what problem solving entails

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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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."

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Problem-Solving Techniques: A Complete Guide

Problem-Solving Techniques are systematic methods for recognising, evaluating, and resolving issues in an organised way. This blog discusses What are Problem-Solving Techniques, their importance, Basic Problem-Solving Techniques, etc. These skills can enhance your problem-solving skills. Read more to learn further.

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According to Indeed , the average salary of a Problem Solver in the UK is £30,000 per year. Further, in this blog, you will learn about the top 15 Problem-Solving Techniques and their importance. 

Table of Contents  

1) What are Problem-Solving Techniques? 

2) The Importance of Problem-Solving Techniques 

3) Basic Problem-Solving Techniques 

4) Top 20+ Problem-Solving Techniques 

5) Conclusion       

What are Problem-Solving Techniques?  

The Importance of Problem-Solving Techniques  

1) Enhancing decision-making: Effective Problem-Solving Techniques enhance the decision-making process. When individuals face problems, they are encouraged to explore various solutions and carefully evaluate their potential outcomes.By considering the consequences of each option, individuals can make wise decisions that lead to positive outcomes.

2) Boosting efficiency: In today's fast-paced world, efficiency is paramount.Problem-Solving Techniques enable individuals to address issues promptly and efficiently. By breaking down problems into manageable steps, they can tackle each component with precision, ultimately speeding up the Problem-Solving process.

3) Fostering innovation: Creativity is a driving force behind innovation, and Problem-Solving Techniques stimulate this aspect. When individuals engage in brainstorming sessions and explore unconventional solutions, they open the door to innovative ideas that can revolutionise their approach to Problem-Solving.

4) Building resilience: The ability to bounce back from challenges and setbacks is known as Resilience. Problem-Solving Techniques encourage individuals to view obstacles as opportunities for growth and learning. By approaching issues with a positive mindset, individuals can build resilience and nurture the confidence to tackle any future challenges.

Problem-Solving Techniques are instrumental in empowering individuals to handle various situations effectively. By improving decision-making, boosting efficiency, fostering innovation, and nurturing resilience, these techniques become valuable assets in both personal and professional endeavours.

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Basic Problem-Solving Techniques  

Basic Problem-Solving Techniques are essential tools that individuals can employ to address a wide range of challenges effectively. These techniques serve as a foundation for Problem-Solving and can be applied in various situations. Here are some basic Problem-Solving Techniques:

1) Identify the problem: The first step  is to clearly identify the issue at hand. Take time to understand the problem's nature, scope, and impact. Gathering relevant information and data is crucial for gaining a comprehensive understanding of the situation.

2) Break down the problem:  Therefore, breaking down the problem into smaller, more manageable parts can make it easier. Analyse the problem's components and consider how they relate to one another.

3) Priorities and set goals: Determine which aspects of the problem are most urgent and require immediate attention. Keep Specific, Measurable, Achievable, Relevant, and Time-bound (SMART) goals to guide the Problem-Solving process.

4) Generate possible solutions: Brainstorm potential solutions to the problem. Encourage creative thinking and be open to creative ideas. At this stage, the quantity of ideas is more important than their quality. All ideas are considered without judgment.  

5) Evaluate and select solutions: After generating a list of potential solutions, evaluate each one based on its feasibility, practicality, and alignment with the established goals. Consider the pros and cons of each option.  

6) Implement the chosen solution: Once the most suitable solution is selected, put it into action. Create a clear action plan outlining the necessary steps, responsibilities, and timelines for implementation.  

7) Monitor progress: Consistently track the progress of the implemented solution. Assess its effectiveness and whether it is achieving the desired results. If necessary, make adjustments to optimise the outcome.

8) Reflect and learn: After solving the problem, take some time to reflect on the process. Identify what worked well and what could be improved. Learning from past experiences can help enhance Problem-Solving skills for future challenges.  

9) Seek feedback: Gather feedback from relevant stakeholders involved in the  Problem-Solving process. Feedback can offer valuable insights and different perspectives, leading to more comprehensive solutions.

10) Stay positive and persistent: Though Problem-Solving can be challenging, maintaining a positive attitude and persistence is essential. Some problems may require multiple attempts and iterations before finding the best solution.

11) Learn from mistakes: Mistakes are a natural part of the Problem-Solving process. Embrace them as learning opportunities and use them to improve future approaches.  

12) Be open to new ideas: Problem-Solving is not a linear process. Stay open to new information, ideas, and perspectives that may arise throughout the process.  

Individuals can incorporate these basic Problem-Solving Techniques into their approach to become more effective in addressing various challenges and making informed decisions. These techniques provide a structured and systematic way to navigate problems, leading to successful outcomes in both personal and professional contexts. 

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Top 20+ Problem-Solving Techniques 

Problem-Solving Techniques are systematic approaches used to identify, analyse, and resolve issues in a structured and effective manner. These techniques are crucial in both personal and professional spheres as they enable individuals to navigate challenges and find practical solutions. Here are the top 20+ Problem-Solving Techniques:

1) Define the problem clearly  

Precisely defining the problem is the cornerstone of effective Problem-Solving. It includes finding the root cause of the issue and understanding its scope. Gathering relevant information and data is crucial at this stage to gain a comprehensive understanding of the problem's context. Articulating the problem in simple terms ensures clarity for all involved in the Problem-Solving process. This will make the communication and collaboration easier.

2) Brainstorming solutions  

Once the problem is well-defined, the next step is to conduct brainstorming sessions. These sessions aim to generate a diverse range of potential solutions. It's essential to create a supportive and open environment during brainstorming, encouraging participants to think freely and creatively. Sometimes, unconventional ideas that emerge during brainstorming sessions can lead to creative and unique solutions that may not have been considered otherwise.

3) Evaluating and selecting solutions  

With a pool of potential solutions, it's time to evaluate each option critically. Consider factors like feasibility, practicality, cost-effectiveness, and alignment with the overarching goals. A well-thought-out evaluation process enables decision-makers to narrow down the list of potential solutions. This approach identifies those solutions that are most viable and likely to address the problem effectively.

4) Implementing the solution  

The selected solution now needs to be put into action. Creating a detailed action plan that defines the specific steps, responsibilities, and timelines is essential. Having a well-structured implementation process ensures that everyone involved understands their role and contributes to the successful execution of the solution.

5) Monitoring and evaluating  

Implementing the solution is not the end of the Problem-Solving process. Continuous monitoring and evaluation are critical to assess the effectiveness of the solution. Regularly tracking progress and gathering feedback from stakeholders allow for adjustments and improvements as needed. This iterative method ensures that the solution remains relevant and optimised over time.

6) Root Cause Analysis (RCA)

Rather than merely addressing the symptoms of a problem, an RCA  seeks to identify the underlying factors that trigger the issue. By targeting the root cause, individuals can develop sustainable solutions that prevent the problem from recurring in the future.

7) SWOT analysis  

A SWOT analysis is a valuable tool that helps individuals understand the internal strengths and weaknesses of their organisation or themselves. It also identifies external opportunities and threats in the environment. By identifying these factors, Problem-solvers can develop well-informed strategies that align with their strengths and capitalise on opportunities. At the same time, they address weaknesses and mitigate threats.

8) Decision matrix analysis  

When faced with multiple solutions, a decision matrix analysis allows for a structured comparison. This technique involves assigning weights to different criteria and scoring each solution based on those criteria. The solution with the highest score indicates the most viable option.

9) Creative thinking  

Encouraging creative thinking during Problem-Solving opens up a world of possibilities. Techniques like mind mapping, brainstorming, and lateral thinking stimulate great ideas and novel approaches to tackle problems creatively.

10) Collaborative  Problem-Solving  

Involving a diverse group of individuals in the Problem-Solving process brings in a variety of perspectives and expertise. Collaborative Problem-Solving fosters a sense of ownership among team members, promoting active participation and commitment to finding effective solutions.  

11) Risk analysis  

Assessing potential risks and challenges associated with each solution helps individuals anticipate and prepare for contingencies. Identifying potential obstacles allows for the implementation of risk mitigation strategies to minimise negative outcomes.  

12) Learn from past experiences  

Reflecting on past Problem-Solving experiences, both successes and failures, provides valuable insights. Learning from these experiences helps improve Problem-Solving skills and approaches over time, making individuals more adept at addressing future challenges.  

13) Consider constraints and resources  

In the process of Problem-Solving, it's essential to take into account the constraints and available resources. These constraints may include budget limitations, time constraints, or external factors beyond one's control. By understanding and acknowledging these limitations, Problem Solvers can craft solutions that are realistic and achievable within the given constraints.  

14) Feedback and input  

Solving problems doesn't need to be an individual effort. Getting advice and opinions from others can offer important perspectives and fresh ideas. Input from colleagues, mentors, or users can enrich your understanding of the issue and open up new solution paths.

15) Continuous learning and adaptability  

Problem-Solving is an ongoing process, and learning is a vital part of it.  Adopt an approach of continuous learning and adaptability. Stay open to new information, emerging technologies, and best practices inProblem-Solving. Being adaptable allows individuals to adjust their approaches as new challenges arise, ensuring they remain effective Problem Solvers in dynamic environments.

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16) Six thinking hats

Different people solve problems uniquely, influenced by their team, job roles, biases, or internal politics. The Six Thinking Hats method helps them tackle problems from various perspectives, focusing on facts and data, creative solutions, or potential drawbacks. This framework effectively removes roadblocks, enabling teams to address all aspects of complex problems comprehensively.

