Toolkit: Complex Systems Toolkit.

Author: Professor Michael Ward, CEng, FIMechE, FIET (University of Strathclyde).

Topic: Defining and understanding complex systems.

Title: The role of Wicked Problems thinking to help understand the extent of engineering involvement in complex systems.

Resource type: Knowledge article.

Relevant disciplines: Any.

Keywords: Available soon.

Licensing: This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. The work on which this project has been based was funded by the Engineering and Physical Sciences Research Council of the UK through the UK FIRES Program (EP/S019111/1) and the Future Electrical Machines Manufacturing Hub (EP/S018034/1). Earlier work supported by High Value Manufacturing Catapult has also been essential in developing the basis for this work.

Downloads: A PDF of this resource will be available soon.

Who is this article for?: This article should be read by educators at all levels in higher education who are seeking an overall perspective on teaching approaches for integrating complex systems in engineering education. 

Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded. 

This resource relates to the Systems Thinking and Critical Thinking INCOSE competencies. 

AHEP mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4):  Analytical Tools and Techniques (critical to the ability to model and solve problems), and Integrated / Systems Approach (essential to the solution of broadly-defined problems).  

Premise:

Engineering is crucial to achieving imperatives such as decarbonisation. Yet engineering typically addresses specific, well-defined challenges rather than broad, ambiguous ones. Education and practice reinforce this approach, with even postgraduate and academic engineers often focusing on problem depth over breadth. While this produces deep technical insights and tangible technological capability, it risks delaying uptake and impact unless multidisciplinary teams are involved. Recognising this gap between aspirations and execution suggests a role for structured frameworks and tools to trigger bridging activity. Wicked problem thinking is a way to understand complex problems and systems thinking, and it is related to situations which are ambiguous, contested, sometimes lacking an end state, evolving over time, requiring collaboration, adaptability, and inherently cross-disciplinary.  

Background:

Climate change is a helpful case in illustrating the gap between global ‘wicked’ problems, and the work of the engineer.  Engineering’s success, by underpinning industrialisation and thereby enabling mass consumption, can also be seen as its biggest failing in contributing to climate change (Datea & Chandrasekharana, 2022) and other environmental impacts. Going forward, engineers must help mitigate it, through better deployment of existing technologies and creation of new ones.  Clearly climate change is complex, spanning scientific, technological, behavioural, and political dimensions, and this complexity limits what can be achieved solely from engineering consideration. Conventional engineering methods, though highly effective at the project and programme level, risk drifting away from the original issue and producing isolated solutions with limited systemic effect. 

Wicked problems thinking:

Global challenges like climate change are sometimes labelled “super-wicked” problems—time-limited, caused partly by the problem-solvers, lacking central authority, and often deferred (Levin et al.). In engineering, wicked problems present a risk, because engineers are inherently tasked with addressing a part of the wider problem and often via particular approaches.  Perhaps it is not surprising, then, that engineers are trained for structured problems with clear solution methods (Schuelke-Leech, 2021). Unfortunately such approaches are rarely transferable directly to wicked contexts, except when problem structure and solution approaches align unusually well. Education reinforces this, as engineering curricula focus on well-defined challenges (Lönngren, 2017).   

At the research level, problems are often entangled, requiring both high-level perspective and detailed work. Sustainable engineering science (Seager et al., 2012) calls for ethical awareness, adaptive methods, and “interactional expertise” drawn from other disciplines. While this opens opportunities to measure cause and effect across scales, tangible short-term indicators often dominate. 

A structured approach to Wicked Problems:

Alford & Head’s (2017) typology places problems on a spectrum from “Tame” to “Very Wicked.” Most engineering projects are tame, even when complex, because specification and management processes reduce ambiguity. Issues like decarbonisation-related engineering research, however, often involves wicked characteristics.  This framework has recently been extended (Fehring, 2025) to allow consideration of a wider range of engineering research scenarios, Figure 1.   

Figure 1.  A framework for categorising complexity of engineering research scenarios (Fehring) 

Each of the identified scenario types is somewhat distinctive, as follows: 

• Tame:  Challenge of delivery and execution within known (but potentially challenging) parameters.   

