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Overview of the Problem-Solving Mental Process

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Rachel Goldman, PhD FTOS, is a licensed psychologist, clinical assistant professor, speaker, wellness expert specializing in eating behaviors, stress management, and health behavior change.

• Identify the Problem
• Define the Problem
• Form a Strategy
• Organize Information
• Allocate Resources
• Monitor Progress
• Evaluate the Results

Frequently Asked Questions

Problem-solving is a mental process that involves discovering, analyzing, and solving problems. The ultimate goal of problem-solving is to overcome obstacles and find a solution that best resolves the issue.

The best strategy for solving a problem depends largely on the unique situation. In some cases, people are better off learning everything they can about the issue and then using factual knowledge to come up with a solution. In other instances, creativity and insight are the best options.

It is not necessary to follow problem-solving steps sequentially, It is common to skip steps or even go back through steps multiple times until the desired solution is reached.

In order to correctly solve a problem, it is often important to follow a series of steps. Researchers sometimes refer to this as the problem-solving cycle. While this cycle is portrayed sequentially, people rarely follow a rigid series of steps to find a solution.

The following steps include developing strategies and organizing knowledge.

1. Identifying the Problem

While it may seem like an obvious step, identifying the problem is not always as simple as it sounds. In some cases, people might mistakenly identify the wrong source of a problem, which will make attempts to solve it inefficient or even useless.

Some strategies that you might use to figure out the source of a problem include :

• Asking questions about the problem
• Breaking the problem down into smaller pieces
• Looking at the problem from different perspectives
• Conducting research to figure out what relationships exist between different variables

2. Defining the Problem

After the problem has been identified, it is important to fully define the problem so that it can be solved. You can define a problem by operationally defining each aspect of the problem and setting goals for what aspects of the problem you will address

At this point, you should focus on figuring out which aspects of the problems are facts and which are opinions. State the problem clearly and identify the scope of the solution.

3. Forming a Strategy

After the problem has been identified, it is time to start brainstorming potential solutions. This step usually involves generating as many ideas as possible without judging their quality. Once several possibilities have been generated, they can be evaluated and narrowed down.

The next step is to develop a strategy to solve the problem. The approach used will vary depending upon the situation and the individual's unique preferences. Common problem-solving strategies include heuristics and algorithms.

• Heuristics are mental shortcuts that are often based on solutions that have worked in the past. They can work well if the problem is similar to something you have encountered before and are often the best choice if you need a fast solution.
• Algorithms are step-by-step strategies that are guaranteed to produce a correct result. While this approach is great for accuracy, it can also consume time and resources.

Heuristics are often best used when time is of the essence, while algorithms are a better choice when a decision needs to be as accurate as possible.

4. Organizing Information

Before coming up with a solution, you need to first organize the available information. What do you know about the problem? What do you not know? The more information that is available the better prepared you will be to come up with an accurate solution.

When approaching a problem, it is important to make sure that you have all the data you need. Making a decision without adequate information can lead to biased or inaccurate results.

5. Allocating Resources

Of course, we don't always have unlimited money, time, and other resources to solve a problem. Before you begin to solve a problem, you need to determine how high priority it is.

If it is an important problem, it is probably worth allocating more resources to solving it. If, however, it is a fairly unimportant problem, then you do not want to spend too much of your available resources on coming up with a solution.

At this stage, it is important to consider all of the factors that might affect the problem at hand. This includes looking at the available resources, deadlines that need to be met, and any possible risks involved in each solution. After careful evaluation, a decision can be made about which solution to pursue.

6. Monitoring Progress

After selecting a problem-solving strategy, it is time to put the plan into action and see if it works. This step might involve trying out different solutions to see which one is the most effective.

It is also important to monitor the situation after implementing a solution to ensure that the problem has been solved and that no new problems have arisen as a result of the proposed solution.

Effective problem-solvers tend to monitor their progress as they work towards a solution. If they are not making good progress toward reaching their goal, they will reevaluate their approach or look for new strategies .

7. Evaluating the Results

After a solution has been reached, it is important to evaluate the results to determine if it is the best possible solution to the problem. This evaluation might be immediate, such as checking the results of a math problem to ensure the answer is correct, or it can be delayed, such as evaluating the success of a therapy program after several months of treatment.

Once a problem has been solved, it is important to take some time to reflect on the process that was used and evaluate the results. This will help you to improve your problem-solving skills and become more efficient at solving future problems.

A Word From Verywell​

It is important to remember that there are many different problem-solving processes with different steps, and this is just one example. Problem-solving in real-world situations requires a great deal of resourcefulness, flexibility, resilience, and continuous interaction with the environment.

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You can become a better problem solving by:

• Practicing brainstorming and coming up with multiple potential solutions to problems
• Being open-minded and considering all possible options before making a decision
• Breaking down problems into smaller, more manageable pieces
• Asking for help when needed
• Researching different problem-solving techniques and trying out new ones
• Learning from mistakes and using them as opportunities to grow

It's important to communicate openly and honestly with your partner about what's going on. Try to see things from their perspective as well as your own. Work together to find a resolution that works for both of you. Be willing to compromise and accept that there may not be a perfect solution.

Take breaks if things are getting too heated, and come back to the problem when you feel calm and collected. Don't try to fix every problem on your own—consider asking a therapist or counselor for help and insight.

If you've tried everything and there doesn't seem to be a way to fix the problem, you may have to learn to accept it. This can be difficult, but try to focus on the positive aspects of your life and remember that every situation is temporary. Don't dwell on what's going wrong—instead, think about what's going right. Find support by talking to friends or family. Seek professional help if you're having trouble coping.

Davidson JE, Sternberg RJ, editors.  The Psychology of Problem Solving .  Cambridge University Press; 2003. doi:10.1017/CBO9780511615771

Sarathy V. Real world problem-solving .  Front Hum Neurosci . 2018;12:261. Published 2018 Jun 26. doi:10.3389/fnhum.2018.00261

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

• Guide: Problem Solving

Daniel Croft

Daniel Croft is an experienced continuous improvement manager with a Lean Six Sigma Black Belt and a Bachelor's degree in Business Management. With more than ten years of experience applying his skills across various industries, Daniel specializes in optimizing processes and improving efficiency. His approach combines practical experience with a deep understanding of business fundamentals to drive meaningful change.

• Last Updated: January 7, 2024
• Learn Lean Sigma

Problem-solving stands as a fundamental skill, crucial in navigating the complexities of both everyday life and professional environments. Far from merely providing quick fixes, it entails a comprehensive process involving the identification, analysis, and resolution of issues.

This multifaceted approach requires an understanding of the problem’s nature, the exploration of its various components, and the development of effective solutions. At its core, problem-solving serves as a bridge from the current situation to a desired outcome, requiring not only the recognition of an existing gap but also the precise definition and thorough analysis of the problem to find viable solutions.

Table of Contents

What is problem solving.

At its core, problem-solving is about bridging the gap between the current situation and the desired outcome. It starts with recognizing that a discrepancy exists, which requires intervention to correct or improve. The ability to identify a problem is the first step, but it’s equally crucial to define it accurately. A well-defined problem is half-solved, as the saying goes.

Analyzing the problem is the next critical step. This analysis involves breaking down the problem into smaller parts to understand its intricacies. It requires looking at the problem from various angles and considering all relevant factors – be they environmental, social, technical, or economic. This comprehensive analysis aids in developing a deeper understanding of the problem’s root causes, rather than just its symptoms.

Finally, effective problem-solving involves the implementation of the chosen solution and its subsequent evaluation. This stage tests the practicality of the solution and its effectiveness in the real world. It’s a critical phase where theoretical solutions meet practical application.

The Nature of Problems

The nature of the problem significantly influences the approach to solving it. Problems vary greatly in their complexity and structure, and understanding this is crucial for effective problem-solving.

Simple vs. Complex Problems : Simple problems are straightforward, often with clear solutions. They usually have a limited number of variables and predictable outcomes. On the other hand, complex problems are multi-faceted. They involve multiple variables, stakeholders, and potential outcomes, often requiring a more sophisticated analysis and a multi-pronged approach to solving.

Structured vs. Unstructured Problems : Structured problems are well-defined. They follow a specific pattern or set of rules, making their outcomes more predictable. These problems often have established methodologies for solving. For example, mathematical problems usually fall into this category. Unstructured problems, in contrast, are more ambiguous. They lack a clear pattern or set of rules, making their outcomes uncertain. These problems require a more exploratory approach, often involving trial and error, to identify potential solutions.

Understanding the type of problem at hand is essential, as it dictates the approach. For instance, a simple problem might require a straightforward solution, while a complex problem might need a more comprehensive, step-by-step approach. Similarly, structured problems might benefit from established methodologies, whereas unstructured problems might need more innovative and creative problem-solving techniques.

The Problem-Solving Process

The process of problem-solving is a methodical approach that involves several distinct stages. Each stage plays a crucial role in navigating from the initial recognition of a problem to its final resolution. Let’s explore each of these stages in detail.

Step 1: Identifying the Problem

Step 2: defining the problem.

Once the problem is identified, the next step is to define it clearly and precisely. This is a critical phase because a well-defined problem often suggests its solution. Defining the problem involves breaking it down into smaller, more manageable parts. It also includes understanding the scope and impact of the problem. A clear definition helps in focusing efforts and resources efficiently and serves as a guide to stay on track during the problem-solving process.

Step 3: Analyzing the Problem

Step 4: generating solutions, step 5: evaluating and selecting solutions.

After generating a list of possible solutions, the next step is to evaluate each one critically. This evaluation includes considering the feasibility, costs, benefits, and potential impact of each solution. Techniques like cost-benefit analysis, risk assessment, and scenario planning can be useful here. The aim is to select the solution that best addresses the problem in the most efficient and effective way, considering the available resources and constraints.

Step 6: Implementing the Solution

Step 7: reviewing and reflecting.

The final stage in the problem-solving process is to review the implemented solution and reflect on its effectiveness and the process as a whole. This involves assessing whether the solution met its intended goals and what could have been done differently. Reflection is a critical part of learning and improvement. It helps in understanding what worked well and what didn’t, providing valuable insights for future problem-solving efforts.

Tools and Techniques for Effective Problem Solving

Problem-solving is a multifaceted endeavor that requires a variety of tools and techniques to navigate effectively. Different stages of the problem-solving process can benefit from specific strategies, enhancing the efficiency and effectiveness of the solutions developed. Here’s a detailed look at some key tools and techniques:

Brainstorming

Swot analysis (strengths, weaknesses, opportunities, threats), root cause analysis.

This is a method used to identify the underlying causes of a problem, rather than just addressing its symptoms. One popular technique within root cause analysis is the “ 5 Whys ” method. This involves asking “why” multiple times (traditionally five) until the fundamental cause of the problem is uncovered. This technique encourages deeper thinking and can reveal connections that aren’t immediately obvious. By addressing the root cause, solutions are more likely to be effective and long-lasting.

Mind Mapping

Each of these tools and techniques can be adapted to different types of problems and situations. Effective problem solvers often use a combination of these methods, depending on the nature of the problem and the context in which it exists. By leveraging these tools, one can enhance their ability to dissect complex problems, generate creative solutions, and implement effective strategies to address challenges.

Developing Problem-Solving Skills

Developing problem-solving skills is a dynamic process that hinges on both practice and introspection. Engaging with a diverse array of problems enhances one’s ability to adapt and apply different strategies. This exposure is crucial as it allows individuals to encounter various scenarios, ranging from straightforward to complex, each requiring a unique approach. Collaborating with others in teams is especially beneficial. It broadens one’s perspective, offering insights into different ways of thinking and approaching problems. Such collaboration fosters a deeper understanding of how diverse viewpoints can contribute to more robust solutions.

Reflection is equally important in the development of problem-solving skills. Reflecting on both successes and failures provides valuable lessons. Successes reinforce effective strategies and boost confidence, while failures are rich learning opportunities that highlight areas for improvement. This reflective practice enables one to understand what worked, what didn’t, and why.

Critical thinking is a foundational skill in problem-solving. It involves analyzing information, evaluating different perspectives, and making reasoned judgments. Creativity is another vital component. It pushes the boundaries of conventional thinking and leads to innovative solutions. Effective communication also plays a crucial role, as it ensures that ideas are clearly understood and collaboratively refined.

In conclusion, problem-solving is an indispensable skill set that blends analytical thinking, creativity, and practical implementation. It’s a journey from understanding the problem to applying a solution and learning from the outcome.

Whether dealing with simple or complex issues, or structured or unstructured challenges, the essence of problem-solving lies in a methodical approach and the effective use of various tools and techniques. It’s a skill that is honed over time, through experience, reflection, and the continuous development of critical thinking, creativity, and communication abilities. In mastering problem-solving, one not only addresses immediate issues but also builds a foundation for future challenges, leading to more innovative and effective outcomes.

• Mourtos, N.J., Okamoto, N.D. and Rhee, J., 2004, February. Defining, teaching, and assessing problem solving skills . In  7th UICEE Annual Conference on Engineering Education  (pp. 1-5).
• Foshay, R. and Kirkley, J., 2003. Principles for teaching problem solving.   Technical paper ,  4 (1), pp.1-16.

Q: What are the key steps in the problem-solving process?

A : The problem-solving process involves several key steps: identifying the problem, defining it clearly, analyzing it to understand its root causes, generating a range of potential solutions, evaluating and selecting the most viable solution, implementing the chosen solution, and finally, reviewing and reflecting on the effectiveness of the solution and the process used to arrive at it.

Q: How can brainstorming be effectively used in problem-solving?

A: Brainstorming is effective in the solution generation phase of problem-solving. It involves gathering a group and encouraging the free flow of ideas without immediate criticism. The goal is to produce a large quantity of ideas, fostering creative thinking. This technique helps in uncovering unique and innovative solutions that might not surface in a more structured setting.

Q: What is SWOT Analysis and how does it aid in problem-solving?

A : SWOT Analysis is a strategic planning tool used to evaluate the Strengths, Weaknesses, Opportunities, and Threats involved in a situation. In problem-solving, it aids by providing a clear understanding of the internal and external factors that could impact the problem and potential solutions. This analysis helps in formulating strategies that leverage strengths and opportunities while mitigating weaknesses and threats.

Q: Why is it important to understand the nature of a problem before solving it?

A : Understanding the nature of a problem is crucial as it dictates the approach for solving it. Problems can be simple or complex, structured or unstructured, and each type requires a different strategy. A clear understanding of the problem’s nature helps in applying the appropriate methods and tools for effective resolution.

Q: How does reflection contribute to developing problem-solving skills?

A : Reflection is a critical component in developing problem-solving skills. It involves looking back at the problem-solving process and the implemented solution to assess what worked well and what didn’t. Reflecting on both successes and failures provides valuable insights and lessons, helping to refine and improve problem-solving strategies for future challenges. This reflective practice enhances one’s ability to approach problems more effectively over time.

Daniel Croft is a seasoned continuous improvement manager with a Black Belt in Lean Six Sigma. With over 10 years of real-world application experience across diverse sectors, Daniel has a passion for optimizing processes and fostering a culture of efficiency. He's not just a practitioner but also an avid learner, constantly seeking to expand his knowledge. Outside of his professional life, Daniel has a keen Investing, statistics and knowledge-sharing, which led him to create the website learnleansigma.com, a platform dedicated to Lean Six Sigma and process improvement insights.

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What is Problem Solving? (Steps, Techniques, Examples)

By Status.net Editorial Team on May 7, 2023 — 5 minutes to read

What Is Problem Solving?

Definition and importance.

Problem solving is the process of finding solutions to obstacles or challenges you encounter in your life or work. It is a crucial skill that allows you to tackle complex situations, adapt to changes, and overcome difficulties with ease. Mastering this ability will contribute to both your personal and professional growth, leading to more successful outcomes and better decision-making.

Problem-Solving Steps

The problem-solving process typically includes the following steps:

• Identify the issue : Recognize the problem that needs to be solved.
• Analyze the situation : Examine the issue in depth, gather all relevant information, and consider any limitations or constraints that may be present.
• Generate potential solutions : Brainstorm a list of possible solutions to the issue, without immediately judging or evaluating them.
• Evaluate options : Weigh the pros and cons of each potential solution, considering factors such as feasibility, effectiveness, and potential risks.
• Select the best solution : Choose the option that best addresses the problem and aligns with your objectives.
• Implement the solution : Put the selected solution into action and monitor the results to ensure it resolves the issue.
• Review and learn : Reflect on the problem-solving process, identify any improvements or adjustments that can be made, and apply these learnings to future situations.

Defining the Problem

To start tackling a problem, first, identify and understand it. Analyzing the issue thoroughly helps to clarify its scope and nature. Ask questions to gather information and consider the problem from various angles. Some strategies to define the problem include:

• Brainstorming with others
• Asking the 5 Ws and 1 H (Who, What, When, Where, Why, and How)
• Analyzing cause and effect
• Creating a problem statement

Generating Solutions

Once the problem is clearly understood, brainstorm possible solutions. Think creatively and keep an open mind, as well as considering lessons from past experiences. Consider:

• Creating a list of potential ideas to solve the problem
• Grouping and categorizing similar solutions
• Prioritizing potential solutions based on feasibility, cost, and resources required
• Involving others to share diverse opinions and inputs

Evaluating and Selecting Solutions

Evaluate each potential solution, weighing its pros and cons. To facilitate decision-making, use techniques such as:

• SWOT analysis (Strengths, Weaknesses, Opportunities, Threats)
• Decision-making matrices
• Pros and cons lists
• Risk assessments

After evaluating, choose the most suitable solution based on effectiveness, cost, and time constraints.

Implementing and Monitoring the Solution

Implement the chosen solution and monitor its progress. Key actions include:

• Communicating the solution to relevant parties
• Setting timelines and milestones
• Assigning tasks and responsibilities
• Monitoring the solution and making adjustments as necessary
• Evaluating the effectiveness of the solution after implementation

Utilize feedback from stakeholders and consider potential improvements. Remember that problem-solving is an ongoing process that can always be refined and enhanced.

Problem-Solving Techniques

During each step, you may find it helpful to utilize various problem-solving techniques, such as:

• Brainstorming : A free-flowing, open-minded session where ideas are generated and listed without judgment, to encourage creativity and innovative thinking.
• Root cause analysis : A method that explores the underlying causes of a problem to find the most effective solution rather than addressing superficial symptoms.
• SWOT analysis : A tool used to evaluate the strengths, weaknesses, opportunities, and threats related to a problem or decision, providing a comprehensive view of the situation.
• Mind mapping : A visual technique that uses diagrams to organize and connect ideas, helping to identify patterns, relationships, and possible solutions.

Brainstorming

When facing a problem, start by conducting a brainstorming session. Gather your team and encourage an open discussion where everyone contributes ideas, no matter how outlandish they may seem. This helps you:

• Generate a diverse range of solutions
• Encourage all team members to participate
• Foster creative thinking

When brainstorming, remember to:

• Reserve judgment until the session is over
• Encourage wild ideas
• Combine and improve upon ideas

Root Cause Analysis

For effective problem-solving, identifying the root cause of the issue at hand is crucial. Try these methods:

• 5 Whys : Ask “why” five times to get to the underlying cause.
• Fishbone Diagram : Create a diagram representing the problem and break it down into categories of potential causes.
• Pareto Analysis : Determine the few most significant causes underlying the majority of problems.

SWOT Analysis

SWOT analysis helps you examine the Strengths, Weaknesses, Opportunities, and Threats related to your problem. To perform a SWOT analysis:

• List your problem’s strengths, such as relevant resources or strong partnerships.
• Identify its weaknesses, such as knowledge gaps or limited resources.
• Explore opportunities, like trends or new technologies, that could help solve the problem.
• Recognize potential threats, like competition or regulatory barriers.

SWOT analysis aids in understanding the internal and external factors affecting the problem, which can help guide your solution.

Mind Mapping

A mind map is a visual representation of your problem and potential solutions. It enables you to organize information in a structured and intuitive manner. To create a mind map:

• Write the problem in the center of a blank page.
• Draw branches from the central problem to related sub-problems or contributing factors.
• Add more branches to represent potential solutions or further ideas.

Mind mapping allows you to visually see connections between ideas and promotes creativity in problem-solving.

Examples of Problem Solving in Various Contexts

In the business world, you might encounter problems related to finances, operations, or communication. Applying problem-solving skills in these situations could look like:

• Identifying areas of improvement in your company’s financial performance and implementing cost-saving measures
• Resolving internal conflicts among team members by listening and understanding different perspectives, then proposing and negotiating solutions
• Streamlining a process for better productivity by removing redundancies, automating tasks, or re-allocating resources

In educational contexts, problem-solving can be seen in various aspects, such as:

• Addressing a gap in students’ understanding by employing diverse teaching methods to cater to different learning styles
• Developing a strategy for successful time management to balance academic responsibilities and extracurricular activities
• Seeking resources and support to provide equal opportunities for learners with special needs or disabilities

Everyday life is full of challenges that require problem-solving skills. Some examples include:

• Overcoming a personal obstacle, such as improving your fitness level, by establishing achievable goals, measuring progress, and adjusting your approach accordingly
• Navigating a new environment or city by researching your surroundings, asking for directions, or using technology like GPS to guide you
• Dealing with a sudden change, like a change in your work schedule, by assessing the situation, identifying potential impacts, and adapting your plans to accommodate the change.
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Article • 7 min read

What Is Problem Solving?

By the Mind Tools Content Team

We all spend a lot of our time solving problems, both at work and in our personal lives.

Some problems are small, and we can quickly sort them out ourselves. But others are complex challenges that take collaboration, creativity, and a considerable amount of effort to solve.

At work, the types of problems we face depend largely on the organizations we're in and the jobs we do. A manager in a cleaning company, for example, might spend their day untangling staffing issues, resolving client complaints, and sorting out problems with equipment and supplies. An aircraft designer, on the other hand, might be grappling with a problem about aerodynamics, or trying to work out why a new safety feature isn't working. Meanwhile, a politician might be exploring solutions to racial injustice or climate change.

But whatever issues we face, there are some common ways to tackle them effectively. And we can all boost our confidence and ability to succeed by building a strong set of problem-solving skills.

Mind Tools offers a large collection of resources to help you do just that!

How Well Do You Solve Problems?

Start by taking an honest look at your existing skills. What's your current approach to solving problems, and how well is it working? Our quiz, How Good Is Your Problem Solving? lets you analyze your abilities, and signposts ways to address any areas of weakness.

Define Every Problem

The first step in solving a problem is understanding what that problem actually is. You need to be sure that you're dealing with the real problem – not its symptoms. For example, if performance in your department is substandard, you might think that the problem lies with the individuals submitting work. However, if you look a bit deeper, the real issue might be a general lack of training, or an unreasonable workload across the team.