17) Lightening Decision Jam (LDJ)

The process involves a series of timed exercises that guide participants through identifying issues, generating solutions, deciding on the best solutions to pursue, and creating action steps. The goal of an LDJ is to sidestep the usual debate and analysis paralysis that can occur in team meetings, leading to clear, actionable outcomes in a short amount of time. This method is particularly useful for solving specific problems, improving processes, or breaking through creative blocks.

18) Problem definition process 

Complex problems don't always require complex solutions; often, simple approaches are enough to tackle them effectively.

Starting with a clear identification and definition of the problem allows the group to shift their perspective, seeing the problem as an opportunity for change. The process begins with pinpointing a central question and examining its various aspects. Then, the group divides into five teams, each adopting unique approaches like escape, reversal, exaggeration, distortion, or wishful thinking to tackle the issue. 

Each team sets a goal related to the problem and brainstorms solutions according to their assigned method, which is later shared with the entire group. This technique facilitates deep conversation and opens the door to innovative solutions by encouraging diverse thinking and creativity.

19) The Five whys  

Sometimes, a team must dig deeper to understand the core reason behind issues in an organisation. RCA helps in pinpointing the root cause of business problems or ongoing challenges. The 5 Whys is a simple and powerful method for locating the root cause of any problem. It starts with forming a problem statement and then asking "why" five times to gradually get to the heart of the issue. This method offers a clear path to discovering the true cause behind a problem.

20) World cafe 

World Cafe is a method that makes it easier for large groups to tackle complex issues together. It works by setting up a cosy, cafe-like environment where people can naturally group together to discuss topics that matter to them, all focused on solving a key problem. By arranging the space like a cafe and guiding participants at the start, you can then let them drive the conversation.

Integrating problem-Solving into the culture of an organisation can be challenging. However, friendly and inviting approaches such as World Cafe are particularly useful for welcoming those who are new to workshop settings, making it easier for everyone to contribute.

21) Discovery & Action Dialogue (DAD) 

Creating a comfortable environment where people can openly share and learn from each other is key to finding solutions together. DAD is a method that can guide a group in deciding which issues they want to tackle and how they plan to solve them. It's really effective in reducing resistance to change and ensuring everyone agrees with the plan. 

This approach also promotes commitment by giving those directly involved the power to make decisions. It's an essential technique for anyone leading group discussions or workshops.

22) Design Sprint 2.0 

Do you want to know how a team can tackle big challenges and quickly move on to creating and testing solutions? Jake Knapp's Design Sprint 2.0, from his book "Sprint," gives you a full plan for a four-day workshop that really works. 

Making a good plan can be hard, and making sure you do everything right can be stressful or take a lot of time, especially if you're not used to it. If you're stuck on a tough problem and want to get your team focused on a fast way to test a new idea or find a quick solution, this four-day workshop template is perfect. It's all about moving quickly and efficiently.

23) Open space technology 

Open Space Technology is created by Harrison Owen. It is a method where big groups can actively solve problems and lead discussions themselves. It works well when there is a lot of knowledge and different perspectives in the room, and you want to explore different ways to tackle a specific issue.

First, gather everyone to focus on a main topic. Go over some basic rules to help guide everyone in solving the problem. Then, let each person pick an issue related to the topic they care about and are willing to handle.

People then write their chosen issue on a paper, announce it to everyone, choose a time and place for a discussion, and put the paper on a wall. As the wall gets covered with different sessions, everyone picks the ones they are interested in and feel they can add value to, and that is when the discussions start. Groups discuss their chosen topics, take notes, and, if it makes sense, share what they have found with everyone else later.

By employing these Problem-Solving Techniques, individuals and organisations can become proficient in tackling a wide range of challenges and making well-informed decisions. Effective Problem-Solving skills are invaluable assets that lead to growth, success, and continuous improvement.

Conclusion  

We hope you read and understand everything about Problem-Solving Techniques. Mastering these techniques empowers individuals to overcome challenges with confidence and make informed decisions. These skills foster adaptability and continuous improvement, leading to successful outcomes in personal and professional contexts. 

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Frequently Asked Questions

Problem-Solving Techniques help conflict management by finding common ground and creating solutions everyone agrees on. They encourage open communication and understanding, which can reduce tension and resolve disputes.

Problem-Solving Techniques can boost personal growth by teaching you how to tackle challenges head-on. They improve critical thinking and decision-making skills, making you more adaptable and resilient in various situations.

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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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7.3 Problem-Solving

Learning objectives.

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

• Describe problem solving strategies
• Define algorithm and heuristic
• Explain some common roadblocks to effective problem solving

   People face problems every day—usually, multiple problems throughout the day. Sometimes these problems are straightforward: To double a recipe for pizza dough, for example, all that is required is that each ingredient in the recipe be doubled. Sometimes, however, the problems we encounter are more complex. For example, say you have a work deadline, and you must mail a printed copy of a report to your supervisor by the end of the business day. The report is time-sensitive and must be sent overnight. You finished the report last night, but your printer will not work today. What should you do? First, you need to identify the problem and then apply a strategy for solving the problem.

The study of human and animal problem solving processes has provided much insight toward the understanding of our conscious experience and led to advancements in computer science and artificial intelligence. Essentially much of cognitive science today represents studies of how we consciously and unconsciously make decisions and solve problems. For instance, when encountered with a large amount of information, how do we go about making decisions about the most efficient way of sorting and analyzing all the information in order to find what you are looking for as in visual search paradigms in cognitive psychology. Or in a situation where a piece of machinery is not working properly, how do we go about organizing how to address the issue and understand what the cause of the problem might be. How do we sort the procedures that will be needed and focus attention on what is important in order to solve problems efficiently. Within this section we will discuss some of these issues and examine processes related to human, animal and computer problem solving.

PROBLEM-SOLVING STRATEGIES

   When people are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

Problems themselves can be classified into two different categories known as ill-defined and well-defined problems (Schacter, 2009). Ill-defined problems represent issues that do not have clear goals, solution paths, or expected solutions whereas well-defined problems have specific goals, clearly defined solutions, and clear expected solutions. Problem solving often incorporates pragmatics (logical reasoning) and semantics (interpretation of meanings behind the problem), and also in many cases require abstract thinking and creativity in order to find novel solutions. Within psychology, problem solving refers to a motivational drive for reading a definite “goal” from a present situation or condition that is either not moving toward that goal, is distant from it, or requires more complex logical analysis for finding a missing description of conditions or steps toward that goal. Processes relating to problem solving include problem finding also known as problem analysis, problem shaping where the organization of the problem occurs, generating alternative strategies, implementation of attempted solutions, and verification of the selected solution. Various methods of studying problem solving exist within the field of psychology including introspection, behavior analysis and behaviorism, simulation, computer modeling, and experimentation.

A problem-solving strategy is a plan of action used to find a solution. Different strategies have different action plans associated with them (table below). For example, a well-known strategy is trial and error. The old adage, “If at first you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

   Another type of strategy is an algorithm. An algorithm is a problem-solving formula that provides you with step-by-step instructions used to achieve a desired outcome (Kahneman, 2011). You can think of an algorithm as a recipe with highly detailed instructions that produce the same result every time they are performed. Algorithms are used frequently in our everyday lives, especially in computer science. When you run a search on the Internet, search engines like Google use algorithms to decide which entries will appear first in your list of results. Facebook also uses algorithms to decide which posts to display on your newsfeed. Can you identify other situations in which algorithms are used?

A heuristic is another type of problem solving strategy. While an algorithm must be followed exactly to produce a correct result, a heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. A “rule of thumb” is an example of a heuristic. Such a rule saves the person time and energy when making a decision, but despite its time-saving characteristics, it is not always the best method for making a rational decision. Different types of heuristics are used in different types of situations, but the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind in the same moment

Working backwards is a useful heuristic in which you begin solving the problem by focusing on the end result. Consider this example: You live in Washington, D.C. and have been invited to a wedding at 4 PM on Saturday in Philadelphia. Knowing that Interstate 95 tends to back up any day of the week, you need to plan your route and time your departure accordingly. If you want to be at the wedding service by 3:30 PM, and it takes 2.5 hours to get to Philadelphia without traffic, what time should you leave your house? You use the working backwards heuristic to plan the events of your day on a regular basis, probably without even thinking about it.

Another useful heuristic is the practice of accomplishing a large goal or task by breaking it into a series of smaller steps. Students often use this common method to complete a large research project or long essay for school. For example, students typically brainstorm, develop a thesis or main topic, research the chosen topic, organize their information into an outline, write a rough draft, revise and edit the rough draft, develop a final draft, organize the references list, and proofread their work before turning in the project. The large task becomes less overwhelming when it is broken down into a series of small steps.

Further problem solving strategies have been identified (listed below) that incorporate flexible and creative thinking in order to reach solutions efficiently.

