Mapping Complex Problems

Some challenges are straightforward.

A broken process can be repaired. A missing resource can be supplied. A technical fault can be fixed.

Other challenges are very different.

Issues such as climate change, educational transformation, healthcare accessibility, organisational culture, social inequality, innovation adoption and digital disruption involve numerous stakeholders, competing priorities, interconnected systems and evolving conditions.

These are complex problems.

Complex problems rarely have simple solutions because they are shaped by multiple influences that interact in dynamic and often unpredictable ways.

Within the Evaluate stage of the 5E Design Thinking Framework, mapping complex problems helps innovators visualise relationships, identify system influences, reveal hidden dependencies and create a clearer understanding of challenges before moving towards solutions.

The goal is not to simplify complexity away.

The goal is to understand it.

A complex problem is a challenge involving multiple interconnected factors that influence one another over time.

Examples include:

• Student engagement
• Organisational culture
• Sustainability transitions
• Healthcare outcomes
• Economic development
• Innovation ecosystems
• Social inclusion
• Digital transformation

Unlike simple problems, complex problems:

• Have many causes
• Involve multiple stakeholders
• Change over time
• Produce unintended consequences
• Resist straightforward solutions

Complexity requires investigation rather than assumption.

Understanding the distinction is important.

Simple Problems

Simple problems have clear causes and solutions.

Example:

A printer is out of paper.

Solution:

Add paper.

Complicated Problems

Complicated problems involve many components but remain largely predictable.

Example:

Building an aircraft.

Expertise and planning can produce reliable outcomes.

Complex Problems

Complex problems involve uncertainty, adaptation and interaction.

Example:

Improving educational outcomes across an entire university.

Outcomes are influenced by many interconnected variables.

Complex problems require learning, experimentation and adaptation.

Human beings naturally simplify complexity.

While simplification can help understanding, it can also create blind spots.

Many innovation failures occur because teams:

• Focus on isolated symptoms
• Ignore stakeholder relationships
• Overlook systemic influences
• Misunderstand dependencies

Mapping provides a visual approach for exploring challenges more comprehensively.

Maps help teams:

• Explore relationships
• Reveal patterns
• Identify opportunities
• Support collaboration
• Create shared understanding

When complexity becomes visible, it becomes more manageable.

Problem mapping is the process of visually representing the factors, stakeholders, relationships and influences associated with a challenge.

Maps may include:

• People
• Systems
• Processes
• Behaviours
• Causes
• Effects
• Dependencies

The purpose is not creating perfect diagrams.

The purpose is improving understanding.

Many complex problems are difficult to understand through text alone.

Visual representations help people:

See Relationships

Connections become visible.

Explore Dependencies

Influences become easier to identify.

Identify Patterns

Repeated structures emerge.

Build Shared Understanding

Teams can discuss a common picture.

Visualisation transforms abstract complexity into something tangible.

One of the simplest forms of problem mapping involves stakeholders.

Questions include:

• Who is involved?
• Who is affected?
• Who has influence?
• Who may resist change?

Example:

Educational Innovation

Stakeholders may include:

• Students
• Educators
• Industry partners
• University leadership
• Professional staff
• Accrediting bodies

Stakeholder maps reveal the human landscape surrounding a challenge.

Ecosystem maps expand beyond stakeholders.

They examine:

• Relationships
• Resources
• Information flows
• Dependencies
• Influences

Innovation rarely occurs within isolated environments.

Ecosystem maps help innovators understand the broader context.

Systems maps focus on interactions.

A systems map might show:

Stakeholders

Who participates?

Processes

What happens?

Inputs

What enters the system?

Outputs

What emerges?

Feedback Loops

How outcomes influence future behaviour?

Systems maps reveal the architecture of complexity.

Rich Pictures are visual representations that combine:

• Stakeholders
• Environments
• Experiences
• Relationships
• Emotions
• Processes

They are intentionally informal and exploratory.

Rich Pictures help teams see complexity holistically rather than analytically.

Many problems exist within experiences.

Journey mapping helps visualise how people move through those experiences over time.

Journey maps often include:

Actions

What people do.

Thoughts

What people think.

Emotions

How they feel.

