a systems approach to problem solving

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Taking a systems thinking approach to problem solving

Systems thinking is an approach that considers a situation or problem holistically and as part of an overall system which is more than the sum of its parts. Taking the big picture perspective, and looking more deeply at underpinnings, systems thinking seeks and offers long-term and fundamental solutions rather than quick fixes and surface change.

Whether in environmental science, organizational change management, or geopolitics, some problems are so large, so complicated and so enduring that it’s hard to know where to begin when seeking a solution.

A systems thinking approach might be the ideal way to tackle essentially systemic problems. Our article sets out the basic concepts and ideas.

What is systems thinking?

Systems thinking is an approach that views an issue or problem as part of a wider, dynamic system. It entails accepting the system as an entity in its own right rather than just the sum of its parts, as well as understanding how individual elements of a system influence one another.

When we consider the concepts of a car, or a human being we are using a systems thinking perspective. A car is not just a collection of nuts, bolts, panels and wheels. A human being is not simply an assembly of bones, muscles, organs and blood.

In a systems thinking approach, as well as the specific issue or problem in question, you must also look at its wider place in an overall system, the nature of relationships between that issue and other elements of the system, and the tensions and synergies that arise from the various elements and their interactions.

The history of systems thinking is itself innately complex, with roots in many important disciplines of the 20th century including biology, computing and data science. As a discipline, systems thinking is still evolving today.

How can systems thinking be applied to problem solving?

A systems thinking approach to problem solving recognizes the problem as part of a wider system and addresses the whole system in any solution rather than just the problem area.

A popular way of applying a systems thinking lens is to examine the issue from multiple perspectives, zooming out from single and visible elements to the bigger and broader picture (e.g. via considering individual events, and then the patterns, structures and mental models which give rise to them).

Systems thinking is best applied in fields where problems and solutions are both high in complexity. There are a number of characteristics that can make an issue particularly compatible with a systems thinking approach:

• The issue has high impact for many people.
• The issue is long-term or chronic rather than a one-off incident.
• There is no obvious solution or answer to the issue and previous attempts to solve it have failed.
• We have a good knowledge of the issue’s environment and history through which we can sensibly place it in a systems context.

If your problem does not have most of these characteristics, systems thinking analysis may not work well in solving it.

Areas where systems thinking is often useful include health, climate change, urban planning, transport or ecology.

What is an example of a systems thinking approach to problem solving?

A tool called the iceberg mode l can be useful in learning to examine issues from a systems thinking perspective. This model frames an issue as an iceberg floating in a wider sea, with one small section above the water and three large sections unseen below.

The very tip of the iceberg, visible above the waterline, shows discrete events or occurrences which are easily seen and understood. For example, successive failures of a political party to win national elections.

Beneath the waterline and invisible, lie deeper and longer-term trends or patterns of behavior. In our example this might be internal fighting in the political party which overshadows and obstructs its public campaigning and weakens its leadership and reputation.

Even deeper under the water we can find underlying causes and supporting structures which underpin the patterns and trends.

For our failing political party, this could mean party rules and processes which encourage internal conflict and division rather than resolving them, and put off the best potential candidates from standing for the party in elections.

The electoral system in the country may also be problematic or unfair, making the party so fearful and defensive against losing its remaining support base, that it has no energy or cash to campaign on a more positive agenda and win new voters.

Mental models

At the very base of the iceberg, deepest under the water, lie the mental models that allow the rest of the iceberg to persist in this shape. These include the assumptions, attitudes, beliefs and motivations which drive the behaviors, patterns and events seen further up in the iceberg.

In this case, this could be the belief amongst senior party figures that they’ve won in the past and can therefore win again someday by repeating old campaigns. Or a widespread attitude amongst activists in all party wings that with the right party leader, all internal problems will melt away and voter preferences will turn overnight.

When is a systems thinking approach not helpful?

If you are looking for a quick answer to a simple question, or an immediate response to a single event, then systems thinking may overcomplicate the process of solving your problem and provide you with more information than is helpful, and in slower time than you need.

For example, if a volcano erupts and the local area needs to be immediately evacuated, applying a thorough systems thinking approach to life in the vicinity of an active volcano is unlikely to result in a more efficient crisis response or save more lives. After the event, systems thinking might be more constructive when considering town rebuilding, local logistics and transport links.

In general, if a problem is short-term, narrow and/or linear, systems thinking may not be the right model of thinking to use.

A final word…

The biggest problems in the real world are rarely simple in nature and expecting a quick and simple solution to something like climate change or cancer would be naive.

If you’d like to know more about applying systems thinking in real life there are many online resources, books and courses you can access, including in specific fields (e.g. FutureLearn’s course on Understanding Systems Thinking in Healthcare ).

Whether you think of it as zooming out to the big picture while retaining a focus on the small, or looking deeper under the water at the full shape of the iceberg, systems thinking can be a powerful tool for finding solutions that recognize the interactions and interdependence of individual elements in the real world.

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What’s systems thinking? The secret to a future-minded organization

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I’ve been working on widening my aperture. What does that mean? In photography, zooming out. Seeing the forest for the trees.

As a writer, I find that I often get bogged down in the details. Sometimes, I look too closely at a topic or an idea without considering the complexities, relationships, and implications. 

It’s easy to see things when we’re close to them. But it takes a concerted effort to step back and look at the bigger picture. It requires a different type of mindset, strategic thinking, and perspective on problem-solving .  

We probably can all think of people who approach the world as system thinkers. You probably can name a few off the top of your head: Ruth Bader Ginsburg, Steve Jobs, Stacey Abrams, Bill Gates, Malala Yousafzai, Barack Obama, and many more.

They’re big-picture thinkers , dreamers, and strategists. They all share curiosity, courage , and the willingness to challenge the status quo. They see the problem at hand in a network of complex systems, and they aren’t afraid to prod at the larger ecosystem. Systems thinking might sound like a clunky, corporate jargon phrase. And in some ways, by definition, it is complex. But at its heart, systems thinking is about seeing things through a wide lens, recognizing how interconnected we are, and acting with empathy and innovation.

Actions have consequences, not always the ones intended. While it can be about solving wicked problems, systems thinking can also be about getting stuff done in ways that are beneficial to the whole organization, not just your little piece of it. A system can be a company, a school, a community, a region, or even a family.

In the context of today’s world of work, systems thinking can help you to be more strategic and better prepared for what the future has in store. Applying systems thinking to our current climate can help us look ahead with a more strategic lens. 

Especially when things are constantly changing — and uncertainty looms overhead — systems thinking helps organizations be better prepared to solve complex problems. Let’s break down what systems thinking is. We’ll also talk about what it takes to become a systems thinker — and how applying systems thinking can help your organization thrive. 

What is systems thinking?

Before we go any further, let’s pause to understand what we mean by systems thinking . 

Systems thinking is the ability that an individual or organization has to solve tough problems. With systems thinking, individuals use strategic, big-picture thinking to make sense of a complex system. 

For example, at BetterUp we talk about how optimizing for the company typically means sub-optimizing for individual teams. But it holds true for any large organization.

Without systems thinking, a team might set its goals very narrowly and pursue them. Sometimes, those pursuits result in strategies that are detrimental to another team or the bigger company objectives.

Companies that want to be more than the sum of their parts need managers who can think systemically and with enough transparency that people can understand the system.

Systems thinking is a holistic approach to problem-solving. It’s a way of looking at how systems work, what that system’s perspective is, and how to better improve system behaviors. 

The systems thinking methodology isn’t necessarily formulaic. It takes some understanding of key concepts to be able to take a systems approach to today’s most challenging problems. 

Systems thinking in leadership 

As we mentioned, many of today’s most notable strategic leaders lean on their systems thinking skills to drive change. It requires a deep understanding of mental models with the goal of improving them to optimize organizational performance . And while you might not know it, many leaders have applied system thinking tools to help come to new conclusions. 

Systems thinking in leadership, however, isn’t a one-size-fits-all approach. Every problem is different with its own set of system dynamics. Let’s break down what some of this could look like in leadership. 

• A future-mindedness. At BetterUp, we’ve studied future-minded leaders . It’s the idea that a leader looks ahead with a sense of pragmatism and optimism. Leaders who use the future-minded lens say they spend 147% more time planning in their lives and 159% more time planning in their work than those with low future-minded leadership skills. The result of all this planning? Future-minded leaders have higher-performing teams. increased agility, team engagement, innovation, risk-taking, performance, and resilience.  

• Strategy and planning. As you could’ve guessed, strategic thinking and strategic planning are big components of adopting a systems perspective. Leaders are able to zoom out to see the whole system, then zoom in to see how the system works. 
• A growth mindset. If we really strip down systems thinking, it’s about problem-solving. This means leaders don’t know everything. They need to learn — and be willing to learn — new things. Leaders who adopt a growth mindset are better equipped to see how the system works because of this perspective. 
• The willingness to be wrong. We’ve probably all had managers who are unwilling to be wrong. Even if the data and science back it up, there’s some excuse as to why their theory, strategy, or process will still work. It’s a fixed mindset that won’t let go. But with system thinkers in leadership, they’re willing to be wrong. They can see when a systems theory isn’t working. And they embrace that vulnerability of admitting they need to re-think what they originally thought. 

“We learn more from people who challenge our thought process than those who affirm our conclusions. Strong leaders engage their critics and make themselves stronger. Weak leaders silence their critics and make themselves weaker. This reaction isn’t limited to people in power. Although we might be on board with the principle, in practice we often miss out on the value of a challenge network.”  Adam Grant, BetterUp Science Board Member, organizational psychologist, author, Think Again

What are examples of systems thinking?

To better understand systems thinking, let’s look at these three examples. Each example demonstrates the innovation that arises when you see the potential for a whole new board game rather than just swapping out one piece of the puzzle.

• Smartphones. I grew up in a house where phones were plugged into the wall and computers took over phone lines. When I wanted to call a friend, I dragged the landline — cord still plugged in — into my bedroom. If I wanted to look something up on the internet, I had to make sure no one in my household was using the phone. Why? Well, because the internet required dialed-in access to the phone line. Fast forward a couple of decades and now, we have tiny, little computers that fit into our pockets. Smartphones allow you to access the internet virtually everywhere you go, so long as there’s a signal or a WiFi log-in. Smartphones didn’t come about just to change where and how we could make a phone call. They evolved because system thinkers like Steve Jobs anticipated how connectivity could change the bigger system of how we consume and interact. Systems thinkers see what could be instead of what is.
• Cryptocurrency. When is the last time you had cash in your wallet? If you’re like me, you rarely carry any cash anymore. Though just twenty years ago, I made sure I had at least $10 in cash with me at all times. But soon, the world evolved with plastic cards that somehow, became much more valuable than any number of bills you could carry in your wallet. Debit and credit cards replaced weekly bank withdrawals. But system thinkers took currency one step further: crypto . Money now moves in networks that securely transfer different types of digital property over the Internet. This technology reimagines how the world does business, but it also has implications for larger monetary, regulatory, and political systems.
• Renewable energy. With climate change , we’re living on the brink of irreversible damage. With global temperatures rising faster than before, system thinkers had to find a way to power the world that doesn’t harm the planet.  Enter: renewable energy. Renewable energy sources (like solar and wind power) have reimagined how we run businesses, travel, and even produce goods. This system-of-systems approach is helping to shape a low-carbon economy . According to Deloitte, slowing the accelerating pace at which the climate crisis is progressing requires overhauling how systems work. 

Push a little further on these examples and you might also see that each also shows the failure to fully imagine the impact on the broader systems they touch.

Smartphones and crypto-currency each have environmental effects, increasing demand for energy and rare materials. Shifts in demand can create new supply chains and new companies as well as shortages and power imbalances. Systems thinking is recognizing that there are no simple answers.

Complex adaptive systems are just that: adaptive. They’re dynamic systems that hinge on feedback loops, innovation, and collaboration . And it’s with systems thinking that we’re able to evolve and innovate to find better solutions to today’s modern challenges. 

6 important concepts of systems thinking

For your organization, adopting concepts of systems thinking can help your business stay a step ahead. Especially in a fast-changing world, it’s critical that organizations stay agile and strategic to stay relevant. Here are six important concepts of systems thinking to help your organization stay resilient, agile, and relevant for the future. 

1. Systems mapping 

To understand how to solve a problem, you need to understand the ecosystems in which the problem lives. This is called systems mapping: getting to know the systems where a problem lives to better take it apart. 

Once you’ve mapped out the systems to help solve your problem, you can do some systems modeling to help understand how they’re connected. Which leads us to … 

2. Interconnectedness 

Interconnectedness. If we know anything about the world, it’s much smaller than we think. And after you’ve mapped out the systems for the problem you’re trying to solve, it’s time to figure out how the systems are connected. 

Sometimes, it may seem nonlinear or non-consequential. But if you dig deep enough, you’ll likely find some fibers connected between specific systems. 

For example, let’s use the pandemic. COVID-19 illuminated that our systems are more connected than we think. The impacts of COVID-19 disproportionately impacted communities of color and those of lower socioeconomic status. On its face, it might not have been readily apparent that a public health crisis would bleed into a different system, our economy. 

3. Synthesis 

This concept is synthesizing. Essentially, it’s making sense of things in the context of the problem you’re trying to solve. Opposite to analysis, synthesis usually is when you combine ideas or things to create something new. 

4. Emergence 

Let’s look at the solar system. We know that the solar system is a large, abstract, and complex system. It’s made up of planets, stars, galaxies, and many other things that we likely have yet to discover. 

But that’s the point of emergence: larger things emerge from smaller things. And when it comes to figuring out how synthesizing (or how you’re putting together different parts), emergence is critical. 

5. Feedback loops 

Feedback is critical to understanding if something is working. More importantly, feedback helps us understand when things aren’t working. 

If you’re adopting systems thinking in your organization, consider how you’re implementing feedback loops into the process. 

For example, let’s say you’re rolling out a new performance management software. Your HR teams are working with managers across the business to adequately train folks on how to use the platform. However, you realize that some managers are missing key milestones, like annual performance reviews . 

You set up some focus groups and office hours with your managers. In these sessions, you learn that your managers are missing out on performance review milestones in the system because they don’t know how to navigate the software. After gathering feedback , you realize that your organization requires more support. 

6. Causality 

Causality is the idea that there’s a cause and effect. It’s pretty simple: your actions impact the outcome. And so when you’re looking at a part of the system to solve, it’s important to test the cause and effect pieces of your systems. 

Let’s go back to our example from above. Because you’ve implemented regular feedback checkpoints within manager office hours, your HR team can better adjust their communication strategy. With help from the internal communication team, your HR team put together some guides on how to best use the software. This helped improve the number of “missed” performance reviews by 30%. 

How to apply systems thinking to the workplace

If you’re ready to apply systems thinking to the workplace, here are four things to keep in mind. 

Practice future-minded thinking 

Future-mindedness can keep organizations prepared for the future. Of course, we know the future is unknown. Especially now, there’s plenty of uncertainty and change looming. 

But with future-mindedness, your organization can be better equipped for what the future holds. Training your leaders to build their future-minded skills can help to keep your organization agile, resilient, and relevant for whatever the future holds. With future-mindedness , the impact speaks for itself: 

• Individual performance and well-being increases 
• Team performance increases with more agility, resilience, and risk-taking 
• Teams are more innovative, creative, and collaborative 
• Employee retention increases by 33% 

Promote a growth mindset 

Organizations, now more than ever, need to adopt a growth mindset. Learning is a lifelong journey for any person. Why wouldn’t organizations adopt the same sort of mindset? 

