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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

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.

concept maps

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.

behavior over time

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.

concept maps

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.

systems thinking

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.

systems thinking solving complex problems

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

systems thinking solving 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

systems thinking solving complex problems

Thank you so much Misi for the helpful information.

systems thinking solving complex problems

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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Taking a systems thinking approach to problem solving

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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So you have what appears to be an unsolvable problem on your hands. It’s an important issue that’s proven to be chronic, its recurrence has made it familiar enough to be identified with a known history, and many have unsuccessfully tried to solve it before.

What you have is a complex problem. Fortunately, a tested strategic approach already exists for solving complex problems - systems thinking .

Systems thinking

What is Systems Thinking?

Founded in 1956 by MIT professor Jay Forrester, systems thinking is an approach to solving complex problems by understanding the systems that allow the problems to exist. You have a complex problem when:

  • There’s no clear cut agreement on what the problem really is because the context it depends on evolves over time.
  • It’s difficult to assess what the real causes are behind the problem due to many factors and feedback loops influencing each other.
  • It’s not certain what the best steps are to solve the problem because there are many potential and / or partial solutions that may require incompatible and even conflicting steps.
  • It’s hard to pinpoint who has sufficient - ownership, accountability, and authority to solve the problem, or if there even is just a single individual that suits the criteria — and it’s challenging to keep various stakeholders from getting in each others' way.

Where traditional analysis zooms into a smaller piece of a whole, systems thinking zooms out to view not just the whole, but other wholes that are affecting each other. Through this approach, systems thinking formalizes methods, tools, and patterns that allow practitioners to understand and manage complex settings and environments. This is why systems thinking is important — and effective — in solving complex problems.

3 Unique Systems Thinking Benefits

Like other established approaches to solving different kinds of problems, systems thinking can prove insightful and effective when used properly. Beyond those general benefits, systems thinking also presents some unique advantages:

Systems Thinking Allows Meaningful Failure

Failure is a discovery mechanism in properly applied systems thinking. It allows you to learn and improve the design or implementation of your solution. Failure in systems thinking can:

  • Allow you to learn and adapt from small missteps quickly.
  • Shows you the right option, or at least reduces the wrong ones, when it comes time to test hypotheses.
  • Only temporarily hamper a system, not completely jeopardize it, in exchange for meaningful input.

Systems Thinking is Inclusive and Collaborative

Because of the holistic viewpoint taken in systems thinking, it inherently opens up levers for collaboration across involved parties. It isn’t just nice to gain input from diverse stakeholders with dynamically interrelated roles and interests — it's required.

Implemented properly, systems thinking encourages a culture of inclusiveness and collaboration to fix systemic problems that in turn benefit multiple stakeholder teams simultaneously.

Systems Thinking Provides Actionable Foresight

Part of why complex problems are hard to solve is because each involved party only ever sees their portion of the issue. Therefore, they typically execute solutions that resolve parts of the constantly evolving problem, which in the holistic view may even lead to other issues or complications.

Systems thinking allows you to predict how systems change and how steps within parts of the system will impact the whole. In applying systems thinking, you analyze causal structure and system dynamics, assess policies and scenarios, and test action steps and hypotheses to foresee consequences in order to synthesize long-term strategies.

Solving Complex Problems with System Thinking Frameworks and Methodologies

So how do you use systems thinking and its frameworks and methodologies in your organization? Systems thinking is not an instant panacea. Implementing its methods and frameworks isn’t like applying smart charts to raw data on spreadsheets. Those aren’t complex problems.

The implementation of systems thinking involves the application of frameworks that illustrate levels of thinking, and the use of tools to allow people to better understand the behaviors of systems.

The Iceberg Framework

At a primary level, systems thinking takes a holistic view to try and understand the connectedness and interactions of various system components, which themselves could be sub-systems. You can start by focusing on points that people gloss over, and attempt to explore these issues by focusing on aspects you don’t understand. The iceberg framework in systems thinking can guide you through this.

The Iceberg Framework

The iceberg framework illustrates four levels of thinking about a problem, arranged thus:

  • “Events” - Events form the tip of the iceberg. Events that characterize a complex problem are the most visible, and therefore also the ones that appear to require being addressed in an immediate, reactionary way. This level of thinking is the “shallowest,” as typically events are only symptoms of underlying issues.
  • “Patterns and trends” - Directly below the tip of the iceberg, the Patterns level is the first one hidden from view. Thinking deeper about events can lead problem solvers to more insight into patterns and trends that lead to them. Any approaches to solving patterns and trends will more effectively resolve events.
  • “Underlying structure” - Even deeper below the surface, you’ll find there are underlying structures that influence the patterns and trends that lead to the visible symptoms of complex problems. This is where the interaction between system components produces the problematic patterns that in turn cause the visible events.
  • “Mental models” - Finally, the bottom of the iceberg that props everything up are the assumptions, beliefs, and values held about a system culminating in the inadvertent creation and maintenance of underlying structures that result in unfavorable patterns within systems, which in turn bubble up to the surface as symptomatic events.

Once systems thinking practitioners understand this framework, they can employ tools and technology that allow human perception to genuinely digest the behavior of complex systems. At this level of systems thinking, qualitative tools generate knowledge to unravel complex problems.

Causal Loop Diagrams and System Archetypes

Some of the most common and flexible tools in systems thinking are causal loop diagrams that demonstrate system feedback structures. They show causal links between system components with directional cause and effect. Causal loop diagrams display the interconnectedness of system components to serve as a starting point for further discussion and policy formulation. Naturally, these diagrams can also help problem solvers identify in which parts of the system they can assert a positive influence to impact the entire loop favorably. In effect, these diagrams can help prevent poor decisions such as quick fixes.

Causal Loop Diagrams

Another important tool in systems thinking are the system archetypes that generally describe how complex systems work. They are generic models or templates representing broad situations to provide a high-level map of complex system behavior. Because they have been well-studied and mapped, these models can identify valuable areas where steps can be taken to resolve complex problems through interventions that are called leverages.

In general, there are two basic feedback loops (reinforcing and balancing) that identify nine system archetypes (or eight or ten, depending on who you ask):

  • Balancing loops with delays
  • Drifting goals
  • Fixes that fail
  • Growth and underinvestment
  • Limits to success
  • Shifting the burden
  • Success to the successful
  • Tragedy of the commons

Each of these archetypes are rarely sufficient models on their own — they merely offer insight into possible, common underlying problems. They can of course also be used as a basic structure upon which you can develop a more detailed model specific to your complex systems.

Adding Advanced Tools into Your Systems Thinking Toolbox

There are several dynamic and structural thinking tools in the systems thinking repertoire. Causal loop diagrams and system archetypes are dynamic thinking tools. Graphical function diagrams and policy structure diagrams are structural thinking tools. All of these can be mapped or used in computer-based tools like a management flight simulator or learning lab.

Of course, there are tools to what you can achieve with your toolbox.

Causal loop diagrams, for example, are static — they cannot describe the evolving properties of a system over time. To overcome such limitations, you need to simulate management issues quantitatively through system dynamics modeling.

Computer models of system dynamics allow you to explore time-dependent complex system behavior under different states. They essentially enable you to simulate how a causal loop diagram evolves as it is affected by different assumptions over time.

Solving Complex Problems in Project Management

Project board with tasks and task lists.

So should you start learning about causal loop diagrams and begin shopping for the best systems dynamics computer modeling tools in the market as soon as you find a project management problem you can’t seem to solve? Don’t jump the gun.

You can implement systems thinking in inquiry and problem diagnosis to great effect without needing diagrams and computer models. Apply the concept of the iceberg model and you might already find you’re asking better questions than before, or you’re catching common quick fix solutions — like needing more budget or hiring more people — that don’t address deeper problems.

Once you realize that you’ve got a complex problem that requires an in-depth systems thinking approach, you can then explore your options with your team. The important part is to embrace the mental models that make systems thinking invaluable for understanding complex systems and resolving the complex problems that arise from them.

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

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Understand Yourself Better:

Big 5 Personality Test

Find my Coach

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. 

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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.  

systems-thinking-future-minded-ness

  • 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. 

systems-thinking-team-meeting-with-people

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? 

systems-thinking-woman-at-white-board-strategy

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.

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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.

The path to individual transformation in the workplace: part two

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Systems Thinking

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.

systems thinking

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.

Featured Image: Photo by NeONBRAND on Unsplash

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systems thinking solving complex problems

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

systems thinking solving complex problems

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.

systems thinking solving complex problems

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?

systems thinking solving complex problems

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.

systems thinking solving complex problems

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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  • Discover MIT's unique, powerful, and integrative System Dynamics approach to assess problems that will not go away
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Systems thinking was designed to improve people's ability to manage organizations comprehensively in a volatile global environment. It offers managers a framework for understanding complex situations and the dynamics those situations produce. Systems thinking is a response to the rapid changes in technology, population, and economic activity that are transforming the world, and as a way to deal with the ever-increasing complexity of today's business.

Senior managers can use systems thinking to design policies that lead their organizations to high performance. The program is intended to give participants the tools and confidence to manage organizations with full understanding and solid strategy.

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This complex problem-solving course introduces participants to MIT's unique, powerful, and integrative System Dynamics approach to assess problems that will not go away and to produce the results they want. Through exercises and simulation models, participants experience the long-term side effects and impacts of decisions and understand the ways in which performance is tied to structures and policies.

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Understanding Systems Thinking: A Path to Insightful Problem-Solving

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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The Systems Thinker -

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 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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What is systems thinking?

By Michael Feder

A professional takes a break to think about solutions

This article has been vetted by University of Phoenix's editorial advisory committee.  Read more about our editorial process.

Kathryn Uhles, MIS, MSP, Dean, College of Business and IT

This article was updated on 12/1/2023.  

At a glance

  • Systems thinking looks at connected wholes rather than separate parts.
  • Systems thinkers are curious, have open minds, are good listeners and seek out root causes.
  • A systems thinker tries to expand the range of options available for solving a problem.
  • Learn systems thinking with a  Bachelor of Science in Management  degree,  Bachelor of Science in Data Science  degree or with an  Operations Management Certificate  from University of Phoenix!

Have you ever met people who intuitively see things from a 10,000-foot view? They look at the big picture rather than get derailed by details, and they’re good at assessing problems before taking action. Such people are probably good “systems thinkers.”

A systems thinking approach means recognizing that a sum is greater than its parts — that all the pieces of an organization connect, interact and play a part in outcomes.

Put another way, according to Study.com, “ systems thinking is based on the idea that all key processes in an organization are interrelated ” — and they work together to achieve a common goal.

Are you tracking so far? If so, systems concepts are probably in your DNA.

If you’re like the rest of us, read on for a systems thinking definition, key elements, examples and ideas on how you might use systems level thinking in your own educational journey or career.

Systems thinking can be applied in business and healthcare settings. Learn more about online management degrees at UOPX!

Is systems thinking a framework? A philosophy? A diagnostic tool?

It can be all those things. By one definition, systems thinking is literally a system of thinking about systems.

University of Phoenix instructor Dr. Michael Marticek teaches systems thinking and explains the concept to his students this way: With systems thinking, you solve problems by investigating factors and outcomes of those factors on your operation or educational work.

“It gets made to sound so tricky,” he says. “But it’s really just logic.”

It might help to view systems thinking as a puzzle, and how the pieces connect to each other to make the whole. A systems perspective is the opposite of “working in a silo.”

Here’s a simple example. Let’s say you’ve got a piece of machinery in which one pesky gear keeps breaking. Instead of replacing that same gear over and over, a systems thinking approach might look at the gear’s construction and design (casting, forging, metallurgy), the operational conditions (weight, friction, torque, noise), the environmental conditions (temperature, humidity, sanitation), and the maintenance (cleanliness, lubrication). Various interconnected factors could be affecting the gear’s performance and durability.

An iceberg metaphor is often used to describe systems thinking. With an iceberg, there’s what we see above the water, and the much bigger, unseen portion underwater.

Continuing with this metaphor, a systems thinker might approach a problem by asking:

  • What could be under the surface that we don’t see?
  • What are the conditions (workplace expectations, staffing issues, budget constraints, etc.) that influence the problem?
  • What issues, people or systems are working together to create what is seen above the water?
  • What ripple effects might be created by our ideas/solutions?

When should I use systems thinking?

Marticek says systems theory can be used to solve complex problems at work, in school or at home. The key is to apply a systems perspective when problems have many interrelated parts.

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According to The Systems Thinker , if a problem meets these four criteria, it could benefit from a systems thinking approach:

  • The issue is important.
  • The problem is recurring.
  • The problem is familiar and has known history.
  • People have unsuccessfully tried to solve the problem.

Key elements of systems thinking

Marticek says systems thinking has six key building blocks:

1.    Interconnections : Projects and people are connected. A systems thinking approach identifies those connections. This shifts the problem from a linear solution to a circular solution.

2.    Emergence : The opposite of working “in silos,” emergence is where a larger idea or outcome is born from smaller parts. It often is a better solution than any single “silo” could have designed.

3.    Synthesis : This means combining two or more things to create something new. “Sometimes you’re combining old ways to make a new way. Sometimes you gain new information and create something new,” Marticek says.

4.    Feedback loops : This is the step that makes whiteboard geeks drool. Feedback loops illustrate via charts or diagrams the feedback between various parts of a system. “You gather different pieces of the pie, and at the end, hopefully you have an outcome,” Marticek says.

5.    Causality: Causality looks at how one thing influences another in an interconnected system.

6.    Systems mapping : Again, whiteboard geeks unite! Systems mapping is the chart or flow that will inform decision-making. “If you hand this to an executive, this flow diagram will help them understand what is needed to make the change,” Marticek says.

For this process to work, buy-in from the top-down and bottom-up is essential. “If you’re going to alter your business or organization, you have to have a new vision. This is the road everyone is on. Everyone has to be on board with the process — you can’t have holdouts who think, ‘My idea is the best,’” Marticek says.

Characteristics of systems thinkers

Systems thinking may seem formulaic, but it’s actually quite the opposite. Rather than work a linear, predictable formula, effective systems thinkers usually have an open mind. Marticek says those who operate from a systems thinking perspective:

  • Are curious
  • Find root causes
  • Have an open mind
  • Are good listeners

“If you have ‘I-know-everything’ executives, this never works. People will try to dismantle that process because of frustration with the person creating it,” he says.

What are examples of systems thinking?

The earlier example of a gear looked at a mechanical system. That can be complicated, but not nearly as complicated as human systems or ecosystems.

Marticek refers his students to a real-life example from Borneo in the 1950s. The people were suffering from an outbreak of malaria, so they went to the World Health Organization (WHO). A decision was made to spray pesticide to control the malaria outbreak.

This killed malaria-carrying bugs, but it also killed wasps, which controlled a worm population. Worms ate through the thatch roofs, many of which collapsed.

The pesticides also were ingested by other insects, which were the food for local lizards, which were the food for local cats. Eventually, cats died off from pesticide poisoning, which caused the rat population to explode. In the end, one infestation was traded for another.

“Thinking one thing would solve the problem created multiple problems along the way,” Marticek says. Systems thinking takes into account the possible ripple effects of an idea before a decision is made.

What is systems thinking in an organization?

Now, let’s apply this to an organization. Let’s say you’ve got a favorite delivery app or home delivery company that’s trying to quickly connect goods or transportation with people in a diverse geographic area.

“Everyone is trying to compete in record time,” Marticek says. “If they’re late, you as the customer might even get 50% of your money back.”

But behind the scenes, morale may be crumbling, drivers may not be able to stop for adequate nutrition or bathroom breaks, and there may even be an unintended consequence of roads that are less safe as drivers push the limits of getting from point A to point B. Wrecks, insurance claims and employee turnover may all be high.

Someone using a systems thinking approach would look at individual decisions and their systematic consequences.

A systems thinking approach can be applied to business situations such as:

  • The complexities of managing airline fleet maintenance and setting schedules, and staffing for on-time arrivals.
  • The difficulties a marketing department may have in getting projects out the door — as finance, legal, creative and business realities collide.
  • The implementation of a new software that addresses customer service issues but may trigger business inefficiencies or require large expenses.

How can I practice systems thinking?

In review, systems thinking looks at all parts of an overall system — rather than isolating them into individual sections. A systems thinker tries to expand the range of options available for solving a problem.

This can be helpful at work, in a volunteer organization, in your educational journey or at home.

Curiosity — rather than criticism — can be a great starting point. Questions like, “What am I not seeing here,” or, “What's under the iceberg that I don’t understand,” can help.

From there:

  • Find the interrelated connections.
  • See what outcomes emerge.
  • Consider how you might be able to synthesize two or more things to make a new thing.
  • Connect feedback between different parts of the system.
  • Examine how one thing influences another thing (think: Pesticides! Rats!).
  • Make your plan, keeping in mind the possible ripple effects and consequences of your decision.

See? No sweat.

Michael Feder

ABOUT THE AUTHOR

Michael Feder is a content marketing specialist at University of Phoenix, where he researches and writes on a variety of topics, ranging from healthcare to IT. He is a graduate of the Johns Hopkins University Writing Seminars program and a New Jersey native!

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Emmerling, T., & Rooders, D. (2020). 7 strategies for better group decision-making. Harvard Business Review . Retrieved from https://hbr.org/2020/09/7-strategies-for-better-group-decision-making . Accessed on 20 Jan 2023.

Pliner, E. (2020). A framework for leaders facing difficult decisions. Harvard Business Review . Retrieved from https://hbr.org/2020/10/a-framework-for-leaders-facing-difficult-decisions . Accessed on 25 Jan 2023.

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systems thinking solving complex problems

How systems thinking compliments behavioural approaches in solving complex problems

A holistic approach to examining problems and identifying patterns of behaviour

Throughout 2021 BehaviourWorks Australia (BWA) is publishing a book to help policymakers and program managers use tools within our ‘Method’ to design and deliver better and more impactful behaviour change programs.

In Chapter 2 , we discuss Systems Thinking and Behaviour; why it is important and how to use it.

In this short follow-up post, we explain how and why we combine systems thinking and behavioural approaches. We start by introducing the concepts of ‘systems’ and ‘systems thinking’ before explaining why systems thinking is useful to combine with a behavioural approach.

What is a system?

A system is any entity where the parts relate to each other in a repetitive pattern of interaction. A pile of metal, for example, is generally not considered to be a system, but the same metals would be considered a system if manufactured into a watch.

Everything from biological organisms to larger, ecological, social, legal and economic structures can therefore be regarded as a system. Systems also exist within a hierarchy. For example, a system will generally contain embedded sub-systems which, in turn, are embedded in larger super-systems.

Some systems are cybernetic; self-governing and self-correcting, based on feedback from their environment. A watch is not a cybernetic system because it requires someone to correct it. By contrast, many heating systems are cybernetic because they use a feedback process to maintain a constant temperature.

