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THE IMPORTANCE OF INVOLVING ALL RELEVANT STAKEHOLDERS

Identifying, mapping and prioritising a project’s stakeholder community are the most important first steps in managing complexity.

Projects and other initiatives can only be considered successful when their key stakeholders acknowledge that they are a success. This requires the effective engagement of at least the key stakeholders to understand and manage their expectations and then deliver the outcome to meet or exceed these ‘managed expectations’.

Unravelling complexity requires information, knowledge, data, opinions and ideas. The stakeholders form the richest source of knowledge, because they are intrinsically involved in finding solutions to a complex issue since they have a ‘stake’ in the outcomes of any decision making and taking action.

Researchers in the field of systems thinking and modelling have acknowledged the importance of involving stakeholders.

Allowing for different perspectives and divergent views is not only important to enrich the knowledge source for finding solutions for the root causes of any problem, but also helps to ensure continued involvement of the stakeholders in the further processes of solving the issues (‘I add value; my knowledge is respected’).

‘Buy-in’ is essential for success in stakeholder engagement. Every party must have a stake in the process and have participating members who have decision-making power. Every party must be committed to the process by ensuring any action they take is based on the decisions made through the engagement.

Involving stakeholders to participate in solving their management problems instead of bringing in outside experts to solve these problems can be described as a ‘participatory’ or ‘bottom-up’ approach.

In participatory systems analysis, the involvement of stakeholders allows the multitude of factors that may influence outcomes or objectives to be identified, whilst systems thinking provides a mechanism through which these stakeholders can interact and discuss their understanding of the management system and the dependent relationships between these factors.

DIFFERENT MENTAL MODES

Each of us has a different set of visions, aspirations and views (mental models) of how to deal with the world around us. Our mental models contain information accumulated through our lived experiences. They determine our perception of new information and help us create new knowledge.

All people relate to the world by forming hypotheses about it, ‘testing’ these hypotheses through their everyday behaviour, observing the feedback from these interactions with environments or other people, and revising their hypotheses if necessary to fit the situation.

The ‘hypotheses’ or patterns of thinking are known as ‘constructs’, because they deal with how people ‘construe’ situations; that is how they develop mental models.

Mental models are ‘…deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action…’.

Mental models reflect the beliefs, values and assumptions that we personally hold, and they underlie our reasons for doing things the way we do. They are so powerful in affecting what we do because they affect what we see and they shape our perceptions.

Mental models are the filters through which we interpret our experiences, evaluate plans, and choose among possible courses of action. The great systems of philosophy, politics, and literature are, in a sense, mental models.

Unfortunately, we cannot simply look at other people and discern their mental models, any collaboration and consensus of people is a matter of shared experience, coincidence, or the result of honest discussion and understanding.

When people grew up and lived in largely isolated communities, individual mental models among members of the community tended to coincide.

In the 21st century, isolation is rare and diversity, complexity and ambiguity are the norm.

We have all become interconnected in a vast physical and digital web.

Potentially contentious issues, such as healthcare, environmental protection, gender relationships, poverty, mental health, economic development, migration, land use or water allocation (just to name a few), are now tangled and magnified in a global system of ecological, economic, social, cultural and political processes, ideas and dynamic interactions.

In any government, organisation, business or community system there are many individuals with an interest in such systems (stakeholders) and each will have a mental model of the system and its purpose depending on their individual understanding, experience, education and values.

This means that among stakeholders there can be a multitude of views and different implicit and explicit understandings of how the processes of the system they are involved in work and the factors that would affect the purposes of the system.

In managing purposeful systems, it is important to accommodate the different world views of the stakeholders involved so that any proposed management interventions are informed by a breadth of available experience, and are acceptable to those who will need to implement changes or live with the consequences of their implementation.

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THE SYSTEMS-BASED EVOLUTIONARY LEARNING LABORATORY FRAMEWORK

This section describes a comprehensive systems thinking approach, embedded in a cyclic Evolutionary Learning Laboratory (ELLab) framework that is designed to deal effectively with complex issues in a variety of contexts.

The ELLab is an innovative systems-based framework – one that differs from other systems frameworks and approaches.

Innovation is embedded throughout the concept, design and application of the ELLab framework. Research and documentation of systems thinking abound in the literature and research journals.

