Introduction
Given the distinctions in judgment calls and goal-setting relevant to complexity, project managers must have a solid comprehension of project complexity and how they could control it. There is widespread agreement that complexity is essential to project management for several reasons. Including:
- How it affects the planning process, synchronization, and regulation.
- How it makes it difficult to define the goals and objectives of major projects clearly.
- How it may impact the choice of an acceptable project organization form and the experience requirements of management personnel.
- How managers may use it to identify suitable project management arrangements (time, cost, quality, safety, etc.).
Numerous works stress the significance of complexity in project contexts generally and, in particular, its impacts on the project’s mission and objectives, project governance form and layout, and the expertise needs of the managerial staff. The worldwide project management community may benefit significantly from identifying and characterizing many facets of project complexity to comprehend better the risks associated with project management complexity (Daniel & Daniel, 2018, p. 184). Project managers need to understand how to use the opportunities presented by complexity to manage them effectively.
Definitions
On what complexity is in project settings, there is contention. Even a specific definition of project complexity encompassing the entire idea does not appear to exist. According to the International Centre for Complex Project Management (ICCPM), complex projects can be identified by effect but not by solution, are typically run over a period that surpasses the development workflow of the technologies involved, and are characterized by unpredictability, ambivalence, changeable interfaces, and considerable political or external pressures.
Project complexity can also be defined and formalized in aspects of distinction (the multitude of components), interrelations, and interoperability (the extent to which these aspects are associated with one another), all of which are controlled by incorporation, that is, by cooperation, interaction, and regulation. According to Overwijk (2020, p. 127), the following factors combine to make up complexity:
- The impact of a decision field
- Linkages between systems and subsystems
- Functional diversity amongst project participants
It is clear that despite the many different notions derived for project complexity, they all revolve around a systematic and gradual process, which all combine to give meaning to the term.
Factors and Characteristics
The interaction between the project’s components, according to experience, is more complex than what the standard project scope statement of the project network would imply. Project managers must recognize the sources and elements contributing to or raising project complexity. Rodriguez Montequin et al. (2018, p. 17) identify four primary sources of complexity: the workflow’s number of components, the environment in which they are used, the needed level of scientific and technological expertise, and the utilized resources. As a result, elements for complicated projects include a considerable quantity of needed resources, a chaotic atmosphere, working at the cutting edge of technology, and many potential interactions.
Due to a lack of agreement, several authors have concentrated on pinpointing the attributes that lead to or enhance project complexity. According to Adzmi and Zainuddin (2018, p. 650), it is essential to distinguish between complexity’s categories, traits, or origins and its severity elements, which can either make complexity more or less severe. Scale, diversity, interconnections, interrelatedness within the project system and contextual reliance are required but insufficient prerequisites for project complexity.
Types of Project Complexity
Like many projects, organizational complexity is a bigger problem for project managers than mechanical or ecological complexity. Various kinds of project difficulty may be caused by how complexity is regarded and evaluated by project managers. According to Floricel et al. (2018, p. 17), the project’s organizational aspects account for about 70% of its complexity. Generally, there have been two basic approaches to complexity (Alvarenga et al., 2019, p. 277). The one, commonly referred to as the discipline of descriptive complexity, views complexity as an inherent quality of a system, a perspective that prompted researchers to attempt to analyze or assess complexity (Ireland & Statsenko, 2020, p. 93). The other commonly called the field of perceived complexity, views complexity as subjective because an observer’s impression of a system’s complexity is misused to determine its true complexity.
For all intensive reasons, a project manager interacts with perceived complexity because the actuality and complexity of the project can be comprehended and coped with. Project managers make the appropriate judgments and take the appropriate measures following this perceived complexity to impact the project development and achieve the intended project state (Rodríguez et al., 2018, p. 17). According to Bosch-Rekveldt and Hertogh (2018, p. 15), choosing the best project management strategy is aided by making a clear difference between the different types of complexity. The authors propose four categories of project complexity: structural, technical, directional, and temporal (Bjorvatn & Wald, 2018, p. 888). These categories are based on the source of complexity.
Structural Complexity
It is a measurement of the number of operating sections on a project. Consequently, it originates from large-scale projects, often divided into smaller tasks and separate contracts (De Rezende et al. 2018, p. 42). These types of projects are likely to be complex in the engineering, construction, and defense industries since it is challenging to manage and keep track of the numerous interconnected tasks and operations (Zheng et al., 2022). Other project types that can benefit from using structural complexity include IT sector subsystems (San Cristóbal et al. 2018, p. 10). They compose upgrades to the financial system, spend monitoring system, software application module configurations, and single management software implementations where the system is a substitute (not a greenfield site), such as a new finance system.