Tools like 5 Whys , Appreciation and Root Cause Analysis get you asking the right questions, and help you to work through the layers of a problem to uncover what's really going on.

However, defining a problem doesn't mean deciding how to solve it straightaway. It's important to look at the issue from a variety of perspectives. If you commit yourself too early, you can end up with a short-sighted solution. The CATWOE checklist provides a powerful reminder to look at many elements that may contribute to the problem, keeping you open to a variety of possible solutions.

Understanding Complexity

As you define your problem, you'll often discover just how complicated it is. There are likely several interrelated issues involved. That's why it's important to have ways to visualize, simplify and make sense of this tangled mess!

Affinity Diagrams are great for organizing many different pieces of information into common themes, and for understanding the relationships between them.

Another popular tool is the Cause-and-Effect Diagram . To generate viable solutions, you need a solid understanding of what's causing the problem.

When your problem occurs within a business process, creating a Flow Chart , Swim Lane Diagram or a Systems Diagram will help you to see how various activities and inputs fit together. This may well highlight a missing element or bottleneck that's causing your problem.

Quite often, what seems to be a single problem turns out to be a whole series of problems. The Drill Down technique prompts you to split your problem into smaller, more manageable parts.

General Problem-Solving Tools

When you understand the problem in front of you, you’re ready to start solving it. With your definition to guide you, you can generate several possible solutions, choose the best one, then put it into action. That's the four-step approach at the heart of good problem solving.

There are various problem-solving styles to use. For example:

• Constructive Controversy is a way of widening perspectives and energizing discussions.
• Inductive Reasoning makes the most of people’s experiences and know-how, and can speed up solution finding.
• Means-End Analysis can bring extra clarity to your thinking, and kick-start the process of implementing solutions.

Specific Problem-Solving Systems

Some particularly complicated or important problems call for a more comprehensive process. Again, Mind Tools has a range of approaches to try, including:

• Simplex , which involves an eight-stage process: problem finding, fact finding, defining the problem, idea finding, selecting and evaluating, planning, selling the idea, and acting. These steps build upon the basic, four-step process described above, and they create a cycle of problem finding and solving that will continually improve your organization.
• Appreciative Inquiry , which is a uniquely positive way of solving problems by examining what's working well in the areas surrounding them.
• Soft Systems Methodology , which takes you through four stages to uncover more details about what's creating your problem, and then define actions that will improve the situation.

Further Problem-Solving Strategies

Good problem solving requires a number of other skills – all of which are covered by Mind Tools.

For example, we have a large section of resources to improve your Creativity , so that you come up with a range of possible solutions.

By strengthening your Decision Making , you'll be better at evaluating the options, selecting the best ones, then choosing how to implement them.

And our Project Management collection has valuable advice for strengthening the whole problem-solving process. The resources there will help you to make effective changes – and then keep them working long term.

Problems are an inescapable part of life, both in and out of work. So we can all benefit from having strong problem-solving skills.

It's important to understand your current approach to problem solving, and to know where and how to improve.

Define every problem you encounter – and understand its complexity, rather than trying to solve it too soon.

There's a range of general problem-solving approaches, helping you to generate possible answers, choose the best ones, and then implement your solution.

Some complicated or serious problems require more specific problem-solving systems, especially when they relate to business processes.

By boosting your creativity, decision-making and project-management skills, you’ll become even better at solving all the problems you face.

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Introduction

Mastering the art of problem-solving is crucial for making better decisions. Whether you're a student, a business owner, or an employee, problem-solving skills can help you tackle complex issues and find practical solutions. The 7-Step Problem-Solving Process is a proven method that can help you approach problems systematically and efficiently.

The 7-Step Problem-Solving Process involves steps that guide you through the problem-solving process. The first step is to define the problem, followed by disaggregating the problem into smaller, more manageable parts. Next, you prioritize the features and create a work plan to address each. Then, you analyze each piece, synthesize the information, and communicate your findings to others.

By following this process, you can avoid jumping to conclusions, overlooking important details, or making hasty decisions. Instead, you can approach problems with a clear and structured mindset, which can help you make better decisions and achieve better outcomes.

In this article, we'll explore each step of the 7-Step Problem-Solving Process in detail so you can start mastering this valuable skill. At the end of the blog post, you can download the process's free PowerPoint and PDF templates .

Step 1: Define the Problem

The first step in the problem-solving process is to define the problem. This step is crucial because finding a solution is only accessible if the problem is clearly defined. The problem must be specific, measurable, and achievable.

One way to define the problem is to ask the right questions. Questions like "What is the problem?" and "What are the causes of the problem?" can help. Gathering data and information about the issue to assist in the definition process is also essential.

Another critical aspect of defining the problem is identifying the stakeholders. Who is affected by it? Who has a stake in finding a solution? Identifying the stakeholders can help ensure that the problem is defined in a way that considers the needs and concerns of all those affected.

Once the problem is defined, it is essential to communicate the definition to all stakeholders. This helps to ensure that everyone is on the same page and that there is a shared understanding of the problem.

Step 2: Disaggregate

After defining the problem, the next step in the 7-step problem-solving process is to disaggregate the problem into smaller, more manageable parts. Disaggregation helps break down the problem into smaller pieces that can be analyzed individually. This step is crucial in understanding the root cause of the problem and identifying the most effective solutions.

Disaggregation can be achieved by breaking down the problem into sub-problems, identifying the contributing factors, and analyzing the relationships between these factors. This step helps identify the most critical factors that must be addressed to solve the problem.

A tree or fishbone diagram is one effective way to disaggregate a problem. These diagrams help identify the different factors contributing to the problem and how they are related. Another way is to use a table to list the other factors contributing to the situation and their corresponding impact on the issue.

Disaggregation helps in breaking down complex problems into smaller, more manageable parts. It helps understand the relationships between different factors contributing to the problem and identify the most critical factors that must be addressed. By disaggregating the problem, decision-makers can focus on the most vital areas, leading to more effective solutions.

Step 3: Prioritize

After defining the problem and disaggregating it into smaller parts, the next step in the 7-step problem-solving process is prioritizing the issues that need addressing. Prioritizing helps to focus on the most pressing issues and allocate resources more effectively.

There are several ways to prioritize issues, including:

• Urgency: Prioritize issues based on their urgency. Problems that require immediate attention should be addressed first.
• Impact: Prioritize issues based on their impact on the organization or stakeholders. Problems with a high impact should be given priority.
• Resources: Prioritize issues based on the resources required to address them. Problems that require fewer resources should be dealt with first.

It is important to involve stakeholders in the prioritization process, considering their concerns and needs. This can be done through surveys, focus groups, or other forms of engagement.

Once the issues have been prioritized, developing a plan of action to address them is essential. This involves identifying the resources required, setting timelines, and assigning responsibilities.

Prioritizing issues is a critical step in problem-solving. By focusing on the most pressing problems, organizations can allocate resources more effectively and make better decisions.

Step 4: Workplan

After defining the problem, disaggregating, and prioritizing the issues, the next step in the 7-step problem-solving process is to develop a work plan. This step involves creating a roadmap that outlines the steps needed to solve the problem.

The work plan should include a list of tasks, deadlines, and responsibilities for each team member involved in the problem-solving process. Assigning tasks based on each team member's strengths and expertise ensures the work is completed efficiently and effectively.

Creating a work plan can help keep the team on track and ensure everyone is working towards the same goal. It can also help to identify potential roadblocks or challenges that may arise during the problem-solving process and develop contingency plans to address them.

Several tools and techniques can be used to develop a work plan, including Gantt charts, flowcharts, and mind maps. These tools can help to visualize the steps needed to solve the problem and identify dependencies between tasks.

Developing a work plan is a critical step in the problem-solving process. It provides a clear roadmap for solving the problem and ensures everyone involved is aligned and working towards the same goal.

Step 5: Analysis

Once the problem has been defined and disaggregated, the next step is to analyze the information gathered. This step involves examining the data, identifying patterns, and determining the root cause of the problem.

Several methods can be used during the analysis phase, including:

• Root cause analysis
• Pareto analysis
• SWOT analysis

Root cause analysis is a popular method used to identify the underlying cause of a problem. This method involves asking a series of "why" questions to get to the root cause of the issue.

Pareto analysis is another method that can be used during the analysis phase. This method involves identifying the 20% of causes responsible for 80% of the problems. By focusing on these critical causes, organizations can make significant improvements.

Finally, SWOT analysis is a valuable tool for analyzing the internal and external factors that may impact the problem. This method involves identifying the strengths, weaknesses, opportunities, and threats related to the issue.

Overall, the analysis phase is critical for identifying the root cause of the problem and developing practical solutions. By using a combination of methods, organizations can gain a deeper understanding of the issue and make informed decisions.

Step 6: Synthesize

Once the analysis phase is complete, it is time to synthesize the information gathered to arrive at a solution. During this step, the focus is on identifying the most viable solution that addresses the problem. This involves examining and combining the analysis results for a clear and concise conclusion.

One way to synthesize the information is to use a decision matrix. This involves creating a table that lists the potential solutions and the essential criteria for making a decision. Each answer is then rated against each standard, and the scores are tallied to arrive at a final decision.

Another approach to synthesizing the information is to use a mind map. This involves creating a visual representation of the problem and the potential solutions. The mind map can identify the relationships between the different pieces of information and help prioritize the solutions.

During the synthesis phase, it is vital to remain open-minded and consider all potential solutions. Involving all stakeholders in the decision-making process is essential to ensure everyone's perspectives are considered.

Step 7: Communicate

After synthesizing the information, the next step is communicating the findings to the relevant stakeholders. This is a crucial step because it helps to ensure that everyone is on the same page and that the decision-making process is transparent.

One effective way to communicate the findings is through a well-organized report. The report should include the problem statement, the analysis, the synthesis, and the recommended solution. It should be clear, concise, and easy to understand.

In addition to the report, a presentation explaining the findings is essential. The presentation should be tailored to the audience and highlight the report's key points. Visual aids such as tables, graphs, and charts can make the presentation more engaging.

During the presentation, it is essential to be open to feedback and questions from the audience. This helps ensure everyone agrees with the recommended solution and addresses concerns or objections.

Effective communication is vital to ensuring the decision-making process is successful. Stakeholders can make informed decisions and work towards a common goal by communicating the findings clearly and concisely.

The 7-step problem-solving process is a powerful tool for helping individuals and organizations make better decisions. By following these steps, individuals can identify the root cause of a problem, prioritize potential solutions, and develop a clear plan of action. This process can be applied to various scenarios, from personal challenges to complex business problems.

Through disaggregation, individuals can break down complex problems into smaller, more manageable parts. By prioritizing potential solutions, individuals can focus their efforts on the most impactful actions. The work step allows individuals to develop a clear action plan, while the analysis step provides a framework for evaluating possible solutions.

The synthesis step combines all the information gathered to develop a comprehensive solution. Finally, the communication step allows individuals to share their answers with others and gather feedback.

By mastering the 7-step problem-solving process, individuals can become more effective decision-makers and problem-solvers. This process can help individuals and organizations save time and resources while improving outcomes. With practice, individuals can develop the skills to apply this process to a wide range of scenarios and make better decisions in all areas of life.

7-Step Problem-Solving Process PPT Template

Free powerpoint and pdf template, executive summary: the 7-step problem-solving process.

The 7-Step Problem-Solving Process is a robust and systematic method to help individuals and organizations make better decisions by tackling complex issues and finding practical solutions. This process comprises defining the problem, disaggregating it into smaller parts, prioritizing the issues, creating a work plan, analyzing the data, synthesizing the information, and communicating the findings.

By following these steps, individuals can identify the root cause of a problem, break it down into manageable components, and prioritize the most impactful actions. The work plan, analysis, and synthesis steps provide a framework for developing comprehensive solutions, while the communication step ensures transparency and stakeholder engagement.

Mastering this process can improve decision-making and problem-solving capabilities, save time and resources, and improve outcomes in personal and professional contexts.

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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.

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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.

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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.

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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.

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Table of Contents

The problem-solving process, how to solve problems: 5 steps, train to solve problems with lean today, what is problem solving steps, techniques, & best practices explained.

Problem solving is the art of identifying problems and implementing the best possible solutions. Revisiting your problem-solving skills may be the missing piece to leveraging the performance of your business, achieving Lean success, or unlocking your professional potential. 

Ask any colleague if they’re an effective problem-solver and their likely answer will be, “Of course! I solve problems every day.” 

Problem solving is part of most job descriptions, sure. But not everyone can do it consistently. 

Problem solving is the process of defining a problem, identifying its root cause, prioritizing and selecting potential solutions, and implementing the chosen solution.

There’s no one-size-fits-all problem-solving process. Often, it’s a unique methodology that aligns your short- and long-term objectives with the resources at your disposal. Nonetheless, many paradigms center problem solving as a pathway for achieving one’s goals faster and smarter. 

One example is the Six Sigma framework , which emphasizes eliminating errors and refining the customer experience, thereby improving business outcomes. Developed originally by Motorola, the Six Sigma process identifies problems from the perspective of customer satisfaction and improving product delivery. 

Lean management, a similar method, is about streamlining company processes over time so they become “leaner” while producing better outcomes. 

Trendy business management lingo aside, both of these frameworks teach us that investing in your problem solving process for personal and professional arenas will bring better productivity.

1. Precisely Identify Problems

As obvious as it seems, identifying the problem is the first step in the problem-solving process. Pinpointing a problem at the beginning of the process will guide your research, collaboration, and solutions in the right direction. 

At this stage, your task is to identify the scope and substance of the problem. Ask yourself a series of questions: 

• What’s the problem? 
• How many subsets of issues are underneath this problem? 
• What subject areas, departments of work, or functions of business can best define this problem? 

Although some problems are naturally large in scope, precision is key. Write out the problems as statements in planning sheets . Should information or feedback during a later step alter the scope of your problem, revise the statements. 

Framing the problem at this stage will help you stay focused if distractions come up in later stages. Furthermore, how you frame a problem will aid your search for a solution. A strategy of building Lean success, for instance, will emphasize identifying and improving upon inefficient systems. 

2. Collect Information and Plan 

The second step is to collect information and plan the brainstorming process. This is another foundational step to road mapping your problem-solving process. Data, after all, is useful in identifying the scope and substance of your problems. 

Collecting information on the exact details of the problem, however, is done to narrow the brainstorming portion to help you evaluate the outcomes later. Don’t overwhelm yourself with unnecessary information — use the problem statements that you identified in step one as a north star in your research process. 

This stage should also include some planning. Ask yourself:

• What parties will ultimately decide a solution? 
• Whose voices and ideas should be heard in the brainstorming process? 
• What resources are at your disposal for implementing a solution? 

Establish a plan and timeline for steps 3-5. 

3. Brainstorm Solutions

Brainstorming solutions is the bread and butter of the problem-solving process. At this stage, focus on generating creative ideas. As long as the solution directly addresses the problem statements and achieves your goals, don’t immediately rule it out. 

Moreover, solutions are rarely a one-step answer and are more like a roadmap with a set of actions. As you brainstorm ideas, map out these solutions visually and include any relevant factors such as costs involved, action steps, and involved parties. 

With Lean success in mind, stay focused on solutions that minimize waste and improve the flow of business ecosystems. 

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4. Decide and Implement

The most critical stage is selecting a solution. Easier said than done. Consider the criteria that has arisen in previous steps as you decide on a solution that meets your needs. 

Once you select a course of action, implement it. 

Practicing due diligence in earlier stages of the process will ensure that your chosen course of action has been evaluated from all angles. Often, efficient implementation requires us to act correctly and successfully the first time, rather than being hurried and sloppy. Further compilations will create more problems, bringing you back to step 1. 

5. Evaluate

Exercise humility and evaluate your solution honestly. Did you achieve the results you hoped for? What would you do differently next time? 

As some experts note, formulating feedback channels into your evaluation helps solidify future success. A framework like Lean success, for example, will use certain key performance indicators (KPIs) like quality, delivery success, reducing errors, and more. Establish metrics aligned with company goals to assess your solutions.

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The Eight Fundamentals of Problem Solving

As business leaders we are consequently required to solve problems. But what are the very fundamentals of problem solving?

Read on to find out.

1. Define the Real Problem

This is the biggie. Ensure that you are solving the right problem. Toyota is justifiably famous for its problem-solving savvy in perfecting its production methods. According to Toyota, the key to their method is to spend relatively more time defining the problem and relatively less time on figuring out the solution.

2. Solve the Root Cause of the Problem

Don’t treat the symptoms; solve the root cause of the problem. There are numerous methods to determine root causes—cause mapping, fishbone diagrams, etc. For me, the easiest and most effective is to use the “Five Whys.” Ask a question and to each answer ask. “Why?” again. Doing this for five times should get you to the root cause of the problem.

3. Use a Hypothesis

As happens on the “CSI” television shows, you should make a best guess as to the solution to the problem at the very beginning of your process—define the initial hypothesis. Then test this initial hypothesis by digging deep to determine whether the hypothesis is right or wrong and adjusting the hypothesis as the facts dictate.

4. Get the Facts

Dig deep and get the facts to truly understand the nature of the problem and the possible solutions. Do the analysis to let the facts do the talking instead of gut instinct. As Wharton’s own Peter Cappelli says: “I tell my MBA students that whenever you are going with your gut, you are doing something wrong. In most cases, you can actually figure it out. So you should sit down and figure it out.”

5. Keep the solution simple

Any solution to a problem has to be implemented by your team. So keep it simple. Be able to explain the solution clearly and precisely in 30 seconds. Limit the action items to solve the problem to three. Go for the solution that solves 80 percent of the problem but that is 100 percent implementable by the team—rather than a 100 percent solution that is unlikely to ever be properly implemented.

6. Do not re-invent the wheel

Plagiarism can be good. If someone has a clever idea or way to solve your problem, by all means legally use it. The “not invented here” syndrome is just sheer arrogance.

7. Gain momentum in problem solving

In situations where you have multiple problems to solve (e.g., business turnarounds) pluck the low-hanging but important fruit first. Solve the easy problems. This gives you momentum, shows progress and gives your team confidence.

8. Consider time

With any solution, ensure that you do first what needs to be done first. Also, ensure that the solution can be implemented in a reasonable period of time. Solutions that take longer than a few months will likely fail. The momentum will die out or top management will move on to another “critical issue.”

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The Stages of the Problem Solving Cycle in Cognitive Psychology – Understanding, Planning, Execution, Evaluation, and Reflection

• Post author By bicycle-u
• Post date 08.12.2023

Problem solving is a fundamental aspect of human cognition. It involves the ability to identify and define a problem, generate potential solutions, evaluate those solutions, and select the most appropriate one. The problem solving cycle is a key concept in cognitive psychology that helps us understand how individuals approach and solve problems.

In the problem solving cycle , individuals first must recognize and define the problem they are facing. This involves identifying the specific issue or obstacle that needs to be overcome. Once the problem is clearly defined, individuals can then move on to the next stage of the cycle.

Next, individuals engage in the process of generating potential solutions . This may involve brainstorming ideas, seeking out information or advice, or experimenting with different approaches. The goal is to come up with as many possible solutions as possible, without judgment or evaluation.

Once a range of potential solutions has been generated, individuals then evaluate these solutions based on their feasibility and effectiveness . This involves assessing the advantages and disadvantages of each solution and considering the potential outcomes of implementing them. It may also involve consulting others or seeking additional information to inform the evaluation process.

Finally, individuals select the most appropriate solution from the evaluated options. This decision-making process takes into account various factors such as the individual’s goals, resources, and constraints. Once a solution has been selected, individuals can then implement and evaluate its effectiveness, closing the problem solving cycle.

The problem solving cycle is a dynamic and iterative process that can be applied to a wide range of problems and situations. It provides a framework for understanding how individuals approach and solve problems, and it can be useful in both personal and professional settings. By understanding the various stages of the problem solving cycle, individuals can become more effective problem solvers and make better decisions.

Understanding the Problem Solving Process

In cognitive psychology, the problem solving process is a key concept in understanding how individuals navigate and overcome challenges. Problem solving is a cyclical process that involves identifying a problem, developing a strategy to solve it, implementing the strategy, and then evaluating the results.

Identifying the problem: The first step in the problem solving cycle is identifying the problem at hand. This may involve defining the problem, gathering information and relevant data, and understanding the desired outcome.

Developing a strategy: Once the problem is identified, individuals must develop a strategy or plan of action to solve it. This may involve brainstorming ideas, evaluating potential solutions, and selecting the best approach.

Implementing the strategy: After a strategy is developed, it must be put into action. This may involve executing specific steps, utilizing resources, and adjusting the strategy as needed.

Evaluating the results: The final step in the problem solving cycle is evaluating the results of the implemented strategy. This may involve assessing the effectiveness of the solution, determining if the desired outcome was achieved, and making any necessary adjustments or improvements.

The Role of Cognitive Psychology

Cognitive psychology plays a crucial role in understanding the problem solving process. It focuses on how individuals perceive, think, and reason about problems, as well as the various strategies and mental processes involved in solving them.

Research in cognitive psychology has shown that problem solving is not purely a linear process, but rather a dynamic and iterative cycle. Individuals may iterate through the different stages of the problem solving cycle multiple times as they encounter new information or face unexpected challenges.

The study of problem solving in cognitive psychology has led to the development of various theories and models, such as the Gestalt theory, which emphasizes the importance of insight and reorganizing information, and the information processing model, which highlights the role of attention, memory, and decision-making in problem solving.

The Importance of Problem Solving Skills

Problem solving is a key concept in cognitive psychology. It is a process that involves identifying, analyzing, and coming up with solutions to problems. Problem solving skills are essential in various aspects of life, including personal and professional contexts.

Mastering problem solving skills enables individuals to tackle challenges and overcome obstacles effectively. It helps in critical thinking, decision making, and finding innovative solutions. Problem solving skills are also important in the field of psychology, as they are often used to understand and address complex psychological issues.

Enhancing Cognitive Abilities

Problem solving activities stimulate and enhance cognitive abilities. They require individuals to think critically, analyze information, and use logical reasoning. By engaging in problem solving, individuals improve their cognitive processes, such as memory, attention, and problem representation.

Building Resilience

Developing problem solving skills also helps in building resilience. It teaches individuals to approach challenges with a proactive mindset and seek solutions rather than giving up. This resilience can be applied in various aspects of life, including personal relationships, work, and education.

In conclusion, problem solving skills play a crucial role in cognitive psychology and various aspects of life. They enhance cognitive abilities, promote critical thinking, and build resilience. Developing and honing problem solving skills is essential for personal growth and success in today’s complex world.

The Four Stages of Problem Solving

Problem solving is a cognitive process that involves the use of mental processes to find a solution to a problem. It is a cycle that is often studied in cognitive psychology. The problem solving cycle consists of four stages, which are:

1. Understanding the Problem

In this stage, the individual must first understand and define the problem. This involves gathering information, analyzing the problem, and identifying the key elements that need to be addressed. It is important to have a clear understanding of the problem before moving on to the next stage.

