Fundamentals of systems thinking

 Everything in this world, and indeed the universe, is connected to something else and is part of something bigger. Our actions have wide consequences that affect people, organizations, and society around us. These consequences may be negligible or significant; they may be immediate or several years down the line. Have you ever made a decision or done something expecting one outcome, but the result was quite different and unexpected? Most of us have had this experience. It might have happened in the school playground, in a sports team, on a social network with family and friends, or at work. In fact, the world's history is full of examples of unintended consequences. Two such examples include:

In Borneo in the 1950s, to eliminate the problem of malaria, the World Health Organization recommended spraying DDT pesticide to kill the carrier mosquitoes; it had two unrelated consequences. First, DDT also killed a species of wasp that controlled the population of caterpillars. Most roofs of Borneo houses are made of thatch, and with natural pest control gone the roofs started to collapse. Second, DDT affected other insects which were a food source for geckos. Although geckos could tolerate the DDT in their bodies it stayed in their system for long enough to kill the population of cats that ate them. With the cats gone the island's population of rats exploded, resulting in the destruction of grain stores and a dramatic increase in the plague. They ended up parachuting cats back into Borneo to address the problem (O'Shaughnessy, 2008).

The global financial crisis of 2008 was caused by a downturn in the US housing market and a rising number of borrowers unable to repay their loans, and it spread throughout the world. The underlying cause of the crisis was the confidence that the strong economic growth throughout the preceding years would continue. This, together with increasing competition between lenders and weak or lax regulations for sub-prime lending, resulted in lenders taking excessive risks by giving mortgages to high-risk homeowners and home builders. To be able to lend more, the lenders borrowed more money. The spark that set the crisis was the rising number of lenders not able to repay their loans coinciding with oversupply.

PART ONE

Fundamentals of systems thinking

In this part of the book, which consists of Chapters 2 and 3, we focus on developing the fundamental concepts and definitions that underpin systems thinking. In Chapter 2 we develop the concept of ‘a system’ and answer the question ‘What is a system?’ as well as introduce some of the core concepts. We finish this chapter by discussing the value of systems thinking and providing systems thinking examples. In Chapter 3 we develop a deeper understanding of systems and systems thinking by introducing systems components and their definitions. Throughout the rest of the book, we use these concepts and definitions to explore the theory and practice of systems thinking.

Introduction to Systems

The objective of this chapter is to introduce the reader to what a system is, its core definitions, and the value of systems thinking, and to provide some examples of how systems thinking could facilitate problem solving and innovation through real-life practical examples.

LEARNING OUTCOMES

Understand what a system is

Understand the core concepts of systems thinking, including:

open and closed systems

hard and soft systems

worldviews

complexity

emergence

self-organizing systems and organizational models

different kinds of systems problems

value of systems thinking

Understand how to think and talk about organizations using core systems concepts

2.1 What is a system?

All of us have come across the term system at some point in our lives and this term might create different associations for different people depending on their cultural and professional background. For instance, if you work in...

Understanding Systems

In a manufacturing company, you might think about a system as a production system or a supply chain system. The company itself is a system, comprising a group of people united by a common business goal. If you went to study abroad, you might start thinking about the educational system in your home country and how it compares with that of the host country, and this will be a very different type of system. While living in a new country, you might also pay closer attention to the cultural or political system of that country without necessarily realizing that these are also types of systems.

What is a system then?

A system is a collection of interacting parts/components/actors, in which the interactions result in system-level properties and behaviors not attributable to the sum of individual parts.

This idea is not new – it comes from ancient Greek philosophy, specifically that the whole is more than the sum of the parts. A car, a school, a city, a factory, or a tree are all systems. These systems are very different but they also have something in common, and that is a purpose. For instance, the car serves a purpose – the purpose of the users. The set of behaviors that a system performs is known as a function of the system. You may be wondering if there is anything that is not a system. The answer is yes. A conglomeration without any particular interconnections or any function is not a system. For example, sand scattered by the road is not a system because you can take away sand and it will remain the sand by the road, nothing more.

Let us think of four examples: a car, a human, a company, and a society. Take a moment to think about what is important about each of these terms. What are the first things that come to your mind?

