Systems Mapping

Systems Mapping is a visualization approach that employs diagrams to illustrate complex systems and their interconnections. It includes concept maps and mind maps, commonly used in project management and business analysis. Benefits include clarity and improved communication, but challenges arise with complex systems and the need for maintenance as they change.

Introduction to Systems Mapping

Systems Mapping is rooted in systems thinking, a discipline that focuses on understanding the interconnectedness and interdependence of elements within a system. A system is a collection of components or elements that work together to achieve a common purpose or goal. Systems Mapping provides a graphical representation of the structure and dynamics of a system, making it easier to explore, analyze, and communicate complex systems.

Key principles of Systems Mapping include:

  1. Visualization: It emphasizes the use of visual representations, such as diagrams or models, to convey the structure and relationships within a system.
  2. Holistic Perspective: Systems Mapping encourages viewing the entire system as a whole, considering both individual components and their interactions.
  3. Interconnectedness: It recognizes that components within a system are interconnected, and changes in one component can have ripple effects throughout the system.
  4. Feedback Loops: Feedback loops and causal relationships are often represented in Systems Maps to illustrate how changes propagate within the system.
  5. Clarity and Communication: Systems Maps serve as a communication tool to convey complex information in a clear and accessible manner.

Key Concepts in Systems Mapping

To effectively utilize Systems Mapping, it’s important to understand key concepts and terminology associated with systems thinking:

1. Components:

Components are the individual elements or parts that make up a system. They can be tangible, such as physical objects or people, or intangible, such as processes, information flows, or relationships.

2. Relationships:

Relationships represent the connections and interactions between components within a system. These relationships can be causal, hierarchical, feedback loops, or other forms of connections.

3. Feedback Loops:

Feedback loops are recurring patterns of interactions within a system where the output of the system affects its inputs. Positive feedback loops amplify changes, while negative feedback loops tend to stabilize a system.

4. Causality:

Causality refers to the cause-and-effect relationships between components in a system. Systems Maps often include arrows or links to depict the direction of causality.

5. Boundaries:

System boundaries define the scope of the system under consideration. They delineate what is part of the system and what lies outside of it.

Methods for Creating Systems Maps

Creating Systems Maps involves a series of steps and methods to represent and analyze complex systems:

1. Define the System:

Clearly define the system or problem you want to explore using Systems Mapping. Understand the boundaries of the system and its purpose.

2. Identify Components:

Identify and list the components or elements within the system. These could be individuals, processes, resources, or any relevant entities.

3. Determine Relationships:

Analyze the relationships between components. How do they interact? What are the cause-and-effect relationships, dependencies, and feedback loops?

4. Visual Representation:

Choose a visual representation format for your Systems Map. Common formats include flowcharts, diagrams, causal loop diagrams, and mind maps.

5. Create the Map:

Construct the Systems Map by placing components and relationships on the chosen visual format. Use arrows, lines, and labels to represent connections and causality.

6. Feedback Loops:

Identify and highlight feedback loops within the system. These loops can help explain dynamic behavior and system responses to changes.

7. Iterative Process:

Systems Mapping is often an iterative process. Maps can evolve and become more detailed as you gain a deeper understanding of the system.

8. Analysis and Insights:

Analyze the Systems Map to gain insights into the system’s behavior, vulnerabilities, and potential points of intervention or improvement.

9. Communication:

Systems Maps are powerful communication tools. Use them to convey complex information to stakeholders, collaborators, or decision-makers.

Real-World Applications of Systems Mapping

Systems Mapping finds applications in diverse fields and domains:

1. Business and Management:

In business and management, Systems Mapping is used to analyze organizational structures, processes, and supply chains. It helps identify areas for optimization and improvement.

2. Healthcare:

In healthcare systems, Systems Mapping is employed to improve patient care, streamline healthcare processes, and enhance coordination among healthcare providers.

3. Environmental Science:

Environmental scientists use Systems Mapping to understand complex environmental challenges, such as ecosystem dynamics, resource management, and climate change impacts.

4. Education:

Educators and curriculum designers use Systems Mapping to create learning models and understand the relationships between curriculum components and student outcomes.