What is systems thinking?

Systems thinking attempts to study the behaviour and properties of systems. It considers patterns of relationships between elements over time using concepts such as influence, balance, feedback and delay. This contrasts with ‘non-systemic thinking’, which simply examines individual elements in isolation without considering reciprocal influences and their effects over time.

What does systems thinking look like?

As an example, Figure 1 (below) shows part of a systems map that summarises arguments for how Paris should address climate change.

This map shows many elements and relationships between them. To hone in on one set of relationships – the diagram visualises an argument that the use of public transport and bikes will influence relative attractiveness of car use; that having more public transport and bikes will make car use appear less attractive.

Similarly, the diagram illustrates an argument that the greater use of bikes will lead to bike lanes being used more, which will make bike use less attractive and influence the attractiveness of other forms of transport.

systems thinking solving complex problems

How do behaviour approaches fit into system thinking?

Behavioural approaches can change systems by influencing the patterns of relationships within them (i.e., between key actors). For instance, consider the ‘ ways to change a system ‘ model in Figure 2 (below).

systems thinking solving complex problems

The model suggests 12 leverage points for system’s change (based on Donella Meadows’ prior work ). Do these ‘ leverage points ’ require changing behaviour? Yes, absolutely. To illustrate this, we can use a common behavioural approach, the Fogg Behavior Model (FBM), to show how these leverage points require behaviour change.

The FBM argues that behaviour requires awareness (i.e., a prompt), motivation and ability. From this perspective, the leverage point ‘ Changing information flows and access ’ is fundamentally about awareness (e.g., if people are not consistently aware of a tax discount for scrapping their car, they won’t change behaviour in response to this information).

Similarly, the leverage point ‘ Changing rules ’ is about awareness and motivations . If people become and stay aware that the new rules for Paris roads are that you cannot travel in a car with less than two people, then they won’t react. If they do know, they are likely to change behaviour, including potentially scrapping or selling their cars to avoid new frictions and risks in their commute.

Finally, ‘ Changing goals within the system ’ can be regarded as being about awareness and motivations , but at a more abstract, policymaking level of behaviour change. It suggests that if power-holders and policymakers decide that their primary goal is to reduce emissions or increase public transport use, then their motivations and behaviours (e.g., policies enacted) are likely to be much more aligned towards changing the state of the system to align with these desired goals.

In short, systems thinking and behavioural approaches are tightly interlinked. Systems Thinking involves understanding and influencing parts of a system, which usually includes people and behaviours.

Behavioural approaches involve understanding and changing people’s behaviours with a system.

Without using behavioural approaches, systems thinking cannot easily translate into systems change. Without systems thinking, behavioural approaches can still change behaviour within a system but in doing so run the risk of producing undesired outcomes.

Authored by Peter Slattery and Stefan Kaufman (one of our resident experts in Systems Thinking).

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systems thinking solving complex problems

Systems Thinking – A Framework to Solve Complex Problems

uhayat

Systems Thinking is an interdisciplinary approach that focuses on understanding the interconnectedness and relationships between various components within a complex system. By considering the whole system and its parts, the approach provides a framework for analyzing and solving complex problems, making informed decisions, and promoting effective solutions.

This approach helps us see the part of the iceberg that’s beneath the water. 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. The thinking approach has been an academic school of thought used in engineering , and policy-making. More recently businesses use it to ensure that their products and services are considering the ‘systems’ that they operate within.

System Thinking

This article explores the key concepts, principles, and benefits of Systems Thinking, as well as its applications in different fields. Additionally, it delves into the tools and methods used to apply the approach. It addresses the challenges associated with this approach and presents case studies highlighting its successful implementations. The approach also discusses the future directions and importance of embracing Systems Thinking in an increasingly interconnected and complex world.

1. Introduction

Systems Thinking is like being the Sherlock Holmes of problem-solving. It’s a way of looking at the big picture and connecting all the little puzzle pieces. It helps understand how everything works together. Instead of focusing only on individual parts, this framework examines the relationships and interactions between those parts to gain a deeper understanding of complex systems.

Historical Development

Systems Thinking has been around longer than bell-bottom jeans (which is saying something). It traces back to the 1920s when social scientists started realizing the limitations of reductionist thinking. Over time, brilliant minds like Ludwig von Bertalanffy and Peter Senge further developed the concept. They recognized that everything is interconnected, and problems are rarely isolated incidents.

The Role of Systems Thinking in Problem Solving

The framework is like having a superpower in problem-solving. It helps us see beyond the surface and understand the underlying causes and effects. By analyzing the relationships between different elements, Systems Thinking allows us to identify the root causes of problems rather than just treating the symptoms. It’s like tackling the weeds in your garden by targeting their roots instead of just plucking the leaves.

2. Key Concepts and Principles of Systems Thinking

Understanding systems and subsystems.

Think of Systems as one big, messy web of interconnectedness. A system can be anything from your smartphone to the global economy. Within a system, there are also smaller subsystems, like different departments within a company. Understanding these systems and their subsystems helps us see how everything fits together and how changes in one part can affect the entire system.

Feedback Loops and Dynamic Interactions

Feedback loops are like the peanut butter and jelly of Systems Thinking. They’re the loops that keep the system going. Positive feedback loops amplify changes, like a snowball effect, while negative feedback loops act as a stabilizing force, like your mom telling you to calm down when you’re in a sugar rush. Dynamic interactions occur when different elements within a system continuously influence and respond to each other. It’s like a never-ending dance party.

Emergence and Nonlinearity

Emergence is like finding a $20 bill in your winter coat pocket. It’s when a whole new behavior or pattern arises from the interactions of components within a system, and it’s really cool. Nonlinearity is like the plot twists in your favorite TV show. It’s the idea that small changes can sometimes have disproportionate effects. So, you never know what might happen next!

3. The Benefits of Adopting this Approach

The approach is like putting on 3D glasses for problem-solving. It allows us to see beyond the surface and understand the complexities of interconnected systems. By considering the broader context, we gain a more holistic understanding of the issue at hand, enabling us to develop more effective solutions.

Improved Decision Making and Problem Solving

The framework is like having a secret weapon in decision-making. By considering the multiple interdependencies and feedback loops within a system, we can make more informed decisions and avoid unintended consequences. It helps us move beyond quick fixes and address the underlying causes of problems.

Increased Innovation and Creativity

This approach is like adding a pinch of creativity to problem-solving. By looking at problems from multiple angles and understanding the relationships between different elements, we can discover innovative solutions that might have been overlooked by traditional linear thinking. It’s like finding the hidden shortcut in your favorite video game.

4. Applying Systems Thinking in Various Fields

Systems thinking in business and management.

In the business world, the framework helps us understand the complex interactions between departments, teams, and stakeholders. By taking a holistic view, we can identify bottlenecks, improve communication , and create more efficient processes. It’s like optimizing the gears in a well-oiled machine.

Systems Thinking in Healthcare

In healthcare , this approach helps us tackle the interconnected challenges of patient care, resource allocation, and policy-making. By understanding the relationships between healthcare providers, patients, and the broader healthcare system, we can improve patient outcomes, reduce costs, and ensure the best possible care for everyone. It’s like stitching up the healthcare system one interconnected thread at a time.

Systems Thinking in Environmental Sustainability

When it comes to saving the planet, the framework is our superhero. It helps us understand the intricate web of relationships between human activities, ecosystems, and climate change. By considering how different actions can have ripple effects across the environment , we can develop strategies that promote sustainability and protect the Earth for future generations. It’s like becoming the caped crusader of environmental stewardship.

And there you have it! Systems Thinking isn’t just for brainiacs or detectives with magnifying glasses. It’s a powerful tool that can help us navigate the complex challenges of our world. So, put on your thinking cap and start unraveling the mysteries of interconnectedness! Importance of Cultivating a Systems Thinking Mindset

5. Tools and Methods for Systems Thinking

Causal loop diagrams.

When it comes to systems thinking, one of the most popular and effective tools is the causal loop diagram. This tool allows you to visually represent the interconnections and feedback loops within a system. By identifying and understanding these relationships, you can gain insights into how changes in one part of the system can impact other parts. Think of it as a way to map out the domino effect within a complex system.

Stock and Flow Diagrams

Stock and flow diagrams are another handy tool for systems thinking. These diagrams help you visualize the stocks, or accumulations, of various factors within a system, as well as the flows that contribute to or deplete these stocks. It’s like tracking the ebb and flow of resources, information, or even emotions within a system. By understanding how stocks and flows interact, you can better comprehend the dynamics and behavior of the system as a whole.

Systems Mapping

Systems mapping is a broader approach to systems thinking that involves creating visual representations of the entire system and its components. It goes beyond just capturing interconnections or feedback loops; it aims to capture the entire landscape of a system. This can involve mapping out the structure, elements, relationships, and boundaries of the system. It’s like creating a blueprint that helps you see the big picture and navigate the complexities of the system.

6. Overcoming Challenges in Systems Thinking

Overcoming reductionism and silo thinking.

One of the biggest challenges in the approach is overcoming reductionism and silo thinking. These are the tendencies to simplify complex systems or to view them as isolated parts, rather than interconnected wholes. To overcome these challenges, we need to embrace a holistic mindset that recognizes the interdependencies and interactions within a system. It’s like stepping back to see the forest instead of just focusing on individual trees.

Dealing with Complexity and Uncertainty

Systems thinking often involves dealing with complexity and uncertainty, which can be overwhelming. However, instead of shying away from these challenges, systems thinkers embrace them as opportunities for learning and adaptation. They recognize that systems are dynamic and constantly evolving and that uncertainties are inherent in complex systems. By embracing complexity and uncertainty, we can better navigate and influence the systems we’re dealing with.

Developing Systems Thinking Skills and Mindset

Developing systems thinking skills and mindset is an ongoing process. It requires curiosity, open-mindedness, and a willingness to challenge existing mental models. It’s like learning a new language or acquiring a new set of lenses through which to view the world. By continuously honing our systems thinking skills and encouraging others to do the same, we can enhance our ability to tackle complex problems and create positive systemic changes.

7. Successful Applications of Systems Thinking

Systems thinking in urban planning.

In urban planning, systems thinking has proven to be instrumental in creating sustainable and livable cities. By considering the interconnectedness of factors like transportation, housing, and public spaces, urban planners can design cities that promote social equity, environmental sustainability, and economic prosperity. Systems thinking helps identify the ripple effects of urban development decisions, leading to more holistic and inclusive urban designs.

Systems Thinking in Education Reforms

Education systems are complex , with various stakeholders, policies, and factors influencing student outcomes. Systems thinking has been applied to understand and address the challenges within education systems, leading to innovative reforms. By considering the interplay between curriculum, teaching methods, parental involvement, and socio-economic factors, education systems can be redesigned to better support student success and bridge achievement gaps.

Systems Thinking in Social Change Initiatives

When it comes to tackling complex social issues like poverty, inequality, or climate change, this approach is invaluable. By examining the root causes and interconnections of these issues, social change initiatives can develop comprehensive strategies that target the underlying systemic drivers. Systems thinking helps identify leverage points and potential unintended consequences, enabling more effective and sustainable solutions.

8. Future Directions

As we face increasingly complex and interconnected global challenges, systems thinking becomes more critical than ever. Whether it’s climate change, public health crises, or economic disparities, these issues cannot be adequately addressed through narrow, isolated approaches. The approach provides the framework to understand the underlying systems at play and develop holistic strategies for long-term change.

Integrating into Education and Training

To foster a systems thinking mindset, it’s crucial to integrate the framework into education and training programs. By teaching students and professionals how to analyze and understand complex systems, we can equip them with the tools and mindset needed to tackle the challenges of the future. This approach should be woven into various disciplines, from STEM fields to social sciences, enabling individuals to approach problems with a holistic and interconnected perspective.

The Importance of Cultivating a Systems Thinking Mindset

Ultimately, cultivating a systems thinking mindset is not only beneficial for addressing complex problems but also for personal growth and development. It promotes critical thinking, creativity, and adaptability – skills that are highly valuable in today’s rapidly changing world.

By embracing systems thinking, we can become more effective problem-solvers, better understand the consequences of our actions, and contribute to creating a more interconnected and sustainable future. So, let’s put on our systems-thinking hats and start making a positive difference in the world.

In conclusion, the framework offers a powerful lens through which we can better understand and navigate the complexities of our world. By recognizing the interconnectedness and interdependencies of systems, we can uncover new insights, identify leverage points for positive change, and develop innovative solutions to the pressing challenges we face.

Embracing Systems Thinking not only enhances our problem-solving abilities but also cultivates a holistic mindset that encourages collaboration, adaptability, and long-term thinking. As we move forward, let us continue to embrace Systems Thinking as a valuable approach that empowers us to create a more sustainable and resilient future.

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uhayat

The author has rich management exposure in banking, textiles, and teaching in business administration.

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Systems Thinking Cornell Certificate Program

Overview and courses.

To succeed and thrive in today’s increasingly interconnected world, the ability to frame, manage, and solve complex problems has never been more essential. This program provides concrete systems thinking tools you can apply to analyze complex situations and foster a culture of organizational learning. You’ll be able to integrate systems thinking concepts, principles, and practices to improve existing processes, operations, and thinking patterns, ultimately developing a more three-dimensional mindset in both work and life.

The courses in this certificate program are required to be completed in the order that they appear.

Course list

  • Framing Complex Problems with Systems Thinking

Whether you need to tackle a complex project, communicate more effectively, rethink your organization or your job, solve world hunger, or figure out your teenager, systems thinking can help you. All of these are complex and challenging real-world problems, sometimes called wicked problems. We all confront problems, big and small, in our personal and professional lives, and most of us are searching for better ways to solve them. In this course, Professors Derek and Laura Cabrera will demonstrate how we can use systems thinking to solve everyday and wicked problems, to transform our organizations, and to increase our personal effectiveness.

At its core, systems thinking attempts to better align the way we think with how the real world works. Our thinking is based on our mental models, but these models, created from our unique perspective with its inherent biases, are usually inadequate representations of reality. The Cabreras illustrate how we can use feedback to recognize and adapt our mental models so that they better align with reality, enhancing our problem-solving capabilities.

For systems thinking to be successful, it must be adaptive. In this course, you will explore the concept of complex adaptive systems, and while these systems seem unnecessarily complicated, the Cabreras will reveal a surprising discovery. Underlying all complex adaptive systems are simple rules, and applying these rules is the key to transforming the way we frame and solve everyday problems.

  • Using the Four Simple Rules of Systems Thinking

While you may not realize it, you are already making use of some of the patterns of systems thinking. For example, you may take a certain perspective on a problem—however, you might not be aware of your perspective and more importantly, may not recognize that you are likely omitting other perspectives. It is these types of omissions that contribute to both the creation of our most challenging problems and our inability to solve them. This course will walk you through the four simple rules of systems thinking, which provide a new paradigm for solving problems. These rules represent distinctions, systems, relationships, and perspectives, or DSRP.

Throughout this course, you will start to unlearn some of the deeply ingrained thought patterns that result in unproductive interactions, unintentional bias, and faulty binary or linear thinking. Systems thinking means intentionally reflecting on how you think, including both the information and the structure of your thoughts and ideas so that you can break old habits and think more systematically. With a variety of examples, tools, and techniques, you will practice making distinctions between ideas or things, organize ideas into systems, recognize hidden or underlying relationships, and identify the perspectives implicit in the information you analyze. As a result, you will be equipped to identify more innovative solutions, build consensus across diverse groups of people, and approach problems with more creativity, adaptability, and clarity.

You are required to have completed the following course or have equivalent experience before taking this course:

  • Visualizing and Modeling Complex Systems

How do you make sense of all the information you are bombarded with on a daily basis? We can barely absorb the overwhelming amount of information, let alone determine its meaning. As Derek and Laura Cabrera illustrate in this course, we humans process information best with our eyes and our hands, and we can take advantage of this fact by using visual maps. Visual maps can help you corral this information, organize and structure it, and most importantly, convert it into knowledge that you can act upon.

In this course, you will use the online mapping software, Plectica, so that you can break down your complex problems using the simple rules of systems thinking, DSRP. Building maps with this easy-to-use software will help you gain insights into processes, relationships, or challenges of any kind, and enable you to quickly and easily share these insights with others. As you become more adept at creating visual maps, your systems thinking skills will increase as you deepen your understanding of complex ideas, communicate these ideas more effectively, and enhance collaboration across groups to spur innovation.

You are required to have completed the following courses or have equivalent experience before taking this course:

  • Building Analytical and Emotional Intelligence with Systems Thinking

Recent surveys show that employers are looking for individuals who have both analytical and emotional intelligence. Organizational leaders across a wide spectrum of industries and professions want people with strong problem-solving skills who can handle their emotions and work effectively with others. How can you learn to better balance your emotions with critical thinking, to balance your own needs with the needs of another? This course will provide you with the tools and guidance for using the simple rules of systems thinking (DSRP) to build both your analytical and emotional intelligence.

By asking more robust questions and challenging yourself to go beyond traditional forms of thought and logic, you can more quickly identify and bridge the gaps in your thinking and build new knowledge about any problem or situation. You will transcend either-or thinking to consider a wider range of possibilities that more closely reflect the real world. These same approaches for building your analytical capabilities also enable you to harness your emotions by helping you gain awareness of your own thinking. This awareness will build your emotional intelligence, which in turn will increase your ability to collaborate, think creatively, and solve tough problems. You will come away from this course with practical approaches you can apply in every area of your life to enhance your work, your decisions, and your relationships.

These courses are required to be completed prior to starting this course:

  • Designing Organizations for Systems Thinking

Why do we start organizations in the first place? We have a vision for the future, and we need to work with others to bring that vision to life. The whole purpose of any organization is collective action. When organizations fail, it is often the result of the failure to harness the collective power of individuals to drive toward that singular vision. However, much like you would design an iPhone, you can also design organizations that are adaptive and can focus everyone on achieving the organization's vision.

In this course, Cornell University faculty members Derek and Laura Cabrera present you with the design principles of intelligent, adaptive organizations built for systems thinking. With expert guidance and hands-on activities, you will create your organization's vision and mission, and build capacity and learning systems that support your organization's ability to achieve these core principles. This approach is a systems leadership and organizational design model that will help you better design, guide, manage, and change your organization. It provides you with a blueprint to build the culture you need to attain your ultimate goal: to have your entire organization, at every level, working toward realizing your company's vision.

Becoming a Systems Leader

For organizations to succeed, they need to develop individuals who are constantly learning and adapting according to information on the ground. Sharing key mental models—at the organizational, team, and individual levels—is critical to creating a culture of learning that enables the organization to survive and thrive through chaos and complexity.