2. Generating Potential Solutions

Once the problem is understood, the next stage involves generating potential solutions. This requires using both logical and creative thinking to come up with possible ways to solve the problem. It is important to consider different perspectives and explore a variety of options.

3. Evaluating and Selecting Solutions

After generating potential solutions, the individual must evaluate and select the most appropriate solution. This involves weighing the pros and cons of each potential solution and considering factors such as feasibility, effectiveness, and practicality. The goal is to select a solution that is likely to lead to the desired outcome.

4. Implementing and Evaluating the Solution

Once a solution has been selected, the final stage involves implementing the solution and evaluating its effectiveness. This may involve taking action, making changes, and monitoring the results. It is important to assess whether the solution has solved the problem and to make adjustments if needed.

In conclusion, problem solving is a cognitive process that involves four stages: understanding the problem, generating potential solutions, evaluating and selecting solutions, and implementing and evaluating the solution. By following this problem solving cycle, individuals can effectively approach and solve a wide range of problems.

Identifying the Problem

The first step in the problem solving cycle is identifying the problem. In cognitive psychology, this step involves recognizing that there is a problem to be solved and understanding what it entails.

When identifying a problem, it is important to clearly define and articulate what the issue is. This can involve breaking the problem down into smaller components or examining the factors that contribute to the problem.

Factors to consider when identifying a problem:

• What is the desired outcome or goal?
• What are the obstacles or challenges that need to be overcome?
• What are the potential causes or explanations for the problem?

Identifying the problem involves gathering information and analyzing it to gain a better understanding of the situation. This can include conducting research, gathering data, or seeking input from others who may have expertise or experience in the area.

Once the problem has been clearly identified, it can then be approached using the problem solving cycle. By breaking down the problem into smaller steps and systematically working through each one, individuals can increase their chances of finding an effective solution.

Defining the Problem

Defining the problem is a crucial step in the problem-solving cycle. In the context of cognitive psychology, a problem can be defined as a situation or task that requires a solution. This could be a complex mathematical equation, a riddle, or a real-life challenge. The process of defining the problem involves clarifying the specific requirements or constraints of the situation and understanding what needs to be solved. By clearly defining the problem, it becomes easier to identify potential strategies and solutions.

When defining a problem, it is important to consider both the immediate and underlying issues. Often, the surface-level problem may not be the root cause, and addressing only the symptoms may not lead to a satisfactory solution. Therefore, it is essential to dig deeper and identify the underlying factors that contribute to the problem.

Clarifying the requirements

One aspect of defining the problem is clarifying the specific requirements or constraints that need to be considered. These requirements can include the desired outcome, the available resources, the time frame, and any limitations or restrictions. By understanding these requirements, it becomes easier to focus on finding a solution that meets the given criteria.

Understanding the problem space

Another important aspect of defining the problem is understanding the problem space. The problem space refers to the set of all possible solutions and strategies that can be explored to solve the problem. By understanding the problem space, individuals can develop a clearer understanding of the scope of the problem and the potential avenues for finding a solution.

Generating Solution Options

In cognitive psychology, problem solving is a key concept that explores how individuals go about finding solutions to problems. One important aspect of the problem solving cycle is generating solution options.

When faced with a problem, individuals engage in cognitive processes to come up with potential solutions. This often involves brainstorming, where individuals generate a list of possible options.

There are various strategies that individuals can use to generate solution options. One common approach is divergent thinking, which involves thinking creatively and generating a large number of potential solutions. This can be done by considering different perspectives, exploring alternative possibilities, and challenging assumptions.

Another strategy is convergent thinking, which involves evaluating and narrowing down the potential solutions. This can be done by considering the feasibility and practicality of each option, as well as weighing the potential risks and benefits.

It is important for individuals to consider a wide range of solution options, as this increases the likelihood of finding an effective solution. This can be achieved by using techniques such as mind mapping, where individuals visually organize their thoughts and ideas to generate new connections and possibilities.

By generating a variety of solution options, individuals can increase their chances of finding the most suitable and effective solution to a problem. This stage of the problem solving cycle is crucial in the overall problem solving process.

Evaluating and Selecting the Best Solution

Once you have gone through the problem solving cycle and generated potential solutions, the next step is to evaluate and select the best solution. This is an essential part of the problem solving process, as it involves critically analyzing each potential solution and determining which one is the most effective and feasible.

When evaluating potential solutions, it is important to consider various factors. One key factor is the effectiveness of each solution in actually solving the problem at hand. Will the solution address the root cause of the problem, or just temporarily alleviate the symptoms?

In addition to effectiveness, it is also important to consider the feasibility of each solution. Is the solution realistic and practical to implement? Does it require significant resources or time that may not be available? These are all important considerations to take into account when evaluating potential solutions.

Furthermore, it is important to consider the potential consequences of each solution. Will the solution create any new problems or unintended side effects? Will it have any negative impacts on other areas or stakeholders? These potential consequences must be carefully considered before making a final decision.

Finally, it is important to approach the evaluation process with an open and flexible mindset. It is not uncommon for new information or perspectives to emerge during the evaluation process, which may alter the assessment of potential solutions. Remaining open to new information and being willing to adapt the evaluation criteria is crucial in selecting the best solution.

By carefully evaluating each potential solution and considering factors such as effectiveness, feasibility, and potential consequences, you can effectively select the best solution to the problem at hand. This is an essential step in the problem solving cycle, as it moves you closer to a successful resolution.

Implementing the Solution

Once the problem-solving cycle has been completed in cognitive psychology, the next step is to implement the solution. This phase involves taking the proposed solution and putting it into action.

Before implementation, it is crucial to evaluate the solution thoroughly. This evaluation helps ensure that the proposed solution is practical and feasible.

Evaluating the Solution

The evaluation process involves considering possible obstacles and risks that could hinder the successful implementation of the solution. By identifying these potential challenges, steps can be taken to mitigate them.

In addition, evaluating the solution also involves conducting a cost-benefit analysis. This analysis takes into account the potential costs and benefits associated with implementing the solution. It helps determine whether the solution is worth pursuing.

Putting the Solution into Action

Once the solution has been thoroughly evaluated, it is time to put it into action. This requires careful planning and coordination.

During the implementation phase, it is important to closely monitor the progress and make any necessary adjustments. This ensures that the solution is effectively addressing the problem at hand.

Furthermore, clear communication is vital during implementation. All relevant stakeholders should be informed and involved in the process to ensure everyone is working towards a common goal.

By implementing the solution effectively, the problem-solving cycle in cognitive psychology can come to a successful conclusion.

Monitoring and Evaluating the Outcome

Monitoring and evaluating the outcome is a crucial step in the problem-solving process in cognitive psychology. After identifying and implementing a solution, it is important to assess whether the problem has been effectively solved and whether the desired outcome has been achieved.

Evaluating the Effectiveness of the Solution

One way to monitor and evaluate the outcome is to assess the effectiveness of the solution. This involves determining whether the chosen solution has successfully addressed the problem and whether it has led to the desired result. Cognitive psychologists often use various measures and metrics to evaluate the effectiveness of problem-solving strategies. These may include objective measures such as test scores or subjective measures such as self-report questionnaires.

By evaluating the effectiveness of the solution, cognitive psychologists can determine whether further adjustments or modifications are necessary. If the outcome is not satisfactory, they can go back to the problem-solving cycle and repeat the steps to find a more suitable solution.

Reflecting on the Process

In addition to evaluating the effectiveness of the solution, it is also important to reflect on the problem-solving process itself. This involves considering the strategies and techniques used, as well as identifying any obstacles or challenges encountered. By reflecting on the process, cognitive psychologists can gain valuable insights into how they approached the problem and how they can improve their problem-solving skills in the future.

Reflection can be done through self-reflection or by seeking feedback from others, such as colleagues or experts in the field. This feedback can provide alternative perspectives and help identify areas for improvement.

In conclusion, monitoring and evaluating the outcome is a critical aspect of the problem-solving cycle in cognitive psychology. By assessing the effectiveness of the solution and reflecting on the process, cognitive psychologists can continually improve their problem-solving skills and contribute to the development of this field.

The Role of Cognitive Processes in Problem Solving

In the field of cognitive psychology, problem solving is a fundamental aspect of human thinking. It involves the use of various cognitive processes to analyze a problem, develop possible solutions, and determine the best course of action.

One key cognitive process involved in problem solving is perception. This process allows individuals to perceive and understand the problem at hand, by gathering information from the environment and organizing it into meaningful patterns. Perception helps identify the relevant aspects of a problem and guides the problem-solving process.

Another important cognitive process in problem solving is reasoning. Reasoning involves logical thinking and the ability to draw conclusions based on available information. It helps individuals make sense of the problem and generate possible solutions. Reasoning also helps evaluate the potential outcomes of each solution and select the most appropriate one.

Memory plays a crucial role in problem solving as well. It allows individuals to recall relevant information from past experiences and apply it to the current problem. Memory aids in recognizing patterns, generating hypotheses, and retrieving information necessary for problem solving. Without memory, it would be challenging to solve problems efficiently.

Moreover, attention and concentration are essential cognitive processes in problem solving. They help individuals focus on the relevant aspects of a problem and block out distractions. Attention allows individuals to allocate cognitive resources effectively and process information in a systematic manner. Concentration enables individuals to stay engaged in problem solving and persevere until a solution is found.

The role of cognitive processes in problem solving is vital as they provide the framework for effective problem-solving strategies. Understanding how perception, reasoning, memory, attention, and concentration contribute to problem solving helps researchers and practitioners develop interventions and techniques to improve problem-solving skills.

In conclusion, cognitive processes are crucial in problem solving. Perception, reasoning, memory, attention, and concentration work together to help individuals analyze problems, generate solutions, and make informed decisions. By studying and understanding these cognitive processes, researchers can enhance problem-solving abilities, ultimately leading to more effective problem-solving strategies in various fields of study and practice.

How Cognitive Biases can Impact Problem Solving

Cognitive biases are inherent tendencies in human thinking that can lead to errors or deviations from rationality. These biases can have a significant impact on problem solving, as they can influence the way individuals perceive, interpret, and evaluate information.

Confirmation Bias

One common cognitive bias that can affect problem solving is confirmation bias. This bias leads individuals to favor information that confirms their existing beliefs or hypotheses while disregarding or downplaying information that contradicts them. In problem-solving scenarios, confirmation bias can prevent individuals from considering alternative solutions or exploring different perspectives, potentially leading to a less effective problem-solving process.

Availability Heuristic

The availability heuristic is another cognitive bias that can impact problem solving. This bias involves relying on easily accessible information or examples when making judgments or decisions. In problem-solving situations, this bias can lead individuals to overlook less accessible information or fail to consider all relevant factors. This can limit the effectiveness of problem solving by restricting the range of potential solutions or failing to consider alternative approaches.

• Overcoming cognitive biases in problem solving

Recognizing and overcoming cognitive biases is crucial for effective problem solving. Strategies such as actively seeking out diverse perspectives, questioning assumptions, and considering alternative explanations can help mitigate the impact of cognitive biases. Additionally, fostering an environment that encourages open-mindedness, critical thinking, and intellectual humility can also support more effective problem-solving processes.

By understanding how cognitive biases can impact problem solving, psychologists and individuals alike can work towards improving their problem-solving skills and decision-making processes. By recognizing and addressing these biases, individuals can enhance their ability to approach problems with greater objectivity, flexibility, and creativity.

The Relationship Between Problem Solving and Decision Making

Problem solving and decision making are closely interconnected in cognitive psychology. When faced with a problem, individuals engage in a cognitive process known as problem solving, which involves identifying and evaluating possible solutions in order to reach a desired goal or outcome. Decision making, on the other hand, refers to the act of choosing one particular solution from the options generated during the problem-solving process.

The problem-solving cycle, a key concept in cognitive psychology, highlights the iterative nature of problem solving and decision making. This cycle consists of several steps, including problem identification, problem analysis, solution generation, solution evaluation, and solution implementation. During the problem identification phase, individuals recognize and define the problem they are facing. Problem analysis involves gathering information and analyzing the underlying causes and factors contributing to the problem. Once a thorough analysis is conducted, individuals can generate potential solutions through creative thinking and brainstorming.

After generating potential solutions, individuals must evaluate the effectiveness and feasibility of each option. This involves considering the potential consequences and weighing the pros and cons of each alternative. By carefully assessing each solution, individuals can make an informed decision and choose the most suitable course of action. Finally, the chosen solution is implemented, and individuals monitor the outcomes to determine whether the problem has been effectively resolved.

It is important to note that problem solving and decision making are not linear processes, but rather they involve feedback loops and revisions as new information becomes available or as the initial solution proves to be ineffective. Successful problem solving and decision making require flexibility, critical thinking, and adaptability to changing circumstances.

In summary, problem solving and decision making are intertwined cognitive processes within the problem-solving cycle. Problem solving involves identifying and evaluating possible solutions, while decision making involves choosing the most appropriate solution. By understanding the relationship between problem solving and decision making, individuals can enhance their problem-solving skills and make more effective decisions in various aspects of life and work.

The Effect of Expertise on Problem Solving

In the cognitive psychology field, the problem solving cycle is a key concept that involves several stages: understanding the problem, devising a plan, executing the plan, and evaluating the solution. An important factor that can influence problem solving abilities is expertise.

Experts, who have extensive knowledge and experience in a specific domain, often exhibit superior problem solving skills compared to novices. This is because experts have a large mental database of problem-solving strategies and a deep understanding of the underlying concepts. They can quickly recognize patterns and make accurate decisions based on their knowledge.

Research has shown that experts are able to solve problems more efficiently and effectively than novices. They are able to quickly identify the relevant information and ignore irrelevant details, which allows them to focus on the core of the problem. Experts also have a better ability to generate and evaluate multiple potential solutions, leading to more creative problem solving.

Furthermore, experts are more likely to use metacognitive strategies, such as self-monitoring and self-regulation, during the problem solving process. They are able to reflect on their own thinking and adjust their strategies as needed. This metacognitive awareness helps experts to overcome obstacles and adapt their problem solving approach as necessary.

However, it is important to note that expertise is domain-specific. An individual may be an expert in one area but not in another. For example, a chess grandmaster may struggle with solving complex math problems. Therefore, expertise does not guarantee proficiency in all problem-solving domains.

In conclusion, expertise plays a significant role in problem solving. Experts have a deeper understanding of the problem domain, possess a larger repertoire of strategies, and exhibit metacognitive awareness. These factors contribute to their more efficient and effective problem solving abilities compared to novices.

Developing Problem Solving Skills through Practice

In the field of psychology, problem solving is considered an essential cognitive skill that helps individuals navigate through various challenges and obstacles. The problem solving cycle, a key concept in cognitive psychology, emphasizes the importance of practice in developing and honing problem solving skills.

Practice plays a crucial role in problem solving as it helps individuals familiarize themselves with different problem-solving techniques and strategies. By engaging in regular practice, individuals can strengthen their analytical thinking, creative problem solving, and decision-making abilities.

Through practice, individuals learn to approach problems systematically, breaking down complex tasks into smaller, more manageable steps. This systematic approach allows individuals to identify the root causes of a problem, generate potential solutions, and evaluate the effectiveness of each solution.

In addition to improving analytical thinking, practice also helps individuals develop their creative problem solving skills. By repeatedly facing various problems, individuals become more comfortable with thinking outside the box and exploring unconventional solutions. This creative thinking enables individuals to come up with innovative and effective solutions to complex problems.

Moreover, practice enhances individuals’ decision-making abilities. As individuals engage in problem solving practice, they become more skilled at assessing different options, weighing the pros and cons, and making informed decisions. This ability to make sound decisions is crucial in both personal and professional contexts.

In conclusion, developing problem solving skills requires consistent practice. By engaging in regular problem solving practice, individuals can improve their analytical thinking, creative problem solving, and decision-making abilities. The problem solving cycle emphasizes the importance of practice in developing these skills, and individuals who actively engage in practice are more likely to become adept problem solvers.

Teaching Problem Solving Skills in Education

Problem solving skills are an essential component of education, as they enable students to analyze and tackle complex issues across various subject areas. By teaching problem solving skills, educators help students develop critical thinking abilities and cognitive strategies that can be applied in real-life situations.

The Problem Solving Cycle

One effective approach to teaching problem solving skills is through the use of the problem solving cycle. The problem solving cycle is a key concept in cognitive psychology, which involves a systematic approach to identifying, analyzing, and resolving problems.

First, students are introduced to a problem or a question that requires analysis and solution. They are encouraged to define the problem clearly and understand its scope. This initial step helps students develop problem awareness and identify potential barriers or constraints that may affect the problem-solving process.

Next, students engage in information gathering and analysis. They gather relevant data, facts, and evidence, and apply critical thinking skills to evaluate and interpret the information. This step helps students develop analytical skills and generate possible solutions.

Once students have gathered and analyzed the information, they move on to the generation of potential solutions. This involves brainstorming and exploring different approaches to the problem, encouraging creativity and flexibility in thinking. Students are encouraged to think outside the box and consider multiple perspectives.

After generating potential solutions, students evaluate each option based on effectiveness, feasibility, and potential consequences. They consider the advantages and disadvantages of each solution, weighing the pros and cons. This step helps students develop decision-making skills and enhances their ability to critically evaluate potential solutions.

Finally, students select the most appropriate solution and implement it. They develop an action plan, outlining the steps needed to solve the problem. This requires effective communication skills, as students may need to collaborate and communicate their ideas with others.

Benefits of Teaching Problem Solving Skills

Teaching problem solving skills in education offers numerous benefits to students. Firstly, it enhances their cognitive abilities, allowing them to think critically and logically. This helps students become more independent learners and problem solvers.

Additionally, teaching problem solving skills improves students’ creativity and innovation. By encouraging them to think outside the box and explore different solutions, educators foster a mindset of curiosity and exploration.

Moreover, problem solving skills are transferable to various contexts, both within and outside of the classroom. Students can apply these skills to academic subjects, as well as to real-life situations, such as social issues, personal challenges, and future career paths.

In conclusion, teaching problem solving skills in education is crucial for students’ cognitive development and future success. By implementing the problem solving cycle and fostering critical thinking abilities, educators empower students with the skills necessary to navigate complex challenges and become lifelong learners.

Real-World Applications of the Problem Solving Cycle

The problem solving cycle is a fundamental concept in cognitive psychology that has numerous applications in real-world situations. This cycle involves a series of steps that individuals go through in order to identify, analyze, and solve problems.

1. Business

In the business world, problem solving is essential for success. From identifying market trends and determining customer needs to finding solutions to production issues or administrative challenges, the problem solving cycle is used to tackle a variety of business-related problems.

2. Education

The problem solving cycle is also highly applicable in education. Teachers often use this approach to help students develop critical thinking skills and solve complex problems. By following this cycle, students learn to break down problems, gather relevant information, analyze various options, and come up with effective solutions.

3. Medicine

Medical professionals frequently employ the problem solving cycle when diagnosing and treating patients. By systematically gathering patient history, evaluating symptoms, conducting tests, and analyzing data, doctors are able to identify the underlying problem and develop appropriate treatment plans.

4. Engineering

In the field of engineering, the problem solving cycle is crucial for designing and implementing solutions. Engineers use this approach to identify and address technical challenges, improve existing systems, and develop innovative technologies. By following this cycle, engineers can efficiently solve complex problems and ensure the success of their projects.

5. Everyday Life

Lastly, the problem solving cycle is applicable to everyday life. Whether it’s figuring out the best route to work, resolving conflicts in relationships, or making important decisions, individuals use this cycle to identify issues, explore possible solutions, and make informed choices.

The problem solving cycle is a versatile concept that finds widespread applications in various domains. From business and education to medicine and engineering, this approach facilitates effective problem solving and decision making. By following the steps of the cycle, individuals and organizations can overcome challenges and achieve their goals.

The Future of Problem Solving Research

In the field of cognitive psychology, research on problem solving is an ongoing and dynamic area of study. As technology continues to advance and our understanding of the cognitive processes involved in problem solving deepens, the future of problem solving research looks promising.

Advancements in Technology

Advancements in technology have already had a significant impact on problem solving research. The use of computer simulations and virtual environments has allowed researchers to create realistic problem-solving scenarios and collect data in a controlled environment. This technology has also allowed for the development of intelligent tutoring systems that can provide personalized feedback and guidance to individuals as they work through various problem-solving tasks.

In the future, we can expect even more sophisticated technologies to be developed, which will enhance our ability to study problem solving. For example, virtual reality technology may allow researchers to create immersive problem-solving environments that closely mimic real-life situations. This could provide researchers with valuable insights into how individuals approach and solve complex problems in a realistic setting.

Integration of Cognitive Processes

As our understanding of cognitive processes continues to grow, future research on problem solving will likely focus on the integration of various cognitive processes. Problem solving is a complex task that involves numerous cognitive processes, such as attention, memory, decision-making, and reasoning. Understanding how these processes interact and influence problem-solving performance will be crucial in developing effective strategies for problem solving.

Researchers may also explore the role of emotions in problem solving. Emotions can have a significant impact on cognitive processes and decision-making. Understanding how emotions influence problem-solving performance may provide valuable insights into how individuals can improve their problem-solving abilities.

Collaborative Problem Solving

Collaborative problem solving, or problem solving in a group setting, is another area that holds great potential for future research. Many real-world problems require collaboration and teamwork to solve effectively. Research on collaborative problem solving can provide valuable insights into how individuals interact and communicate with each other during problem-solving tasks, and how team dynamics impact problem-solving performance.

Furthermore, advancements in communication technology have made it easier than ever for individuals to collaborate remotely. Studying how individuals solve problems in virtual teams or online communities can provide valuable insights into the dynamics of collaborative problem solving in today’s interconnected world.

Continued Development of the Problem Solving Cycle

The problem solving cycle, which involves the stages of problem identification, solution generation, solution implementation, and solution evaluation, will continue to be a key concept in problem solving research. Researchers will seek to understand how individuals move through these stages, the strategies they employ at each stage, and how their problem-solving performance can be optimized.

By understanding the cognitive processes involved in each stage of the problem solving cycle, researchers can develop interventions and strategies to help individuals become more effective problem solvers.

In conclusion, the future of problem solving research in cognitive psychology looks promising. Advancements in technology, a deeper understanding of cognitive processes, the study of collaborative problem solving, and the continued development of the problem solving cycle will all contribute to our understanding of problem solving and help individuals become more effective in solving complex problems.

Questions and answers:

What is the problem-solving cycle.

The problem-solving cycle is a key concept in cognitive psychology that refers to the sequence of steps or processes involved in solving a problem.