5. Project Management:

Project managers utilize Systems Mapping to visualize project workflows, dependencies, and potential bottlenecks. It aids in project planning and risk management.

6. Public Policy:

Policy analysts and government agencies use Systems Mapping to assess the impacts of policies on various stakeholders and to model potential policy changes.

The Significance of Systems Mapping

Systems Mapping holds significant importance in addressing complex challenges and improving decision-making in various fields:

  1. Visual Clarity: It provides a visual representation that enhances clarity and understanding of complex systems, making it easier for stakeholders to grasp the big picture.
  2. Identification of Leverage Points: Systems Maps can help identify leverage points within a system—areas where interventions or changes can have a significant impact.
  3. Risk Assessment: It allows for the identification of vulnerabilities and potential risks within a system, helping organizations proactively address issues.
  4. Communication Tool: Systems Maps serve as effective communication tools to convey complex information and insights to diverse audiences.
  5. Problem-Solving: By visualizing complex systems and their interactions, Systems Mapping facilitates problem-solving and decision-making by providing a structured framework for analysis.
  6. Innovation: It encourages innovative thinking by exploring new ways to improve or optimize systems.


Systems Mapping is a valuable approach for visualizing, analyzing, and understanding complex systems in diverse fields and disciplines. Whether applied in business, healthcare, environmental science, education, or public policy, Systems Mapping provides a structured and holistic perspective that can lead to improved decision-making, problem-solving, and innovation. As our world becomes increasingly interconnected and complex, Systems Mapping continues to play a pivotal role in helping individuals and organizations navigate the intricacies of systems and effectively address complex challenges.

Case Studies

  • Project Management:
    • Work Breakdown Structure (WBS): A hierarchical representation of project tasks and their dependencies, helping project managers plan and execute projects effectively.
    • Gantt Chart: A timeline-based map showing project tasks, durations, and dependencies, aiding in project scheduling.
  • Business Analysis:
    • Process Flowchart: Illustrates the steps involved in a business process, such as order processing or customer onboarding.
    • Value Stream Map: Depicts the value-added and non-value-added activities within a business process to identify areas for improvement.
  • Environmental Science:
    • Ecosystem Mapping: Visualizes the components of an ecosystem, including species, habitats, and their interactions, to study ecological dynamics.
    • Carbon Cycle Diagram: Represents the flow of carbon through various components of the Earth’s systems, helping understand carbon emissions and climate change.
  • Social Sciences:
    • Causal Loop Diagram (CLD): Models the interactions between economic, social, and environmental factors in a region to study complex societal issues like poverty or urbanization.
    • Concept Map: Used in education to help students organize and connect concepts in subjects like psychology or sociology.
  • Education:
    • Mind Maps: Students create mind maps to summarize and connect key concepts in subjects like history or literature, aiding in study and understanding.
    • Flow Diagrams: Used in physics or chemistry classes to illustrate scientific processes or reactions.
  • Healthcare:
    • Patient Journey Map: Visualizes the steps a patient goes through in a healthcare system, from registration to treatment, to identify areas for improving patient experience.
    • Medical Process Flowchart: Represents the workflow of medical procedures, such as diagnosis or surgery, to enhance healthcare process efficiency.
  • Information Technology:
    • Network Topology Diagram: Shows the structure of computer networks, including routers, switches, and connections, to help IT professionals manage network infrastructure.
    • Data Flow Diagram (DFD): Illustrates the flow of data within a software system, assisting in software design and development.
  • Urban Planning:
    • City Infrastructure Map: Visualizes urban infrastructure like roads, utilities, and public spaces, aiding city planners in making informed decisions about development and sustainability.
    • Traffic Flow Diagram: Represents traffic patterns and congestion in a city, helping traffic engineers optimize traffic signals and road design.

