explain what you understand by a systems approach to problem solving and decision making

Taking a systems thinking approach to problem solving

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

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?

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.

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 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:

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?

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.

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.

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.

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.

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.

You may also like

Systems thinking vs. linear thinking: understanding the key differences, exploring critical thinking vs. systems thinking, 5 ways to apply systems thinking to your business operations: a strategic guide, what is systems thinking, download this free ebook.

Hey! You are using an outdated browser. Please upgrade your browser to improve your experience.

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

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

What Does Systems Thinking Involve?

Tips for beginners.

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

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

Why Use Systems Thinking?

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

When Should We Use Systems Thinking?

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

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

Where Should We Start?

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

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

How Do We Use Systems Thinking Tools?

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

THE ICEBERG

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

How Do We Know That We’ve “Got It”?

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

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

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

Michael Goodman is principal at Innovation Associates Organizational Learning

Related Articles

Moving from blame to accountability.

When something goes wrong in an organization, the first question that is often posed is, “Whose fault is…

The “Thinking” in Systems Thinking: How Can We Make It Easier to Master?

Despite significant advances in personal computers and systems thinking software over the last decade, learning to apply systems…

What is Your Organization’s Core Theory of Success?

Managers in today’s organizations are continually confronted with new challenges and increased performance expectations. At the same time,…

Breaking the Cycle of Organizational Addiction

Every so often in the world of business, we see an enterprise that, after years of steady progress…

Sign up to stay in the loop

Receive updates of new articles and save your favorites..

• First Name *
• Last Name *
• Password * Enter Password Confirm Password

Lean Six Sigma Training Certification

• Facebook Instagram Twitter LinkedIn YouTube
• (877) 497-4462

Systems Thinking: A Holistic Approach to Solving Complex Problems

February 22nd, 2024

Everything has become so interconnected, comprising of multi-pronged challenges. We still try to tackle modern problems with linear thinking approaches that isolate problems and reduce complexity.

But, more often than usual, they fall short of providing a viable solution.

Here, systems thinking offers an alternative perspective to understand how things influence one another within embedded contexts.

This holistic approach proves uniquely capable of untangling thorny issues like sustainability , inequality, or emerging diseases and making decision making effective.

As systems thinking gains wider traction, questions arise about what exactly it entails and why it matters. This article maps out the fundamental principles of systems thinking, dynamic tools used, diverse applications across sectors, and the overall benefits of adopting a systems view, especially in 2024.

The systemic perspective holds special relevance for problem solvers and changemakers currently grappling with twisted challenges and complex systems fundamentally shaped by interdependence.

By revealing hidden connections and patented patterns, systems thinking empowers interventions well-matched to our intricately networked world.

From classrooms to boardrooms, systems tools meet teams in any field to support analysis, communication, planning, or evaluation through an inter-relational lens geared to 22nd-century dynamics shaping our existence.

What is Systems Thinking?

Systems thinking is an approach to understanding how things influence one another within a whole entity. Systems thinking studies connections between key parts to see the collective behaviors that result. Expanding perspectives brings clarity to complex situations.

Systems thinking provides a framework for seeing relationships and patterns to explain how systems function. The key concepts include recognizing the interconnected and interdependent nature of systems and shifting from linear to circular causality.

Reductionist Thinking vs. Systems Thinking

In systems thinking, systems behave as integrated wholes in which elements dynamically impact each other over time.

This contrasts with traditional forms of reductionist thinking that isolate parts to understand systems.

Reductionism breaks systems down into discrete elements, rather than examining the fuzzy system boundaries, complex interactions, and unintended consequences that arise within intricate open systems in the real world.

Systems thinking offers a new perspective focused on the linkages, relationships, emergence, and feedback processes underlying systems functioning. By mapping reinforcing and balancing loops, systems thinking can identify behavior-over-time patterns for a system. This helps explain the whole picture better than reductionism.

Key Concepts of Systems Thinking

Several principles form the foundation of systems thinking. First, systems thinking recognizes the importance of feedback loops in driving system behavior. Feedback loops capture how the output of one part of a system impacts the input to another part, creating causal chains.

Reinforcing feedback loops amplify change exponentially while balancing loops counteract the change.

By mapping these feedback loops, system archetypes emerge – common patterns like limits to growth, escalation, and tragedy of the commons. These system archetypes help diagnose systemic issues, revealing core interrelating dynamics.

System archetypes function as conceptual models for understanding challenges like sustainability, urban decay, and organizational change.

In complex systems, leverage points serve as places to intervene for substantial impact. The goal is to identify where minimal effort shifts the system, through changes to parameters, feedback loops, or paradigm-shifting transformations at the level of goals or mindsets. This contrasts with incidental low-leverage tweaks.

Changing social or ecological systems often involves unintended consequences. However each system has interconnections, time delays, and complex human motivations at play. These can undermine change efforts when not adequately mapped and anticipated.

Systems thinking aims to reveal these unintended ripple effects so they can be weighed when leveraging change.

So, while unintended consequences often limit pure design, systems thinking provides insights to navigate reform more wisely. By elevating awareness of inter-dependencies and causal loops, one can recognize patterns, structures, boundaries, and relationships fundamental to systems insights.

Using Systems Thinking Approaches

Systems thinkers employ various conceptual tools to understand systems, communicate about them, and guide interventions.

Causality mapping visually depicts variables in a system, their connections, and the direction of causal influence. This illumination of causal links reveals chains of systemic connectivity not otherwise apparent. It supports the analysis of cascading effects and feedback dynamics.

Systems mapping outlines key system components, their attributes and functions, and interrelationships. This structural perspective clarifies the organization of various elements into an integrated whole.

Systems mapping tools can also overlay dynamic processes like information flows and decision pathways to evaluate systemic leverage points.

Mental models strongly shape how people perceive systems and strategic choices within them. Two people can have divergent understandings of the same system. Reflecting critically on how mental models influence thinking is crucial for expanding limited mindsets that bound perspectives on addressing systemic issues.

More detailed system dynamics computer simulations help model system behavior by mapping dynamic complexity. This computational modeling integrates time delays, feedback processes, stocks, and flows to run long-term scenario forecasts for deeper analysis of complex systems like ecosystems, markets, or hospitals.

Adaptive systems thinkers also recognize that models have limits and that systems change over time in nonlinear ways. Rather than attempting precise prediction and control, adaptive approaches use feedback to dynamically adjust interventions according to emergent system patterns.

This flexibility to meet systems in flux is well-suited for catalyzing change in complex contexts.

Applying Systems Thinking

Systems thinking has powerful and diverse applications across sectors:

In business, systems thinking helps managers gain perspective on organizational challenges and identify root causes of problems like low morale or stagnant sales. By mapping reinforcing loops, leaders can find intervention points to shift momentum.

Systems thinking offers analytic tools to rethink structures, decision processes, and feedback channels for organizational change.

Government policymakers similarly utilize systems approaches to craft robust public policies able to balance social, environmental and , outcomes. Methodologies like group model building bring together diverse stakeholders to map out key system relationships as part of the policy design process.

This systems perspective enables policies attuned to ripple effects.

Nonprofit organizations working on social change also apply systems thinking to guide advocacy and programming. For instance, systems tools like behavior over time graphs and connection circles help groups explicitly map the structural causes perpetuating social problems like homelessness at a community level.

This equips nonprofits to pursue systemic intervention points.

More broadly, systems thinking skills help strengthen collaborative problem solving in teams. Facilitating activities that surface mental models, unpack complex dynamics, and scan for unintended consequences builds shared systemic understanding to transform discussion and explore structural solutions.

Overall, systems thinking fosters paradigm shifts towards interconnected, ecological, and holistic thinking in any problem solving context. This empowers more responsible decision-making.

Benefits of Systems Thinking

Adopting a systems thinking perspective carries many advantages:

Systems thinking allows one to see situations more completely rather than getting lost in details. By focusing on interconnections and processes that link system elements, systems thinking provides a “big picture” orientation. This expanded framework reveals areas of critical linkage within the messiness of complex contexts.

A systems view also aids in identifying types of high-leverage interventions amidst complexity. For instance, by mapping system archetypes like limits to growth or tragedy of the commons, one can pinpoint potent areas to reroute damaging feedback loops.

A systems lens highlights openings for targeted changes to cascade through interconnected subsystems.

Systems thinking also anticipates longer-term consequences of potential actions. By tracing causal threads through a system, secondary and tertiary effects are revealed that may otherwise go unseen.

This equips better foresight for the unintended impacts that might ripple across time and space from well-intentioned interventions.

Additionally, systems thinking brings order and coherence to complexity. By surfacing the organic patterning at play, systems tools decode complex dynamics in understandable yet nuanced ways.

Conceptual frameworks like stocks and flows clarify the structural forces driving issues like urban brain drain or suburban sprawl without oversimplifying.

In all of these ways, systems thinking empowers solutions better aligned to real-world complexity while still providing transformational direction. It permeates analysis with key principles of inter-relationship, temporality, perspectival flexibility, and buried connectivity – allowing insight into predicaments otherwise overwhelming.

Systems Thinking in Practice

For those first learning systems thinking, frustrations can arise. Ingrained linear thinking patterns clash with the new multidimensional perspective. Beginners also face cognitive overload wrestling with interconnections between system elements. However, skills gradually build from foundational concepts towards adept systems analysis.