Think about how you can cultivate a growth mindset within your workplace. For example, how are you encouraging professional development ? Are you promoting from within and encouraging career mobility ? In what ways are you creating career advancement opportunities? Do your employees invest in upskilling or reskilling? 

Create space for feedback 

The success of any organization hinges on the ability to provide — and receive — feedback . At BetterUp, we see feedback as a gift. It’s a way to identify what’s working. But more importantly, it’s how we evolve and grow. 

Are you creating spaces for feedback? How are you keeping a pulse on your employees’ engagement ? Are you encouraging upward feedback or 360-degree feedback ? 

Use coaching 

We all need guidance. Especially when we’re tasked with solving some of the toughest problems, it helps to have an outside perspective. 

That’s where coaching comes in. With BetterUp, you can pair your employees with personalized support to help crack tough problems. A coach can help your employees tap into parts of themselves that they didn’t know existed. In turn, it will help improve your organizational effectiveness . 

Try BetterUp. Together, we can build a future better equipped to solve tomorrow’s problems.

Madeline Miles

Madeline is a writer, communicator, and storyteller who is passionate about using words to help drive positive change. She holds a bachelor's in English Creative Writing and Communication Studies and lives in Denver, Colorado. In her spare time, she's usually somewhere outside (preferably in the mountains) — and enjoys poetry and fiction.

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Systems Thinking: A Deep Dive Into The Framework To Successfully Solve Complex Problems

Systems thinking, also known as systems analysis or system dynamics, looks at the world that emphasizes how things work together and interact. It’s an approach to understanding complex problems by breaking them down into their constituent parts so you can analyze them in terms of cause-and-effect relationships. This detailing helps us understand why something happens rather than just what it looks like on the surface. This article will explore the critical concepts around systems thinking.

Professor J. W. Forrester developed the concept of Systems thinking in 1956. Researchers have defined complexity as “the property of being composed of many interrelated elements.” Systems thinking is not new; philosophers have been using this concept since ancient times. But until recently, most people did not realize that their everyday lives were governed by rules similar to those found in natural phenomena. However, scientists have begun to recognize that living organisms also exhibit emergent properties and self-organization in recent years. These discoveries suggest that there may exist universal principles governing life on Earth.

Table of Contents

How Does Systems Thinking Differ from Critical Thinking?

Systems thinking is a way of looking at the world that emphasizes how things are connected. It’s about seeing patterns and relationships, not just in individual parts but also across systems as a whole. This approach can be applied to any situation or problem you encounter—from personal life to business management to global politics.

Critical thinking is an entirely different type of mindset. Instead of viewing problems through the lens of interconnectedness, it focuses on identifying what needs to change and then figuring out ways to make those changes happen. In this sense, critical thinking is more like detective work than systems thinking: You start with a hypothesis and then try to prove whether or not your theory is correct by testing it against reality.

Why are systems thinking important?

Systems thinkers are those who understand the world as a complex adaptive system. They see that everything in nature, including human society and organizations, has dynamics that one cannot comprehend by studying only one part or even looking at details from different perspectives. Instead, they look for patterns across all aspects of reality to know how things work together. This approach leads them to ask questions such as: How do we create change? What makes something successful? Why do some organizations fail while others thrive? And what can we learn about ourselves when we study other species?

What are Complex Systems?

Complex systems can be defined as a set of interacting elements that produce emergent properties. The American mathematician and philosopher John von Neumann coined the term complex system in his book “Theory of Self-Reproducing Automata.” He used it to describe self-reproducing machines or automatons. In this context, he meant an entity that can reproduce itself from its parts without any external intervention. This definition has been widely adopted since then. It is also known as autopoiesis, self-organization, self-regulation, self-maintenance, or self-production.

A simple example would be a living cell where each component interacts with other elements. These interactions lead to the production of new proteins and DNA molecules. Thus the whole process leads to the reproduction of the original molecule.

What Are Complex Systems In Business?

Complex systems are a new way of looking at the world. They’re not just about understanding how things work, but also why they do what they do and how to make them better.

The term “complex system” was coined by John P. Kotter in his book Leading Change. He defined it as: “a set of people or organizations that interact with each other more than one would expect from chance alone.”

The idea is simple – if you look closely enough at any group of people interacting together, patterns will emerge to help us understand their behavior. This insight has been used for centuries in psychology, sociology, anthropology, economics, and politics. But until recently, these insights have only applied to small groups of individuals.

What Are Adaptive Systems?

Adaptive systems are complex, dynamic, and self-organizing. They can be viewed as a collection of interacting components that continuously adapt to changing conditions in their environment. The term “adaptation” is used in the sense of an ongoing process rather than a one-time event or outcome. Adaptive systems have no fixed state, but instead, they continually change over time. In this way, they resemble living organisms that also constantly evolve through adaptation.

Adaptive systems are a way of looking at the world. You can use them to describe any system changing and adapting to its environment or apply to business processes. The term adaptive was coined by John Todd, who defined it as “a process which changes itself according to external conditions.” He also said: “The purpose of an adaptive system is not to achieve some pre-determined goal but rather to maintain stability within the context of change.” This definition has been widely adopted since then.

What are the characteristics of systems thinking?

Systems Thinking is a way to look at the world. It’s not just about looking for problems but also finding solutions and making things better. Systems Thinking helps us understand how to make our lives more sustainable by changing ourselves and our environment.

Characteristics of the Systems Thinking approach include;

1) A focus on understanding complex social-ecological interactions in their natural context. This understanding means that it considers all aspects of an issue or problem – from human behavior to physical processes, including feedback loops between these two levels.

2) An emphasis on learning through experience rather than knowledge alone. The goal is to understand what works best when applied to specific situations.

3) Emphasis on action over-analysis. We need to act now to solve current issues and create new opportunities. Analysis should be used to inform decisions, not dictate them.

4) Focus on creating positive change. Change happens if people want it to happen. If you don’t like something, then do something about it!

5) Use multiple perspectives. Each perspective provides different insights into the same situation. However, when combined, they give a fuller picture.

6) Look beyond the obvious. There may be other factors involved which you may have overlooked. 

7) Think globally, act locally. Our actions affect everyone around us. Therefore, we must think globally before acting locally.

How do you use System thinking?

Systems Thinking is a way of looking at the world. It’s not just about seeing things as they are, but also how we can change them to be better for everyone involved. Systems Thinking helps us understand that everything in our lives impacts other parts of life and vice versa. We need to think more holistically when solving problems because there isn’t always one solution or many solutions.

Here are the steps you can use to adopt systems thinking;

1) Understand what system means: A system works together with others so that all its components work towards achieving some goal. For example, if I have a car, my engine will run by itself without pushing buttons. But, if I want to start the car, I press the button, and the starter motor turns over the engine. The same thing happens inside people – their heartbeats, lungs breathe, or the stomach digest food. All these processes automatically happen unless someone stops them from doing this.

So, a system is like a machine where each part does its job independently until another component comes into action. So, when we talk about systems, we mean anything that functions with other elements to achieve a common purpose.

2) Identify the problem: Once you know what a system is, you must identify the problem within the system. The problem could be due to a lack of knowledge, skills, resources, time, money, motivation, or support. You may find yourself asking questions such as “Why did this happen? Why didn’t anyone else notice this before now? What would make this situation different next time? How can we prevent this happening again?” These types of questions help you get started identifying the problem.

 3) Define the boundaries: Now that you have identified the problem, you should define the perimeter around the problem. In other words, you should decide who needs to take responsibility for fixing the issue. For example, who is responsible for making sure the problem doesn’t occur again? Is it only the person who made a mistake? Or is it the whole team/company? Whose fault was it? Was it the manager’s fault? Did he fail to supervise his staff correctly? Or were the employees lazy or under-skilled? Is it a training issue or lack of enough equipment? Is the environment conducive to learning new skills? There are lots of factors that contribute to creating a good working environment. Some of these might include physical space, communication channels, management style, culture.

 It depends on the context of whether you consider these issues essential or not. But once you have defined the boundaries, you can move forward to solve the problem.

4) Decide on possible actions: After defining the boundaries, you should develop several options to fix the problem. Each option should address the root cause of the problem. For instance, if you were trying to improve employee performance, you wouldn’t just focus on improving pay rates. Instead, you would look at how your organization trains employees, provides opportunities for career development, encourages feedback, rewards positive behavior, and promotes teamwork. Similarly, when you try to reduce waste in an organization, you don’t simply cut down on paper consumption. Instead, you need to think about ways to eliminate unnecessary paperwork, streamline procedures, and encourage collaboration between departments. Again, you will observe the patterns of behavior of your employees and act accordingly.

 5) Choose one solution and implement it: Finally, after deciding upon all the necessary steps to resolve the problem, choose one answer and start implementing it. If multiple solutions are available, pick the most appropriate one based on cost, complexity, risk, impact, and feasibility. The key here is to ensure that you do something rather than nothing. And remember, no matter which approach you use, you will always face challenges along the way. So be prepared!

What kind of problems do systems thinking solve?

I’m not sure if this is the right place to ask, but I’ve been reading a lot about “systems thinking” lately, and it seems like there are many different definitions. Some people say that it’s just an approach for solving complex problems, while others claim that it can be used as a tool for understanding any system or process. So what exactly do you mean when you talk about systems thinking? What kinds of problems does it help you solve? Is it only applicable in specific fields? Or could anyone use it to understand their own life better? Let’s explore the application of systems thinking in detail.

Systems Thinking is a way of looking at things from multiple perspectives simultaneously. The problems may represent complex systems or not. It helps us see how all parts fit together into one whole picture. For example, we might look at our body and think about its functions separately, such as digestion or respiration, and consider them holistically by seeing how they work together to keep us alive. 

These two approaches allow us to apply systems thinking to other areas of our lives. We can learn more about ourselves through systems thinking than we ever thought possible!

For instance, let’s imagine your car breaks down on the side of the road. You have no idea where to go, so you call AAA. They send out someone who will come pick up your vehicle and bring it back to the shop. The mechanic tells you that he needs to replace some parts because something went wrong during the repair. He says he has to order new parts online since his store doesn’t carry those particular items anymore. While waiting for him to return, you start wondering why you need to buy another set of tires. Why don’t you already have good ones? After all, you drive every day. Then you remember that you haven’t changed the oil in over a year. That means you should probably get a tune-up soon. And maybe you should change the air filter too. Perhaps even clean the windows.

All of these tasks seem simple enough, but now you’re starting to realize that each job requires several steps before it gets done. If you could view everything around you in terms of systems, you would notice that the entire situation was much bigger than you initially realized. 

Examples of systems thinking in everyday life/Business.

In this section, we will describe some examples of how the concept of Systems Thinking can be applied to real-life situations. We have chosen these cases because they represent many other similar problems people face every day and could benefit from a more systemic approach. The first example is about an organization with no clear vision or strategy; the second one shows how a company has created value using Systemic Thinking. In both cases, it is essential to understand what kind of system you want to build.

Example 1: A lack of strategic direction

The following case study describes a large international corporation where several departments had strategies without any overall plan. Each department had its own goals and objectives, but none knew anything about the others’ activities. This disparity resulted in much confusion among employees who did not understand why they should do certain things. There was also a high turnover rate within each department as well as between departments. It took years before anyone realized that all parts needed to work together towards achieving the same goal.

The solution? Create a shared vision and common values across the whole organization. Once everyone understood the big picture, everything became much clearer. Employees started working on projects that made sense and helped achieve the desired results. They felt part of something bigger than themselves. And most importantly, the company’s performance improved significantly.

Example 2: Creating value through systemic thinking

This story illustrates how a small business used Systemic Thinking to improve its operations. When the owner decided to sell his business, he wanted to ensure that the new owners would continue running it successfully after him. So he asked himself, “What does my business need?” After answering this question, he came up with three primary needs: Generating revenue, providing exemplary service to customers, and keeping costs low. These three requirements formed the basis of his business plan.

He then looked into the market and discovered that two companies were already providing services very close to his business. However, neither of them met all three criteria mentioned above. So he set out to find another way to meet these needs. By doing so, he discovered that four distinct markets existed in his area. He created a marketing mix that included advertising campaigns targeting specific groups of potential clients with this knowledge. As a result, his sales increased dramatically. His profits went down slightly due to higher production costs, but he still raised his net income substantially.

Systems Thinking helps us see our world differently. We can use it to help solve the problems we are facing today and prepare for future challenges.

     Systems Thinking is an approach to problem-solving based on understanding systems instead of focusing only on individual elements. The idea behind this concept is simple: if you look at your environment from a broader perspective, you will be better prepared to deal with unexpected events. In addition, you will have more options available when making decisions because you will consider many factors simultaneously rather than just looking at a single aspect.

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Understanding Systems Thinking: A Path to Insightful Problem-Solving

In today’s dynamic and complex business landscape, traditional problem-solving approaches often fall short in addressing persistent challenges. Enter systems thinking, a powerful methodology that offers a fresh perspective by considering the interconnectedness of various elements within a system. In this article, we delve into the fundamentals of systems thinking, exploring its principles, benefits, and practical tips for beginners. Whether you’re eager to introduce this approach in your organisation or looking to enhance your problem-solving skills, let’s embark on a journey of understanding the intricacies of systems thinking.

Table of Contents

Understanding Systems Thinking

Practical tips for beginners, the benefits of systems thinking, when to apply systems thinking, getting started, utilising systems thinking tools, indicators of progress in systems thinking.

Systems thinking encompasses a broad range of principles, tools, and a philosophical mindset. It involves understanding the circular nature of the world we live in, recognising the role of structures in shaping the conditions we face, and acknowledging the existence of powerful laws governing systems. By adopting a systems thinking approach, we gain a deeper understanding of the consequences of our actions, allowing us to make more informed decisions.

• Study Archetypes: Dive into the classic stories and patterns to enhance your understanding.
• Practice Frequently: Analyse real-world scenarios, such as newspaper articles and current headlines, through a systems lens.
• Apply Systems Thinking Everywhere: Extend your application of systems thinking beyond the workplace to gain a holistic perspective.
• Embrace Different Perspectives: Use systems thinking to explore alternative viewpoints and understand how others perceive a system.
• Accept the Learning Curve: Recognise that becoming skilled in utilising systems thinking tools takes time and practice. Embrace the journey!

Systems thinking offers several compelling reasons to adopt its principles in problem-solving endeavours. By broadening our thinking and enabling us to articulate problems in novel ways, it expands the range of choices available for resolving complex issues. Furthermore, systems thinking emphasises the importance of considering the interconnectedness of various elements, highlighting that every decision has ripple effects throughout the system. By anticipating these impacts, we can make informed choices and minimise unintended consequences.

Ideally, systems thinking is suited for problems with the following characteristics:

• Importance: The issue at hand holds significant significance.
• Chronicity: The problem persists over time, rather than being a one-time event.
• Familiarity: The problem has a known history, indicating previous attempts at resolution.
• Previous Failures: Past efforts to solve the problem have been unsuccessful.