What are the stages of the problem-solving cycle?

The problem-solving cycle typically consists of four stages: problem identification, problem definition, strategy selection, and solution implementation.

How does problem identification occur in the problem-solving cycle?

Problem identification involves recognizing that there is a problem or a discrepancy between a desired state and the current state.

What is problem definition in the problem-solving cycle?

Problem definition involves clearly specifying or defining the problem in a way that allows for a focused approach to finding a solution.

What is strategy selection in the problem-solving cycle?

Strategy selection involves choosing an appropriate approach or method to solve the problem, such as using a specific algorithm or heuristic.

What is the problem-solving cycle in cognitive psychology?

The problem-solving cycle is a concept in cognitive psychology that outlines the steps individuals go through when tackling a problem. It involves identifying the problem, gathering information, generating possible solutions, evaluating the solutions, and implementing the best one.

How does the problem-solving cycle help in problem-solving?

The problem-solving cycle provides a structured approach to problem-solving by breaking it down into manageable steps. By following this cycle, individuals can better understand the problem, explore various solutions, evaluate their effectiveness, and ultimately make an informed decision on how to solve the problem.

Related posts:

• A Comprehensive Guide to the Problem Solving Cycle in Psychology – Strategies, Techniques, and Applications
• The Importance of Implementing the Problem Solving Cycle in Education to Foster Critical Thinking and Problem-Solving Skills in Students
• The Step-by-Step Problem Solving Cycle for Effective Solutions
• The Comprehensive Guide to the Problem Solving Cycle in PDF Format
• The Importance of the Problem Solving Cycle in Business Studies – Strategies for Success
• A Comprehensive Guide on the Problem Solving Cycle – Step-by-Step Approach with Real-Life Example
• The Seven Essential Steps of the Problem Solving Cycle
• Exploring the Problem Solving Cycle in Computer Science – Strategies, Techniques, and Tools

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7 Module 7: Thinking, Reasoning, and Problem-Solving

This module is about how a solid working knowledge of psychological principles can help you to think more effectively, so you can succeed in school and life. You might be inclined to believe that—because you have been thinking for as long as you can remember, because you are able to figure out the solution to many problems, because you feel capable of using logic to argue a point, because you can evaluate whether the things you read and hear make sense—you do not need any special training in thinking. But this, of course, is one of the key barriers to helping people think better. If you do not believe that there is anything wrong, why try to fix it?

The human brain is indeed a remarkable thinking machine, capable of amazing, complex, creative, logical thoughts. Why, then, are we telling you that you need to learn how to think? Mainly because one major lesson from cognitive psychology is that these capabilities of the human brain are relatively infrequently realized. Many psychologists believe that people are essentially “cognitive misers.” It is not that we are lazy, but that we have a tendency to expend the least amount of mental effort necessary. Although you may not realize it, it actually takes a great deal of energy to think. Careful, deliberative reasoning and critical thinking are very difficult. Because we seem to be successful without going to the trouble of using these skills well, it feels unnecessary to develop them. As you shall see, however, there are many pitfalls in the cognitive processes described in this module. When people do not devote extra effort to learning and improving reasoning, problem solving, and critical thinking skills, they make many errors.

As is true for memory, if you develop the cognitive skills presented in this module, you will be more successful in school. It is important that you realize, however, that these skills will help you far beyond school, even more so than a good memory will. Although it is somewhat useful to have a good memory, ten years from now no potential employer will care how many questions you got right on multiple choice exams during college. All of them will, however, recognize whether you are a logical, analytical, critical thinker. With these thinking skills, you will be an effective, persuasive communicator and an excellent problem solver.

The module begins by describing different kinds of thought and knowledge, especially conceptual knowledge and critical thinking. An understanding of these differences will be valuable as you progress through school and encounter different assignments that require you to tap into different kinds of knowledge. The second section covers deductive and inductive reasoning, which are processes we use to construct and evaluate strong arguments. They are essential skills to have whenever you are trying to persuade someone (including yourself) of some point, or to respond to someone’s efforts to persuade you. The module ends with a section about problem solving. A solid understanding of the key processes involved in problem solving will help you to handle many daily challenges.

7.1. Different kinds of thought

7.2. Reasoning and Judgment

7.3. Problem Solving

READING WITH PURPOSE

Remember and understand.

By reading and studying Module 7, you should be able to remember and describe:

• Concepts and inferences (7.1)
• Procedural knowledge (7.1)
• Metacognition (7.1)
• Characteristics of critical thinking:  skepticism; identify biases, distortions, omissions, and assumptions; reasoning and problem solving skills  (7.1)
• Reasoning:  deductive reasoning, deductively valid argument, inductive reasoning, inductively strong argument, availability heuristic, representativeness heuristic  (7.2)
• Fixation:  functional fixedness, mental set  (7.3)
• Algorithms, heuristics, and the role of confirmation bias (7.3)
• Effective problem solving sequence (7.3)

By reading and thinking about how the concepts in Module 6 apply to real life, you should be able to:

• Identify which type of knowledge a piece of information is (7.1)
• Recognize examples of deductive and inductive reasoning (7.2)
• Recognize judgments that have probably been influenced by the availability heuristic (7.2)
• Recognize examples of problem solving heuristics and algorithms (7.3)

Analyze, Evaluate, and Create

By reading and thinking about Module 6, participating in classroom activities, and completing out-of-class assignments, you should be able to:

• Use the principles of critical thinking to evaluate information (7.1)
• Explain whether examples of reasoning arguments are deductively valid or inductively strong (7.2)
• Outline how you could try to solve a problem from your life using the effective problem solving sequence (7.3)

7.1. Different kinds of thought and knowledge

• Take a few minutes to write down everything that you know about dogs.
• Do you believe that:
• Psychic ability exists?
• Hypnosis is an altered state of consciousness?
• Magnet therapy is effective for relieving pain?
• Aerobic exercise is an effective treatment for depression?
• UFO’s from outer space have visited earth?

On what do you base your belief or disbelief for the questions above?

Of course, we all know what is meant by the words  think  and  knowledge . You probably also realize that they are not unitary concepts; there are different kinds of thought and knowledge. In this section, let us look at some of these differences. If you are familiar with these different kinds of thought and pay attention to them in your classes, it will help you to focus on the right goals, learn more effectively, and succeed in school. Different assignments and requirements in school call on you to use different kinds of knowledge or thought, so it will be very helpful for you to learn to recognize them (Anderson, et al. 2001).

Factual and conceptual knowledge

Module 5 introduced the idea of declarative memory, which is composed of facts and episodes. If you have ever played a trivia game or watched Jeopardy on TV, you realize that the human brain is able to hold an extraordinary number of facts. Likewise, you realize that each of us has an enormous store of episodes, essentially facts about events that happened in our own lives. It may be difficult to keep that in mind when we are struggling to retrieve one of those facts while taking an exam, however. Part of the problem is that, in contradiction to the advice from Module 5, many students continue to try to memorize course material as a series of unrelated facts (picture a history student simply trying to memorize history as a set of unrelated dates without any coherent story tying them together). Facts in the real world are not random and unorganized, however. It is the way that they are organized that constitutes a second key kind of knowledge, conceptual.

Concepts are nothing more than our mental representations of categories of things in the world. For example, think about dogs. When you do this, you might remember specific facts about dogs, such as they have fur and they bark. You may also recall dogs that you have encountered and picture them in your mind. All of this information (and more) makes up your concept of dog. You can have concepts of simple categories (e.g., triangle), complex categories (e.g., small dogs that sleep all day, eat out of the garbage, and bark at leaves), kinds of people (e.g., psychology professors), events (e.g., birthday parties), and abstract ideas (e.g., justice). Gregory Murphy (2002) refers to concepts as the “glue that holds our mental life together” (p. 1). Very simply, summarizing the world by using concepts is one of the most important cognitive tasks that we do. Our conceptual knowledge  is  our knowledge about the world. Individual concepts are related to each other to form a rich interconnected network of knowledge. For example, think about how the following concepts might be related to each other: dog, pet, play, Frisbee, chew toy, shoe. Or, of more obvious use to you now, how these concepts are related: working memory, long-term memory, declarative memory, procedural memory, and rehearsal? Because our minds have a natural tendency to organize information conceptually, when students try to remember course material as isolated facts, they are working against their strengths.

One last important point about concepts is that they allow you to instantly know a great deal of information about something. For example, if someone hands you a small red object and says, “here is an apple,” they do not have to tell you, “it is something you can eat.” You already know that you can eat it because it is true by virtue of the fact that the object is an apple; this is called drawing an  inference , assuming that something is true on the basis of your previous knowledge (for example, of category membership or of how the world works) or logical reasoning.

Procedural knowledge

Physical skills, such as tying your shoes, doing a cartwheel, and driving a car (or doing all three at the same time, but don’t try this at home) are certainly a kind of knowledge. They are procedural knowledge, the same idea as procedural memory that you saw in Module 5. Mental skills, such as reading, debating, and planning a psychology experiment, are procedural knowledge, as well. In short, procedural knowledge is the knowledge how to do something (Cohen & Eichenbaum, 1993).

Metacognitive knowledge

Floyd used to think that he had a great memory. Now, he has a better memory. Why? Because he finally realized that his memory was not as great as he once thought it was. Because Floyd eventually learned that he often forgets where he put things, he finally developed the habit of putting things in the same place. (Unfortunately, he did not learn this lesson before losing at least 5 watches and a wedding ring.) Because he finally realized that he often forgets to do things, he finally started using the To Do list app on his phone. And so on. Floyd’s insights about the real limitations of his memory have allowed him to remember things that he used to forget.

All of us have knowledge about the way our own minds work. You may know that you have a good memory for people’s names and a poor memory for math formulas. Someone else might realize that they have difficulty remembering to do things, like stopping at the store on the way home. Others still know that they tend to overlook details. This knowledge about our own thinking is actually quite important; it is called metacognitive knowledge, or  metacognition . Like other kinds of thinking skills, it is subject to error. For example, in unpublished research, one of the authors surveyed about 120 General Psychology students on the first day of the term. Among other questions, the students were asked them to predict their grade in the class and report their current Grade Point Average. Two-thirds of the students predicted that their grade in the course would be higher than their GPA. (The reality is that at our college, students tend to earn lower grades in psychology than their overall GPA.) Another example: Students routinely report that they thought they had done well on an exam, only to discover, to their dismay, that they were wrong (more on that important problem in a moment). Both errors reveal a breakdown in metacognition.

The Dunning-Kruger Effect

In general, most college students probably do not study enough. For example, using data from the National Survey of Student Engagement, Fosnacht, McCormack, and Lerma (2018) reported that first-year students at 4-year colleges in the U.S. averaged less than 14 hours per week preparing for classes. The typical suggestion is that you should spend two hours outside of class for every hour in class, or 24 – 30 hours per week for a full-time student. Clearly, students in general are nowhere near that recommended mark. Many observers, including some faculty, believe that this shortfall is a result of students being too busy or lazy. Now, it may be true that many students are too busy, with work and family obligations, for example. Others, are not particularly motivated in school, and therefore might correctly be labeled lazy. A third possible explanation, however, is that some students might not think they need to spend this much time. And this is a matter of metacognition. Consider the scenario that we mentioned above, students thinking they had done well on an exam only to discover that they did not. Justin Kruger and David Dunning examined scenarios very much like this in 1999. Kruger and Dunning gave research participants tests measuring humor, logic, and grammar. Then, they asked the participants to assess their own abilities and test performance in these areas. They found that participants in general tended to overestimate their abilities, already a problem with metacognition. Importantly, the participants who scored the lowest overestimated their abilities the most. Specifically, students who scored in the bottom quarter (averaging in the 12th percentile) thought they had scored in the 62nd percentile. This has become known as the  Dunning-Kruger effect . Many individual faculty members have replicated these results with their own student on their course exams, including the authors of this book. Think about it. Some students who just took an exam and performed poorly believe that they did well before seeing their score. It seems very likely that these are the very same students who stopped studying the night before because they thought they were “done.” Quite simply, it is not just that they did not know the material. They did not know that they did not know the material. That is poor metacognition.

In order to develop good metacognitive skills, you should continually monitor your thinking and seek frequent feedback on the accuracy of your thinking (Medina, Castleberry, & Persky 2017). For example, in classes get in the habit of predicting your exam grades. As soon as possible after taking an exam, try to find out which questions you missed and try to figure out why. If you do this soon enough, you may be able to recall the way it felt when you originally answered the question. Did you feel confident that you had answered the question correctly? Then you have just discovered an opportunity to improve your metacognition. Be on the lookout for that feeling and respond with caution.

concept :  a mental representation of a category of things in the world

Dunning-Kruger effect : individuals who are less competent tend to overestimate their abilities more than individuals who are more competent do

inference : an assumption about the truth of something that is not stated. Inferences come from our prior knowledge and experience, and from logical reasoning

metacognition :  knowledge about one’s own cognitive processes; thinking about your thinking

Critical thinking

One particular kind of knowledge or thinking skill that is related to metacognition is  critical thinking (Chew, 2020). You may have noticed that critical thinking is an objective in many college courses, and thus it could be a legitimate topic to cover in nearly any college course. It is particularly appropriate in psychology, however. As the science of (behavior and) mental processes, psychology is obviously well suited to be the discipline through which you should be introduced to this important way of thinking.

More importantly, there is a particular need to use critical thinking in psychology. We are all, in a way, experts in human behavior and mental processes, having engaged in them literally since birth. Thus, perhaps more than in any other class, students typically approach psychology with very clear ideas and opinions about its subject matter. That is, students already “know” a lot about psychology. The problem is, “it ain’t so much the things we don’t know that get us into trouble. It’s the things we know that just ain’t so” (Ward, quoted in Gilovich 1991). Indeed, many of students’ preconceptions about psychology are just plain wrong. Randolph Smith (2002) wrote a book about critical thinking in psychology called  Challenging Your Preconceptions,  highlighting this fact. On the other hand, many of students’ preconceptions about psychology are just plain right! But wait, how do you know which of your preconceptions are right and which are wrong? And when you come across a research finding or theory in this class that contradicts your preconceptions, what will you do? Will you stick to your original idea, discounting the information from the class? Will you immediately change your mind? Critical thinking can help us sort through this confusing mess.

But what is critical thinking? The goal of critical thinking is simple to state (but extraordinarily difficult to achieve): it is to be right, to draw the correct conclusions, to believe in things that are true and to disbelieve things that are false. We will provide two definitions of critical thinking (or, if you like, one large definition with two distinct parts). First, a more conceptual one: Critical thinking is thinking like a scientist in your everyday life (Schmaltz, Jansen, & Wenckowski, 2017).  Our second definition is more operational; it is simply a list of skills that are essential to be a critical thinker. Critical thinking entails solid reasoning and problem solving skills; skepticism; and an ability to identify biases, distortions, omissions, and assumptions. Excellent deductive and inductive reasoning, and problem solving skills contribute to critical thinking. So, you can consider the subject matter of sections 7.2 and 7.3 to be part of critical thinking. Because we will be devoting considerable time to these concepts in the rest of the module, let us begin with a discussion about the other aspects of critical thinking.

Let’s address that first part of the definition. Scientists form hypotheses, or predictions about some possible future observations. Then, they collect data, or information (think of this as making those future observations). They do their best to make unbiased observations using reliable techniques that have been verified by others. Then, and only then, they draw a conclusion about what those observations mean. Oh, and do not forget the most important part. “Conclusion” is probably not the most appropriate word because this conclusion is only tentative. A scientist is always prepared that someone else might come along and produce new observations that would require a new conclusion be drawn. Wow! If you like to be right, you could do a lot worse than using a process like this.

A Critical Thinker’s Toolkit 

Now for the second part of the definition. Good critical thinkers (and scientists) rely on a variety of tools to evaluate information. Perhaps the most recognizable tool for critical thinking is  skepticism (and this term provides the clearest link to the thinking like a scientist definition, as you are about to see). Some people intend it as an insult when they call someone a skeptic. But if someone calls you a skeptic, if they are using the term correctly, you should consider it a great compliment. Simply put, skepticism is a way of thinking in which you refrain from drawing a conclusion or changing your mind until good evidence has been provided. People from Missouri should recognize this principle, as Missouri is known as the Show-Me State. As a skeptic, you are not inclined to believe something just because someone said so, because someone else believes it, or because it sounds reasonable. You must be persuaded by high quality evidence.

Of course, if that evidence is produced, you have a responsibility as a skeptic to change your belief. Failure to change a belief in the face of good evidence is not skepticism; skepticism has open mindedness at its core. M. Neil Browne and Stuart Keeley (2018) use the term weak sense critical thinking to describe critical thinking behaviors that are used only to strengthen a prior belief. Strong sense critical thinking, on the other hand, has as its goal reaching the best conclusion. Sometimes that means strengthening your prior belief, but sometimes it means changing your belief to accommodate the better evidence.

Many times, a failure to think critically or weak sense critical thinking is related to a  bias , an inclination, tendency, leaning, or prejudice. Everybody has biases, but many people are unaware of them. Awareness of your own biases gives you the opportunity to control or counteract them. Unfortunately, however, many people are happy to let their biases creep into their attempts to persuade others; indeed, it is a key part of their persuasive strategy. To see how these biases influence messages, just look at the different descriptions and explanations of the same events given by people of different ages or income brackets, or conservative versus liberal commentators, or by commentators from different parts of the world. Of course, to be successful, these people who are consciously using their biases must disguise them. Even undisguised biases can be difficult to identify, so disguised ones can be nearly impossible.

Here are some common sources of biases:

• Personal values and beliefs.  Some people believe that human beings are basically driven to seek power and that they are typically in competition with one another over scarce resources. These beliefs are similar to the world-view that political scientists call “realism.” Other people believe that human beings prefer to cooperate and that, given the chance, they will do so. These beliefs are similar to the world-view known as “idealism.” For many people, these deeply held beliefs can influence, or bias, their interpretations of such wide ranging situations as the behavior of nations and their leaders or the behavior of the driver in the car ahead of you. For example, if your worldview is that people are typically in competition and someone cuts you off on the highway, you may assume that the driver did it purposely to get ahead of you. Other types of beliefs about the way the world is or the way the world should be, for example, political beliefs, can similarly become a significant source of bias.
• Racism, sexism, ageism and other forms of prejudice and bigotry.  These are, sadly, a common source of bias in many people. They are essentially a special kind of “belief about the way the world is.” These beliefs—for example, that women do not make effective leaders—lead people to ignore contradictory evidence (examples of effective women leaders, or research that disputes the belief) and to interpret ambiguous evidence in a way consistent with the belief.
• Self-interest.  When particular people benefit from things turning out a certain way, they can sometimes be very susceptible to letting that interest bias them. For example, a company that will earn a profit if they sell their product may have a bias in the way that they give information about their product. A union that will benefit if its members get a generous contract might have a bias in the way it presents information about salaries at competing organizations. (Note that our inclusion of examples describing both companies and unions is an explicit attempt to control for our own personal biases). Home buyers are often dismayed to discover that they purchased their dream house from someone whose self-interest led them to lie about flooding problems in the basement or back yard. This principle, the biasing power of self-interest, is likely what led to the famous phrase  Caveat Emptor  (let the buyer beware) .  

Knowing that these types of biases exist will help you evaluate evidence more critically. Do not forget, though, that people are not always keen to let you discover the sources of biases in their arguments. For example, companies or political organizations can sometimes disguise their support of a research study by contracting with a university professor, who comes complete with a seemingly unbiased institutional affiliation, to conduct the study.

People’s biases, conscious or unconscious, can lead them to make omissions, distortions, and assumptions that undermine our ability to correctly evaluate evidence. It is essential that you look for these elements. Always ask, what is missing, what is not as it appears, and what is being assumed here? For example, consider this (fictional) chart from an ad reporting customer satisfaction at 4 local health clubs.

Clearly, from the results of the chart, one would be tempted to give Club C a try, as customer satisfaction is much higher than for the other 3 clubs.

There are so many distortions and omissions in this chart, however, that it is actually quite meaningless. First, how was satisfaction measured? Do the bars represent responses to a survey? If so, how were the questions asked? Most importantly, where is the missing scale for the chart? Although the differences look quite large, are they really?

Well, here is the same chart, with a different scale, this time labeled:

Club C is not so impressive any more, is it? In fact, all of the health clubs have customer satisfaction ratings (whatever that means) between 85% and 88%. In the first chart, the entire scale of the graph included only the percentages between 83 and 89. This “judicious” choice of scale—some would call it a distortion—and omission of that scale from the chart make the tiny differences among the clubs seem important, however.

Also, in order to be a critical thinker, you need to learn to pay attention to the assumptions that underlie a message. Let us briefly illustrate the role of assumptions by touching on some people’s beliefs about the criminal justice system in the US. Some believe that a major problem with our judicial system is that many criminals go free because of legal technicalities. Others believe that a major problem is that many innocent people are convicted of crimes. The simple fact is, both types of errors occur. A person’s conclusion about which flaw in our judicial system is the greater tragedy is based on an assumption about which of these is the more serious error (letting the guilty go free or convicting the innocent). This type of assumption is called a value assumption (Browne and Keeley, 2018). It reflects the differences in values that people develop, differences that may lead us to disregard valid evidence that does not fit in with our particular values.

Oh, by the way, some students probably noticed this, but the seven tips for evaluating information that we shared in Module 1 are related to this. Actually, they are part of this section. The tips are, to a very large degree, set of ideas you can use to help you identify biases, distortions, omissions, and assumptions. If you do not remember this section, we strongly recommend you take a few minutes to review it.

skepticism :  a way of thinking in which you refrain from drawing a conclusion or changing your mind until good evidence has been provided

bias : an inclination, tendency, leaning, or prejudice

• Which of your beliefs (or disbeliefs) from the Activate exercise for this section were derived from a process of critical thinking? If some of your beliefs were not based on critical thinking, are you willing to reassess these beliefs? If the answer is no, why do you think that is? If the answer is yes, what concrete steps will you take?

7.2 Reasoning and Judgment

• What percentage of kidnappings are committed by strangers?
• Which area of the house is riskiest: kitchen, bathroom, or stairs?
• What is the most common cancer in the US?
• What percentage of workplace homicides are committed by co-workers?

An essential set of procedural thinking skills is  reasoning , the ability to generate and evaluate solid conclusions from a set of statements or evidence. You should note that these conclusions (when they are generated instead of being evaluated) are one key type of inference that we described in Section 7.1. There are two main types of reasoning, deductive and inductive.