• Analytically complex:  Known and accepted performance gaps with corrective actions not obvious. 

• Communicatively complex:  Multiple elements being brought together at the discretion of different parties.    

• Complex:  Major external influences drive the need for fundamental change.   

• Cognitively complex:  All agree on the need for action, but the nature of the action is unclear. 

• Politically complex:  A known technological challenge, which can only be addressed collaboratively via multiple parties.  

• Conceptually contentious:  Many indicators of impending change and the need to respond, but response is open to interpretation.   

• Politically turbulent:  Major competing factions exist, promoting alterative interpretations to global problems. 

• Very wicked:  All that is known for certain is that there is a tangible basis for concern and no obvious route to resolution. 

• Supportable opportunity: An area where research is interesting and sufficiently well aligned to available funding models to be well supported. 

• Provocation: A general issue is raised as a burning platform for action, without any consideration of potential mitigations. 

• Challenging opportunity: An area with potential for development, but not well aligned to themes supported by funders. 

• Realisation: Evidence of the issue is presented and published without any proposal or speculation on solutions. 

• Paradigm shift: An area of potential Research and Development and potential major breakthrough which is contrary to accepted thinking. 

• Call to Action: A call to adopt a solution which is available but for the most part unacceptable at the human or social level.  

• Ignored Issues: Situations that only become problems because they are not discussed based on their taboo nature or unacceptability of discussion in an area. 

Conclusions:

• Engineers can often be drawn into issues and challenges which can require multidisciplinary approaches.  

• A structured framework, such as the one described here, can be helpful in allowing the nature of a particular situation to be understood and the applicability of different approaches considered. 

• Pure engineering approaches are most applicable in scenarios closest to Tame Problems. 

• Multidisciplinary approaches seem most essential in cases closest to Very Wicked Problems. 

• Engineering research extends to a wider range of scenarios than those considered problems per se, and these have been added to the categorisation framework.  This extension of the framework, while not problem specific, is helpful in providing a logical means of extending the consideration to wider research situations. 

• One of the primary areas of potential in this form of analysis is to demonstrate the degree of separation that can exist between focused and engineering R&D and the system level problem which drives it. 

References:

• Alford, J and Head, B. W. ‘Wicked and less wicked problems: a typology and a contingency framework’, Policy and Society, 36:3, (2017) 397-413, DOI: 10.1080/14494035.2017.1361634

• Datea, Geetanjali. and Chandrasekharana, Sanjay., ‘Beyond Efficiency: Engineering for Sustainability Requires Solving for Pattern’, Engineering Studies, 10, 1, (2022), 12–37

• Fehring, F. ‘A wicked and complex problem-based analysis framework applying wicked problem thinking to the supply chain and engineering research domain’, Student thesis: Doctoral Thesis, University of Strathclyde, (2025)

• Lönngren, J., ‘Wicked Problems in Engineering Education : Preparing Future Engineers to Work for Sustainability’ PhD dissertation, Chalmers Tekniska Högskola), (2017)

• Schuelke-Leech, Beth-Anne., ‘A Problem Taxonomy for Engineering’, IEEE Transactions on Technology and Society’, 2, .2, pp.105-105, (2021)

• Seager, T., Selinger, E. and Wiek, A., ‘Sustainable Engineering Science for Resolving Wicked Problems’, J Agric Environ Ethics 25, (2012), 467–484, DOI 10.1007/s10806-011-9342-2 

Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters. 

Toolkit: Complex Systems Toolkit.

Authors: Dr Neil Carhart, University of Bristol; Dr. Francesco Ciriello, King’s College London; Richard Beasley, RB Systems.

Topic: Definitions of key terms relevant to Engineered Complex Systems.

Title: Engineering complex systems glossary. 

Resource type: Knowledge article.

Relevant disciplines: Any.

Keywords: Available soon.

Licensing: This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. 

Downloads: 

• A PDF of this resource will be available soon.

• Glossary table: Excel spreadsheet.

