15. Human Capabilities for Systems Leadership: Disseminating Systems Thinking through Education and Training

Ulf Dieckmann
Gerid Hager
Piotr Magnuszewski
Martin Lees

Most people do not encounter the principles of systems thinking in their formal education. Consequently, without the necessary tools at their disposal, they cannot apply systems thinking to understand and evaluate systemic issues that affect their lives and futures.

Yet we live in a systems world, in which systems thinking is increasingly indispensable. Four trends over the past few decades have enhanced the need for individual and collective actors to understand and engage with challenges of a systemic nature:

  • Interconnectedness. Humanity is confronted with an array of deeply interconnected difficulties and objectives. These often involve linkages between local, regional, and global scales and extend across the economic, social, environmental, and security facets of human activities. Long-term trends toward economic, political, and digital globalisation are intensifying these interconnections.

  • Speed. The processes associated with these challenges are dramatically accelerated by new information and communications technologies supporting finance, economic and trade systems, just-in-time production chains, food production and distribution, and research and innovation. This implies that the consequences of interventions cannot just be analysed in paced iterations, as was the traditional practice, but must often be anticipated and integrated holistically in the very design of such interventions, requiring step changes in the systemic scope of the underlying analyses.

  • Data. The technological systems enabling this acceleration often make it possible to measure, monitor, and memorise an incredible and highly heterogeneous amount of data across many spatial and temporal scales. In principle, this unprecedented flow of data can enable systems analyses and systems solutions of a qualitatively different kind and reach than was possible before.

  • Computing. The computing power and algorithmic prowess available for processing all this data have risen to a level at which fundamentally new practices of analysis are emerging - e.g. using machine learning and artificial intelligence - that enable data scientists to harvest the available information in innovative ways. Through the diffusion of powerful software, the power to conduct such analyses is moving from the hands of a select crowd of experts to a much larger group of data analysts and citizens.

Together, these trends have led to a revival of systems thinking, following an earlier golden era that started about 50 years ago. Today, the demand for systems thinking is widely articulated, and it is seen, sometimes perhaps even with too much optimism, as critical for overcoming an overly technocratic, reductionist, elitist, or compartmentalised traditional approach, and thus, apt for tackling the most difficult challenges of the 21st century.

While systems thinking offers a coherent, rigorous, and balanced approach to analyse and understand complex, interconnected, and dynamic issues, the character and ambition of systems thinking have been changing over time. After innovations in operations research during and after World War 2 broke new ground in terms of recognising feedbacks, nonlinearities, and networks, simple early applications of systems analyses have often become integrated into disciplinary analyses. Through decades of development, today’s ambitions have risen considerably, driven by similar rises in needs and capabilities. In this understanding, systems thinking, by definition, is going further than established disciplinary approaches toward the integrated, interdisciplinary, and holistic analyses of complex systems. Likewise, challenges at the cutting edge of contemporary systems analysis can be expected to recede into the disciplinary background of mainstream practices, to be replaced by new challenges arising at the forefront of devising integrated approaches to addressing issues in complex, interconnected, and dynamic systems.

Based on these considerations, disseminating systems thinking through education and training will always be a moving target. With the functioning of institutions and the formulation and implementation of policies critically depending on the knowledge, skills, and motivations of people at every level, self-innovating education and training in systems thinking will be central to produce a new generation of public- and private-sector leaders, experts, and teachers – and an informed public – competent to understand and act on the systemic challenges of the world. Such competences in systems leadership are also essential for the effective and efficient design of institutions facilitating the development of multidisciplinary teamwork and interdepartmental strategies and programs, supported by innovative modelling, scenario analysis, and the tools of systems thinking.

OECD and IIASA are both in the vanguard of institutions addressing these challenges, pursuing their missions bolstered by considerable track records of achievements.