However, its practical implementation and tracking of discernible impact is at best unclear, disjointed and highly variable.

The ELLab recognises these deficiencies in the practical application of systems thinking and provides a framework and implementation pathway to bridge the gap between science, research and the need to make a difference in the varied economic and socio-political environments in which decision makers, managers and the broader community grapple with the complexities of the real world.

The ELLab recognises the multi-dimensional nature of the broad environmental parameters and creates a practical approach to the engagement with stakeholders, identification of issues and the analysis and synthesis of the issues. Above all, the ELLab recognises that the impact of research is of little significance if the science is right but the application, analysis and route of impact are poorly executed.

In the ELLab, which is both virtual (a way of thinking; a concept) and real (individuals coming together to work for consensus), all stakeholders involved develop a deep understanding of the system, a shared vision and skills for systemic continuous adaption, innovation and improvement.

The ELLab consists of a unique seven step iterative process of thinking and acting in which the participants engage in well-defined activities, creating a systemic framework and environment where policy makers, managers, local facilitators, members of the community and researchers collaborate and learn together in an ‘experimental laboratory’ – to understand and address complex multidimensional and multi-stakeholder problems of common interest in a systemic way.

The ultimate goal is to achieve coherent actions directed towards sustainable outcomes.

The process of establishing an ELLab is a unique ‘methodology’ to collaboratively integrate and use existing and future knowledge to help manage complex issues. It starts at the ‘Fourth level of thinking’ with an issues workshop (step 1) and a series of forums with specialist groups to gather the mental models of all stakeholders involved in the issue under consideration, their perceptions of how the system works, what they regard as barriers to success and drivers of the system and possible strategies (solutions) to overcome these problems.

This is followed by implementing the ‘Third level of thinking’ through follow-up capacity building (step 2) sessions during which the participants (all stakeholders) learn how to integrate the various mental models into a systems structure (step 3).

The Vensim software program is a valuable tool for the development of a systems model (Causal Loop Diagram) of the issue under consideration. This learning step is of particular importance in order for all involved to take ‘ownership’ of the systems model.

Once completed, the participants move to the ‘Second level of thinking’ by interpreting and exploring the model for patterns, how different components of the model are interconnected and what feedback loops, reinforcing loops and balancing loops exist. This step aims to assist relevant stakeholders to develop an understanding of their interdependencies and the role and responsibility of each stakeholder group in the entire system.

The main barriers and drivers of the system are discussed in more detail, which provides the stakeholders with an opportunity to develop a deeper understanding of the implications of coordinated actions, strategies and policies.

Overall, this process provides all stakeholders with a better understanding of each other’s mental models and the development of a shared understanding of the issue(s) under consideration.

The interpretation leads to the identification of leverage points for systemic intervention (step 4).

Leverage points are places within a complex system (e.g. an economy, a living body, a city, an ecosystem) ‘where a small shift in one thing can produce big changes in everything.’

Senge also refers to leverage points as the ‘right places in a system where small, well-focused actions can sometimes produce significant, enduring improvements’.

Identification of leverage points greatly assists the devising of systemic interventions (finding systems based solutions) that will contribute to the achievement of goals or solving problems in the system under consideration.

The outcomes are used to develop a refined systems model, which at the same time forms an Integrated Systemic Master Plan (step 5), with systemically defined goals and strategies (systemic interventions).

In order to operationalise the master plan, Bayesian Belief Network (BBN) modelling is used to determine the requirements for implementation of the management strategies; the factors that could affect the expected outcomes; and the order in which activities should be carried out to ensure cost-effectiveness and to maximize impact.

The process of developing good policies and investment decisions is based on the best knowledge (scientific data and information, experiential knowledge, expert opinions) that is available at any point in time.

The systems model can be used to test the possible outcomes of different systemic interventions by observing what will happen to the system as a whole when a particular strategy or combination of strategies is implemented. That is before any time or money is invested in the actual implementation thereof.

Once the systemic interventions have been identified and an operational plan has been developed, the next step for the people responsible for the different areas of management is to implement the strategies and/or policies (step 6) that will create the biggest impact. Targets are determined and monitoring programs are implemented to measure and/or observe the outcomes of the strategies and policies.

In many cases it only requires an adjustment of existing monitoring programs to comply with the targets set within the ELLab process (e.g. to include factors to be measured that were used in the construction of the Bayesian Management Model).