When approaching a problem through systems thinking, it’s crucial to foster a blame-free environment. Instead of focusing on assigning blame, encourage curiosity within the team. Prompt discussions by asking thought-provoking questions like, “What aspects of this problem are we failing to comprehend?”

To ensure a comprehensive analysis, employ the iceberg framework. Encourage the team to describe the problem by examining its events, patterns, and underlying structures. Additionally, diverse perspectives are essential. Involve individuals from various departments or functional areas to capture a comprehensive range of mental models.

One of the fundamental tools in systems thinking is the causal loop diagram. When using this tool, remember that simplicity is key. Start with a small and straightforward diagram, gradually adding elements as necessary. The diagram should reflect the story your group aims to depict accurately. Don’t fret about creating a diagram that includes every variable; focus on capturing the causal relationships that matter most.

Another valuable resource in systems thinking is the use of archetypes. These classic stories serve as powerful illustrations of systems behaviour. Keep the application of archetypes simple and relatable, allowing individuals to draw parallels between the archetypes and their own problems.

As you progress in your journey of applying systems thinking, it’s essential to gauge your proficiency and recognise when you have truly grasped its principles. Here are some indicators that can help you determine if you’re on the right track:

• Asking Different Kinds of Questions: A hallmark of systems thinking is a shift in the types of questions you ask. Instead of focusing solely on immediate causes and effects, you start exploring the underlying systemic structures and interconnections. You find yourself inquiring about feedback loops, dependencies, and unintended consequences, seeking a more holistic understanding of the system at play.
• Recognising Cautionary Flags: With a growing understanding of systems thinking, you become attuned to catchphrases that may oversimplify complex problems. For instance, when someone suggests, “The problem is we need more (sales staff, revenue),” you instinctively recognise the need to delve deeper. You redirect the discussion towards systemic factors, understanding that increasing staff or revenue alone may not address the root causes.
• Detecting Archetypes and Balancing Processes: As you deepen your knowledge of systems thinking, you begin to identify recurring patterns or archetypes in stories and real-world situations. These archetypes, such as “The Tragedy of the Commons” or “Shifting the Burden,” illustrate common systemic behaviours. Recognising these archetypes enables you to spot imbalances and reinforcing processes within a system, facilitating a more comprehensive analysis of complex issues.
• Surfacing Mental Models: Systems thinking invites a deep exploration of mental models—the deeply held beliefs, assumptions, and perspectives that shape our understanding of the world. As you progress, you become adept at recognising and challenging your own mental models and those of others. By surfacing and examining these mental models, you can uncover potential biases and broaden your perspective, enabling more robust problem-solving.
• Identifying Leverage Points: Leverage points are strategic areas within a system where interventions can have a significant and lasting impact. With increasing proficiency in systems thinking, you start recognising these leverage points, understanding which actions can create meaningful change. This heightened awareness empowers you to identify leverage points in classic systems stories and apply them creatively to real-world challenges.

Systems thinking is a transformative approach to problem-solving, offering a powerful lens through which to understand complex issues. By embracing these principles and utilising its tools, you can unlock fresh insights and uncover interconnected patterns. Whether you’re just beginning your journey or seeking to refine your skills, systems thinking empowers you to tackle challenges more comprehensively, paving the way for effective and sustainable solutions.

Remember, systems thinking is not just a method; it’s a lifelong practice that cultivates curiosity, clarity, compassion, choice, and courage. Embrace this holistic approach, and you’ll witness a paradigm shift in the way you perceive the world and address complex problems.

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Bridging the Evidence Gap in Obesity Prevention: A Framework to Inform Decision Making (2010)

Chapter: 4 defining the problem: the importance of taking a systems perspective, 4 defining the problem: the importance of taking a systems perspective.

O besity is a multifaceted problem that warrants complex thinking and a broad systems perspective to frame the problem, understand potential causes, identify critical leverage points of influence, and take effective action. Linear approaches to complex public health problems such as the obesity crisis are clearly useful, but cannot address the multiple dimensions of the real world and the many influences on the energy balance equation (Foresight, 2007). It is necessary to embrace complexity and to develop strategies and implement change at multiple levels to influence human behavior and reverse the current upward trends in weight. A systems perspective offers a new approach to obesity research and action that can meet this challenge (Huang et al., 2009).

The systems approach has a nearly 50-year history since its development by Forrester at the Massachusetts Institute of Technology (Forrester, 1991). Increasingly, obesity scholars are looking to other disciplines, from biology to psychology to computer sciences and engineering, that use this approach. In the health arena, the approach has been used to elucidate seemingly intractable problems, including cardiovascular disease (Homer et al., 2004), diabetes (Milstein et al., 2007), mental health (Smith et al., 2004), public health emergencies (Hoard et al., 2005), and tobacco control (National Cancer Institute, 2007).

The complex issue of obesity lends itself to a systems approach quite well. Like tobacco control, which employed diverse and multilevel strategies (Abrams et al., 2003, 2010), progress in the obesity field will require a paradigm shift toward an interdisciplinary knowledge base that integrates systems theory with concepts and practice from community development, social ecology, social networks, and public health (Best et al., 2003).

This chapter explains how systems thinking expands upon the multilevel, multisector strategies already proposed or in use to prevent obesity. It provides a primer on the concepts of such thinking and examines how the systems approach can be applied to identify the determinants, strategies, and actions that must be considered to address the obesity crisis. The chapter provides several practical examples of how systems thinking can be used in both small and large ways to expand the boundaries of current models and advance effective change in public health. The chapter also links the systems approach and its application to the L.E.A.D. framework ( Figure 4-1 ), describing how it enhances the ability to generate, use, and learn from evidence and explaining how specific content pertaining to each step of the framework will differ according to the system on which one is focusing. Box 4-1 defines the key systems concepts pertinent to the discussion.

UNDERSTANDING A SYSTEMS APPROACH

As explained in Chapter 2 , multilevel, multisector strategies, often based on ecological models (e.g., Figure 1-5 in Chapter 1 ), 1 have gained widespread acceptance for understanding the determinants of obesity and for framing prevention and control activities (Glass and McAtee, 2006). While these models acknowledge the multiple levels of a system and show their interrelationships, however, they may not always be complex enough to capture the dynamic interactions and the short- and long-term feedback loops among the many influences on the energy balance (Foresight, 2007; Sterman, 2006). Systems investigation can complement other methods by capturing this complexity, translating it into actions that can have an impact on the obesity problem and making it possible to predict unintended consequences and time-delayed effects (Mabry et al., 2008).

FIGURE 4-1 The L ocate Evidence, E valuate Evidence, A ssemble Evidence, Inform D ecisions (L.E.A.D.) framework for obesity prevention decision making.

NOTE: The element of the framework addressed in this chapter is highlighted.

A systems approach requires seeing the whole picture and not just a fragment, understanding the broader context, appreciating interactions among levels, and taking an interdisciplinary approach (Leischow and Milstein, 2006). A systems approach highlights the importance of the circumstances, or context, in which an action is taken in order to understand its implementation and potential impact. Thus while investigators must, for practical reasons, establish boundaries to define the system being studied, they must also recognize that each system exists within and interacts with a hierarchy of nested systems (Midgley, 2000). In addition, appreciating leverage points or points of power within a system can help explain how a small shift in one element of a complex system can produce larger changes in other elements (Meadows, 1999). These advantages of systems investigation are particularly important for interventions targeting obesity, given their far-reaching impact on the population; solutions should be designed to maximize benefit and minimize negative consequences.

The systems approach offers a further advantage with respect to the well-recognized gap between research and practice, which limits the extent to which advances in research translate to advances in improving public health. Most efforts to

link research to practice and policy have merely highlighted the challenges of transferring knowledge from single-discipline, highly controlled research to practice settings. Interdisciplinary investigation using a systems approach can potentially help close this gap (Mabry et al., 2008).

A systems approach to solving health problems requires new tools, including data, methods, theories, and statistical analysis different from those traditionally used in linear approaches. No single discipline can provide these tools. Therefore, it is necessary to approach health research with a collaborative team of investigators who bring knowledge and expertise from a variety of disciplines and sectors (Leischow et al., 2008). The theoretical frameworks and methodologies that result from such collaboration can generate new conceptual syntheses, new measurement techniques (e.g., social network analysis), and interdisciplinary fields of inquiry (e.g., behavioral genetics) with the capacity to tackle complex population health problems (Fowler et al., 2009).

Sterman (2006) explains how the dynamics of a system work, using policy resistance as an example. His explanation, reproduced in Box 4-2 , encompasses the key concepts and variables in systems thinking: stocks, flows, feedback processes (positive or self-reinforcing and negative or self-correcting), side effects, and time delays.

USES OF SYSTEMS THINKING, APPROACHES, MAPPING, AND MODELING

Systems can be small or large and often coincide with the levels defined in an ecological model. For example, a school can be thought of as a micro-system within a larger community; as a meso-system within the even larger national, political, and social milieu; or as a macro-system within a global-system context. This section provides several examples of how systems thinking pertains to public health problems: body mass index (BMI) screening in schools, tobacco control in the United States, obesity modeling in the United States, and obesity prevention in the United Kingdom.

BMI Screening in Schools

The monitoring of childhood growth has been a contentious issue for several decades (James and Lobstein, 2009). In recent years, school districts have been under pressure to respond to the childhood obesity epidemic. Despite limited evidence on the value of schools providing individually directed help for children with higher BMIs, the establishment of school-based surveillance to document obesity prevalence and to inform the development of prevention and treatment policies has been recommended (e.g., Massachusetts Department of Public Health, 2009). Although the measurement of weight and height within schools appears relatively simple and in fact has been taking place for decades, the development of rigorous measurement and reporting protocols has been limited until recently. This lack of a well-defined process, together with the failure to take a systems perspective, can result in a number of unintended consequences and perturbations to the system. For example, children may feel embarrassed or stigmatized during the process, parents may feel unequipped to act on the information they receive, health care providers in the community may not be educated about obesity treatment, the community may lack adequate pediatric programming to which children can be referred, and schools may forego other screening programs to make room for BMI screening (for example, hearing and vision screenings were cut back when the Massachusetts Public Health Council voted to require BMI screening of schoolchildren [Mullen, 2009]). In addition, although obesity rates may be high, insufficient funds or a lack of political will may prevent the school system from accessing the funding and assistance needed to address these unintended consequences, leaving the community feeling frustrated and helpless.

The Tobacco Control Movement

Although historically the tobacco control movement targeted individuals and their behaviors, it evolved into a multilevel systems approach to the problem (Abrams, 2007). Clearly, individual behavior change was the goal, but strategies involving industry, legislation, public health programming and messaging, and the health care system worked together to create that change. None of the strategies implemented as part of the movement worked alone. State by state, it was demonstrated that a combi-

nation of strategies was better than any single intervention, and the more components that were used, the better (CDC, 1999; Levy et al., 2007). The movement can be seen as a good example to inform the field of obesity prevention.

To explore this paradigm shift, a pilot project, the Initiative on the Study and Implementation of Systems (ISIS), was conducted with funding from the National Cancer Institute (NCI) (Best et al., 2006). ISIS was designed to (1) explore how systems thinking approaches might improve understanding of the factors contributing to tobacco use, (2) inform strategic decision making on which efforts might be most effective for reducing tobacco use, and (3) serve as an exemplar for addressing other public health problems. Contextually, tobacco control can be viewed as a system comprising smaller systems and existing within the broader systems of public health; economics; and society at the local, regional, and global levels. Figure 4-2 shows the evolution of tobacco control approaches toward systems thinking (NCI, 2007).

The ISIS project was an attempt to understand the whole problem of tobacco use comprehensively, and ultimately to address the problem through systems change. As a result of strategic planning, the ISIS group identified four priority areas ( Figure 4-3 ) that together serve as a synergistic foundation for understanding and improving public health from a systems perspective (Leischow et al., 2008; NCI,

FIGURE 4-2 Evolution of tobacco control approaches toward systems thinking.

NOTES: Quitlines indicate telephone hotlines for smoking cessation. ASSIST = American Stop Smoking Intervention Study for Cancer Prevention; COMMIT = Community Intervention Trial for Smoking Cessation; ISIS = Initiative on the Study and Implementation of Systems; NCI = National Cancer Institute.

SOURCE: NCI, 2007.

FIGURE 4-3 Priority areas identified by the Initiative on the Study and Implementation of Systems (ISIS) group.

SOURCE: Reprinted from Leischow et al., Copyright © 2008, with permission from Elsevier.

2007). Simulation modeling, conducted in the third of ISIS’s priority areas, has been useful for exploring the impact of changes in various parameters within the complex systems that have an impact on population-level outcomes related to tobacco use behaviors and policies (Abrams et al., 2010; Levy et al., 2010a,b).

Mapping of Obesity Causality in the United States

System dynamics modeling can help map causality by addressing risks and outcomes; when performed prospectively, it can be used to predict future outcomes, and when performed retrospectively, it can be used to understand how strategies and delivery systems interacted with a population during an intervention. The process proceeds iteratively through the general steps shown in Figure 4-4 , beginning with the identification of a persistent problem (Milstein and Homer, 2006). Milstein and Homer

FIGURE 4-4 Iterative steps in system dynamics modeling.

SOURCE: Milstein and Homer, 2006.

(2009) use system dynamics modeling to map the forces that contribute to the persistent obesity problem (see Figure 4-5 ). This exercise helps in understanding the causes of obesity, the broader systems to which they belong, and how they are thought to interact. Such mapping can therefore elucidate potential mechanisms and dynamic pathways on which intervention strategies should focus.

Once such maps have been developed, they can be converted into computer simulation models that can be used to identify interventions and policies with the potential to alleviate the problem. These experiments are followed by sensitivity analyses to assess areas of uncertainty in the models and to guide future research. Once the models have been finalized, stakeholders are convened to participate in “action labs,” in which the models allow them to discover for themselves the likely consequences of alternative policy scenarios (Milstein and Homer, 2009).

A broad array of modeling techniques are used for different purposes in many different fields. Because of the complexity of the obesity problem, the most suitable modeling techniques will have several characteristics (Hammond, 2009). First, because of the scale of the epidemic, models may provide the most insight if they capture multiple levels of analysis. Second, to capture the dynamics of such a complex system, models must be able to incorporate individual heterogeneity and adaptation over time. Finally, models must be able not only to provide a better understanding of the problem and the mechanisms behind it, but also to aid in the design of new and better interventions to slow and reverse the epidemic.

Obesity Prevention in the United Kingdom

The most comprehensive effort to both understand and map the obesity epidemic and formulate a national action plan was carried out by the Foresight Group in the United Kingdom (Foresight, 2007). The Foresight Tackling Obesities: Future Choices Project was aimed at producing a sustainable response to obesity in the United Kingdom over the 40 years following the plan’s release. Using a systems approach, the group pursued objectives that included using the scientific evidence base across a wide range of disciplines to identify the many factors that influence obesity, looking beyond the obvious to achieve an integrated understanding of the relationships among these factors and their relative importance, building on this evidence to identify effective interventions, analyzing how future levels of obesity might change, and identifying what the most effective future responses might be. A detailed causal loop obesity system map was produced to display the interrelationships among the various contributors to energy balance; a simplified version of this map is shown in Figure 4-6 .

In addition, a strategic framework was developed to identify gaps in current initiatives that would have to be filled to mount an integrated policy response. Its authors identify six key elements of this framework (Jebb, 2009):

FIGURE 4-5 The obesity “system”: a broad causal map.