Who is this article for?: This article should be read by educators at all levels in higher education who are seeking an overall perspective on teaching approaches for integrating complex systems in engineering education. 

Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded. 

This resource relates to the Systems Thinking and Critical Thinking INCOSE competencies. 

AHEP mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): Analytical Tools and Techniques (critical to the ability to model and solve problems), and Integrated / Systems Approach (essential to the solution of broadly-defined problems).  

Premise: 

This document aims to provide definitions of key terms regarding engineered complex systems.  

There are many existing relevant glossaries (for example, the Systems Engineering Body of Knowledge or SEBoK) so we have implemented a process to select a curated list of 14 common terms that are fundamental when considering the idea of complexity in engineered solutions, and therefore of importance to educators in this space. Rather than adding new definitions for each term we offer appropriate and accessible definitions from the literature, together with commentary exploring wider context and consideration where relevant.  

Approach: 

Some care is needed when using any definition around terms relating to complexity – because complexity itself is complex. There are multiple valid perspectives and so any one definition is unlikely to capture the totality of nuance and satisfy the variety of viewpoints. The process for selecting these terms involved collating an initial long list for potential inclusion, along with the ways in which each has been previously defined. These are provided as a supplementary annex to the main glossary. The method is further described in the following sub-section.  

An initial list of potential terms to define was generated by cross-referencing existing glossaries. Terms that occurred in multiple glossaries were included in the long list. The definitions of these terms were extracted from these existing glossaries and are cited in the references. In addition, the relationship to the INCOSE Competencies is shown. The range of potential terms, and the variety of definitions that already exist, illustrate the complexity of describing complexity!  

The authors used three categorisations of the definitions to help further group and classify the terms. The following categories are tagged to relevant terms in the glossary: 

1. Property – whether or not the term describes a property applied to systems; 

2. Principle – whether or not the term represents a principle that should be used when engineering complex situations or systems; 

3. Approach – whether or not the term represents an approach, or element of an approach that should / could be used when engineering complex situations or systems. 

Finally, explanatory commentary was added to most definitions to more specifically address an engineering education context.  

Glossary:

Architecture 

Definition: “an abstract description of the entities of a system and the relationship between those entities.” Crawley et al. (2016) System Architecture: Strategy & Product Development for Complex Systems

Boundary 

#Property #Principle 

Definition: “Define the system to be addressed. A description of the boundary of the system can include the following: definition of internal and external elements/items involved in realizing the system purpose as well as the system boundaries in terms of space, time, physical, and operational. Also, identification of what initiates the transitions of the system to operational status and what initiates its disposal is important.” NASA (2007) NASA Systems Engineering Handbook, p304 

Commentary: The boundary defines the scope of the system being considered, and by implication, what sits outside of the system. As such, it is critically important to define the boundary of the system-of-interest. When dealing with complex systems this can be a challenging task and may even benefit from acknowledging multiple boundaries (e.g. physical, spatial, functional, logical etc.). For example, the boundary of the physical elements of a system could be considered within a wider boundary of the problem space.  

Complexity 

#Property 

Definition: “A complex system is a system in which there are non-trivial relationships between cause and effect: each effect may be due to multiple causes; each cause may contribute to multiple effects; causes and effects may be related as feedback loops, both positive and negative; and cause-effect chains are cyclic and highly entangled rather than linear and separable.” INCOSE (2019) INCOSE Systems Engineering and Systems Definitions 

Commentary: Early conceptions of complexity emphasised the difficulty in understanding, predicting or verifying the behaviours of a system. A key distinction arising from this is the complicated and complex are not synonymous.  This concept of the difficulty in predicting behaviours is reflected in the definitions of the NASA Systems Engineering Handbook, SEBoK and ISO 24765. This is the key resultant consideration but does not describe the underlying property which causes this difficulty. While this definition relates more to complex systems than complexity, it is chosen for the way in which it goes beyond the consequences of complexity.  