Because no systems model can ever be completely ‘correct’ in a complex and uncertain world and unintended consequences always occur, the only way to
manage complexity is by reflecting (step 7) at regular intervals on the outcomes of the actions and decisions that have been taken to determine how successful or unsuccessful the interventions are and to identify unintended consequences and new barriers that were previously unforeseen.

In summary, the ELLab framework is generic and is designed to deal with any complex issue, regardless of its context (e.g. from large organizations and natural or social systems, to a dysfunctional family or a small business that is not profitable) or discipline area (e.g. business, health, engineering, education, marketing, development, environmental management and so on). The following sections provide further elaboration on and demonstration of various successful applications of the ELLab framework in solving complex problems in a variety of contexts

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THE COMPLEXITY OF ANY SYSTEM THAT WE HAVE TO DEAL WITH

We have all become interconnected in a vast physical and digital web. Potentially contentious issues, such as healthcare, environmental protection, gender relationships, poverty, mental health, economic development, migration, land use or water allocation (just to name a few), are now tangled and magnified in a global system of ecological, economic, social, cultural and political processes, ideas and dynamic interactions in relentlessly challenging ways not experienced before the Industrial and Technological Revolutions.

These increasing complex issues and challenges require new ways of thinking and a fresh approach to address the multi-dimensional and multidisciplinary nature of complexity.

There is an urgent need for a societal change to deal with complexity in a world that focuses on reductionist approaches (breaking things or issues into parts; traditional linear thinking; seeking silver bullets).

The need to step outside our collective ‘comfort zone’, develop new ways of thinking and act in the interest of our future is crucial.

System thinking offers a holistic and integrative way of appreciating all the major dimensions of any complex problem, and enables the formation of effective and long-term management strategies.

It is not only the ‘privilege’ of systems scientists to ‘tame’ complexity – everyone must deal with it.

Complex problems can only be solved if we have sufficient knowledge and everyone has some level of knowledge and wisdom about the issues facing society.

Critical to the success of any problem management is the continued involvement of stakeholders throughout the processes of finding effective solutions, creating and implementing management plans and refining the management over time. That requires a working knowledge of systems thinking in practice – not necessarily to become a systems scientist, but for everyone to develop a sufficient level of knowledge and skills to engage effectively in systemic decision making.

This course is therefore written for everyone who has to deal with issues in the wide range of areas of interest in society within the context of economic constraints, cultural sensitivities, different political agendas and other social issues.

This chapter describes the processes for unravelling complexity through participatory systems analysis and the interpretation of systems structures to identify leverage points for systemic interventions. It further demonstrates the promotion of effective change and the enhancement of cross-sectoral communication and collaborative learning. This learning focuses on finding solutions to complex issues by applying an iterative, systems-based approach, both locally and globally.

Current approaches to understanding and dealing with complex problems are almost universally ad hoc and non-systemic.

Few individuals or groups consider the issues holistically, i.e., few appreciate the interconnectedness of the elements of the vast system of which they are a part; and honest discussion is rare.

Silos of ideas, policy and activity abound; and issues bubble along without satisfactory resolution, ranging from ocean protection to city planning.

It has become apparent that complex problems cannot be solved anymore through a traditional single discipline and linear thinking mindsets. There is an increasing demand for society to move away from linear thinking that often leads to ‘quick fixes’ that do not last, to a new way of thinking that is systems-based.

It has become clear that more comprehensive and cross-partisan approaches are required. They must take into account participants’ mental models and encourage systems thinking.

In other words, it is only by appreciating the dynamic interplay of all the elements in a system that today’s complex social, economic or environmental problems can be solved.

Although systems thinking is an ‘old’ concept, it is increasingly being regarded as a ‘new way of thinking’ to understand and manage complex problems at both local or global levels.

The analogy of an iceberg is used to illustrate the conceptual model known as the Four Levels of Thinking for understanding systems.

In this conceptual model, events or symptoms (those issues that are easily identifiable) represent only the visible part of the iceberg above the waterline.

Most decisions and interventions currently take place at this level, because ‘quick fixes’ (treating the symptoms) appear to be the easiest way out, although they do not provide long lasting solutions.

However, at the deeper (fourth) level of thinking that hardly ever comes to the surface are the ‘mental models of individuals and organisations that influence why things work the way they do. Mental models reflect the beliefs, values and assumptions that we personally hold, and they underlie our reasons for doing things the way we do’.