Key Highlights

  • Visual Representation: Systems Mapping involves creating visual representations of complex systems using diagrams, charts, and graphs. This visual approach makes it easier to understand, analyze, and communicate intricate relationships within a system.
  • Holistic View: It provides a holistic view of a system by capturing the interdependencies, components, and processes that contribute to its functioning. This comprehensive perspective helps in identifying bottlenecks, inefficiencies, and opportunities for improvement.
  • Interdisciplinary Tool: Systems Mapping is interdisciplinary and applicable across various domains, including project management, business analysis, environmental science, social sciences, healthcare, information technology, urban planning, and more.
  • Problem-Solving: It is a valuable tool for problem-solving and decision-making. Systems Maps can reveal root causes of issues, enabling informed decision-making and targeted interventions.
  • Communication Aid: Systems Maps serve as powerful communication tools. They simplify complex concepts and facilitate effective communication among stakeholders, team members, and decision-makers.
  • Planning and Optimization: In fields like project management and urban planning, Systems Mapping aids in planning, optimizing workflows, and resource allocation. For instance, it helps project managers create detailed work breakdown structures (WBS) and Gantt charts for project scheduling.
  • Environmental Analysis: Systems Mapping is crucial for environmental analysis, as it allows scientists to visualize ecosystems, carbon cycles, and other natural processes. It contributes to the understanding of ecological dynamics and climate change.
  • Education and Learning: In education, Systems Mapping is used to enhance learning. Mind maps, concept maps, and flow diagrams help students organize information, connect concepts, and improve comprehension.
  • Process Improvement: Businesses use Systems Mapping to analyze and optimize processes. Flowcharts, value stream maps, and causal loop diagrams aid in identifying inefficiencies and streamlining operations.
  • Healthcare Quality: Systems Mapping plays a role in healthcare quality improvement. Patient journey maps and medical process flowcharts help healthcare professionals enhance patient experiences and streamline healthcare delivery.
  • IT Infrastructure Management: IT professionals rely on Systems Mapping to manage complex network topologies and software systems. Network topology diagrams and data flow diagrams assist in network and software design.
  • Urban Development: In urban planning, Systems Mapping helps cities plan infrastructure, traffic management, and sustainable development. City infrastructure maps and traffic flow diagrams aid urban planners in making informed decisions.

Connected Thinking Frameworks

Convergent vs. Divergent Thinking

Convergent thinking occurs when the solution to a problem can be found by applying established rules and logical reasoning. Whereas divergent thinking is an unstructured problem-solving method where participants are encouraged to develop many innovative ideas or solutions to a given problem. Where convergent thinking might work for larger, mature organizations where divergent thinking is more suited for startups and innovative companies.

Critical Thinking

Critical thinking involves analyzing observations, facts, evidence, and arguments to form a judgment about what someone reads, hears, says, or writes.


The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman in 1972. Biases are seen as systematic errors and flaws that make humans deviate from the standards of rationality, thus making us inept at making good decisions under uncertainty.

Second-Order Thinking

Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.

Lateral Thinking

Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.

Bounded Rationality

Bounded rationality is a concept attributed to Herbert Simon, an economist and political scientist interested in decision-making and how we make decisions in the real world. In fact, he believed that rather than optimizing (which was the mainstream view in the past decades) humans follow what he called satisficing.

Dunning-Kruger Effect

The Dunning-Kruger effect describes a cognitive bias where people with low ability in a task overestimate their ability to perform that task well. Consumers or businesses that do not possess the requisite knowledge make bad decisions. What’s more, knowledge gaps prevent the person or business from seeing their mistakes.

Occam’s Razor

Occam’s Razor states that one should not increase (beyond reason) the number of entities required to explain anything. All things being equal, the simplest solution is often the best one. The principle is attributed to 14th-century English theologian William of Ockham.

Lindy Effect

The Lindy Effect is a theory about the ageing of non-perishable things, like technology or ideas. Popularized by author Nicholas Nassim Taleb, the Lindy Effect states that non-perishable things like technology age – linearly – in reverse. Therefore, the older an idea or a technology, the same will be its life expectancy.


Antifragility was first coined as a term by author, and options trader Nassim Nicholas Taleb. Antifragility is a characteristic of systems that thrive as a result of stressors, volatility, and randomness. Therefore, Antifragile is the opposite of fragile. Where a fragile thing breaks up to volatility; a robust thing resists volatility. An antifragile thing gets stronger from volatility (provided the level of stressors and randomness doesn’t pass a certain threshold).