Coupling 

#Property #Principle 

Definition: “Coupling […] means to fasten together, or simply to connect things […] Coupling suggests a relationship between connected entities. If they are coupled, in some way they can affect each other […] For the system to be useful, its components have to be connected – coupled – so that they can work together. That said, putting them together arbitrarily won’t do the trick. The components have to be coupled in a way that achieves the goals of the system. Not only is coupling the glue that holds a system together, but it also makes the value of the system higher than the sum of its parts.” Khononov (2024) Balancing Coupling in Software Design: Universal Design Principles for Architecting Modular Software Systems, Ch1 

Commentary: Coupling is a very important concept. It is the interconnection and interdependence that makes the system more (or less) than the sum of its parts. Standard Systems architecture advice is to minimise coupling between system elements (or between the systems in a system-of-systems). This is because high coupling correlates to higher structural complexity, reduced resilience and flexibility in the system, and introduces challenges for modularity in the system design. Lower or looser coupling means changes in one part of the system (in design or operation) are less likely to induce or require changes in another part. However, this lower coupling is not always possible and may be necessary to improve system performance (for example communication through intermediate layers in a system to reduce coupling can introduce unacceptable amounts of overhead and latency in the system). In design terms, high coupling between system elements means that those elements cannot be designed independently.  

Emergence 

#Principle 

Definition: “As the entities of a system are brought together, their interaction will cause function, behaviour, performance and other intrinsic (anticipated and unanticipated) properties to emerge… Emergence refers to what appears, materializes, or surfaces when a system operates.” Crawley et al. (2016) System Architecture: Strategy & Product Development for Complex Systems 

Commentary: It is worth noting that Crawley et al. (2014) go on to add “As a consequence of emergence, change propagates in unpredictable ways. System success occurs when anticipated emergence occurs, while system failure occurs when anticipated emergent properties fail to appear or when unanticipated undesirable emergent properties appear.” This emergence that gives rise to the difficulty in understanding, predicting or verifying the behaviours of a system (see Complexity).

Form 

#Property 

Definition: “The shape, size, dimensions, mass, weight, and other measurable parameters which uniquely characterize an item.” SAE International (2019) ANSI/EIA-649C 

Function 

#Principle #Approach 

Definition: “A function is defined as the transformation of input flows, with defined performance targets for how well the function is performed in different conditions. A function usually has logical pre-conditions that trigger its operation. ”Systems Engineering Body of Knowledge v2.12 (2025)  

Commentary: In general usage it is common to hear reference to ‘Form and Function’ in tandem, but it is the distinction between them and their relationship to one another that is important to engineering complex systems. Thinking in terms of functionality is a good way of abstracting the system to define what it does (or is needed to do) rather than what it is (and therefore by extension its form).  Functions are normally allocated to single sub-elements of the system.  Complexity arises at functional interfaces, or when different elements perform the same function. Thinking in terms of functionality encourages creativity as designers consider all the different ways in which the function could be performed – and then apply requirement constraints to choose the best/most feasible option.  Thinking in terms of “objects” first constrains design by presupposing the solutions.  Equally, when the solution goes wrong, thinking in terms of what function is failing and why, rather than focusing on a failed part allows identification of the true root cause. Organisations also have functions (such as Engineering, Human Resources, etc.) as a group of roles that perform a specific set of activities. This is important for considering the organisation/System that creates the engineered solution (which is itself a complex system, but secondary to the main application of the idea of function). 

Iteration 

#Approach 

Definition: “Iteration is used as a generic term for successive application of a systems approach to the same problem situation, learning from each application, in order to progress towards greater stakeholder satisfaction.” Systems Engineering Body of Knowledge v2.12 (2025)  

Lifecycle  

#Property #Principle #Approach 

Definition: “The evolution of a system, product, service, project or other human-made entity from conception through retirement.” ISO (2024) ISO/IEC/IEEE 24748-1:2024 

Commentary: Understanding the lifecycle of an engineered artefact is very important. Issues arising in later stages (e.g. production, support/maintenance, upgrade and disposal) must be considered during the system’s initial development. In a system-of-systems or a capability system a significant source of complexity is the fact that different system elements have different lifecycles, and so may change or be changed independently of other elements with which they may interact or interdepend.  