Additional Problem Solving Strategies :

• Abstraction – refers to solving the problem within a model of the situation before applying it to reality.
• Analogy – is using a solution that solves a similar problem.
• Brainstorming – refers to collecting an analyzing a large amount of solutions, especially within a group of people, to combine the solutions and developing them until an optimal solution is reached.
• Divide and conquer – breaking down large complex problems into smaller more manageable problems.
• Hypothesis testing – method used in experimentation where an assumption about what would happen in response to manipulating an independent variable is made, and analysis of the affects of the manipulation are made and compared to the original hypothesis.
• Lateral thinking – approaching problems indirectly and creatively by viewing the problem in a new and unusual light.
• Means-ends analysis – choosing and analyzing an action at a series of smaller steps to move closer to the goal.
• Method of focal objects – putting seemingly non-matching characteristics of different procedures together to make something new that will get you closer to the goal.
• Morphological analysis – analyzing the outputs of and interactions of many pieces that together make up a whole system.
• Proof – trying to prove that a problem cannot be solved. Where the proof fails becomes the starting point or solving the problem.
• Reduction – adapting the problem to be as similar problems where a solution exists.
• Research – using existing knowledge or solutions to similar problems to solve the problem.
• Root cause analysis – trying to identify the cause of the problem.

The strategies listed above outline a short summary of methods we use in working toward solutions and also demonstrate how the mind works when being faced with barriers preventing goals to be reached.

One example of means-end analysis can be found by using the Tower of Hanoi paradigm . This paradigm can be modeled as a word problems as demonstrated by the Missionary-Cannibal Problem :

Missionary-Cannibal Problem

Three missionaries and three cannibals are on one side of a river and need to cross to the other side. The only means of crossing is a boat, and the boat can only hold two people at a time. Your goal is to devise a set of moves that will transport all six of the people across the river, being in mind the following constraint: The number of cannibals can never exceed the number of missionaries in any location. Remember that someone will have to also row that boat back across each time.

Hint : At one point in your solution, you will have to send more people back to the original side than you just sent to the destination.

The actual Tower of Hanoi problem consists of three rods sitting vertically on a base with a number of disks of different sizes that can slide onto any rod. The puzzle starts with the disks in a neat stack in ascending order of size on one rod, the smallest at the top making a conical shape. The objective of the puzzle is to move the entire stack to another rod obeying the following rules:

• 1. Only one disk can be moved at a time.
• 2. Each move consists of taking the upper disk from one of the stacks and placing it on top of another stack or on an empty rod.
• 3. No disc may be placed on top of a smaller disk.

  Figure 7.02. Steps for solving the Tower of Hanoi in the minimum number of moves when there are 3 disks.

Figure 7.03. Graphical representation of nodes (circles) and moves (lines) of Tower of Hanoi.

The Tower of Hanoi is a frequently used psychological technique to study problem solving and procedure analysis. A variation of the Tower of Hanoi known as the Tower of London has been developed which has been an important tool in the neuropsychological diagnosis of executive function disorders and their treatment.

GESTALT PSYCHOLOGY AND PROBLEM SOLVING

As you may recall from the sensation and perception chapter, Gestalt psychology describes whole patterns, forms and configurations of perception and cognition such as closure, good continuation, and figure-ground. In addition to patterns of perception, Wolfgang Kohler, a German Gestalt psychologist traveled to the Spanish island of Tenerife in order to study animals behavior and problem solving in the anthropoid ape.

As an interesting side note to Kohler’s studies of chimp problem solving, Dr. Ronald Ley, professor of psychology at State University of New York provides evidence in his book A Whisper of Espionage  (1990) suggesting that while collecting data for what would later be his book  The Mentality of Apes (1925) on Tenerife in the Canary Islands between 1914 and 1920, Kohler was additionally an active spy for the German government alerting Germany to ships that were sailing around the Canary Islands. Ley suggests his investigations in England, Germany and elsewhere in Europe confirm that Kohler had served in the German military by building, maintaining and operating a concealed radio that contributed to Germany’s war effort acting as a strategic outpost in the Canary Islands that could monitor naval military activity approaching the north African coast.

While trapped on the island over the course of World War 1, Kohler applied Gestalt principles to animal perception in order to understand how they solve problems. He recognized that the apes on the islands also perceive relations between stimuli and the environment in Gestalt patterns and understand these patterns as wholes as opposed to pieces that make up a whole. Kohler based his theories of animal intelligence on the ability to understand relations between stimuli, and spent much of his time while trapped on the island investigation what he described as  insight , the sudden perception of useful or proper relations. In order to study insight in animals, Kohler would present problems to chimpanzee’s by hanging some banana’s or some kind of food so it was suspended higher than the apes could reach. Within the room, Kohler would arrange a variety of boxes, sticks or other tools the chimpanzees could use by combining in patterns or organizing in a way that would allow them to obtain the food (Kohler & Winter, 1925).

While viewing the chimpanzee’s, Kohler noticed one chimp that was more efficient at solving problems than some of the others. The chimp, named Sultan, was able to use long poles to reach through bars and organize objects in specific patterns to obtain food or other desirables that were originally out of reach. In order to study insight within these chimps, Kohler would remove objects from the room to systematically make the food more difficult to obtain. As the story goes, after removing many of the objects Sultan was used to using to obtain the food, he sat down ad sulked for a while, and then suddenly got up going over to two poles lying on the ground. Without hesitation Sultan put one pole inside the end of the other creating a longer pole that he could use to obtain the food demonstrating an ideal example of what Kohler described as insight. In another situation, Sultan discovered how to stand on a box to reach a banana that was suspended from the rafters illustrating Sultan’s perception of relations and the importance of insight in problem solving.

Grande (another chimp in the group studied by Kohler) builds a three-box structure to reach the bananas, while Sultan watches from the ground.  Insight , sometimes referred to as an “Ah-ha” experience, was the term Kohler used for the sudden perception of useful relations among objects during problem solving (Kohler, 1927; Radvansky & Ashcraft, 2013).

Solving puzzles.

   Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below (see figure) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

How long did it take you to solve this sudoku puzzle? (You can see the answer at the end of this section.)

   Here is another popular type of puzzle (figure below) that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Did you figure it out? (The answer is at the end of this section.) Once you understand how to crack this puzzle, you won’t forget.

   Take a look at the “Puzzling Scales” logic puzzle below (figure below). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

What steps did you take to solve this puzzle? You can read the solution at the end of this section.

Pitfalls to problem solving.

   Not all problems are successfully solved, however. What challenges stop us from successfully solving a problem? Albert Einstein once said, “Insanity is doing the same thing over and over again and expecting a different result.” Imagine a person in a room that has four doorways. One doorway that has always been open in the past is now locked. The person, accustomed to exiting the room by that particular doorway, keeps trying to get out through the same doorway even though the other three doorways are open. The person is stuck—but she just needs to go to another doorway, instead of trying to get out through the locked doorway. A mental set is where you persist in approaching a problem in a way that has worked in the past but is clearly not working now.

Functional fixedness is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. During the Apollo 13 mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

   Researchers have investigated whether functional fixedness is affected by culture. In one experiment, individuals from the Shuar group in Ecuador were asked to use an object for a purpose other than that for which the object was originally intended. For example, the participants were told a story about a bear and a rabbit that were separated by a river and asked to select among various objects, including a spoon, a cup, erasers, and so on, to help the animals. The spoon was the only object long enough to span the imaginary river, but if the spoon was presented in a way that reflected its normal usage, it took participants longer to choose the spoon to solve the problem. (German & Barrett, 2005). The researchers wanted to know if exposure to highly specialized tools, as occurs with individuals in industrialized nations, affects their ability to transcend functional fixedness. It was determined that functional fixedness is experienced in both industrialized and nonindustrialized cultures (German & Barrett, 2005).

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. Sometimes, however, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000 home? Why would the realtor show you the run-down houses and the nice house? The realtor may be challenging your anchoring bias. An anchoring bias occurs when you focus on one piece of information when making a decision or solving a problem. In this case, you’re so focused on the amount of money you are willing to spend that you may not recognize what kinds of houses are available at that price point.

The confirmation bias is the tendency to focus on information that confirms your existing beliefs. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Representative bias describes a faulty way of thinking, in which you unintentionally stereotype someone or something; for example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Finally, the availability heuristic is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision . Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in the table below.

Were you able to determine how many marbles are needed to balance the scales in the figure below? You need nine. Were you able to solve the problems in the figures above? Here are the answers.

   Many different strategies exist for solving problems. Typical strategies include trial and error, applying algorithms, and using heuristics. To solve a large, complicated problem, it often helps to break the problem into smaller steps that can be accomplished individually, leading to an overall solution. Roadblocks to problem solving include a mental set, functional fixedness, and various biases that can cloud decision making skills.