Building human capabilities for systems leadership is a multifaceted challenge, as a wide variety of target audiences can benefit from the dissemination of systems thinking through education and training:

  • Practitioners. Policymakers, public administrators, ministry officers, business leaders, diplomats, negotiators, and development-aid officials need systems thinking to arrive at more integrated solutions to many pressing policy issues. Such solutions, when devised and implemented appropriately, are superior to traditional approaches by addressing problems more robustly (since systems boundaries have been drawn comprehensively); covering more loopholes and opportunities for gaming the system (since the underlying feedbacks have been recognised); and gaining acceptance among larger segments of the relevant constituencies (since complementary views of multiple stakeholder groups have been taken into account).

  • Experts. Policy analysts, systems analysts, and education analysts often use systems thinking as a core part of their professional toolbox. Typically, these experts need to train in and subsequently apply concepts, methods, models, and tools at the cutting edge of systems thinking. Achieving a higher degree of integration and using a more modern suite of systems-analysis tools are likely to make their research stand out from the mainstream and help generate additional impacts beyond their immediate peer audiences.

  • Teachers. University, school, and adult-education teachers have an important responsibility to lay the groundwork of systems thinking in the minds of learners, enabling next-generation systems competence and systems leadership. Their general objective in teaching systems thinking is to communicate transferable knowledge, qualitative approaches, and flexible heuristics. Such teaching enables learners personally to experience successful applications of systems thinking before they take such approaches into the contexts of institutional decision-making and scientific research.

  • Learners. University students, school students, and adult-education participants will initially experience the growth of their competences in simple applications of systems thinking. Once the power and versatility of systems thinking becomes tangible to them, they are more likely to infuse the underlying approaches – depending on the direction in which their professional responsibilities develop – into institutional decision-making and scientific research.

  • General public. The broadest audience for the dissemination of systems thinking is citizens interested in understanding the complex systems in which their lives unfold. For members of the general public, systems thinking can be highly beneficial, helping them to avoid pitfalls of reasoning when managing everyday situations or engaging in debates about policy issues.

The high diversity of relevant target audiences underscores why the successful dissemination of systems thinking cannot follow a one-size-fits-all strategy. Instead, there will be more and less successful ways of communicating the concepts, methods, models, and tools of systems analysis to each of these audiences. More successful training and teaching will take into account the level of knowledge the training commences from; highlight those benefits of systems thinking that are particularly attractive for motivating the given audience; and use examples and applications that are close to the target audience’s experiences and needs.

The key to systems thinking is a sufficiently broad and inclusive framing aware of systems dynamics. Accordingly, systems approaches display a higher level of ambition than traditional approaches toward overcoming overly compartmentalised methods of analysing complex phenomena. It also means that the standards of systems analysis are constantly rising. What may have been an adequately ambitious level of inclusive framing, and thus part of systems analysis, decades ago, often becomes part of disciplinary analyses once it is widely accomplished. Systems analysis, understood in this way, keeps raising its standards.

Two recent examples illustrate this. First is the widespread drive towards so-called nexus research in the earth-system sciences, through which analyses of anthropogenic impacts on land, energy, and water – and, possibly, additional targets – are becoming increasingly intertwined. This drive can be seen as a natural response not only to the need for such integration, which has existed for decades, but also to the fact that such an ambitious degree of integration has gradually transitioned into the realm of operational feasibility during the last decade. A second example is the rise of research on network dynamics and systemic risk in the wake of the Global Financial Crisis of 2008. This development can be interpreted as a swift and still-expanding movement toward applying the advances of decades of research on network theory and complex adaptive systems to the new set of highly integrative system-level questions that have quickly gained prominence and momentum through this crisis.

When striving to frame a challenge in the spirit of systems thinking, many aspects need to be considered, some of which may be problem-specific. Yet, there are at least five dimensions of inclusivity that are consistently helpful for structuring the perspectives on essentially any challenge to which systems thinking can usefully be applied (Figure 15.1):