In this course, Professors Derek and Laura Cabrera demonstrate how to become a systems leader; that is, someone who can use systems thinking at the organizational level, at the team level, and at the individual level. You will create a culture for your organization that is built on shared mental models and develop techniques to incentivize thought leaders to support the culture based on your vision, mission, capacity, and learning. At the team level, where the real work of the organization gets done, you will explore the process of building, sharing and evolving mental models through collaborative mapping and feedback processes. And finally, you will turn your own thinking into doing, to ensure that your actions are aligned with key organizational mental models. With tools, techniques, and expert guidance, you can begin to implement systems thinking at all levels of the organization, creating teams and individuals upon which organizational culture, values, and success are built.

Leadership Symposium   LIVE

Symposium sessions feature three days of live, highly interactive virtual Zoom sessions that will explore today’s most pressing topics. The Leadership Symposium offers you a unique opportunity to engage in real-time conversations with peers and experts from the Cornell community and beyond. Using the context of your own experiences, you will take part in reflections and small-group discussions to build on the skills and knowledge you have gained from your courses.

Join us for the next Symposium in which we’ll discuss the ways that leaders across industries have continued engaging their teams over the past two years while pivoting in strategic ways. You will support your coursework by applying your knowledge and experiences to relevant topics for leaders. Throughout this Symposium, you will examine different areas of leadership, including innovation, strategy, and engagement. By participating in relevant and engaging discussions, you will discover a variety of perspectives and build connections with your fellow participants from various industries.

Upcoming Symposium: February 6-8, 2024 from 11am – 1pm ET

  • Addressing Barriers to Performance
  • Shifting Perspective to Reframe Decisions
  • The Business Impact of Global Issues

All sessions are held on Zoom.

Future dates are subject to change. You may participate in as many sessions as you wish. Attending Symposium sessions is not required to successfully complete any certificate program. Once enrolled in your courses, you will receive information about upcoming events. Accessibility accommodations will be available upon request.

How It Works

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Faculty Authors

Derek Cabrera

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Derek Cabrera (Ph.D., Cornell) is a systems scientist, Professor, and social entrepreneur and is internationally known for his work in systems thinking, systems leadership, and systems modeling. He is currently a lecturer at Cornell University where he teaches systems thinking and organizational leadership and design. He is senior scientist at  Cabrera Research Lab , and co-founder and Chief Science Officer of  Plectica . He has given two TED Talks, written and produced a  rap song , a children’s book on cognition, and authored numerous book chapters and peer-reviewed journal articles. His research has been profiled in peer-reviewed journals, trade magazines, and popular publications, and he is author of eight books including,  Systems Thinking Made Simple: New Hope for Solving Wicked Problems  (winner of the 2017 AECT outstanding book award),  Thinking at Every Desk: Four Simple Skills to Transform Your Classroom , and  Flock Not Clock: Align People, Processes, and Systems to Achieve your Vision . Credited with discovering the underlying rules of systems thinking, Cabrera is co-editor of the Routledge Handbook of Systems Thinking. His work in public schools was documented in the full-length documentary film,  RE:Thinking . He was Research Fellow at the Santa Fe Institute (SFI) for the Study of Complex Systems and National Science Foundation IGERT Fellow in Nonlinear Systems in the Department of Theoretical and Applied Mechanics at Cornell University. As a National Science Foundation postdoctoral fellow, he developed new techniques to model systems approaches in the evaluation of Science, Technology, Engineering, and Mathematics (STEM). Cabrera was awarded the Association of American Colleges and Universities’ K. Patricia Cross Future Educational Leaders Award. He serves on the United States Military Academy at West Point’s Systems Engineering Advisory Board. His contributions to the field of systems thinking have been integrated into NSF, NIH, and USDA-NIFA programs, K-12, higher education, NGOs, federal agencies, corporations, and business schools. His systems models are used by many of Silicon Valley’s most innovative companies. Systems Thinking Made Simple is used as an introductory text for undergraduate and graduate students in numerous colleges and universities including Cornell University and West Point Military Academy. Cabrera has developed and patented a suite of systems thinking tools for use in academia, business, and beyond. Prior to becoming a scientist, Cabrera worked for fifteen years around the world as a mountain guide and experiential educator for Outward Bound and other organizations and has climbed many of the world’s highest mountains. He holds a Ph.D. from Cornell University and lives in Ithaca, NY, with his wife, Laura Cabrera, three children, and four dogs.

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Systems Thinking

Laura Cabrera

Laura is Plectica’s Chief Research Officer.

For over 15 years, Laura has conducted translational research to increase public understanding, application, and dissemination of systems science, including for USDA, the National Academy of Sciences Institute of Medicine, HHS, and the Dept. of Justice.

She is also a senior researcher at Cabrera Research Lab, has authored five books on systems thinking and its applications, and is a member of the United States Military Academy at West Point’s Systems Engineering Advisory Board.

Laura holds a PhD in Policy Analysis and Management, a Master’s in Public Administration, and a B.A., all from Cornell.

Her family is her favorite system…

Key Course Takeaways

  • Devise more effective approaches to managing complex systems, situations, processes, and problems
  • Analyze and model changes to complex systems
  • Enhance the logic you use to solve problems
  • Strengthen your emotional intelligence through structured awareness
  • Build a culture that inspires systems thinking at the organizational, team, and individual levels of the organization

systems thinking solving complex problems

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systems thinking solving complex problems

What You'll Earn

  • Systems Thinking Certificate from Cornell University’s Jeb E. Brooks School of Public Policy
  • 60 Professional Development Hours (6 CEUs)
  • 60 Professional Development Units (PDUs) toward PMI recertification

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Who should enroll.

  • Technical and engineering leaders
  • Project managers
  • Consultants
  • Business decision-makers
  • Team leaders across any industry

“This is a fantastic program to learn how to approach your work in a new and innovative way. The curriculum gave me a framework for how I approach the complex systems issues I’m trying to improve in my community, and it gave me the right language to speak about my approach and educate others. This program helped me be the “systems thinker” who has the ability to zoom in and out on complex issues and lead meaningful change.”

Request information now by completing the form below..

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Systems Thinking and How It Can Help Build a Sustainable World: A Beginning Conversation

Megan Seibert | November 8, 2018 | Leave a Comment Download as PDF

systems thinking solving complex problems

Perspective | style="text-align: left;"> Pine Watt | Unsplash

This article was originally published in the July 2018 Edition of The Solutions Journal

“For some, the development of systems thinking is crucial for the survival of humanity.” – John Sterman

“The light begins to twinkle from the rocks:   The long day wanes: the slow moon climbs: the deep Moans round with many voices. Come, my friends, ’Tis not too late to seek a newer world.”   – Alfred Lord Tennyson, Ulysses 

Humanity stands at a precipice. Overpopulation, resource scarcities, degraded ecosystem functioning from pollution and biodiversity loss, and anthropogenic climate change are damaging the life-supporting capacity of the planet. Diminishing returns on fossil fuel energy investments, combined with their dwindling availability and environmental harm, threaten industrial civilization. Many people recognize the need to transition to sustainable, resilient ways of living, but the prospect of such a transition is daunting, not only from a logistical perspective, but also because it requires new ways of thinking about and addressing complex problems. Widespread adoption of systems thinking represents one of society’s best bets for making real progress towards this daunting transition, but few actually understand what it is. This article is intended to introduce systems thinking into our common lexicon – to explain what it is at a basic level, how it can be used, and why it may very well be the key to humanity’s survival over the long run.

Let’s start at the very beginning. What is a system? 

Seibert_image1

A system is a set of things interacting in a way that produces something greater than the sum of its parts. Systems can range in complexity. Compare, for instance, a car, which is relatively easy to understand and even diagnose when something goes wrong, to a tropical rainforest, which contains so many living and nonliving components that we’re only just beginning to understand how they work. All systems have a function or purpose that is brought about by the very nature of how the system is built. The universe can be viewed as a massive set of systems interacting in infinitely complex ways, with any given system containing various subsystems while simultaneously acting as a subsystem of a larger system.

This vast and almost cosmic beauty is part of the appeal of thinking in terms of systems. Yet before going further, it’s important to understand three concepts for framing discussions about systems:

  • Systems aren’t objective things that exist “out there.” They are subjective ways of thinking that humans have come up with to make sense of the complexities of the world.
  • Since “systems” are human constructions and can be thought of in infinitely many complex ways, we have to be clear about how we’re framing any particular system of interest. For example, what are its boundaries? What perspective are we taking when talking about it? How do its parts interact? And so forth.
  • It helps when framing a system to know why we’re even talking about it in the first place! Sure, we can wax poetic about abstract notions of “systemsness,” but ultimately, thinking about things as systems is useful because it helps us to understand the world and solve problems. When analyzing or discussing systems, try to ground them in the practical context of real-world  problems or phenomena, or the conversation will likely go nowhere fast.

Here are some examples of a system:

  • A human body is a set of DNA, cells, tissues, and organs that interrelate in complex ways to form a unique organism with higher intelligence and consciousness – a “greater whole” that simply cannot be explained by studying cells and neurons themselves.
  • A forest is a collection of plants, animals, soil, water, and countless other tiny creatures and materials interacting in vast food webs and biological processes that give rise to a unique landscape dominated by trees. (Another set of plants, animals, soil, and water interacting in different food webs and with different biological processes produces something entirely different – say a grassland or a desert.)
  • An economy is the set of rules, behaviors, and institutions that govern how people within a society exchange goods and services. Like the landscapes in the example above, all economies have the same general parts – people, goods, services, rules, and laws – but the unique ways in which they interact determine the unique form each one takes.

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We tend to think of structures or phenomena as systems when we know there are things interacting in complex (often elusive) ways that generate a result we want to understand better – and likely change or improve.

What, then, is systems thinking?

Systems thinking is concerned with expanding our awareness to see the relationships between parts and wholes rather than looking at just discrete, isolated parts. Holism, which is synonymous with systems thinking, derives its name from the Greek word holon , which refers to a universe made up of integrated wholes that cannot be understood by their parts alone. At its core, systems thinking means:

  • Looking at the big picture
  • Taking a wider perspective
  • Considering multiple perspectives
  • Peeling back the layers of the onion
  • Examining how things relate
  • Looking for root causes and improvements
  • Challenging and changing our paradigms

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Systems thinking is not new. Humans have been recognizing and contemplating the interaction between parts and wholes since the dawn of civilization. Vedic philosophy in ancient India is the oldest known example – almost 10,000 years ago – of humans thinking holistically. Indeed, holism is at the center of most Eastern cultural and spiritual traditions. In Western culture, the Pythagoreans of ancient Greece developed a school of thought based on cosmic wholes and harmony through numbers. It was around this time that the word “holon” originated. Indigenous peoples around the world are known for their ability to view people as part of a greater complex web of life that they respect and harmonize with. Some Amazonian tribes interact with and ingest plants in their environments that break down barriers in the mind, allowing for transcendent awareness and understanding. Yogic meditation can have a similar effect. Systems thinking is just a new name for a natural, innate way of relating to the world around us. Reductionism (looking at just the parts), dualism (viewing things as separate), and myopia (taking a narrow view) have increasingly supplanted this ancient way of relating, particularly in the last few hundred years of the industrial revolution. Systems thinking – the term given to the modern rebirth of holistic thinking in academic and professional fields – compels us to listen to our instincts, break down barriers, see the bigger picture, explore possibilities, and relearn much of what we’ve already known.

It’s worth emphasizing that it is these habits of the mind, not the terms we use to describe them, that are most important. We use the terms “systems thinking” or “holistic thinking” here because they’re common in our current lexicon, but remember that the Hindu realizing transcendent Oneness with the universe, the scientist using a formal systems thinking methodology to do research, and the American store clerk who understands that we no longer live in a democracy are all “thinking in systems,” whether they know it by that name or not.

Here are a few examples of shifting from reductionist, dualist, or myopic thinking to systems thinking:

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  • Reductionist/dualist/myopic thinking . Humans are separate from nature and need to control it to make our lives better and realize the greatest possible material progress.
  •  Systems thinking . Humans evolved from nature and are inextricably linked to it. Nothing exists independent of the natural world. We depend upon it for our survival, even if the things it provides us – food, water, and natural resources for all the products we use – are coming from places we can’t readily see. If we use up and damage too much of nature, we’ll ruin the very habitat we and other creatures depend upon for survival.
  • Reductionist/dualist/myopic thinking . In order to reduce terrorism, we need to wage more war against the terrorists.
  • Systems thinking . Waging unprovoked war is what largely leads to terrorism in the first place. To stop terrorism, we need to stop the very actions that are causing it, not intensify those actions.
  • Reductionist/dualist/myopic thinking. People who are poor or struggling to get by just aren’t working hard enough.
  •  Systems thinking. Poverty and hardship are the inescapable result of our societal system. Modern industrial capitalism inherently creates “haves” and “have nots.” The unluckiest – those born into the wrong family or who are victims of the worst circumstances – suffer more than everyone else.

Systems thinking and power structures – there’s a reason most of us have never heard of it

Most people have never heard of systems thinking. Chances are the concept is relatively new to you if you’re reading this now. If so, or if you’re just naturally curious, you might ask, “Why should I think in systems and how is systems thinking more helpful than reductionist, dualist, or myopic thinking?” Hopefully the section above – and your own instincts – sufficiently answer this. Why would one choose to take a narrow, incomplete view of the world, seeing everything and everyone as separate, when we can take a wider perspective that recognizes the simple fact that things are interconnected in many different ways, leading to consequences because of those connections, not in spite of them?

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Rather than asking why one should think in systems, perhaps the more piercing question is: why has holistic thinking been stamped out of us again and again over time, most vigorously so during the modern industrial age? The simple answer is that power and control are not compatible with a well-educated citizenry that sees the big picture. Modern industrial civilization is built upon the mechanization and commodification of society and nature, with those at the top benefiting from the enormous outputs generated by the “cogs in the wheel” toiling at the bottom. If we become aware of this vast, complex machine and start to understand how it works, we might want to break or change it! We might want to create a different system in which all parts of society and nature can flourish, not just those in power. Such is the struggle of humankind (at least within the last 10,000 or so years of civilization) and hence the struggle between power structures and holistic education. It’s no coincidence that our modern educational system is oriented around rote memorization of endless facts that most people find useless in their lives. If we learned what is really useful – how parts and wholes interact, tapping into the full capabilities of our minds – power structures would face a serious threat.

How to cultivate the habit of systems thinking

There’s no silver bullet to thinking in systems – no five simple steps, no condensed guidebook. But you don’t have to be an academic with a fancy degree. Systems thinking is a furnishing of the mind, a way of viewing the world that one simply develops more and more over time, like any other practice. Here are some basic habits to consider cultivating – whether you’re new to systems thinking or it’s been your modus operandi :

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  • Be a critical thinker. Don’t just readily accept what anyone or any ideology says. Think for yourself. Consider the motivations behind what anyone says or claims and demand cogent reasoning and empirical or experiential evidence.
  • Be a badger. Badgers are known for their expert digging skills. Start unearthing things. Ask questions; be curious. Pull back the layers and continually dig deeper and wider.
  • See the connections. In the process of digging you’ll start to see all the complex ways in which things in our lives are intertwined. Pull on one string and find it’s connected to another – which is connected to yet another, and so on. Nothing exists in isolation. The parts dwell in the wholes and the wholes dwell in the parts. As the ancient Hindu text The Upanishads famously states, “Tat tvam asi” – “thou art that.”
  • Expand the time horizons of your thinking. The extent to which we think way back in time and way forward in time has a tremendous impact on how barriers are broken down – or erected – in our thinking and thus how we see the ways in which parts and wholes interact. Like the digging badger in a cosmic time machine, try going back before modern industrial times… then to the beginnings of the agricultural revolution 10,000 years ago… then to ancient hunters and gatherers… then to the first appearance of life on earth… then before there was an Earth… and likewise forward to your children’s time, and their children’s time… then 500 years and thousands and millions of years into the future, even when the Earth will eventually collide into the sun and the universe will expand to the point of heat death.
  • Expand the spatial horizons or your thinking. We can think about things on a very small spatial scale or a very large spatial scale, or anything in between – from atoms, to cells, to organisms, communities, ecosystems, the planet, the solar system, the galaxy, the universe, and even other universes.
  • Consider multiple perspectives. What is meant by “perspective” in systems thinking is not an opinion or position, but another way of framing a system, usually its boundaries and dynamics. For example, take someone who is fishing on a river. We can examine this scene from a number of perspectives. We can take an energetic/economic perspective, looking at the gas and money spent to drive to and from the river and how that measures against the return of energy gained through sustenance from any fish caught. We can look at the angler through a recreational/spiritual perspective, considering the joy, expansiveness, and oneness with nature one feels when being on a river trying to outsmart a fish, just like our ancient ancestors did millennia ago when trying to survive in the wild. We can look at the angler from the perspective of fish management by examining the role recreational fishing plays in managing a fish population. We can take a long-term evolutionary perspective and see that the knowledge, skills, and spiritual connections of  fishing are valuable – if not vital – to maintain and pass on to future generations. Surely ten other people could come up with ten other perspectives. Considering different perspectives is important because it generally expands our awareness and affects how we frame problems and intervene in systems.

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How can systems thinking help to build a sustainable world?

Systems thinking is the ideal problem-solving framework for sustainability. The two go hand-in-hand. A sustainable community is one whose actions don’t diminish the social opportunities and ecosystem health for future generations while being resilient against social and ecological shocks or changes. This requires looking far into the future, thinking beyond ourselves about the greater collective (born and unborn, human and non-human), and looking deeper below the surface to understand how things really work. Systems thinking is precisely poised to help do just this.

Here are some starting places, corresponding to the habits outlined above, for how systems thinking can help move us towards sustainability.

Be a critical thinker

  • Think beyond what is espoused in the mainstream, whether it be a major political party, the conventional wisdom of a social group, or the media. That which becomes mainstream has a decent chance of being influenced (with or without good intentions) by the likes of power, group think, and myopic feel-good-ism.
  • Even if something isn’t mainstream, consider its motivations and whether it’s backed by cogent reasoning, empirical evidence, and/or evidence from your own experiences and observations. Look at original sources. Come to your own conclusions.
  • Most things in this world aren’t all good or all bad. Develop nuanced conceptions of people and ideas, realizing that both can be complex and multi-faceted.

Be a badger

  • Be curious about the world and understand how it really works. How do politics really work? Do we really live in a democracy? Where does all our “stuff” come from and where does our trash go? Are solar panels really “clean”? Is being vegan really the answer? Why are two billion people hungry every day? Why can’t I get a job despite my academic credentials and experience? Why has the US been at war for 15 years? Why are so many people miserable? Why were nearly all the global freedom leaders of the 20 th century assassinated and movements for freedom and justice squelched? Is the world I see around me the only reality that’s possible?