References:

Openstax Psychology text by Kathryn Dumper, William Jenkins, Arlene Lacombe, Marilyn Lovett and Marion Perlmutter licensed under CC BY v4.0. https://openstax.org/details/books/psychology

Review Questions:

1. A specific formula for solving a problem is called ________.

a. an algorithm

b. a heuristic

c. a mental set

d. trial and error

2. Solving the Tower of Hanoi problem tends to utilize a  ________ strategy of problem solving.

a. divide and conquer

b. means-end analysis

d. experiment

3. A mental shortcut in the form of a general problem-solving framework is called ________.

4. Which type of bias involves becoming fixated on a single trait of a problem?

a. anchoring bias

b. confirmation bias

c. representative bias

d. availability bias

5. Which type of bias involves relying on a false stereotype to make a decision?

6. Wolfgang Kohler analyzed behavior of chimpanzees by applying Gestalt principles to describe ________.

a. social adjustment

b. student load payment options

c. emotional learning

d. insight learning

7. ________ is a type of mental set where you cannot perceive an object being used for something other than what it was designed for.

a. functional fixedness

c. working memory

Critical Thinking Questions:

1. What is functional fixedness and how can overcoming it help you solve problems?

2. How does an algorithm save you time and energy when solving a problem?

Personal Application Question:

1. Which type of bias do you recognize in your own decision making processes? How has this bias affected how you’ve made decisions in the past and how can you use your awareness of it to improve your decisions making skills in the future?

anchoring bias

availability heuristic

confirmation bias

functional fixedness

hindsight bias

problem-solving strategy

representative bias

trial and error

working backwards

Answers to Exercises

algorithm:  problem-solving strategy characterized by a specific set of instructions

anchoring bias:  faulty heuristic in which you fixate on a single aspect of a problem to find a solution

availability heuristic:  faulty heuristic in which you make a decision based on information readily available to you

confirmation bias:  faulty heuristic in which you focus on information that confirms your beliefs

functional fixedness:  inability to see an object as useful for any other use other than the one for which it was intended

heuristic:  mental shortcut that saves time when solving a problem

hindsight bias:  belief that the event just experienced was predictable, even though it really wasn’t

mental set:  continually using an old solution to a problem without results

problem-solving strategy:  method for solving problems

representative bias:  faulty heuristic in which you stereotype someone or something without a valid basis for your judgment

trial and error:  problem-solving strategy in which multiple solutions are attempted until the correct one is found

working backwards:  heuristic in which you begin to solve a problem by focusing on the end result

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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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48 Problem Solving

Department of Psychological and Brain Sciences, University of California, Santa Barbara

• Published: 03 June 2013
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Problem solving refers to cognitive processing directed at achieving a goal when the problem solver does not initially know a solution method. A problem exists when someone has a goal but does not know how to achieve it. Problems can be classified as routine or nonroutine, and as well defined or ill defined. The major cognitive processes in problem solving are representing, planning, executing, and monitoring. The major kinds of knowledge required for problem solving are facts, concepts, procedures, strategies, and beliefs. Classic theoretical approaches to the study of problem solving are associationism, Gestalt, and information processing. Current issues and suggested future issues include decision making, intelligence and creativity, teaching of thinking skills, expert problem solving, analogical reasoning, mathematical and scientific thinking, everyday thinking, and the cognitive neuroscience of problem solving. Common themes concern the domain specificity of problem solving and a focus on problem solving in authentic contexts.

The study of problem solving begins with defining problem solving, problem, and problem types. This introduction to problem solving is rounded out with an examination of cognitive processes in problem solving, the role of knowledge in problem solving, and historical approaches to the study of problem solving.

Definition of Problem Solving

Problem solving refers to cognitive processing directed at achieving a goal for which the problem solver does not initially know a solution method. This definition consists of four major elements (Mayer, 1992 ; Mayer & Wittrock, 2006 ):

Cognitive —Problem solving occurs within the problem solver’s cognitive system and can only be inferred indirectly from the problem solver’s behavior (including biological changes, introspections, and actions during problem solving). Process —Problem solving involves mental computations in which some operation is applied to a mental representation, sometimes resulting in the creation of a new mental representation. Directed —Problem solving is aimed at achieving a goal. Personal —Problem solving depends on the existing knowledge of the problem solver so that what is a problem for one problem solver may not be a problem for someone who already knows a solution method.

The definition is broad enough to include a wide array of cognitive activities such as deciding which apartment to rent, figuring out how to use a cell phone interface, playing a game of chess, making a medical diagnosis, finding the answer to an arithmetic word problem, or writing a chapter for a handbook. Problem solving is pervasive in human life and is crucial for human survival. Although this chapter focuses on problem solving in humans, problem solving also occurs in nonhuman animals and in intelligent machines.

How is problem solving related to other forms of high-level cognition processing, such as thinking and reasoning? Thinking refers to cognitive processing in individuals but includes both directed thinking (which corresponds to the definition of problem solving) and undirected thinking such as daydreaming (which does not correspond to the definition of problem solving). Thus, problem solving is a type of thinking (i.e., directed thinking).

Reasoning refers to problem solving within specific classes of problems, such as deductive reasoning or inductive reasoning. In deductive reasoning, the reasoner is given premises and must derive a conclusion by applying the rules of logic. For example, given that “A is greater than B” and “B is greater than C,” a reasoner can conclude that “A is greater than C.” In inductive reasoning, the reasoner is given (or has experienced) a collection of examples or instances and must infer a rule. For example, given that X, C, and V are in the “yes” group and x, c, and v are in the “no” group, the reasoning may conclude that B is in “yes” group because it is in uppercase format. Thus, reasoning is a type of problem solving.

Definition of Problem

A problem occurs when someone has a goal but does not know to achieve it. This definition is consistent with how the Gestalt psychologist Karl Duncker ( 1945 , p. 1) defined a problem in his classic monograph, On Problem Solving : “A problem arises when a living creature has a goal but does not know how this goal is to be reached.” However, today researchers recognize that the definition should be extended to include problem solving by intelligent machines. This definition can be clarified using an information processing approach by noting that a problem occurs when a situation is in the given state, the problem solver wants the situation to be in the goal state, and there is no obvious way to move from the given state to the goal state (Newell & Simon, 1972 ). Accordingly, the three main elements in describing a problem are the given state (i.e., the current state of the situation), the goal state (i.e., the desired state of the situation), and the set of allowable operators (i.e., the actions the problem solver is allowed to take). The definition of “problem” is broad enough to include the situation confronting a physician who wishes to make a diagnosis on the basis of preliminary tests and a patient examination, as well as a beginning physics student trying to solve a complex physics problem.

Types of Problems

It is customary in the problem-solving literature to make a distinction between routine and nonroutine problems. Routine problems are problems that are so familiar to the problem solver that the problem solver knows a solution method. For example, for most adults, “What is 365 divided by 12?” is a routine problem because they already know the procedure for long division. Nonroutine problems are so unfamiliar to the problem solver that the problem solver does not know a solution method. For example, figuring out the best way to set up a funding campaign for a nonprofit charity is a nonroutine problem for most volunteers. Technically, routine problems do not meet the definition of problem because the problem solver has a goal but knows how to achieve it. Much research on problem solving has focused on routine problems, although most interesting problems in life are nonroutine.

Another customary distinction is between well-defined and ill-defined problems. Well-defined problems have a clearly specified given state, goal state, and legal operators. Examples include arithmetic computation problems or games such as checkers or tic-tac-toe. Ill-defined problems have a poorly specified given state, goal state, or legal operators, or a combination of poorly defined features. Examples include solving the problem of global warming or finding a life partner. Although, ill-defined problems are more challenging, much research in problem solving has focused on well-defined problems.

Cognitive Processes in Problem Solving

The process of problem solving can be broken down into two main phases: problem representation , in which the problem solver builds a mental representation of the problem situation, and problem solution , in which the problem solver works to produce a solution. The major subprocess in problem representation is representing , which involves building a situation model —that is, a mental representation of the situation described in the problem. The major subprocesses in problem solution are planning , which involves devising a plan for how to solve the problem; executing , which involves carrying out the plan; and monitoring , which involves evaluating and adjusting one’s problem solving.

For example, given an arithmetic word problem such as “Alice has three marbles. Sarah has two more marbles than Alice. How many marbles does Sarah have?” the process of representing involves building a situation model in which Alice has a set of marbles, there is set of marbles for the difference between the two girls, and Sarah has a set of marbles that consists of Alice’s marbles and the difference set. In the planning process, the problem solver sets a goal of adding 3 and 2. In the executing process, the problem solver carries out the computation, yielding an answer of 5. In the monitoring process, the problem solver looks over what was done and concludes that 5 is a reasonable answer. In most complex problem-solving episodes, the four cognitive processes may not occur in linear order, but rather may interact with one another. Although some research focuses mainly on the execution process, problem solvers may tend to have more difficulty with the processes of representing, planning, and monitoring.

Knowledge for Problem Solving

An important theme in problem-solving research is that problem-solving proficiency on any task depends on the learner’s knowledge (Anderson et al., 2001 ; Mayer, 1992 ). Five kinds of knowledge are as follows:

Facts —factual knowledge about the characteristics of elements in the world, such as “Sacramento is the capital of California” Concepts —conceptual knowledge, including categories, schemas, or models, such as knowing the difference between plants and animals or knowing how a battery works Procedures —procedural knowledge of step-by-step processes, such as how to carry out long-division computations Strategies —strategic knowledge of general methods such as breaking a problem into parts or thinking of a related problem Beliefs —attitudinal knowledge about how one’s cognitive processing works such as thinking, “I’m good at this”

Although some research focuses mainly on the role of facts and procedures in problem solving, complex problem solving also depends on the problem solver’s concepts, strategies, and beliefs (Mayer, 1992 ).

Historical Approaches to Problem Solving

Psychological research on problem solving began in the early 1900s, as an outgrowth of mental philosophy (Humphrey, 1963 ; Mandler & Mandler, 1964 ). Throughout the 20th century four theoretical approaches developed: early conceptions, associationism, Gestalt psychology, and information processing.

Early Conceptions

The start of psychology as a science can be set at 1879—the year Wilhelm Wundt opened the first world’s psychology laboratory in Leipzig, Germany, and sought to train the world’s first cohort of experimental psychologists. Instead of relying solely on philosophical speculations about how the human mind works, Wundt sought to apply the methods of experimental science to issues addressed in mental philosophy. His theoretical approach became structuralism —the analysis of consciousness into its basic elements.