NOTES: Blue arrows indicate same-direction links; green arrows indicate opposite-direction links; R loops indicate reinforcing processes; B loops indicate balancing processes. All parameters vary by such factors as age, sex, race/ethnicity, income, and geography.

SOURCE: Milstein and Homer, 2009. Reprinted with permission.

FIGURE 4-6 Simplified version of the causal loop obesity system map showing the interrelationships among various contributors to energy balance. The map was developed by the UK Foresight Group to understand and chart the obesity epidemic in order to inform a national action plan.

SOURCES: Vandenbroeck et al., 2007.

systematic change that addresses the diverse determinants of obesity simultaneously to minimize the risk of compensatory actions;

integrated interventions at all levels of society—individual, family, local, national and international—recognizing that individual choices are shaped by the wider context;

interventions across the life course to reinforce and sustain long-term behavior change;

diverse interventions that combine focused initiatives (which impose change), “enablers” (which inform and facilitate change), and “amplifiers” (which address social norms and the cultural context);

actions planned over time such that early initiatives build a climate for subsequent interventions; and

ongoing evidence gathering, including population-level surveillance and evaluation of interventions.

The Foresight Group identified as a key research challenge “the evaluation of new policy initiatives at all levels (process audits, behaviors and biomarkers, long-term health and economic outcomes)” (Jebb, 2009, p. 39). These types of causal loops magnify the need for new ways of evaluating and incorporating evidence not only from research studies, but also from the real-world experience of obesity initiatives undertaken not just within a particular country but around the world.

Although outcomes of systems approaches such as the Foresight Group’s causal loop system map appear complex, they are useful for informing practical, real-world intervention strategies. For example, Foresight’s Tackling Obesities: Future Choices Project was used to inform a cross-government strategy for England that was part of a sustained program to reduce obesity and support healthy weight maintenance (Cross-Government Obesity Unit, 2010).

RELATION TO THE L.E.A.D. FRAMEWORK

The idea that evidence should be identified, evaluated, and summarized from a systems perspective is fundamental to the framework proposed in this report. A systems perspective broadens the traditional approach to locating, evaluating, and assembling evidence (which generally limits the evidence to results of rigorous randomized controlled trials) to encompass evidence that reflects the complexity of the problem. Users of the framework are encouraged to approach every aspect of decision making with a comprehensive lens, considering the complex context in which programs and policies will be implemented and how it may affect their implementation and impact. A systems perspective enables the decision maker to understand interactions among smaller systems within the larger system and identify potential synergies or harms that should be explored before implementation. Creating “what if” scenarios based on systems maps can help decision makers and stakeholders think about various approaches and where to focus efforts, as well as potential costs; elements that are critical in the design of interventions or program and policy evaluations; and feedback loops that can be sources of evaluation data (see Chapter 6 ).

APPLICATION AND FUTURE DIRECTIONS

According to Hammond (2009), the most effective models for addressing the obesity epidemic are likely to be those that capture multiple mechanisms at multiple levels,

integrate micro and macro data and dynamics, account for significant heterogeneities, and allow for policy experimentation. To fully realize the potential application of systems theory to obesity prevention, a number of strategies will be required. First, current and future leaders should be trained in the science and understanding of systems and their application to the obesity crisis. This training would include causal mapping, conceptualization of interventions, and computational and simulation modeling techniques. The application of these methods to the obesity epidemic will be challenging—there will be important data that are not yet available, uncertainty about a number of assumptions, and many key mechanisms whose inner workings are unknown (Hammond, 2009). In some cases, smaller systems will have to be studied independently, perhaps with relatively homogeneous populations, before being integrated into a more comprehensive model. Various combinations of models can then be explored and tested against the same outcome data, building slowly toward a model that encompasses the full breadth of the system by integrating all those narrower models. Second, empirical research should be funded and executed using systems theory as a guide. Focused studies can be used to confirm and quantify relationships and to test their effects. Ideally, this research would be carried out in conjunction with modeling studies to produce the most informative data and to guide future research. Third, both knowledge generators and users must work collaboratively with different disciplines to build interdisciplinary capacity.

Caution will be necessary regarding the use of models and the need to link their application with empirical research. The interplay between systems theory and research requires high-quality experimental and quasi-experimental designs. Systems thinking puts researchers in a better position to ask the right questions. Research applications allow a systems model to make the right predictions.

In conclusion, systems thinking in public health cannot be encompassed by a single discipline or even a single “systems thinking” approach (e.g., system dynamics models). Rather, it requires interdisciplinary integration of approaches to public health aimed at understanding and reconciling linear and nonlinear, qualitative and quantitative, and reductionistic and holistic thinking and methods to create a federation of systems approaches (NCI, 2007).

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To battle the obesity epidemic in America, health care professionals and policymakers need relevant, useful data on the effectiveness of obesity prevention policies and programs. Bridging the Evidence Gap in Obesity Prevention identifies a new approach to decision making and research on obesity prevention to use a systems perspective to gain a broader understanding of the context of obesity and the many factors that influence it.

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Systems Thinking: How to Solve Problems So They Stay Solved

From production to customer service and marketing, organizations are made up of a series of interconnected parts. While each function may appear to operate efficiently on its own, a change in just one cog can throw the whole system out of whack. The problems that arise in interconnected organizations can be difficult to solve.

Systems thinking is problem-solving approach that examines the relationships between functions in an organization. Systems thinking is powerful because it enables you to predict the consequences of a potential change. This problem-solving method can also help you eliminate silos, see different viewpoints, and remain focused on the big picture.

Ultimately, systems thinking empowers you to solve problems so that they stay solved. Instead of offering quick-fix solutions that work only in the short term, systems thinking helps you make decisions that benefit your organization in the long run.

You will learn how to:

• Apply systems thinking in the workplace in ways that benefit you and your organization: encouraging innovation, learning from mistakes, and enhancing leadership and management skills.
• Apply the tools of systems thinking to solve a problem.
• Minimize the unintended consequences of major decisions.

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What is systems thinking?

Systems thinking is an approach to problem solving which takes into account the overall system as well as its individual parts. According to Peter Senge, it’s “a framework for seeing interrelationships rather than things, for seeing patterns rather than static snapshots. It is a set of general principles spanning fields as diverse as physical and social sciences, engineering and management” [ Peter Senge, The Fifth Discipline, 2nd Ed 2006 ].

Why is it important?

Complex projects need both technical and managerial leaders who understand each other’s needs and requirements, and who consequently can work in an integrated way. There is substantial evidence that an integrated project management and systems engineering approach adds value by reducing the need for re-planning and rework, and optimising the risk margin, allowing projects to fulfill their objectives both on time, and to budget.

Read more on the Systems Thinking resource page .

You can also find more through the Systems Thinking Specific Interest Group (SIG), which has a valuable resource area with links to material including books, papers, presentations and webinars. The aim of the  Systems Thinking SIG  is:  “To promote systems thinking as a methodology to improve delivery of complex change initiatives“  and welcomes collaboration and input. To read more about the origin of the SIG, have a look at the article published on  the integration of P3M and systems engineering .

John McGlynn’s blog  also explains more about the development and aim of the SIG and encourages involvement.

According to new research from APM, conventional project management relying on prescribed systems and processes leaves no room for flexibility. Even agile methods are not enough as projects increase in complexity.

The research was awarded funding from APM’s research fund in 2017 to gain a better insight into the current level of understanding, application and recognition of the potential benefits of systems thinking.  Read the report  to discover how systems thinking can be used in project management.

People who think about systems thinking in projects argue that when you have complex interactions between people or other variables on a project it becomes very difficult to plot a straight linear path towards the defined outcome. One solution to dealing with uncertainty and ambiguity is to use a programme approach to organising the work – a framework that expects the outcomes to be created in iterative tranches or chunks of activity. Read more  in this blog  by Ruth Murray-Webster.

Finally, the excerpt below explains how project managers can benefit from a systems thinking approach:

The management of change in projects that are building or modifying complex systems is challenging. We define systems as complicated if they consist of many elements of different types, although, individually, each may have characteristics that can be described in simple terms. We consider systems as complex if some of the relationships and interactions between subsystems are not easily understood, and thus difficult to manage.

But project managers can borrow from engineering systems thinking, which evolved as a consequence of technical systems becoming too complicated to analyse and manage by means of conventional engineering approaches. Systems thinking enables managers to analyse the components of systems and to handle their interactions.

Systems thinking can be applied not only to technical systems, but also to projects. In this sense, projects can be considered as complex and complicated systems, where tasks and activities are the equivalent of subsystems.

Read more about this in the recent  Project Journal  article,  Chess or dominoes .

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Systems Thinking: What, Why, When, Where, and How?

I f you’re reading The Systems Thinker®, you probably have at least a general sense of the benefits of applying systems thinking in the work-place. But even if you’re intrigued by the possibility of looking at business problems in new ways, you may not know how to go about actually using these principles and tools. The following tips are designed to get you started, whether you’re trying to introduce systems thinking in your company or attempting to implement the tools in an organization that already supports this approach.

What Does Systems Thinking Involve?

Tips for beginners.

• Study the archetypes.
• Practice frequently, using newspaper articles and the day’s headlines.
• Use systems thinking both at work and at home.
• Use systems thinking to gain insight into how others may see a system differently.
• Accept the limitations of being in-experienced; it may take you a while to become skilled at using the tools. The more practice, the quicker the process!
• Recognize that systems thinking is a lifelong practice

It’s important to remember that the term “systems thinking” can mean different things to different people. The discipline of systems thinking is more than just a collection of tools and methods – it’s also an underlying philosophy. Many beginners are attracted to the tools, such as causal loop diagrams and management flight simulators, in hopes that these tools will help them deal with persistent business problems. But systems thinking is also a sensitivity to the circular nature of the world we live in; an awareness of the role of structure in creating the conditions we face; a recognition that there are powerful laws of systems operating that we are unaware of; a realization that there are consequences to our actions that we are oblivious to. Systems thinking is also a diagnostic tool. As in the medical field, effective treatment follows thorough diagnosis. In this sense, systems thinking is a disciplined approach for examining problems more completely and accurately before acting. It allows us to ask better questions before jumping to conclusions. Systems thinking often involves moving from observing events or data, to identifying patterns of behavior overtime, to surfacing the underlying structures that drive those events and patterns. By understanding and changing structures that are not serving us well (including our mental models and perceptions), we can expand the choices available to us and create more satisfying, long-term solutions to chronic problems. In general, a systems thinking perspective requires curiosity, clarity, compassion, choice, and courage. This approach includes the willingness to see a situation more fully, to recognize that we are interrelated, to acknowledge that there are often multiple interventions to a problem, and to champion interventions that may not be popular (see “The Systems Orientation: From Curiosity to Courage,”V5N9).

Why Use Systems Thinking?

Systems thinking expands the range of choices available for solving a problem by broadening our thinking and helping us articulate problems in new and different ways. At the same time, the principles of systems thinking make us aware that there are no perfect solutions; the choices we make will have an impact on other parts of the system. By anticipating the impact of each trade-off, we can minimize its severity or even use it to our own advantage. Systems thinking therefore allows us to make informed choices. Systems thinking is also valuable for telling compelling stories that describe how a system works. For example, the practice of drawing causal loop diagrams forces a team to develop shared pictures, or stories, of a situation. The tools are effective vehicles for identifying, describing, and communicating your understanding of systems, particularly in groups.

When Should We Use Systems Thinking?

Problems that are ideal for a systems thinking intervention have the following characteristics:

• The issue is important.
• The problem is chronic, not a one-time event.
• The problem is familiar and has a known history.
• People have unsuccessfully tried to solve the problem before.

Where Should We Start?

When you begin to address an issue, avoid assigning blame (which is a common place for teams to start a discussion!). Instead, focus on items that people seem to be glossing over and try to arouse the group’s curiosity about the problem under discussion. To focus the conversation, ask, “What is it about this problem that we don’t understand?”

In addition, to get the full story out, emphasize the iceberg framework. Have the group describe the problem from all three angles: events, patterns, and structure (see “The Iceberg”). Finally, we often assume that everyone has the same picture of the past or knows the same information. It’s therefore important to get different perspectives in order to make sure that all viewpoints are represented and that solutions are accepted by the people who need to implement them. When investigating a problem, involve people from various departments or functional areas; you may be surprised to learn how different their mental models are from yours.

How Do We Use Systems Thinking Tools?

Causal Loop Diagrams. First, remember that less is better. Start small and simple; add more elements to the story as necessary. Show the story in parts. The number of elements in a loop should be determined by the needs of the story and of the people using the diagram. A simple description might be enough to stimulate dialogue and provide a new way to see a problem. In other situations, you may need more loops to clarify the causal relationships you are surfacing.

THE ICEBERG

The Archetypes. When using the archetypes, or the classic stories in systems thinking, keep it simple and general. If the group wants to learn more about an individual archetype, you can then go into more detail. Don’t try to “sell” the archetypes; people will learn more if they see for themselves the parallels between the archetypes and their own problems. You can, however, try to demystify the archetypes by relating them to common experiences we all share.

How Do We Know That We’ve “Got It”?

Here’s how you can tell you’ve gotten a handle on systems thinking:

• You’re asking different kinds of questions than you asked before.
• You’re hearing “catchphrases” that raise cautionary flags. For example, you find yourself refocusing the discussion when someone says, “The problem is we need more (sales staff, revenue).”
• You’re beginning to detect the archetypes and balancing and reinforcing processes in stories you hear or read.
• You’re surfacing mental models (both your own and those of others).
• You’re recognizing the leverage points for the classic systems stories.

Once you’ve started to use systems thinking for inquiry and diagnosis, you may want to move on to more complex ways to model systems-accumulator and flow diagrams, management flight simulators, or simulation software. Or you may find that adopting a systems thinking perspective and using causal loop diagrams provide enough insights to help you tackle problems. However you proceed, systems thinking will forever change the way you think about the world and approach issues. Keep in mind the tips we’ve listed here, and you’re on your way!

Michael Goodman is principal at Innovation Associates Organizational Learning

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The Six Systems Thinking Steps to Solve Complex Problems

A quick overview of common problem solving techniques indicates that most of these methods focus on the problem rather than the whole eco-system where the problem exists. Along with the challenges of global economy , problems turn out to be more complicated and sometimes awakening problems. Climate change, traffic problems, and organizational problems that have developed through the years are all complex problems that we shouldn’t look at the same way as simple or linear problems. Part of the problem of thinking about a complex problem is the way we approach it, which may contribute to making the problem even more complex. As stated by Albert Einstein, “The problems cannot be solved using the same level of thinking that created them.” Systems thinking tends to focus on the broader ecosystem rather than the problem itself.

Systems thinking was developed by Jay Forrester and members of the Society for Organizational Learning at MIT. The idea is described in his book, The Fifth Discipline , as follows: “Systems thinking is a discipline for seeing wholes. It is a framework for seeing interrelationships rather than things, for seeing patterns of change rather than static ‘snapshots.’” A common example of the systems thinking method is the life around us where multiple systems interact with each other and are affected by each other. This wide perspective of systems thinking promotes it to solve complex problems that are dependent on external factors. Below are some of the stations that system thinking may contribute to solve.