If you start with the car, perhaps the first thing that comes to your mind is car parts, such as an engine, a battery, tyres, steering wheel, and windscreen. But you might also think about travel safety, road rules and regulations, the driver or other aspects of the system in which the car can operate. All these aspects indicate that you already start thinking in systems. Or perhaps you will think about travel, which is the purpose of the car as a system.

If you think about a human, perhaps the first things that comes to mind will be body parts and internal organs, such as legs, arms, a heart, a brain or kidneys. Perhaps you might also think about systems that comprise the human body, like the respiratory system or immune system.

 

you might consider human qualities, such as attitudes or character, or parts of the surrounding system in which the human exists, for instance a family.

A company is a more complex system than a human, and you will probably immediately consider a lot of aspects, such as products, services, customers, employees, managers, processes, business units, profits, equipment, buildings and so on. Perhaps you will also consider its structure and the aspects that govern the company, such as its strategy, policies, value and culture, or corporate image.

When thinking about a society, you will probably start with people, communities, culture, social norms, laws and regulations. As a system that is even more complex than a company, it will have a lot of aspects with complex relationships connecting them.

Obviously, these systems are very different from each other. However, even the same system can be seen differently by various people because they see different subsystems and have different viewpoints. For example, if several students are asked to draw an image of a university, some might draw a building in which they study. However, if they study online, their learning experience will be very different, and they might draw a laptop or an online environment instead. Figure 2.1 shows images of a university drawn by four different students during the first (the upper row) and the second (the lower row) year of the Covid-19 pandemic. We can see as the students started returning to campus, their image of the university also changed.

Figure 2.1 Images of a university drawn by different students

Others might focus on people and draw their peers, teachers and other staff they interact with. From this viewpoint, a university is not so much a physical system; rather, it is a system of people exchanging ideas. Others yet might think about a university as consisting of subsystems, such as schools, departments and research institutes, and existing in a wider system, the system of higher education, as well as interacting with other systems, such as industry and government.

Based on the above discussion we offer three different definitions of systems thinking as summarized in Table 2.1, none of which are perfect. Instead, they highlight complementary facets of systems thinking. One of the objectives of systems thinking then might be helping to create a shared image—a shared language and view of the system.

Table 2.1 Definitions of systems thinking

Source Definition

Checkland (1999: p. 3) The use of systems ideas in trying to understand the world’s complexity.

Randle and Stroink (2018: p. 646) A cognitive paradigm with which people come to perceive themselves and the world to be dynamic entities that display continually emerging patterns arising from the interactions among many interdependent connecting components.

Monat and Gannon (2015) A perspective (i.e. holistic as opposed to analytical thinking), a language (system's terminology and core concepts), and a set of tools (methods and frameworks for modelling and analysing systems).

2.2 Core concepts

In the previous section, we discussed that the same system can be seen in different ways depending on a viewpoint. Systems can be classified in different ways, and sometimes drawing such distinctions can be useful in helping to understand a system. In this section, we are going to discuss some of the core concepts that underpin systems thinking.

Open and closed systems

Systems can be open or closed. Open systems interact with the environment. They can change the environment and they can be changed by the environment.

environment. If we take the ocean as an example, it is a system comprising different elements, such as water and its chemical composition, marine flora and fauna, as well as products of human activities (such as plastic pollution). It interacts freely with the surrounding environment. On the surface of matter, such as evaporation of water from the surface that is then turned back to the ocean in the form of rain. Ocean currents signify the patterns of system behaviour and impact atmospheric temperature in different parts of the planet. The ocean also interacts with outer space through the atmosphere; in particular, sunlight can reach its surface and change its temperature, which will impact interactions between different parts of the marine ecosystem below the surface.

Closed systems, on the other hand, do not interact with the environment (Figure 2.2) and therefore they do not have any reaction behaviour to the environment. In fact, closed vs open system is not a binary state; rather systems exist in a spectrum that ranges from fully open systems at one end to fully closed systems at the other end. Most systems are open, but although closed systems are rare, they do exist. A good example of a closed system is a controlled experiment in a laboratory, such as virus research. In such a system, the virus cultured and grown in the lab must be part of a closed system. If it is open, even a little bit, the virus might escape into the environment.