Wundt’s main contribution to the study of problem solving, however, was to call for its banishment. According to Wundt, complex cognitive processing was too complicated to be studied by experimental methods, so “nothing can be discovered in such experiments” (Wundt, 1911/1973 ). Despite his admonishments, however, a group of his former students began studying thinking mainly in Wurzburg, Germany. Using the method of introspection, subjects were asked to describe their thought process as they solved word association problems, such as finding the superordinate of “newspaper” (e.g., an answer is “publication”). Although the Wurzburg group—as they came to be called—did not produce a new theoretical approach, they found empirical evidence that challenged some of the key assumptions of mental philosophy. For example, Aristotle had proclaimed that all thinking involves mental imagery, but the Wurzburg group was able to find empirical evidence for imageless thought .

Associationism

The first major theoretical approach to take hold in the scientific study of problem solving was associationism —the idea that the cognitive representations in the mind consist of ideas and links between them and that cognitive processing in the mind involves following a chain of associations from one idea to the next (Mandler & Mandler, 1964 ; Mayer, 1992 ). For example, in a classic study, E. L. Thorndike ( 1911 ) placed a hungry cat in what he called a puzzle box—a wooden crate in which pulling a loop of string that hung from overhead would open a trap door to allow the cat to escape to a bowl of food outside the crate. Thorndike placed the cat in the puzzle box once a day for several weeks. On the first day, the cat engaged in many extraneous behaviors such as pouncing against the wall, pushing its paws through the slats, and meowing, but on successive days the number of extraneous behaviors tended to decrease. Overall, the time required to get out of the puzzle box decreased over the course of the experiment, indicating the cat was learning how to escape.

Thorndike’s explanation for how the cat learned to solve the puzzle box problem is based on an associationist view: The cat begins with a habit family hierarchy —a set of potential responses (e.g., pouncing, thrusting, meowing, etc.) all associated with the same stimulus (i.e., being hungry and confined) and ordered in terms of strength of association. When placed in the puzzle box, the cat executes its strongest response (e.g., perhaps pouncing against the wall), but when it fails, the strength of the association is weakened, and so on for each unsuccessful action. Eventually, the cat gets down to what was initially a weak response—waving its paw in the air—but when that response leads to accidentally pulling the string and getting out, it is strengthened. Over the course of many trials, the ineffective responses become weak and the successful response becomes strong. Thorndike refers to this process as the law of effect : Responses that lead to dissatisfaction become less associated with the situation and responses that lead to satisfaction become more associated with the situation. According to Thorndike’s associationist view, solving a problem is simply a matter of trial and error and accidental success. A major challenge to assocationist theory concerns the nature of transfer—that is, where does a problem solver find a creative solution that has never been performed before? Associationist conceptions of cognition can be seen in current research, including neural networks, connectionist models, and parallel distributed processing models (Rogers & McClelland, 2004 ).

Gestalt Psychology

The Gestalt approach to problem solving developed in the 1930s and 1940s as a counterbalance to the associationist approach. According to the Gestalt approach, cognitive representations consist of coherent structures (rather than individual associations) and the cognitive process of problem solving involves building a coherent structure (rather than strengthening and weakening of associations). For example, in a classic study, Kohler ( 1925 ) placed a hungry ape in a play yard that contained several empty shipping crates and a banana attached overhead but out of reach. Based on observing the ape in this situation, Kohler noted that the ape did not randomly try responses until one worked—as suggested by Thorndike’s associationist view. Instead, the ape stood under the banana, looked up at it, looked at the crates, and then in a flash of insight stacked the crates under the bananas as a ladder, and walked up the steps in order to reach the banana.

According to Kohler, the ape experienced a sudden visual reorganization in which the elements in the situation fit together in a way to solve the problem; that is, the crates could become a ladder that reduces the distance to the banana. Kohler referred to the underlying mechanism as insight —literally seeing into the structure of the situation. A major challenge of Gestalt theory is its lack of precision; for example, naming a process (i.e., insight) is not the same as explaining how it works. Gestalt conceptions can be seen in modern research on mental models and schemas (Gentner & Stevens, 1983 ).

Information Processing

The information processing approach to problem solving developed in the 1960s and 1970s and was based on the influence of the computer metaphor—the idea that humans are processors of information (Mayer, 2009 ). According to the information processing approach, problem solving involves a series of mental computations—each of which consists of applying a process to a mental representation (such as comparing two elements to determine whether they differ).

In their classic book, Human Problem Solving , Newell and Simon ( 1972 ) proposed that problem solving involved a problem space and search heuristics . A problem space is a mental representation of the initial state of the problem, the goal state of the problem, and all possible intervening states (based on applying allowable operators). Search heuristics are strategies for moving through the problem space from the given to the goal state. Newell and Simon focused on means-ends analysis , in which the problem solver continually sets goals and finds moves to accomplish goals.

Newell and Simon used computer simulation as a research method to test their conception of human problem solving. First, they asked human problem solvers to think aloud as they solved various problems such as logic problems, chess, and cryptarithmetic problems. Then, based on an information processing analysis, Newell and Simon created computer programs that solved these problems. In comparing the solution behavior of humans and computers, they found high similarity, suggesting that the computer programs were solving problems using the same thought processes as humans.

An important advantage of the information processing approach is that problem solving can be described with great clarity—as a computer program. An important limitation of the information processing approach is that it is most useful for describing problem solving for well-defined problems rather than ill-defined problems. The information processing conception of cognition lives on as a keystone of today’s cognitive science (Mayer, 2009 ).

Classic Issues in Problem Solving

Three classic issues in research on problem solving concern the nature of transfer (suggested by the associationist approach), the nature of insight (suggested by the Gestalt approach), and the role of problem-solving heuristics (suggested by the information processing approach).

Transfer refers to the effects of prior learning on new learning (or new problem solving). Positive transfer occurs when learning A helps someone learn B. Negative transfer occurs when learning A hinders someone from learning B. Neutral transfer occurs when learning A has no effect on learning B. Positive transfer is a central goal of education, but research shows that people often do not transfer what they learned to solving problems in new contexts (Mayer, 1992 ; Singley & Anderson, 1989 ).

Three conceptions of the mechanisms underlying transfer are specific transfer , general transfer , and specific transfer of general principles . Specific transfer refers to the idea that learning A will help someone learn B only if A and B have specific elements in common. For example, learning Spanish may help someone learn Latin because some of the vocabulary words are similar and the verb conjugation rules are similar. General transfer refers to the idea that learning A can help someone learn B even they have nothing specifically in common but A helps improve the learner’s mind in general. For example, learning Latin may help people learn “proper habits of mind” so they are better able to learn completely unrelated subjects as well. Specific transfer of general principles is the idea that learning A will help someone learn B if the same general principle or solution method is required for both even if the specific elements are different.

In a classic study, Thorndike and Woodworth ( 1901 ) found that students who learned Latin did not subsequently learn bookkeeping any better than students who had not learned Latin. They interpreted this finding as evidence for specific transfer—learning A did not transfer to learning B because A and B did not have specific elements in common. Modern research on problem-solving transfer continues to show that people often do not demonstrate general transfer (Mayer, 1992 ). However, it is possible to teach people a general strategy for solving a problem, so that when they see a new problem in a different context they are able to apply the strategy to the new problem (Judd, 1908 ; Mayer, 2008 )—so there is also research support for the idea of specific transfer of general principles.

Insight refers to a change in a problem solver’s mind from not knowing how to solve a problem to knowing how to solve it (Mayer, 1995 ; Metcalfe & Wiebe, 1987 ). In short, where does the idea for a creative solution come from? A central goal of problem-solving research is to determine the mechanisms underlying insight.

The search for insight has led to five major (but not mutually exclusive) explanatory mechanisms—insight as completing a schema, insight as suddenly reorganizing visual information, insight as reformulation of a problem, insight as removing mental blocks, and insight as finding a problem analog (Mayer, 1995 ). Completing a schema is exemplified in a study by Selz (Fridja & de Groot, 1982 ), in which people were asked to think aloud as they solved word association problems such as “What is the superordinate for newspaper?” To solve the problem, people sometimes thought of a coordinate, such as “magazine,” and then searched for a superordinate category that subsumed both terms, such as “publication.” According to Selz, finding a solution involved building a schema that consisted of a superordinate and two subordinate categories.

Reorganizing visual information is reflected in Kohler’s ( 1925 ) study described in a previous section in which a hungry ape figured out how to stack boxes as a ladder to reach a banana hanging above. According to Kohler, the ape looked around the yard and found the solution in a flash of insight by mentally seeing how the parts could be rearranged to accomplish the goal.

Reformulating a problem is reflected in a classic study by Duncker ( 1945 ) in which people are asked to think aloud as they solve the tumor problem—how can you destroy a tumor in a patient without destroying surrounding healthy tissue by using rays that at sufficient intensity will destroy any tissue in their path? In analyzing the thinking-aloud protocols—that is, transcripts of what the problem solvers said—Duncker concluded that people reformulated the goal in various ways (e.g., avoid contact with healthy tissue, immunize healthy tissue, have ray be weak in healthy tissue) until they hit upon a productive formulation that led to the solution (i.e., concentrating many weak rays on the tumor).

Removing mental blocks is reflected in classic studies by Duncker ( 1945 ) in which solving a problem involved thinking of a novel use for an object, and by Luchins ( 1942 ) in which solving a problem involved not using a procedure that had worked well on previous problems. Finding a problem analog is reflected in classic research by Wertheimer ( 1959 ) in which learning to find the area of a parallelogram is supported by the insight that one could cut off the triangle on one side and place it on the other side to form a rectangle—so a parallelogram is really a rectangle in disguise. The search for insight along each of these five lines continues in current problem-solving research.