• Complex problems that involve different factors, which require understanding the big picture in order to be efficiently solved
• Situations that are affecting, are being affected by, or affect the surrounding systems
• Problems that have turned more complicated by previous attempts to solve them

Concepts of Systems Thinking

In order to understand systems thinking, a number of concepts should be highlighted in order to define the relation between the problem and the other elements in the system and how to observe this relation in order to reach an effective solution. These principles include the following.

• All systems are composed of interconnected parts, and changing one part affects the entire system, including other parts.
• The structure of a system determines its behavior, which means that the system depends on the connection between parts rather that the part themselves.
• System behavior is an emergent phenomenon. System behavior is hard to predict due its continuously changing, non-linear relations and its time delay. It can’t be predicted by simply inspecting its elements or structure.
• Feedback loops control a system’s major dynamic behavior. The feedback loop is a number of connections causing an output from one part to eventually influence input to that same part. The number of feedback loops are larger than the system parts, which contributes to increasing system complicity.
• Complex social systems exhibit counterintuitive behavior. Solving complex problems can’t be achieved through everyday problem solving methods. They can be solved only through analytical methods and tools. Solving complex problems can be achieved through systems thinking, a process that fits the problem, and system dynamics , which is an approach to model systems by emphasizing their feedback loops.

Systems Thinking in Six Steps

In their paper Six Steps to Thinking Systemically , Michael Goodman and Richard Karash introduced six steps to apply systems thinking principles while solving complex problems. These steps were part of their case study to Bijou Bottling company’s problem of getting their orders shipped on time.

Set 1: Tell the Story

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The first step in solving the problem is to understand it, and this can be achieved through looking deeply at the whole system rather than individual parts. This step requires meeting with the stakeholders to share their vision about the situation. One of the common tools to build this understanding is to utilize Concept Maps, which are graphical tools used to represent the organization or a structure of knowledge. Concept Maps visually present the system’s elements, concept links, proposition statements, cross-links, and examples.

Step 2: Draw Behavior Over Time (BOT) Graphs

When thinking about a problem, we are influenced with the current situation that is reflected in our analysis, yet the problem follows a time dimension, which means that it should be tracked through the time. The Behavior Over Time graph draws a curve that presents a specific behavior (Y) through the time (X). This graph helps us to understanding whether or not the current solution is effective.

Step 3: Create a Focusing Statement

At this point, there should be a clear vision about the problem solving process, which is defined in the from of a statement that indicates the team’s target and why the problem occurs.

Step 4: Identify the Structure

After having clear vision about the problem through the proposed statement, the system structure should be described, including the behavior patterns. Building these patterns helps in understanding more about the problem, and it can be formed as a system archetype.

Step 5: Going Deeper into the Issues

After defining the problem and the system structure, this step tends to understand the underlying problems through clarifying four items: the purpose of the system (what we want), the mental models, the large system, and personal role in the situation.

Set 6: Plan an Intervention

The previously collected information is used to start the intervention phase, where modifications to the current problem relate parts to connections. This intervention attempts to reach the desirable behavior.

Practice Example of Systems Thinking

One of the direct examples of adopting the systems thinking method was presented by Daniel Aronson highlighting insects who caused damage crops. Traditional thinking to solve crop damage is to apply more pesticides to reduce the number of insects and subsequently reduce the crop damage. However, this solution solves the problem for a short term. In the long run, the problem isn’t truly solved, as the original insect eating the crops are controlling the population of another species of insect in the environment either by preying on it or competing with it. Subsequently, the crop damage increases again due to the increasing numbers of other insect species.

Observing the ecosystem that includes both the insects and the crops, systems thinking suggests exploring a solution that ensures reducing the crop damage in the long run without affecting the environmental balance, such as deploying the Integrated Pest Management that has proven success based on MIT and the National Academy of Science. This solution tends to control the number of an insect species by introducing its predators in the area.

Unlike everyday problems, complex problems can’t be solved using traditional problem solving methods due to the nature of the problems and their complexity. One of the theories that attempts to understand complex problems is systems thinking, which is defined by a number of characters. Six steps are to be used to explore and solve complex problems under the umbrella of systems thinking, which help us to observe and think in a whole eco-system rather than individual parts. Systems thinking can be deployed in multiple domains to solve organization problem, or global problems such as energy, pollution, and poverty.

Dr Rafiq Elmansy

I'm an academic, author and design thinker, currently teaching design at the University of Leeds with a research focus on design thinking, design for health, interaction design and design for behaviour change. I developed and taught design programmes at Wrexham Glyndwr University, Northumbria University and The American University in Cairo. Additionally, I'm a published book author and founder of Designorate.com. I am a fellow for the Higher Education Academy (HEA), the Royal Society of Arts (FRSA), and an Adobe Education Leader. I write Adobe certification exams with Pearson Certiport. My design experience involves 20 years working with clients such as the UN, World Bank, Adobe, and Schneider. I worked with the Adobe team in developing many Adobe applications for more than 12 years.

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3 thoughts on “ The Six Systems Thinking Steps to Solve Complex Problems ”

“Systems thinking was developed by Jay Forrester and members of the Society for Organizational Learning at MIT. The idea is described in his book, The Fifth Discipline, as follows:” Peter Senge is the author of The Fifth Discipline

Thank you so much Misi for the helpful information.

Thank you for the valuable information. I believe that systems thinking can be applied to every aspect of our lives. When you teach yourself to spot patterns, cycles, and loops instead of individuals elements. You see behind the scenes. Understand what actually needs addressing to move forward and make progress faster with less damage.

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Soft Systems Methodology (SSM)

Understanding very complex issues.

By the Mind Tools Content Team

Some problem solving tools can oversimplify the world when, in reality, it can be complex and messy.

In cases where many different factors contribute to an issue, and there are lots of different perspectives to consider, it can be difficult to tell where the root of the problem really lies. All this confusion can make finding a solution seem impossible. What you need is a problem solving approach that gives you a clear view of what's involved, so that you can focus on what you can do to improve the situation. In situations like this, Soft Systems Methodology (SSM) might be just what you need.

How SSM Was Developed

Soft Systems Methodology grew out of general systems theory, which views everything in the world as part of an open, dynamic, and interconnected system. The various parts of this system interact with one another, often in a nonlinear way, to produce a result.

According to general systems theory, organizations consist of complex, dynamic, goal-oriented processes – and all of these work together, in a coordinated way, to produce a particular result. For example, if a company's strategy is to maximize profits by bringing new products to market quickly, then the systems within the company must all work together to achieve this goal.

When something goes wrong within the system, or any of its subsystems, you must analyze the individual parts to discover a solution. In hard sciences, you can do this in a very controlled, analytical way. However, when you add human or "soft" elements – like social interaction, corporate politics, and individual perspectives – it's a much more difficult process.

That's why Peter Checkland, a management scientist and systems professor, applied the science of systems to the process of solving messy and confusing management problems. The result was Soft Systems Methodology – a way to explore complex situations with different stakeholders; numerous goals; different viewpoints and assumptions; and complicated interactions and relationships.

SSM helps you compare the "real world" with a model of how the world could be. Through this modeling process, you can go beyond the individual perspectives that might limit your thinking – and you can recognize what's causing the problems within the system.

Because SSM deals with real-world situations, it needs to reflect real-world problems, which often have nonlinear relationships that are not well defined. As a result, SSM activities are also nonlinear and not perfectly defined. Many other problem-solving tools can be shown as flow charts with a series of clearly defined steps. But diagrams used in SSM are more like mind maps – they show relationships between activities, but they don't show a linear route through them.

Checkland warns against thinking of SSM as a step-by-step process. However, if SSM is to be useful, you need to know where to begin. In this article, therefore, we'll give you a series of steps to help you get started (you can abandon this stepwise approach when you're more familiar with the methodology). To learn more about using the SSM approach, read " Learning for Action ," by Peter Checkland and John Poulter.

"Learning for Action" by Peter Checkland and John Poulter, © John Wiley & Sons, Inc. Terms reproduced with permission.

Although it's easy to think of Soft Systems Methodology as a "problem-solving approach," Checkland encourages SSM users to avoid thinking of a "problem" that can be "solved" by a "solution." These words imply that something is well defined and straightforward. Instead, he prefers the terms problematical situation and improvements .

Here's an example: "My car won't start" is a problem that might be solved by the solution "Charge the battery." However, consider "People don't enjoy driving this new model of car." This is a problematical situation for the manufacturer, which needs to look for actions that might improve the driving experience for customers.

Step 1: Explore the Problematical Situation

Create what Checkland calls a "rich picture" of what's happening. This is, in effect, a mind map . It shows the main individuals, groups, organizations, relationships, cultures, politics, and processes involved in the situation. Also, try to identify the different perspectives, or "worldviews," that different groups have of the situation.

Then, among these individuals or groups, identify the "client" who wants an improvement in the situation, the "practitioner" who is carrying out the SSM-based investigation, and the stakeholders who would be affected by an improvement in the situation.

Your goal, here, is to include as much relevant information as possible on a large sheet of paper.

Step 2: Create Purposeful Activity Models

Identify the "purposeful activities" being carried out by people involved in the situation. These are things that they're doing, as well as the actions they're taking to improve the problematical situation. Make note of which activities belong to which worldview.

Then, create a "root definition" of each activity. This is a more sophisticated description of the basic idea, and it contains enough detail to stimulate an in-depth discussion later on.

Checkland proposes two tools for developing the root definition. The first is called PQR:

• P stands for "What?"
• Q stands for "How?"
• R stands for "Why?"

If you answer the above questions, you can complete this formula: "Do P, by doing Q, to help achieve R."

The other tool is CATWOE . Use this to further improve the root definition by thinking about the following:

• Customers – Who receives the system's output?
• Actors – Who performs the work within, or implements changes to, the system?
• Transformation – What is affected by the system, and what does it do? This is often considered the most important part of CATWOE.
• Worldview – What is the big picture?
• Owner – Who owns the process?
• Environment – What are the restrictions and limits on any solution? What else is happening around it?

Finally, develop these into purposeful activity models. Ideally, you'll have 5–7 steps to cover all of these descriptions for each purposeful activity model, although you can break down individual steps into their own root definitions and activity models.

Checkland recommends reviewing these in the light of "three E's":

• Efficacy – Ways to monitor if the transformation is, in fact, creating the intended outcome.
• Efficiency – Ways to monitor if the benefits of the transformation are greater than the cost (in time, effort, and money) of creating them.
• Effectiveness – Ways to identify if the individual transformation also contributes to higher-level or longer-term goals.

Step 3: Discuss the Problematic Situation

Discuss in detail each purposeful activity model. Your goal is to find ways to improve the problematic situation. Some of the following questions may help:

• Does each part of the model truly represent what happens in reality?
• Do the dependencies and relationships between activities in the model also exist in reality?
• Is each activity efficacious, efficient, and effective?
• Who performs each activity? Who else could do it?
• How is each activity done? How else could it be done?
• When and where is each activity done? When or where else could it be done?

Having created a list of possible improvements, you may want to create purposeful activity models for each one. Following the process for doing so helps ensure that you've considered all of the various worldviews involved, which is necessary for the improvement to have a realistic chance of being implemented.

Step 4: Define "Actions to Improve"

The group doing the SSM-based analysis of the problematical situation now has to agree on which actions it thinks will improve the situation, and the group must define those actions in enough detail to create an implementation plan.

Remember, because people have different worldviews, there won't necessarily be agreement on which actions to take to improve the situation. However, everyone involved should reach what Checkland describes as an "accommodation" or compromise, so that they agree on practical options that meet the three E's – efficacy, efficiency, and effectiveness.

Change generally involves people, processes , and things . New "things" are usually the easiest to change: you can simply buy new equipment or systems. New processes need a lot of definition, but they can also be reasonably clear and straightforward to implement. Changes to people – involving culture or attitudes – are typically much more difficult. For more on this, see our article on Change Management .

We've presented Soft Systems Methodology here as a set of steps, but experienced SSM practitioners usually perform its activities in a repeated and ongoing manner – and they're flexible with SSM ideas, rather than following a strict process.

Checkland, P. and Poulter, J. (2007). ‘ Learning for Action: A Short Definitive Account of Soft Systems Methodology, and Its Use for Practitioners, Teachers and Students,’ Hoboken: Wiley.

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What 'systems thinking' actually means - and why it matters for innovation today

Systems thinking helps us see the part of the iceberg that's beneath the water Image:  Ezra Jeffrey

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Stay up to date:.

• Systems thinking can help us grasp the interconnectedness of our world.
• During the uncertainty of the pandemic, it can spur innovation.

We are currently living through VUCA (volatile, uncertain, complex and ambiguous) times.

As innovators, general professionals, key workers, citizens and humans, everything we do is ever more interdependent on each other. ‘No man is an island’ is a well-known phrase, yet in practice, how often do we understand the interconnectedness of everything around us? Enter systems thinking.

In some circles, there has been a lot of hype around taking an "ecosystems view" during this global pandemic, which frankly is not something new. Systems thinking has been an academic school of thought used in engineering, policy-making and more recently adapted by businesses to ensure their products and services are considering the ‘systems’ that they operate within.

Defining innovation

Every firm defines innovation in a different way. I enjoy using the four-quadrant model (see figure below) for simplicity: incremental innovation utilises your existing technology within your current market; architectural innovation is applying your technology in different markets; disruptive innovation involves applying new technology to current markets; and radical innovation displaces an entire business model.

During COVID-19, we are seeing a mixture of these. Many firms will start with incremental changes, adapting their products to a new period of uncertainty. With the right methodology and balance of internal and external capabilities, there is potential for radical and disruptive innovation that meets new needs, or fundamentally, creates new needs based on our current circumstances. Systems thinking is essential in untapping these types of innovation and ensuring they flourish long-term.

A dynamic duo

‘Systems thinking’ does not have one set toolkit but can vary across different disciplines, for example, in service design some may consider a ‘blueprint’ a high-level way to investigate one’s ‘systems of interest’. Crucially, this school of thought is even more powerful when combined with more common approaches, such as human-centered design (HCD).

The latter is bottom-up – looking in detail at a specific problem statement, empathising with its users and developing solutions to target them. Whereas the former is top-down – understanding the bigger picture, from policy and economics to partnerships and revenue streams. Systems thinking unpacks the value chain within an organisation and externally. It complements design thinking: together they’re a dynamic duo.

For starters, this philosophy needs to enter our everyday thinking. Yes, it is crucial for innovation, but an easy first step is to use systems thinking casually throughout your life. How is this purchase affecting other systems in the supply chain? What is the local economic impact of me shopping at the larger supermarket? Who will be the most negatively impacted if I don’t practice social distancing?

This mapping tool from the World Economic Forum is central in understanding causal relationships and effects during COVID-19. It helps to drive systems-informed decision making. Once this becomes mainstream, we can begin integrating data for systems modelling tools that will help us map impact across the multiple layers of influence from this pandemic. So, what does this mean for businesses?

Systems thinking for business

To illustrate how systems thinking applies in business, let's use a simplified example of a bank branch.

Event: COVID-19 declared a pandemic, lockdown implemented for all people and businesses, except key workers and essential firms. Branches are shutting, people are afraid to go to non-essential establishments.

Patterns/trends: what trends have there been over time? Scientists have warned us about being ‘pandemic-ready’ for years, but we have had misinformation or a lack of transparency from other ‘systems’ who should have been driving this.