With consistent practice, systems thinkers progress to parsing dynamics of specialized contexts like public health, smart grids, or supply chains. These domain experts learn to rapidly orient to unfamiliar systems through a systemic lens to ask probing questions.

Expanding one’s toolkit with advanced skills like system dynamics modeling and group facilitation extends capabilities to address complex settings.

Some systems thinkers like Donella Meadows significantly advance the field through groundbreaking applications. Meadows demonstrated deep systems wisdom over her career with The Limits to Growth and pioneering system dynamics methodologies.

These mentors develop strong systemic intuition after internalizing inter-relational patterns for decades. Their capacity to shift mental models in themselves and others unlocks societal transformation.

Ultimately, accomplished systems thinkers heed the call to teach others systemic perspectives that spread. Skills-building workshops on causal loop mapping, systems archetypes, communication tactics, and facilitation techniques proliferate systems literacy.

Outreach occurs across diverse communities given universal relevance. Each effort to cultivate systems thinking and broaden capacity for recognizing systemic leverage sustains movement toward positive change.

SixSigma.us offers both Live Virtual classes as well as Online Self-Paced training. Most option includes access to the same great Master Black Belt instructors that teach our World Class in-person sessions. Sign-up today!

Virtual Classroom Training Programs Self-Paced Online Training Programs

SixSigma.us Accreditation & Affiliations

Monthly Management Tips

• Be the first one to receive the latest updates and information from 6Sigma
• Get curated resources from industry-experts
• Gain an edge with complete guides and other exclusive materials
• Become a part of one of the largest Six Sigma community
• Unlock your path to become a Six Sigma professional

" * " indicates required fields

MBA Knowledge Base

Business • Management • Technology

Home » Management Information Systems » Systems Approach to Problem Solving

Systems Approach to Problem Solving

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

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

1. Defining Problems and Opportunities

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

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

2. Systems Thinking

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

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

3. Developing Alternate Solutions

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

4. Evaluating Alternate Solutions

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

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

5. Selecting the Best Solution

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

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

6. Desingning and Implementing Solution

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

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

7. Post Implementation Review

Related posts:.

• Operations Research approach of problem solving
• Systems Approach to Management
• How Creativity Helps in Problem Solving Process?
• Case Study on Information Systems: Cisco Systems
• The Concept of Systems
• Types of Systems
• Types of Information Systems
• Strategic Information Systems
• Business benefits of ERP systems
• Role of a Systems Analyst in Organizations

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Reqi Systems Engineering Articles

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.

Related Posts

Leave a Reply Cancel reply

You must be logged in to post a comment.

The Leading Source of Insights On Business Model Strategy & Tech Business Models

What Is Systems Thinking? Systems Thinking In A Nutshell

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.

Table of Contents

Understanding systems thinking

Systems thinking is based on systems theory and is responsible for one of the major breakthroughs in the understanding of complex organizations.

Systems theory studies systems from the perspective of the whole system, various subsystems, and the recurring patterns or relationships between subsystems. 

The application of this theory in an organizational context is called systems analysis – of which systems thinking is a primary component.

In general terms, systems thinking considers systems in terms of their overall structures, patterns, and cycles.

This broad and holistic perspective enables organizations to identify solutions that address as many problems as possible.

In systems thinking , these solutions are known as leverage points because they leverage improvement throughout the system. Prioritizing leverage points across an entire system is called whole systems thinking .

The approach differs from traditional analysis methods which study systems by separating them into their constituent parts.

In addition to analyzing organizational complexity, systems thinking has also been used in medical, environmental, political, economic, and educational contexts.

Why use systems thinking?

By considering the system as a whole, systems thinking encourages organizations to broaden their perspectives and consider new or innovative solutions. This is particularly important for problems that are:

• Chronic – that is, they are not a one-time event.
• Familiar – or those that have a known history of repeated occurrences.
• Complex – where people have unsuccessfully tried to find a solution in the past and failed.

Perhaps more profoundly, systems thinking promotes the idea that there is no perfect solution to any situation. Every decision the business makes will impact other parts of the system, so the “right” decision may be assumed to be any with the least severe negative impact. 

For project teams, systems thinking diagrams are also important in telling compelling user stories. Diagrams that deal with cause and effect force the team to develop shared pictures and stories that can be understood and communicated by every member.

Six key themes of systems thinking

Here are some of the key themes that comprise a systems thinking mindset:

Interconnectedness

Systems thinkers understand that everything is connected. Trees need carbon dioxide, water, and sunlight to thrive.

Humans, in turn, can only survive by eating the food and oxygen that trees and other plants produce.

Systems thinkers see the world as a dynamic, chaotic, and interrelated arrangement of relationships and feedback loops.

In most cases, synthesis means the act of combining things to create something new.

In systems thinking, synthesis means separating complexity into manageable parts to understand the whole and the parts simultaneously.

A term used to describe the natural outcome of things interacting with one another.

Key characteristics of emergence include non-linearity and self-organization.

Feedback loops

A natural consequence of interconnectedness are the feedback loops which flow between the elements of a system.

There are two main types: reinforcing and balancing .

Reinforcing feedback loops involve elements in the loop reinforcing more of the same, such as population growth in a large city.

Balancing loops are comprised of elements in some form of harmony, such as the relative abundance of predators and prey in an ecosystem.

Systems mapping

This is one of the key tools in a system thinker’s arsenal.

There are many ways to map a system, including behavior-over-time graphs, iceberg models, causal loop diagrams, and connected circles.

Whatever the method chosen, it should define how the elements within a system behave and how they are related.

Insights can then be used to develop effective shifts, interventions, policy, and project decisions.

Systems thinking also encourages the individual to consider causality as a dynamic and constantly evolving process.

Most people understand simple cause and effect, but relatively few can apply the concept to gain a deeper understanding of system feedback loops, agency, connections, and relationships.

Systems thinking examples 

Japanese car maker Subaru operates the only zero-waste automotive manufacturing facility in the United States.

While the EV revolution is now well underway, car manufacturing itself remains a process with a harmful carbon footprint.

This is mostly because the sourcing and processing of raw materials such as steel, aluminum, plastic, and rubber are extremely energy-intensive.

In a 2018 report , for example, it was estimated that the vehicle industry’s GHG emissions exceeded those of the European Union.

Subaru’s approach

Operating in an industry not known for environmental values, Subaru employed systems thinking to radically rethink its operations.

Over a period of just two years, the company transformed its Lafayette, Indiana-based assembly plant into a zero-waste facility.

With assistance from an environmental consultancy firm, Subaru adopted the three Rs of sustainability: reduce, reuse, and recycle.

Underpinning this effort was the kaizen philosophy of continuous improvement with employees rewarded for ideas that promoted environmental stewardship.

In 2016, Subaru recycled almost 94 million pounds of material which included some 80 million pounds of metal .

The factory itself also sits on an 832-acre site surrounded by forests, prairie grass, and other habitats for some of America’s most iconic plant and animal species.

Collaboration and results

Subaru has not only acknowledged its role in climate change but has also shared its processes with more than 500 companies .

According to executive vice president Tom Easterday, this includes firms outside of the automotive industry:

“ We sometimes joke that we’ve had everything from potato chips to rocket ships visit us – from Frito Lay to Raytheon. ”

The National Parks Service (NPS) has also turned to Subaru for assistance with its own zero-waste initiative.

Systems thinking has enabled Subaru to frame issues within the broader contexts in which it operates.

Importantly, the company understands the interconnectedness of business , the environment, and society as a whole.

“ We don’t need the government to tell us to be good environmental stewards – it’s good for business ” , Easterday explained. 

To meet increased consumer demand for organic food, Costco started to invest in organic farmers in its supply chain.

The move relates to the key systems thinking principle of causality and has a basic but effective premise: If Costco provides the means for producers to transition to organic, the retailer can enter into “first buyer” agreements with them, stock more organic food in its stores, and increase revenue .

Around the time of the initiative in 2016, organic food sales in the United States had tripled over the past decade to be worth $35.95 billion .

While the industry enjoyed grew at an impressive rate of 10%, the fact remained that if there was more organic produce, revenue and growth would be even higher.

Costco’s role in the industry

To some extent, growth in organic food sales has been stifled by structural issues in the agricultural industry.

Namely, the powerful influence of multinationals who control food supply with vast, monoculture farms and the governments that subsidize them.

However, Costco’s initiative shows that companies can use systems thinking and take a more proactive approach to manage their supply chains. This particular retailer improved its bottom line by meeting consumer demand in a rapidly growing industry.

But in the process, Costco also increased ethical and environmental standards in the food industry and made it more attractive as a potential recipient of investment or subsidization. 

Key takeaways

• Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. In addition to analyzing organizational and project complexity, it is also used in medical, environmental, political, economic, and educational contexts.
• Systems thinking promotes the idea that there is no perfect solution to any situation. This helps the organization choose the best course of action by anticipating the potential impact of each option.
• The systems thinking mindset is comprised of six key themes: interconnectedness, synthesis, emergence, feedback loops, systems mapping, and causality.