  • Impacts. Maybe the most obvious dimension in which systems thinking requires inclusive framing concerns the impacts of the considered dynamics. This is where system boundaries feature prominently and detrimentally affect the quality of analysis when drawn too narrowly. In the latter case, important impacts are left out and cannot be accounted for as part of an integrated analysis. It is now widely acknowledged, if perhaps not yet widely remedied, that what economic analyses refer to as externalities are almost always critical components of the wider problems to be solved. The notion of externalities results from drawing narrow boundaries around a system’s economic components in general, and around the processes affecting and affected by prices through market forces in particular, while leaving the system’s environmental and social components on the outside. Even if changes in market dynamics negatively impact those other components – be it through pollution, losses of biodiversity, overexploitation of natural resources, or anthropogenic climate warming on the environmental side; or through declines of trust or precaution, reductions of public safety, rises in infection risks, or degradations in public health on the social side – these impacts fall outside the scope of market-based analyses. While it is sometimes possible to internalise externalities through taxes, many externalities cannot easily be regulated in such market-based manners. In such situations, it is therefore crucial to draw system boundaries widely enough to capture the externalities as part of a sufficiently holistic accounting of impacts.

  • Feedbacks. Crucially, the various impacts occurring throughout a system may all be part of feedback loops. Ignoring such feedbacks is particularly hazardous: while short-term predictions may well be accurate, potentially inspiring an erroneous sense of confidence, long-term predictions may be far off the mark. A prominent example are the feedbacks between demography, education, and affluence. Curbing demographic growth often helps promote education and raise affluence, which, in turn, further curb demographic growth. Overlooking those potent feedbacks has led to the notion of demographic explosion staying at centre stage in many discussions of sustainable development during the past decades, resulting in simplistic perspectives that increasingly reveal themselves as inadequate. In general, feedbacks can be positive or negative. Positive feedbacks occur when the rise in one indicator stimulates the rise of another, and vice versa. Such positive feedbacks destabilise certain components of a system. Negative feedbacks, in contrast, are stabilising and occur when one indicator’s rise causes another indicator’s reduction, and vice versa. Although any of a system’s feedback loops can be critical to understanding its behaviour, overlooking positive feedbacks, with their potential for generating exponential growth or runaway collapse, can be particularly harmful to the quality of systems analysis.

  • Trade-offs. When specifying the objectives of a particular policy intervention, trade-offs and synergies naturally come into play. The reason is that such objectives at the system level typically have multiple components, and advancing in the direction of one component may make it harder (in the case of trade-offs) or easier (in the case of synergies) to advance in the direction of another component. It is even possible that under a sufficiently broad perspective a trade-off can turn into a synergy, and vice-versa. For example, many economists and corporations have traditionally viewed environmental regulations as detrimental to their performance, owing to compliance costs. However, when reframed more broadly, it has been argued that environmental regulations can lower production costs through increased resource productivity. Instead of considering the relationship between environmental health and business profits as an inevitable trade-off, this leads to a perspective in which businesses can be both environmentally friendly and economically competitive (Porter and van der Linde, 1999). As this example illustrates, when trade-offs or synergies are not well reflected in an analysis, either because some of their components are left outside the drawn system boundaries or because the relationships specifying the trade-offs or synergies are poorly quantified, major errors in the predictions derived from such analyses are inevitable.

  • Emergences. Many systems of sufficiently high complexity have the capacity to self-organise in ways that lead to newly emergent phenomena and dynamics. Such emergences mean that the rules of the game played in the system are qualitatively altered, in ways that were difficult to anticipate before the change happened. Typical examples are broad political developments, such as revolutions, the emergence of new parties, or social movements, which are notoriously difficult to predict in analyses until they have started to unfold. These emergent phenomena are often associated with behavioural, social, and institutional dynamics. Since culture, psychology, and beliefs profoundly affect real-world systems, the human and social dimensions of systems thinking are fundamental. Hence, including such aspects in system models can be a critical, if not sufficient, antidote against overlooking emergences. Other examples of emergent phenomena are associated with tipping points in natural systems, such as a lake’s sudden eutrophication, the closure of the ecological niche of an overexploited species, or the breakdown of the thermohaline circulation driving the Gulf Stream. The quality of a system’s analysis rises with recognising and accounting for a wide range of emergent phenomena that can act as game changers.