In some cases, North Korea is used as an example of a closed system, which is not strictly true. You could argue North Korea is actually an open environment.

system because it has some interactions with its environment, that is some of the neighbouring countries, and has limited trade with the world outside its boundaries – it’s just that its economic and political systems are not as open as other countries.

From a business and management perspective all organizations are open systems, although the degree of their openness may vary significantly. For instance, a local grocery store is a more closed system than a large chain like Tesco, because it only interacts with a few suppliers and caters to the needs of the local community. Its key advantage is convenience. While Tesco has to be integrated into large international supply networks to procure a large variety of products and satisfy the needs of a diverse range of customers and understand the heterogeneous customer groups well to survive competition from other large chains.

Hard and soft systems

Some systems, for example machines, are engineered. They have high-integrity components and predictable behaviours. Their parts are connected through well-understood interaction patterns, and feedback is used to compensate for deviation by adjusting technical control parameters. These systems stem from an engineering paradigm and are hard systems. A car in itself is an example of a hard system.

Engineers naturally develop an ability to think in systems when studying and imagining hard systems, how different components in such systems behave, and how they interact with each other. However, they tend to find it difficult to replicate this experience with other types of systems. Other types of systems are composed of autonomous agents (normally people or animals). These are known as soft systems. For example, a school or a society is a soft system. These systems stem from a social paradigm. Soft system parts, autonomous agents, are characterized by high variety of change and unpredictable behaviours. They are connected through loosely defined dynamic webs of relationships, power structures, shared interests and values. Feedback is used to compensate for deviation through influence, motivations and persuasion.

In a way, all hard systems are embedded into soft systems. If we look at the car example, the car as a hard system exists within a broader soft system, in which the driver drives it and interacts with other drivers, pedestrians and local ecosystems (e.g. by emitting pollutants into the atmosphere). These...

interactions are governed by rules formalized to a varying degree. When designing a car, engineers will ensure that it complies with formalized regulations as well as study the conditions of its use, but they cannot always anticipate the ways in which the car might be used, and what kinds of new behaviours it might produce. For instance, when designing an autonomous vehicle, the designers might not be able to foresee the new behaviours from the pedestrians and other drivers who might want to try and test it to its limits or ‘play’ the system.

If we build upon the car example, the car as a hard system is very predictable. If you drive 100 Mini Coopers in the same day you will feel that they are all the same. This is because the components that make these cars are highly engineered with tight tolerances. Thus, engineers can predict, within certain parameters, how various components and subsystems interact with each other and how the cars they produce will drive. However, once you put the human component, i.e. the driver, into the car the system becomes a lot more unpredictable, because we cannot predict how the human component will interact with the car and how the car will behave in response to these interactions. Control systems, such as the highway code (rules of the road), have been produced to make these systems more predictable and increase road safety, but we still cannot predict how somebody who has had a restless night or an argument with their partner in the morning will behave when driving to work that morning. This is why insurance companies when insuring our cars place greater emphasis on the driver than they do on the cars.

From a business and management perspective, all organizations are soft systems that contain subsystems, some of which may be hard systems. For example, in a manufacturing company there are several different subsystems, such as human resource management, manufacturing and planning systems. The planning system will knit together a number of people from different functions such as sales, manufacturing, purchasing and finance who will use enterprise requirements planning (ERP) software to develop business, sales, manufacturing or procurement plans. In this example, the planning system is a soft system as it comprises autonomous human agents, but it also contains a hard subsystem, i.e. the ERP software.

Worldviews

In systems thinking, different people can look at or study the same system but see different things. In other words, they conceptualize the system differently.

To some extent, this is exemplified in the students’ sketches of the university (Figure 2.1). Usually people’s worldview, i.e. the way they see and interpret things around them, is influenced by parameters such as their education, upbringing, education, profession and life experiences. Usually, people develop mental models and assumptions about life, work, relationships and so on that shape their worldview over the course of their lives. For instance, what we read in the news is only one side of the story understood through the filters of our own upbringing. The Guardian’s 1986 ‘Points of view’ video, which you can find online (see video link 2.1 in the online resources on the Koganpage.com product page) is illustrative of how the same event can have diverse interpretations when seen from three different points of view.