Key Highlights

• Systems Thinking: Systems thinking is a holistic approach to investigating the factors and interactions that contribute to potential outcomes. It involves understanding complex organizations by considering the whole system, various subsystems, and the recurring patterns or relationships between them.
• Applications: Systems thinking finds applications in diverse fields such as organizational analysis , medical, environmental, political, economic, and educational contexts. It offers a broad and holistic perspective that helps identify solutions to a wide range of problems.
• Leverage Points: In systems thinking, solutions are referred to as leverage points. These points are crucial elements that, when targeted, can lead to significant improvements throughout the entire system. Prioritizing leverage points is essential in whole systems thinking.
• Interconnectedness: Understanding that everything is connected, and recognizing the dynamic, chaotic, and interrelated arrangement of relationships and feedback loops within a system.
• Synthesis: Combining elements to create something new and separating complexity into manageable parts to understand the whole and its parts simultaneously.
• Emergence: The natural outcome of things interacting with one another, characterized by non-linearity and self-organization.
• Feedback Loops: The consequence of interconnectedness, where feedback flows between elements in a system, leading to reinforcing or balancing loops.
• Systems Mapping: Utilizing various tools such as behavior-over-time graphs, iceberg models, causal loop diagrams, and connected circles to map and understand system behavior and relationships.
• Causality: Considering causality as a dynamic and constantly evolving process, moving beyond simple cause-and-effect relationships.
• Benefits: Systems thinking encourages organizations to broaden their perspectives and consider new or innovative solutions. It is particularly useful for addressing chronic, familiar, and complex problems that have resisted solutions in the past. By recognizing the interconnectedness of systems, it promotes the idea that there is no perfect solution, but rather decisions that minimize negative impacts.

Connected Thinking Frameworks

Convergent vs. Divergent Thinking

Critical Thinking

Second-Order Thinking

Lateral Thinking

Bounded Rationality

Dunning-Kruger Effect

Occam’s Razor

Lindy Effect

Antifragility

Systems Thinking

Vertical Thinking

Metaphorical Thinking

Maslow’s Hammer

Peter Principle

Straw Man Fallacy

Google Effect

Streisand Effect

Compromise Effect

Butterfly Effect

IKEA Effect

Ringelmann Effect 

The Overview Effect

House Money Effect

Recognition Heuristic

Representativeness Heuristic

Take-The-Best Heuristic

Bundling Bias

Barnum Effect

Anchoring Effect

Decoy Effect

Commitment Bias

First-Principles Thinking

Ladder Of Inference

Goodhart’s Law

Six Thinking Hats Model

Mandela Effect

Crowding-Out Effect

Bandwagon Effect

Moore’s Law

Disruptive Innovation

Value Migration

Bye-Now Effect

Stereotyping

Murphy’s Law

Law of Unintended Consequences

Fundamental Attribution Error

Outcome Bias

Hindsight Bias

Read Next:  Biases ,  Bounded Rationality ,  Mandela Effect ,  Dunning-Kruger Effect ,  Lindy Effect ,  Crowding Out Effect ,  Bandwagon Effect .

Main Guides:

• Business Models
• Business Strategy
• Marketing Strategy
• Business Model Innovation
• Platform Business Models
• Network Effects In A Nutshell
• Digital Business Models

More Resources

About The Author

Gennaro Cuofano

Discover more from fourweekmba.

Subscribe now to keep reading and get access to the full archive.

Type your email…

Continue reading

Understanding Systems Thinking: A Guide to the Key Concepts and Benefits

Updated: April 10, 2023 by Ken Feldman

The famed statistician and quality consultant, Dr. W. Edwards Deming, defined a system as “…. a network of interdependent components that work together to try to accomplish the aim of the system. A system must have an aim. Without the aim, there is no system.”

Systems thinking is based on the concept that it is better to view all the components as a whole rather than as individual components, while focusing on the interrelationship of the individual components.

Overview: What is systems thinking? 

Systems thinking is based upon the concept that a ll systems are composed of interconnected parts. These connections and interrelationships cause behavior of one part to impact another. All parts are connected.

Key elements of a system are:

• Input, Processing, and Output 
• Environment

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

• The issue is important.
• The problem is chronic and ongoing and not just a one-time event.
• The problem is familiar and has a known history.
• Previous attempts to solve the problem have failed.

Key concepts of systems thinking:

• Interconnectedness – everything is connected
• Synthesis – Synthesis is about understanding the whole and the parts at the same time, along with the relationships and the connections that make up the whole. This is different from analysis which is the dissection of complexity into manageable individual components.
• Emergence – Emergence is the outcome of the synergies and interrelationships of the parts.
• Feedback Loops – Since everything is interconnected in systems thinking, there are constant feedback loops and flows between the elements of the system.

The graph below illustrates the difference between systems thinking and non-systems thinking concepts.

Difference in concepts between systems and non systems thinking

Tools of systems thinking used to collect, analyze, synthesize, and develop system insights are:

• ladder of inference 
• behavior-over-time graph 
• connection circle 
• stock-flow map 
• iceberg visual 
• causal loop diagram. 

3 benefits of systems thinking 

As the world becomes more complex, systems thinking will provide you the following benefits:

• See the bigger picture 

Systems thinking allows you to view things from the 30,000-foot perspective rather than from ground level. 

• Greater clarity 

By zooming out and viewing the wider process, you can see the interrelationships and interactions between your system elements.

• Understand and fix the “problems that never seem to go away”

Most problems are caused by the interaction of things rather than only by the individual element. Systems thinking will help you better understand these interactions so you can solve the more complex and chronic problems you always seem to have. 

Why is systems thinking important to understand? 

In a world where interconnectedness and complexity exists understanding systems thinking offers you a disciplined approach to find innovative solutions to problems.

Encourage a big picture perspective

By understanding the system’s interconnected parts, their historical evolution and their relationships with each other, systems thinkers can look for other optional ways of achieving system improvement 

See problems as opportunities 

Without a way to see problems in the context of a complex, interconnected whole system, solving problems using linear thinking risks making your problem more complex.  

Understand and prepare for rapid change 

Systems thinking offers a way to better predict future outcomes—based not on past events, but on a more insightful understanding of the surrounding environment and its elements.

An industry example of systems thinking

One of the classic examples showing the contrast between systems and non-systems thinking relates to a problem at the Washington Monument in Washington, D.C. The problem was the surface of the monument was disintegrating. A team was formed to analyze the problem. They initially used the 5 Why technique, which is a version of the cause and effect technique. 

Every time they thought they solved the problem; they created a new one. Eventually they stood back and viewed the problem through the lens of systems thinking rather than individual events. The solution was quick and inexpensive. Here was the thought process:

• Why is the Monument disintegrating? – Because of the use of harsh chemicals. 
• Why are harsh chemicals being used? – To clean pigeon poop – solution is to change chemicals. 
• Why are there so many pigeons? – They eat spiders and there are a lot of spiders at the monument – solution is to put up insect netting.
• Why so many spiders? – They eat gnats and there are lots of gnats at the monument.
• Why so many gnats? – They are attracted to the light at dusk. 

Solution: Turn on the lights 30 minutes later. 

3 best practices when thinking about systems thinking 

Here are a few tips for effectively using systems thinking. .

• Ask different questions

Try to ask questions about underlying structural relationships or patterns of behavior exhibited over time. Focus on potential delays, balancing or reinforcing processes, and unintended consequences. Use circular rather than linear thinking.  

• Search out and use feedback loops

Information gleaned from your system feedback loops will give you insight into potential relationships and interactions between process elements and the subsequent impacts. 

• Think about system boundaries 

Understand what elements of your process are part of the system and what is in the surrounding environment that may change and affect the state of the system. To draw this boundary you need to know your scope of action, what you can alter and what lies beyond your ability to directly change.

Frequently Asked Questions (FAQ) about systems thinking

What is the opposite of systems thinking.

Systems thinking is circular in nature while non-system thinking is linear. System thinking looks at the whole and the relationship of the parts. Non-system linear thinking looks at the individual components of the process.

What is systems thinking?

Systems thinking is a management approach that views a system as a set of linkages and interactions between the components which make up the entire defined system.

What are the basic concepts of systems thinking?

• Interconnectedness – Everything is connected.
• Causality – In systems thinking, causality is about being able to understand the way the parts of the system influence each other.
• Systems Mapping – Here you Identify and map the elements within a system to understand how they interconnect, relate and act in the overall system.

Systems thinking is based on the concept that the parts of a system or process are all connected and the relationship between these parts drives the behavior and outcomes of the system. By seeking to understand the connectedness of all the components you can understand how the process works and can gain insights to allow for system improvements.

About the Author

Ken Feldman

Academics & Programs

Faculty & research, ulmer career management center, alumni & friends, news & events.

• Resources for:
• Current Students
• Staff & Faculty Resources
• Recruiters & Employers
• Press & Media

About the College of Business

The UofL College of Business enhances the intellectual and economic vitality of our city, the region, and the broader business world through our academic programs, research, and community outreach activities. We strongly believe that lives improve through entrepreneurship, innovation, critical and rigorous thinking, diverse ideas, and people.