Expand the time horizons of your thinking

  • Look backwards to the deep history of humans, from ancient hunters and gatherers to stationary agrarians forming civilized societies. Doing so puts our current trajectory and way of life into perspective, highlighting: 1) that we are living through an extraordinarily short-lived Carbon Pulse marked by a way of life that is vastly different from what the vast majority of humans have ever experienced – or ever will experience, 2) potentialities for our future after the Carbon Pulse, and 3) a connection to our ancestors and the collective consciousness we carry from them.
  • Look forward to the future. If we want to understand how we can live equitably in healthy habitats in perpetuity, we must adopt a long-term outlook and think about the future consequences of our actions for humans – born and unborn – and non-humans alike. Think decades, a century, and several millennia out. Can our current trajectory and actions persist for that long? What legacy – that is, mix of opportunities and constraints – are we leaving for our posterity, other creatures, and the planet? Is the popular rhetoric about a sustainable future realistic?

Expand the spatial horizons or your thinking

  • An unfortunate advent of the Industrial Revolution is the widespread adoption of individual-oriented thinking rather than collective-oriented thinking. Our ability to shape a sustainable future is entirely dependent upon our ability to extend our sphere of concern beyond ourselves to our fellow brothers, sisters, creatures, and Mother Earth.
  • Think about the biophysical consequences of our individual and collective actions spread across the world, starting near you geographically and extending to far off places. What are the impacts of my actions – of our collective actions – on other people’s health and other ecosystems?

See the connections

Being a critically thinking badger with expanded spatial and temporal horizons will invariably reveal some key underlying connections – connections that represent the very heart of what we must address to move towards a sustainable world. Here are some:

  • A struggle between common people and those in power; between justice and corruption; between ignorance and truth seeking; between the forces of dark and light. We need to push past our fears to stoke the latent yet ever-present fire that burns in so many of us to fight against power and corruption for a better world we know in our hearts is possible.
  • Inputs and outputs. Nothing comes from nothing; there is no “away” to throw to. We must reconnect with these consummate ecological principles and open our eyes to see that which is not readily in front of us. Every physical product in modern industrial civilization requires, on the front end, energy and natural resources, and produces, on the back end, waste and pollution. We need to understand these dynamics and how they’ll have to be changed in a biophysically constrained world in order to maintain human and ecosystem health in perpetuity.
  • It takes energy to make energy. This can be succinctly described by the difference between energy and what is called exergy. Energy is, for example, the solar radiation that reaches the earth’s surface. But humans can’t directly use solar radiation – it has to be transformed into a useable form of energy that can do work for us, which is exergy. This transformation process itself requires energy. As we transition from the Carbon Pulse into a non-fossil fueled energy regime, it is of critical importance to understand how much net energy will be available, and in what forms – something sorely missing in most conversations about renewable energy.
  • It takes raw materials to make energy. The energy-to-exergy transformation process requires not only energy, but raw materials. In addition to assessing future net energy availability, we also have to analyze the metals, water, and other (often toxic) man-made substances that currently go into making renewable energy technologies and everything else in our lives, considering whether their supply can be sustained in perpetuity and what the impacts of their extraction and use will be.
  • Sustained life depends upon sustained healthy habitats. It’s easy to forget, living in our predominantly urban and suburban environments, that our lives depend inextricably upon the health and vitality of natural habitats. Even for those who appreciate this simple fact, having been disconnected from living directly off the land for several generations makes the practical, full implications of what this means challenging to grasp. Transitioning to a sustainable world will take more than focusing on energy and trying to preserve our current quality of life. It will require looking at the ecological implications of everything we do (from our population levels to manufacturing processes to the impacts of hydroelectric dams) and determining whether we find those impacts on the health of our habitats acceptable over the long-run. This process of evaluation is necessarily both objective (e.g. ecological integrity assessments) and subjective (e.g. value laden decisions by society about the conditions we chose to live in and how much “space” we chose to give to other creatures and the planet).
  • Politics matters. Journalist Jon Schwarz recently said, “Twenty years ago, U.S. elites had so successfully depoliticized America that simply caring about politics was like having a super-weird  hobby. It wasn’t even like being a Civil War re-enactor; it was like being a War of 1812 re-enactor. The social opprobrium meant that many of the people in grassroots politics were troubled kooks… If you can, make politics one of the centers of your life. Politics is absolutely a matter of life and death. Treat it like it is.” Let us not forget the definition of politics – the complex relations between people living in society. Getting these relations “right” – modifying existing laws, constitutions, and even forms of government, however minor or radical – is precisely what will shape the structural landscape that will either promote or hinder transitioning to a sustainable world. So is having the courage to talk about topics that matter – topics that all too often are placed under the “political” taboo simply because they make us uncomfortable or invoke ethics.

Consider multiple perspectives

  • There are many forms a sustainable world cannot take, but there are also many forms a sustainable world can take. A sustainable future will not be one size fits all. Consider, for example, that with a given amount of net energy and remaining natural resources, we could (hypothetically) cram nine billion on the planet in perpetuity, with little breathing room, or we could have two billion people living with more abundance. Also consider that one community may choose to live a subsistence lifestyle while another may choose to enjoy more luxuries.
  • Consider that the state of consciousness we know in the modern industrial world is not the only state of consciousness possible, nor necessarily the most helpful or desirable. As Timothy Leary famously said, “Turn on, tune in, and drop out….’Turn on’ [means] go within to activate your neural and genetic equipment. Become sensitive to the many and various levels of consciousness and the specific triggers that engage them…‘Tune in’ [means] to interact harmoniously with the world around you – externalize, materialize, express your new internal perspectives. ‘Drop out’ [suggests] an active, selective, graceful process of detachment from involuntary or unconscious commitments – a self-reliance, discovery of one’s singularity, a commitment to mobility, choice, and change.”  New scientific research coming out of the Imperial College of London’s Psychedelic Research Group suggests that mind manifesting psychedelics that have been used around the world for thousands of years may be an important key to bringing about systemic societal change through their ability to enhance cognitive connections and our sense of oneness with the world around us. Learn how to manifest the full holistic potential of your mind, whether through teacher plants, yoga, communing with nature, or other healthy forms of activation and development that resonate with you.
  • Challenge and evolve your paradigms. Use the knowledge you gain from growing a systems perspective to continually develop your paradigms about this world and the future, remaining flexible and nimble in your thinking, open to new information and considerations, always grounded in physical limits and ecological realities. Then use your particular talents and passions to help build a better future – because it can be better, but only if we act deliberately and quickly.

History has a knack for repeating itself. Waves of revolt, suppression, and enlightenment weave in and out of the fabric of the human experience, fading out in one generation to be replaced by something new, only to reappear in a new form decades or even millennia later. Such is the case with systems thinking. This age-old way of holistically viewing and relating to the world around us has taken new root in Western academic and professional fields under a new moniker. By understanding systems thinking and exploring its history and contemporary developments, we will find ourselves able to think more creatively (but with a solid grounding in physical realities) and be better prepared to tackle today’s environmental and social crises.

Megan is a systems thinker committed to steering humanity away from its failing trajectory.  She has an MS in Systems Science/Environmental Management and a dual engineering and international studies BS.  Her works spans the fields of sustainability, environmental action education, and government contracting.  She’s most concerned with the unprecedented transition civilization faces as the Fossil Fuel Age draws to a close and is working to spearhead a radical community-level action plan informed by holistic biophysical analysis. Megan lives near Corvallis, Oregon.

The  MAHB Blog  is a venture of the Millennium Alliance for Humanity and the Biosphere. Questions should be directed to   [email protected]

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Solving Complex Problems: Structured Thinking, Design Principles, and AI

Sang-Gook Kim

Download the Course Schedule

How do you solve important, large-scale challenges with evolving and contradictory constraints? In this 5-day course, transform your approach to large-scale problem solving, from multi-stakeholder engineering projects to the online spread of misinformation. Alongside engineers and leaders from diverse industries, you’ll explore actionable innovative frameworks for assessing, communicating, and implementing complex systems—and significantly increase your likelihood of success.

THIS COURSE MAY BE TAKEN INDIVIDUALLY OR AS PART OF THE  PROFESSIONAL CERTIFICATE PROGRAM IN INNOVATION & TECHNOLOGY  OR THE  PROFESSIONAL CERTIFICATE PROGRAM IN DESIGN & MANUFACTURING .

systems thinking solving complex problems

Engineering projects with shifting goals. Inefficient national healthcare systems. The online spread of misinformation. Every day, professionals are tasked with addressing major challenges that present opportunities for great triumph—or significant failure. How do you approach an important, large-scale challenge with evolving and contradictory constraints? Is the solution a new technology, a new policy, or something else altogether? In our new course Solving Complex Problems: Structured Thinking, Design Principles, and AI , you’ll acquire core principles that will change the way you approach and solve large-scale challenges—increasing your likelihood of success. Over the course of five days, you will explore proven design principles, heuristic-based insights, and problem-solving approaches, and learn how to persuasively present concepts and system architectures to stakeholders. Methods utilize recent developments in AI and Big Data, as well as innovative strategies from MIT Lincoln Laboratory that have been successfully applied to large and complex national defense systems. By taking part in interactive lectures and hands-on projects, you will learn to think through and leverage important steps, including problem abstraction, idea generation, concept development and refinement, system-level thinking, and proposal generation. Alongside an accomplished group of global peers, you will explore the strategies and frameworks you need to implement large-scale systems that can have a significant positive impact—and minimize the probability of failure.

Certificate of Completion from MIT Professional Education  

Solving Complex Problems cert image

  • Approach and solve large and complex problems.
  • Assess end-to-end processes and associated challenges, in order to significantly increase the likelihood of success in developing more complex systems.
  • Implement effective problem-solving techniques, including abstracting the problem, idea generation, concept development and refinement, system-level thinking, and proposal generation.
  • Utilize system-level thinking skills to evaluate, refine, down select, and evaluate best ideas and concepts.
  • Apply the Axiomatic Design methodology to a broad range of applications in manufacturing, product design, software, and architecture.
  • Generate and present proposals that clearly articulate innovative ideas, clarify the limits of current strategies, define potential customers and impact, and outline a success-oriented system development and risk mitigation plan.
  • Effectively communicate ideas and persuade others, and provide valuable feedback.
  • Confidently develop and execute large-scale system concepts that will drive significant positive impact.

Edwin F. David Head of the Engineering Division, MIT Lincoln Laboratory

Jonathan E. Gans Group Leader of the Systems and Architectures Group, MIT Lincoln Laboratory

Robert T-I. Shin Principal Staff in the Intelligence, Surveillance, and Reconnaissance (ISR) and Tactical Systems Division, MIT Lincoln Laboratory Director, MIT Beaver Works

This course is appropriate for professionals who design or manage complex systems with shifting needs and goals. It is also well suited to those who want to improve the quality and performance of their operations and decision-making in a large-scale system environment. Potential participants include engineers, group leaders, and senior managers in government and industries including automotive, aerospace, semiconductors, engineering, manufacturing, healthcare, bio-medical, finance, architecture, public policy, education, and military.

Computer Requirements

A laptop with PowerPoint is required.

Solving Complex Problems: Structured Thinking, Design Principles and AI - Brochure Image

  • Our Mission

Teaching Students About Systems Thinking

These strategies guide students to explore the interconnected parts of complex systems like the human body, governments, and ecosystems.

Illustrated blocks

Our world is interconnected and complex. As a result, our students need to move beyond fragmented ways of thinking, which look at problems in isolation or focus on short-term solutions. By developing our students to be systems thinkers, we can enable them to see patterns and organize their learning both inside and outside of school.

Let’s break this idea down by first describing what we mean by a system. Generally speaking, a system is a group of interconnected elements that are organized for a function or a purpose. System elements, or parts, may be physical or intangible things.

Importantly, system parts are interdependent. A change in one element can produce change within the entire system. This means systems are nonlinear. When consequences occur, they’re not isolated. They ripple through a system. Systems we encounter daily include the human body, cities, governments, social networks, and the Earth’s climate.

To give a narrative example, in Dr. Seuss’s well-known book The Lorax , the parts of the system are things like the water, air, Truffula Fruits, Brown Bar-ba-loots, and Humming-Fish, as well as the Once-ler’s greed and desire for economic growth above all else. Imagine if the Once-ler had truly understood how his behaviors impacted the Truffula Tree ecosystem, including the sustainability of his own Thneed production. His inability to think holistically led not only to a range of negative environmental consequences, but also to the collapse of his own business. 

In a global issue such as plastic pollution, system parts may include crude oil production, plastic manufacturing, companies, consumers, wastewater, and greenhouse gas emissions.

Systems thinking helps students manage complexity

Systems thinking is a mindset as well as a set of tools that enables students to recognize and understand relationships and interconnectedness. It’s an ability to toggle between the parts and the whole of a system to understand how interactions produce negative or positive behaviors. 

Systems thinking supports our students to understand the complexity of the world and manage its uncertainty, especially in a time of increased globalization; it is an essential component of critical thinking that teachers can apply across the curriculum. For example, using systems thinking, students can do the following:

  • Chart character development in a piece of literature with behavior-over-time graphs
  • Map nonlinear causes and consequences of historical or political conflicts
  • Understand the relationships between parts of a cell, as well as between cells, organs, and body systems
  • Analyze and take action on real-world issues, such as global warming, poverty, or overfishing

Teachers, curriculum coordinators, and school leaders can also use systems thinking tools, such as Agency by Design’s Mapping Systems protocol , to better understand the way parts of our educational system connect to produce positive or negative outcomes for students, such as lower attendance, higher referrals to learning interventions, or increased mental health issues.   

Fostering systems thinking as critical thinking

There are a number of ways teachers can facilitate systems thinking in the classroom. By slightly shifting how we interact with students—our questions or thinking prompts—we can promote “thinking in systems.”

Question with intention: Knowing we want to move away from “A leads to B” linear thinking, we can intentionally ask questions that encourage students to reflect on multiple parts of a system and how they connect. Instead of asking, “What caused this?” which communicates that there is a single cause, we can instead ask, “What factors contributed to this?” allowing students to search for multiple causes and nonlinear relationships.

Take a helicopter view: Toggling between the details and the big picture is an important systems thinking skill and one of the habits of a systems thinker . When looking at a situation, event, or particular issue, encourage students to discuss systems as a whole. For example, in the classroom we may create a circle, where each student represents a system part and makes connections with a ball of string. Students name how they connect to another system part as they toss the ball of string to one another, with each student retaining some of the string as they pass the ball around. At the end, students can see the interconnectedness of parts by gently tugging on the yarn and seeing who is affected.

Encourage pattern recognition: We want students to see the web of interconnections within systems and recognize how systems connect to other systems. During the Covid-19 pandemic, for instance, we saw how health systems impacted transportation and the economy, leading to certain goods being unavailable. By asking, “What’s this got to do with that?” we nudge students to go both deep and wide in an investigation.

Strategies for Teaching systems thinking

Many strategies for systems thinking encourage students to visualize and create “system pictures.” Because of the high degree of interaction within systems, many strategies invite students to map connections in nonlinear ways. Here are some concrete strategies we can use in the classroom.

Connected circles: In this strategy, a circle represents a particular system, and the parts of the system are written around the outside. Using a case study such as an article, video, or real-life experience, students chart connections across the parts of the circle, writing the relationship between parts on the connector line. A connected circles template can be modified for any system that students will explore.

Systems models: After researching a system such as a tropical rainforest or coral reef, students create a systems model using divergent physical materials, e.g. Lego, magnetic tiles, wooden blocks, paper, cotton balls, shells, stones, etc. After making representations of the system and its parts, students annotate the model with sticky notes, arrows, etc. to show relationships between them. This may also include inputs and outputs of the system. For example, sunlight and carbon dioxide go into the rainforest (inputs), and oxygen and water vapor come out (outputs).

Games and simulations: Matthew Farber has written extensively about the use of constructionist gaming to promote thinking about complex systems. He shows how making and thinking come together to allow students to play with systems. The Joan Ganz Cooney Center at Sesame Workshop also writes about the role of digital learning to promote understanding of systemic causes in young children. 

By inviting students to play with and explore systems thinking tools, we enable them to see structures and patterns within and across the content areas. Such engagements can empower students to find solutions to local, global, and intercultural issues that may have previously seemed unsolvable.

ORIGINAL RESEARCH article

Ambient and focal attention during complex problem-solving: preliminary evidence from real-world eye movement data.

Yuxuan Guo

  • 1 Institute of Psychology III, Engineering Psychology and Applied Cognitive Research, Technische Universität Dresden, Dresden, Germany
  • 2 Department of Electronic Systems, Aalborg University, Aalborg, Denmark

Time course analysis of eye movements during free exploration of real-world scenes often reveals an increase in fixation durations together with a decrease in saccade amplitudes, which has been explained within the two visual systems approach, i.e., a transition from ambient to focal. Short fixations and long saccades during early viewing periods are classified as ambient mode of vision, which is concerned with spatial orientation and is related to simple visual properties such as motion, contrast, and location. Longer fixations and shorter saccades during later viewing periods are classified as focal mode of vision, which is concentrated in the foveal projection and is capable of object identification and its semantic categorization. While these findings are mainly obtained in the context of image exploration, the present study endeavors to investigate whether the same pattern of interplay between ambient and focal visual attention is deployed when people work on complex real-world tasks—and if so, when? Based on a re-analysis of existing data that integrates concurrent think aloud and eye tracking protocols, the present study correlated participants’ internal thinking models to the parameters of their eye movements when they planned solutions to an open-ended design problem in a real-world setting. We hypothesize that switching between ambient and focal attentional processing is useful when solvers encounter difficulty compelling them to shift their conceptual direction to adjust the solution path. Individuals may prefer different attentional strategies for information-seeking behavior, such as ambient-to-focal or focal-to-ambient. The observed increase in fixation durations and decrease in saccade amplitudes during the periods around shifts in conceptual direction lends support to the postulation of the ambient-to-focal processing; however, focal-to-ambient processing is not evident. Furthermore, our data demonstrate that the beginning of a shift in conceptual direction is observable in eye movement behavior with a significant prolongation of fixation. Our findings add to the conclusions drawn from laboratory settings by providing preliminary evidence for ambient and focal processing characteristics in real-world problem-solving.

1 Introduction

1.1 two visual systems reviewed.

Vision is a sense that allows to sample the information from our surroundings, select and code different aspects of information, and produce visually guided behaviors to interact with the world ( James, 1890 ). Understanding vision and visual perception is of long-lasting interest. Over the last decades, research into vision has proposed a model that made distinctions between the functional organization of the two visual processing systems.