Deductive reasoning

Suppose your teacher tells you that if you get an A on the final exam in a course, you will get an A for the whole course. Then, you get an A on the final exam. What will your final course grade be? Most people can see instantly that you can conclude with certainty that you will get an A for the course. This is a type of reasoning called  deductive reasoning , which is defined as reasoning in which a conclusion is guaranteed to be true as long as the statements leading to it are true. The three statements can be listed as an  argument , with two beginning statements and a conclusion:

Statement 1: If you get an A on the final exam, you will get an A for the course

Statement 2: You get an A on the final exam

Conclusion: You will get an A for the course

This particular arrangement, in which true beginning statements lead to a guaranteed true conclusion, is known as a  deductively valid argument . Although deductive reasoning is often the subject of abstract, brain-teasing, puzzle-like word problems, it is actually an extremely important type of everyday reasoning. It is just hard to recognize sometimes. For example, imagine that you are looking for your car keys and you realize that they are either in the kitchen drawer or in your book bag. After looking in the kitchen drawer, you instantly know that they must be in your book bag. That conclusion results from a simple deductive reasoning argument. In addition, solid deductive reasoning skills are necessary for you to succeed in the sciences, philosophy, math, computer programming, and any endeavor involving the use of logic to persuade others to your point of view or to evaluate others’ arguments.

Cognitive psychologists, and before them philosophers, have been quite interested in deductive reasoning, not so much for its practical applications, but for the insights it can offer them about the ways that human beings think. One of the early ideas to emerge from the examination of deductive reasoning is that people learn (or develop) mental versions of rules that allow them to solve these types of reasoning problems (Braine, 1978; Braine, Reiser, & Rumain, 1984). The best way to see this point of view is to realize that there are different possible rules, and some of them are very simple. For example, consider this rule of logic:

therefore q

Logical rules are often presented abstractly, as letters, in order to imply that they can be used in very many specific situations. Here is a concrete version of the of the same rule:

I’ll either have pizza or a hamburger for dinner tonight (p or q)

I won’t have pizza (not p)

Therefore, I’ll have a hamburger (therefore q)

This kind of reasoning seems so natural, so easy, that it is quite plausible that we would use a version of this rule in our daily lives. At least, it seems more plausible than some of the alternative possibilities—for example, that we need to have experience with the specific situation (pizza or hamburger, in this case) in order to solve this type of problem easily. So perhaps there is a form of natural logic (Rips, 1990) that contains very simple versions of logical rules. When we are faced with a reasoning problem that maps onto one of these rules, we use the rule.

But be very careful; things are not always as easy as they seem. Even these simple rules are not so simple. For example, consider the following rule. Many people fail to realize that this rule is just as valid as the pizza or hamburger rule above.

if p, then q

therefore, not p

Concrete version:

If I eat dinner, then I will have dessert

I did not have dessert

Therefore, I did not eat dinner

The simple fact is, it can be very difficult for people to apply rules of deductive logic correctly; as a result, they make many errors when trying to do so. Is this a deductively valid argument or not?

Students who like school study a lot

Students who study a lot get good grades

Jane does not like school

Therefore, Jane does not get good grades

Many people are surprised to discover that this is not a logically valid argument; the conclusion is not guaranteed to be true from the beginning statements. Although the first statement says that students who like school study a lot, it does NOT say that students who do not like school do not study a lot. In other words, it may very well be possible to study a lot without liking school. Even people who sometimes get problems like this right might not be using the rules of deductive reasoning. Instead, they might just be making judgments for examples they know, in this case, remembering instances of people who get good grades despite not liking school.

Making deductive reasoning even more difficult is the fact that there are two important properties that an argument may have. One, it can be valid or invalid (meaning that the conclusion does or does not follow logically from the statements leading up to it). Two, an argument (or more correctly, its conclusion) can be true or false. Here is an example of an argument that is logically valid, but has a false conclusion (at least we think it is false).

Either you are eleven feet tall or the Grand Canyon was created by a spaceship crashing into the earth.

You are not eleven feet tall

Therefore the Grand Canyon was created by a spaceship crashing into the earth

This argument has the exact same form as the pizza or hamburger argument above, making it is deductively valid. The conclusion is so false, however, that it is absurd (of course, the reason the conclusion is false is that the first statement is false). When people are judging arguments, they tend to not observe the difference between deductive validity and the empirical truth of statements or conclusions. If the elements of an argument happen to be true, people are likely to judge the argument logically valid; if the elements are false, they will very likely judge it invalid (Markovits & Bouffard-Bouchard, 1992; Moshman & Franks, 1986). Thus, it seems a stretch to say that people are using these logical rules to judge the validity of arguments. Many psychologists believe that most people actually have very limited deductive reasoning skills (Johnson-Laird, 1999). They argue that when faced with a problem for which deductive logic is required, people resort to some simpler technique, such as matching terms that appear in the statements and the conclusion (Evans, 1982). This might not seem like a problem, but what if reasoners believe that the elements are true and they happen to be wrong; they will would believe that they are using a form of reasoning that guarantees they are correct and yet be wrong.

deductive reasoning :  a type of reasoning in which the conclusion is guaranteed to be true any time the statements leading up to it are true

argument :  a set of statements in which the beginning statements lead to a conclusion

deductively valid argument :  an argument for which true beginning statements guarantee that the conclusion is true

Inductive reasoning and judgment

Every day, you make many judgments about the likelihood of one thing or another. Whether you realize it or not, you are practicing  inductive reasoning   on a daily basis. In inductive reasoning arguments, a conclusion is likely whenever the statements preceding it are true. The first thing to notice about inductive reasoning is that, by definition, you can never be sure about your conclusion; you can only estimate how likely the conclusion is. Inductive reasoning may lead you to focus on Memory Encoding and Recoding when you study for the exam, but it is possible the instructor will ask more questions about Memory Retrieval instead. Unlike deductive reasoning, the conclusions you reach through inductive reasoning are only probable, not certain. That is why scientists consider inductive reasoning weaker than deductive reasoning. But imagine how hard it would be for us to function if we could not act unless we were certain about the outcome.

Inductive reasoning can be represented as logical arguments consisting of statements and a conclusion, just as deductive reasoning can be. In an inductive argument, you are given some statements and a conclusion (or you are given some statements and must draw a conclusion). An argument is  inductively strong   if the conclusion would be very probable whenever the statements are true. So, for example, here is an inductively strong argument:

• Statement #1: The forecaster on Channel 2 said it is going to rain today.
• Statement #2: The forecaster on Channel 5 said it is going to rain today.
• Statement #3: It is very cloudy and humid.
• Statement #4: You just heard thunder.
• Conclusion (or judgment): It is going to rain today.

Think of the statements as evidence, on the basis of which you will draw a conclusion. So, based on the evidence presented in the four statements, it is very likely that it will rain today. Will it definitely rain today? Certainly not. We can all think of times that the weather forecaster was wrong.

A true story: Some years ago psychology student was watching a baseball playoff game between the St. Louis Cardinals and the Los Angeles Dodgers. A graphic on the screen had just informed the audience that the Cardinal at bat, (Hall of Fame shortstop) Ozzie Smith, a switch hitter batting left-handed for this plate appearance, had never, in nearly 3000 career at-bats, hit a home run left-handed. The student, who had just learned about inductive reasoning in his psychology class, turned to his companion (a Cardinals fan) and smugly said, “It is an inductively strong argument that Ozzie Smith will not hit a home run.” He turned back to face the television just in time to watch the ball sail over the right field fence for a home run. Although the student felt foolish at the time, he was not wrong. It was an inductively strong argument; 3000 at-bats is an awful lot of evidence suggesting that the Wizard of Ozz (as he was known) would not be hitting one out of the park (think of each at-bat without a home run as a statement in an inductive argument). Sadly (for the die-hard Cubs fan and Cardinals-hating student), despite the strength of the argument, the conclusion was wrong.

Given the possibility that we might draw an incorrect conclusion even with an inductively strong argument, we really want to be sure that we do, in fact, make inductively strong arguments. If we judge something probable, it had better be probable. If we judge something nearly impossible, it had better not happen. Think of inductive reasoning, then, as making reasonably accurate judgments of the probability of some conclusion given a set of evidence.

We base many decisions in our lives on inductive reasoning. For example:

Statement #1: Psychology is not my best subject

Statement #2: My psychology instructor has a reputation for giving difficult exams

Statement #3: My first psychology exam was much harder than I expected

Judgment: The next exam will probably be very difficult.

Decision: I will study tonight instead of watching Netflix.

Some other examples of judgments that people commonly make in a school context include judgments of the likelihood that:

• A particular class will be interesting/useful/difficult
• You will be able to finish writing a paper by next week if you go out tonight
• Your laptop’s battery will last through the next trip to the library
• You will not miss anything important if you skip class tomorrow
• Your instructor will not notice if you skip class tomorrow
• You will be able to find a book that you will need for a paper
• There will be an essay question about Memory Encoding on the next exam

Tversky and Kahneman (1983) recognized that there are two general ways that we might make these judgments; they termed them extensional (i.e., following the laws of probability) and intuitive (i.e., using shortcuts or heuristics, see below). We will use a similar distinction between Type 1 and Type 2 thinking, as described by Keith Stanovich and his colleagues (Evans and Stanovich, 2013; Stanovich and West, 2000). Type 1 thinking is fast, automatic, effortful, and emotional. In fact, it is hardly fair to call it reasoning at all, as judgments just seem to pop into one’s head. Type 2 thinking , on the other hand, is slow, effortful, and logical. So obviously, it is more likely to lead to a correct judgment, or an optimal decision. The problem is, we tend to over-rely on Type 1. Now, we are not saying that Type 2 is the right way to go for every decision or judgment we make. It seems a bit much, for example, to engage in a step-by-step logical reasoning procedure to decide whether we will have chicken or fish for dinner tonight.

Many bad decisions in some very important contexts, however, can be traced back to poor judgments of the likelihood of certain risks or outcomes that result from the use of Type 1 when a more logical reasoning process would have been more appropriate. For example:

Statement #1: It is late at night.

Statement #2: Albert has been drinking beer for the past five hours at a party.

Statement #3: Albert is not exactly sure where he is or how far away home is.

Judgment: Albert will have no difficulty walking home.

Decision: He walks home alone.

As you can see in this example, the three statements backing up the judgment do not really support it. In other words, this argument is not inductively strong because it is based on judgments that ignore the laws of probability. What are the chances that someone facing these conditions will be able to walk home alone easily? And one need not be drunk to make poor decisions based on judgments that just pop into our heads.

The truth is that many of our probability judgments do not come very close to what the laws of probability say they should be. Think about it. In order for us to reason in accordance with these laws, we would need to know the laws of probability, which would allow us to calculate the relationship between particular pieces of evidence and the probability of some outcome (i.e., how much likelihood should change given a piece of evidence), and we would have to do these heavy math calculations in our heads. After all, that is what Type 2 requires. Needless to say, even if we were motivated, we often do not even know how to apply Type 2 reasoning in many cases.

So what do we do when we don’t have the knowledge, skills, or time required to make the correct mathematical judgment? Do we hold off and wait until we can get better evidence? Do we read up on probability and fire up our calculator app so we can compute the correct probability? Of course not. We rely on Type 1 thinking. We “wing it.” That is, we come up with a likelihood estimate using some means at our disposal. Psychologists use the term heuristic to describe the type of “winging it” we are talking about. A  heuristic   is a shortcut strategy that we use to make some judgment or solve some problem (see Section 7.3). Heuristics are easy and quick, think of them as the basic procedures that are characteristic of Type 1.  They can absolutely lead to reasonably good judgments and decisions in some situations (like choosing between chicken and fish for dinner). They are, however, far from foolproof. There are, in fact, quite a lot of situations in which heuristics can lead us to make incorrect judgments, and in many cases the decisions based on those judgments can have serious consequences.

Let us return to the activity that begins this section. You were asked to judge the likelihood (or frequency) of certain events and risks. You were free to come up with your own evidence (or statements) to make these judgments. This is where a heuristic crops up. As a judgment shortcut, we tend to generate specific examples of those very events to help us decide their likelihood or frequency. For example, if we are asked to judge how common, frequent, or likely a particular type of cancer is, many of our statements would be examples of specific cancer cases:

Statement #1: Andy Kaufman (comedian) had lung cancer.

Statement #2: Colin Powell (US Secretary of State) had prostate cancer.

Statement #3: Bob Marley (musician) had skin and brain cancer

Statement #4: Sandra Day O’Connor (Supreme Court Justice) had breast cancer.

Statement #5: Fred Rogers (children’s entertainer) had stomach cancer.

Statement #6: Robin Roberts (news anchor) had breast cancer.

Statement #7: Bette Davis (actress) had breast cancer.

Judgment: Breast cancer is the most common type.

Your own experience or memory may also tell you that breast cancer is the most common type. But it is not (although it is common). Actually, skin cancer is the most common type in the US. We make the same types of misjudgments all the time because we do not generate the examples or evidence according to their actual frequencies or probabilities. Instead, we have a tendency (or bias) to search for the examples in memory; if they are easy to retrieve, we assume that they are common. To rephrase this in the language of the heuristic, events seem more likely to the extent that they are available to memory. This bias has been termed the  availability heuristic   (Kahneman and Tversky, 1974).

The fact that we use the availability heuristic does not automatically mean that our judgment is wrong. The reason we use heuristics in the first place is that they work fairly well in many cases (and, of course that they are easy to use). So, the easiest examples to think of sometimes are the most common ones. Is it more likely that a member of the U.S. Senate is a man or a woman? Most people have a much easier time generating examples of male senators. And as it turns out, the U.S. Senate has many more men than women (74 to 26 in 2020). In this case, then, the availability heuristic would lead you to make the correct judgment; it is far more likely that a senator would be a man.

In many other cases, however, the availability heuristic will lead us astray. This is because events can be memorable for many reasons other than their frequency. Section 5.2, Encoding Meaning, suggested that one good way to encode the meaning of some information is to form a mental image of it. Thus, information that has been pictured mentally will be more available to memory. Indeed, an event that is vivid and easily pictured will trick many people into supposing that type of event is more common than it actually is. Repetition of information will also make it more memorable. So, if the same event is described to you in a magazine, on the evening news, on a podcast that you listen to, and in your Facebook feed; it will be very available to memory. Again, the availability heuristic will cause you to misperceive the frequency of these types of events.

Most interestingly, information that is unusual is more memorable. Suppose we give you the following list of words to remember: box, flower, letter, platypus, oven, boat, newspaper, purse, drum, car. Very likely, the easiest word to remember would be platypus, the unusual one. The same thing occurs with memories of events. An event may be available to memory because it is unusual, yet the availability heuristic leads us to judge that the event is common. Did you catch that? In these cases, the availability heuristic makes us think the exact opposite of the true frequency. We end up thinking something is common because it is unusual (and therefore memorable). Yikes.

The misapplication of the availability heuristic sometimes has unfortunate results. For example, if you went to K-12 school in the US over the past 10 years, it is extremely likely that you have participated in lockdown and active shooter drills. Of course, everyone is trying to prevent the tragedy of another school shooting. And believe us, we are not trying to minimize how terrible the tragedy is. But the truth of the matter is, school shootings are extremely rare. Because the federal government does not keep a database of school shootings, the Washington Post has maintained their own running tally. Between 1999 and January 2020 (the date of the most recent school shooting with a death in the US at of the time this paragraph was written), the Post reported a total of 254 people died in school shootings in the US. Not 254 per year, 254 total. That is an average of 12 per year. Of course, that is 254 people who should not have died (particularly because many were children), but in a country with approximately 60,000,000 students and teachers, this is a very small risk.

But many students and teachers are terrified that they will be victims of school shootings because of the availability heuristic. It is so easy to think of examples (they are very available to memory) that people believe the event is very common. It is not. And there is a downside to this. We happen to believe that there is an enormous gun violence problem in the United States. According the the Centers for Disease Control and Prevention, there were 39,773 firearm deaths in the US in 2017. Fifteen of those deaths were in school shootings, according to the Post. 60% of those deaths were suicides. When people pay attention to the school shooting risk (low), they often fail to notice the much larger risk.

And examples like this are by no means unique. The authors of this book have been teaching psychology since the 1990’s. We have been able to make the exact same arguments about the misapplication of the availability heuristics and keep them current by simply swapping out for the “fear of the day.” In the 1990’s it was children being kidnapped by strangers (it was known as “stranger danger”) despite the facts that kidnappings accounted for only 2% of the violent crimes committed against children, and only 24% of kidnappings are committed by strangers (US Department of Justice, 2007). This fear overlapped with the fear of terrorism that gripped the country after the 2001 terrorist attacks on the World Trade Center and US Pentagon and still plagues the population of the US somewhat in 2020. After a well-publicized, sensational act of violence, people are extremely likely to increase their estimates of the chances that they, too, will be victims of terror. Think about the reality, however. In October of 2001, a terrorist mailed anthrax spores to members of the US government and a number of media companies. A total of five people died as a result of this attack. The nation was nearly paralyzed by the fear of dying from the attack; in reality the probability of an individual person dying was 0.00000002.

The availability heuristic can lead you to make incorrect judgments in a school setting as well. For example, suppose you are trying to decide if you should take a class from a particular math professor. You might try to make a judgment of how good a teacher she is by recalling instances of friends and acquaintances making comments about her teaching skill. You may have some examples that suggest that she is a poor teacher very available to memory, so on the basis of the availability heuristic you judge her a poor teacher and decide to take the class from someone else. What if, however, the instances you recalled were all from the same person, and this person happens to be a very colorful storyteller? The subsequent ease of remembering the instances might not indicate that the professor is a poor teacher after all.

Although the availability heuristic is obviously important, it is not the only judgment heuristic we use. Amos Tversky and Daniel Kahneman examined the role of heuristics in inductive reasoning in a long series of studies. Kahneman received a Nobel Prize in Economics for this research in 2002, and Tversky would have certainly received one as well if he had not died of melanoma at age 59 in 1996 (Nobel Prizes are not awarded posthumously). Kahneman and Tversky demonstrated repeatedly that people do not reason in ways that are consistent with the laws of probability. They identified several heuristic strategies that people use instead to make judgments about likelihood. The importance of this work for economics (and the reason that Kahneman was awarded the Nobel Prize) is that earlier economic theories had assumed that people do make judgments rationally, that is, in agreement with the laws of probability.

Another common heuristic that people use for making judgments is the  representativeness heuristic (Kahneman & Tversky 1973). Suppose we describe a person to you. He is quiet and shy, has an unassuming personality, and likes to work with numbers. Is this person more likely to be an accountant or an attorney? If you said accountant, you were probably using the representativeness heuristic. Our imaginary person is judged likely to be an accountant because he resembles, or is representative of the concept of, an accountant. When research participants are asked to make judgments such as these, the only thing that seems to matter is the representativeness of the description. For example, if told that the person described is in a room that contains 70 attorneys and 30 accountants, participants will still assume that he is an accountant.

inductive reasoning :  a type of reasoning in which we make judgments about likelihood from sets of evidence

inductively strong argument :  an inductive argument in which the beginning statements lead to a conclusion that is probably true

heuristic :  a shortcut strategy that we use to make judgments and solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

availability heuristic :  judging the frequency or likelihood of some event type according to how easily examples of the event can be called to mind (i.e., how available they are to memory)

representativeness heuristic:   judging the likelihood that something is a member of a category on the basis of how much it resembles a typical category member (i.e., how representative it is of the category)

Type 1 thinking : fast, automatic, and emotional thinking.

Type 2 thinking : slow, effortful, and logical thinking.

• What percentage of workplace homicides are co-worker violence?

Many people get these questions wrong. The answers are 10%; stairs; skin; 6%. How close were your answers? Explain how the availability heuristic might have led you to make the incorrect judgments.

• Can you think of some other judgments that you have made (or beliefs that you have) that might have been influenced by the availability heuristic?

7.3 Problem Solving

• Please take a few minutes to list a number of problems that you are facing right now.
• Now write about a problem that you recently solved.
• What is your definition of a problem?

Mary has a problem. Her daughter, ordinarily quite eager to please, appears to delight in being the last person to do anything. Whether getting ready for school, going to piano lessons or karate class, or even going out with her friends, she seems unwilling or unable to get ready on time. Other people have different kinds of problems. For example, many students work at jobs, have numerous family commitments, and are facing a course schedule full of difficult exams, assignments, papers, and speeches. How can they find enough time to devote to their studies and still fulfill their other obligations? Speaking of students and their problems: Show that a ball thrown vertically upward with initial velocity v0 takes twice as much time to return as to reach the highest point (from Spiegel, 1981).

These are three very different situations, but we have called them all problems. What makes them all the same, despite the differences? A psychologist might define a  problem   as a situation with an initial state, a goal state, and a set of possible intermediate states. Somewhat more meaningfully, we might consider a problem a situation in which you are in here one state (e.g., daughter is always late), you want to be there in another state (e.g., daughter is not always late), and with no obvious way to get from here to there. Defined this way, each of the three situations we outlined can now be seen as an example of the same general concept, a problem. At this point, you might begin to wonder what is not a problem, given such a general definition. It seems that nearly every non-routine task we engage in could qualify as a problem. As long as you realize that problems are not necessarily bad (it can be quite fun and satisfying to rise to the challenge and solve a problem), this may be a useful way to think about it.

Can we identify a set of problem-solving skills that would apply to these very different kinds of situations? That task, in a nutshell, is a major goal of this section. Let us try to begin to make sense of the wide variety of ways that problems can be solved with an important observation: the process of solving problems can be divided into two key parts. First, people have to notice, comprehend, and represent the problem properly in their minds (called  problem representation ). Second, they have to apply some kind of solution strategy to the problem. Psychologists have studied both of these key parts of the process in detail.

When you first think about the problem-solving process, you might guess that most of our difficulties would occur because we are failing in the second step, the application of strategies. Although this can be a significant difficulty much of the time, the more important source of difficulty is probably problem representation. In short, we often fail to solve a problem because we are looking at it, or thinking about it, the wrong way.

problem :  a situation in which we are in an initial state, have a desired goal state, and there is a number of possible intermediate states (i.e., there is no obvious way to get from the initial to the goal state)

problem representation :  noticing, comprehending and forming a mental conception of a problem

Defining and Mentally Representing Problems in Order to Solve Them

So, the main obstacle to solving a problem is that we do not clearly understand exactly what the problem is. Recall the problem with Mary’s daughter always being late. One way to represent, or to think about, this problem is that she is being defiant. She refuses to get ready in time. This type of representation or definition suggests a particular type of solution. Another way to think about the problem, however, is to consider the possibility that she is simply being sidetracked by interesting diversions. This different conception of what the problem is (i.e., different representation) suggests a very different solution strategy. For example, if Mary defines the problem as defiance, she may be tempted to solve the problem using some kind of coercive tactics, that is, to assert her authority as her mother and force her to listen. On the other hand, if Mary defines the problem as distraction, she may try to solve it by simply removing the distracting objects.