If you ask a finance manager, an operations manager and a marketing manager about how their business works, they will probably give you different stories about the same business, although the three stories will most probably have a degree of consistency and overlap between them. That is because they are looking at the same business or system from different angles and have different worldviews that shape their viewpoint. A lot of soft systems are influenced by different viewpoints and mental models, and this is probably one of the main differences between hard and soft systems.

The worldview of someone also influences how the systems are conceptualized, modelled and analysed. Organizational routines or processes can be modelled as a flow chart, and this approach will be in line with the hard systems paradigm. At the same time, we can tell a story about what happens in the process, and this approach will be consistent with the soft systems paradigm. The flow chart will show the nuts and bolts of the process, but it will probably fail to capture what goes on in meetings, discussions over a water cooler, in emails and so on – i.e. human activities behind the flow-charted process. In the meantime, the story will capture much richer information about what really happens in the process. It reflects human activities that bring the process to life and make things happen.

Complexity and systems

When talking about complexity, we can think of it in terms of technical and perceived complexity. Technical complexity is an intrinsic property of a system. What makes systems complex are:

.the number of parts

.the number of connections

.dynamic relationships between parts

.non-linear interactions

.varying responses (predictability of response)

Perceived complexity is all about how stakeholders see a system. They may perceive a system to be more or less complex because they do not understand all the parts and/or the connections.

Systems can be complicated or complex. When we talk about the complexity of systems, we really need to understand the difference between the two concepts. The term complicated comes from the Latin words com and plic, meaning folded together. If we take an example of a car, we can deconstruct it, study each component and understand it, and then put it back together – the car will work in the same way, and by studying each component and subsystem we can understand how it works as a whole. Hard systems are normally complicated. Although they may have multiple parts, hard systems can be understood in parts, and the behaviour of these parts interacting with each other will be predictable based on the behaviour of each part.

In contrast, complex systems cannot be understood simply by studying individual parts of the system. If you think about a pianist, an office manager and a burglar, they are all composed of the same parts (such as heart, lungs, kidneys, brain) and subsystems (such as circulatory system, respiratory system, nervous system) but their behaviours are very different and so much more complicated than the sum of their body parts. There is the whole range of external factors such as education, upbringing, the environment they work in and so on that influence the behaviour of a human as a system. All these factors create unpredictable behaviour of how the components of a human being come together and create complex behavioural patterns.

The term complex comes from the Latin word complexus, which means plaited or woven together. In other words, the parts of a complex system are woven together. Therefore, the system can only be understood as a whole. Human beings, teams, organizations, supply chains, value-creating ecosystems are complex systems. There is a lot more to complexity than what we have said in this short section; however, the theme of complexity builds up throughout the book as you advance through the chapters.

Emergence

Emergence is one of the most fascinating features of our universe and it is a key concept of systems. Emergence refers to the properties of the system that...

are caused by the interactions and relationships between elements rather than by the elements themselves. We may observe these as simple things forming bigger, more complex things that have different properties from the sum of their parts. In other words, emergence is complexity arising from simplicity and it can be observed everywhere in the world around us. At some point you must have seen a flock of birds or shoal of fish making patterns in the sky or water. Flocks of birds are bound together by very simple rules, such as being within a wing's length of each other, which results in the emergence of the patterns we observe in the sky. If you search the internet for flock of birds videos you can see some examples of these emergent behaviours. In these systems there is no predetermined pattern, there is no emperor bird or fish that says let’s create this or that shape. The shapes emerge as a result of the individual actions of each bird/fish and the interactions between the birds/fish within a flock/shoal.

In a similar vein, if you have never seen geese in flight, you would never guess that they would form a 'V' shape. This pattern emerges because of the relationships between each bird, i.e. the components of the system. When a goose moves its wings through the air, the wing tips create vortices that make it easier for another goose to fly behind, because these vortices create additional lift. A trailing goose naturally moves to fly behind the wingtip of the leading goose, where it finds the greatest lift. When several birds are together, this results in that classic 'V' shape. A group of birds flying together in this way can fly 70 per cent further than a single bird.