However, what about banking patterns? More customer service has moved online, digital banks and fintech developments have decreased the urgency for face-to-face business in branches. Are there trends in customer behaviours? More consumers are searching for all their products and services online, and this was common before the pandemic had begun.

Underlying structures: what has influenced these patterns and how are they interconnected? A growing desire for digitalised experiences and convenience is popular in financial services and customers will begin to seek and only interact with businesses who have the infrastructure to operate this way. A minimal number of touchpoints is seen as desirable, providing quicker, stress-free experiences, as consumers want to spend less time on these engagements when work-life balance has become more integrated, and therefore is important to preserve.

Mental models: what assumptions, beliefs and values do people hold about the system? Behavioural economics tells us that customers will adapt and change their consumer spending habits. Used to the convenience of online, less relevance will be seen for branches, and banks will need to further adapt. The ‘new normal’ will contain old and new beliefs. Which ones keep bank branches in place? Human contact and customer service? The agency in dealing with your finances face-to-face? Will a new experience or service be required to keep bank branches relevant or are online digital banks all consumers will need?

Beyond this, do banks have an ethical obligation to monitor spending habits to identify signs of debt and underlying mental health problems? What relationship should banks have with data? How do they balance intuitive service with consumer privacy?

Going through the layers of this iceberg unearths part of the power from using systems thinking and exemplifies how to guide your strategy in a sustainable way.

Only focusing on events? You’re reacting.

Thinking about patterns/trends? You’re anticipating.

Unpicking underlying structures? You’re designing.

Understanding mental models? You’re transforming.

Transformative thinking is how we innovate and systems thinking is essential for this journey.

We’ve only explored the tip of the iceberg (pun intended) on the philosophy of systems thinking. There are many in-depth tools available to discover the approach in more depth.

Ask yourselves if you want to survive the VUCA future ahead. Do you want your organisation to have the capacity to innovate and sustain itself? Are you willing to change your thought pattern to consider the systems in which we all live in?

If the answers to any of the questions above are yes, then you are on the right path to mastering systems thinking to successfully innovate.

The more we begin to use systems thinking every day, the better our innovation will become. We can all be architects for a better world with sustainable growth if we understand the core tenants of this approach. To echo my introduction, no customer, or citizen, or business, or policy, or company, or idea itself is an island. Whatever ‘new normal’ we have, systems thinking should drive this future and will ensure innovation is pursued with knowledge of the complex intricacies that we are living through.

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World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.

The views expressed in this article are those of the author alone and not the World Economic Forum.

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• v.5(3); 2018 Oct

A systems approach to healthcare: from thinking to ­practice

John clarkson.

A Cambridge Engineering Design Centre, University of Cambridge, Cambridge, UK

B Royal College of Physicians, London, UK

C Cambridge Engineering Design Centre, University of Cambridge, Cambridge, UK

Alexander Komashie

D Cambridge Engineering Design Centre, University of Cambridge, Cambridge, UK

Tom Bashford

E Division of Anaesthesia, Department of Medicine, Addenbrooke’s Hospital, Cambridge, UK.

Medicine is increasingly complex, involving a highly connected system of people, resources, processes, and institutions. Attempts to improve care involve disruptions to this system, with the potential for wide-ranging consequences, both positive and negative. Despite this, many improvement methodologies are poorly equipped to manage either complexity or risk – instead focusing on discrete interventions whose effects are narrowly monitored. Engineers have long understood that complex problems require a systems view, and that attempts to make things better can themselves introduce new risk into a system. Given this, an engineering systems approach may be of significant value to those trying to improve healthcare. Two fundamental questions emerge from such an approach: what can we do better, and what could possibly go wrong? This paper describes the evolution of a systems approach to healthcare, and explores a recently co-developed framework outlining a systems approach based upon a synergy between healthcare and engineering.

Introduction

Healthcare is the product of a complex adaptive system of people, equipment, processes, and institutions working together. Problems can arise with either deficiencies in individual system elements, or in their relationship with each other, and improving the overall function of such a system can be challenging. 1 This insight – a systems view of healthcare – reframes our understanding as to how care is delivered and can be improved.

A striking example of this is the case of Dr Hadiza Bawa-Garba, 2,3 a paediatrician convicted of gross negligence and manslaughter in 2015 , temporarily suspended from practising medicine by a medical practitioners tribunal, and later struck off by the General Medical Council (GMC). The case has raised many questions both about how we allocate blame when systems fail and how we improve them in the future to avoid catastrophe. The British Medical Journal (BMJ) responded: ‘It is tragic that a child has died. But no one is served when one doctor is blamed for the failings of an overstretched and understaffed system.’ 4

The Bawa-Garba case highlights the complexity of direct healthcare, where the actions of an individual doctor can be contextualised within a team, a ward, and a hospital all facing deficiencies. However, it also throws into relief the wider system in play – of regulatory bodies, the legal framework within which medicine is practised, the media, and prevailing cultural attitudes toward the NHS.

‘Systems that work do not just happen, they need to be planned, designed and built.’ This is the view of the Royal Academy of Engineering, 5 experts in the design of complex systems. Engineers have long understood that well designed systems can prompt individuals toward desired behaviours, and act to restrain them from undesirable ones. This understanding is reflected in much of the medical literature around improvement from fields such as quality improvement, implementation science, and operational research. However, a consolidated systems approach to healthcare improvement has been elusive.

Critics of a systems approach to healthcare might argue that it is simply a mechanism to absolve individuals where they have made mistakes or acted inappropriately, or that it is an excuse to paint improvement as too difficult to attempt. We argue instead that a systems approach should seek to answer fundamental questions about the people involved in a given situation, the wider system in which they operate, the opportunities for risk, and what can be designed to mitigate these. There will be occasions where individuals are culpable, where machines fail, or where processes are weak; the system should be designed to reduce the possible harm which results. More optimistically perhaps, robust systems offer the opportunity for increased quality and efficiency without a commensurate increase in material resources – an increasing priority for an NHS under pressure.

Background to the need for a systems approach

The idea of a systems approach is not new. The first half of the 20th century saw a growing interest in systems and their inherent complexities in several disciplines including engineering and biology. 6 Within healthcare, however, the turn of the new millennium may be seen as a watershed in the recognition of a systems approach to improvement.

The World Health Report 2000 had a primary focus on health systems. 7 This report on global health systems began to address questions around the elements of a good health system and the monitoring of system performance. In the following few years, high profile reports were published both in the USA and the UK that were to significantly challenge the status quo and justify the need for a better approach to improving the quality of the healthcare delivery systems in these countries.

In the USA, the publication of two key reports by the Institute of Medicine (IOM) – To err is human 8 and Crossing the Quality Chasm 9 – demonstrated a disparity in the state of patient safety and the concerning discrepancy between the care that was possible and that which many patients were receiving. The revelation of these challenges within the American healthcare system were enough to raise quality of healthcare to centre stage.

Similar challenges were being described in the UK over the same period. 10–12 A report into the systematic failures that led to the deaths of nearly 30 children at the Bristol Royal Infirmary (BRI) in 2001 concluded that the poor performance and errors identified at the BRI were the results of systems which were poorly performing. 13 More importantly, the report suggested that these problems were reflective of the state of the wider NHS at the time. In response to these findings the Department of Health (DoH) made far-reaching changes to the health system with a focus on standards, performance monitoring, patient-centeredness, patient and public involvement. The response also provided opportunity for design and systems engineers to contribute to the challenges through a commitment to ‘working with the Design Council to identify opportunities for design solutions to patient safety’. 14 The Design Council also establishes the RED team to bring design thinking to healthcare improvement and transformation. 15,16

This led to the first review of design and systems practice within the NHS. The review concluded that ‘the NHS is seriously out of step with modern thinking and practice with regard to design’. 17 Since then, several reports, initiatives and models have been produced but of particular relevance is Building a Better Delivery System , the report which launched the ‘New Engineering/Health Care Partnership’. 18 More than a dozen major reports had echoed the essence of this new partnership by 2010 with many describing the heightened interest in solving problems in healthcare delivery using industrial and systems engineering tools. 19 More recently, the President’s Council of Advisors on Science and Technology (PCAST) recommended that a systems engineering approach be propagated at all levels of the health care system in the USA. 20

Several other high profile reports have consistently alluded to the need for a systems approach, although often lacking guidance on how to realise this at any level of the NHS or in the USA. 17 , 21–32 Even within the academic literature, it is difficult to find a definition or presentation of a systems approach that lends itself to pragmatic improvement efforts.

Realising a systems approach in practice

In 2016, in response to the calls to adopt a systems approach to designing and delivering high-quality services in the UK, the Royal Academy of Engineering (RAEng), in collaboration with the Royal College of Physicians (RCP) and the Academy of Medical Sciences (AMS), established a cross-disciplinary Working Group to work with the health and care professions to explore how engineers can add to current understanding and practice of systems engineering in quality improvement and healthcare design.’

To an engineer, the world is full of systems. From the simple water heater to the fully integrated international airport, all systems share one key feature: their elements together produce results not obtainable by the same elements alone. A systems approach involves integrating the necessary disciplines into a team who then use a structured process to deliver a system, working from needs to requirements and from design to delivery. 33–35 A systems approach has also been described as

…a framework for seeing interrelationships rather than things, for seeing patterns rather than static snapshots – it is a set of general principles spanning fields as diverse as physical and social sciences, engineering, and management. 36

This can be depicted as a ‘V-model’ (Fig ​ (Fig1), 1 ), which illustrates the logical relationships between different activities. However, to those unfamiliar with the language of systems engineering, the nuances and value of the V-model may be difficult to appreciate.

The INCOSE (2009) V-model.

Early discussions within the RAEng Working Group reflected on the importance of people, systems, design and risk perspectives on a system, and on the realisation that particular focus on these complementary views could deliver many of the benefits of a systems approach (Table ​ (Table1 1 ).

The elements of a systems approach

These perspectives provided the framework for a series of workshops with engineers and health and care professionals to explore the relevance of each perspective to health and care improvement and to express them as a series of open questions. These were subsequently merged with a number of project management questions to form a simple spiral (Fig ​ (Fig2), 2 ), an ordered list of questions pertinent to systems improvement. The spiral illustrates that the questions are revisted at each stage of design and delivery in an iterative manner.

A spiral model of the questions that define an iterative approach to health and care improvement.

This representation, of an idealised view of a systems approach, does little to guide how it might be used in practice. The health and care professionals consulted were more used to a linear improvement process, typified as one that transforms current performance into something measurably better (Fig ​ (Fig3). 3 ). This approach is common to all improvement processes with a focus on the critical stages required for success (Table ​ (Table2 2 ).

A linear improvement process transforming current performance into a measurably better state.

The critical stages of an improvement approach

The linear (improvement) and spiral (systems) models may be combined to generate a helical model of health and care improvement (Fig ​ (Fig4). 4 ). This resonated with health and care improvement specialists, going some way toward translating the description of a systems approach into a practical implementation guide. To help further, case studies from published work were used to illustrate the potential of a systems approach in practice, reviews of improvement approaches eg the Model for Improvement, Lean etc, and key literature were undertaken. Further background to the core concepts were provided. The final report, Engineering Better Care: a systems approach to health and care design and continuous improvement, 37 provides an accessible description of a systems approach, and how it can build on current approaches to improvement in healthcare, nearly 20 years after the first call to adopt such an approach. 17

A systems-spiral improvement process. An ordered and iterative set of activities drawn from people , systems , design and risk perspectives and linked to the spiral questions, applied at each stage of the improvement process.

A healthcare–engineering synergy

The practice of healthcare can be conceived as two objectives: to provide care, and to avoid causing harm. Similarly, engineering can be considered as the practice of solving problems, while managing the risk inherent in those solutions. A shared understanding between engineering and healthcare might then be – what can we do better, and what could possibly go wrong?

In England the New Care Models programme 38 and similar work, are showing promise in a redesigning and delivering health and care systems to meet population and system needs. These have had varying approaches to design and improvement, with varying outcomes.

The value of the systems approach put forward in Engineering Better Care is that it provides a simple framework for those trying to improve care to reflect on their efforts with a new perspective. Seeking to answer the questions posed prompts reflection on both the methodologies used, and the desired outcomes. This does not need to supplant existing methods, but instead might suggest where alternative techniques could add value. The ongoing challenge is to bring this framework to bear on real problems, in partnership with those already striving to make things better.

Further work is now underway to develop a practical toolkit that transforms the systems approach into practice (Fig ​ (Fig5). 5 ). The focus here is on the definition of a range of simple but effective interventions to identify a real need, define a problem and a business case for change, develop viable solutions and deliver the preferred solution into practice.

An Engineering Better Care toolkit, facilitating a systems approach to health and care improvement.

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8 Soft systems methodology

Learning Outcomes

• Contextualise systems as a ‘Wholistic’ project management method approach.
• Compose the requirements for a Systems Lens application.
• Formulate Soft Systems Methodology frameworks.

This module will explore a systems approach to integrating all the different components within the project environment, to create a comprehensive approach to solving the problem.

Broadly speaking, a systems approach is used to create an understanding of the interrelationships between different components within the environment, the project, and the stakeholders. Through a generalisation of the different components, the project team is better able to understand the interdependent nature of the factors (Cleland 1997; Meredith and Mantel 2011; Kerzner 2017). Additionally, the systems approach allows the project team to understand the situation in its entirety, including resources, materials, market conditions, organisational needs, stakeholders and so forth. By understanding these factors, the project is better able to meet the project objectives and keep the end-state in mind throughout, to ensure that the approach is the most efficient and effective process possible.

This is a disciplined way to view the environment and identify potential solutions to problems while being open to opportunities. These opportunities can be realised through understanding that everything is related to everything else in the environment or organisation.

A system is a composition of numerous related and dependent components which, through interactions with one another, create a whole. Therefore, a system is a compilation of distinct factors or components which form a complex whole. Although this definition is general, a key element of a system is how the collection of factors or components come together to produce an outcome (INCOSE 2015). This outcome is not attainable by the individual elements – an outcome can only be created  through the interactions between and across the components and factors.

By applying a systems approach to project management, the view of the project changes from a set of tasks and activities to a combination of sub-systems which work together to make a broader system (Cleland 1997; Meredith and Mantel 2011; Kerzner 2017). The broader system’s effectiveness and performance is impacted by the corresponding performance of the sub-systems of which it is comprised. Therefore, by viewing the project management process as a system which operates as an entity comprised of sub-systems, project managers can identify areas within the project which could lead to success or failure. However, the sub-systems which comprise the project are not limited to internal factors within the organisation – external components or factors play a significant role within the systems approach.

Through a systems approach, a project manager, project team and the broader project organisation are empowered to consider the impacts of the environment when implementing changes or projects. The context surrounding the project should be established at the outset as this will provide a viewpoint of the system. This viewpoint will support decision-making throughout the project, encourage realignment of resources as needed and trigger changes in response to the environment.