Heuristics are problem-solving strategies, that is, general approaches to how to solve problems. Newell and Simon ( 1972 ) suggested three general problem-solving heuristics for moving from a given state to a goal state: random trial and error , hill climbing , and means-ends analysis . Random trial and error involves randomly selecting a legal move and applying it to create a new problem state, and repeating that process until the goal state is reached. Random trial and error may work for simple problems but is not efficient for complex ones. Hill climbing involves selecting the legal move that moves the problem solver closer to the goal state. Hill climbing will not work for problems in which the problem solver must take a move that temporarily moves away from the goal as is required in many problems.

Means-ends analysis involves creating goals and seeking moves that can accomplish the goal. If a goal cannot be directly accomplished, a subgoal is created to remove one or more obstacles. Newell and Simon ( 1972 ) successfully used means-ends analysis as the search heuristic in a computer program aimed at general problem solving, that is, solving a diverse collection of problems. However, people may also use specific heuristics that are designed to work for specific problem-solving situations (Gigerenzer, Todd, & ABC Research Group, 1999 ; Kahneman & Tversky, 1984 ).

Current and Future Issues in Problem Solving

Eight current issues in problem solving involve decision making, intelligence and creativity, teaching of thinking skills, expert problem solving, analogical reasoning, mathematical and scientific problem solving, everyday thinking, and the cognitive neuroscience of problem solving.

Decision Making

Decision making refers to the cognitive processing involved in choosing between two or more alternatives (Baron, 2000 ; Markman & Medin, 2002 ). For example, a decision-making task may involve choosing between getting $240 for sure or having a 25% change of getting $1000. According to economic theories such as expected value theory, people should chose the second option, which is worth $250 (i.e., .25 x $1000) rather than the first option, which is worth $240 (1.00 x $240), but psychological research shows that most people prefer the first option (Kahneman & Tversky, 1984 ).

Research on decision making has generated three classes of theories (Markman & Medin, 2002 ): descriptive theories, such as prospect theory (Kahneman & Tversky), which are based on the ideas that people prefer to overweight the cost of a loss and tend to overestimate small probabilities; heuristic theories, which are based on the idea that people use a collection of short-cut strategies such as the availability heuristic (Gigerenzer et al., 1999 ; Kahneman & Tversky, 2000 ); and constructive theories, such as mental accounting (Kahneman & Tversky, 2000 ), in which people build a narrative to justify their choices to themselves. Future research is needed to examine decision making in more realistic settings.

Intelligence and Creativity

Although researchers do not have complete consensus on the definition of intelligence (Sternberg, 1990 ), it is reasonable to view intelligence as the ability to learn or adapt to new situations. Fluid intelligence refers to the potential to solve problems without any relevant knowledge, whereas crystallized intelligence refers to the potential to solve problems based on relevant prior knowledge (Sternberg & Gregorenko, 2003 ). As people gain more experience in a field, their problem-solving performance depends more on crystallized intelligence (i.e., domain knowledge) than on fluid intelligence (i.e., general ability) (Sternberg & Gregorenko, 2003 ). The ability to monitor and manage one’s cognitive processing during problem solving—which can be called metacognition —is an important aspect of intelligence (Sternberg, 1990 ). Research is needed to pinpoint the knowledge that is needed to support intelligent performance on problem-solving tasks.

Creativity refers to the ability to generate ideas that are original (i.e., other people do not think of the same idea) and functional (i.e., the idea works; Sternberg, 1999 ). Creativity is often measured using tests of divergent thinking —that is, generating as many solutions as possible for a problem (Guilford, 1967 ). For example, the uses test asks people to list as many uses as they can think of for a brick. Creativity is different from intelligence, and it is at the heart of creative problem solving—generating a novel solution to a problem that the problem solver has never seen before. An important research question concerns whether creative problem solving depends on specific knowledge or creativity ability in general.

Teaching of Thinking Skills

How can people learn to be better problem solvers? Mayer ( 2008 ) proposes four questions concerning teaching of thinking skills:

What to teach —Successful programs attempt to teach small component skills (such as how to generate and evaluate hypotheses) rather than improve the mind as a single monolithic skill (Covington, Crutchfield, Davies, & Olton, 1974 ). How to teach —Successful programs focus on modeling the process of problem solving rather than solely reinforcing the product of problem solving (Bloom & Broder, 1950 ). Where to teach —Successful programs teach problem-solving skills within the specific context they will be used rather than within a general course on how to solve problems (Nickerson, 1999 ). When to teach —Successful programs teaching higher order skills early rather than waiting until lower order skills are completely mastered (Tharp & Gallimore, 1988 ).

Overall, research on teaching of thinking skills points to the domain specificity of problem solving; that is, successful problem solving depends on the problem solver having domain knowledge that is relevant to the problem-solving task.

Expert Problem Solving

Research on expertise is concerned with differences between how experts and novices solve problems (Ericsson, Feltovich, & Hoffman, 2006 ). Expertise can be defined in terms of time (e.g., 10 years of concentrated experience in a field), performance (e.g., earning a perfect score on an assessment), or recognition (e.g., receiving a Nobel Prize or becoming Grand Master in chess). For example, in classic research conducted in the 1940s, de Groot ( 1965 ) found that chess experts did not have better general memory than chess novices, but they did have better domain-specific memory for the arrangement of chess pieces on the board. Chase and Simon ( 1973 ) replicated this result in a better controlled experiment. An explanation is that experts have developed schemas that allow them to chunk collections of pieces into a single configuration.

In another landmark study, Larkin et al. ( 1980 ) compared how experts (e.g., physics professors) and novices (e.g., first-year physics students) solved textbook physics problems about motion. Experts tended to work forward from the given information to the goal, whereas novices tended to work backward from the goal to the givens using a means-ends analysis strategy. Experts tended to store their knowledge in an integrated way, whereas novices tended to store their knowledge in isolated fragments. In another study, Chi, Feltovich, and Glaser ( 1981 ) found that experts tended to focus on the underlying physics concepts (such as conservation of energy), whereas novices tended to focus on the surface features of the problem (such as inclined planes or springs). Overall, research on expertise is useful in pinpointing what experts know that is different from what novices know. An important theme is that experts rely on domain-specific knowledge rather than solely general cognitive ability.

Analogical Reasoning

Analogical reasoning occurs when people solve one problem by using their knowledge about another problem (Holyoak, 2005 ). For example, suppose a problem solver learns how to solve a problem in one context using one solution method and then is given a problem in another context that requires the same solution method. In this case, the problem solver must recognize that the new problem has structural similarity to the old problem (i.e., it may be solved by the same method), even though they do not have surface similarity (i.e., the cover stories are different). Three steps in analogical reasoning are recognizing —seeing that a new problem is similar to a previously solved problem; abstracting —finding the general method used to solve the old problem; and mapping —using that general method to solve the new problem.

Research on analogical reasoning shows that people often do not recognize that a new problem can be solved by the same method as a previously solved problem (Holyoak, 2005 ). However, research also shows that successful analogical transfer to a new problem is more likely when the problem solver has experience with two old problems that have the same underlying structural features (i.e., they are solved by the same principle) but different surface features (i.e., they have different cover stories) (Holyoak, 2005 ). This finding is consistent with the idea of specific transfer of general principles as described in the section on “Transfer.”

Mathematical and Scientific Problem Solving

Research on mathematical problem solving suggests that five kinds of knowledge are needed to solve arithmetic word problems (Mayer, 2008 ):

Factual knowledge —knowledge about the characteristics of problem elements, such as knowing that there are 100 cents in a dollar Schematic knowledge —knowledge of problem types, such as being able to recognize time-rate-distance problems Strategic knowledge —knowledge of general methods, such as how to break a problem into parts Procedural knowledge —knowledge of processes, such as how to carry our arithmetic operations Attitudinal knowledge —beliefs about one’s mathematical problem-solving ability, such as thinking, “I am good at this”

People generally possess adequate procedural knowledge but may have difficulty in solving mathematics problems because they lack factual, schematic, strategic, or attitudinal knowledge (Mayer, 2008 ). Research is needed to pinpoint the role of domain knowledge in mathematical problem solving.

Research on scientific problem solving shows that people harbor misconceptions, such as believing that a force is needed to keep an object in motion (McCloskey, 1983 ). Learning to solve science problems involves conceptual change, in which the problem solver comes to recognize that previous conceptions are wrong (Mayer, 2008 ). Students can be taught to engage in scientific reasoning such as hypothesis testing through direct instruction in how to control for variables (Chen & Klahr, 1999 ). A central theme of research on scientific problem solving concerns the role of domain knowledge.

Everyday Thinking

Everyday thinking refers to problem solving in the context of one’s life outside of school. For example, children who are street vendors tend to use different procedures for solving arithmetic problems when they are working on the streets than when they are in school (Nunes, Schlieman, & Carraher, 1993 ). This line of research highlights the role of situated cognition —the idea that thinking always is shaped by the physical and social context in which it occurs (Robbins & Aydede, 2009 ). Research is needed to determine how people solve problems in authentic contexts.

Cognitive Neuroscience of Problem Solving

The cognitive neuroscience of problem solving is concerned with the brain activity that occurs during problem solving. For example, using fMRI brain imaging methodology, Goel ( 2005 ) found that people used the language areas of the brain to solve logical reasoning problems presented in sentences (e.g., “All dogs are pets…”) and used the spatial areas of the brain to solve logical reasoning problems presented in abstract letters (e.g., “All D are P…”). Cognitive neuroscience holds the potential to make unique contributions to the study of problem solving.