In the late sixties, Trevarthen (1968) postulated an anatomical separation between vision of space and vision of objects based on experiments with split-brain monkeys, and named the two visual systems ambient and focal . The ambient system provides a visual spatial frame for action centered on the body as a whole. The focal system, on the other hand, functions as a high-resolution analyzer system centered around the foveal projection. At about the same time, Schneider (1967) who described experiments on golden hamsters with brain lesions also came to the conclusion that there were two visual systems: one responsible for the coding of location (‘where’), and one responsible for the identification of the stimulus (‘what’). These distinctions marked a significant departure from earlier descriptions of the model of two visual systems. The model of two visual systems has developed and gradually crystallized over years with experimental support from a variety of research fields. Later perspectives on modularity in the two visual systems placed more emphasis on output distinctions, e.g., visual control of action vs. visual perception. Based on behavioral evidence from lesion studies, Ungerleider and Mishkin (1982) distinguished two broad cortical pathways of visual processing, the dorsal and ventral streams. This proposal paved the way for the later model of visual processing which differentiates between vision for action and vision for perception ( Goodale and Milner, 1992 ; Goodale et al., 1994 ; Milner and Goodale, 1995 ; Milner and Goodale, 2008 ). Milner and Goodale’s (1995) version of the model of two visual systems takes more account of the functional standpoint that separate visual pathways are specialized for different uses to which vision can be put. The dorsal stream transforms visual information about the goal object into the appropriate coordinates of surrounding arrays in real-time, providing a viewer-centered framework and playing a role in the guidance of our actions in picking it up. The ventral stream transforms visual inputs into rich and detailed perceptual representations that encode the size, orientation, and location of objects relative to the other, as well as its semantic properties, allowing us to parse the scene and to recognize objects (and their relations) in the visual world.

Even though the above-mentioned studies generated slightly different terms and definitions, the distinction between egocentric spatial frame and object recognition, between ‘ambient’ and ‘focal’, has persisted in visual neuroscience ( Bridgeman, 1991 ; Andre and Rogers, 2006 ; Rooney et al., 2017 ; Owens et al., 2018 ). More importantly, this ambient-focal dichotomy has also been applied to the field of eye movement research. According to Trevarthen (1968) , the course of interplay between the ambient and focal system, such as the ongoing perception of object identities within appropriate spatial context, also closely depends upon the oculomotor adaption. During normal daily activities, such as reading a newspaper or viewing an image, oculomotor activity can be described as an interplay between saccades and fixations ( Yarbus, 1967 ). Saccades—fast ballistic movement of the eyes—direct the small high-resolution foveal region from one point of interest to another. The relatively stable periods between saccades are known as fixations, within which the intake of high-resolution visual information occurs. These two parameters of oculomotor behavior effectively change to favor one or other visual mode: a large field of vision is explored by larger saccades, which gives the impression of a strong stimulation of peripheral spatial apprehension, and therefore a fall in high-acuity focal attention. Foveal resolution of configuration, pattern, hue, etc., within the spatial context is organized during successive intent fixations, which gives the impression of stimulation of a high-acuity analyzer system and depresses peripheral ambient attention.

The concept of using conjugate eye movements as the most direct sign of the interplay between two visual systems has been sharpened by a series of eye movement studies of scene perception. In static scene viewing research, Antes (1974) was one of the first who reported an increase in fixation durations together with a decrease in saccade amplitudes over the time course of scene inspection. Unema et al. (2005) further investigated the systematics in information processing during static scene viewing, demonstrating changes in fixation durations and saccade amplitudes over time. The authors interpreted the observed fixation and saccade behavior with the ambient/focal visual systems approach ( Trevarthen, 1968 ). Specifically, in Unema et al. (2005) , the short fixation durations and long saccade amplitudes observed during the early viewing periods were interpreted as ambient mode of vision, which may be used to structure a spatial frame and determine the whereabouts of the objects in the scene. Having the spatial frame stabilized makes it possible to pay closer attention to an object of interest and analyze it in detail. Correspondingly, the longer fixation durations and shorter saccade amplitudes observed during the later viewing periods were interpreted as focal mode of vision. This interpretation is supported by Velichkovsky et al. (2005) , who found that objects/regions of a scene fixated in the course of focal processing (when fixation duration was long and the subsequent saccade amplitude was short) were better recognized than those similarly fixated in the course of ambient exploration (when fixation duration was short and the subsequent saccade amplitude was long) in a recognition task. Further evidence for transitions between ambient and focal visual processing in static scene viewing was provided by Pannasch et al. (2008) who studied the time course of eye movements while participants viewed scenes under various conditions. Their data demonstrated a systematic increase in fixation durations together with decreased saccade amplitudes over a period of 6 s across different natural viewing conditions. This default-like viewing behavior was repeated after the presentation of a new stimulus, suggesting that ambient to focal processing was evoked by the onset of a new visual environment and served as basic attentional mechanism in static scene viewing independently of viewing condition.

Comparable research into eye movements during more naturalistic dynamic scene viewing demonstrates the same dichotomy between ambient and focal eye movement characteristics. First indications of a dynamic balance between the ambient and focal processing were reported by Velichkovsky et al. (2002) analyzing hazard perception during a driving simulation task. Later, Smith and Mital (2013) compared viewing gaze behavior of dynamic to static scenes and found that dynamic scene viewing exhibited similar eye movements to previously described static scene viewing. Finally, Eisenberg and Zacks (2016) investigated patterns of eye movements while participants viewed naturalistic movies or live action. They found that participants shifted from focal to ambient processing (decreasing fixation durations and increasing saccade amplitudes) around subjective event boundaries between meaningful units of activity. The authors suggested that event boundaries function similarly to the onset of a new scene during static scene viewing. Because people need to update their working memory representations when features of the current environment change and activity becomes less predictable, this event model update entails ambient eye movements for exploratory processing around event boundaries.

The interplay between ambient and focal visual processing is not only identified in relation to external events in the visual environment, such as the onset of new stimuli or subjective event boundaries as discussed above. First evidence suggests that the interplay between these two modes of processing also takes place during the performance of more complex tasks without any external changes. In a recent study by Guo et al. (2022) , participants engaged in an extended task that required them to switch between different sub-tasks until the macro task was completed. After participants switched from one sub-task to another, the authors found indications of ambient to focal visual processing shift (increasing fixation durations and decreasing saccade amplitudes) over the processing time between different sub-tasks. Extending previous research, Guo et al. (2022) suggested that the shift between ambient and focal attentional processing can be triggered internally, closely related to the inner mental model, such as mental shifts between different tasks.

Taken together, characteristics in eye movement patterns adequately reflect the functional dichotomy and the transition between the ambient and focal visual system. Short fixations and long saccades are optimal for “driving” ambient vision extending over the whole visual field, which is of the ability to adapt to spatial alterations or to extensive temporo-spatial relationships—for example, stimuli onset/activity changes in scene viewing tasks trigger ambient gaze behavior as demonstrated in ( Unema et al., 2005 ; Pannasch et al., 2008 ; Eisenberg and Zacks, 2016 ), or the mental shifts between different tasks in ( Guo et al., 2022 ). In contrast, longer fixations and shorter saccades are essential in maintaining the resolving power of focal vision, which is of decisive importance to the recognition and learning of complex details.

1.2 Visual attention deployment in complex problem-solving

Although the ambient and focal visual processing phenomenon has been replicated in numerous studies, it has yet to be investigated in more naturalistic settings. The use of naturalistic stimuli within laboratory studies, e.g., the real-world scenes utilized in scene viewing tasks (see Pannasch et al., 2008 ; Smith and Mital, 2013 ), provides a bridge between laboratory and naturalistic settings. However, a deeper understanding of visual processing mechanisms cannot be achieved without determining whether the results derived from images depicting real-world scenes generalize to the visual world itself, that is, to the situation in which the participant is looking at and interacting with the real-world dynamic environment. To this effect, a more natural and complex task, such as solving problems in real-world settings that requires participants to continuously interact with the environment, would be appropriate. Prior research has demonstrated a strong relationship between attention deployment and problem-solving by showing the activation of attention-related brain areas as people solve problems ( Kounios et al., 2008 ; Kounios and Beeman, 2009 ). More importantly, eye tracking studies extended prior research by providing direct evidence for a relationship between visual attention and problem-solving, e.g., eye movements and blinks have revealed dynamic differences in overt attention when people solve problems with sudden insight versus analytically ( Salvi et al., 2015 ).

However, the deployment of visual attention in problem-solving was mostly investigated in laboratory settings as people solved short, highly structured, visually presented problems (e.g., Knoblich et al., 2001 ; Rehder and Hoffman, 2005 ). Compared to laboratory tasks, problems in real life are often more fuzzy, ill-structed, and require more voluntary control of visual attention for gathering and refining relevant information contained within the environment ( Simon, 1978 ). Ill-structed problems are defined by having an ambiguous problem state, incomplete or ambiguous goals, which do not include only one specific solution path. To solve ill-structured problems, solvers need to integrate multiple knowledge domains and to constantly interact with the environment in order to systematically evaluate possible problem states intervening between the starting state and the goal state ( Newell and Simon, 1972 ; Kounios et al., 2008 ). The complexity of such problems can be managed through decomposition of the problem into a series of smaller sub-problems that are easier to address in sequential steps. Correspondingly, in ongoing problem-solving, solvers are likely to encounter difficulties when working on possible solution paths through steps, which results in impasses, and forces solvers to adjust their conceptual direction. To overcome an impasse, the solver must address and reevaluate the troubling issue, shift between possible ideas or approaches to define or update the problem state (a reorganization of the conceptual representation of a problem), eventually conclude with a solution ( Ohlsson, 1992 ; Ollinger et al., 2014 ).

The important role of perceptual processes in problem-solving, especially in the generation of the solver’s internal representation of the problem, was demonstrated early by Simon (1978) as well as Newell and Simon (1972) in their ‘information-processing theory of human problem-solving’. In particular, their theory postulates that the framework for problem-solving behavior is established by three components: information-processing system, task environment, and problem representation. The information-processing system is an adaptive system that relates problem representation and task environment to each other. Solving a problem may require drawing upon large stores of information in long-term memory and in external reference sources, e.g., the task environment. The task environment refers to an environment containing a goal, a problem or task, as well as the amount of semantic information necessary to solve the problem. As outlined above, solving a problem is an odyssey through different problem states—what the solver knows about the problem at a particular moment of time—until the current state of knowledge includes the solution to attain the goal. To set forth from one problem state to another, in other words, updating the state of knowledge, the solver must gather or retrieve relevant information available in the task environment and successfully embed critical features into his conceptual representation of the problem ( Kaplan and Simon, 1990 ; Ollinger et al., 2014 , 2017 ).

Given that problem-solving behavior can be characterized as a series of elementary information processes organized into strategies or programs ( Simon, 1978 ), when the task environment remains constant, a deployment of attentional strategies for information-seeking behavior may be necessary to sharpen the problem-solving efforts. This leads to our research question: What role does the interplay between ambient and focal visual attention play when people are working on a realistic complex problem? As previously mentioned, ambient/focal visual attention is governed by neural processes that have been argued to support spatial representations or object-oriented (detail-based) representations. Ambient and focal attention are likely involved in just that—the representation of said information, with other processes/mechanisms using that information to intelligently guide thought and behavior. The processing of information operates through one or other visual attention inherently driven by the goals of the observer. To gain further insight into our research question, we conducted a reanalysis of data from an eye tracking study ( Kaszowska, 2019 ). This study utilized a tool design task to explore complex problem-solving in a real-world setting and understand how individuals adjust their conceptual direction when working on a complex problem. The chosen complex ill-structured tool design task served as a testbed for investigating problem-solving strategies and complex cognition, with a specific focus on examining the link between attention, gaze deployment, and verbalization in naturalistic scenarios.

In Kaszowska (2019) , 45 engineering students had to conceptualize a tool—a physical piece of equipment—that could be used by a specific end user (either a robot, a human, or a team consisting of both robot and human) in sorting Lego blocks into individual containers according to a reference image depicting a sorted kit. The purpose of this prospective tool was to facilitate and optimize the sorting process. This tool design task only specified the initial state (a need for a tool) and the end state (a tool improves sorting efficiency) of the problem, without predetermining any solution path. Participants planned possible solutions for approximately 10 min while thinking aloud (i.e., participants were verbalizing their ongoing thought processes). The concurrent think aloud reflects ongoing cognitive activities, such as what information is being processed and how it is processed ( Ericsson and Simon, 1980 ; Russo et al., 1989 ; Payne, 1994 ). During this planning process, participants could manipulate the Lego pieces, refer to both the reference image and the end user’s appearance. While free-viewing information contained within the environment, their eye movements were recorded using a mobile eye-tracker. Kaszowska (2019) combined the concurrent think aloud with eye tracking recording to analyze how participants engaged with ideas when exploring possible solution paths to the tool design problem. In particular, the author content-coded the think aloud data and isolated specific instances where the verbalization content indicated a shift in conceptual direction and termed them pivots and pivot sequences . A pivot sequence is initiated during the pivot when the need for updating or redefining the problem representation arises. More precisely, the pivot sequence is defined as a three-stage problem-solving process, which starts with encountering a troubling issue, responding with a pivot (recognizing an issue), and then resolving the issue immediately. Given the nature of concurrent verbalizations, which reflect how designers engage with design ideas and what cognitive processes contribute to the ongoing planning and problem-solving, a thorough analysis of speech content units can effectively capture moments of hesitation, uncertainty, or the evaluation of small decisions and judgments. Functionally, hesitation markers in language production have been theorized to create time for verbal planning in speech ( Maclay and Osgood, 1959 ; Rochester, 1973 ). In many cases, hesitations are relevant for communication and provide information about underlying cognitive processes ( Brennan and Williams, 1995 ; Tenbrink et al., 2011 ). As such, the pivot is often reflected as a hesitation marker in participant’s verbalizations, which is essentially a verbal event (including filled nonverbal content such as “ums” and “uhs” or silences); refer to Figure 1 for an example of a pivot sequence in think aloud data, illustrating how the content units of verbalization change over the three stages—considering alternatives, pivot, and proposing a design idea.

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Figure 1 . Diagram depicting the analysis windows. The pivot sequence in think aloud data is presented in accordance with its stages. The red frame illustrates the numbering of a sequence of 10 fixations/saccades selected for the pivot and the control analysis for testing whether transitions between ambient and focal processing occur in tandem with pivot events. The blue frame illustrates the numbering of a sequence of 9 fixations selected for the investigation of visual fixation responses to the onset of a pivot event, as well as the defined observation period for evaluating fixation durations before any pivot event.

To explore perceptual and attentional processes in how humans interact with the surrounding world, Kaszowska (2019) introduced two categorical predictors to model oculomotor behavior: pivot kind (denoting whether the conceptual shift occurred within an idea or between ideas) and fixation kind (categorize eye gaze on regions of interest with respect to verbalization content). This approach yielded valuable insights into the intricate relationship between visual attention and speech. Specifically, the author explored how guiding look-ahead fixations (i.e., fixations anticipating interactions with the subsequent pivot resolution phrase content) and monitoring look-back fixations (i.e., fixations monitoring interactions with the preceding troubling trigger phrase content) accompany changes in conceptual direction (reflected as pivot sequences in concurrent think aloud data). Look-ahead and look-back eye movements are extensively studied in the literature in the context of active vision, specifically in the interplay between vision and movement such as reaching and grasping. Look-ahead fixations are prominent during natural tasks, where participants sometimes fixate on objects before manipulating them ( Pelz and Canosa, 2001 ; Mennie et al., 2007 ), suggesting that guiding eye movements are purposeful and have a role in task planning. In contrast, look-back fixations return to a previously inspected region of interest within a narrow temporal window after an action has been completed ( Gilchrist and Harvey, 2000 ; Mennie et al., 2007 ). The study ( Kaszowska, 2019 ) unveiled a tight linkage between eye movements and verbalization during problem-solving, demonstrating that the guiding and monitoring processes were differentially deployed over the course of conceptual direction shifts. In pivot sequences, where participants are more likely to evaluate various independent ideas or approaches, look-ahead fixation were more frequent 1 s before and after the pivot compared to during the pivot (i.e., the resolution phrase content is more frequently attended to before and after the given pivot). On the other hand, during smaller-scale conceptual shifts—pivot sequences where participants are more likely to alter between various aspects of the same idea—the proportion of look-ahead fixation (the focus on resolution phrase) decreases over the pivot sequence. The frequency of monitoring look-back fixation remains stable throughout the pivot sequence, irrespective of the pivot magnitude (e.g., a pivot either denotes a shift to a different idea or a shift to a different aspect of the same idea), implying that the involvement of monitoring processes is invariant of conceptual shift scope. Additionally, the study reported a variation in fixation duration as a function of pivot magnitude (pivots denote a shift to a different idea are accompanied by shorter fixations) and pivot sequence stage (fixation durations increase over the course of a pivot sequence).

This paradigm ( Kaszowska, 2019 ) is methodologically advantageous for addressing our research question because (a) the objects in the task environment (e.g., the end user and the reference image) are rich in semantic information that must be supplied to solve the tool design problem, which requires a role for perceptual processes in the given context. (b) Recording eye movements and verbal think aloud protocol effectively provide a high temporal density of observations for exploring the interaction between perceptual and cognitive processes in problem-solving. The deployment and interplay of ambient and focal attention for visual information processing will be reflected in moment-by-moment changes in the characteristics of eye movement patterns throughout the course of the given problem-solving task.