Scientists also talk about emergence when they study the behaviour of physical things. For example, the shape of each snowflake is unique and it emerges as a result of the interaction of different water molecules experiencing different temperatures under different atmospheric conditions. Similarly, we can also observe emergent behaviour in wider society. The traffic in our cities or the culture of a particular tribe or country emerges as a result of the individual beliefs and behaviours of each driver and person, i.e. component of the system, and their interactions – and often these are difficult to predict. For example, if we think of slums in some of our large cities, no one in the city planning office said, ‘let’s create a slum here.’ These slums emerge through complex interactions between a number of forces that include large numbers of people living in dense spaces, local leaders competing for power, the economy of the country, poverty, traffic, pollution, health services, education, conflicts with the police, neglect by the state and so on all resulting in a unique sense of community, culture, music, expressions, sometimes even architectural beauty and currency, which feels very different to other parts of the same city or country. In these situations the outcome is unpredictable – it can generate corruption and violence as well as relative peace and a tourism economy.

We can find similar examples of emergent behaviour in organizational systems. For instance, in the absence of a clear mission or goals an organization’s strategy emerges over time because of actions taken and the pattern these actions create over time. At any point in time, we may be able to look back at various decisions and actions the organization followed to see the pattern that defines the organization’s journey. Emergence is also true even if an organization has a specific mission and goals. In many cases organizations define their goals and how they are going to achieve these, but as they exist as part of a larger economic system, things happen around them that make them respond to the changes in their operating environment. As a result, what they realize is often not the same as what they set out to do. In the strategy literature this is known as the intended strategy, i.e. what they set out to do, and the emergent or realized strategy, i.e. what they actually ended up doing.

Based on the above discussion the level of emergence can vary between weak and strong. Weak emergence means that the behaviour of the system can be explained, modelled or predicted (for example, engineered systems). Strong emergence means that the behaviour of the system is more difficult to explain, model or predict as is the case in soft systems. Again, these concepts of emergence will develop further as we progress through this book.

Self-organization systems and organizational models

When we think about organizations, we automatically think about hierarchy, although the degree of hierarchy can vary. In nature, whilst some species, such as apes, are organized hierarchically, other species resemble much more a network demonstrating emergent behaviours through simple rules. For example, when we look at a flock of birds, we can see order emerging from apparent chaos.

Such order is an example of a self-organizing system, whereby organization is decentralized and distributed over all the elements of the system, i.e. individual birds in the flock. In this system no single bird sets the pattern or pre-defines the behaviour of the flock, nor is their behaviour managed by external forces, although it can be altered in response to external events, such as an approaching bird of prey. Instead, the system is self-managed or self-organized or self-organized.

This type of system is therefore significantly different from a self-organized. This type of system is therefore significantly different from a centrally managed or indeed a hierarchical system; it is essentially a network that self-organizes (Figure 2.3). We can describe self-organization in decentralized systems as a process where some form of overall order arises from local interactions between parts of an initially disordered system. The system somehow develops simple rules that each element obeys. As a consequence, complex and unpredictable behaviours emerge.

Hierarchies and central control systems are generally associated with higher levels of intelligence, but in nature, networks can function equally well. In fact, from the organizational perspective, the more self-organized the system is, the more resilient it is. If in a centralized system something happens to the central unit, the whole organization can stop functioning. Similarly, hierarchies, although a little bit more resilient, have multiple points of failure. If one of the nodes in one of the branches fails it would take out the whole of that branch, affecting the performance of the system. In networks there are no concentrations of points of failure, and therefore failure of any single unit will not have a significant impact on the overall functioning of the system; consequently, as a system a network is far more resilient.

From a business and management perspective the degree of self-organization or self-management in a system has become an important consideration, as it helps us to better understand the system and its behaviour. In most economies, industry sectors (such as textiles, engineering, food and drink, pharmaceutical) are not managed by a central organization. Each company is an autonomous part of the wider system (i.e. a sector) which operates within a given set of rules (legal, regulatory, moral). Thus we can consider these as self-organizing systems. If we wish to change the behaviour of a self-organizing system, we usually have to change the governing rules of the system. For example, in the transport sector if we wish to increase the uptake of electric vehicles, we create new rules that incentivize the supply and use of electric vehicles and disincentivize the supply and use of vehicles burning fossil fuels.