Problem solving has always been a topic at the fringe of cognitive psychology—too complicated to study intensively but too important to completely ignore. Problem solving—especially in realistic environments—is messy in comparison to studying elementary processes in cognition. The field remains fragmented in the sense that topics such as decision making, reasoning, intelligence, expertise, mathematical problem solving, everyday thinking, and the like are considered to be separate topics, each with its own separate literature. Yet some recurring themes are the role of domain-specific knowledge in problem solving and the advantages of studying problem solving in authentic contexts.

Future Directions

Some important issues for future research include the three classic issues examined in this chapter—the nature of problem-solving transfer (i.e., How are people able to use what they know about previous problem solving to help them in new problem solving?), the nature of insight (e.g., What is the mechanism by which a creative solution is constructed?), and heuristics (e.g., What are some teachable strategies for problem solving?). In addition, future research in problem solving should continue to pinpoint the role of domain-specific knowledge in problem solving, the nature of cognitive ability in problem solving, how to help people develop proficiency in solving problems, and how to provide aids for problem solving.

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Further Reading

Baron, J. ( 2008 ). Thinking and deciding (4th ed). New York: Cambridge University Press.

Duncker, K. ( 1945 ). On problem solving. Psychological Monographs , 58(3) (Whole No. 270).

Holyoak, K. J. , & Morrison, R. G. ( 2005 ). The Cambridge handbook of thinking and reasoning . New York: Cambridge University Press.

Mayer, R. E. , & Wittrock, M. C. ( 2006 ). Problem solving. In P. A. Alexander & P. H. Winne (Eds.), Handbook of educational psychology (2nd ed., pp. 287–304). Mahwah, NJ: Erlbaum.

Sternberg, R. J. , & Ben-Zeev, T. ( 2001 ). Complex cognition: The psychology of human thought . New York: Oxford University Press.

Weisberg, R. W. ( 2006 ). Creativity . New York: Wiley.

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14.3 Problem Solving and Decision Making in Groups

Learning objectives.

• Discuss the common components and characteristics of problems.
• Explain the five steps of the group problem-solving process.
• Describe the brainstorming and discussion that should take place before the group makes a decision.
• Compare and contrast the different decision-making techniques.
• Discuss the various influences on decision making.

Although the steps of problem solving and decision making that we will discuss next may seem obvious, we often don’t think to or choose not to use them. Instead, we start working on a problem and later realize we are lost and have to backtrack. I’m sure we’ve all reached a point in a project or task and had the “OK, now what?” moment. I’ve recently taken up some carpentry projects as a functional hobby, and I have developed a great respect for the importance of advanced planning. It’s frustrating to get to a crucial point in building or fixing something only to realize that you have to unscrew a support board that you already screwed in, have to drive back to the hardware store to get something that you didn’t think to get earlier, or have to completely start over. In this section, we will discuss the group problem-solving process, methods of decision making, and influences on these processes.

Group Problem Solving

The problem-solving process involves thoughts, discussions, actions, and decisions that occur from the first consideration of a problematic situation to the goal. The problems that groups face are varied, but some common problems include budgeting funds, raising funds, planning events, addressing customer or citizen complaints, creating or adapting products or services to fit needs, supporting members, and raising awareness about issues or causes.

Problems of all sorts have three common components (Adams & Galanes, 2009):

• An undesirable situation. When conditions are desirable, there isn’t a problem.
• A desired situation. Even though it may only be a vague idea, there is a drive to better the undesirable situation. The vague idea may develop into a more precise goal that can be achieved, although solutions are not yet generated.
• Obstacles between undesirable and desirable situation. These are things that stand in the way between the current situation and the group’s goal of addressing it. This component of a problem requires the most work, and it is the part where decision making occurs. Some examples of obstacles include limited funding, resources, personnel, time, or information. Obstacles can also take the form of people who are working against the group, including people resistant to change or people who disagree.

Discussion of these three elements of a problem helps the group tailor its problem-solving process, as each problem will vary. While these three general elements are present in each problem, the group should also address specific characteristics of the problem. Five common and important characteristics to consider are task difficulty, number of possible solutions, group member interest in problem, group member familiarity with problem, and the need for solution acceptance (Adams & Galanes, 2009).

• Task difficulty. Difficult tasks are also typically more complex. Groups should be prepared to spend time researching and discussing a difficult and complex task in order to develop a shared foundational knowledge. This typically requires individual work outside of the group and frequent group meetings to share information.
• Number of possible solutions. There are usually multiple ways to solve a problem or complete a task, but some problems have more potential solutions than others. Figuring out how to prepare a beach house for an approaching hurricane is fairly complex and difficult, but there are still a limited number of things to do—for example, taping and boarding up windows; turning off water, electricity, and gas; trimming trees; and securing loose outside objects. Other problems may be more creatively based. For example, designing a new restaurant may entail using some standard solutions but could also entail many different types of innovation with layout and design.
• Group member interest in problem. When group members are interested in the problem, they will be more engaged with the problem-solving process and invested in finding a quality solution. Groups with high interest in and knowledge about the problem may want more freedom to develop and implement solutions, while groups with low interest may prefer a leader who provides structure and direction.
• Group familiarity with problem. Some groups encounter a problem regularly, while other problems are more unique or unexpected. A family who has lived in hurricane alley for decades probably has a better idea of how to prepare its house for a hurricane than does a family that just recently moved from the Midwest. Many groups that rely on funding have to revisit a budget every year, and in recent years, groups have had to get more creative with budgets as funding has been cut in nearly every sector. When group members aren’t familiar with a problem, they will need to do background research on what similar groups have done and may also need to bring in outside experts.
• Need for solution acceptance. In this step, groups must consider how many people the decision will affect and how much “buy-in” from others the group needs in order for their solution to be successfully implemented. Some small groups have many stakeholders on whom the success of a solution depends. Other groups are answerable only to themselves. When a small group is planning on building a new park in a crowded neighborhood or implementing a new policy in a large business, it can be very difficult to develop solutions that will be accepted by all. In such cases, groups will want to poll those who will be affected by the solution and may want to do a pilot implementation to see how people react. Imposing an excellent solution that doesn’t have buy-in from stakeholders can still lead to failure.

Group problem solving can be a confusing puzzle unless it is approached systematically.

Muness Castle – Problem Solving – CC BY-SA 2.0.

Group Problem-Solving Process

There are several variations of similar problem-solving models based on US American scholar John Dewey’s reflective thinking process (Bormann & Bormann, 1988). As you read through the steps in the process, think about how you can apply what we learned regarding the general and specific elements of problems. Some of the following steps are straightforward, and they are things we would logically do when faced with a problem. However, taking a deliberate and systematic approach to problem solving has been shown to benefit group functioning and performance. A deliberate approach is especially beneficial for groups that do not have an established history of working together and will only be able to meet occasionally. Although a group should attend to each step of the process, group leaders or other group members who facilitate problem solving should be cautious not to dogmatically follow each element of the process or force a group along. Such a lack of flexibility could limit group member input and negatively affect the group’s cohesion and climate.

Step 1: Define the Problem

Define the problem by considering the three elements shared by every problem: the current undesirable situation, the goal or more desirable situation, and obstacles in the way (Adams & Galanes, 2009). At this stage, group members share what they know about the current situation, without proposing solutions or evaluating the information. Here are some good questions to ask during this stage: What is the current difficulty? How did we come to know that the difficulty exists? Who/what is involved? Why is it meaningful/urgent/important? What have the effects been so far? What, if any, elements of the difficulty require clarification? At the end of this stage, the group should be able to compose a single sentence that summarizes the problem called a problem statement . Avoid wording in the problem statement or question that hints at potential solutions. A small group formed to investigate ethical violations of city officials could use the following problem statement: “Our state does not currently have a mechanism for citizens to report suspected ethical violations by city officials.”

Step 2: Analyze the Problem

During this step a group should analyze the problem and the group’s relationship to the problem. Whereas the first step involved exploring the “what” related to the problem, this step focuses on the “why.” At this stage, group members can discuss the potential causes of the difficulty. Group members may also want to begin setting out an agenda or timeline for the group’s problem-solving process, looking forward to the other steps. To fully analyze the problem, the group can discuss the five common problem variables discussed before. Here are two examples of questions that the group formed to address ethics violations might ask: Why doesn’t our city have an ethics reporting mechanism? Do cities of similar size have such a mechanism? Once the problem has been analyzed, the group can pose a problem question that will guide the group as it generates possible solutions. “How can citizens report suspected ethical violations of city officials and how will such reports be processed and addressed?” As you can see, the problem question is more complex than the problem statement, since the group has moved on to more in-depth discussion of the problem during step 2.

Step 3: Generate Possible Solutions

During this step, group members generate possible solutions to the problem. Again, solutions should not be evaluated at this point, only proposed and clarified. The question should be what could we do to address this problem, not what should we do to address it. It is perfectly OK for a group member to question another person’s idea by asking something like “What do you mean?” or “Could you explain your reasoning more?” Discussions at this stage may reveal a need to return to previous steps to better define or more fully analyze a problem. Since many problems are multifaceted, it is necessary for group members to generate solutions for each part of the problem separately, making sure to have multiple solutions for each part. Stopping the solution-generating process prematurely can lead to groupthink. For the problem question previously posed, the group would need to generate solutions for all three parts of the problem included in the question. Possible solutions for the first part of the problem (How can citizens report ethical violations?) may include “online reporting system, e-mail, in-person, anonymously, on-the-record,” and so on. Possible solutions for the second part of the problem (How will reports be processed?) may include “daily by a newly appointed ethics officer, weekly by a nonpartisan nongovernment employee,” and so on. Possible solutions for the third part of the problem (How will reports be addressed?) may include “by a newly appointed ethics commission, by the accused’s supervisor, by the city manager,” and so on.