1.3 Ambient-focal attentional strategies in problem-solving

In light of previous findings, we formulate our hypothesis with the underlying assumption that the interplay between ambient and focal processing mechanisms is discernible in relation to changes in inner mental models, such as when people update their event model of the current environment ( Eisenberg and Zacks, 2016 ) or when they switch between different tasks ( Guo et al., 2022 ). Therefore, one possibility is that a shift in conceptual direction during problem-solving might entail a shift between ambient and focal visual attention. Because shifts in conceptual direction typically occur when people identify a troubling issue, and when their conceptual representation of the problem is incomplete or incapable of leading to the solution. To resolve the troubling issue, a qualitative attentional shift would be a reasonable strategy to facilitate the restructuring and updating of the problem representation during this timeframe. However, the precise nature of such visual attention shifts remains ambiguous, given that the processing of information occurs through different attentional strategies depending largely on the current viewing goals of the designer. In Kaszowska (2019) , when designers change their conceptual direction, the troubling trigger and resolution phrases within a pivot sequence may transition either within the same content category (reflecting sustained focus on a particular object or event) or between different categories (reflecting a shift in general focus). More importantly, in the given task, eye movements play both the guiding and monitoring role in active vision (referred to as look-ahead and look-back fixations, as previously discussed), and these guiding and monitoring eye movements are differentially involved in various conceptual direction shifts, demonstrating that participants were involved in different ways of interacting with information. As such, the attentional shift strategy facilitating conceptual direction shifts could vary from trial to trial. For instance, it is likely that people engage in ambient exploratory processing at the troubling trigger’s onset—in the form of relatively short fixation durations together with long saccade amplitudes—in order to gather broad information within the egocentric spatial framework (task environment) and register features or events that might be associated with the troubling issue. Whereas after a shift in conceptual direction, a determined solution pops into mind, information about the space within the ambient field provides context for the ordering of focal perception within a specific part of the field—in the form of longer fixation durations together with shorter saccade amplitudes—which enable people to filter out distracting or irrelevant information and to think about the solution content represented in the conceptual system. On the other hand, the other direction—a transition from focal to ambient processing—seems also feasible. Suppose that a shift in conceptual direction represents the moment when the solver is heavily focused and realizes that he has reached an impasse, compelling him to explore new ideas. It is therefore possible that people maintain focal processing of the current problem representation until the realization of an impasse that demands a shift in conceptual direction. Once the conceptual direction has shifted, people switch from focal to ambient processing in order to capture as much information as possible for refining the mental representation of the newly concluded solution. Considering that individual characteristics, such as prior or advanced knowledge ( Gralla, 2014 ), age ( Griffin and Spieler, 2006 ), expertise ( Wineburg, 1991 ), or cultural background ( Kim, 2002 ), influencing how speakers perceive situations and approach tasks also make a difference in verbalizations, individuals may exhibit preferences for different attentional strategies, such as ambient-to-focal or focal-to-ambient.

Preliminary evidence for the temporal change in eye movement behavior around pivot events was reported in Kaszowska (2019) ; fixation durations showed a significant increase over the pivot sequence stage (before, during, and after a pivot). Nevertheless, the original study did not provide a time course of fixation durations and saccade amplitudes throughout the periods preceding and following pivot events, nor a comparable control analysis which could lead to an evaluated probability of having distinct eye movement patterns due to the presence or absence of pivot events.

Our analysis of the data by Kaszowska (2019) therefore sought to examine temporal changes in fixation durations and saccade amplitudes during the periods around conceptual direction shifts (reflected as pivot events in think aloud data). For simplicity, below we describe the conceptual direction shift as “pivot event” according to Kaszowska (2019) . Specifically, we hypothesized that pivot events would be accompanied by transitions between ambient and focal visual processing. If participants employed the ambient-to-focal attentional strategy, fixation durations would be short and saccade amplitudes would be long during the periods when they were approaching the pivot events. In contrast, in the periods following pivot events, fixation durations would become longer and saccade amplitudes would become shorter. Alternatively, if participants employed the focal-to-ambient attentional strategy, eye movement behavior would exhibit reversed temporal changes (decreased fixation durations and increased saccade amplitudes) during the periods around pivot events. However, such characteristics should not exist in a condition without pivot event. In a comparable control analysis (without any pivot event), where participants were fluently verbalizing the content of their thoughts without altering the conceptual direction, fixation durations and saccade amplitudes would be maintained at a steady level. It is also worth emphasizing that not every shift in conceptual direction necessarily coincides with a transition between ambient and focal visual processing. In other words, individuals may not consistently alter their gaze behavior in response to pivot events. Throughout a self-paced problem-solving process, it is likely that an individual exhibits varying patterns of gaze behavior during the periods around pivot events, including cases where gaze remains unchanged, transitions from ambient to focal processing, or transitions from focal to ambient processing. Nevertheless, our primary focus here is to investigate the predominant visual processing mechanism employed in the context of complex problem-solving. Consequently, we are interested in detecting qualitative attentional shifts in complex problem-solving as well as in a better understanding of the correspondence between parameters of eye movement and the temporal dominance of one of the two modes of visual processing.

2 Materials and methods

For our analysis, we used the data set from a real-world tool design task as an approximation to a real-life problem-solving situation. Below, we present an overview of the experiment setup, the data, and the methodology upon which we built our current work.

2.1 Tool design task

2.1.1 ethics declaration.

The study was approved by Tufts University Social, Behavioral, and Educational IRB under protocol approval number 1502022 ( Kaszowska, 2019 ).

2.1.2 Participant information

Forty-five participants (23 women, all native or near-native English proficiency) undergraduate and pre-master’s students (age M  = 19.7, SD  = 2.5) from Tufts University completed the study for monetary compensation. Participants were randomly assigned to one of three different conditions, each confronting a different intended end user for the tool (robot; human; or a team consisting of robot and human). Fifteen participants were randomly assigned (8 women in robot and human scenarios, respectively; 7 women in team scenario) to the conditions. Participants came from engineering (mechanical, civil, biomedical, environmental, electrical, and general), human factors, and computer science study programs.

2.1.3 Recording

Eye movement and think aloud recordings were performed using SMI Mobile Eye Tracking Glasses (ETG-1; SensoMotoric Instruments, Inc., Germany), at 30 Hz.

2.1.4 Task materials

Participants received a sample mixed up Lego NXT kit with trays (see Figure 2A ), and a printed reference picture (see Figure 2B ). Participants were free to manipulate Lego pieces.

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Figure 2 . Task materials. (A) Shows sample mixed up Lego NXT kit. (B) Shows reference picture for a sorted kit.

2.1.5 Set up

Testing took place in individual sessions. The participant was seated at a table, with the intended end user positioned centrally across the table: in robot and human conditions, the user was positioned centrally, whereas in the team condition both users were positioned next to each other (see Figure 3A for participant view). In both robot and team conditions, the robot was switched off, and one arm was propped up on a plain box (due to table height). In both human and team conditions, a human confederate was seated on a high stool, with hands resting in her lap.

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Figure 3 . Experiment setup. (A) Shows participants’ view in team condition, with the wooden frame surrounding the view. (B) Shows a schematic view of the experiment setup from above.

A wooden frame with green markers was attached to the table on the edge close to the end users (see Figure 3A ); it served as a reference for mapping eye movement data. For the purpose of maintaining a clean task environment (in which only task materials, the end user, and the table were presented), the setup was surrounded on three sides by a white room divider, with the supervising researcher seated nearby but out of participant’s sight (see Figure 3B ).

2.1.6 Procedure

The experiment started with an introduction, i.e., the researcher explained the purpose and content of the study, followed by obtaining written consent from the participant. Shortly after, the researcher gave a short demonstration of the mobile eye tracking system to familiarize the participant with the setup; the participant put on eye tracking glasses and was instructed to move around to get comfortable with the equipment.

For eye-tracker calibration, a whiteboard with pushpins was propped against the wooden frame on the participant station to cover the entire front field of the participant’s view (positioned at arm’s length to the participant), with pushpins serving as calibration points. A three-point calibration was performed. Following initial calibration, the participant again looked at calibration points as directed by the researcher to confirm calibration accuracy; if the estimated gaze point did not overlap with calibration points at this stage, calibration was repeated until satisfactory accuracy was achieved. After calibration, the whiteboard was removed, and task materials (Lego kit and reference image) were placed on the table in front of the participant. Furthermore, the participant received a think aloud training following procedure from Tenbrink and Taylor (2015) prior to the design task.

To begin with the task, the participant was provided with an explanation of the design problem. Specifically, the participant was instructed to conceptualize a tool (a physical piece of equipment) to optimize the sorting of Lego bricks for a particular end user (sorting must match the reference image Figure 2B ). Participant might not be familiar with the full extent of robot’s/person’s capabilities. If a particular capability or feature was crucial for participant’s design, for example the height of the robot/person, the participant could make an assumption. Upon understanding the design problem, the participant was given a 10 min brainstorming time window during which to explore possible solution paths. During brainstorming, the participant could look at the end user/reference image and manipulate the Lego bricks. After the 10 min brainstorming, the participant received plain paper, pens, scissors, and tape for use in visualizing his/her tool design idea (see Figure 4 for two examples of solutions provided by participants).

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Figure 4 . Examples for solutions provided by participants. (A) Shows a sketch of the tool idea drawn by a participant who worked with the robot end user. (B) Shows a prototype of the tool idea built by a participant who worked with the robot end user.

2.2 Data set

Throughout the course of 10 min brainstorming, both think aloud and eye tracking data were simultaneously recorded, leading to a true data fusion that allowed us to investigate the cognitive processes underlying design planning. It should be noted that, in Kaszowska (2019) , the intended end user for the tool (robot; human; or a team consisting of robot and human) did not affect the tool planning process. As our primary interest was to measure whether the eye movement behavior would be affected by a shift in conceptual direction, the data pre-processing and analysis presented in this work did not consider the end user factor.

2.2.1 Pivot events in think aloud

The analysis of verbalizations began with a verbatim transcription and proofreading (by two researchers), during which the speech is converted from the audio recording into a written form. Importantly, each word in the transcript was automatically timestamped using Google’s Speech-to-Text Conversion (version 1) and subsequently proofread by a researcher to ensure accuracy to 100 ms.

The think aloud data analysis was based on Cognitive Discourse Analysis ( Tenbrink, 2014 ), emphasizing two approaches to the verbal data: content-based inspection (providing in-depth insights about the designer’s current focus during solution planning), and analysis of linguistic features (reflecting patterns associated with particular concepts emergent in the protocol). Such semantic-content analysis of think aloud data enabled the identification of pivot events (instances where the verbalization indicates a shift in conceptual direction). The process of identifying pivot events involved three individuals: two coders, C1 and C2, and a referee designated as R1. The procedure unfolded through the following sequential steps: (a) Development of the pivot coding scheme: C1, C2, and R1 independently read the same three transcripts. C1 and C2 marked what they considered to be pivot events. Then C1, C2, and R1 compared their markings, addressing discrepancies through discussion. All discrepancies were resolved through discussion. In cases where C1 and C2 could not arrive at a compromise, R1 made the final decision. Based on this discussion, the final definition of pivot events was formalized. (b) C1 and C2 independently coded three new transcripts without consultation. The alpha assessing of inter-rater reliability was 0.89, exceeding the threshold of 0.8 suggested by Krippendorff (2004) . (c) C1 and C2 divided the remaining transcripts between themselves and conducted independent coding. In cases of uncertainty, R1 was consulted by the individual coders.

As outlined earlier in the introduction, a pivot event is often reflected as hesitation marker—such as “hm” or “um” in verbal reporting—indicating hesitation, uncertainty, or rethinking of an idea, denoting a shift in conceptual direction during the planning of solution paths. However, it is possible in the context of concurrent think aloud that not every hesitation corresponds to a conceptual direction shift, and not every conceptual direction shift is accompanied by a hesitation marker. Nonetheless, the pivot events within think aloud transcripts were identified based on their context, that is, based on the whether the sematic content of think aloud indicated a design direction shift.

2.2.2 Pivot events in eye tracking data

Eye tracking and think aloud data were matched based on event timestamps at the level of individual fixations and words. Each pivot event was identified within the timestamped transcripts. Pivot events can encompass silences and nonverbal content such as um , therefore the beginning and ending timestamps of pivot events were determined with regard to the surrounding timestamped words within the three-stage pivot sequence. For instance, a pivot event began at the ending timestamp of the preceding word (i.e., the last word in the trigger phrase when the participant encountered a troubling issue) and ended at the starting timestamp of the first word in the subsequent utterance (i.e., the first word in the resolution phrase). The corresponding timestamps from the transcripts were then used to identify time windows of interest related to pivot events within the eye tracking data. Fixations that coincided with the beginning and ending timestamps of each pivot event were annotated.

2.2.3 Eye movements pre-processing

Pre-processing of raw eye tracking samples was performed using SMI BeGaze (version 3.5, SensoMotoric Instruments, Inc.). Fixation data was provided in the form of a text file with start/end timestamps, duration, x -and y -coordinates for fixation position, and pupil-related metrics. Saccade amplitude was determined as the distance between two fixation locations (with x and y coordinates). Furthermore, fixations that contained blinks were excluded prior to data analysis. Fixations lasting less than 100 ms were removed if they occurred on either side of a blink. Fixation durations were trimmed to remove all fixations that were less than the sampling interval of 33 ms. This removed 0.2% of the eye movement data.

2.3 Data analysis

All analyses of eye movements reported here were carried out using MATLAB R2022a and R statistical software ( R Core Team, 2022 ). Fixations and saccades were analyzed in terms of fixation durations (ms) and saccade amplitudes (deg). Specifically, we examined the indications of ambient and focal modes of processing (reflected in temporal changes in fixation durations and saccade amplitudes) during the periods around the pivot events identified within the 10 min planning process. Throughout this 10 min planning process, a total of 2,854 pivot events were identified across all participants, with variations observed among participants (ranging from a minimum of 28 to a maximum of 127 pivot events). The median duration of pivot events is 1700 ms, with an interquartile range of 3,000 ms. Eye movements that occurred within this 10 min planning process constitute the database (a total of 141,958 fixations and saccades) for further processes.

As our goal was to examine whether pivot events are accompanied by transitions between ambient and focal visual processing, fixation durations and saccade amplitudes around pivot events were compared to fixation durations and saccade amplitudes during periods without pivot events (control analysis). The approach proceeds as follows (see red frame in Figure 1 for a visualization of the procedure). First, we selected 5 fixations preceding and 5 fixations following one pivot event to measure the temporal changes in gaze behavior during the periods around pivot events. The amplitude of subsequent saccades of these selected fixations were also subjected to analysis. To prevent any overlap between the selected fixations/saccades, if the interval between two pivot events was shorter than 10 fixations (e.g., when there were only 8 fixations between one pivot event end and the next pivot event start), the related metrics for both pivot events (i.e., the fixations/saccades within this interval) were excluded from the analysis. Then, to provide a comparable control analysis, we randomly selected continuous sequences of 10 fixations and their subsequent saccades from the database that did not include any pivot events (i.e., when participants were fluently verbalizing their thoughts without altering their conceptual direction) nor the pivot-related metrics (i.e., the 5 fixations/saccades preceding or following pivot events). The above procedure resulted in a total of 30,880 fixations and saccades as the dataset for pivot condition (about 34 sequences per participant, SD = 8.75) and a total of 39,380 fixations and saccades as the dataset for control analysis (about 44 sequences per participant, SD = 18.85), respectively. It is noteworthy that the utilization of an analysis window of 5 fixations before/after one pivot event enabled a more extensive analysis, covering 54% of all pivot events. In the given context, opting for a smaller analysis window allows for the inclusion of a greater number of pivot events for analysis (with consideration of the ‘no-overlapping’ selection criterion described above). Conversely, extending the analysis window to, for instance, 6 or 7 fixations before/after a pivot, would substantially reduce the number of pivot events available for analysis, covering 48 and 41% of pivot events, respectively.

Prior to analyses of the above-created datasets, we assessed the overall distribution of fixation durations from the database. As shown in Figure 5 , the distribution of fixation durations was positively skewed (skewness = 3.59) with the mode below the mean, where the median is more reflective of central tendency than the mean. Furthermore, given the likelihood of individuals exhibiting varying gaze behavior patterns around pivot events throughout the problem-solving process and the differing frequency of pivot events among participants, we aggregated data using median values, which are less affected by extreme values. Specifically, median values of fixation durations and saccade amplitudes were computed for each participant at every fixation number (corresponding to the numbering of fixations 1–10 selected around a pivot event, as depicted in Figure 1 ). These computed median values served as the basis for subsequent statistical analyses, including repeated measures multivariate analysis of variance (rm-MANOVA). Tests based on the MANOVA approach are free from sphericity assumptions and therefore do not lead to an inflated Type 1 error rate, which result in the more powerful test statistic if there is a contrast among the means that is reliable ( O'Brien and Kaiser, 1985 ; Algina and Keselman, 1997 ; Park et al., 2009 ). In the rm-MANOVA, Pillai test statistic was used and reported ( O'Brien and Kaiser, 1985 ).

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Figure 5 . The frequency distribution of fixation durations (70,979 counts) from the database. Red, blue, and green lines represent mean, median, and mode values, respectively.

Before delving deeper into individual processing mechanisms, we first evaluated whether the presence or absence of pivot events might lead to distinct gaze behavior. For this purpose, the analysis window containing 10 fixations was evenly divided into two phases: (1–5 represent the phase before and 6–10 represent the phase after a pivot event); average fixation durations during these two phases (averaging the medians) were computed individually for each participant in both the pivot and control analysis. A paired t -test was subsequently performed to determine whether the pivot and the control analysis differed in terms of temporal changes in fixation durations. These temporal changes, specific to each participant, were calculated as the difference between the average fixation duration in the phase before and the phase after, separately for both the pivot and control analysis. The results indicated a significant difference between the pivot and the control analysis for temporal changes in fixation duration, t (44) = 2.15, p  < 0.05; the mean difference between the two conditions was 7.20 ms, 95% CI [0.44, 13.96].

In order to investigate the effect of a pivot event on a finer grained level, e.g., what attentional strategy was deployed or preferred during this timeframe, we categorized participants into two groups—ambient-to-focal vs. focal-to-ambient—based on their temporal changes in fixation durations around pivot events in the pivot condition: 62% ( N  = 28) participants exhibited an increase in their average fixation durations from the phase before to the phase after pivot events, which constitutes the ambient-to-focal group; 38% ( N  = 17) participants exhibited a decrease in their average fixation durations from the phase before to the phase after pivot events, which constitutes the focal-to-ambient group. These distinct temporal changes observed for individual participant provided an initial assessment of their primary attentional strategy. For each group, custom contrast analysis within rm-MANOVA was used to validate the presence of their respective attentional strategy. Specifically, we tested two sets of contrasts: comparisons of phases (before vs. after) in each condition were performed to determine the characteristics of ambient and focal mode of processing; and comparisons of temporal changes in fixation durations/saccade amplitudes between the two conditions (pivot vs. control analysis) were performed to determine whether ambient-to-focal/focal-to-ambient processing occurs in tandem with pivot events. To set up contrasts, rm-MANOVAs were firstly conducted: rm-MANOVAs were conducted on the median values of fixation duration and saccade amplitude with the fixation number (from 1 to 10) and condition (pivot vs. control analysis), both serving as within-subjects factors, respectively (results of rm-MANOVAs see Table 1 ). The estimated marginal means for fixation durations/saccade amplitudes resulting from rm-MANOVAs are displayed in Figure 6 . For the ambient-to-focal group ( Figures 6A , B ), in the pivot condition, fixation durations were relatively short and the amplitude of subsequent saccades were long during the phase before pivot events. While during the phase after pivot events, fixation durations became longer and the amplitude of subsequent saccades became shorter. For the focal-to-ambient group ( Figures 6C , D ), in the pivot condition, fixation durations showed a decrease from the phase before to the phase after pivot events, while the amplitude of subsequent saccades remained relatively stable with a slight decrease. On the other hand, in the control analysis, both groups displayed generally steady fixation durations and saccade amplitudes between the two phases.