The University of Louisville College of Business offers a wide variety of degree programs to help you accelerate your success and achieve your professional goals. Whether you’re laying a strong foundation for your business career, taking the next big step on your professional journey, or building specialized industry expertise, we’ve got you covered.

UofL College of Business faculty pride themselves on real-world experience and depth of research. They value innovation, critical thinking, and the exchange of new ideas. Our distinguished faculty will help you achieve your goals — before and after graduation.

The Ulmer Career Management Center is a state-of-the-art resource connecting local, regional, and international employers with high-potential College of Business students and alumni.

The UofL College of Business continues to succeed thanks to the commitment and resources of alumni and friends. Learn about our latest initiatives, the impact of our alumni on our mission, and how you can stay involved.

Get up-to-date on the latest news from the College of Business community.

• Staff & Faculty

Systems Thinking: How to Solve Problems So They Stay Solved

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

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

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

You will learn how to:

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

Seminar Fee

$430 (includes instruction, seminar manual, refreshments, certificate of completion and parking)

Stay Notified of Upcoming Classes

Interested to learn about our other programs? Check out our other Seminars . Or sign up and we will keep you informed about future educational offerings.

• Search all Louisville
• Search College of Business

Systems Approach to “Problem Solving”

Cite this chapter.

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

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

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime
• Available as EPUB and PDF
• Read on any device
• Instant download
• Own it forever
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info
• Durable hardcover edition

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Unable to display preview.  Download preview PDF.

Author information

Authors and affiliations.

The University of Hull, Hull, England

Robert L. Flood

City University, London, England

Ewart R. Carson

You can also search for this author in PubMed   Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 1993 Springer Science+Business Media New York

About this chapter

Flood, R.L., Carson, E.R. (1993). Systems Approach to “Problem Solving”. In: Dealing with Complexity. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2235-2_6

Download citation

DOI : https://doi.org/10.1007/978-1-4757-2235-2_6

Publisher Name : Springer, Boston, MA

Print ISBN : 978-1-4419-3227-3

Online ISBN : 978-1-4757-2235-2

eBook Packages : Springer Book Archive

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

How to answer "What is your approach to problem-solving?" (with sample answers)

Why Employers Ask This

The question "What is your approach to problem-solving?" is a commonly asked question in job interviews. This is because employers want to know how you handle challenges and overcome obstacles, as problem-solving is an essential skill in any work environment. They need someone who can think critically and come up with effective solutions to workplace problems.

Employers also want to understand your problem-solving process to see if it aligns with the company's culture and values. They may ask about your approach to problem-solving to see if you are a strategic thinker who can prioritize tasks and make sound decisions under pressure.

How to Answer the Question

When answering this question, it's essential to understand that the interviewer is looking for specific details about your problem-solving approach. Here are some tips to help you structure your answer:

• Describe the Problem: Start by describing the problem you faced. Explain the context, who was involved, and what caused the problem. Be specific and use examples to support your statements.
• Explain Your Approach: Next, describe the steps you took to solve the problem. Be clear about your methods and tools used, while also considering the company's core values in your approach. Make sure to highlight how your approach addressed the problem's root cause and achieved a meaningful resolution.
• Share the Outcome: Finally, share the outcome of your actions. Explain how your approach was successful, how you measured it, and what benefits it brought to the organization. If you were not able to solve the problem, explain what steps you took and what you learned from the process.

Remember to use specific examples, demonstrate your problem-solving skills in the best light possible, and share outcomes to show initiative and showcase your ability to effectively address problems.

Sample answers

1. bad answer:.

My approach to problem-solving is to just come up with a quick solution and see if it works. If it doesn't, I try something else until I find something that works.

Why it's bad: This answer shows a lack of preparation and planning. It doesn't demonstrate any critical thinking or analytical skills that a potential employer would value.

2. Good answer:

My approach to problem-solving is to first assess the situation and gather all the information I can. Then, I break down the problem into smaller parts and identify any potential obstacles or challenges. Once I have a clear understanding of the issue, I brainstorm a range of possible solutions, evaluate each option, and select the best course of action. Finally, I implement and monitor the chosen solution to ensure its effectiveness and make adjustments if necessary.

Why it's good: This answer shows a structured and methodical approach to problem-solving. The potential employer will appreciate the candidate's attention to detail and ability to work through complex problems.

3. Good answer:

My approach to problem-solving is to involve my team members and stakeholders. I find that collaborating with others brings in different perspectives that I may not have thought of on my own. I encourage open communication and brainstorming sessions where everyone is free to contribute their ideas. Then, we evaluate each idea and select the best one together as a team. This helps create a sense of ownership and buy-in from everyone involved.

Why it's good: This answer shows strong leadership and teamwork skills. The potential employer will appreciate the candidate's ability to work well with others and successfully navigate group dynamics to find the best solution.

4. Okay answer:

My approach to problem-solving is to stay calm and reflective. I take a moment to step back, assess the situation objectively, and then determine what actions to take. I try to look at the problem from different angles to find the root cause and develop a strategy to resolve it.

Why it's okay: This answer shows a level-headedness in managing stressful situations and a willingness to think outside the box. However, it could benefit from more specific examples that demonstrate critical thinking and problem-solving skills.

• INTERPERSONAL SKILLS
• Decision-Making and Problem Solving

Search SkillsYouNeed:

Interpersonal Skills:

• A - Z List of Interpersonal Skills
• Interpersonal Skills Self-Assessment
• Communication Skills
• Emotional Intelligence
• Conflict Resolution and Mediation Skills
• Customer Service Skills
• Team-Working, Groups and Meetings

Decision-Making and Problem-Solving

• Effective Decision Making
• Decision-Making Framework
• Introduction to Problem Solving

Identifying and Structuring Problems

Investigating Ideas and Solutions

Implementing a Solution and Feedback

• Creative Problem-Solving

Social Problem-Solving

• Negotiation and Persuasion Skills
• Personal and Romantic Relationship Skills

Subscribe to our FREE newsletter and start improving your life in just 5 minutes a day.

You'll get our 5 free 'One Minute Life Skills' and our weekly newsletter.

We'll never share your email address and you can unsubscribe at any time.

The SkillsYouNeed Guide to Interpersonal Skills

Making decisions and solving problems are two key areas in life, whether you are at home or at work. Whatever you’re doing, and wherever you are, you are faced with countless decisions and problems, both small and large, every day.

Many decisions and problems are so small that we may not even notice them. Even small decisions, however, can be overwhelming to some people. They may come to a halt as they consider their dilemma and try to decide what to do.

Small and Large Decisions

In your day-to-day life you're likely to encounter numerous 'small decisions', including, for example:

Tea or coffee?

What shall I have in my sandwich? Or should I have a salad instead today?

What shall I wear today?

Larger decisions may occur less frequently but may include:

Should we repaint the kitchen? If so, what colour?

Should we relocate?

Should I propose to my partner? Do I really want to spend the rest of my life with him/her?

These decisions, and others like them, may take considerable time and effort to make.

The relationship between decision-making and problem-solving is complex. Decision-making is perhaps best thought of as a key part of problem-solving: one part of the overall process.

Our approach at Skills You Need is to set out a framework to help guide you through the decision-making process. You won’t always need to use the whole framework, or even use it at all, but you may find it useful if you are a bit ‘stuck’ and need something to help you make a difficult decision.

Decision Making

Effective Decision-Making

This page provides information about ways of making a decision, including basing it on logic or emotion (‘gut feeling’). It also explains what can stop you making an effective decision, including too much or too little information, and not really caring about the outcome.

A Decision-Making Framework

This page sets out one possible framework for decision-making.

The framework described is quite extensive, and may seem quite formal. But it is also a helpful process to run through in a briefer form, for smaller problems, as it will help you to make sure that you really do have all the information that you need.

Problem Solving

Introduction to Problem-Solving

This page provides a general introduction to the idea of problem-solving. It explores the idea of goals (things that you want to achieve) and barriers (things that may prevent you from achieving your goals), and explains the problem-solving process at a broad level.

The first stage in solving any problem is to identify it, and then break it down into its component parts. Even the biggest, most intractable-seeming problems, can become much more manageable if they are broken down into smaller parts. This page provides some advice about techniques you can use to do so.

Sometimes, the possible options to address your problem are obvious. At other times, you may need to involve others, or think more laterally to find alternatives. This page explains some principles, and some tools and techniques to help you do so.

Having generated solutions, you need to decide which one to take, which is where decision-making meets problem-solving. But once decided, there is another step: to deliver on your decision, and then see if your chosen solution works. This page helps you through this process.

‘Social’ problems are those that we encounter in everyday life, including money trouble, problems with other people, health problems and crime. These problems, like any others, are best solved using a framework to identify the problem, work out the options for addressing it, and then deciding which option to use.

This page provides more information about the key skills needed for practical problem-solving in real life.

Further Reading from Skills You Need

The Skills You Need Guide to Interpersonal Skills eBooks.

Develop your interpersonal skills with our series of eBooks. Learn about and improve your communication skills, tackle conflict resolution, mediate in difficult situations, and develop your emotional intelligence.

Guiding you through the key skills needed in life

As always at Skills You Need, our approach to these key skills is to provide practical ways to manage the process, and to develop your skills.

Neither problem-solving nor decision-making is an intrinsically difficult process and we hope you will find our pages useful in developing your skills.