Moving up to the third level of thinking is a critical step towards understanding how these mental models can be integrated in a systems structure that reveals how the different components are interconnected and affect one another. Thus, systemic structures unravel the intricate lace of relationships in complex systems.

The second level of thinking is to explore and identify the patterns that become apparent when a larger set of events (or data points) become linked to create a ‘history’ of past behaviours or outcomes and to quantify or qualify the relationships between the components of the system as a whole.

The systems thinking paradigm and methodology embrace these four levels of thinking by moving decision-makers and stakeholders from the event level to deeper levels of thinking and providing a better understanding of the system under consideration.

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WHAT IS A SYSTEM?

The story of ‘the six blind men and an elephant’ has slightly different versions in different cultures. The story goes like this: Once upon a time, there lived
six blind men in a village. One day the villagers told them, ‘Hey, there is an elephant in the village today.’ They had no idea what an elephant was. They decided, ‘even though we would not be able to see it, let’s go and feel it anyway’. All of them went to where the elephant was standing. Every one of them touched the elephant:

• ‘Hey, an elephant is a pillar’, said the first man who touched his leg.
• ‘Oh, no! It is a rope’, said the second man who touched the tail.
• ‘Oh, no! It is a huge snake’, said the third man who touched the trunk.
• ‘It is a big hand fan’, said the fourth man who touched the ear.
• ‘It is a huge wall’, said the fifth man who touched the belly.
• ‘It is a solid pipe’, said the sixth man who touched the tusk of the elephant.

The reason each of them was experiencing it differently is because each one of them touched a different part of the elephant. In other words, each of them had a partial truth. The elephant has all the features that each of them described, but isn’t fully what they described unless we combine all of their answers.

Only when each individual learns that they are part of a system, touching upon truth at some point, but probably not touching upon the total systemic truth, will each teammate seek out alternative perspectives.

Many times, disagreements are not really disagreements at all, but just individuals seeing or feeling a different aspect of the system. Revealing a portion of the truth, that only when combined yields the whole truth.

In other words, ‘the behaviour of a system cannot be known just by knowing the elements of which the system is made’.

However, this is still a prevailing philosophy, or ways of doing things, in our society. That is, when one wants to understand a system, there is a common tendency to break it into parts and study each part separately.

There are various definitions of a system. For example:

• ‘A system is a way of looking at the world’.
• ‘A system is a collection of parts that interact with one another to function as a whole’.
• ‘A system is a set of elements or parts that is coherently organised and interconnected in a pattern or structure that produces a characteristic set of
  behaviours, often classified as its ‘function’ or ‘purpose’’.
• ‘Simply defined, a system is a complex whole the functioning of which depends on its parts and the interactions between those parts’.
• ‘A system is more than the sum of its parts – it is the product of their interactions’.

It is important to note that a collection is also composed of a number of parts, but they are just ‘thrown’ together and are not interconnected. A system must consist of:

• Elements or parts,
• The interconnectedness and interactions between these parts, and
• A function or purpose

Examples of systems: A football team; the digestive system; a school; a city; a corporation; an animal; a tree; a forest, etc.

A forest is a larger system that encompasses subsystems of trees and animals.

Similarly, your body is a large system that consists of various subsystems.

For instance, the digestive system includes elements such as teeth, enzymes, stomach, and intestines. They are interrelated through the physical flow of food, and through an elegant set of regulating chemical signals. The function of this system is to break down food into its basic nutrients and to transfer those nutrients into the bloodstream (another system) while discarding unusable wastes.

What is systems thinking?

Different scholars define systems thinking slightly differently, for example:

• ‘Systems thinking is a way of looking at, learning about, and understanding complex situations’.
• ‘Systems thinking is a way of seeing and talking about reality that helps us better understand and work with systems to influence the quality of our lives’.
• ‘Systems thinking is a big idea – the idea that you really can understand and tame the complexity of the real world by seeing things in the round, as a
  whole’ .
• Systems thinking is a ‘new way of thinking’ to understand and manage complex problems.

In beliefs about the relationship between humans and the rest of the natural world, in philosophical understandings of the universe, or medicine and healing, we see numerous examples of cultures which have, throughout history, operated with a ‘holistic view’, seeing things as a whole or a system; this is the essence of systems thinking. The following examples clearly illustrate the centuries-old existence of systems thinking in many cultures.