Systems Thinking

Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. It is about thinking non-linearly, and understanding the second-order consequences of actions and input into the system.

Vertical Thinking

Vertical thinking, on the other hand, is a problem-solving approach that favors a selective, analytical, structured, and sequential mindset. The focus of vertical thinking is to arrive at a reasoned, defined solution.

Maslow’s Hammer

Maslow’s Hammer, otherwise known as the law of the instrument or the Einstellung effect, is a cognitive bias causing an over-reliance on a familiar tool. This can be expressed as the tendency to overuse a known tool (perhaps a hammer) to solve issues that might require a different tool. This problem is persistent in the business world where perhaps known tools or frameworks might be used in the wrong context (like business plans used as planning tools instead of only investors’ pitches).

Peter Principle

The Peter Principle was first described by Canadian sociologist Lawrence J. Peter in his 1969 book The Peter Principle. The Peter Principle states that people are continually promoted within an organization until they reach their level of incompetence.

Straw Man Fallacy

The straw man fallacy describes an argument that misrepresents an opponent’s stance to make rebuttal more convenient. The straw man fallacy is a type of informal logical fallacy, defined as a flaw in the structure of an argument that renders it invalid.

Streisand Effect

The Streisand Effect is a paradoxical phenomenon where the act of suppressing information to reduce visibility causes it to become more visible. In 2003, Streisand attempted to suppress aerial photographs of her Californian home by suing photographer Kenneth Adelman for an invasion of privacy. Adelman, who Streisand assumed was paparazzi, was instead taking photographs to document and study coastal erosion. In her quest for more privacy, Streisand’s efforts had the opposite effect.


As highlighted by German psychologist Gerd Gigerenzer in the paper “Heuristic Decision Making,” the term heuristic is of Greek origin, meaning “serving to find out or discover.” More precisely, a heuristic is a fast and accurate way to make decisions in the real world, which is driven by uncertainty.

Recognition Heuristic

The recognition heuristic is a psychological model of judgment and decision making. It is part of a suite of simple and economical heuristics proposed by psychologists Daniel Goldstein and Gerd Gigerenzer. The recognition heuristic argues that inferences are made about an object based on whether it is recognized or not.

Representativeness Heuristic

The representativeness heuristic was first described by psychologists Daniel Kahneman and Amos Tversky. The representativeness heuristic judges the probability of an event according to the degree to which that event resembles a broader class. When queried, most will choose the first option because the description of John matches the stereotype we may hold for an archaeologist.

Take-The-Best Heuristic

The take-the-best heuristic is a decision-making shortcut that helps an individual choose between several alternatives. The take-the-best (TTB) heuristic decides between two or more alternatives based on a single good attribute, otherwise known as a cue. In the process, less desirable attributes are ignored.

Bundling Bias

The bundling bias is a cognitive bias in e-commerce where a consumer tends not to use all of the products bought as a group, or bundle. Bundling occurs when individual products or services are sold together as a bundle. Common examples are tickets and experiences. The bundling bias dictates that consumers are less likely to use each item in the bundle. This means that the value of the bundle and indeed the value of each item in the bundle is decreased.

Barnum Effect

The Barnum Effect is a cognitive bias where individuals believe that generic information – which applies to most people – is specifically tailored for themselves.

First-Principles Thinking

First-principles thinking – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.

Ladder Of Inference

The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.

Goodhart’s Law

Goodhart’s Law is named after British monetary policy theorist and economist Charles Goodhart. Speaking at a conference in Sydney in 1975, Goodhart said that “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Goodhart’s Law states that when a measure becomes a target, it ceases to be a good measure.

Six Thinking Hats Model

The Six Thinking Hats model was created by psychologist Edward de Bono in 1986, who noted that personality type was a key driver of how people approached problem-solving. For example, optimists view situations differently from pessimists. Analytical individuals may generate ideas that a more emotional person would not, and vice versa.