At an organizational level, however, most organizations have a defined management structure, and thus they are not considered as self-organizing systems. However, we do occasionally see elements of self-organization within organizations. Conceptually, a self-managing work team is an example of a self-organizing system, but in practice they are rarely completely autonomous and often they have internal management structures.

Continuing in this vein, holacracy is a form of organization that distributes authority and decision making through a network of self-organized teams that are bound together with a shared purpose and common set of goals and rules. The term has been derived from the word holos, which means ‘whole’ in Greek, and describes autonomous, self-organizing units that are dependent on the greater whole of which they are part, essentially a bit like a school of fish, a flock of birds or a company in an ecosystem. In this book we do not intend to go into lengthy debates about organizational structures and governance models, but it would suffice to say that in terms of organizational structure, holacracy is a form of self-organizing network.

In the literature it is also common to come across terminologies such as autocracy (central control or command and control), bureaucracy (hierarchical control) and netocracy (network-based self-management) that describe different governance philosophies and models.

Systems problems

The key value of systems thinking is in helping us see complex systems as a whole, and understand their behaviour and the underlying problems so that we can develop effective solutions to systems problems. Systems problems can be broadly classified into tame, messy, and wicked problems.

Tame problems can be defined and solved. They have a correct solution, and it can be optimized. Most engineering problems are tame problems. An example of such problems is a location problem in logistics that requires an organization to identify the most optimal location for a warehouse to minimize transportation costs for delivery operations. To solve this problem, scientists and engineers can develop optimization algorithms that can work out the optimal location for a warehouse.

Messy problems are the most common type of problem. Instead, often we are looking for a ‘good enough’ solution. This happens in most real-world problems, whereby the solutions require compromises. An example can be building a wind farm that might blend in with the natural landscape that local residents value. In such a situation, the proposed problem, building a wind farm, might benefit some stakeholders, e.g., the energy supplier and residents with renewable energy, but disadvantage others, e.g., the tourism industry. Solving this problem requires negotiations and compromises, which might eventually benefit everyone to an extent.

Wicked problems always involve a loser and a winner. These are problems that cannot be solved but must nevertheless be managed. Climate change is an example of such a wicked problem. For instance, we know that if we want to continue supporting economic growth, it will have a more significant environmental impact, but reducing economic growth will have a significant negative impact on many groups of people. There is no ideal solution; instead, both impacts will have to be managed. In relation to climate change, a company might be faced with a wicked problem of understanding its impact on operations and deciding how to prepare for its adverse effects. This might require decisions that might prove unpopular in the short term but will ensure long-term sustainability and survival of the business.

2.3 Value of systems thinking

To understand the real value of systems thinking, we need to recognize that nothing in this world exists in isolation and that everything is connected to something else. Everything is affected by something and potentially affects something else. With systems thinking, one can begin to understand, explain, and predict why complex systems such as organizations, people, and societies behave the way they do.

We saw this with the financial crisis in 2008–2009, when one policy in one sector of the economy had a huge impact on the economies of most countries around the world. We have also seen it happening during the Covid-19 pandemic. Disruptions in specific parts of supply chains had a cascading effect, disrupting the whole supply chain. As a result, people’s lives were disrupted in all sorts of ways; for example, the UK ran short of toilet paper due to panic buying, and housebuilders ran out of construction materials and were not able to complete homes for as long as nine months. These disruptions were not predicted, and the supply chain was not prepared to quickly adjust to these changes.

These examples demonstrate the connectedness and unpredictability of the world we live in today. Therefore, when we make changes to our organizations or to our life, we need to think about how that might impact other parts of the organization or the wider system.

With systems thinking, we can begin to understand and explain why organizations behave the way they do and start predicting how they might behave in the future. The models and methods covered in Part 2 of this book will equip you with tools to help you understand the systems and start modeling them to explain their patterns of behavior. Parts 3 and 4 of the book will discuss further how we can predict the behavior of a system by simulating system models, particularly when dealing with complex systems, and how we can start modeling systems that do not yet exist. These tools will help us to gain answers to various strategic questions. For example, how will supply chains perform in 5, 10, or 40 years with the impact of climate change? Or what could a new industrial system look like in response to future trends and constraints? Then we can start thinking about the interventions that allow us to change the system’s behavior.