Australian indigenous cultures (the oldest continuing cultures in the world) have a deep connection with the land that is expressed in their stories, art and dance. For them, country is a word for all the values, places, resources, stories and cultural obligations associated with that area and its features. It describes the entirety of their ancestral domains.

Systems concepts have also been present in the thinking and philosophy of Maori people in New Zealand. These indigenous people highlight the importance of the ‘Earth Mother’ and the ‘Sky Father’ and perceive that everything in the universe is connected.

For millennia, Native Americans have employed traditional healing modalities that are very old in methodology and holistic in nature. This ancient holistic approach is still used today by many Native Americans to resolve health care problems.

Eastern philosophy has evolved a unique, systemically non-linear and holistic worldview. For example, ancient Chinese philosophers believed that everything in the universe was made up of two forces called ‘yin’ and ‘yang’. This reflects not only the collective wisdom of ancient Chinese people about the fundamental features of the universe, but also influences the way of metaphysical thinking of subsequent Chinese in various schools or movements.

Reductionism is a concept in philosophy that claims a description of properties in a complex system can be ‘reduced’ to the lower-level properties of the
system’s components.

However, Western thinking was heavily built upon three fundamental pillars, namely:

• Greek reductionism, separation of mind and matter
• Which led to the separation of mind and body advocated by René Descartes
• And a deterministic-monotheistic worldview originated by Isaac Newton

René Descartes taught Western civilization that the thing to do with complexity was to break it up into component parts and tackle them separately. This is still the prevalent mode of thinking in the West.

Systems thinking is not a new concept. It is not easy to identify the precise beginning of the systems thinking field, as the beginning is a matter of perspective.

For example, Midgley suggests that the field and study of systems began in the early 20th century with either Alexander Bogdanov or Ludwig von Bertalanffy.

It is widely acknowledged in the literature that Checkland and Senge also proposed influential systems thinking approaches.

Systems thinking is a very broad field.

Sherwood concludes that it would be impossible to cover all of its associated tools, techniques, methods and approaches in a single document. Understandably, there have been various books and papers written on the topic of systems thinking.

The application of systems thinking has been evident in many diverse fields and disciplines such as, to mention but a few, management, business, decision making and consensus building, human resource management, organisational learning, health, commodity systems, agricultural production systems, natural resource management, environmental conflict management, education, social theory and management, food security and population policy, sustainability, and complexity management.

Amongst the vast number of publications on systems thinking, Peter Senge’s book, ‘The Fifth Discipline’ is described as ‘bestselling’, ‘more than 1 million in print’ and ‘one of the seminal management books of the past seventy-five years’. Senge describes what he believes are the five new component technologies that are gradually converging to innovate learning organisations, namely

• Systems Thinking
• Personal Mastery
• Mental Models
• Building Shared Vision and
• Team Learning

He emphasises how important it is that the five disciplines develop as an ensemble and points out the challenges of integrating new tools, rather than ‘simply apply them separately’.

This is why systems thinking is the fifth discipline – ‘the discipline that integrates the disciplines, fusing them into a coherent body of theory and practice’.

Apart from the millions that read this book, why is this ‘Fifth Discipline’ not yet absorbed into everyday decision making or implementation? Why is the journey from theory to impact so difficult?

In spite of its extensive application in various fields, systems thinking has mostly been used and applied by systems scientists and some academics.

The application of systems thinking by policy makers, managers, practitioners, and ordinary people remains limited. This has been attributed, but not limited to, several factors including the ‘difficulty to sell systemic thinking’, systems thinking is not yet a phrase in general use, it is a frequently misunderstood term meaning many things to many people, the emphasis in formal education is evidently placed on events, parts, and isolated processes rather than systemic relationships, and the bulk of systems education to date has been focused on training specialists.

In addition, the diverse schools of systems thoughts create confusion about the systems thinking concept. There is an urgent need to make systems and interconnected thinking become popular, or ‘unremarkable’ as suggested by Allen, and easy to understand by all, i.e., become ‘a common language’ as proposed by Zhu or ‘absorbed into scientific research, in the same way that statistics, is today an integral part of all sciences’ as postulated by Bosch, et al.