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Table 1 . Results of the repeated measure-MANOVA tests on median fixation durations/saccade amplitudes for respective groups.

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Figure 6 . Observations of fixation durations and saccade amplitudes with and without pivot events for respective groups. Estimated marginal means (estimated under rm-MANOVAs) for fixation durations (A,C) and saccades amplitudes (B,D) are grouped into two phases based on fixation number (fixation/saccade 1–5 represent the phase before and fixation/saccade 6–10 represent the phase after a pivot event), with the box representing medians, 25 and 75% quartiles and the whiskers the range.

Subsequently, custom contrasts were performed separately for the respective group based on the estimated marginal means for fixation durations/saccade amplitudes of the pivot and of the control analysis (results of custom contrasts see Table 2 ). The results for the ambient-to-focal group revealed significant differences in temporal changes in eye movement behavior between the two conditions: fixation durations exhibited a significantly greater increase while saccade amplitudes showed a significantly greater decrease in the pivot condition than in the control analysis. More importantly, the estimated differences (for ambient-to-focal group in Table 2 ) demonstrated a similar pattern to the distribution of the marginal means (see Figures 6A , B ): in the pivot condition, fixation durations significantly increased from the phase before to the phase after pivot events, while saccade amplitudes showed a decrease. Nevertheless, in the control analysis, eye movement behavior exhibited a generally smaller change, namely a decrease in fixation durations and a minimal increase in saccade amplitudes. On the other hand, the results for the focal-to-ambient group showed a significant difference in temporal changes in fixation durations between the two conditions: fixation durations displayed a significantly greater decrease in the pivot condition than in the control analysis ( cf. Figures 6C , D ). No significant difference was observed between the two conditions for temporal changes in saccade amplitudes. In the control analysis, eye movement behavior remained relatively stable.

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Table 2 . Custom contrasts within repeated measure-MANOVA tests for respective groups.

4 Supplementary analysis

Past research has shown that eye movements are not solely the result of current visual processing needs, but also depend on internal (mental) representations ( Richardson and Spivey, 2000 ; Spivey and Geng, 2001 ; Altmann, 2004 ; Ehrlichman et al., 2007 ). For instance, Richardson and Spivey (2000) reported eye movements to relevant regions triggered by questions about auditory and semantic—rather than visual—information acquired even when the actual stimulus/event is no longer presented. As outlined earlier, a pivot event typically occurred when participants started to be faced with a difficulty and had to choose between possible ideas/approaches to update the problem state, as a result of greater cognitive demand in language production ( Barr, 2001 ). Suppose the onset of a pivot event reflects an impair in both the straight cognitive aspects of speech planning and the metacognitive aspects of problem-solving (in this context, participants began to shift their conceptual direction), which introduces a top-down interference to the attentional system, requiring the individual to find a new balance between internal processing versus perceptual processing. This balance shift might result in a breakdown of the “normal” moment-to-moment gaze control process and manifest itself in gaze behavior. As such, expecting a smooth transition between ambient and focal gaze behavior (e.g., fixation durations steadily increase while saccade amplitudes decrease) at this very moment may be somewhat oversimplified. Correspondingly, an exploratory analysis of visual fixations around pivot event onset is carried out in order to investigate how people’s gaze behavior may be affected when they experience the beginning of a conceptual direction shift.

4.1 Data analysis

For the exploratory analysis of potential oculomotor responses to the beginning of a pivot event, we used a similar approach (see blue frame in Figure 1 for a visualization of the procedure). We selected the onset of the pivot event as a reference point and analyzed fixations occurring around this time. In particular, we defined an analysis window consisting of a continuous sequence of 9 fixations. These 9 fixations were selected as the 4 fixations preceding and the 4 fixations following the one during which the pivot event began. Pivot events were excluded from analysis if they spanned fewer than 5 fixations or if the interval between them was shorter than 4 fixations (for the purpose of ensuring the 4 fixations preceding the pivot event onset did not overlap with the end of previous pivot event). In order to prevent any potential influence of ambient/focal processing occurring after pivot events on our observations, the 4 fixations following the pivot event onset should take place within the pivot event itself. This procedure resulted in 11,394 fixations as the dataset for further analysis (about 28 sequences per participant, SD  = 7.01).

Moreover, as we suppose that visual fixations might work as an instantaneous indicator of the onset of a pivot event, an assessment of how different fixations are distributed around the time of pivot event onset was also of interest. This approach is beneficial for localizing effects in time since it can show whether the predicted behavior (e.g., a change in fixation duration) is primarily attributable to the pivot event onset. For this purpose, the above analysis was extended with two additional approaches. First, we categorized fixation durations (11,394 fixations forming the above dataset) into tertiles (i.e., short, intermediate, and long) and compared their frequencies around the onset of the pivot event. Second, we evaluated fixation durations prior to the occurrence of any pivot event. Specifically, we defined an observation period for each participant that started with the think aloud onset and terminated before the occurrence of the first pivot event (for an example, see the lower part of the blue frame in Figure 1 ). The duration of this observation period as well as the median value of the fixation durations within it (about 42 fixations per participant) were then computed for each participant individually.

4.2 Visual fixations as an instantaneous indicator of pivot event onset

To investigate the effect of the beginning of a pivot event on visual fixations, an rm-MANOVA was conducted on the median values of fixation durations (computed for each participant at every fixation number, ranging from “-4” to “4” relative to the onset of the pivot event, as depicted in Figure 1 ), with the fixation number serving as within-subjects factor. Analysis revealed significant changes of fixation durations over the fixation numbers, F (8, 37) = 5.06, p  < 0.001, Pillai’s trace = 0.52. The estimated marginal means for fixation durations resulting from the rm-MANOVA are displayed in Figure 7A . As shown in Figure 7A , an instantaneous prolongation of fixation can be observed at the moment of the pivot event onset (numbered as “0”). Interestingly, the durations of the fixations preceding and following the pivot event onset do not seem to be affected much by the occurrence of pivot event. The follow-up post hoc pairwise t -test comparisons (Holm corrected) confirmed that the fixations during which the pivot event began were significantly longer than fixations both preceding and following the pivot event onset (all p  < 0.05), with the exception of the latest fixation within the pivot event numbered as “4” in Figure 7A . No significant difference was found between fixations preceding and following the pivot onset.

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Figure 7 . Visual fixations relative to the onset of the pivot event. Estimated marginal means (estimated under rm-MANOVA) for fixation durations are plotted over the fixation number relative to the onset of a pivot event (A) . The “0” corresponds to the fixation at the moment of the pivot event began. Error bars represent ±1 standard error. Frequencies of fixation durations of three categories around the onset of a pivot event (B) . Median fixation duration within the period ranging from think aloud onset until the first pivot event as a function of the period duration is plotted as data point for each individual participant (C) , with two outliers (data points located on the x-axis above 100 s) excluded. The purple dashed line represents linear regression fit to the data.

Another interesting effect can be seen in Figure 7B , as we compared frequencies of the three categories of fixation durations (categorized into tertiles) around the onset of the pivot event. It clearly demonstrates that the three categories of fixation durations were affected by the beginning of a pivot event in different ways: there was a considerable reduction of relatively short fixations (category less than 133 ms) and an increase of longer fixations (category above 233 ms). Finally, the assessment of fixation durations within the period ranging from think aloud onset until the first pivot event (see Figure 7C ) revealed that, for instance, participants tended to conduct relatively short fixations (e.g., shorter than 233 ms) until they approached the first pivot event. Meanwhile, the linear regression slope in Figure 7C shows a positive correlation between fixation duration and the period from think aloud onset until the first pivot event, indicating that when it took longer for participants to reach the first pivot, longer fixations tended to be involved. However, this correlation exceeded statistical significance ( r  = 0.404, p  = 0.411).

5 Discussion

Solving problems in real-world settings is an inherently complex process that requires people to systematically evaluate and update the problem states which lie on different possible solution paths linking the initial problem state and the goal state ( Newell and Simon, 1972 ; Kounios et al., 2008 ; Barbey and Barsalou, 2009 ). The work presented here investigated eye movement behavior when participants explored possible solution paths to a complex tool design problem, and gathered additional insights into the relationship between visual attention and internal thinking underlying solving processes. In particular, we analyzed participants’ eye movements within and around the pivot events (i.e., the specific instances where participants shifted the conceptual direction as they planned solutions to the design problem) identified within the concurrent think aloud protocol (participants verbalized ongoing thought processes out loud). The analysis of eye movements around pivot events suggested a deployment of the ambient-to-focal rather than focal-to-ambient visual processing—participants’ fixation durations increased while saccade amplitudes decreased from the periods preceding to the periods following pivot events. In contrast, such characteristics were not observed in the control analysis which did not involve pivot events, indicating that the ambient-to-focal processing occurred in tandem with shifts in conceptual direction during problem-solving. Furthermore, the analysis of visual fixations around the pivot event onset revealed a significant increase in fixation duration at the moment of the pivot event onset, suggesting that starting a shift in conceptual direction manifests itself in oculomotor behavior.

5.1 Deployment of ambient and focal attention in problem-solving

Viewing change of problem representation as a search process for solution allows us to account for complex problem-solving ( Newell and Simon, 1972 ; Kaplan and Simon, 1990 ; Ohlsson, 1992 ), such as tool designing. In light of the crucial role that perceptual processes play in generating problem representations ( Simon, 1978 ), it is possible that when solvers encounter difficulties compelling them to shift their conceptual direction in order to adjust the solution path, they employ certain perceptual strategies to facilitate representing critical features of the task environment in their conceptual representation of the problem. We therefore hypothesized that a switch between ambient and focal visual attention would be useful during that timeframe. Individuals might be differentially susceptible to this particular phenomenon. To be specific, individuals inclined toward the ambient-to-focal attentional strategy may find ambient exploratory processing enables a rapid influx of information necessary for adaptive updating of problem representation (as they are approaching the shift in conceptual direction), whereas more memory-based focal processing (as its underlying ventral stream utilizes stored representations of the information/features) facilitates a deep understanding and fluent processing of the semantic meanings of the new solution arising in mind. In contrast, individuals inclined toward the focal-to-ambient attentional strategy may find ambient processing to be an effective alternative for refining the new solution represented in the conceptual system with immediate information/features since the focal processing of the initial problem representation has reached an impasse.

Our data provide support for this hypothesis. First, distinct fixation behaviors were observed (regarding temporal changes) between the pivot condition and the control analysis without pivot events, highlighting the close interaction between perceptual and cognitive processes. Second, a more detailed analysis of eye movement behavior for participants in ambient-to-focal and focal-to-ambient groups (participants were classified based on their fixation behavior) yielded different results. In the ambient-to-focal group, participants’ fixation durations were relatively short and saccade amplitudes were long prior to pivot events, i.e., where participants approached the shift in conceptual direction, suggesting ambient mode of processing. Once pivot events were over (the conceptual direction has shifted), fixation durations became longer and saccade amplitudes became shorter, suggesting focal mode of processing. Alternatively, one could only accept that the main rm-MANOVA analysis shows saccade amplitudes interacting with the control analysis for the ambient-to-focal group (refer to the interaction between two factors in Table 1 ), but this is not necessarily the case in the given context. Over a pivot sequence where the participant sustained focus on a particular object/event (an instance where the troubling trigger and resolution phrases fall within the same content category), larger saccades for ambient viewing (e.g., registering different aspects of the reference image) are not essential for a much smaller attentional window. Therefore, it is possible that the saccade amplitudes show significant differences in the contrast analysis with more nuanced time modeling that the overall rm-MANOVA did not capture. The phenomenon observed in the pivot condition is fundamentally different from the control analysis. In the control analysis, participants’ fixation durations and saccade amplitudes remained generally stable over time—fixation durations remained long and saccade amplitudes remained short—as they were fluently thinking aloud without altering their conceptual direction, demonstrating their involvement in a rather stable focal processing. The differing gaze behavior between the pivot and the control analysis may be attributed, in part or fully, to the hypothesis that the occurrence of a shift in conceptual direction drives the change from ambient to focal visual processing. Our view that ambient to focal visual attention effectively complements shifts in conceptual direction connects nicely with a view reported by Guo et al. (2022) , in which ambient to focal processing behavior is found to be deployed in task processing and is closely relative to the inner mental model, i.e., mental shifts between different tasks lead to such gaze behavior.

On the other hand, the focal-to-ambient attentional strategy would reverse this pattern. However, in the focal-to-ambient group, no focal to ambient behavior was identified for saccade amplitudes, and the statistical difference between the pivot and the control analysis was not significant for saccade amplitudes. A possible explanation for the observation that fixation durations and saccade amplitudes both showed a decrease from the phase before to the phase after pivot events is that the short fixations and saccades may serve for rapid information sampling and retrieval, facilitating the refinement of the newly generated solution. After a shift in conceptual direction, the problem representation is updated with critical visual features, and a determined solution pops into mind. However, refining this updated problem representation may require returning the eyes to the critical features for retention and activation of semantic representations and identities of attend features ( Henderson and Hollingworth, 2006 ; Ferreira et al., 2008 ). Given that solvers are already acquainted with the critical features embedded in their updated mental representation (e.g., their locations and spatial relations), exhaustive scanning of the task environment to obtain broad information is no longer necessary. Instead, short fixations and saccades may be more effective means of revisiting the target features, allowing for rapidly sampling and retrieval of additional aspects of information within rather specific attentional windows. It is therefore possible that this eye movement behavior is a result of strategic decisions aimed at minizine the working memory load, rather than retaining a detailed visual representation of the external world ( Hayhoe and Ballard, 2005 ; Henderson and Hollingworth, 2006 ).

Furthermore, it is noteworthy that the mean saccade amplitudes for the focal-to-ambient group, in both the pivot and control analysis, are distinctly larger than those observed for the ambient-to-focal group ( cf. Figures 6B , D ). This observation underscores the existence of diverse perceptual processing behaviors employed during problem-solving, which are evident through distinct eye movement patterns, specifically in fixation-and saccade-related metrics.

Conversely, considering the reported temporal changes in fixation durations/saccade amplitudes around pivot events were relatively small, one could argue that the observed differences may be attributable to possible measurement error. This consideration is pertinent when taking into account that the data were sampled at 30 Hz, which could lead to less precise characterization of eye movement events ( Anantrasirichai et al., 2016 ; Mack et al., 2017 ; Stein et al., 2021 ). However, it is unlikely that the differing eye movement patterns between the pivot and the control analysis were due to an effect of measurement error, especially given that the overall value of fixation durations was considerably small (see Figure 5 , the mode value) and the differences in temporal changes of fixation durations and saccade amplitudes between the two conditions were statistically significant for the ambient-to-focal group. Instead, it is possible that individual differences among participants (e.g., differences in the frequency of pivot events and in fixation-and saccade-metrics, cf. y-axis values of fixation duration and saccade amplitude between the two groups in Figure 6 ), or variations in the characteristics of pivot events (e.g., duration, magnitude, and the speaker’s conceptual focus before/after a pivot), led to the predicated features of ambient and focal visual attention, but lack of a more compelling distinction. From a methodological perspective, however, eye tracking data with higher temporal resolution would be desirable in order to underpin the results presented here. Furthermore, in an extended self-paced task, inherent intraindividual differences become relevant; participants may exhibit diverse patterns of gaze behavior throughout the task, involving shifts from focal to ambient, ambient to focal, or maintaining a consistent pattern. Collecting and aggregating data from these events for each participant could have potentially reduced the statistical differences when analyzing temporal changes in fixation durations and saccade amplitudes. Future research that delves into intraindividual differences within extended complex tasks will shed light on how gaze behavior evolves over time or in response to varying events.

It is also worth noting that the time scale used in the current study for measuring ambient and focal modes of processing is vastly different from that used in earlier studies. Previous research looked at changes in attentional processing over a few seconds of time. For instance, in scene viewing studies, ambient and focal eye movement characteristics were monitored over time courses ranging from 20 fixations ( Velichkovsky et al., 2005 ) up to 20 s ( Unema et al., 2005 ; Eisenberg and Zacks, 2016 ). Other than well-controlled scene viewing tasks in which participants attend to the stimulus for a specified amount of time as instructed, Guo et al. (2022) measured ambient and focal gaze behavior over a 3 s time scale based on the results of gaze distribution analysis. However, these analysis windows are unlikely to generalize to our study, since participants were free to view and interact with the real-world task environment during the problem-solving process. It is difficult to predict the precise moment at which participants will become aware of the impasse in their solution paths. Considering that the size of the analysis window directly affects the number of pivot events included in the analysis (as detailed in the Data Analysis section), estimating 10 fixations/saccades (study phase) around the pivot event can be a more versatile approach across various conceptual shifts.

Importantly, pivot events, signifying shifts in conceptual direction, occurred frequently in the think aloud data of our study. These frequent conceptual shifts can be attributed to two factors. First, it is essential to note that not all conceptual shifts in our analysis are qualitatively equal; they vary in magnitude, involving shifts between main ideas or different perspectives on the same idea. Since our primary focus is on identifying qualitative attentional shifts in relation to shifts in conceptual direction, including all types of conceptual shifts allowed for a more extensive analysis. Second, participants were actively engaged in brainstorming, a process characterized by frequent shifts in conceptual direction as individuals explored possible avenues to solve the problem and promptly evaluated ideas. Additionally, it is noteworthy that the analysis approach for identifying pivot events in think aloud was an original contribution by Kaszowska (2019) . Think-aloud studies in complex tasks generally look at broad themes explored by participants (e.g., Gagné and Smith, 1962 ; Van Gog et al., 2005 ; Ward et al., 2011 ; Elling et al., 2012 ) rather than delving into specific problem-solving strategies as approximated by minor changes in language.

Overall, the point to be emphasized here is that while different eye movement behaviors were identified around conceptual direction shift, one apparent similarity is that the control of eye movements is contingent on the specific circumstances under which differences in cognitive processes are exhibited, e.g., the presence of conceptual direction shift is accompanied by a change in gaze behavior. Moreover, the available evidence supports the formulation of the ambient-to-focal attentional strategy in problem-solving, even though it is not always employed by everyone. Nevertheless, given the considerations and limitations mentioned above, as well as the relatively subtle distinctions observed between ambient and focal eye movement characteristics, our findings should be considered provisional, and this study requires replication in another venue to test the reproducibility and consistency of our findings. Further work to bridge the gap between the laboratory analysis conclusions and the data observed in real-world settings is needed to uncover more powerful evidence of the effects of conceptual shift on ambient and focal attentional mechanisms.