As you might guess, when a problem is represented one way, the solution may seem very difficult, or even impossible. Seen another way, the solution might be very easy. For example, consider the following problem (from Nasar, 1998):

Two bicyclists start 20 miles apart and head toward each other, each going at a steady rate of 10 miles per hour. At the same time, a fly that travels at a steady 15 miles per hour starts from the front wheel of the southbound bicycle and flies to the front wheel of the northbound one, then turns around and flies to the front wheel of the southbound one again, and continues in this manner until he is crushed between the two front wheels. Question: what total distance did the fly cover?

Please take a few minutes to try to solve this problem.

Most people represent this problem as a question about a fly because, well, that is how the question is asked. The solution, using this representation, is to figure out how far the fly travels on the first leg of its journey, then add this total to how far it travels on the second leg of its journey (when it turns around and returns to the first bicycle), then continue to add the smaller distance from each leg of the journey until you converge on the correct answer. You would have to be quite skilled at math to solve this problem, and you would probably need some time and pencil and paper to do it.

If you consider a different representation, however, you can solve this problem in your head. Instead of thinking about it as a question about a fly, think about it as a question about the bicycles. They are 20 miles apart, and each is traveling 10 miles per hour. How long will it take for the bicycles to reach each other? Right, one hour. The fly is traveling 15 miles per hour; therefore, it will travel a total of 15 miles back and forth in the hour before the bicycles meet. Represented one way (as a problem about a fly), the problem is quite difficult. Represented another way (as a problem about two bicycles), it is easy. Changing your representation of a problem is sometimes the best—sometimes the only—way to solve it.

Unfortunately, however, changing a problem’s representation is not the easiest thing in the world to do. Often, problem solvers get stuck looking at a problem one way. This is called  fixation . Most people who represent the preceding problem as a problem about a fly probably do not pause to reconsider, and consequently change, their representation. A parent who thinks her daughter is being defiant is unlikely to consider the possibility that her behavior is far less purposeful.

Problem-solving fixation was examined by a group of German psychologists called Gestalt psychologists during the 1930’s and 1940’s. Karl Dunker, for example, discovered an important type of failure to take a different perspective called  functional fixedness . Imagine being a participant in one of his experiments. You are asked to figure out how to mount two candles on a door and are given an assortment of odds and ends, including a small empty cardboard box and some thumbtacks. Perhaps you have already figured out a solution: tack the box to the door so it forms a platform, then put the candles on top of the box. Most people are able to arrive at this solution. Imagine a slight variation of the procedure, however. What if, instead of being empty, the box had matches in it? Most people given this version of the problem do not arrive at the solution given above. Why? Because it seems to people that when the box contains matches, it already has a function; it is a matchbox. People are unlikely to consider a new function for an object that already has a function. This is functional fixedness.

Mental set is a type of fixation in which the problem solver gets stuck using the same solution strategy that has been successful in the past, even though the solution may no longer be useful. It is commonly seen when students do math problems for homework. Often, several problems in a row require the reapplication of the same solution strategy. Then, without warning, the next problem in the set requires a new strategy. Many students attempt to apply the formerly successful strategy on the new problem and therefore cannot come up with a correct answer.

The thing to remember is that you cannot solve a problem unless you correctly identify what it is to begin with (initial state) and what you want the end result to be (goal state). That may mean looking at the problem from a different angle and representing it in a new way. The correct representation does not guarantee a successful solution, but it certainly puts you on the right track.

A bit more optimistically, the Gestalt psychologists discovered what may be considered the opposite of fixation, namely  insight . Sometimes the solution to a problem just seems to pop into your head. Wolfgang Kohler examined insight by posing many different problems to chimpanzees, principally problems pertaining to their acquisition of out-of-reach food. In one version, a banana was placed outside of a chimpanzee’s cage and a short stick inside the cage. The stick was too short to retrieve the banana, but was long enough to retrieve a longer stick also located outside of the cage. This second stick was long enough to retrieve the banana. After trying, and failing, to reach the banana with the shorter stick, the chimpanzee would try a couple of random-seeming attempts, react with some apparent frustration or anger, then suddenly rush to the longer stick, the correct solution fully realized at this point. This sudden appearance of the solution, observed many times with many different problems, was termed insight by Kohler.

Lest you think it pertains to chimpanzees only, Karl Dunker demonstrated that children also solve problems through insight in the 1930s. More importantly, you have probably experienced insight yourself. Think back to a time when you were trying to solve a difficult problem. After struggling for a while, you gave up. Hours later, the solution just popped into your head, perhaps when you were taking a walk, eating dinner, or lying in bed.

fixation :  when a problem solver gets stuck looking at a problem a particular way and cannot change his or her representation of it (or his or her intended solution strategy)

functional fixedness :  a specific type of fixation in which a problem solver cannot think of a new use for an object that already has a function

mental set :  a specific type of fixation in which a problem solver gets stuck using the same solution strategy that has been successful in the past

insight :  a sudden realization of a solution to a problem

Solving Problems by Trial and Error

Correctly identifying the problem and your goal for a solution is a good start, but recall the psychologist’s definition of a problem: it includes a set of possible intermediate states. Viewed this way, a problem can be solved satisfactorily only if one can find a path through some of these intermediate states to the goal. Imagine a fairly routine problem, finding a new route to school when your ordinary route is blocked (by road construction, for example). At each intersection, you may turn left, turn right, or go straight. A satisfactory solution to the problem (of getting to school) is a sequence of selections at each intersection that allows you to wind up at school.

If you had all the time in the world to get to school, you might try choosing intermediate states randomly. At one corner you turn left, the next you go straight, then you go left again, then right, then right, then straight. Unfortunately, trial and error will not necessarily get you where you want to go, and even if it does, it is not the fastest way to get there. For example, when a friend of ours was in college, he got lost on the way to a concert and attempted to find the venue by choosing streets to turn onto randomly (this was long before the use of GPS). Amazingly enough, the strategy worked, although he did end up missing two out of the three bands who played that night.

Trial and error is not all bad, however. B.F. Skinner, a prominent behaviorist psychologist, suggested that people often behave randomly in order to see what effect the behavior has on the environment and what subsequent effect this environmental change has on them. This seems particularly true for the very young person. Picture a child filling a household’s fish tank with toilet paper, for example. To a child trying to develop a repertoire of creative problem-solving strategies, an odd and random behavior might be just the ticket. Eventually, the exasperated parent hopes, the child will discover that many of these random behaviors do not successfully solve problems; in fact, in many cases they create problems. Thus, one would expect a decrease in this random behavior as a child matures. You should realize, however, that the opposite extreme is equally counterproductive. If the children become too rigid, never trying something unexpected and new, their problem solving skills can become too limited.

Effective problem solving seems to call for a happy medium that strikes a balance between using well-founded old strategies and trying new ground and territory. The individual who recognizes a situation in which an old problem-solving strategy would work best, and who can also recognize a situation in which a new untested strategy is necessary is halfway to success.

Solving Problems with Algorithms and Heuristics

For many problems there is a possible strategy available that will guarantee a correct solution. For example, think about math problems. Math lessons often consist of step-by-step procedures that can be used to solve the problems. If you apply the strategy without error, you are guaranteed to arrive at the correct solution to the problem. This approach is called using an  algorithm , a term that denotes the step-by-step procedure that guarantees a correct solution. Because algorithms are sometimes available and come with a guarantee, you might think that most people use them frequently. Unfortunately, however, they do not. As the experience of many students who have struggled through math classes can attest, algorithms can be extremely difficult to use, even when the problem solver knows which algorithm is supposed to work in solving the problem. In problems outside of math class, we often do not even know if an algorithm is available. It is probably fair to say, then, that algorithms are rarely used when people try to solve problems.

Because algorithms are so difficult to use, people often pass up the opportunity to guarantee a correct solution in favor of a strategy that is much easier to use and yields a reasonable chance of coming up with a correct solution. These strategies are called  problem solving heuristics . Similar to what you saw in section 6.2 with reasoning heuristics, a problem solving heuristic is a shortcut strategy that people use when trying to solve problems. It usually works pretty well, but does not guarantee a correct solution to the problem. For example, one problem solving heuristic might be “always move toward the goal” (so when trying to get to school when your regular route is blocked, you would always turn in the direction you think the school is). A heuristic that people might use when doing math homework is “use the same solution strategy that you just used for the previous problem.”

By the way, we hope these last two paragraphs feel familiar to you. They seem to parallel a distinction that you recently learned. Indeed, algorithms and problem-solving heuristics are another example of the distinction between Type 1 thinking and Type 2 thinking.

Although it is probably not worth describing a large number of specific heuristics, two observations about heuristics are worth mentioning. First, heuristics can be very general or they can be very specific, pertaining to a particular type of problem only. For example, “always move toward the goal” is a general strategy that you can apply to countless problem situations. On the other hand, “when you are lost without a functioning gps, pick the most expensive car you can see and follow it” is specific to the problem of being lost. Second, all heuristics are not equally useful. One heuristic that many students know is “when in doubt, choose c for a question on a multiple-choice exam.” This is a dreadful strategy because many instructors intentionally randomize the order of answer choices. Another test-taking heuristic, somewhat more useful, is “look for the answer to one question somewhere else on the exam.”

You really should pay attention to the application of heuristics to test taking. Imagine that while reviewing your answers for a multiple-choice exam before turning it in, you come across a question for which you originally thought the answer was c. Upon reflection, you now think that the answer might be b. Should you change the answer to b, or should you stick with your first impression? Most people will apply the heuristic strategy to “stick with your first impression.” What they do not realize, of course, is that this is a very poor strategy (Lilienfeld et al, 2009). Most of the errors on exams come on questions that were answered wrong originally and were not changed (so they remain wrong). There are many fewer errors where we change a correct answer to an incorrect answer. And, of course, sometimes we change an incorrect answer to a correct answer. In fact, research has shown that it is more common to change a wrong answer to a right answer than vice versa (Bruno, 2001).

The belief in this poor test-taking strategy (stick with your first impression) is based on the  confirmation bias   (Nickerson, 1998; Wason, 1960). You first saw the confirmation bias in Module 1, but because it is so important, we will repeat the information here. People have a bias, or tendency, to notice information that confirms what they already believe. Somebody at one time told you to stick with your first impression, so when you look at the results of an exam you have taken, you will tend to notice the cases that are consistent with that belief. That is, you will notice the cases in which you originally had an answer correct and changed it to the wrong answer. You tend not to notice the other two important (and more common) cases, changing an answer from wrong to right, and leaving a wrong answer unchanged.

Because heuristics by definition do not guarantee a correct solution to a problem, mistakes are bound to occur when we employ them. A poor choice of a specific heuristic will lead to an even higher likelihood of making an error.

algorithm :  a step-by-step procedure that guarantees a correct solution to a problem

problem solving heuristic :  a shortcut strategy that we use to solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

confirmation bias :  people’s tendency to notice information that confirms what they already believe

An Effective Problem-Solving Sequence

You may be left with a big question: If algorithms are hard to use and heuristics often don’t work, how am I supposed to solve problems? Robert Sternberg (1996), as part of his theory of what makes people successfully intelligent (Module 8) described a problem-solving sequence that has been shown to work rather well:

• Identify the existence of a problem.  In school, problem identification is often easy; problems that you encounter in math classes, for example, are conveniently labeled as problems for you. Outside of school, however, realizing that you have a problem is a key difficulty that you must get past in order to begin solving it. You must be very sensitive to the symptoms that indicate a problem.
• Define the problem.  Suppose you realize that you have been having many headaches recently. Very likely, you would identify this as a problem. If you define the problem as “headaches,” the solution would probably be to take aspirin or ibuprofen or some other anti-inflammatory medication. If the headaches keep returning, however, you have not really solved the problem—likely because you have mistaken a symptom for the problem itself. Instead, you must find the root cause of the headaches. Stress might be the real problem. For you to successfully solve many problems it may be necessary for you to overcome your fixations and represent the problems differently. One specific strategy that you might find useful is to try to define the problem from someone else’s perspective. How would your parents, spouse, significant other, doctor, etc. define the problem? Somewhere in these different perspectives may lurk the key definition that will allow you to find an easier and permanent solution.
• Formulate strategy.  Now it is time to begin planning exactly how the problem will be solved. Is there an algorithm or heuristic available for you to use? Remember, heuristics by their very nature guarantee that occasionally you will not be able to solve the problem. One point to keep in mind is that you should look for long-range solutions, which are more likely to address the root cause of a problem than short-range solutions.
• Represent and organize information.  Similar to the way that the problem itself can be defined, or represented in multiple ways, information within the problem is open to different interpretations. Suppose you are studying for a big exam. You have chapters from a textbook and from a supplemental reader, along with lecture notes that all need to be studied. How should you (represent and) organize these materials? Should you separate them by type of material (text versus reader versus lecture notes), or should you separate them by topic? To solve problems effectively, you must learn to find the most useful representation and organization of information.
• Allocate resources.  This is perhaps the simplest principle of the problem solving sequence, but it is extremely difficult for many people. First, you must decide whether time, money, skills, effort, goodwill, or some other resource would help to solve the problem Then, you must make the hard choice of deciding which resources to use, realizing that you cannot devote maximum resources to every problem. Very often, the solution to problem is simply to change how resources are allocated (for example, spending more time studying in order to improve grades).
• Monitor and evaluate solutions.  Pay attention to the solution strategy while you are applying it. If it is not working, you may be able to select another strategy. Another fact you should realize about problem solving is that it never does end. Solving one problem frequently brings up new ones. Good monitoring and evaluation of your problem solutions can help you to anticipate and get a jump on solving the inevitable new problems that will arise.

Please note that this as  an  effective problem-solving sequence, not  the  effective problem solving sequence. Just as you can become fixated and end up representing the problem incorrectly or trying an inefficient solution, you can become stuck applying the problem-solving sequence in an inflexible way. Clearly there are problem situations that can be solved without using these skills in this order.

Additionally, many real-world problems may require that you go back and redefine a problem several times as the situation changes (Sternberg et al. 2000). For example, consider the problem with Mary’s daughter one last time. At first, Mary did represent the problem as one of defiance. When her early strategy of pleading and threatening punishment was unsuccessful, Mary began to observe her daughter more carefully. She noticed that, indeed, her daughter’s attention would be drawn by an irresistible distraction or book. Fresh with a re-representation of the problem, she began a new solution strategy. She began to remind her daughter every few minutes to stay on task and remind her that if she is ready before it is time to leave, she may return to the book or other distracting object at that time. Fortunately, this strategy was successful, so Mary did not have to go back and redefine the problem again.

Pick one or two of the problems that you listed when you first started studying this section and try to work out the steps of Sternberg’s problem solving sequence for each one.

a mental representation of a category of things in the world

an assumption about the truth of something that is not stated. Inferences come from our prior knowledge and experience, and from logical reasoning

knowledge about one’s own cognitive processes; thinking about your thinking

individuals who are less competent tend to overestimate their abilities more than individuals who are more competent do

Thinking like a scientist in your everyday life for the purpose of drawing correct conclusions. It entails skepticism; an ability to identify biases, distortions, omissions, and assumptions; and excellent deductive and inductive reasoning, and problem solving skills.

a way of thinking in which you refrain from drawing a conclusion or changing your mind until good evidence has been provided

an inclination, tendency, leaning, or prejudice

a type of reasoning in which the conclusion is guaranteed to be true any time the statements leading up to it are true

a set of statements in which the beginning statements lead to a conclusion

an argument for which true beginning statements guarantee that the conclusion is true

a type of reasoning in which we make judgments about likelihood from sets of evidence

an inductive argument in which the beginning statements lead to a conclusion that is probably true

fast, automatic, and emotional thinking

slow, effortful, and logical thinking

a shortcut strategy that we use to make judgments and solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

udging the frequency or likelihood of some event type according to how easily examples of the event can be called to mind (i.e., how available they are to memory)

judging the likelihood that something is a member of a category on the basis of how much it resembles a typical category member (i.e., how representative it is of the category)

a situation in which we are in an initial state, have a desired goal state, and there is a number of possible intermediate states (i.e., there is no obvious way to get from the initial to the goal state)

noticing, comprehending and forming a mental conception of a problem

when a problem solver gets stuck looking at a problem a particular way and cannot change his or her representation of it (or his or her intended solution strategy)

a specific type of fixation in which a problem solver cannot think of a new use for an object that already has a function

a specific type of fixation in which a problem solver gets stuck using the same solution strategy that has been successful in the past

a sudden realization of a solution to a problem

a step-by-step procedure that guarantees a correct solution to a problem

The tendency to notice and pay attention to information that confirms your prior beliefs and to ignore information that disconfirms them.

a shortcut strategy that we use to solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

Introduction to Psychology Copyright © 2020 by Ken Gray; Elizabeth Arnott-Hill; and Or'Shaundra Benson is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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• What Is a Fishbone Diagram? | Templates & Examples

What Is a Fishbone Diagram? | Templates & Examples

Published on January 2, 2023 by Tegan George . Revised on January 29, 2024.

A fishbone diagram is a problem-solving approach that uses a fish-shaped diagram to model possible root causes of problems and troubleshoot possible solutions. It is also called an Ishikawa diagram, after its creator, Kaoru Ishikawa, as well as a herringbone diagram or cause-and-effect diagram.

Fishbone diagrams are often used in root cause analysis , to troubleshoot issues in quality management or product development. They are also used in the fields of nursing and healthcare, or as a brainstorming and mind-mapping technique many students find helpful.

Table of contents

How to make a fishbone diagram, fishbone diagram templates, fishbone diagram examples, advantages and disadvantages of fishbone diagrams, other interesting articles, frequently asked questions about fishbone diagrams.

A fishbone diagram is easy to draw, or you can use a template for an online version.

• Your fishbone diagram starts out with an issue or problem. This is the “head” of the fish, summarized in a few words or a small phrase.
• Next, draw a long arrow, which serves as the fish’s backbone.
• From here, you’ll draw the first “bones” directly from the backbone, in the shape of small diagonal lines going right-to-left. These represent the most likely or overarching causes of your problem.
• Branching off from each of these first bones, create smaller bones containing contributing information and necessary detail.
• When finished, your fishbone diagram should give you a wide-view idea of what the root causes of the issue you’re facing could be, allowing you to rank them or choose which could be most plausible.

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See an example

There are no built-in fishbone diagram templates in Microsoft programs, but we’ve made a few free ones for you to use that you can download below. Alternatively, you can make one yourself using the following steps:

• In a fresh document, go to Insert > Shapes
• Draw a long arrow from left to right, and add a text box on the right-hand side. These serve as the backbone and the head of the fish.
• Next, add lines jutting diagonally from the backbone. These serve as the ribs, or the contributing factors to the main problem.
• Next, add horizontal lines jutting from each central line. These serve as the potential causes of the problem.

Lastly, add text boxes to label each function.

You can try your hand at filling one in yourself using the various blank fishbone diagram templates below, in the following formats:

Fishbone diagram template Excel

Download our free Excel template below!

Fishbone diagram template Word

Download our free Word template below!

Fishbone diagram template PowerPoint

Download our free PowerPoint template below!

Fishbone diagrams are used in a variety of settings, both academic and professional. They are particularly popular in healthcare settings, particularly nursing, or in group brainstorm study sessions. In the business world, they are an often-used tool for quality assurance or human resources professionals.

Fishbone diagram example #1: Climate change

Let’s start with an everyday example: what are the main causes of climate change?

Fishbone diagram example #2: Healthcare and nursing

Fishbone diagrams are often used in nursing and healthcare to diagnose patients with unclear symptoms, or to streamline processes or fix ongoing problems. For example: why have surveys shown a decrease in patient satisfaction?

Fishbone diagram example #3: Quality assurance

QA professionals also use fishbone diagrams to troubleshoot usability issues, such as: why is the website down?

Fishbone diagram example #4: HR

Lastly, an HR example: why are employees leaving the company?

Fishbone diagrams come with advantages and disadvantages.

• Great tool for brainstorming and mind-mapping, either individually or in a group project.
• Can help identify causal relationships and clarify relationships between variables .
• Constant iteration of “why” questions really drills down to root problems and elegantly simplifies even complex issues.

Disadvantages

• Can lead to incorrect or inconsistent conclusions if the wrong assumptions are made about root causes or the wrong variables are prioritized.
• Fishbone diagrams are best suited to short phrases or simple ideas—they can get cluttered and confusing easily.
• Best used in the exploratory research phase, since they cannot provide true answers, only suggestions.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

Fishbone diagrams have a few different names that are used interchangeably, including herringbone diagram, cause-and-effect diagram, and Ishikawa diagram.

These are all ways to refer to the same thing– a problem-solving approach that uses a fish-shaped diagram to model possible root causes of problems and troubleshoot solutions.

Fishbone diagrams (also called herringbone diagrams, cause-and-effect diagrams, and Ishikawa diagrams) are most popular in fields of quality management. They are also commonly used in nursing and healthcare, or as a brainstorming technique for students.

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1.7: Problem Solving Process

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Learning how to use a structured problem solving process will help you to be more organized and support your future courses. Also, it will train your brain how to approach problems. Just like basketball players practice jump shots over and over to train their body how to act in high pressure scenarios, if you are comfortable and familiar with a structured problem solving process, when you’re in a high pressure situation like a test, you can just jump into the problem like muscle memory.

6 Step Problem Solving Method:

• Write out the answer with all necessary information that is given to you. It feels like it takes forever, but it’s important to have the problem and solution next to each other.
• Draw the problem, this is usually a free-body diagram (don’t forget a coordinate frame). Eventually, as you get further into the course, you might need a few drawings. One would be a quick sketch of the problem in the real world, then modelling it into a simplified engineering drawing, and finally the free-body diagram.
• Write out a list of the known/given values with the variable and unit, i.e m = 14 kg   (variable = number unit)
• Write out a list of the unknown values that you will have to solve for in order to solve the problem
• You can also add any assumptions you made here that change the problem.
• Also state any constants, i.e. g = 32.2 ft/m 2   or g = 9.81 m/s 2
• This step helps you to have all of the information in one place when you solve the problem. It’s also important because each number should include units, so you can see if the units match or if you need to convert some numbers so they are all in English or SI. This also gives you the variables side by side to ensure they are unique (so you don’t accidentally have 2 ‘d’ variables and can rename one with a subscript).
• Write a simple sentence or phrase explaining what method/approach you will be using to solve the problem.
• For example: ‘use method of joints’, or equilibrium equations for a rigid body, MMOI for a certain shape, etc.
• This is going to be more important when you get to the later chapters and especially next semester in Dynamics where you can solve the same problem many ways. Might as well practice now!
• This is the actual solving step. This is where you show all the work you have done to solve the problem.
• When you get an answer, restate the variable you are solving for, include the unit, and put a box around the answer.
• Write a simple sentence explaining why (or why not) your answer makes sense. Use logic and common sense for this step.
• When possible, use a second quick numerical analysis to verify your answer. This is the “gut check” to do a quick calculation to ensure your answer is reasonable.
• This is the most confusing step as students often don’t know what to put here and up just writing ‘The number looks reasonable’. This step is vitally important to help you learn how to think about your answer. What does that number mean? What is it close to? For example, if you find that x = 4000 m, that’s a very large distance! In the review, I would say, ‘the object is 4 km long which is reasonable for a long bridge’. See how this is compared to something similar? Or you could do a second calculation to verify the number is correct, such as adding up multiple parts of the problem to confirm the total length is accurate i.e. ‘x + y + z = total, yes it works!’