  • Stakeholders. When a policy challenge involves many stakeholder groups, the inclusive framing of solutions, or of processes suitable for collectively identifying them, is essential for the subsequent degree of policy acceptance. In contrast, when solutions are sought with insufficient inclusivity – for example, when governments and market actors cooperate while excluding environmentalists or indigenous people – the acceptance, implementation, and longevity of the resultant measures tend to suffer. Starting out from a sufficiently wide framing in terms of stakeholder groups will thus be costly initially, but may pay off in the longer run in terms of establishing solutions that enjoy a higher degree of endorsement and robustness.

Beyond the five key dimensions of inclusivity in systems thinking outline above, four additional perspectives help avoid overly narrow framings. Each of these perspectives can be thought of as providing a mental checklist that systems analysts can use to minimise the risk of overlooking important aspects of a problem and consequently framing it too narrowly (Figure 15.2):

  • Sectors. Good systems thinking often requires multi-sectoral approaches. Scanning through the economic sectors and governance areas that are related to a particular challenge is therefore helpful to ensure that no important impacts, feedbacks, trade-offs, emergences, or stakeholders have been overlooked. As part of this scrutiny, care should be taken to ensure that the resultant analysis is not unduly dominated by economic perspectives.

  • Governance dimensions. Good systems thinking looks across the governance spectrum, from policy decisions to the policy institutions that shape policy development. By covering all these dimensions, systems approaches can lead to specific recommendations for changes at all of these levels, including recommendations for institutional modernisation.

  • Disciplines. Good systems thinking often requires interdisciplinary approaches. Including – or, at least, consulting with – representatives from different disciplines in the framing of a particular analysis can thus substantially reduce the risk of arriving at a too narrow framing. As part of this scrutiny, care should be taken to ensure that the resultant analysis is not unduly dominated by natural-science perspectives and that cultural and psychological factors are properly accounted for.

  • Scales. Good systems thinking often requires multi-scale approaches since the impacts, feedbacks, trade-offs, emergences, and stakeholders associated with one scale can differ, subtly or substantially, from those associated with another scale. Regarding spatial scales, revealing teleconnections or conflicts among the interests of local, regional, and global stakeholders are among the benefits that are likely to accrue from an awareness of how scales are connected in the context of a particular problem. Regarding temporal scales, conflicting interests are not only central for understanding intergenerational equity, but also have a bearing on appreciating how incentives to policymakers and business leaders are affected by the durations of their terms of office.

Common cognitive pitfalls can impede good systems thinking. Based on the work of several authors (Senge, 2006, Meadows, 2008, Booth Sweeney and Meadows, 2010, Benson and Marlin, 2017, Booth Sweeney, no date), we propose the following suite of mental heuristics that can aid practitioners in avoiding these pitfalls:

  • Broad perspective. The problem should be approached from a sufficiently broad perspective, by examining its boundaries, seeking to understand the big picture, seeing the system from different angles, tolerating ambiguity, and resisting the urge to come to simple conclusions and quick fixes.

  • Structural scrutiny. Framing the approach to a particular challenge should be undertaken with careful scrutiny of a system’s structure and associated behaviour; by observing how system elements change over time; looking for connections between system elements; identifying stocks (accumulations) and flows; revealing cause-effect relationships; and anticipating unintended consequences of decisions and policies (policy resistance).

  • Nonlinearity awareness. Nonlinearities affecting the system dynamics should receive particular attention, by identifying nonlinear interactions between system elements; accounting for loops of cause-effect relationships (feedbacks); and recognizing the impacts of time delays and cumulative processes.

  • Enlightened management. The management of complex systems should be based on adequately modern approaches, by focusing on possible leverage actions or leverage points (Meadows, 1999); monitoring the outcomes of actions; considering iterative adjustments of actions; challenging hidden mental models (often limited by bounded rationality); and being open to deeper strategic revisions or even institutional change.

Although these mental heuristics – or examples of systems principles – may look simple in theory, they are surprisingly hard to apply in practice, as learning from evidence in complex systems can be hampered by many barriers (Sterman, 2006).

