents that bring about the whole organization functioning (Dooley K, et.al, 1997). Henceforth, this fosters a complex dynamic between individual or micro level (bottom-up) and organisation or macro level (Top-down). The interaction between both systems are different in schemas, but are interdependent (Dooley, K, et.al, 1997). These dynamic and interdependent interactions render the global coherent pattern of organisation. In sum, these dimensions demonstrate how CAS diverges from linear systems. Fundamentally, these constructs provides a backbone of understanding project management in complex, uncertain and complicated environment.
By comparing and contrasting between conventional linear PD methodologies such as PMBOK Guide in particular versus the new methodology of CAS there are significant differences between them. The differences can be demonstrated in Table 3.2.
Table 3.2 Comparison between Linear versus CAS framework of PD
By contrasting between Linear and CAS approach of PD, it is self-evident to elicit that both have distinctive variation and methodologies. Through literature review, it is self-evident that the conventional PD methodology has significant limitations. The critical problem of the conventional PD is viewing the project as isolation with closed-loop boundary. Additionally, this methodology was predisposed by a set of theory that pre-specifying phases or steps of the processes to be undertaken through a series of control and management tools to evaluate the cost-quality-time. This resonates with the assumption of rationality due to cause-effect thinking and linearity about the control and boundaries. Nonetheless, it also disregards other essential elements such as flexibility, informality, feedback and autonomy that may affect the PD.
Table 4.1 Restriction of Linear Approach versus Complement CAS framework of PD
By contrast, in light of the complexity and uncertainty nature of the project, a CAS framework offers a powerful and useful insight in understanding the PM. By adopting the CAS framework, it is to recognize that project management within the context of PD processes are systems with agents that are interconnected through a nested network. Each subsystem or elements have the ability for autonomous decision making. Align with this notion, in the LF organisational setting, the CAS takes into account of the whole system elements – such as CM, Project Management Teams, Market, Environment dimension. Furthermore, the most salient considerations are the interactions between each of the elements are semi-structures (Brown and Eisenhardt, 1997). Apart from above generic properties, it is worth noting that there are some other key insights claimed for CAS structure which are imperative in understanding the CAS framework (Chan, 2001). These are listed as follows.
- Distributed Control –In lieu of highly structured and tightly coupled (Linear) which propagate high level of efficiency, the LF organisational structure between all the stakeholders are deliberated to be relatively unstructured and uncoupled. The resultant behaviour of the systems is due to the interrelationships between the stakeholders in the project. In other word, there is no single centralized structures that manage the overall system’s behaviour under the CAS framework.
- Connectivity – As a result of interrelationship, interaction collectively, independence as well as inter-connectivity of the system, subsystem, elements and its environment, these contribute partly to the project complexity as opposed to typical technology and organisational context of complexity. This signifies that a decision or action by one of the elements in the system will affect all other related elements, subsystem and ultimately the overall system.
- Adaptation and Co-evolution – In response to perturbations and change, elements in a system has the capacity (semi-autonomous) to ‘synchronize’ and ‘desynchronize’ (also known as self-organisation) in order to adapt within their environment. Through adaptation, the systems will evolve to reveal the desired characteristic that inclined to the success of the project goals or objectives. In the LF organisation context, rather than capitulate to mechanistic prediction and quantitative analysis of conventional PM methodology, the intention is to lay prominence on the qualitative dynamical trajectories on the whole system (Garnsey, E, et.al, 2006).
- Sensitive Dependence – The interaction between elements is in non-linear fashion (Aritua B, et. al, 2007; McCarthy IP, et. al, 2006). In another sense, CAS are sensitive and small changes can have a surprisingly counterintuitive influence/implication to the overall behaviour in the form of ‘butterfly effect’ or complying with ‘Power Law Distribution’ rather than following the normal Gaussian Distribution (Garnsey, E, et.al., 2006). Similarly, this phenomenon signal a fruitful understanding the repercussion of the reciprocal interaction between any elements of the stakeholder in LF project setting either in reinforcing or balancing feedback loop. Thus, in real project setting, the emergent behaviour of the project is fundamentally unpredictable in nature. As opposed to Linear approach, long-term prediction and control are not essential to be practicable in CAS framework.
- Far-from-Equilibrium – Attributable to the non-linear nature of the dynamical system, any change in processes happens far-from equilibrium, in contrast with linear system that accepted the concept of a system having equilibrium (Newtonian Paradigm) (Dooley, K, 1997). It is clear that the crux of this argument centers on how opened systems are obligated to discover any opportunities that might create different structures and new patterns of relationship as opposed to isolated systems evolve toward equilibrium, an unchanging state.
On the other side of the spectrum, it could be also observed that CAS posits some limitation. Firstly, it does not depict the operational detail. Moreover, it is very challenging to understand or even visualizing by modelling the collective behaviour pattern of the organisation. In addition, the most salient observation is that since the process consequences are random, this lead to misconception that it is therefore unpredictable.
On the other hand, the literature review proposes and supports that CAS framework takes a more holistic, interdisciplinary approach to the development of complex projects. Having said that, through the inherent properties of non-linearity, self-organising as well as the co-evolution that cascades the emergent order of the system, this leads to believe that the complex system is essentially challenging to predict with enough veracity. These attributes are the essential elements in understanding on how to manage projects. Obviously, it is self-evident that it is to define CAS is broad, complicated and often difficult to grasp. Besides, CAS has often been misunderstood that due to randomness, the system cannot be predicted.
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