Additional notes for this course:

• It’s important to include the number and label the steps so it’s clear what you’re doing, as shown in the example below.
• It’s okay if you make mistakes, just put a line through it and keep going.
• Remember your header should include your name, the page number, total number of pages, the course number, and the assignment number. If a problem spans a number of pages, you should include it in the header too.

Key Takeaways

Basically: Use a 6-step structured problem solving process: 1. Problem, 2. Draw, 3. Known & Unknown, 4. Approach, 5. Analysis (Solve), 6. Review

Application: In your future job there is likely a structure for analysis reports that will be used. Each company has a different approach, but most have a standard that should be followed. This is good practice.

Looking ahead: This will be part of every homework assignment.

Written by Gayla & Libby

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3.3: Creative Problem-Solving Process

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LEARNING OBJECTIVES

By the end of this section, you will be able to:

• Describe the five steps in the creative problem-solving process
• Identify and describe common creative problem-solving tools

Creativity can be an important trait of an entrepreneur. In that discussion, we learned about creativity’s role in innovation . Here, we will look in more depth at creativity’s role in problem-solving . Let’s first formally define creativity as the development of original ideas to solve an issue. The intent of being an entrepreneur is to break away from practical norms and use imagination to embrace quick and effective solutions to an existing problem, usually outside the corporate environment.

The Steps of the Creative Problem-Solving Process

Training oneself to think like an entrepreneur means learning the steps to evaluating a challenge: clarify, ideate, develop, implement, and evaluate (Figure 3.3.1).

Step 1: Clarify

To clarify is the critical step of recognizing the existence of a gap between the current state and a desired state. This can also be thought of as having need awareness , which occurs when the entrepreneur notes a gap between societal or customer needs and actual circumstances. Clarifying the problem by speaking with clients and developing a detailed description of the problem brings the specifics of a problem to light. Failure to identify the specifics of a problem leaves the entrepreneur with the impossible task of solving a ghost problem, a problem that is fully unknown or unseen. To establish and maintain credibility, an entrepreneur must clarify the problem by focusing on solving the problem itself, rather than solving a symptom of the problem.

For example, a farm could have polluted water, but it would not be enough to solve the problem only on that farm. Clarifying would involve identifying the source of the pollution to adequately tackle the problem. After gaining an understanding of a problem, the entrepreneur should begin to formulate plans for eliminating the gap. A fishbone diagram, as shown in Figure 3.3.2, is a tool that can be used to identify the causes of such a problem.

In the case of our water pollution example, a fishbone diagram exploring the issue might reveal the items shown in Figure 3.3.3.

Step 2: Ideate

To ideate is the step of the creative problem-solving process that involves generating and detailing ideas by the entrepreneur. After collecting all information relevant to the problem, the entrepreneur lists as many causes of the problem as possible. This is the step in which the largest variety of ideas are put forth. Each idea must be evaluated for feasibility and cost as a solution to the problem. If a farm does not have clean water, for example, the entrepreneur must list causes of toxic water and eliminate as many of those causes as possible. The entrepreneur must then move forward investigating solutions to bring the water back to a safe state. If, say, nearby livestock are polluting the water, the livestock should be isolated from the water source.

Step 3: Develop

To develop is the step in which the entrepreneur takes the list of ideas generated and tests each solution for feasibility. The entrepreneur must consider the cost of each idea and the obstacles to implementation. In the preceding example, adding a chemical to the water may not be a feasible solution to the farmer. Not every farmer wants additional chloride or fluoride added to the water due to the effect on both humans and livestock. These tradeoffs should be addressed in the feasibility assessment. The farmer might prefer a filtration system, but the cost of that solution might not be practicable. The entrepreneur should identify and assess alternative solutions to find one that is most cost-effective and feasible to the customer.

Step 4: Implement

To implement is the step in which the solution to the problem is tested and evaluated. The entrepreneur walks through the planned implementation with the client and tests each part of the solution, if a service, or thoroughly tests a developed good. The entrepreneur implements the solution and goes through a structured system of follow-up to ensure the solution remains effective and viable. In the water example, the solution would be reducing runoff from toxic insecticides by adding prairie strips, buffers of grass, and vegetation along banks of streams.

Step 5: Evaluate

To evaluate is the step in which the final solution is assessed. This is a very important step that entrepreneurs often overlook. Any fallacy in the implementation of the product or service is reassessed, and new solutions are implemented. A continual testing process may be needed to find the final solution. The prairie strips, buffers of grass, and vegetation along banks of streams chosen in the farming water example should then be analyzed and tested to ensure the chosen solution changed the content of the water.

ARE YOU READY?

Implementing Creative Problem Solving

Removing waste is a problem, and it can also present an entrepreneurial opportunity. Try to examine ways in which waste products that you usually pay to have hauled away can now generate revenue. Whether it’s recycling aluminum cans or cardboard, or garbage that could be used to feed animals, your task is to come up with solutions to this entrepreneurial-oriented problem.

• Try following the first step of the creative problem-solving process and clearly identify the problem.
• Next, gather data and formulate the challenge.
• Then, explore ideas and come up with solutions.
• Develop a plan of action.
• Finally, note how you would evaluate the effectiveness of your solution.

Using Creativity to Solve Problems

Entrepreneurs are faced with solving many problems as they develop their ideas for filling gaps, whether those opportunities involve establishing a new company or starting a new enterprise within an existing company. Some of these problems include staffing, hiring and managing employees, handling legal compliance, funding, marketing, and paying taxes. Beyond the mundane activities listed, the entrepreneur, or the team that the entrepreneur puts in place, is indispensable in maintaining the ongoing creativity behind the product line or service offered. Innovation and creativity in the business are necessary to expand the product line or develop a groundbreaking service.

It is not necessary for the entrepreneur to feel isolated when it comes to finding creative solutions to a problem. There are societies, tools, and new methods available to spur the creativity of the entrepreneur that will further support the success and expansion of a new enterprise. 14 Learning and using entrepreneurial methods to solve problems alleviates the stress many startup owners feel. The entrepreneur’s creativity will increase using collaborative methodologies. Some entrepreneurial collaborative methodologies include crowdsourcing, brainstorming, storyboarding, conducting quick online surveys to test ideas and concepts, and team creativity activities.

Crowdsourcing

Professor Daren Brabham at the University of Southern California has written books on crowdsourcing and touts its potential in for-profit and not-for-profit business sectors. He defines it simply as “an online, distributed problem-solving and production model.” 15 Crowdsourcing involves teams of amateurs and nonexperts working together to form a solution to a problem. 16 The idea, as cbsnews.com’s Jennifer Alsever has put it, is to “tap into the collective intelligence of the public at large to complete business-related tasks that a company would normally either perform itself or outsource to a third-party provider. Yet free labor is only a narrow part of crowdsourcing's appeal. More importantly, it enables managers to expand the size of their talent pool while also gaining deeper insight into what customers really want. The challenge is to take a cautionary approach to the ‘wisdom of the crowd,’ which can lead to a ‘herd’ mentality.” 17

LINK TO LEARNING

Read this article that discusses what crowdsourcing is, how to use it, and its benefits for more information.

This new business prototype, similar to outsourcing, features an enterprise posting a problem online and asking for volunteers to consider the problem and propose solutions. Volunteers earn a reward, such as prize money, promotional materials like a T-shirt, royalties on creative outlets like photos or designs, and in some cases, compensation for their labor. Before proposing the solution, volunteers learn that the solutions become the intellectual property of the startup posting the problem. The solution is then mass-produced for profit by the startup that posted the problem. 18 The process evolves into the crowdsourcing process after the enterprise mass produces and profits from the labor of the volunteers and the team. Entrepreneurs should consider that untapped masses have solutions for many issues for which agendas do not yet exist. Crowdsourcing can exploit those agendas and add to the tools used to stimulate personal creativity. This type of innovation is planned and strategically implemented for profit.

For example, Bombardier held a crowdsourced innovation contest to solicit input on the future of train interiors, including seat design and coach class interior. A corporate jury judged the submissions, with the top ten receiving computers or cash prizes. Companies are often constrained, however, by internal rules limiting open source or external idea sourcing, as they could be accused of “stealing” an idea. While crowdsourcing outside of software can be problematic, some products such as MakerBot’s 3D printers, 3DR’s drones, and Jibo’s Social Robot have used developer kits and “makers” to help build a community and stimulate innovation from the outside.

WORK IT OUT

A Crowdsourced Potato Chip

In an effort to increase sales among millennials, PepsiCo turned to crowdsourcing to get new flavor ideas for their Lay’s potato chips (called Walker’s in the UK). Their 2012 campaign, “Do Us a Flavor,” was so successful that they received over 14 million submissions. The winner was Cheesy Garlic Bread, which increased their potato chip sales by 8 percent during the first three months after the launch.

• What are some other products that would work well for a crowdsourced campaign contest?
• What items wouldn’t work well?

Amazon’s Mechanical Turk is an online crowdsourcing platform that allows individuals to post tasks for workers to complete. In many instances, these tasks are compensated, but the payment can be less than one dollar per item completed. Mechanical Turk is one of the largest and most well-known crowdsourcing platforms, but there are a number of other more niche ones as well that would apply to smaller markets. In the case of innovation contests and outsourced tasks from corporations, those tasks may be hosted internally by the corporation.

Brainstorming

Brainstorming is the generation of ideas in an environment free of judgment or dissension with the goal of creating solutions. Brainstorming is meant to stimulate participants into thinking about problem-solving in a new way. Using a multifunctional group, meaning participants come from different departments and with different skill sets, gives entrepreneurs and support teams a genuine chance to suggest and actualize ideas. The group works together to refine and prototype potential solutions to a problem.

Brainstorming is a highly researched and often practiced technique for the development of innovative solutions. One of the more successful proponents of brainstorming is the United Nations Children’s Fund (UNICEF). UNICEF faces unique problems of solving resource problems for mothers and children in underdeveloped nations. See how UNICEF practices brainstorming to solve problems including child survival, gender inclusion, refugee crises, education, and others.

The setting for a brainstorming session should remain as informal and relaxed as possible. The group needs to avoid standard solutions. All ideas are welcome and listed and considered with no censorship and with no regard to administrative restrictions. All team members have an equal voice. The focus of brainstorming is on quantity of ideas rather than on the ideal solution provided in every suggestion. A classic entrepreneurial brainstorming activity, as popularized by business software developer Strategyzer, is known as the “silly cow” exercise. Teams come up with ideas for new business models pertaining to a cow, with the results often outrageous, ranging from sponsored cows to stroking cows for therapeutic release. Participants are asked to identify some aspect of a cow and develop three business models around that concept in a short time period, typically two minutes or fewer. The activity is designed to get creative juices flowing.

Watch this video from ABC’s Nightline that shows how IDEO designed a new shopping cart for an example of a design process that involves brainstorming.

Storyboarding

Storyboarding is the process of presenting an idea in a step-by-step graphic format, as Figure 3.3.4 shows. This tool is useful when the entrepreneur is attempting to visualize a solution to a problem. The steps to the solution of a problem are sketched and hung in graphic format. Once the original graphic is placed, images of steps working toward a solution are added, subtracted, and rearranged on a continual basis, until the ultimate solution emerges in the ultimate graphic format. For many years, entrepreneurs have used this process to create a pre-visual for various media sequences.

Team Creativity

Team creativity is the process whereby an entrepreneur works with a team to create an unexpected solution for an issue or challenge. Teams progress through the same creative problem-solving process described already: clarify, ideate, develop, implement, and evaluate. The main advantage of team creativity is the collaboration and support members receive from one another. Great teams trust in other team members, have diverse members with diverse points of view, are cohesive, and have chemistry.

Team members should work in a stress-free and relaxing environment. Reinforcement and expansion of ideas in the team environment motivates the team to continually expand horizons toward problem solution. A small idea in a team may spark the imagination of a team member to an original idea. Mark Zuckerberg, co-founder of Facebook, once said, “The most important thing for you as an entrepreneur trying to build something is, you need to build a really good team. And that’s what I spend all my time on.” 19

ENTREPRENEUR IN ACTION

Taaluma Totes 20

Young entrepreneurs Jack DuFour and Alley Heffern began to notice the beautiful fabrics that came from the different countries they visited. The entrepreneurs thought about what could be done with the fabrics to create employment opportunities both in the country from which the fabric originated and in their home base of Virginia. They decided to test producing totes from the fabrics they found and formed Taaluma Totes (Figure 3.3.5). DuFour and Heffern also wanted to promote the production of these fabrics and help underserved populations in countries where the fabric originated maintain a living or follow a dream.

The team continued to test the process and gathered original fabrics, which they sent to Virginia to create totes. They trained individuals with disabilities in Virginia to manufacture the totes, thus serving populations in the United States. The entrepreneurs then decided to take 20 percent of their profits and make microloans to farmers and small business owners in the countries where the fabric originated to create jobs there. Microloans are small loans, below $50,000, which certain lenders offer to enterprising startups. These startups, for various reasons (they are in poor nations, at the poverty level), can’t afford a traditional loan from a major bank. The lenders offer business support to the borrower, which in turn helps the borrower repay the microloan. The microloans from Taaluma are repaid when the borrower is able. Repayments are used to buy more fabric, completing Taaluma’s desire to serve dual populations. If the process proved unsuccessful, the co-owners would revise the process to meet the plan’s requirements.

DuFour and Heffern now have fabrics from dozens of countries from Thailand to Ecuador. The totes are specialized with features to meet individual needs. The product line is innovated regularly and Taaluma Totes serves a dual purpose of employing persons with disabilities in Virginia and creating employment for underserved populations in other countries.

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Ideas Made to Matter

Design thinking, explained

Rebecca Linke

Sep 14, 2017

What is design thinking?

Design thinking is an innovative problem-solving process rooted in a set of skills.The approach has been around for decades, but it only started gaining traction outside of the design community after the 2008 Harvard Business Review article [subscription required] titled “Design Thinking” by Tim Brown, CEO and president of design company IDEO.

Since then, the design thinking process has been applied to developing new products and services, and to a whole range of problems, from creating a business model for selling solar panels in Africa to the operation of Airbnb .

At a high level, the steps involved in the design thinking process are simple: first, fully understand the problem; second, explore a wide range of possible solutions; third, iterate extensively through prototyping and testing; and finally, implement through the customary deployment mechanisms. 

The skills associated with these steps help people apply creativity to effectively solve real-world problems better than they otherwise would. They can be readily learned, but take effort. For instance, when trying to understand a problem, setting aside your own preconceptions is vital, but it’s hard.

Creative brainstorming is necessary for developing possible solutions, but many people don’t do it particularly well. And throughout the process it is critical to engage in modeling, analysis, prototyping, and testing, and to really learn from these many iterations.

Once you master the skills central to the design thinking approach, they can be applied to solve problems in daily life and any industry.

Here’s what you need to know to get started.

Understand the problem 

The first step in design thinking is to understand the problem you are trying to solve before searching for solutions. Sometimes, the problem you need to address is not the one you originally set out to tackle.

“Most people don’t make much of an effort to explore the problem space before exploring the solution space,” said MIT Sloan professor Steve Eppinger. The mistake they make is to try and empathize, connecting the stated problem only to their own experiences. This falsely leads to the belief that you completely understand the situation. But the actual problem is always broader, more nuanced, or different than people originally assume.

Take the example of a meal delivery service in Holstebro, Denmark. When a team first began looking at the problem of poor nutrition and malnourishment among the elderly in the city, many of whom received meals from the service, it thought that simply updating the menu options would be a sufficient solution. But after closer observation, the team realized the scope of the problem was much larger , and that they would need to redesign the entire experience, not only for those receiving the meals, but for those preparing the meals as well. While the company changed almost everything about itself, including rebranding as The Good Kitchen, the most important change the company made when rethinking its business model was shifting how employees viewed themselves and their work. That, in turn, helped them create better meals (which were also drastically changed), yielding happier, better nourished customers.

Involve users

Imagine you are designing a new walker for rehabilitation patients and the elderly, but you have never used one. Could you fully understand what customers need? Certainly not, if you haven’t extensively observed and spoken with real customers. There is a reason that design thinking is often referred to as human-centered design.

“You have to immerse yourself in the problem,” Eppinger said.

How do you start to understand how to build a better walker? When a team from MIT’s Integrated Design and Management program together with the design firm Altitude took on that task, they met with walker users to interview them, observe them, and understand their experiences.  

“We center the design process on human beings by understanding their needs at the beginning, and then include them throughout the development and testing process,” Eppinger said.

Central to the design thinking process is prototyping and testing (more on that later) which allows designers to try, to fail, and to learn what works. Testing also involves customers, and that continued involvement provides essential user feedback on potential designs and use cases. If the MIT-Altitude team studying walkers had ended user involvement after its initial interviews, it would likely have ended up with a walker that didn’t work very well for customers. 

It is also important to interview and understand other stakeholders, like people selling the product, or those who are supporting the users throughout the product life cycle.

The second phase of design thinking is developing solutions to the problem (which you now fully understand). This begins with what most people know as brainstorming.

Hold nothing back during brainstorming sessions — except criticism. Infeasible ideas can generate useful solutions, but you’d never get there if you shoot down every impractical idea from the start.

“One of the key principles of brainstorming is to suspend judgment,” Eppinger said. “When we're exploring the solution space, we first broaden the search and generate lots of possibilities, including the wild and crazy ideas. Of course, the only way we're going to build on the wild and crazy ideas is if we consider them in the first place.”

That doesn’t mean you never judge the ideas, Eppinger said. That part comes later, in downselection. “But if we want 100 ideas to choose from, we can’t be very critical.”

In the case of The Good Kitchen, the kitchen employees were given new uniforms. Why? Uniforms don’t directly affect the competence of the cooks or the taste of the food.

But during interviews conducted with kitchen employees, designers realized that morale was low, in part because employees were bored preparing the same dishes over and over again, in part because they felt that others had a poor perception of them. The new, chef-style uniforms gave the cooks a greater sense of pride. It was only part of the solution, but if the idea had been rejected outright, or perhaps not even suggested, the company would have missed an important aspect of the solution.

Prototype and test. Repeat.

You’ve defined the problem. You’ve spoken to customers. You’ve brainstormed, come up with all sorts of ideas, and worked with your team to boil those ideas down to the ones you think may actually solve the problem you’ve defined.

“We don’t develop a good solution just by thinking about a list of ideas, bullet points and rough sketches,” Eppinger said. “We explore potential solutions through modeling and prototyping. We design, we build, we test, and repeat — this design iteration process is absolutely critical to effective design thinking.”

Repeating this loop of prototyping, testing, and gathering user feedback is crucial for making sure the design is right — that is, it works for customers, you can build it, and you can support it.

“After several iterations, we might get something that works, we validate it with real customers, and we often find that what we thought was a great solution is actually only just OK. But then we can make it a lot better through even just a few more iterations,” Eppinger said.

Implementation

The goal of all the steps that come before this is to have the best possible solution before you move into implementing the design. Your team will spend most of its time, its money, and its energy on this stage.

“Implementation involves detailed design, training, tooling, and ramping up. It is a huge amount of effort, so get it right before you expend that effort,” said Eppinger.

Design thinking isn’t just for “things.” If you are only applying the approach to physical products, you aren’t getting the most out of it. Design thinking can be applied to any problem that needs a creative solution. When Eppinger ran into a primary school educator who told him design thinking was big in his school, Eppinger thought he meant that they were teaching students the tenets of design thinking.

“It turns out they meant they were using design thinking in running their operations and improving the school programs. It’s being applied everywhere these days,” Eppinger said.

In another example from the education field, Peruvian entrepreneur Carlos Rodriguez-Pastor hired design consulting firm IDEO to redesign every aspect of the learning experience in a network of schools in Peru. The ultimate goal? To elevate Peru’s middle class.

As you’d expect, many large corporations have also adopted design thinking. IBM has adopted it at a company-wide level, training many of its nearly 400,000 employees in design thinking principles .

What can design thinking do for your business?

The impact of all the buzz around design thinking today is that people are realizing that “anybody who has a challenge that needs creative problem solving could benefit from this approach,” Eppinger said. That means that managers can use it, not only to design a new product or service, “but anytime they’ve got a challenge, a problem to solve.”

Applying design thinking techniques to business problems can help executives across industries rethink their product offerings, grow their markets, offer greater value to customers, or innovate and stay relevant. “I don’t know industries that can’t use design thinking,” said Eppinger.

Ready to go deeper?

Read “ The Designful Company ” by Marty Neumeier, a book that focuses on how businesses can benefit from design thinking, and “ Product Design and Development ,” co-authored by Eppinger, to better understand the detailed methods.

Register for an MIT Sloan Executive Education course:

Systematic Innovation of Products, Processes, and Services , a five-day course taught by Eppinger and other MIT professors.

• Leadership by Design: Innovation Process and Culture , a two-day course taught by MIT Integrated Design and Management director Matthew Kressy.
• Managing Complex Technical Projects , a two-day course taught by Eppinger.
• Apply for M astering Design Thinking , a 3-month online certificate course taught by Eppinger and MIT Sloan senior lecturers Renée Richardson Gosline and David Robertson.

Steve Eppinger is a professor of management science and innovation at MIT Sloan. He holds the General Motors Leaders for Global Operations Chair and has a PhD from MIT in engineering. He is the faculty co-director of MIT's System Design and Management program and Integrated Design and Management program, both master’s degrees joint between the MIT Sloan and Engineering schools. His research focuses on product development and technical project management, and has been applied to improving complex engineering processes in many industries.

Read next: 10 agile ideas worth sharing

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What Is Creative Problem-Solving & Why Is It Important?

• 01 Feb 2022

One of the biggest hindrances to innovation is complacency—it can be more comfortable to do what you know than venture into the unknown. Business leaders can overcome this barrier by mobilizing creative team members and providing space to innovate.

There are several tools you can use to encourage creativity in the workplace. Creative problem-solving is one of them, which facilitates the development of innovative solutions to difficult problems.

Here’s an overview of creative problem-solving and why it’s important in business.

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What Is Creative Problem-Solving?

Research is necessary when solving a problem. But there are situations where a problem’s specific cause is difficult to pinpoint. This can occur when there’s not enough time to narrow down the problem’s source or there are differing opinions about its root cause.