5.2 Supplementary analysis: oculomotor response to the beginning of a conceptual shift

Our supplementary analysis is largely exploratory. Given that starting a shift in conceptual direction interrupts the ongoing thought processes during problem-solving, impairing cognitive performance (i.e., speech planning) by competing for the individual’s limited attentional resources, and thereby allowing additional information to be processed for reconstructing/updating the problem representation, it seems plausible to expect oculomotor behavior to display a notable response to the onset of a pivot event. The results provide broad support for this hypothesis. The analysis of fixation durations around the moment of pivot event onset indicates that fixation responses to the beginning of pivot events were strong, reliable, and rapid with a significant prolongation (see Figures 7A , B ). More importantly, such long fixations (e.g., longer than 233 ms) seem mostly allocated to the moment of pivot event onset (see Figures 7B , C ).

In search of factors that may clarify the observed effect, a group of possible explanations have emerged. These explanations are not mutually exclusive and could operate in a parallel fashion. One is that the prolongation of fixations may be an expression of the orienting response ( Pannasch et al., 2001 ; Graupner et al., 2007 ). Prior findings demonstrating that the presentation of a distractor in stimulation ( Graupner et al., 2007 ; Pannasch et al., 2011 ; Devillez et al., 2017 ) or abrupt visual changes, such as the appearance of new objects ( Brockmole and Henderson, 2008 ) or the emergence of hazard events ( Velichkovsky et al., 2002 ), captures attention immediately and results in an effect on the duration of a current fixation. Especially, through earlier statements that can be found in a well-known paradigm of eye tracking research, namely distractor presentation experiments, a comparable behavior of visual fixation was observed for both visual and auditory distractors during scene viewing (see Figure 8A ); and this observation was interpreted within the framework of novelty-based reactions such as orienting response ( Pannasch et al., 2001 ; Graupner et al., 2007 ; Pannasch and Velichkovsky, 2009 ). The orienting response describes the behavioral and physiological responses, such as a deceleration of heart rate ( Graham and Clifton, 1966 ) or distinctive meaningful brain network activity ( Williams et al., 2000 ), to any novel or significant events. Such an orienting response is thought to signal the active orientation of attention towards these events and to facilitate event processing. In difference to fixation responses to meaningless distractors, similar effects were later reported in a study of hazard-related changes in fixation durations ( Velichkovsky et al., 2002 ). Velichkovsky et al. (2002) found that during a driving simulation task, when participants detected a hazardous event (i.e., dangerous traffic situation), fixation duration remarkably increased, despite the numerous repetitions of the hazard event across 5 consecutive drive trials (see Figure 8B ). The authors explained this behavior as participants engaged in more focal processing of the detailed information from the hazard event, which was considered necessary to avoid an accident.

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Figure 8 . Comparable oculomotor responses from earlier studies. Panel (A) is adapted from Pannasch et al. (2001) with permission, depicting the presentation of a visual or auditory distractor prolonging fixations during unspaced scene viewing. Panel (B) is adapted from Velichkovsky et al. (2002) with permission, depicting an instantaneous increase in fixation duration when participants detected an immediate hazard in a driving simulation task.

Our finding replicated the results from the above-mentioned eye tracking studies—despite the substantial difference being that there was no novel or significant external event involved in the current experimental paradigm—a prolongation of fixations always appeared. In the present study, all changes in eye movement behavior were based on internal process changes, following closely the actual path of thinking. It is interesting to note that although internal and external events are not automatically analogous, they both manifest themselves in oculomotor behavior in the same manner. Rather than relying on external triggers, the onset of updating internal representation of a problem could also evoke a notable fixation response (i.e., instantaneously prolonged fixation duration). However, the view that an internal event could elicit orienting reflex will need to be justified by future investigations.

Another possible explanation for the finding that fixations were longer at the moment of pivot event onset is that longer fixation durations are associated with the internalization of attention ( Foulsham et al., 2013 ; Krasich et al., 2018 ; Zhang et al., 2021 ). It seems puzzling that, as noted earlier, fixation durations are typically used to identify transitory information-processing priorities of the visual system, with longer fixations classified as focal level processing that is associated with a more in-depth analysis of visual information ( cf. Unema et al., 2005 ; Pannasch et al., 2008 ; Fischer et al., 2013 ). However, studies of the relationship between mind wandering and eye movements in the contexts of scene perception ( Krasich et al., 2018 ; Zhang et al., 2021 ) and reading ( Reichle et al., 2010 ; Faber et al., 2018 ) demonstrate that the longer fixation duration may also indicate lesser engagement with visual information processing. For instance, mind wandering was found to be associated with fewer and longer fixation durations on the scene compared with reports of attentive viewing during real-world scene viewing ( Krasich et al., 2018 ). Mind wandering can be viewed as a state where one’s attentional priorities shift away from external environment towards internal thoughts and feelings ( Smallwood and Schooler, 2006 ), e.g., looking at the visual surroundings but thinking of something else irrelevant to the primary task. Experiencing conceptual direction shifts (pivot event) in problem-solving may share important information-processing characteristics with mind wandering—as it also requires the shift of attention away from online sensory information towards internal conceptual representation of the problem, which involves the explicit internalization of attention. In our case, however, internally focused attention is still intentionally directed toward the primary task, i.e., tool design. Considered in this light, when attentional resources decouple from external information and turn inward for the purpose of reorganizing/updating problem representation at the onset of a pivot event, visual processing may become less efficient. Consequently, the benefit of maintaining the current fixation may increase, leading to a prolonged fixation. Indeed, previous research has suggested that difficulties at the level of visual and cognitive processing can delay or even cancel saccade initiation, thereby extending the durations of fixations ( Yang and McConkie, 2001 ; Nuthmann et al., 2010 ).

Based on this view, our data suggest that eye movements could be used to predict the moment-to-moment information-processing prioritization of the visual system across changing attentive states—from attending to ongoing task-relevant stimuli to focusing on internal representation. This finding can serve as an important springboard for future research exploring the potential uses of real-time gaze-based detection of conceptual shifts in applied context, e.g., task processing or problem-solving.

In addition to the above-discussed explanations, a more “low-level” account suggests that the observed transient increase in fixation duration may be attributable to the synchrony with the vocal response used to define the onset of the pivot event in the think aloud protocol. Sensorimotor synchronization refers to a situation in which an action is coordinated with a predictable external event, especially one characterized by periodic or rhythmic patterns ( Large and Jones, 1999 ; Repp, 2005 ). This phenomenon has been extensively investigated in the context of simple repetitive tasks, where participants are required to accompany a stimulus with a simple movement, for example, finger tapping to a visual, auditory or combined auditory–visual metronome (e.g., Aschersleben, 2002 ; Chen et al., 2002 ; Repp, 2003 ). Interpreting the transient increase in fixation duration as a result of some form of sensorimotor synchronization would imply that the observed transient prolongation of fixation is an epiphenomenon stemming from the specific paradigm—namely, the co-registration of eye movements and a think aloud protocol—rather than being linked to problem-solving. Nevertheless, this explanation appears less plausible, given that participants were continuously speaking (thinking aloud) both before and after this specific vocal response. Future investigations are required to explore the potential influence of sensorimotor synchronization on human gaze behavior.

6 Conclusion

The current work investigated eye movement behavior while participants adjusted their solution paths to a complex open-ended design problem, which revealed an intimate relationship between visual attention and cognitive processes underlying problem-solving. Adding to the existing knowledge about ambient and focal visual attention, our data provide preliminary support for the existence of ambient and focal attentional processing during realistic complex problem-solving by demonstrating temporal dynamics in fixation durations and saccade amplitudes during the periods around shifts in conceptual direction. Moreover, our data demonstrate that the beginning of a shift in conceptual direction is observable in oculomotor behavior with a significant prolongation of fixations. The findings presented here show a direct relation between patterns of eye movement and modes of attentional processing, which offers a point of departure for future research into ambient and focal attentional mechanisms in higher—semantic and metacognitive—levels of information processing during complex tasks. As a result, eye tracking will become of greater importance in the development of future applications, as well as part of future applications themselves.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Tufts University Social, Behavioral, and Educational IRB. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

YG conceptualized the study, conducted the data analyses, drafted and revised the manuscript under supervision of SP and JH. SP, JH, and AK reviewed and approved the final version of the manuscript for submission. All authors contributed to the article and approved the submitted version.

This work was funded by “Deutsche Forschungsgemeinschaft“(DFG, German Research Foundation) under grant number 319919706/RTG2323 “Conducive Design of Cyber-Physical Production Systems” and as part of Germany’s Excellence Strategy – EXC 2050/1 – Project ID 390696704 – Cluster of Excellence “Centre for Tactile Internet with Human-in-the-Loop” (CeTI) of Technische Universität Dresden. The data collection of the original work was funded by Tufts Collaborates Seed Grant Program.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: two visual systems, problem-solving, think aloud, real-world eye movements, ambient attention, focal attention, fixation duration, saccade amplitude

Citation: Guo Y, Pannasch S, Helmert JR and Kaszowska A (2024) Ambient and focal attention during complex problem-solving: preliminary evidence from real-world eye movement data. Front. Psychol . 15:1217106. doi: 10.3389/fpsyg.2024.1217106

Received: 04 May 2023; Accepted: 31 January 2024; Published: 15 February 2024.

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Copyright © 2024 Guo, Pannasch, Helmert and Kaszowska. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yuxuan Guo, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Heavy Machinery Meets AI

  • Vijay Govindarajan
  • Venkat Venkatraman

systems thinking solving complex problems

Until recently most incumbent industrial companies didn’t use highly advanced software in their products. But now the sector’s leaders have begun applying generative AI and machine learning to all kinds of data—including text, 3D images, video, and sound—to create complex, innovative designs and solve customer problems with unprecedented speed.

Success involves much more than installing computers in products, however. It requires fusion strategies, which join what manufacturers do best—creating physical products—with what digital firms do best: mining giant data sets for critical insights. There are four kinds of fusion strategies: Fusion products, like smart glass, are designed from scratch to collect and leverage information on product use in real time. Fusion services, like Rolls-Royce’s service for increasing the fuel efficiency of aircraft, deliver immediate customized recommendations from AI. Fusion systems, like Honeywell’s for building management, integrate machines from multiple suppliers in ways that enhance them all. And fusion solutions, such as Deere’s for increasing yields for farmers, combine products, services, and systems with partner companies’ innovations in ways that greatly improve customers’ performance.

Combining digital and analog machines will upend industrial companies.

Idea in Brief

The problem.

Until recently most incumbent industrial companies didn’t use the most advanced software in their products. But competitors that can extract complex designs, insights, and trends using generative AI have emerged to challenge them.

The Solution

Industrial companies must develop strategies that fuse what they do best—creating physical products—with what digital companies do best: using data and AI to parse enormous, interconnected data sets and develop innovative insights.

The Changes Required

Companies will have to reimagine analog products and services as digitally enabled offerings, learn to create new value from data generated by the combination of physical and digital assets, and partner with other companies to create ecosystems with an unwavering focus on helping customers solve problems.

For more than 187 years, Deere & Company has simplified farmwork. From the advent of the first self-scouring plow, in 1837, to the launch of its first fully self-driving tractor, in 2022, the company has built advanced industrial technology. The See & Spray is an excellent contemporary example. The automated weed killer features a self-propelled, 120-foot carbon-fiber boom lined with 36 cameras capable of scanning 2,100 square feet per second. Powered by 10 onboard vision-processing units handling almost four gigabytes of data per second, the system uses AI and deep learning to distinguish crops from weeds. Once a weed is identified, a command is sent to spray and kill it. The machine moves through a field at 12 miles per hour without stopping. Manual labor would be more expensive, more time-consuming, and less reliable than the See & Spray. By fusing computer hardware and software with industrial machinery, it has helped farmers decrease their use of herbicide by more than two-thirds and exponentially increase productivity.

  • Vijay Govindarajan is the Coxe Distinguished Professor at Dartmouth College’s Tuck School of Business, an executive fellow at Harvard Business School, and faculty partner at the Silicon Valley incubator Mach 49. He is a New York Times and Wall Street Journal bestselling author. His latest book is Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future . His Harvard Business Review articles “ Engineering Reverse Innovations ” and “ Stop the Innovation Wars ” won McKinsey Awards for best article published in HBR. His HBR articles “ How GE Is Disrupting Itself ” and “ The CEO’s Role in Business Model Reinvention ” are HBR all-time top-50 bestsellers. Follow him on LinkedIn . vgovindarajan
  • Venkat Venkatraman is the David J. McGrath Professor at Boston University’s Questrom School of Business, where he is a member of both the information systems and strategy and innovation departments. His current research focuses on how companies develop winning digital strategies. His latest book is Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future.  Follow him on LinkedIn . NVenkatraman

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  3. Solving Complex Problems: Structured Thinking, Design Principles, and

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  4. System Dynamics Understanding Complex Problems through Systems Thinking

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  5. 8 Tips for Solving Complex Problems

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  1. The problem observed by Stanford lecturer

  2. SOLVING PROBLEMS & USING ANALYTICAL & INTERGRATED THINKING

  3. Systems Thinking

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  5. Complexity Science : 3 Systems Thinking

  6. The Five Pillars of Systems Thinking: Communication, People, Objectives, Metrics, and Networks

COMMENTS

  1. The Six Systems Thinking Steps to Solve Complex Problems

    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

  2. Taking a systems thinking approach to problem solving

    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.

  3. How to solve complex problems using systems thinking

    Founded in 1956 by MIT professor Jay Forrester, systems thinking is an approach to solving complex problems by understanding the systems that allow the problems to exist. You have a complex problem when: There's no clear cut agreement on what the problem really is because the context it depends on evolves over time.

  4. Systems Thinking in the Workplace: A Complete Guide

    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.

  5. Systems Thinking: A Deep Dive Into The Framework To Successfully Solve

    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.

  6. What 'systems thinking' actually means

    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.

  7. Framing Complex Problems with Systems Thinking

    Framing Complex Problems with Systems Thinking Cornell Course Tell me more! Online Course Overview Whether you need to tackle a complex project, communicate more effectively, rethink your organization or your job, solve world hunger, or figure out your teenager, systems thinking can help you.

  8. Complex Problem Solving Through Systems Thinking

    Systems thinking was designed to improve people's ability to manage organizations comprehensively in a volatile global environment. It offers managers a framework for understanding complex situations and the dynamics those situations produce. Systems thinking is a response to the rapid changes in technology, population, and economic activity ...

  9. Understanding Systems Thinking: A Path to Insightful Problem-Solving

    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.

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

    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.

  11. What is systems thinking?

    1. Interconnections: Projects and people are connected. A systems thinking approach identifies those connections. This shifts the problem from a linear solution to a circular solution. 2. Emergence: The opposite of working "in silos," emergence is where a larger idea or outcome is born from smaller parts.

  12. Introduction: Managing Complex Tasks with Systems Thinking

    In this section: Parts III to VII of this book, we will see how systems thinking can help us solve complex and dynamic problems in various domains, such as education, technology, agriculture, sustainability, and healthcare. Systems thinking is a way of understanding the interrelationships and patterns of behavior in a complex situation.

  13. Assessing systems thinking: A tool to measure complex reasoning through

    Systems thinking is a critical interdisciplinary skill that describes the cognitive flexibility needed to collaboratively work on problems facing society. Although institutions of higher education are asked to develop systems thinkers and many programs strive towards such an aim, mechanisms to assess this competency are lacking.

  14. 141: Solving Complex Problems with Systems Thinking

    Solving complex problems with systems thinking. Both systems thinking and systems engineering are necessary, and they're on two different axes. One system is not an extension of the other. In reinforcing feedback loops, a small amount of growth enforces the overall likelihood of growth. Systems engineering techniques break complex problems ...

  15. How systems thinking compliments behavioural approaches in solving

    How systems thinking compliments behavioural approaches in solving complex problems A holistic approach to examining problems and identifying patterns of behaviour Throughout 2021 BehaviourWorks Australia (BWA) is publishing a book to help policymakers and program managers use tools within our 'Method' to design and deliver better and more ...

  16. Systems Thinking

    Systems Thinking is an interdisciplinary approach that focuses on understanding the interconnectedness and relationships between various components within a complex system. By considering the whole system and its parts, the approach provides a framework for analyzing and solving complex problems, making informed decisions, and promoting effective solutions.

  17. How to Use Systems Thinking to Solve Tough Problems and Get ...

    To fireproof your hillside, you have to see the whole system - including the patterns, institutional structures and values that played a part in creating the problem - in order to solve it. As defined, systems thinking is an approach to problem solving that attempts to balance holistic thinking and reductionist thinking.

  18. Systems Thinking

    Whether you need to tackle a complex project, communicate more effectively, rethink your organization or your job, solve world hunger, or figure out your teenager, systems thinking can help you. All of these are complex and challenging real-world problems, sometimes called wicked problems.

  19. Systems Thinking and How It Can Help Build a Sustainable World ...

    Systems thinking is the ideal problem-solving framework for sustainability. The two go hand-in-hand. A sustainable community is one whose actions don't diminish the social opportunities and ecosystem health for future generations while being resilient against social and ecological shocks or changes.

  20. Solving Complex Problems: Structured Thinking, Design Principles, and AI

    In our new course Solving Complex Problems: Structured Thinking, Design Principles, and AI, you'll acquire core principles that will change the way you approach and solve large-scale challenges—increasing your likelihood of success.

  21. Solving Complex Problems with Systems Thinking

    A system-based approach is a step-by-step plan that breaks up the complex problem into smaller problems, layering a solution on top of a solution for each step, allowing for the variables...

  22. Systems Thinking For Social Change: A Practical Guide to Solving

    It also gives concrete guidance on how to incorporate systems thinking in problem solving, decision making, and strategic planning without becoming a technical expert. ... "It is not hard for people to appreciate that fragmented, piecemeal efforts to solve complex problems are ineffective. But having concrete approaches to an alternative is ...

  23. Teaching K-12 Students About Systems Thinking

    Take a helicopter view: Toggling between the details and the big picture is an important systems thinking skill and one of the habits of a systems thinker.When looking at a situation, event, or particular issue, encourage students to discuss systems as a whole. For example, in the classroom we may create a circle, where each student represents a system part and makes connections with a ball of ...

  24. Frontiers

    Keywords: two visual systems, problem-solving, think aloud, real-world eye movements, ambient attention, focal attention, fixation duration, saccade amplitude. Citation: Guo Y, Pannasch S, Helmert JR and Kaszowska A (2024) Ambient and focal attention during complex problem-solving: preliminary evidence from real-world eye movement data. Front.

  25. Heavy Machinery Meets AI

    The Problem. Until recently most incumbent industrial companies didn't use the most advanced software in their products. But competitors that can extract complex designs, insights, and trends ...