FEATURED PAPER
By Pascal Bohulu Mabelo
South Africa
Abstract
Project delivery, particularly of large and complex infrastructure entails the engineering and implementation of a “solution” to an undesirable situation. Due to complexity, such a solution entails solving multi-dimensional problems (or aspects thereof); while the ‘traditional’ Pareto Analysis helps in prioritising the relevant problems or aspects, a ‘systemic’ approach shall prove more effective. Such an approach would also apply to quality improvements and risk management.
Second Order Pareto Analysis
In a recent publication (Mabelo, 2021), the author made the point that poor understanding of the problem to be solved may cause a project to fail (Haik and Shahin, 2011) and, thus, “Long before any design project starts, the design engineer has to believe that there is a problem that is worthy of their attention. The design engineer must feel a need [i.e., empathy] to solve the problem […] must have a yearning to solve the problem [i.e., an undesirable situation]” (Slocum, 2008). However, decisions concerning the technical solutions to problems are often made by the designers themselves, who implicitly select “preferred” options on the basis of their own understanding (Mabelo, 2021).
It is no wonder that the Engineering Design and Development (EDD) requires a process that can transform a problem or undesirable situation into a suitable solution or a dream into reality
—a problem-solving process—that is consistent with the INCOSE definition of Systems Engineering (SE):
“An interdisciplinary approach and means to enable the realization of successful systems. It focuses on defining customer needs and required functionality early in the development cycle, documenting requirements, and then proceeding with design synthesis and system validation while considering the complete problem […] SE considers both the business and the technical needs of all customers with the goal of providing a quality product that meets users’ needs.” (Fossnes and Forsberg, INCOSE, 2006)
Furthermore, SE defines a Complex Adaptive System (CAS) as a “dynamic system” able to adapt to and evolve with a changing (or rather evolving) environment. “It is important to realize that there is no separation between a system and its environment in the idea that a system always adapts to a changing environment” (Chan, 2001)—from this definition, CASoS refers to a Complex Adaptive “System of Systems” (Sandia Laboratories, 2011).
The author suggests that the Tacoma Narrows Bridge was not designed as a Complex Adaptive System (CAS or CASoS); thus, it lacked the “resilience” to survive the adverse interactions with the environment (Mabelo, 2021). Most Large Infrastructure Projects fit the definition of CAS or CASoS due to their usually large scale—and for being nested in socio-economic contexts.
Moreover, CAS/CASoS exhibit system-attributes such as Connectivity (i.e., complexity arising from interrelationships/interdependencies of elements); Distributed Control (i.e., no single centralised control mechanism governing behaviour of the system); and Emergent Order (i.e., potential for emergent behaviour).
“A project can be said to be complex if it consists of many interdependent parts, each of which can change in ways that are not totally predictable, and which can then have unpredictable impacts on other elements [as well as the environment] that are themselves capable of change.” (Cleland et al, 2002)
On the other hand, still on account of complexity, Sussman et al (2007, 2009) refers to “Complex, Large-scale, Interconnected, Open, Sociotechnical” as CLIOS, a new class of engineering systems with a wide-ranging social and environmental impact due to their “nested complexity”. This occurs when a physical domain is nested within and interacts with an institutional sphere, where both entities are deemed complex. From that perspective, most LIPs are basically CLIOS—which suggests the existence of multi-dimensional problems (i.e., various problems and/or many aspects of the same problems) that must be solved and addressed about a particular undesirable situation.
For instance, a rapid-transit project would entail many technical, legal and socio-economic issues such as axle-loading, tunnelling, noise pollution, tariff, crime, flora protection and property rights. Similarly, a port project would not only deal with docking, cranes, bunkering and dredgers—but also with customs/security, rail connection, warehousing capacity, ecology and “weather control”.
This begs the important question as to which identifiable problems (or aspects thereof) ought to be prioritised for solving by way of new design(s). The need for selection becomes more acute, even critical not only in the face of constrained resources, but more so owing to the usefulness of “achieving more with less”—solving the few problems that cause the most undesirability. The Pareto Analysis, based on the 80/20 Principle, is useful as a tool for achieving the above purpose (i.e., focus on the few items with most impact):
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How to cite this paper: Mabelo, P. B. (2022). Second Order Pareto Analysis; PM World Journal, Vol. XI, Issue IX, September. Available online at https://pmworldlibrary.net/wp-content/uploads/2022/09/pmwj121-Sep2022-Mabelo-second-order-pareto-analysis.pdf
About the Author
Pascal Bohulu Mabelo
South Africa
Pascal Bohulu Mabelo, MBA, MSc (Industrial), BSc (Civil), Pr Eng, Pr CPM, Pr PMSA, PMP, has more than 25 years of professional experience and possesses a wide range of technical and managerial skills pertaining to large and complex infrastructure projects. He has worked in large infrastructure projects as a design engineer, project/programme manager, project consultant and project management executive; Pascal was honoured to serve as national chairman of Project Management South Africa (PMSA), the leading Project Management professional association in Southern Africa.
Pascal has published books: “Managing Engineering Processes in Large Infrastructure Projects” (2021); he has also published “How to Manage Project Stakeholders – Effective Strategies for Large Infrastructure Projects” (2020) and “Operational Readiness – How to Achieve Successful System Deployment” (2020). He currently promotes the application of Systems Thinking and/or Systems Engineering principles and concept to unravel complexity in Large Infrastructure Projects (LIPs) in order to address their persistent risks of failure and their massive, even pernicious, cost and schedule overruns.