Start with: Decision Making Problem Solving

See also: Improving Communication Interpersonal Communication Skills Building Confidence

Decision Making vs. Problem Solving

What's the difference.

Decision making and problem solving are two closely related concepts that are essential in both personal and professional settings. While decision making refers to the process of selecting the best course of action among various alternatives, problem solving involves identifying and resolving issues or obstacles that hinder progress towards a desired outcome. Decision making often involves evaluating different options based on their potential outcomes and consequences, while problem solving requires analyzing the root causes of a problem and developing effective strategies to overcome it. Both skills require critical thinking, creativity, and the ability to weigh pros and cons. Ultimately, decision making and problem solving are interconnected and complementary processes that enable individuals to navigate complex situations and achieve desired goals.

Further Detail

Introduction.

Decision making and problem solving are two essential cognitive processes that individuals and organizations engage in to navigate through various challenges and achieve desired outcomes. While they are distinct processes, decision making and problem solving share several attributes and are often interconnected. In this article, we will explore the similarities and differences between decision making and problem solving, highlighting their key attributes and how they contribute to effective problem-solving and decision-making processes.

Definition and Purpose

Decision making involves selecting a course of action from multiple alternatives based on available information, preferences, and goals. It is a cognitive process that individuals use to make choices and reach conclusions. On the other hand, problem solving refers to the process of finding solutions to specific issues or challenges. It involves identifying, analyzing, and resolving problems to achieve desired outcomes.

Both decision making and problem solving share the purpose of achieving a desired outcome or resolving a particular situation. They require individuals to think critically, evaluate options, and consider potential consequences. While decision making focuses on choosing the best course of action, problem solving emphasizes finding effective solutions to specific problems or challenges.

Attributes of Decision Making

Decision making involves several key attributes that contribute to its effectiveness:

• Rationality: Decision making is often based on rational thinking, where individuals evaluate available information, weigh pros and cons, and make logical choices.
• Subjectivity: Decision making is influenced by personal preferences, values, and biases. Individuals may prioritize certain factors or options based on their subjective judgment.
• Uncertainty: Many decisions are made under conditions of uncertainty, where individuals lack complete information or face unpredictable outcomes. Decision makers must assess risks and make informed judgments.
• Time Constraints: Decision making often occurs within time constraints, requiring individuals to make choices efficiently and effectively.
• Trade-offs: Decision making involves considering trade-offs between different options, as individuals must prioritize certain factors or outcomes over others.

Attributes of Problem Solving

Problem solving also encompasses several key attributes that contribute to its effectiveness:

• Analytical Thinking: Problem solving requires individuals to analyze and break down complex problems into smaller components, facilitating a deeper understanding of the issue at hand.
• Creativity: Effective problem solving often involves thinking outside the box and generating innovative solutions. It requires individuals to explore alternative perspectives and consider unconventional approaches.
• Collaboration: Problem solving can benefit from collaboration and teamwork, as diverse perspectives and expertise can contribute to more comprehensive and effective solutions.
• Iterative Process: Problem solving is often an iterative process, where individuals continuously evaluate and refine their solutions based on feedback and new information.
• Implementation: Problem solving is not complete without implementing the chosen solution. Individuals must take action and monitor the outcomes to ensure the problem is effectively resolved.

Interconnection and Overlap

While decision making and problem solving are distinct processes, they are interconnected and often overlap. Decision making is frequently a part of the problem-solving process, as individuals must make choices and select the most appropriate solution to address a specific problem. Similarly, problem solving is inherent in decision making, as individuals must identify and analyze problems or challenges before making informed choices.

Moreover, both decision making and problem solving require critical thinking skills, the ability to evaluate information, and the consideration of potential consequences. They both involve a systematic approach to gather and analyze relevant data, explore alternatives, and assess the potential risks and benefits of different options.

Decision making and problem solving are fundamental cognitive processes that individuals and organizations engage in to navigate through challenges and achieve desired outcomes. While decision making focuses on selecting the best course of action, problem solving emphasizes finding effective solutions to specific problems or challenges. Both processes share attributes such as rationality, subjectivity, uncertainty, time constraints, and trade-offs (in decision making), as well as analytical thinking, creativity, collaboration, iterative process, and implementation (in problem solving).

Understanding the similarities and differences between decision making and problem solving can enhance our ability to approach complex situations effectively. By leveraging the attributes of both processes, individuals and organizations can make informed choices, address challenges, and achieve desired outcomes.

Comparisons may contain inaccurate information about people, places, or facts. Please report any issues.

How to master the seven-step problem-solving process

In this episode of the McKinsey Podcast , Simon London speaks with Charles Conn, CEO of venture-capital firm Oxford Sciences Innovation, and McKinsey senior partner Hugo Sarrazin about the complexities of different problem-solving strategies.

Podcast transcript

Simon London: Hello, and welcome to this episode of the McKinsey Podcast , with me, Simon London. What’s the number-one skill you need to succeed professionally? Salesmanship, perhaps? Or a facility with statistics? Or maybe the ability to communicate crisply and clearly? Many would argue that at the very top of the list comes problem solving: that is, the ability to think through and come up with an optimal course of action to address any complex challenge—in business, in public policy, or indeed in life.

Looked at this way, it’s no surprise that McKinsey takes problem solving very seriously, testing for it during the recruiting process and then honing it, in McKinsey consultants, through immersion in a structured seven-step method. To discuss the art of problem solving, I sat down in California with McKinsey senior partner Hugo Sarrazin and also with Charles Conn. Charles is a former McKinsey partner, entrepreneur, executive, and coauthor of the book Bulletproof Problem Solving: The One Skill That Changes Everything [John Wiley & Sons, 2018].

Charles and Hugo, welcome to the podcast. Thank you for being here.

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

Simon London: Problem solving is a really interesting piece of terminology. It could mean so many different things. I have a son who’s a teenage climber. They talk about solving problems. Climbing is problem solving. Charles, when you talk about problem solving, what are you talking about?

Charles Conn: For me, problem solving is the answer to the question “What should I do?” It’s interesting when there’s uncertainty and complexity, and when it’s meaningful because there are consequences. Your son’s climbing is a perfect example. There are consequences, and it’s complicated, and there’s uncertainty—can he make that grab? I think we can apply that same frame almost at any level. You can think about questions like “What town would I like to live in?” or “Should I put solar panels on my roof?”

You might think that’s a funny thing to apply problem solving to, but in my mind it’s not fundamentally different from business problem solving, which answers the question “What should my strategy be?” Or problem solving at the policy level: “How do we combat climate change?” “Should I support the local school bond?” I think these are all part and parcel of the same type of question, “What should I do?”

I’m a big fan of structured problem solving. By following steps, we can more clearly understand what problem it is we’re solving, what are the components of the problem that we’re solving, which components are the most important ones for us to pay attention to, which analytic techniques we should apply to those, and how we can synthesize what we’ve learned back into a compelling story. That’s all it is, at its heart.

I think sometimes when people think about seven steps, they assume that there’s a rigidity to this. That’s not it at all. It’s actually to give you the scope for creativity, which often doesn’t exist when your problem solving is muddled.

Simon London: You were just talking about the seven-step process. That’s what’s written down in the book, but it’s a very McKinsey process as well. Without getting too deep into the weeds, let’s go through the steps, one by one. You were just talking about problem definition as being a particularly important thing to get right first. That’s the first step. Hugo, tell us about that.

Hugo Sarrazin: It is surprising how often people jump past this step and make a bunch of assumptions. The most powerful thing is to step back and ask the basic questions—“What are we trying to solve? What are the constraints that exist? What are the dependencies?” Let’s make those explicit and really push the thinking and defining. At McKinsey, we spend an enormous amount of time in writing that little statement, and the statement, if you’re a logic purist, is great. You debate. “Is it an ‘or’? Is it an ‘and’? What’s the action verb?” Because all these specific words help you get to the heart of what matters.

Want to subscribe to The McKinsey Podcast ?

Simon London: So this is a concise problem statement.

Hugo Sarrazin: Yeah. It’s not like “Can we grow in Japan?” That’s interesting, but it is “What, specifically, are we trying to uncover in the growth of a product in Japan? Or a segment in Japan? Or a channel in Japan?” When you spend an enormous amount of time, in the first meeting of the different stakeholders, debating this and having different people put forward what they think the problem definition is, you realize that people have completely different views of why they’re here. That, to me, is the most important step.

Charles Conn: I would agree with that. For me, the problem context is critical. When we understand “What are the forces acting upon your decision maker? How quickly is the answer needed? With what precision is the answer needed? Are there areas that are off limits or areas where we would particularly like to find our solution? Is the decision maker open to exploring other areas?” then you not only become more efficient, and move toward what we call the critical path in problem solving, but you also make it so much more likely that you’re not going to waste your time or your decision maker’s time.

How often do especially bright young people run off with half of the idea about what the problem is and start collecting data and start building models—only to discover that they’ve really gone off half-cocked.

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

Simon London: OK. So step one—and there is a real art and a structure to it—is define the problem. Step two, Charles?

Charles Conn: My favorite step is step two, which is to use logic trees to disaggregate the problem. Every problem we’re solving has some complexity and some uncertainty in it. The only way that we can really get our team working on the problem is to take the problem apart into logical pieces.