Considerations

Before a project manager considers applying a systems approach (Cleland 1997; Meredith and Mantel 2011; Kerzner 2017), there are several components which need to be considered:

• How all tasks, activities, processes, and deliverables within the project depend on one another needs to be documented. However, consideration is needed to understand the properties of the individual components outside of their dependencies.
• Project goals need to be clear; each component of the project should be working towards those goals.
• Resources supporting the project should be consistent throughout. Where additional resources are required, the impacts on the outcome need to be considered. This includes impact on quality, scope, budget, and schedule.
• Uncertainty is expected within a project. Consideration is required to provide support in managing and responding to uncertainty as it arises (for example, risk and issues management processes).
• Resources should be allocated roles and responsibilities based on their skills and experience. These resources can work together as part of a sub-project team, to support the development of different deliverables. For each deliverable, a different approach may be required to manage the needs and complexities.
• Visualisation can be used to support documenting the complexities.

Through a systems approach, project managers are supported to ensure they are aiming for the project’s goals and objectives.

Let’s watch the following video by Systems Innovations which explains the primary differences between analytical methods of reasoning and systems thinking

Video [5 mins,  41 sec]   Note: Closed captions are available by selecting the CC button in the video below.

How to apply a systems approach

In addition to using traditional project management methodologies, the systems approach can be used to effectively manage a project. Based on systems theory, there are 4 primary tools and principles which can be applied from the Systems Thinking Iceberg, recreated in Figure 28.

Figure 28. Systems Thinking Iceberg, by Carmen Reaiche and Samantha Papavasiliou, licensed under CC BY (Attribution) 4.0

Based on Figure 28, below are 4 principles and tools which can be applied to projects to support the systems approach to project management (Cleland 1997; Meredith and Mantel 2011; Kerzner 2017).

•  a detailed problem statement
•  triggers, causes and side-effects
•  the reactions of the different stakeholders
•  links between problems and solutions previously attempted.
•  when it occurs (frequency)
•  who has been impacted
•  steps taken to rectify
•  interactions between the event and other factors or events
•  identifying potential causes
•  testing potential solutions.
•  environmental elements within the system
•  causes of the behavioural patterns
•  stakeholders within the system
•  underlying interactions between stakeholders, environment, and causes.
•  what supports the underlying structure
•  the values, expectations, and beliefs within the system and broader environment
•  how the problem is understood
•  the proposed solutions and how will they be implemented and analysed.

Systems approaches can be applied through a cyclical method which considers the relationships between each component of a project phase. See Figure 29 for examples.

Figure 29.  Examples of the cyclical approach that can be used to support systems approaches to project management, by Carmen Reaiche and Samantha Papavasiliou, licensed under CC BY (Attribution) 4.0

By applying the systems approach, organisations can understand the interactions between different areas, documents, and tasks and activities. By using a systems approach:

• Project managers are able to realise the need for a holistic approach to prepare, plan, and implement a project.
• The multidimensional components which have an impact on the outcomes of a project (for example, technological, financial, resources, cultural, etc.) can be documented.
• Project managers can understand how different dimensions or structural components will influence the stakeholders and their expectations, and how the market and environment can change swiftly and significantly. This is commonly in response to economic factors, ecological issues, stakeholder values, news cycles and so forth.
• The end-to-end interactions between tasks, activities, resources, stakeholders and so on, are considered and work together to reach the common goals and objectives of the broader system (or the project).

Therefore, when the systems approach is applied to a project, project managers are better able to respond to the conditions outside of their control, and create efficiencies within their projects boundaries to maximise outcomes.

Soft Systems Method

Soft Systems Methodology (SSM) is an approach which is used to create structure in complex problems and develop changes which are both feasible for and wanted by all the stakeholders. These stakeholders include internal stakeholders (employees, developers) and external stakeholders (users, clients, competitors). As a result, everyone provides different insights into and solutions to solve a problem (Checkland and Scholes 1990; Checkland 2000; Checkland and Poulter 2006).

To support the understanding of SSM, a soft system can be defined as a human activity system (HAS). This HAS is purposeful and organised in that groups of people work collectively to achieve a purpose or outcome.

SSM was designed to allow each heterogeneous group of stakeholders the opportunity to provide their insights into the problem. Each group or stakeholder can document the problem in their own way and provide their insights into feasible or desirable outcomes or solutions (Checkland 2000).

Through collaboration, a solution can be created that is agreed upon by all stakeholders. It supports quicker decision-making through consensus. The approach is used to show the links between the real world and the considerations and components documented within the systems world.

The 7 steps to SSM

There are 7 steps to SSM (see Figure 30). These steps are not necessarily carried out in linear order and some steps may not need to be completed. These steps should be used to support collaboration, decision-making and problem-solving.

Figure 30. SSM 7 steps, by Carmen Reaiche and Samantha Papavasiliou, licensed under CC BY (Attribution) 4.0

Step 1. Identify the problem situation  

This step involves gathering relevant information to understand the problem situation. There are several tools which can be used to support information gathering (Checkland and Scholes 1990; Checkland 2000; Checkland and Poulter 2006), including:

•  interviews
•  brainstorming sessions
•  historical and current data
•  news articles
•  document analysis
•  organisational structure
•  control policies
•  observation sessions.

Through the information gathered, analysis should support understanding the possible components and factors which could influence or impact the problem situation.

Let’s go through the rest of the steps using a sample organisation: Lugano. Lugano is a financial firm that offers digital services to clients. This organisation is experiencing decreased overall use of digital services and significant increases in the need for support provided by frontline employees by telephone. It is unclear what is causing this increased need for support. Information is gathered via employee and user feedback, data and document analysis. Lugano will  be used as an example in the following step.

Step 2. Describe the problem situation

From Step 1, the analyst has sufficient information to understand the problem space and document the situation through pictures or diagrams. The tool recommended in SSM is the rich picture diagram (Checkland and Scholes 1990; Checkland 2000; Checkland and Poulter 2006). This diagram outlines the problem situation using a graphical representation of the different relationships, communication mechanisms, processes, structure, people, concerns, conflict, and climate. A rich picture can incorporate images, text, symbols, and icons.

Figure 31 provides an example of part of a rich picture. This example highlights Lugano’s relationships between the digital services provided to users, and the support mechanisms in place to provide guidance when needed. The problem situation Lugano is the increased requirement for support and the decreased use of digital services. The problems highlighted in Lugano’s example include the need for skills development and training for users, accuracy and relevance of information and records provided, and access to services.

Figure 31.  Example rich picture from a digital service offering perspective, by Carmen Reaiche and Samantha Papavasiliou, licensed under CC BY (Attribution) 4.0

Step 3. Develop key definitions

Once the rich picture has been created, the next step is to determine the best way for the system to function. This process starts with creating root definitions which provide an ideal view of the key systems and structures (Checkland and Scholes 1990; Checkland 2000; Checkland and Poulter 2006). This commonly follows the CATWOE elements (Checkland and Scholes 1990; Checkland 2000; Checkland and Poulter 2006). Using the sample organisation:

Customers: Who are Lugano’s clients, and the users, stakeholders, and key players within a system?

Actors: Who are the employees within the organisation who support the transformation process?

Transformation: Which process will be transformed by Lugano, specifically considering what the output is and how the problem will be solved?

Worldview/Weltanschauung: What is the bigger picture or the environmental view of the situation, specifically the stakeholders within the environment who can influence the transformation?

Owners: Who within Lugano can make the changes or has the power to approve the start and end of the project or transformation?

Environmental constraints: What are the elements within the environment which influence Lugano and have the capacity to impact the system negatively, and how should they be managed?

CATWOE supports the creation of the root definition, which is defined as the representation of the problem situation to be addressed. Therefore, a root definition is defined as a statement which concisely and clearly describes the system of interest (or under review). It commonly starts with a single sentence that begins with ‘A system to’ followed by ‘all key elements of the system’.

Table 7. A CATWOE example using Lugano

Table 8. A root definition example using Lugano

Tables 7 and 8 provide an example of CATWOE and creating the root definition for the digital service example. This example shows the key players and the aim of the transformation within the root definition. Through this approach, the problem became clearer, and the system of interest became the digital service and surrounding environment.

When applying SSM its important to understand the transformation component correctly, especially in relation to inputs and outputs (Checkland and Scholes 1990; Checkland 2000; Checkland and Poulter 2006). This is outlined in Figure 32, which shows that Input (I) should support the transformation and lead to the Output (O). A common mistake is incorrectly identifying the system input (the entity change) with the resources required to implement the change.

Figure 32. Inputs create transformation which leads to outputs, by Carmen Reaiche and Samantha Papavasiliou, licensed under CC BY (Attribution) 4.0

Forbes and Checkland (1987) provided some definitions and rules to support the documentation of the transformation:

•  (T) transforms the Input (I) into Outputs (O).
•  The input must be present in the output; however, it will be in a different or changed state.
•  An abstract (intangible) input will create an abstract (intangible) outcome.
•  A tangible (concrete) input will create a tangible (concrete) output.

Step 4: Create conceptual models

This step requires creating a conceptual model which is used to analyse the activities which need to occur to undertake the transformation. The activities outlined should only be based on actions taken by actors (internal to the organisation). These activities need to link back to the root definition and be limited to a project group to control (Wilson 2001). All activities need to achieve the objectives of the transformation, and activities must include monitoring the transformation and providing feedback. It should consider what is meant by success, how it is measured and who will measure it.

The key activities required for the digital services example include:

• Determine what factors influence digital service use.
• Assess actions required to improve these.
• Take action.
• Measure behavioural change.
• Measure impact of change on the environment.
• Report results.
• Monitor and manage the system performance, recommend improvements.

Figure 33. Example draft of the digital services conceptual map, by Carmen Reaiche and Samantha Papavasiliou, licensed under CC BY (Attribution) 4.0

As outlined in Figure 33, there are clear operational activities which need to be taken to activate the transformation. Each activity should be monitored to ensure it is easy to follow and that there is a clear process in place. The conceptual model outlined in Figure 33 is in draft state – it shows a starting point for developing a complete model.

Within a conceptual model, Forbes and Checkland (1987) recommended:

•  having 7+/-2 activities of the same size
•  describing each activity using a verb
•  using arrows to show logical dependencies
•  numbering activities to reaffirm the dependencies.

Conceptual models are made to document HAS, which are softer models (Tavella and Hjortso 2012). This is because it is difficult for human behaviour to repeat and reproduce the same actions repeatedly with the same results. Therefore, there is an innate variability in the human activities and performances outlined within the conceptual models. These still require monitoring and controlling to support the transformation and ensure that changes are made as required. The overarching structure of a HAS is outlined in Figure 34, and this approach can be used to support improvements to the conceptual model. This calls out the operational system within the organisation’s control (operational subsystem) and the elements which occur outside of the direct control of the organisation, this being the response to the implemented change. These are tracked and monitored and as changes are required, they are implemented.

Figure 34. HAS overarching structure, by Carmen Reaiche and Samantha Papavasiliou, licensed under CC BY (Attribution) 4.0

This monitoring and controlling process should follow the 3Es: effective, efficient, efficacy (Wilson 2001; Checkland 2000). When planning, the transformation needs to consider:

•   Effective : Is the system acting in the way it should be? Does the system contribute to the broader organisational goals?
•   Efficient : Does the system use the least number of resources? Does it use the resources appropriately?
•   Efficacy : Does the system provide the expected results?

Using the 3Es, a project manager is better equipped to determine what level of monitoring and controlling is required and how it could be completed.

Another critical component of a conceptual model is the use of feedback loops (Checkland 2000; Wilson 2001). Within conceptual models, there are commonly two forms:

•  Internal feedback loop. This loop highlights how the actors (or the individual completing the work) need to alter how they work to meet the transformation.
•  External feedback loop. This loop looks at the links between the inputs and the outputs, specifically interested in how the system is performing.

Therefore, an effective project manager needs to clearly define their success measures for the transformation and ensure that they are built into the system.

Step 5. Compare conceptual models to reality

Conceptual models are developed through applying theory; however, they are not necessarily representative of reality. Therefore, Step 5 requires an understanding of how much these models reflect the real world (Checkland 2000; Wilson 2001). This requires an analysis of the gaps, to determine whether the provided solution will meet the needs. This analysis is required to understand:

•  conceptual model activities
•  the real world
•  what can be completed.

Table 9 is an example of the analysis for the digital services transformation, using 3 columns based on the above analysis questions.

Table 9. Example conceptual model vs. real world comparison (digital services example)

Step 6. Assess feasibility and define changes

Based on the results of Step 5, a feasibility assessment is required of the suggested changes (Checkland 2000; Wilson 2001). The changes are normally classified as a change in:

•  procedures and processes
•  attitudes or behaviours.

This requires an analysis of 3 primary elements: feasibility, priorities and risk analysis.

Feasibility

Feasibility requires understanding how the different activities will be undertaken. A feasibility analysis will need to consider whether something is achievable (Checkland and Scholes 1990; Checkland 2000; Checkland and Poulter 2006), based on:

•  Cultural feasibility: Will the employees or actors involved be able to complete the work?
• Technical feasibility: What is the required support or modern technology required to implement the change?
•  Dependencies: Are there links between the organisational and technological systems? What order do updates need to go in?
•  Win-Win: Do the recommended changes make it easier for the organisation, employees, and clients?

This is a vital component; the changes need to be prioritised based on what impact they will have on the desired transformation, what risks they pose and how difficult they will be to implement. This can follow Kaplan and Norton’s (1993) balanced scorecard approach – an example of factors is outlined in Figure 35.

Figure 35. Example of the balanced scorecard for the digital services example, by Carmen Reaiche and Samantha Papavasiliou, licensed under CC BY (Attribution) 4.0

According to Kaplan and Norton (1993) there are 4 primary elements within the balanced scorecard and successful organisations, projects, and transformation find a balance between each of these components.  Each component provides a different view of the organisation to operate efficiently and effectively. These components are:

• Financial perspective: outlines the different cost measures involved in the organisation, project and or change.
• Client perspective: outlines how client satisfaction, retention and market share will be measured and improved.
• Internal processes perspective: outlines what the change will cost and how it will impact the quality of the internal business processes.
• Innovative perspective: outlines measures of employee satisfaction, knowledge management, improvement rates and number or percentage of employees included in the improvement.

These 4 components or perspectives are interlinked – they do not function in isolation. Using the scorecard approach, the factors within the perspectives need to consider:

•  objectives: organisational objectives and strategies
•  measures: following the objectives, how you will measure progress
•  targets: what is the objective aiming to achieve
•  initiatives: actions taken to meet the objectives.

Risk analysis

The third tool to support feasibility assessment is the completion of a risk assessment. Risk analysis is the process which determines the likelihood and impact of a risk occurring. The assessment considers how the risk will impact the project schedule, quality, budget, and scope. The analysis technique recommended in SSM is the risk analysis matrix.

The risk analysis matrix assesses the likelihood of a risk occurring and the overall severity if it were to occur. These are classified by importance and impact. Likelihood and consequence (impact) are measured as low, medium, high, or very high (Vose 2008), as shown in Figure 36.

Figure 36. Example of a risk analysis matrix, by Carmen Reaiche and Samantha Papavasiliou, licensed under CC BY (Attribution) 4.0

Each risk should be identified, analysed, and considered as part of the feasibility assessment.

To complete the assessment, the project manager should understand the potential feasibility of the changes, the priority of each change and the level of risk associated. This should be used as a guide to help determine which changes should be implemented.

Step 7. Take action to implement proposed changes

The final step is to implement the proposed and agreed upon changes (as outlined in Step 6). The implementation should follow the required steps outlined within the conceptual model (and reality analysis). Once implemented, there is a potential for the system changes to provide new opportunities and problems that require responses. As a result, the process would need to start again.