Systems thinking and analysis is a life skill. It will enhance the problem analysis and solutions capability of people from all walks of life irrespective of where they live, their level of seniority and the sector they work in. It is a skill that is important for working and living. Without systems thinking and accompanying tools and techniques, it would be near impossible to predict the behaviour of complex systems, particularly human activity and societal systems such as organizations, supply chains, the education system, innovation systems, healthcare systems and so on.

CASE STUDY: A systems thinking case study

This case study focuses on the supply system between an international chemical manufacturing company producing dynamite, and quarries who buy sticks of dynamite to blast rockfaces to make gravel.

The manufacturing company produces dynamite from two inert liquids by mixing them together to create an explosive. The explosive liquid has to be stored somewhere safely before it is plasticized by adding plasticizers. The plasticizing process resembles that of making a dough. The plasticized explosive liquid becomes dynamite. The dynamite needs to be stored somewhere safely until it is transported and delivered to the customers, i.e., the quarries.

Naturally, when we look at business processes, we ask ourselves a question: how do we improve performance? The most obvious solutions would be to improve the on-time delivery performance, reduce the cost, or perhaps improve productivity in different steps of the process. However, these solutions will only result in incremental improvements to this system. If, on the other hand, we take a wider view of the system, we may be able to see other kinds of improvement opportunities. 

The first step in this journey might be asking the question of what the customer does with this dynamite. This question expands the boundaries of the system. If we look at the wider picture, then we will see that the dynamite is transported to a quarry, the quarry receives the dynamite and stores it, then they employ qualified people to administer the dynamite on the rock face. They drill holes on the rock face, then they place correct amounts of dynamite inside the holes, wire it together, and finally press a button to perform the explosion. The explosion turns the rockface to large pieces of rock, i.e., rock on the ground. After the explosion, the quarry takes large pieces of rock scattered on the ground and processes this rock into smaller pieces of gravel using crushing machines. This gravel is later used in construction to make roads, aggregate for concrete, gardens, etc. In this supply system, the quarry creates value by processing the rock using the crushing machines, and this is where the quarry has the majority of its investment.

When we look at this extended system, we can recognize a lot of non-value-adding activities. A lot of the steps in the process involve storing and transporting hazardous compounds, which requires a lot of attention to safety and security, where explosives might attract unwanted criminal attention. The safety and security requirements not only increase costs, but they also slow the system down. Thinking about it, plasticizing is only there to make the explosive transportable, so how can we remove unessential steps, simplify the supply system, and improve its performance?

The only steps that add value are rock-processing activities. When we come to this realization, the question that should be asked instead is: how do we get the explosive to the rock face to get ‘the rock on the ground?’ When the manufacturing company asked themselves this question and recognized the objective of the wider system, they came up with the Mobile Manufacturing Unit (MMU) solution, which eventually replaced all other manufacturing facilities. The MMU is a truck with two tanks for storing the two inert liquids separately and safely. With this approach, all the steps between storing the two inert liquids and providing rock on the ground are replaced with the MMU.

For the customer, the process has also changed. Now all they need to do is call the company and say how many tonnes of rock they need and how they want the rock distributed. Then the MMU will do the calculations, drill the holes, pump the two liquids into the holes, and therefore make the explosive right inside the holes. They will then wire it up, perform the explosion, and finally deliver the ‘rock on the ground’ for the customer to process it. This change, which is illustrated in Figure 2.4, means that the quarries just need to focus on their core business, i.e., processing the rock on the ground.

What this example demonstrates is that if we look at only one part of a system and ask how to improve the system, we get one set of answers. But this part does not exist in isolation. It is connected to the wider world through its customers, suppliers, and other stakeholders. When we expand the boundaries of the system and look at the wider system, e.g., by including the customer in these boundaries and looking at what the customer does with our product, we get a different solution.