Mandela Effect

The Mandela effect is a phenomenon where a large group of people remembers an event differently from how it occurred. The Mandela effect was first described in relation to Fiona Broome, who believed that former South African President Nelson Mandela died in prison during the 1980s. While Mandela was released from prison in 1990 and died 23 years later, Broome remembered news coverage of his death in prison and even a speech from his widow. Of course, neither event occurred in reality. But Broome was later to discover that she was not the only one with the same recollection of events.

Crowding-Out Effect

The crowding-out effect occurs when public sector spending reduces spending in the private sector.

Bandwagon Effect

The bandwagon effect tells us that the more a belief or idea has been adopted by more people within a group, the more the individual adoption of that idea might increase within the same group. This is the psychological effect that leads to herd mentality. What in marketing can be associated with social proof.

Moore’s Law

Moore’s law states that the number of transistors on a microchip doubles approximately every two years. This observation was made by Intel co-founder Gordon Moore in 1965 and it become a guiding principle for the semiconductor industry and has had far-reaching implications for technology as a whole.

Disruptive Innovation

Disruptive innovation as a term was first described by Clayton M. Christensen, an American academic and business consultant whom The Economist called “the most influential management thinker of his time.” Disruptive innovation describes the process by which a product or service takes hold at the bottom of a market and eventually displaces established competitors, products, firms, or alliances.

Value Migration

Value migration was first described by author Adrian Slywotzky in his 1996 book Value Migration – How to Think Several Moves Ahead of the Competition. Value migration is the transferal of value-creating forces from outdated business models to something better able to satisfy consumer demands.

Bye-Now Effect

The bye-now effect describes the tendency for consumers to think of the word “buy” when they read the word “bye”. In a study that tracked diners at a name-your-own-price restaurant, each diner was asked to read one of two phrases before ordering their meal. The first phrase, “so long”, resulted in diners paying an average of $32 per meal. But when diners recited the phrase “bye bye” before ordering, the average price per meal rose to $45.


Groupthink occurs when well-intentioned individuals make non-optimal or irrational decisions based on a belief that dissent is impossible or on a motivation to conform. Groupthink occurs when members of a group reach a consensus without critical reasoning or evaluation of the alternatives and their consequences.


A stereotype is a fixed and over-generalized belief about a particular group or class of people. These beliefs are based on the false assumption that certain characteristics are common to every individual residing in that group. Many stereotypes have a long and sometimes controversial history and are a direct consequence of various political, social, or economic events. Stereotyping is the process of making assumptions about a person or group of people based on various attributes, including gender, race, religion, or physical traits.

Murphy’s Law

Murphy’s Law states that if anything can go wrong, it will go wrong. Murphy’s Law was named after aerospace engineer Edward A. Murphy. During his time working at Edwards Air Force Base in 1949, Murphy cursed a technician who had improperly wired an electrical component and said, “If there is any way to do it wrong, he’ll find it.”

Law of Unintended Consequences

The law of unintended consequences was first mentioned by British philosopher John Locke when writing to parliament about the unintended effects of interest rate rises. However, it was popularized in 1936 by American sociologist Robert K. Merton who looked at unexpected, unanticipated, and unintended consequences and their impact on society.

Fundamental Attribution Error

Fundamental attribution error is a bias people display when judging the behavior of others. The tendency is to over-emphasize personal characteristics and under-emphasize environmental and situational factors.

Outcome Bias

Outcome bias describes a tendency to evaluate a decision based on its outcome and not on the process by which the decision was reached. In other words, the quality of a decision is only determined once the outcome is known. Outcome bias occurs when a decision is based on the outcome of previous events without regard for how those events developed.

Hindsight Bias

Hindsight bias is the tendency for people to perceive past events as more predictable than they actually were. The result of a presidential election, for example, seems more obvious when the winner is announced. The same can also be said for the avid sports fan who predicted the correct outcome of a match regardless of whether their team won or lost. Hindsight bias, therefore, is the tendency for an individual to convince themselves that they accurately predicted an event before it happened.

Read Next: BiasesBounded RationalityMandela EffectDunning-Kruger EffectLindy EffectCrowding Out EffectBandwagon Effect.

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