In such cases, you can use creative problem-solving , which allows you to explore potential solutions regardless of whether a problem has been defined.

Creative problem-solving is less structured than other innovation processes and encourages exploring open-ended solutions. It also focuses on developing new perspectives and fostering creativity in the workplace . Its benefits include:

• Finding creative solutions to complex problems : User research can insufficiently illustrate a situation’s complexity. While other innovation processes rely on this information, creative problem-solving can yield solutions without it.
• Adapting to change : Business is constantly changing, and business leaders need to adapt. Creative problem-solving helps overcome unforeseen challenges and find solutions to unconventional problems.
• Fueling innovation and growth : In addition to solutions, creative problem-solving can spark innovative ideas that drive company growth. These ideas can lead to new product lines, services, or a modified operations structure that improves efficiency.

Creative problem-solving is traditionally based on the following key principles :

1. Balance Divergent and Convergent Thinking

Creative problem-solving uses two primary tools to find solutions: divergence and convergence. Divergence generates ideas in response to a problem, while convergence narrows them down to a shortlist. It balances these two practices and turns ideas into concrete solutions.

2. Reframe Problems as Questions

By framing problems as questions, you shift from focusing on obstacles to solutions. This provides the freedom to brainstorm potential ideas.

3. Defer Judgment of Ideas

When brainstorming, it can be natural to reject or accept ideas right away. Yet, immediate judgments interfere with the idea generation process. Even ideas that seem implausible can turn into outstanding innovations upon further exploration and development.

4. Focus on "Yes, And" Instead of "No, But"

Using negative words like "no" discourages creative thinking. Instead, use positive language to build and maintain an environment that fosters the development of creative and innovative ideas.

Creative Problem-Solving and Design Thinking

Whereas creative problem-solving facilitates developing innovative ideas through a less structured workflow, design thinking takes a far more organized approach.

Design thinking is a human-centered, solutions-based process that fosters the ideation and development of solutions. In the online course Design Thinking and Innovation , Harvard Business School Dean Srikant Datar leverages a four-phase framework to explain design thinking.

The four stages are:

• Clarify: The clarification stage allows you to empathize with the user and identify problems. Observations and insights are informed by thorough research. Findings are then reframed as problem statements or questions.
• Ideate: Ideation is the process of coming up with innovative ideas. The divergence of ideas involved with creative problem-solving is a major focus.
• Develop: In the development stage, ideas evolve into experiments and tests. Ideas converge and are explored through prototyping and open critique.
• Implement: Implementation involves continuing to test and experiment to refine the solution and encourage its adoption.

Creative problem-solving primarily operates in the ideate phase of design thinking but can be applied to others. This is because design thinking is an iterative process that moves between the stages as ideas are generated and pursued. This is normal and encouraged, as innovation requires exploring multiple ideas.

Creative Problem-Solving Tools

While there are many useful tools in the creative problem-solving process, here are three you should know:

Creating a Problem Story

One way to innovate is by creating a story about a problem to understand how it affects users and what solutions best fit their needs. Here are the steps you need to take to use this tool properly.

1. Identify a UDP

Create a problem story to identify the undesired phenomena (UDP). For example, consider a company that produces printers that overheat. In this case, the UDP is "our printers overheat."

2. Move Forward in Time

To move forward in time, ask: “Why is this a problem?” For example, minor damage could be one result of the machines overheating. In more extreme cases, printers may catch fire. Don't be afraid to create multiple problem stories if you think of more than one UDP.

3. Move Backward in Time

To move backward in time, ask: “What caused this UDP?” If you can't identify the root problem, think about what typically causes the UDP to occur. For the overheating printers, overuse could be a cause.

Following the three-step framework above helps illustrate a clear problem story:

• The printer is overused.
• The printer overheats.
• The printer breaks down.

You can extend the problem story in either direction if you think of additional cause-and-effect relationships.

4. Break the Chains

By this point, you’ll have multiple UDP storylines. Take two that are similar and focus on breaking the chains connecting them. This can be accomplished through inversion or neutralization.

• Inversion: Inversion changes the relationship between two UDPs so the cause is the same but the effect is the opposite. For example, if the UDP is "the more X happens, the more likely Y is to happen," inversion changes the equation to "the more X happens, the less likely Y is to happen." Using the printer example, inversion would consider: "What if the more a printer is used, the less likely it’s going to overheat?" Innovation requires an open mind. Just because a solution initially seems unlikely doesn't mean it can't be pursued further or spark additional ideas.
• Neutralization: Neutralization completely eliminates the cause-and-effect relationship between X and Y. This changes the above equation to "the more or less X happens has no effect on Y." In the case of the printers, neutralization would rephrase the relationship to "the more or less a printer is used has no effect on whether it overheats."

Even if creating a problem story doesn't provide a solution, it can offer useful context to users’ problems and additional ideas to be explored. Given that divergence is one of the fundamental practices of creative problem-solving, it’s a good idea to incorporate it into each tool you use.

Brainstorming

Brainstorming is a tool that can be highly effective when guided by the iterative qualities of the design thinking process. It involves openly discussing and debating ideas and topics in a group setting. This facilitates idea generation and exploration as different team members consider the same concept from multiple perspectives.

Hosting brainstorming sessions can result in problems, such as groupthink or social loafing. To combat this, leverage a three-step brainstorming method involving divergence and convergence :

• Have each group member come up with as many ideas as possible and write them down to ensure the brainstorming session is productive.
• Continue the divergence of ideas by collectively sharing and exploring each idea as a group. The goal is to create a setting where new ideas are inspired by open discussion.
• Begin the convergence of ideas by narrowing them down to a few explorable options. There’s no "right number of ideas." Don't be afraid to consider exploring all of them, as long as you have the resources to do so.

Alternate Worlds

The alternate worlds tool is an empathetic approach to creative problem-solving. It encourages you to consider how someone in another world would approach your situation.

For example, if you’re concerned that the printers you produce overheat and catch fire, consider how a different industry would approach the problem. How would an automotive expert solve it? How would a firefighter?

Be creative as you consider and research alternate worlds. The purpose is not to nail down a solution right away but to continue the ideation process through diverging and exploring ideas.

Continue Developing Your Skills

Whether you’re an entrepreneur, marketer, or business leader, learning the ropes of design thinking can be an effective way to build your skills and foster creativity and innovation in any setting.

If you're ready to develop your design thinking and creative problem-solving skills, explore Design Thinking and Innovation , one of our online entrepreneurship and innovation courses. If you aren't sure which course is the right fit, download our free course flowchart to determine which best aligns with your goals.

About the Author

Browse Course Material

Course info, instructors.

• Teaching and Learning Laboratory (TLL)
• Singapore University of Technology and Design (SUTD)

Departments

• Supplemental Resources

As Taught In

• Engineering
• Differential Equations
• Communication

Learning Resource Types

Stem concept videos, problem solving process.

This video presents students with a problem solving process that they might find useful in solving ill defined problems. Students see how this problem solving process was used by MIT graduate students to complete a class project.

Learning Objectives

After watching this video students will be able to:

• Identify the steps of the problem solving process.
• Recognize that the problem solving process is iterative.

Funding provided by the Singapore University of Technology and Design (SUTD)

Developed by the Teaching and Learning Laboratory (TLL) at MIT for SUTD

• Download video
• Download transcript

Instructor Guide

Problem Solving Process Instructor Guide (PDF)

It is highly recommended that the video is paused when prompted so that students are able to attempt the activities on their own and then check their solutions against the video.

During the video, students will think about their approach to problem solving.

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What Is Problem Solving?

You will often see beach clean-up drives being publicized in coastal cities. There are already dustbins available on the beaches,…

You will often see beach clean-up drives being publicized in coastal cities. There are already dustbins available on the beaches, so why do people need to organize these drives? It’s evident that despite advertising and posting anti-littering messages, some of us don’t follow the rules.

Temporary food stalls and shops make it even more difficult to keep the beaches clean. Since people can’t ask the shopkeepers to relocate or prevent every single person from littering, the clean-up drive is needed.  This is an ideal example of problem-solving psychology in humans. ( 230-fifth.com ) So, what is problem-solving? Let’s find out.

What Is Problem-Solving?

At its simplest, the meaning of problem-solving is the process of defining a problem, determining its cause, and implementing a solution. The definition of problem-solving is rooted in the fact that as humans, we exert control over our environment through solutions. We move forward in life when we solve problems and make decisions. 

We can better define the problem-solving process through a series of important steps.

Identify The Problem: 

This step isn’t as simple as it sounds. Most times, we mistakenly identify the consequences of a problem rather than the problem itself. It’s important that we’re careful to identify the actual problem and not just its symptoms. 

Define The Problem: 

Once the problem has been identified correctly, you should define it. This step can help clarify what needs to be addressed and for what purpose.

Form A Strategy: 

Develop a strategy to solve your problem. Defining an approach will provide direction and clarity on the next steps. 

Organize The Information:  

Organizing information systematically will help you determine whether something is missing. The more information you have, the easier it’ll become for you to arrive at a solution.  

Allocate Resources:  

We may not always be armed with the necessary resources to solve a problem. Before you commit to implementing a solution for a problem, you should determine the availability of different resources—money, time and other costs.

Track Progress: 

The true meaning of problem-solving is to work towards an objective. If you measure your progress, you can evaluate whether you’re on track. You could revise your strategies if you don’t notice the desired level of progress. 

Evaluate The Results:  

After you spot a solution, evaluate the results to determine whether it’s the best possible solution. For example, you can evaluate the success of a fitness routine after several weeks of exercise.

Meaning Of Problem-Solving Skill

Now that we’ve established the definition of problem-solving psychology in humans, let’s look at how we utilize our problem-solving skills.  These skills help you determine the source of a problem and how to effectively determine the solution. Problem-solving skills aren’t innate and can be mastered over time. Here are some important skills that are beneficial for finding solutions.

Communication

Communication is a critical skill when you have to work in teams.  If you and your colleagues have to work on a project together, you’ll have to collaborate with each other. In case of differences of opinion, you should be able to listen attentively and respond respectfully in order to successfully arrive at a solution.

As a problem-solver, you need to be able to research and identify underlying causes. You should never treat a problem lightly. In-depth study is imperative because often people identify only the symptoms and not the actual problem.

Once you have researched and identified the factors causing a problem, start working towards developing solutions. Your analytical skills can help you differentiate between effective and ineffective solutions.

Decision-Making

You’ll have to make a decision after you’ve identified the source and methods of solving a problem. If you’ve done your research and applied your analytical skills effectively, it’ll become easier for you to take a call or a decision.

Organizations really value decisive problem-solvers. Harappa Education’s   Defining Problems course will guide you on the path to developing a problem-solving mindset. Learn how to identify the different types of problems using the Types of Problems framework. Additionally, the SMART framework, which is a five-point tool, will teach you to create specific and actionable objectives to address problem statements and arrive at solutions. 

Explore topics & skills such as Problem Solving Skills , PICK Chart , How to Solve Problems & Barriers to Problem Solving from our Harappa Diaries blog section and develop your skills.

7.1 What Is Cognition?

Learning objectives.

By the end of this section, you will be able to:

• Describe cognition
• Distinguish concepts and prototypes
• Explain the difference between natural and artificial concepts
• Describe how schemata are organized and constructed

Imagine all of your thoughts as if they were physical entities, swirling rapidly inside your mind. How is it possible that the brain is able to move from one thought to the next in an organized, orderly fashion? The brain is endlessly perceiving, processing, planning, organizing, and remembering—it is always active. Yet, you don’t notice most of your brain’s activity as you move throughout your daily routine. This is only one facet of the complex processes involved in cognition. Simply put, cognition is thinking, and it encompasses the processes associated with perception, knowledge, problem solving, judgment, language, and memory. Scientists who study cognition are searching for ways to understand how we integrate, organize, and utilize our conscious cognitive experiences without being aware of all of the unconscious work that our brains are doing (for example, Kahneman, 2011).

Upon waking each morning, you begin thinking—contemplating the tasks that you must complete that day. In what order should you run your errands? Should you go to the bank, the cleaners, or the grocery store first? Can you get these things done before you head to class or will they need to wait until school is done? These thoughts are one example of cognition at work. Exceptionally complex, cognition is an essential feature of human consciousness, yet not all aspects of cognition are consciously experienced.

Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem solving, in addition to other cognitive processes. Cognitive psychologists strive to determine and measure different types of intelligence, why some people are better at problem solving than others, and how emotional intelligence affects success in the workplace, among countless other topics. They also sometimes focus on how we organize thoughts and information gathered from our environments into meaningful categories of thought, which will be discussed later.

Concepts and Prototypes

The human nervous system is capable of handling endless streams of information. The senses serve as the interface between the mind and the external environment, receiving stimuli and translating it into nervous impulses that are transmitted to the brain. The brain then processes this information and uses the relevant pieces to create thoughts, which can then be expressed through language or stored in memory for future use. To make this process more complex, the brain does not gather information from external environments only. When thoughts are formed, the mind synthesizes information from emotions and memories ( Figure 7.2 ). Emotion and memory are powerful influences on both our thoughts and behaviors.

In order to organize this staggering amount of information, the mind has developed a "file cabinet" of sorts. The different files stored in the file cabinet are called concepts. Concepts are categories or groupings of linguistic information, images, ideas, or memories, such as life experiences. Concepts are, in many ways, big ideas that are generated by observing details, and categorizing and combining these details into cognitive structures. You use concepts to see the relationships among the different elements of your experiences and to keep the information in your mind organized and accessible.

Concepts are informed by our semantic memory (you will learn more about semantic memory in a later chapter) and are present in every aspect of our lives; however, one of the easiest places to notice concepts is inside a classroom, where they are discussed explicitly. When you study United States history, for example, you learn about more than just individual events that have happened in America’s past. You absorb a large quantity of information by listening to and participating in discussions, examining maps, and reading first-hand accounts of people’s lives. Your brain analyzes these details and develops an overall understanding of American history. In the process, your brain gathers details that inform and refine your understanding of related concepts such as war, the judicial system, and voting rights and laws.

Concepts can be complex and abstract, like justice, or more concrete, like types of birds. In psychology, for example, Piaget’s stages of development are abstract concepts. Some concepts, like tolerance, are agreed upon by many people, because they have been used in various ways over many years. Other concepts, like the characteristics of your ideal friend or your family’s birthday traditions, are personal and individualized. In this way, concepts touch every aspect of our lives, from our many daily routines to the guiding principles behind the way governments function.

Another technique used by your brain to organize information is the identification of prototypes for the concepts you have developed. A prototype is the best example or representation of a concept. For example, what comes to your mind when you think of a dog? Most likely your early experiences with dogs will shape what you imagine. If your first pet was a Golden Retriever, there is a good chance that this would be your prototype for the category of dogs.

Natural and Artificial Concepts

In psychology, concepts can be divided into two categories, natural and artificial. Natural concepts are created “naturally” through your experiences and can be developed from either direct or indirect experiences. For example, if you live in Essex Junction, Vermont, you have probably had a lot of direct experience with snow. You’ve watched it fall from the sky, you’ve seen lightly falling snow that barely covers the windshield of your car, and you’ve shoveled out 18 inches of fluffy white snow as you’ve thought, “This is perfect for skiing.” You’ve thrown snowballs at your best friend and gone sledding down the steepest hill in town. In short, you know snow. You know what it looks like, smells like, tastes like, and feels like. If, however, you’ve lived your whole life on the island of Saint Vincent in the Caribbean, you may never actually have seen snow, much less tasted, smelled, or touched it. You know snow from the indirect experience of seeing pictures of falling snow—or from watching films that feature snow as part of the setting. Either way, snow is a natural concept because you can construct an understanding of it through direct observations, experiences with snow, or indirect knowledge (such as from films or books) ( Figure 7.3 ).

An artificial concept , on the other hand, is a concept that is defined by a specific set of characteristics. Various properties of geometric shapes, like squares and triangles, serve as useful examples of artificial concepts. A triangle always has three angles and three sides. A square always has four equal sides and four right angles. Mathematical formulas, like the equation for area (length × width) are artificial concepts defined by specific sets of characteristics that are always the same. Artificial concepts can enhance the understanding of a topic by building on one another. For example, before learning the concept of “area of a square” (and the formula to find it), you must understand what a square is. Once the concept of “area of a square” is understood, an understanding of area for other geometric shapes can be built upon the original understanding of area. The use of artificial concepts to define an idea is crucial to communicating with others and engaging in complex thought. According to Goldstone and Kersten (2003), concepts act as building blocks and can be connected in countless combinations to create complex thoughts.

A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.

There are several types of schemata. A role schema makes assumptions about how individuals in certain roles will behave (Callero, 1994). For example, imagine you meet someone who introduces himself as a firefighter. When this happens, your brain automatically activates the “firefighter schema” and begins making assumptions that this person is brave, selfless, and community-oriented. Despite not knowing this person, already you have unknowingly made judgments about them. Schemata also help you fill in gaps in the information you receive from the world around you. While schemata allow for more efficient information processing, there can be problems with schemata, regardless of whether they are accurate: Perhaps this particular firefighter is not brave, they just work as a firefighter to pay the bills while studying to become a children’s librarian.

An event schema , also known as a cognitive script , is a set of behaviors that can feel like a routine. Think about what you do when you walk into an elevator ( Figure 7.4 ). First, the doors open and you wait to let exiting passengers leave the elevator car. Then, you step into the elevator and turn around to face the doors, looking for the correct button to push. You never face the back of the elevator, do you? And when you’re riding in a crowded elevator and you can’t face the front, it feels uncomfortable, doesn’t it? Interestingly, event schemata can vary widely among different cultures and countries. For example, while it is quite common for people to greet one another with a handshake in the United States, in Tibet, you greet someone by sticking your tongue out at them, and in Belize, you bump fists (Cairns Regional Council, n.d.)

Because event schemata are automatic, they can be difficult to change. Imagine that you are driving home from work or school. This event schema involves getting in the car, shutting the door, and buckling your seatbelt before putting the key in the ignition. You might perform this script two or three times each day. As you drive home, you hear your phone’s ring tone. Typically, the event schema that occurs when you hear your phone ringing involves locating the phone and answering it or responding to your latest text message. So without thinking, you reach for your phone, which could be in your pocket, in your bag, or on the passenger seat of the car. This powerful event schema is informed by your pattern of behavior and the pleasurable stimulation that a phone call or text message gives your brain. Because it is a schema, it is extremely challenging for us to stop reaching for the phone, even though we know that we endanger our own lives and the lives of others while we do it (Neyfakh, 2013) ( Figure 7.5 ).

Remember the elevator? It feels almost impossible to walk in and not face the door. Our powerful event schema dictates our behavior in the elevator, and it is no different with our phones. Current research suggests that it is the habit, or event schema, of checking our phones in many different situations that makes refraining from checking them while driving especially difficult (Bayer & Campbell, 2012). Because texting and driving has become a dangerous epidemic in recent years, psychologists are looking at ways to help people interrupt the “phone schema” while driving. Event schemata like these are the reason why many habits are difficult to break once they have been acquired. As we continue to examine thinking, keep in mind how powerful the forces of concepts and schemata are to our understanding of the world.

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What are the 7 Steps to Problem-Solving? & Its Examples

7 steps to problem-solving.

7 Steps to Problem-Solving is a systematic process that involves analyzing a situation, generating possible solutions, and implementing the best course of action. While different problem-solving models exist, a common approach often involves the following seven steps:

Define the Problem:

• Clearly articulate and understand the nature of the problem. Define the issue, its scope, and its impact on individuals or the organization.

Gather Information:

• Collect relevant data and information related to the problem. This may involve research, observation, interviews, or any other method to gain a comprehensive understanding.

Generate Possible Solutions:

• Brainstorm and generate a variety of potential solutions to the problem. Encourage creativity and consider different perspectives during this phase.

Evaluate Options:

• Assess the strengths and weaknesses of each potential solution. Consider the feasibility, potential risks, and the likely outcomes associated with each option.

Make a Decision:

• Based on the evaluation, choose the most suitable solution. This decision should align with the goals and values of the individual or organization facing the problem.

Implement the Solution:

• Put the chosen solution into action. Develop an implementation plan, allocate resources, and carry out the necessary steps to address the problem effectively.

Evaluate the Results:

• Assess the outcomes of the implemented solution. Did it solve the problem as intended? What can be learned from the process? Use this information to refine future problem-solving efforts.

It’s important to note that these steps are not always linear and may involve iteration. Problem-solving is often an ongoing process, and feedback from the implementation and evaluation stages may lead to adjustments in the chosen solution or the identification of new issues that need to be addressed.

Problem-Solving Example in Education

• Certainly: Let’s consider a problem-solving example in the context of education.
• Problem: Declining Student Engagement in Mathematics Classes

Background:

A high school has noticed a decline in student engagement and performance in mathematics classes over the past few years. Students seem disinterested, and there is a noticeable decrease in test scores. The traditional teaching methods are not effectively capturing students’ attention, and there’s a need for innovative solutions to rekindle interest in mathematics.

Steps in Problem-Solving

Identify the problem:.

• Clearly define the issue: declining student engagement and performance in mathematics classes.
• Gather data on student performance, attendance, and feedback from teachers and students.

Root Cause Analysis

• Conduct surveys, interviews, and classroom observations to identify the root causes of disengagement.
• Identify potential factors such as teaching methods, curriculum relevance, or lack of real-world applications.

Brainstorm Solutions

• Organize a team of educators, administrators, and even students to brainstorm creative solutions.
• Consider integrating technology, real-world applications, project-based learning, or other interactive teaching methods.

Evaluate and Prioritize Solutions

• Evaluate each solution based on feasibility, cost, and potential impact.
• Prioritize solutions that are likely to address the root causes and have a positive impact on student engagement.

Implement the Chosen Solution

• Develop an action plan for implementing the chosen solution.
• Provide training and resources for teachers to adapt to new teaching methods or technologies.

Monitor and Evaluate

• Continuously monitor the implementation of the solution.
• Collect feedback from teachers and students to assess the effectiveness of the changes.

Adjust as Needed

• Be willing to make adjustments based on ongoing feedback and data analysis.
• Fine-tune the solution to address any unforeseen challenges or issues.

Example Solution

• Introduce a project-based learning approach in mathematics classes, where students work on real-world problems that require mathematical skills.
• Incorporate technology, such as educational apps or interactive simulations, to make learning more engaging.
• Provide professional development for teachers to enhance their skills in implementing these new teaching methods.

Expected Outcomes:

• Increased student engagement and interest in mathematics.
• Improvement in test scores and overall academic performance.
• Positive feedback from both teachers and students.

Final Words

This problem-solving approach in education involves a systematic process of identifying, analyzing, and addressing issues to enhance the learning experience for students.

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