What we find, of course, is that the way to disaggregate the problem often gives you an insight into the answer to the problem quite quickly. I love to do two or three different cuts at it, each one giving a bit of a different insight into what might be going wrong. By doing sensible disaggregations, using logic trees, we can figure out which parts of the problem we should be looking at, and we can assign those different parts to team members.

Simon London: What’s a good example of a logic tree on a sort of ratable problem?

Charles Conn: Maybe the easiest one is the classic profit tree. Almost in every business that I would take a look at, I would start with a profit or return-on-assets tree. In its simplest form, you have the components of revenue, which are price and quantity, and the components of cost, which are cost and quantity. Each of those can be broken out. Cost can be broken into variable cost and fixed cost. The components of price can be broken into what your pricing scheme is. That simple tree often provides insight into what’s going on in a business or what the difference is between that business and the competitors.

If we add the leg, which is “What’s the asset base or investment element?”—so profit divided by assets—then we can ask the question “Is the business using its investments sensibly?” whether that’s in stores or in manufacturing or in transportation assets. I hope we can see just how simple this is, even though we’re describing it in words.

When I went to work with Gordon Moore at the Moore Foundation, the problem that he asked us to look at was “How can we save Pacific salmon?” Now, that sounds like an impossible question, but it was amenable to precisely the same type of disaggregation and allowed us to organize what became a 15-year effort to improve the likelihood of good outcomes for Pacific salmon.

Simon London: Now, is there a danger that your logic tree can be impossibly large? This, I think, brings us onto the third step in the process, which is that you have to prioritize.

Charles Conn: Absolutely. The third step, which we also emphasize, along with good problem definition, is rigorous prioritization—we ask the questions “How important is this lever or this branch of the tree in the overall outcome that we seek to achieve? How much can I move that lever?” Obviously, we try and focus our efforts on ones that have a big impact on the problem and the ones that we have the ability to change. With salmon, ocean conditions turned out to be a big lever, but not one that we could adjust. We focused our attention on fish habitats and fish-harvesting practices, which were big levers that we could affect.

People spend a lot of time arguing about branches that are either not important or that none of us can change. We see it in the public square. When we deal with questions at the policy level—“Should you support the death penalty?” “How do we affect climate change?” “How can we uncover the causes and address homelessness?”—it’s even more important that we’re focusing on levers that are big and movable.

Would you like to learn more about our Strategy & Corporate Finance Practice ?

Simon London: Let’s move swiftly on to step four. You’ve defined your problem, you disaggregate it, you prioritize where you want to analyze—what you want to really look at hard. Then you got to the work plan. Now, what does that mean in practice?

Hugo Sarrazin: Depending on what you’ve prioritized, there are many things you could do. It could be breaking the work among the team members so that people have a clear piece of the work to do. It could be defining the specific analyses that need to get done and executed, and being clear on time lines. There’s always a level-one answer, there’s a level-two answer, there’s a level-three answer. Without being too flippant, I can solve any problem during a good dinner with wine. It won’t have a whole lot of backing.

Simon London: Not going to have a lot of depth to it.

Hugo Sarrazin: No, but it may be useful as a starting point. If the stakes are not that high, that could be OK. If it’s really high stakes, you may need level three and have the whole model validated in three different ways. You need to find a work plan that reflects the level of precision, the time frame you have, and the stakeholders you need to bring along in the exercise.

Charles Conn: I love the way you’ve described that, because, again, some people think of problem solving as a linear thing, but of course what’s critical is that it’s iterative. As you say, you can solve the problem in one day or even one hour.

Charles Conn: We encourage our teams everywhere to do that. We call it the one-day answer or the one-hour answer. In work planning, we’re always iterating. Every time you see a 50-page work plan that stretches out to three months, you know it’s wrong. It will be outmoded very quickly by that learning process that you described. Iterative problem solving is a critical part of this. Sometimes, people think work planning sounds dull, but it isn’t. It’s how we know what’s expected of us and when we need to deliver it and how we’re progressing toward the answer. It’s also the place where we can deal with biases. Bias is a feature of every human decision-making process. If we design our team interactions intelligently, we can avoid the worst sort of biases.

Simon London: Here we’re talking about cognitive biases primarily, right? It’s not that I’m biased against you because of your accent or something. These are the cognitive biases that behavioral sciences have shown we all carry around, things like anchoring, overoptimism—these kinds of things.

Both: Yeah.

Charles Conn: Availability bias is the one that I’m always alert to. You think you’ve seen the problem before, and therefore what’s available is your previous conception of it—and we have to be most careful about that. In any human setting, we also have to be careful about biases that are based on hierarchies, sometimes called sunflower bias. I’m sure, Hugo, with your teams, you make sure that the youngest team members speak first. Not the oldest team members, because it’s easy for people to look at who’s senior and alter their own creative approaches.

Hugo Sarrazin: It’s helpful, at that moment—if someone is asserting a point of view—to ask the question “This was true in what context?” You’re trying to apply something that worked in one context to a different one. That can be deadly if the context has changed, and that’s why organizations struggle to change. You promote all these people because they did something that worked well in the past, and then there’s a disruption in the industry, and they keep doing what got them promoted even though the context has changed.

Simon London: Right. Right.

Hugo Sarrazin: So it’s the same thing in problem solving.

Charles Conn: And it’s why diversity in our teams is so important. It’s one of the best things about the world that we’re in now. We’re likely to have people from different socioeconomic, ethnic, and national backgrounds, each of whom sees problems from a slightly different perspective. It is therefore much more likely that the team will uncover a truly creative and clever approach to problem solving.

Simon London: Let’s move on to step five. You’ve done your work plan. Now you’ve actually got to do the analysis. The thing that strikes me here is that the range of tools that we have at our disposal now, of course, is just huge, particularly with advances in computation, advanced analytics. There’s so many things that you can apply here. Just talk about the analysis stage. How do you pick the right tools?

Charles Conn: For me, the most important thing is that we start with simple heuristics and explanatory statistics before we go off and use the big-gun tools. We need to understand the shape and scope of our problem before we start applying these massive and complex analytical approaches.

Simon London: Would you agree with that?

Hugo Sarrazin: I agree. I think there are so many wonderful heuristics. You need to start there before you go deep into the modeling exercise. There’s an interesting dynamic that’s happening, though. In some cases, for some types of problems, it is even better to set yourself up to maximize your learning. Your problem-solving methodology is test and learn, test and learn, test and learn, and iterate. That is a heuristic in itself, the A/B testing that is used in many parts of the world. So that’s a problem-solving methodology. It’s nothing different. It just uses technology and feedback loops in a fast way. The other one is exploratory data analysis. When you’re dealing with a large-scale problem, and there’s so much data, I can get to the heuristics that Charles was talking about through very clever visualization of data.

You test with your data. You need to set up an environment to do so, but don’t get caught up in neural-network modeling immediately. You’re testing, you’re checking—“Is the data right? Is it sound? Does it make sense?”—before you launch too far.

Simon London: You do hear these ideas—that if you have a big enough data set and enough algorithms, they’re going to find things that you just wouldn’t have spotted, find solutions that maybe you wouldn’t have thought of. Does machine learning sort of revolutionize the problem-solving process? Or are these actually just other tools in the toolbox for structured problem solving?

Charles Conn: It can be revolutionary. There are some areas in which the pattern recognition of large data sets and good algorithms can help us see things that we otherwise couldn’t see. But I do think it’s terribly important we don’t think that this particular technique is a substitute for superb problem solving, starting with good problem definition. Many people use machine learning without understanding algorithms that themselves can have biases built into them. Just as 20 years ago, when we were doing statistical analysis, we knew that we needed good model definition, we still need a good understanding of our algorithms and really good problem definition before we launch off into big data sets and unknown algorithms.

Simon London: Step six. You’ve done your analysis.

Charles Conn: I take six and seven together, and this is the place where young problem solvers often make a mistake. They’ve got their analysis, and they assume that’s the answer, and of course it isn’t the answer. The ability to synthesize the pieces that came out of the analysis and begin to weave those into a story that helps people answer the question “What should I do?” This is back to where we started. If we can’t synthesize, and we can’t tell a story, then our decision maker can’t find the answer to “What should I do?”

Simon London: But, again, these final steps are about motivating people to action, right?

Charles Conn: Yeah.

Simon London: I am slightly torn about the nomenclature of problem solving because it’s on paper, right? Until you motivate people to action, you actually haven’t solved anything.

Charles Conn: I love this question because I think decision-making theory, without a bias to action, is a waste of time. Everything in how I approach this is to help people take action that makes the world better.

Simon London: Hence, these are absolutely critical steps. If you don’t do this well, you’ve just got a bunch of analysis.

Charles Conn: We end up in exactly the same place where we started, which is people speaking across each other, past each other in the public square, rather than actually working together, shoulder to shoulder, to crack these important problems.

Simon London: In the real world, we have a lot of uncertainty—arguably, increasing uncertainty. How do good problem solvers deal with that?

Hugo Sarrazin: At every step of the process. In the problem definition, when you’re defining the context, you need to understand those sources of uncertainty and whether they’re important or not important. It becomes important in the definition of the tree.