Training in systems thinking can take many forms, the best choices of which strongly depend on the intended audience. As a starting point for designing specific interventions, it may be helpful to recognise the following universally relevant training dimensions (Figure 15.3):

  • Systems principles. Most training interventions for promoting systems thinking among non-experts will de-emphasise technicalities and instead highlight the principles characterising good systems thinking. The main aspects of these systems principles have been laid out above: good systems analysts systematically strive to frame their approaches inclusively (with regard to impacts, feedbacks, trade-offs, emergences, and stakeholders); proactively consider complementary perspectives (in terms of sectors, governance dimensions, disciplines, and scales); and avoid cognitive pitfalls (by adopting a broad perspective, structural scrutiny, nonlinearity awareness, and enlightened management). Teaching these principles in the abstract can only go so far. It is therefore helpful to embed their teaching in the broader context of the following additional training dimensions.

  • Qualitative methods. Qualitative (“soft”) methods have been developed to allow non-experts to contribute to systems analysis, often in a participatory setting. In a group-learning context, such methods have been popularised, in particular, through Peter Senge’s book “The Fifth Discipline” (Senge, 2006). Qualitative methods often look very accessible at first sight, but their proper use requires expert support. For example, while using simple examples of applications of these methods during training sessions can greatly improve the tangible understanding of basic systems principles, this approach must be used with caution: its apparent simplicity can be deceptive, and the overly complicated diagrams it sometimes engenders may frustrate participants. The portfolio of qualitative methods to be covered in the teaching of systems thinking would typically include elements of the following (Rosenhead and Mingers, 2001): qualitative scenario analysis, causal-loop analysis, cognitive mapping, and soft systems methodology.

  • Quantitative methods. Quantitative methods are part and parcel of any real-world systems analysis. Consequently, the training of systems-analysis experts has to give high priority to teaching a broad range of salient methods. For non-experts, in contrast, the learning of quantitative methods can raise undesirable barriers, because it requires sufficient time, depends on adequate background training, involves specialized hardware and software, and risks frustration. For such audiences, it will be more appropriate to provide information about the existence of salient methods and about how they are used in systems analyses, rather than build detailed skills to apply these methods. The portfolio of quantitative methods to be covered in the teaching of systems thinking would typically include elements of the following: quantitative scenario analysis, statistics, machine learning, dynamical systems, stochastic processes, game theory, agent-based modelling, bifurcation analysis, and control theory.

  • Simple models. Building awareness of the consequences of nonlinearities and feedbacks is another central dimension of training in systems thinking. This poses particular challenges, since real-world experiences leave most people ill-equipped to assess and understand nonlinearities and feedbacks. Simple models can play an important role in addressing this training need, enabling the target audience to explore – and thus, ultimately, to understand – such complex dynamics in minimalistic settings. The range of specific phenomena to be covered in the teaching of systems thinking aided by simple models would typically include the following: exponential and logistic growth; positive and negative feedbacks; time delays and lagged responses; emergence of oscillations and chaos; clustering and percolation; contagion and systemic risk; strategic interactions and best responses; tipping points and bifurcations; collective phenomena and phase transitions; and pattern formation and self-organisation.

  • Complex models. Contemporary systems analysis heavily relies on complex models, whose development and maintenance requires long-term commitments by sizable teams of researchers. The models themselves may involve, for example, agent-based dynamics or optimisation principles based on linear programming, but commonly are so extensive that specifying them in the short space of a scientific paper’s methods section is impossible. Accordingly, introductions to the use of such models often have the character of demonstration sessions, in which trainees are shown what the model can accomplish, how model inputs are specified, and how model outputs are extracted and interpreted. Since such complex models are, therefore, not well amenable to teaching, it is critical, for the purpose of training non-experts in systems thinking, to explain how the design and operation of such models are related to the more comprehensible systems principles, qualitative methods, quantitative methods, and simple models.

  • Examples. The sixth training dimension is highly important and involves success stories, application narratives, and case studies. By grounding the more general and abstract dimensions in the context of more specific and concrete challenges, approaches, and solutions, the practices of systems analysis become tangible.