Advantages of SSM

There are several advantages to applying SSM, including:

• provides a structure for complex problems or situations
• easy to follow steps
• rigorous testing required
• encourages multiple iterations.

Disadvantages of SSM

There are several potential disadvantages to applying SSM, including:

• requires organisational change, which can be difficult to convince stakeholders of
• solutions can be narrowed down too early
• rich pictures are challenging to create, due to their lack of structure
• actions are expected quickly; however, the process can be time consuming.

In sum, SSM provides an analysis tool and technique which outlines the different requirements for the system transformation. This module outlines the 7 primary steps required to implement the methodology. SSM is a systems approach which can be used to undertake problem-solving and analysis of complex situations. Therefore, a cycle of research, learning and reflection is recommended based on the perceptions of all the stakeholders to better provide solutions for the problem space.

Test your knowledge

Key Takeaways

• A system is composed of numerous related and dependent components which, through interactions with one another, create a whole. Therefore, a system is a compilation of distinct factors or components which form a complex whole.
• By viewing the project management process as a system which operates as an entity comprised of sub-systems, project managers can identify areas within the project which could lead to success or failure.
• Systems approaches can be applied through a cyclical approach which considers the relationships between each component of a project phase.
• SSM is used to create structure in complex problem and then develop changes which are both feasible for and wanted by all the stakeholders.

Checkland P and Poulter J (2006) Learning for action: a short definitive account of soft systems methodology and its use, for practitioners, teachers, and students , John Wiley and Sons Ltd, United States.

Checkland P (2000) ‘Soft systems methodology: a thirty year retrospective’, Systems Research and Behavioral Science , 17(S1):S11–S58.

Checkland P and Scholes J (1990), Soft systems methodology in action , vol. 7, Wiley, Chichester.

Cleland DI (1997) ‘Defining a project management system’, Project Management Quarterly , 8(4):37–40.

Forbes P and Checkland PB (1987) ‘Monitoring and control in systems models’, Internal Discussion Paper 3/87, Department of Systems, University of Lancaster.

INCOSE (2015) INCOSE systems engineering handbook: a guide for system life cycle processes and activities , 4th edn, Wiley, United States.

Kaplan RS and Norton DP (1993) ‘Putting the balance scorecard to work’, Harvard Business Review Magazine , Sep/Oct, accessed 3 August 2022. https://hbr.org/1993/09/putting-the-balanced-scorecard-to-work

Kerzner H (2017) Project management: a systems approach to planning, scheduling, and controlling , 12th edn, Wiley, United States.

Meredith JR and Mantel Jr SJ (2011) Project management: a managerial approach , John Wiley & Sons.

Tavella E and Hjortsø C (2012). ‘Enhancing the design and management of a local organic food supply chain with soft systems methodology,’ International Food and Agribusiness Management Review ,  15(2): 47–68.

Vose D (2008) Risk analysis: a quantitative guide , 3rd edn, Wiley, United States.

Wilson B (2001) Soft systems methodology conceptual model building and its contribution , Wiley, United States.

Management Methods for Complex Projects Copyright © 2022 by Carmen Reaiche and Samantha Papavasiliou is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

Systems Approach to “Problem Solving”

Cite this chapter.

• Robert L. Flood 3 &
• Ewart R. Carson 4  

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Much of humanity’s efforts in the developed and developing world aim to overcome the “problems” created by changes in science, technology and the effects of these on society. Knowledge gained by traditional and systems sciences has been implemented in technological developments and devices. This has often led to unforeseen consequences such as pollution, unemployment, and scarcity of resources. Efficient and effective technical expertise is required to plan and design to overcome these difficulties. Chapter 5 presented one contribution from systems science. Often, however, such requirements involve hard decisions to be made. More often than not, a conflict of interests arises. New approaches are needed to help to manage that conflict. In this chapter, which continues to develop Theme C, we introduce a number of these approaches to “problem solving” each able to contribute in particular ways to deal with the complexities of modern society. Let us first set the scene.

• Problematic Situation
• System Methodology
• Constitutive Rule
• Problem Context
• Soft System Methodology

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Home » Management Information Systems » Systems Approach to Problem Solving

Systems Approach to Problem Solving

The systems approach to problem solving used a systems orientation to define problems and opportunities and develop solutions. Studying a problem and formulating a solution involve the following interrelated activities:

• Recognize and define a problem or opportunity using systems thinking.
• Develop and evaluate alternative system solutions.
• Select the system solution that best meets your requirements.
• Design the selected system solution.
• Implement and evaluate the success of the designed system.

1.  Defining Problems and Opportunities

Problems and opportunities are identified in the first step of the systems approach. A problem can be defined as a basic condition that is causing undesirable results. An opportunity is a basic condition that presents the potential for desirable results. Symptoms must be separated from problems. Symptoms are merely signals of an underlying cause or problem.

Symptom: Sales of a company’s products are declining. Problem: Sales persons are losing orders because they cannot get current information on product prices and availability. Opportunity: We could increase sales significantly if sales persons could receive instant responses to requests for price quotations and product availability.

2. Systems Thinking

Systems thinking is to try to find systems, subsystems, and components of systems in any situation your are studying. This viewpoint ensures that important factors and their interrelationships are considered. This is also known as using a systems context, or having a systemic view of a situation. I example, the business organization or business process in which a problem or opportunity arises could be viewed as a system of input, processing, output, feedback, and control components. Then to understand a problem and save it, you would determine if these basic system functions are being properly performed.

The sales function of a business can be viewed as a system. You could then ask: Is poor sales performance (output) caused by inadequate selling effort (input), out-of-date sales procedures (processing), incorrect sales information (feedback), or inadequate sales management (control)? Figure  illustrates this concept.

3. Developing Alternate Solutions

There are usually several different ways to solve any problem or pursue any opportunity. Jumping immediately from problem definition to a single solution is not a good idea. It limits your options and robs you of the chance to consider the advantages and disadvantages of several alternatives. You also lose the chance to combine the best points of several alternative solutions.

Where do alternative solutions come from/ experience is good source. The solutions that have worked, or at least been considered in the past, should be considered again. Another good source of solutions is the advice of others, including the recommendations of consultants and the suggestions of expert systems. You should also use your intuition and ingenuity to come up with a number of creative solutions. These could include what you think is an ideal solution. The, more realistic alternatives that recognize the limited financial, personnel, and other resources of most organizations could be developed. Also, decision support software packages can be used to develop and manipulate financial, marketing, and other business operations. This simulation process can help you generate a variety of alternative solutions. Finally, don’t forget that “doing nothing” about a problem or opportunity is a legitimate solution, with its own advantages and disadvantages.

4. Evaluating Alternate Solutions

Once alternative solutions have been developed, they must be evaluated so that the best solution can be identified. The goal of evaluation is to determine how well each alternative solution meets your business and personal requirements. These requirements are key characteristics and capabilities that you feed are necessary for your personal or business success.

If you were the sales manager of a company, you might develop very specific requirements for solving the sales-related information problems of your salespeople. You would probably insist that any computer-based solution for your sales force be very reliable and easy to use. You might also require that any proposed solution have low start-up costs, or have minimal operating costs compared to present sales processing methods.

Then you would develop evaluation criteria and determine how well each alternative solution meets these criteria. The criteria you develop will reflect how you previously defined business and personal requirements. For example, you will probably develop criteria for such factors as start-up costs, operating costs, ease of use, and reliability. Criteria may be ranked or weighted, based on their importance in meeting your requirements.

5. Selecting the Best Solution

Once all alternative solutions have been evaluated, you can being the process of selecting the best solution. Alternative solutions can be compared to each other because they have been evaluated using the same criteria.

Alternatives with a low accuracy evaluation (an accuracy score less than 10), or a low overall evaluation (an overall score less than 70) should be rejected. Therefore, alternative B for sales data entry is rejected, and alternative A, the use of laptop computers by sales reps, is selected.

6.  Desingning and Implementing Solution

Once a solution has been selected, it must be designed and implemented. You may have to depend on other business end users technical staff   to help you develop design specifications and an implementation plan. Typically, design specifications might describe the detailed characteristics and capabilities of the people, hardware, software, and data resources and information system activities needed by a new system. An implementation plan specifies the resources, activities, and timing needed for proper implementation. For example, the following items might be included in the design specifications and implementation plan for a computer-based sales support system:

• Types and sources of computer hardware, and software to be acquired for the sales reps.
• Operating procedures for the new sales support system.
• Training of sales reps and other personnel.
• Conversion procedures and timetable for final implementation.

7.  Post Implementation Review

The final step of the systems approach recognizes that an implemented solution can fail to solve the problem for which it was developed. The real world has a way of confounding even the most well-designed solutions. Therefore, the results of implementing a solution should be monitored and evaluated. This is called a postimple-implemented. The focus of this step is to determine if the implemented solution has indeed helped the firm and selected subsystems meet their system objectives. If not, the systems approach assumes you will cycle back to a previous step and make another attempt to find a workable solution.

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Header Right

Systems approach to problem solving.

By Dinesh Thakur

Systems approach is widely used in problem solving in different contexts. Researchers in the field of science and technology have used it for quite some time now. Business problems can also be analyzed and solved using this approach. The following steps are required for this:

We’ll be covering the following topics in this tutorial:

Defining the Problem

This is the step when the problem has to be defined. Sometimes one may confuse the symptoms or the exhibition of a behavior to be a problem but actually it may only be a symptom of a larger malaise. It may just exhibit the behavior of a larger phenomenon. It is vital to drill deep into an issue and clearly understand the problem rather than having a superficial understanding of the problem. One must appreciate that this in the initial stage of problem solving and if the problem itself is not correctly diagnosed then the solution will obviously be wrong. Systems approach is therefore used to understand the problem in granular detail to establish requirement and objectives in-depth. By using the systems approach the problem will be analyzed in its totality with inherent elements and their interrelationships and therefore this detailed analysis will bring out the actual problem and separate out the symptom from it.

Developing Alternative Solutions

This the logical next step in the systems approaches for problem solving. In this stage alternative solutions are generated. This requires creativity and innovation. In this stage-the analyst uses creativity to come up with possible solutions to the problem. Typically in this stage only the outline of solutions are generated rather than the actual solutions.

Selecting a Solution

In this step, the solution that suits the requirement and objectives in the most comprehensive manner is selected as the ‘best’ solution. This is done after evaluating all the possible solutions and then comparing the possible set of solutions to find the most suitable solution lot of mathematical, financial and technical models is used to select the most appropriate solution.

Designing the Solution

Once the most appropriate solution is chosen, it is then made into a design document to give it the shape of an actionable solution, as in the evaluation stage, only the outline of the solution is used. At this stage the details of the solution are worked out to create the blueprint for the solution. Several design diagrams are used to prepare the design document. At this stage the requirement specifications are again compared with the solution design to double check the suitability of the solution for the problem.

Implementing the Solution

It is the next step in the process. The solution that has been designed is implemented as per the specifications -laid down in the design document. During implementation care is taken to ensure that there are no deviations from the design.

Reviewing the Solution

This is the final step in the problem solving process where the review of the impact of the solution is noted. This is a stage for finding out if the desired result has been achieved that was set out.

A Systems Approach Example

Let us assume that A is the coach of the Indian cricket team. Let us also assume that the objective that A has been entrusted with is to secure a win over the touring Australian cricket team. The coach uses a systems approach to attain this objective. He starts by gathering information about his own team.

Through systems approach he views his own Indian team as a system whose environment would include the other team in the competition, umpires, regulators, crowd and media. His system, i.e., team itself maybe conceptualized as having two subsystems, i.e., players and supporting staff for players. Each subsystem would have its own set of components/entities like the player subsystem will have openers, middle order batsmen, fast bowlers, wicket keeper, etc. The supporting staff subsystem would include bowling coach, batting coach, physiotherapist, psychologist, etc. All these entities would indeed have a bearing on the actual outcome of the game. The coach adopts a systems approach to determine the playing strategy that he will adopt to ensure that the Indian side wins. He analyses the issue in a stepwise manner as given below:

Step 1: Defining the problem-In this stage the coach tries to understand the past performance of his team and that of the other team in the competition. His objective is to defeat the competing team. He realizes that the problem he faces is that of losing the game. This is his main problem.

Step 2: Collecting data-The coach employs his supporting staff to gather data on the skills and physical condition of the players in the competing team by analyzing past performance data, viewing television footage of previous games, making psychological profiles of each player. The support staff analyses the data and comes up with the following observations:

• Both teams use an aggressive strategy during the period of power play. The competing Australian team uses the opening players to spearhead this attack. However, recently the openers have had a personal fight and are facing interpersonal problems.
• The game is being played in Mumbai and the local crowd support is estimated to be of some value amounting to around fifty runs. Also the crowd has come to watch the Indian team win. A loss here would cost the team in terms of morale.
• The umpires are neutral and are not intimidated by large crowd support but are lenient towards sledging.

Step 3: Identifying alternatives-Based on the collected data the coach generates the following alternate strategies:

• Play upon the minds of the opening players of the competitors by highlighting their personal differences using sledging alone.
• Employ defensive tactics during power play when the openers are most aggressive and not using sledging.
• Keep close in fielders who would sledge and employ the best attacking bowlers of the Indian team during the power play.

Step 4: Evaluating alternatives-After having generated different alternatives, the coach has to select only one. The first alternative may lead to loss of concentration on the part of openers and result in breakthroughs. However, there is a chance that the interpersonal differences between the two openers may have already been resolved before they come to the field and in such a case this strategy will fail. The second strategy provides a safer option in the sense that it will neutralize the aggressive game of the openers but there is limited chance of getting breakthroughs. The third option of employing aggressive close in fielders to play upon the internal personal differences of the openers and at the same time employing the best bowlers may lead to breakthroughs and may also restrict the aggressive openers.

Step 5: Selecting the best alternative-The coach selects the third alternative as it provides him with the opportunity of neutralizing the aggressive playing strategy of the openers as well as increases the chances of getting breakthrough wickets.

Step 6: Implementing and monitoring-The coach communicates his strategy to his players and support staff, instructs support staff to organize mock sessions and tactics to be employed to make the strategy a success. The players and support staff performance is monitored by the coach on a regular basis to ensure that the strategy is employed perfectly.

Simplifying a System or Applying Systems Approach For Problem Solving

The easiest way to simplify a system for better understanding is to follow a two-stage approach.

Partitioning the System into Black Boxes

This is the first stage of the simplification process, in this stage the system is partitioned into black boxes. Black boxes need limited knowledge to be constructed. To construct a black box one needs to know the input that goes into it, the output that comes out of it and its function. The knowledge of how the functionality is achieved is not required for constructing a black box. Black box partitioning helps in the comprehension of the system, as the entire system gets broken down into granular functionalities of a set of black boxes.

Organizing the Black Boxes into Hierarchies

This is the second stage of the simplification process, in this stage the black boxes constructed in the earlier phase are organized into hierarchies so that the relationships among the black boxes is easily established. Once, a hierarchy of the black boxes is established, the system becomes easier to understand as the internal working of the system becomes clearer.

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Dinesh Thakur is a Freelance Writer who helps different clients from all over the globe. Dinesh has written over 500+ blogs, 30+ eBooks, and 10000+ Posts for all types of clients.

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