Touchpoints

Where interactions occur.

Journey maps reveal opportunities that may otherwise remain hidden.

Causal maps focus on cause-and-effect relationships.

Questions include:

• What influences this problem?
• What consequences emerge?
• What relationships exist?

Causal maps help innovators move beyond symptoms towards deeper understanding.

Complex systems often contain dependencies.

Examples:

• Processes depend upon technologies.
• Technologies depend upon people.
• People depend upon information.
• Information depends upon systems.

Dependency maps reveal vulnerabilities and opportunities.

Problem landscapes provide broad overviews.

Rather than focusing on a single issue, they explore:

• Related problems
• Stakeholders
• Opportunities
• Constraints
• Influences

This approach is especially useful at the beginning of large innovation projects.

Complexity often emerges through relationships.

Questions include:

• What influences what?
• Who influences whom?
• Which factors reinforce one another?
• Which factors constrain progress?

Relationships often matter more than individual elements.

Feedback loops help explain how systems behave over time.

Reinforcing Loops

Amplify outcomes.

Example:

Higher engagement → Better outcomes → Greater motivation → Higher engagement.

Balancing Loops

Stabilise systems.

Example:

Increasing demand → Resource constraints → Reduced service quality → Lower demand.

Understanding loops improves intervention design.

Leverage points are places within a system where relatively small changes create significant effects.

Examples:

Education

Improving feedback systems.

Healthcare

Improving patient communication.

Organisations

Improving information sharing.

Innovation becomes more effective when leverage points are identified.

Educational challenges often involve:

• Curriculum
• Assessment
• Technology
• Student wellbeing
• Support services
• Faculty capability

A systems map may reveal interactions that remain invisible through traditional analysis.

Educational innovation benefits significantly from visualisation.

Organisational problems are rarely isolated.

Examples include:

Culture

Linked to leadership, communication and incentives.

Innovation

Linked to risk, resources, collaboration and strategy.

Engagement

Linked to purpose, management, workload and recognition.

Problem maps reveal these interactions.

Community challenges often involve:

• Social systems
• Government policies
• Economic influences
• Cultural factors
• Infrastructure

Mapping helps create more inclusive and informed approaches.

Complexity should rarely be analysed alone.

Collaborative mapping:

• Increases diversity of perspectives
• Reveals hidden assumptions
• Builds shared understanding
• Creates stakeholder ownership

Different people often see different parts of the system.

Collaboration improves the map.

Starting With Solutions

Mapping should focus on understanding before intervention.

Oversimplifying Problems

Complexity should be explored, not ignored.

Including Too Few Stakeholders

Missing perspectives reduce understanding.

Treating Maps as Static

Systems evolve.

Maps should evolve too.

Seeking Perfect Accuracy

Maps are learning tools, not exact representations.

Mapping strengthens design thinking by helping teams:

• Understand context
• Identify opportunities
• Explore systems
• Reveal relationships
• Clarify challenges

Strong innovation depends on understanding complexity before generating solutions.

Complexity Mapping Workshop

Objective

Visualise a complex challenge.

Instructions

• Define the challenge.
• Identify stakeholders.
• Identify important factors.
• Draw relationships.
• Highlight feedback loops.
• Identify leverage points.
• Discuss opportunities.

Expected Outcome

A shared visual understanding of complexity.

Estimated Time

60–90 minutes.

Select a challenge from your workplace, course or community.

Create:

• A stakeholder map
• A systems map
• A journey map

Compare what each representation reveals and identify opportunities that were previously invisible.

• What influences the challenge you are exploring?
• Which relationships appear most important?
• What stakeholders are missing from your understanding?
• Where might leverage points exist?
• Are you seeing symptoms or systems?

• Complex problems involve interconnected factors.
• Visualisation helps reveal relationships.
• Stakeholder maps show people.
• Systems maps show interactions.
• Journey maps show experiences.
• Feedback loops influence behaviour.
• Leverage points create opportunities.
• Understanding complexity improves innovation decisions.

Choose a complex challenge and create three different maps of it. Focus on understanding rather than solving. Often the most valuable innovation insights emerge when people can finally see the challenge as a system rather than a collection of isolated issues.