You need to think carefully about the branches of the tree that are more certain and less certain as you define them. They don’t have equal weight just because they’ve got equal space on the page. Then, when you’re prioritizing, your prioritization approach may put more emphasis on things that have low probability but huge impact—or, vice versa, may put a lot of priority on things that are very likely and, hopefully, have a reasonable impact. You can introduce that along the way. When you come back to the synthesis, you just need to be nuanced about what you’re understanding, the likelihood.

Often, people lack humility in the way they make their recommendations: “This is the answer.” They’re very precise, and I think we would all be well-served to say, “This is a likely answer under the following sets of conditions” and then make the level of uncertainty clearer, if that is appropriate. It doesn’t mean you’re always in the gray zone; it doesn’t mean you don’t have a point of view. It just means that you can be explicit about the certainty of your answer when you make that recommendation.

Simon London: So it sounds like there is an underlying principle: “Acknowledge and embrace the uncertainty. Don’t pretend that it isn’t there. Be very clear about what the uncertainties are up front, and then build that into every step of the process.”

Hugo Sarrazin: Every step of the process.

Simon London: Yeah. We have just walked through a particular structured methodology for problem solving. But, of course, this is not the only structured methodology for problem solving. One that is also very well-known is design thinking, which comes at things very differently. So, Hugo, I know you have worked with a lot of designers. Just give us a very quick summary. Design thinking—what is it, and how does it relate?

Hugo Sarrazin: It starts with an incredible amount of empathy for the user and uses that to define the problem. It does pause and go out in the wild and spend an enormous amount of time seeing how people interact with objects, seeing the experience they’re getting, seeing the pain points or joy—and uses that to infer and define the problem.

Simon London: Problem definition, but out in the world.

Hugo Sarrazin: With an enormous amount of empathy. There’s a huge emphasis on empathy. Traditional, more classic problem solving is you define the problem based on an understanding of the situation. This one almost presupposes that we don’t know the problem until we go see it. The second thing is you need to come up with multiple scenarios or answers or ideas or concepts, and there’s a lot of divergent thinking initially. That’s slightly different, versus the prioritization, but not for long. Eventually, you need to kind of say, “OK, I’m going to converge again.” Then you go and you bring things back to the customer and get feedback and iterate. Then you rinse and repeat, rinse and repeat. There’s a lot of tactile building, along the way, of prototypes and things like that. It’s very iterative.

Simon London: So, Charles, are these complements or are these alternatives?

Charles Conn: I think they’re entirely complementary, and I think Hugo’s description is perfect. When we do problem definition well in classic problem solving, we are demonstrating the kind of empathy, at the very beginning of our problem, that design thinking asks us to approach. When we ideate—and that’s very similar to the disaggregation, prioritization, and work-planning steps—we do precisely the same thing, and often we use contrasting teams, so that we do have divergent thinking. The best teams allow divergent thinking to bump them off whatever their initial biases in problem solving are. For me, design thinking gives us a constant reminder of creativity, empathy, and the tactile nature of problem solving, but it’s absolutely complementary, not alternative.

Simon London: I think, in a world of cross-functional teams, an interesting question is do people with design-thinking backgrounds really work well together with classical problem solvers? How do you make that chemistry happen?

Hugo Sarrazin: Yeah, it is not easy when people have spent an enormous amount of time seeped in design thinking or user-centric design, whichever word you want to use. If the person who’s applying classic problem-solving methodology is very rigid and mechanical in the way they’re doing it, there could be an enormous amount of tension. If there’s not clarity in the role and not clarity in the process, I think having the two together can be, sometimes, problematic.

The second thing that happens often is that the artifacts the two methodologies try to gravitate toward can be different. Classic problem solving often gravitates toward a model; design thinking migrates toward a prototype. Rather than writing a big deck with all my supporting evidence, they’ll bring an example, a thing, and that feels different. Then you spend your time differently to achieve those two end products, so that’s another source of friction.

Now, I still think it can be an incredibly powerful thing to have the two—if there are the right people with the right mind-set, if there is a team that is explicit about the roles, if we’re clear about the kind of outcomes we are attempting to bring forward. There’s an enormous amount of collaborativeness and respect.

Simon London: But they have to respect each other’s methodology and be prepared to flex, maybe, a little bit, in how this process is going to work.

Hugo Sarrazin: Absolutely.

Simon London: The other area where, it strikes me, there could be a little bit of a different sort of friction is this whole concept of the day-one answer, which is what we were just talking about in classical problem solving. Now, you know that this is probably not going to be your final answer, but that’s how you begin to structure the problem. Whereas I would imagine your design thinkers—no, they’re going off to do their ethnographic research and get out into the field, potentially for a long time, before they come back with at least an initial hypothesis.

Want better strategies? Become a bulletproof problem solver

Hugo Sarrazin: That is a great callout, and that’s another difference. Designers typically will like to soak into the situation and avoid converging too quickly. There’s optionality and exploring different options. There’s a strong belief that keeps the solution space wide enough that you can come up with more radical ideas. If there’s a large design team or many designers on the team, and you come on Friday and say, “What’s our week-one answer?” they’re going to struggle. They’re not going to be comfortable, naturally, to give that answer. It doesn’t mean they don’t have an answer; it’s just not where they are in their thinking process.

Simon London: I think we are, sadly, out of time for today. But Charles and Hugo, thank you so much.

Charles Conn: It was a pleasure to be here, Simon.

Hugo Sarrazin: It was a pleasure. Thank you.

Simon London: And thanks, as always, to you, our listeners, for tuning into this episode of the McKinsey Podcast . If you want to learn more about problem solving, you can find the book, Bulletproof Problem Solving: The One Skill That Changes Everything , online or order it through your local bookstore. To learn more about McKinsey, you can of course find us at McKinsey.com.

Charles Conn is CEO of Oxford Sciences Innovation and an alumnus of McKinsey’s Sydney office. Hugo Sarrazin is a senior partner in the Silicon Valley office, where Simon London, a member of McKinsey Publishing, is also based.

Explore a career with us

Related articles.

Strategy to beat the odds

Five routes to more innovative problem solving

The power has been restored and the SLO Campus will reopen on June 5.

• Cuesta College Home
• Current Students
• Student Success Centers

Study Guides

• Critical Thinking

Decision-making and Problem-solving

Appreciate the complexities involved in decision-making & problem solving.

Develop evidence to support views

Analyze situations carefully

Discuss subjects in an organized way

Predict the consequences of actions

Weigh alternatives

Generate and organize ideas

Form and apply concepts

Design systematic plans of action

A 5-Step Problem-Solving Strategy

Specify the problem – a first step to solving a problem is to identify it as specifically as possible.  It involves evaluating the present state and determining how it differs from the goal state.

Analyze the problem – analyzing the problem involves learning as much as you can about it.  It may be necessary to look beyond the obvious, surface situation, to stretch your imagination and reach for more creative options.

seek other perspectives

be flexible in your analysis

consider various strands of impact

brainstorm about all possibilities and implications

research problems for which you lack complete information. Get help.

Formulate possible solutions – identify a wide range of possible solutions.

try to think of all possible solutions

be creative

consider similar problems and how you have solved them

Evaluate possible solutions – weigh the advantages and disadvantages of each solution.  Think through each solution and consider how, when, and where you could accomplish each.  Consider both immediate and long-term results.  Mapping your solutions can be helpful at this stage.

Choose a solution – consider 3 factors:

compatibility with your priorities

amount of risk

practicality

Keys to Problem Solving

Think aloud – problem solving is a cognitive, mental process.  Thinking aloud or talking yourself through the steps of problem solving is useful.  Hearing yourself think can facilitate the process.

Allow time for ideas to "gel" or consolidate.  If time permits, give yourself time for solutions to develop.  Distance from a problem can allow you to clear your mind and get a new perspective.

Talk about the problem – describing the problem to someone else and talking about it can often make a problem become more clear and defined so that a new solution will surface.

Decision Making Strategies

Decision making is a process of identifying and evaluating choices.  We make numerous decisions every day and our decisions may range from routine, every-day types of decisions to those decisions which will have far reaching impacts.  The types of decisions we make are routine, impulsive, and reasoned.  Deciding what to eat for breakfast is a routine decision; deciding to do or buy something at the last minute is considered an impulsive decision; and choosing your college major is, hopefully, a reasoned decision.  College coursework often requires you to make the latter, or reasoned decisions.

Decision making has much in common with problem solving.  In problem solving you identify and evaluate solution paths; in decision making you make a similar discovery and evaluation of alternatives.  The crux of decision making, then, is the careful identification and evaluation of alternatives.  As you weigh alternatives, use the following suggestions:

Consider the outcome each is likely to produce, in both the short term and the long term.

Compare alternatives based on how easily you can accomplish each.

Evaluate possible negative side effects each may produce.

Consider the risk involved in each.

Be creative, original; don't eliminate alternatives because you have not heard or used them before.

An important part of decision making is to predict both short-term and long-term outcomes for each alternative.  You may find that while an alternative seems most desirable at the present, it may pose problems or complications over a longer time period.