Technical Complexity
It is found in projects including architecture, structural engineering, and R&D that involve unproven or unknown design elements or technological components and where complexity develops due to the uncertainty around the results of numerous distinct design solutions (Ahmad et al., 2020, p. 343). Technological complexity is classified by Cerezo-Narváez et al. (2021, p. 885) in terms of distinction and interconnectedness. These categories are further divided into three types that are listed in increasing order of complexity:
- Pooled, in which each component makes a precisely defined involvement in the project.
- Incremental, in which one component’s yield becomes another component’s input.
- Reciprocal, in which each element’s yield is the other components’ inputs.
Directional Complexity
Directional complexity is frequently seen in implementation activities where the project’s direction is unclear, and project managers must take action to improve an adverse condition.
Temporal Complexity
It is the result of initiatives when significant uncertainty surrounding future limitations could disrupt the project owing to unforeseen legislative changes or rapid technological developments.
Conclusion
Delays and cost overruns are frequent when inherently unstable situations are tackled analytically. It is frequently discovered that conventional project management tools and approaches, predicated on the notion that a set of activities can be distinct, with well-defined information regarding time, cost, and resources, and with considerable preplanning and control, are insufficient. Project managers receive inflated estimates from these conventional methods, which take a structured method and ignore the project’s various feedback mechanisms and nonlinear interactions. Unlike the traditional, deterministic structures typically studied, project managers must be able to make judgments in these dynamic yet unstable systems that are constantly growing and changing randomly and are difficult to anticipate.
Reference List
Adzmi, RM & Zainuddin, H 2018, ‘A Theoretical Framework of Critical Success Factors on Information Technology Project Management during Project Planning’, International Journal of Engineering & Technology, 7(4.35), p. 650. Web.
Ahmad, F, Adhami, AY, & Smarandache, F 2020, ‘Modified neutrosophic fuzzy optimization model for optimal closed-loop supply chain management under uncertainty’, Optimization Theory Based on Neutrosophic and Plithogenic Sets, pp. 343–403. Web.
Alvarenga, JC, Branco, RR, Guedes, ALA, Soares, CAP, & e Silva, WDS 2019, ‘The Project Manager Core Competencies to Project Success’, International Journal of Managing Projects in Business, 13(2), pp. 277–92. Web.
Bjorvatn, T & Wald, A 2018, ‘Project Complexity and Team-Level Absorptive Capacity as Drivers of Project Management Performance’, International Journal of Project Management, 36(6), pp. 876–88. Web.
Bosch-Rekveldt, M, Bakker, H, & Hertogh, M 2018, ‘Comparing Project Complexity across Different Industry Sectors’, Complexity 2018, pp. 1–15. Web.
Cerezo-Narváez, A, Pastor-Fernández, A, Otero-Mateo, M, Ballesteros-Pérez, P, & Rodríguez-Pecci, F 2021, ‘Knowledge as an organizational asset for managing complex projects: The case of naval platforms’, Sustainability, 13(2), p. 885. Web.
Daniel, PA, & Daniel, C 2018, ‘Complexity, uncertainty and mental models: From a paradigm of regulation to a paradigm of emergence in project management’, International Journal of Project Management, 36(1), pp. 184–197. Web.
De Rezende, LB, Blackwell, P, & Pessanha Gonçalves, MD 2018, ‘Research Focuses, Trends, and Major Findings on Project Complexity: A Bibliometric Network Analysis of 50 Years of Project Complexity Research’, Project Management Journal, 49(1), pp. 42–56. Web.
Floricel, S, Piperca, S, & Tee, R 2018, ‘Strategies for Managing the Structural and Dynamic Consequences of Project Complexity’, Complexity, 2018, pp. 1–17. Web.
Ireland, V, & Statsenko, L 2020, ‘Managing complex projects and systems: A literature synthesis’, Australian Journal of Multi-Disciplinary Engineering, 16(1), pp. 93–110. Web.
Overwijk, J 2020, ‘Paradoxes of Rationalisation: Openness and Control in Critical Theory and Luhmann’s Systems Theory’, Theory, Culture & Society, 38(1), pp. 127–48. Web.
Rodríguez Montequín, V, Villanueva Balsera, J, Cousillas Fernández, SM, & Ortega Fernández, F 2018, ‘Exploring Project Complexity through Project Failure Factors: Analysis of Cluster Patterns Using Self-Organizing Maps’, Complexity, 2018, pp. 1–17. Web.
San Cristóbal, JR, Carral, L, Diaz, E, Fraguela, JA, & Iglesias, G 2018, ‘Complexity and Project Management: A General Overview’, Complexity, 2018, pp. 1–10. Web.
Sweetman, R & Conboy, K 2018, ‘Portfolios of Agile Projects’, Project Management Journal, 49(6), pp. 18–38. Web.
Zheng, J, Gu, Y, Luo, L, Zhang, Y, Xie, H, & Chang, K 2022, ‘Identifying the definition, measurement, research focuses, and prospects of Project Complexity: A Systematic Literature Review’, Engineering, Construction and Architectural Management. Web.