For teaching systems thinking to non-experts, the approach indicated by the arrows in Figure 15.3 seems most appropriate. This approach works by illustrating qualitative and quantitative methods, as well as simple and complex models, through success stories, application narratives, and case studies, to instil in the target audience, as the primary objective of the training, a clear understanding of the principles underlying systems analysis.

Mirroring the diversity of target audiences and the richness of training dimensions, many instruments are suitable for disseminating systems thinking through education and training. The two principal characteristics according to which these training instruments can be organised are the target audience (ranging from practitioners and experts to teachers and learners to the general public) and the training duration (ranging from minutes to years). The following list is an inventory of the broad range of possibilities:

  • For practitioners. In typical settings, practitioners have little time to devote to learning about systems analysis and systems thinking. Training interventions for this audience thus have to be relatively compact and particularly relevant in serving their professional needs. Short courses and professional training sessions lasting for a few days may be most suitable. Other options include written briefing materials such as policy reports that combine high accessibility with high information density. Such materials can draw on practical, focused examples, potentially using simple qualitative methods, to convey the realities of systems dynamics and the associated risks to policy makers, public administrators, ministry officers, business leaders, diplomats, negotiators, and development-aid officials who are not familiar with the concepts and tools of systems thinking. Simulation games, described in the next section, can be attractive, due to their capacity to immerse participants in relevant cases and to offer experiential learning. Some audiences, however, regard this approach as not entirely serious. In view of the relevance of systems thinking for supporting longer-term processes of institutional design and transformation, special training interventions for practitioners can be envisaged in the contexts of developmental aid and institutional management. Such interventions could be arranged over a longer period, potentially accompanying the relevant design and transformation processes.

  • For experts. Training instruments for enhancing the systems-analysis skills of experts in narrowly defined thematic areas are already well established and typically comprise training workshops and collaborative research activities. Where broader introductions for these audiences are deemed useful, they can take the forms described above for practitioners.

  • For teachers. To promote the ability of teachers to enhance skills in systems analysis and systems thinking, materials can be developed that make it easier for them to integrate such objectives into their teaching portfolios. At the most ambitious and comprehensive level, this can take the form of curricula for university students, school students, and adult-education students. At the next level, teaching modules can be developed that enable teachers to combine multiple modules as building blocks according to their needs. At the most concrete level, specific course materials can be offered. Teachers often need specific tools to use together with their learners. Accordingly, introducing qualitative methods and simulation games may be suitable, and even simple quantitative methods have been successfully utilised1. When the goal is to interest teachers in systems thinking by highlighting its potential as part of their teaching activities, broader introductions, as described above for practitioners, can be considered.

  • For learners. To benefit university students, curricula for bachelor, masters, and PhD degrees can be adjusted toward communicating the concepts and tools of systems thinking and systems analysis, potentially supported by the teaching modules and course materials mentioned above. A comprehensive approach to building societal competences in systems thinking must start with students at school or even earlier. Training elements suitable for university therefore need to be adjusted and redeveloped for learners with less advanced academic backgrounds, before being incorporated, for example, into school projects and adult education. For many learners, especially in developing countries and rural regions, the availability of such opportunities through online courses and distance learning will be essential. For advanced university students, teaching should ideally be complemented by hands-on practical exercises and mentored research.

  • For the public. Many of the above instruments are also suitable for other audiences and the public. In particular, briefing materials can be developed at all levels, tailored to specific audiences. A particular approach with broad relevance and wide current appeal is simulation games. Such games, when carefully designed and applied, can be used for all audiences, to enable immersive group experiences that can be highly valuable for instilling and anchoring in the minds of participants key insights about the functioning and management of complex systems. Details about this promising approach are provided in the next section.