Model 

#Approach 

Definition: “An abstraction of a system, aimed at understanding, communicating, explaining, or designing aspects of interest of that system” Dori, D. (2003) Conceptual modelling and system architecting, p286 

Commentary: An abstraction is a simplification. The selection of what to exclude, what to include, and at what level of granularity to depict it, is informed by the purpose of the model and the point of view from which it is created. Models do not have to be quantitative, nor is their purpose exclusively analytical. 

Stakeholder 

Definition: “A group or individual who is affected by or has an interest or stake in a program or project.” NASA (2019) NASA Systems Engineering Handbook SP-2016-6105 (Rev. 2) 

Commentary: It is worth noting the potential difference between a stakeholder of the project that develops the system, and a stakeholder of the system that is developed.  

System 

#Principle #Approach 

Definition: “A system is an arrangement of parts or elements that together exhibit behaviour or meaning that the individual constituents do not.” INCOSE (2019) INCOSE Fellows Briefing to INCOSE Board of Directors, January 2019 

Commentary: There are many similar definitions of a system, each may offer a slightly different phrasing which can resonate better with different individuals. The origins of this definition is explained in the Systems Engineering Body of Knowledge. In assessing complexity in engineered system, the concept of “systems” is of course of key value.  There are two important aspects two consider: 

1) Many schools of Systems Science argue that systems do not actually exist (apart from perhaps the complete universe) – they are defined for the convenience of consideration, and so the definition of the boundary of the “system of interest” is both important and somewhat arbitrary. As such, the system-of-interest can have multiple useful boundaries.  While it might be possible to identify and articulate the physical boundary of an engineered artefact (and it should be acknowledged), it might not be the most useful boundary to consider.  

2) The point of defining a “system of interest” includes being able to consider it as a system and so use the properties seen in systems (boundary, interface with outside, affected by/affecting environment, made up of parts, part of something larger, has a lifecycle, seen differently by different people (with different perspectives), are dynamic, exhibit emergence etc.) as a “framework for curiosity” (as the INCOSE SE competency framework defines systems thinking).

In engineered systems (rather than natural systems) it is important to distinguish between purpose (what those engineering or creating it want it do) and emergence (what it actually does). 

Systems Engineering 

#Principle #Approach 

Definition: “Systems Engineering is a transdisciplinary and integrative approach to enable the successful realization, use, and retirement of engineered systems, using systems principles and concepts, and scientific, technological, and management methods.” INCOSE (2019) INCOSE Systems Engineering and Systems Definitions 

Systems Thinking 

#Approach 

Definition: “Systems thinking is thinking about a question, circumstance, or problem explicitly as a system – a set of interrelated entities.” Crawley et al. (2016) System Architecture: Strategy & Product Development for Complex Systems 

Commentary: Crawley et al (2016) go on to add “This means identifying the system, its form and function, by identifying its entities and their interrelationships, its system boundary and context, and the emergent properties of the system based on the function of the entities, and their functional interactions.”  

References:

• Crawley, E. Cameron, B. & Selva, D. (2016). System Architecture: Strategy & Product Development for Complex Systems, Pearson 

• Dori, D. (2003). “Conceptual modeling and system architecting.” Communications of the ACM, 46(10), pp. 62-65. 

• INCOSE (2019). Systems Engineering and System Definitions – Version 1.0, Available Online at: incose-se-definitions-tp-2020-002-06.pdf  

• ISO (2024). Systems and software engineering — Life cycle management -ISO/IEC/IEEE 24748-1:2024 

• Khononov, V. (2024). Balancing Coupling in Software Design: Universal Design Principles for Architecting Modular Software Systems, Addison-Wesley Professional,  

• NASA. (2007). Systems Engineering Handbook – Revision 1. Washington, DC, USA: National Aeronautics and Space Administration (NASA). NASA/SP-2007-6105. 

• NASA (2016). Systems Engineering Handbook – Revision 2. Washington, DC, USA, National Aeronautics and Space Administration (NASA). NASA/SP-2016-6105 (Rev. 2) 

• SAE International (2019). National Consensus Standard for Configuration Management -ANSI/EIA-649C 

Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.