For the manufacturing company, this was a significant change in the business model. They changed their business model from manufacturing dynamite to providing rock on the ground service. In other words, they transformed from a manufacturing company to a service provider.

This is an example of the power of systems thinking; it helps us think about the wider system and develop more meaningful ways of changing the system for the benefit of everyone.

Reflective questions

In the above case study, we have demonstrated how by changing the boundaries and taking a wider systems perspective the company was able to find a different solution that made the whole system significantly more effective for both organizations. Try to reflect on other types of stakeholders that might be involved in the system. Can you think of any emergent behavior that this new type of relationship might lead to?

If you were to describe the viewpoint of the company before and after the change, how would you do it? In your opinion, has the viewpoint of the gravel manufacturers changed with the introduction of the new business model by their supplier?

Reflect on the type of problem that the new business model has helped to solve. What other types of problems might it have created?

2.4 Summary

In this chapter, we have introduced the definition and characteristics of a system, discussed different types of system classifications (e.g., open vs. closed systems or hard vs. soft systems), and introduced some of the key concepts such as emergence and self-organization. We then discussed the types of problems that systems thinking addresses, the value of systems thinking, and provided an example of how systems thinking can help facilitate problem solving and innovation.

REFLECTIVE EXERCISE

Emergence – In this chapter, we defined emergence as the behavioral properties of the system that are caused by the interactions and relationships between elements rather than by the elements themselves. Reflecting on your experiences, think of situations where you experienced emergence. For example, have you ever been in a situation where before you went into a meeting you had   talked to a few people and you had a good idea as to how the meeting was going to go, but it did not go quite as you expected? Think about what caused this unexpected outcome: was it just one person saying something unexpected that ended up changing the course of the discussion? It is often small, unexpected occurrences or interventions that create unexpected outcomes. Reflecting on your experiences, can you think about what these small, unexpected interventions may have been that resulted in the unexpected outcomes?

Management Structure

Think about what management structures you have experienced. As a student, you may have worked for a small corner shop stacking shelves where the owner/manager was the central controller who told everyone what to do. Did you work in an organization that had a bureaucratic hierarchical structure? Have you experienced a self-organizing netocratic organization, even such as a group of friends with a common interest where you all decide to do something fun at the weekends? Think about these different experiences and what worked well and what did not work so well in different contexts. Could self-organization work as well or better in the organization where you may have experienced central control? What would be the challenges?

TEAM EXERCISE: REFLECTIONS ON AN ORGANIZATION

The purpose of this exercise is to demonstrate that when different people conceptualize the same organization, everyone’s conceptualization may be different. Before you start the exercise, you should identify an organization everyone is familiar with. This could be a well-known local fast-food restaurant or even the participants’ university or school. If everyone is from the same organization, then ask each member to draw an image of their organization.

Ask the participants to draw a quick sketch/image of the organization in no more than three minutes. It is important that they do not overthink this; they should draw the first image that comes to their mind. Then ask each participant to explain the image to others. For larger groups, to save time, this can be done in smaller groups of three or four people.

While explaining their pictures, encourage the participants to tell a story behind the image rather than simply describe different components. Note the differences between the stories. You might notice that different people tell the same story using different images and words. Some will take a much more hard systems approach (e.g., products, manufacturing equipment, information systems) and others will focus more on the people side of the organization. Reflect on the worldviews emerging from these stories.

If the exercise has been conducted with people working in the same organization, this exercise should also help participants see each other’s worldviews, which may help to explain some of the differences and even tensions in the organization.

References

Checkland PB (1999) Systems Thinking, Systems Practice, Wiley.

Monat, JP and Gannon, TF (2015) What is systems thinking? A review of selected literature plus recommendations, American Journal of Systems Science, 4 (1), pp 11–26.

Randle, JM and Stroink, ML (2018) The development and initial validation of the paradigm of systems thinking, Systems Research and Behavioral Science, 35 (6), pp 645–57.

Further Reading

Bernstein, E, Bunch, J, Canner, N and Lee, M (2016) Beyond the Holacracy Hype, Harvard Business Review, Jul–Aug, https://hbr.org/2016/07/beyond-the-holacracy-hype (archived at https://perma.cc/RB2F-LZLC).