The various training instruments outlined above can all benefit from a clear understanding of what constitutes the essentials of systems thinking and systems analysis. Surprisingly, such an understanding often remains implicit in the work of many practitioners and experts. While the associated plurality of opinions may be enriching, it can also engender confusion. For this reason, it would be beneficial to distil the essentials of systems thinking and systems analysis into what may be called a foundation course, such that the design of such a course can serve as a foundation for the design of more specific interventions. Ideally, the foundation course would provide two levels of specification: first, it would identify the essentials of systems thinking and systems analysis to be covered; and second, it would identify multiple alternative means of coverage that are differentially geared to the needs and capabilities of different audiences.

Simulation games offer an innovative, experiential way to train systems competence, i.e., the ability to understand and assess the interlinked nature of a highly connected human-earth system. This includes the ability to deal with uncertainty and incomplete information at multiple levels, as well as skills to communicate and make joint decisions across departments, industries, sectors, and stakeholders.

What is needed are learning and training situations based on real-life scenarios that offer the possibility to test actions, boldly try and explore new strategies, and reflect on the resulting consequences within a safe, simulated environment. “The World’s Future – A Sustainable Development Goals Game” is an innovative experiential game2 jointly developed by the Centre for Systems Solutions3 and IIASA. It combines the benefits of systems analysis and simulation techniques with the dynamics of group-based scenario building and creative role-playing. The experiential-game approach thus offers a highly immersive and transformative learning experience.

Within about six hours, game participants gain broad and deep insights into the complexities of and multi-level interactions among the Sustainable Development Goals (SDGs) within the human-earth system, which cannot be achieved as easily and profoundly using conventional training instruments. The simulation-game approach deliberately does not offer how-to-guidelines or solutions, but instead creates a space within which participants can better understand and learn how to deal with incomplete information, feedback processes, and how to face complex challenges together. It offers tangible experiences that can greatly improve the systems-thinking skills of participants, allowing them better to grasp interlinked social-ecological complexity.

Since 2017, participants from the Directorate General for International Cooperation and Development of the European Commission, the European Parliament, the European External Action Service, and the OECD have successfully engaged in the “The World’s Future – A Sustainable Development Goals Game” gameplay (Figure 15.4), among others, offering the following testimonials:

  • “It was a humbling and eye-opening experience for me as a policy writer – to be confronted with the complexity of policy making in action and trying to find sustainable solutions, even in a simplified version of reality.” – Participant from the Directorate General DEVCO of the European Commission

  • “I got a much clearer insight that policy making is actually very messy based on imperfect understanding of the system and incentives, and on imperfect information of what others are doing.” – Participant from OECD

  • “As an industry, why would we really care about climate impacts or try to avoid them? But down the line, we experienced the effects on our infrastructure and workforce. We didn’t think about that connection in the beginning.” – Participant from OECD


Benson, T., and Marlin, S. (2017). The Habit-Forming Guide to Becoming a Systems Thinker. Pittsburgh, PA, USA: Systems Thinking Group

Booth Sweeney, L. (no date). Thinking About Systems: 12 Habits of Mind. Available online at http://www.lindaboothsweeney.net/thinking/habits

Booth Sweeney, L., and Meadows, D. (2010). The Systems Thinking Playbook: Exercises to Stretch and Build Learning and Systems Thinking Capabilities. White River Junction, VT, USA: Chelsea Green Publishing

Meadows, D.H. (1999). Leverage Points: Places to Intervene in A System. Available online at http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system.

Meadows, D.H. (2008). Thinking in Systems: A Primer. White River Junction, VT, USA: Chelsea Green Publishing

Porter, M.E., and van der Linde, C. (1999). Green and competitive: Ending the stalemate. Journal of Business Administration and Policy Analysis, Vol. 27–29, pp. 215–229

Rosenhead, J., and Mingers, J. (2001). Rational Analysis for A Problematic World Revisited: Problem Structuring Methods for Complexity, Uncertainty and Conflict, 2nd Edition. Chichester, UK: John Wiley and Sons

Senge, P.M. (2006). The Fifth Discipline: The Art and Practice of The Learning Organization. New York, NY, USA: Broadway Business

Sterman, J.D. (2006). Learning from evidence in a complex world. American Journal of Public Health, Vol. 96(3), pp. 505–514

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