• Uses of Critical Thinking
• Critically Evaluating the Logic and Validity of Information
• Recognizing Propaganda Techniques and Errors of Faulty Logic
• Developing the Ability to Analyze Historical and Contemporary Information
• Recognize and Value Various Viewpoints
• Appreciating the Complexities Involved in Decision-Making and Problem-Solving
• Being a Responsible Critical Thinker & Collaborating with Others
• Suggestions
• Read the Textbook
• When to Take Notes
• 10 Steps to Tests
• Studying for Exams
• Test-Taking Errors
• Test Anxiety
• Objective Tests
• Essay Tests
• The Reading Process
• Levels of Comprehension
• Strengthen Your Reading Comprehension
• Reading Rate
• How to Read a Textbook
• Organizational Patterns of a Paragraph
• Topics, Main Ideas, and Support
• Inferences and Conclusions
• Interpreting What You Read
• Concentrating and Remembering
• Converting Words into Pictures
• Spelling and the Dictionary
• Eight Essential Spelling Rules
• Exceptions to the Rules
• Motivation and Goal Setting
• Effective Studying
• Time Management
• Listening and Note-Taking
• Memory and Learning Styles
• Textbook Reading Strategies
• Memory Tips
• Test-Taking Strategies
• The First Step
• Study System
• Maximize Comprehension
• Different Reading Modes
• Paragraph Patterns
• An Effective Strategy
• Finding the Main Idea
• Read a Medical Text
• Read in the Sciences
• Read University Level
• Textbook Study Strategies
• The Origin of Words
• Using a Dictionary
• Interpreting a Dictionary Entry
• Structure Analysis
• Common Roots
• Word Relationships
• Using Word Relationships
• Context Clues
• The Importance of Reading
• Vocabulary Analogies
• Guide to Talking with Instructors
• Writing Help

Dr. Elizabeth Coria Selected for Aspen Institute Fellowship

Marie schoeff art gallery exhibition, cuesta college celebrates 59th commencement ceremony.

Build Your Future

Register for Fall

More From Forbes

Tips and techniques for problem-solving and decision-making.

• Share to Facebook
• Share to Twitter
• Share to Linkedin

Divya Parekh , of The DP Group, covers business growth, storytelling, high-impact performance and authority building.

Are you struggling to find effective solutions to problems you face in your professional or entrepreneurial ventures? Are you often indecisive when faced with complex decisions?

The ability to solve problems and make decisions quickly and effectively can mean the difference between success and failure. There are two main approaches to problem-solving and decision-making: vertical thinking and horizontal thinking. Both approaches have strengths and weaknesses, so understanding the differences between them can help you apply the right method at the right time.

Let's look at a few case studies to understand the very different benefits of these two approaches.

Vertical Thinking For Decision-Making

First, let's take Jane, the CFO of a financial services company. She needs to decide whether to invest in a new company software system.

Jane gathers all the relevant data about the software system and analyzes it thoroughly. She compares the cost of the system to the potential benefits, evaluates the risks involved and consults with subject matter experts. After careful consideration, she decides the benefits outweigh the costs and risks, and the company should invest in the software system.

This is vertical thinking: making a well-informed decision based on a thorough analysis of the data. Vertical thinking is especially useful in situations where there is a clear goal and a need for a precise, data-driven approach. Experts often use it in fields like finance, where decisions depend heavily on facts and figures.

Best Travel Insurance Companies

Best covid-19 travel insurance plans, horizontal thinking for problem-solving.

Let's move on to Sophie, the head of marketing for a fashion company. The company has been struggling to attract new customers.

Sophie sets up a brainstorming meeting with different department heads. They come up with a variety of creative solutions based on their diverse perspectives. One idea that stands out is to partner with a popular social media influencer to promote the company's products. The team works together to develop a plan to reach out to the influencer and negotiate a partnership.

This is horizontal thinking: working with a team to generate a variety of ideas and consider different perspectives to find an innovative solution. Horizontal thinking is a great approach for problem-solving when the problem is complex and there may be multiple solutions or approaches. Creative professionals, especially in marketing, advertising and designing, highly value this approach.

How Emotions Affect These Approaches

Over several years of coaching, I've noticed that emotions can play a significant role in problem-solving and decision-making, regardless of the thinking style used.

For instance, when using vertical thinking, emotions such as frustration and impatience can arise when a person or team has been working on a problem for an extended period with no clear solution. Conversely, when a team lands on a solution, there can be a sense of relief and accomplishment.

Similarly, when using horizontal thinking, emotions such as excitement and optimism can arise during a brainstorming session when new and creative ideas are being generated. However, disappointment or frustration can also arise when an idea fails to work.

It's important to recognize and acknowledge these emotions as they can affect team dynamics and ultimately, the success of the problem-solving process. I encourage leaders to create a safe and supportive environment where team members feel comfortable expressing their emotions and concerns.

Make These Thinking Styles Work For You

In my experience, a personalized approach that balances both vertical and horizontal thinking can help manage emotions and any other issues that arise effectively. By using vertical thinking to identify specific problems and solutions, and horizontal thinking to generate creative ideas, you can create a problem-solving process that encourages collaboration, creativity and innovation while minimizing negative emotions.

Are you ready to take your problem-solving and decision-making skills to the next level?

Forbes Coaches Council is an invitation-only community for leading business and career coaches. Do I qualify?

• Editorial Standards
• Reprints & Permissions

• Skip to main content
• Skip to primary sidebar
• Skip to secondary sidebar
• Skip to footer

Computer Notes

• Computer Fundamental
• Computer Memory
• DBMS Tutorial
• Operating System
• Computer Networking
• C Programming
• C++ Programming
• Java Programming
• C# Programming
• SQL Tutorial
• Management Tutorial
• Computer Graphics
• Compiler Design
• Style Sheet
• JavaScript Tutorial
• Html Tutorial
• Wordpress Tutorial
• Python Tutorial
• PHP Tutorial
• JSP Tutorial
• AngularJS Tutorial
• Data Structures
• E Commerce Tutorial
• Visual Basic
• Structs2 Tutorial
• Digital Electronics
• Internet Terms
• Servlet Tutorial
• Software Engineering
• Interviews Questions
• Basic Terms
• Troubleshooting

Header Right

Simon’s model of decision-making.

By Dinesh Thakur

Herbert Simon made key contributions to enhance our understanding of the decision-making process. In fact, he pioneered the field of decision support systems. According to (Simon 1960) and his later work with (Newell 1972), decision-making is a process with distinct stages. He suggested for the first time the decision-making model of human beings. His model of decision-making has three stages:

• Intelligence which deals with the problem identification and the data collection on the problem. • Design which deals with the generation of alternative solutions to the problem at hand. • Choice which is selecting the ‘best’ solution from amongst the alternative solutions using some criterion. 

The figure given below depicts Simon’s decision-making model clearly.

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

Intelligence Phase

This is the first step towards the decision-making process. In this step the decision-maker identifies/detects the problem or opportunity. A problem in the managerial context is detecting anything that is not according to the plan, rule or standard. An example of problem is the detection of sudden very high attrition for the present month by a HR manager among workers. Opportunity seeking on the other hand is the identification of a promising circumstance that might lead to better results. An example of identification of opportunity is-a marketing manager gets to know that two of his competitors will shut down operations (demand being constant) for some reason in the next three months, this means that he will be able to sell more in the market.

Thus, we see that either in the case of a problem or for the purpose of opportunity seeking the decision-making process is initiated and the first stage is the clear understanding of the stimulus that triggers this process. So if a problem/opportunity triggers this process then the first stage deals with the complete understanding of the problem/opportunity. Intelligence phase of decision-making process involves: Problem Searching: For searching the problem, the reality or actual is compared to some standards. Differences are measured & the differences are evaluated to determine whether there is any problem or not. Problem Formulation: When the problem is identified, there is always a risk of solving the wrong problem. In problem formulation, establishing relations with some problem solved earlier or an analogy proves quite useful.

Design Phase

Design is the process of designing solution outlines for the problem. Alternative solutions are designed to solve the same problem. Each alternative solution is evaluated after gathering data about the solution. The evaluation is done on the basic of criteria to identify the positive and negative aspects of each solution. Quantitative tools and models are used to arrive at these solutions. At this stage the solutions are only outlines of actual solutions and are meant for analysis of their suitability alone. A lot of creativity and innovation is required to design solutions.

Choice Phase

It is the stage in which the possible solutions are compared against one another to find out the most suitable solution. The ‘best’ solution may be identified using quantitative tools like decision tree analysis or qualitative tools like the six thinking hats technique, force field analysis, etc.

This is not as easy as it sounds because each solution presents a scenario and the problem itself may have multiple objectives making the choice process a very difficult one. Also uncertainty about the outcomes and scenarios make the choice of a single solution difficult.

You’ll also like:

• Bounded Rationality Model of Decision Making
• What do you understand by Decision Making? Discuss the nature and characteristics of Decision
• Role of Information in Decision-making
• Decision-Making and the Human Brain
• Decision Making Tools and Techniques

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

For any type of query or something that you think is missing, please feel free to Contact us .

Basic Course

• Database System
• Management System
• Electronic Commerce

Programming

• Structured Query (SQL)
• Java Servlet

World Wide Web

• Java Script
• HTML Language
• Cascading Style Sheet
• Java Server Pages