Step 4: Evaluate Solutions

During this step, solutions can be critically evaluated based on their credibility, completeness, and worth. Once the potential solutions have been narrowed based on more obvious differences in relevance and/or merit, the group should analyze each solution based on its potential effects—especially negative effects. Groups that are required to report the rationale for their decision or whose decisions may be subject to public scrutiny would be wise to make a set list of criteria for evaluating each solution. Additionally, solutions can be evaluated based on how well they fit with the group’s charge and the abilities of the group. To do this, group members may ask, “Does this solution live up to the original purpose or mission of the group?” and “Can the solution actually be implemented with our current resources and connections?” and “How will this solution be supported, funded, enforced, and assessed?” Secondary tensions and substantive conflict, two concepts discussed earlier, emerge during this step of problem solving, and group members will need to employ effective critical thinking and listening skills.

Decision making is part of the larger process of problem solving and it plays a prominent role in this step. While there are several fairly similar models for problem solving, there are many varied decision-making techniques that groups can use. For example, to narrow the list of proposed solutions, group members may decide by majority vote, by weighing the pros and cons, or by discussing them until a consensus is reached. There are also more complex decision-making models like the “six hats method,” which we will discuss later. Once the final decision is reached, the group leader or facilitator should confirm that the group is in agreement. It may be beneficial to let the group break for a while or even to delay the final decision until a later meeting to allow people time to evaluate it outside of the group context.

Step 5: Implement and Assess the Solution

Implementing the solution requires some advanced planning, and it should not be rushed unless the group is operating under strict time restraints or delay may lead to some kind of harm. Although some solutions can be implemented immediately, others may take days, months, or years. As was noted earlier, it may be beneficial for groups to poll those who will be affected by the solution as to their opinion of it or even to do a pilot test to observe the effectiveness of the solution and how people react to it. Before implementation, groups should also determine how and when they would assess the effectiveness of the solution by asking, “How will we know if the solution is working or not?” Since solution assessment will vary based on whether or not the group is disbanded, groups should also consider the following questions: If the group disbands after implementation, who will be responsible for assessing the solution? If the solution fails, will the same group reconvene or will a new group be formed?

Once a solution has been reached and the group has the “green light” to implement it, it should proceed deliberately and cautiously, making sure to consider possible consequences and address them as needed.

Jocko Benoit – Prodigal Light – CC BY-NC-ND 2.0.

Certain elements of the solution may need to be delegated out to various people inside and outside the group. Group members may also be assigned to implement a particular part of the solution based on their role in the decision making or because it connects to their area of expertise. Likewise, group members may be tasked with publicizing the solution or “selling” it to a particular group of stakeholders. Last, the group should consider its future. In some cases, the group will get to decide if it will stay together and continue working on other tasks or if it will disband. In other cases, outside forces determine the group’s fate.

“Getting Competent”

Problem Solving and Group Presentations

Giving a group presentation requires that individual group members and the group as a whole solve many problems and make many decisions. Although having more people involved in a presentation increases logistical difficulties and has the potential to create more conflict, a well-prepared and well-delivered group presentation can be more engaging and effective than a typical presentation. The main problems facing a group giving a presentation are (1) dividing responsibilities, (2) coordinating schedules and time management, and (3) working out the logistics of the presentation delivery.

In terms of dividing responsibilities, assigning individual work at the first meeting and then trying to fit it all together before the presentation (which is what many college students do when faced with a group project) is not the recommended method. Integrating content and visual aids created by several different people into a seamless final product takes time and effort, and the person “stuck” with this job at the end usually ends up developing some resentment toward his or her group members. While it’s OK for group members to do work independently outside of group meetings, spend time working together to help set up some standards for content and formatting expectations that will help make later integration of work easier. Taking the time to complete one part of the presentation together can help set those standards for later individual work. Discuss the roles that various group members will play openly so there isn’t role confusion. There could be one point person for keeping track of the group’s progress and schedule, one point person for communication, one point person for content integration, one point person for visual aids, and so on. Each person shouldn’t do all that work on his or her own but help focus the group’s attention on his or her specific area during group meetings (Stanton, 2009).

Scheduling group meetings is one of the most challenging problems groups face, given people’s busy lives. From the beginning, it should be clearly communicated that the group needs to spend considerable time in face-to-face meetings, and group members should know that they may have to make an occasional sacrifice to attend. Especially important is the commitment to scheduling time to rehearse the presentation. Consider creating a contract of group guidelines that includes expectations for meeting attendance to increase group members’ commitment.

Group presentations require members to navigate many logistics of their presentation. While it may be easier for a group to assign each member to create a five-minute segment and then transition from one person to the next, this is definitely not the most engaging method. Creating a master presentation and then assigning individual speakers creates a more fluid and dynamic presentation and allows everyone to become familiar with the content, which can help if a person doesn’t show up to present and during the question-and-answer section. Once the content of the presentation is complete, figure out introductions, transitions, visual aids, and the use of time and space (Stanton, 2012). In terms of introductions, figure out if one person will introduce all the speakers at the beginning, if speakers will introduce themselves at the beginning, or if introductions will occur as the presentation progresses. In terms of transitions, make sure each person has included in his or her speaking notes when presentation duties switch from one person to the next. Visual aids have the potential to cause hiccups in a group presentation if they aren’t fluidly integrated. Practicing with visual aids and having one person control them may help prevent this. Know how long your presentation is and know how you’re going to use the space. Presenters should know how long the whole presentation should be and how long each of their segments should be so that everyone can share the responsibility of keeping time. Also consider the size and layout of the presentation space. You don’t want presenters huddled in a corner until it’s their turn to speak or trapped behind furniture when their turn comes around.

• Of the three main problems facing group presenters, which do you think is the most challenging and why?
• Why do you think people tasked with a group presentation (especially students) prefer to divide the parts up and have members work on them independently before coming back together and integrating each part? What problems emerge from this method? In what ways might developing a master presentation and then assigning parts to different speakers be better than the more divided method? What are the drawbacks to the master presentation method?

Decision Making in Groups

We all engage in personal decision making daily, and we all know that some decisions are more difficult than others. When we make decisions in groups, we face some challenges that we do not face in our personal decision making, but we also stand to benefit from some advantages of group decision making (Napier & Gershenfeld, 2004). Group decision making can appear fair and democratic but really only be a gesture that covers up the fact that certain group members or the group leader have already decided. Group decision making also takes more time than individual decisions and can be burdensome if some group members do not do their assigned work, divert the group with self-centered or unproductive role behaviors, or miss meetings. Conversely, though, group decisions are often more informed, since all group members develop a shared understanding of a problem through discussion and debate. The shared understanding may also be more complex and deep than what an individual would develop, because the group members are exposed to a variety of viewpoints that can broaden their own perspectives. Group decisions also benefit from synergy, one of the key advantages of group communication that we discussed earlier. Most groups do not use a specific method of decision making, perhaps thinking that they’ll work things out as they go. This can lead to unequal participation, social loafing, premature decisions, prolonged discussion, and a host of other negative consequences. So in this section we will learn some practices that will prepare us for good decision making and some specific techniques we can use to help us reach a final decision.

Brainstorming before Decision Making

Before groups can make a decision, they need to generate possible solutions to their problem. The most commonly used method is brainstorming, although most people don’t follow the recommended steps of brainstorming. As you’ll recall, brainstorming refers to the quick generation of ideas free of evaluation. The originator of the term brainstorming said the following four rules must be followed for the technique to be effective (Osborn, 1959):

• Evaluation of ideas is forbidden.
• Wild and crazy ideas are encouraged.
• Quantity of ideas, not quality, is the goal.
• New combinations of ideas presented are encouraged.

To make brainstorming more of a decision-making method rather than an idea-generating method, group communication scholars have suggested additional steps that precede and follow brainstorming (Cragan & Wright, 1991).

• Do a warm-up brainstorming session. Some people are more apprehensive about publicly communicating their ideas than others are, and a warm-up session can help ease apprehension and prime group members for task-related idea generation. The warm-up can be initiated by anyone in the group and should only go on for a few minutes. To get things started, a person could ask, “If our group formed a band, what would we be called?” or “What other purposes could a mailbox serve?” In the previous examples, the first warm up gets the group’s more abstract creative juices flowing, while the second focuses more on practical and concrete ideas.
• Do the actual brainstorming session. This session shouldn’t last more than thirty minutes and should follow the four rules of brainstorming mentioned previously. To ensure that the fourth rule is realized, the facilitator could encourage people to piggyback off each other’s ideas.
• Eliminate duplicate ideas. After the brainstorming session is over, group members can eliminate (without evaluating) ideas that are the same or very similar.
• Clarify, organize, and evaluate ideas. Before evaluation, see if any ideas need clarification. Then try to theme or group ideas together in some orderly fashion. Since “wild and crazy” ideas are encouraged, some suggestions may need clarification. If it becomes clear that there isn’t really a foundation to an idea and that it is too vague or abstract and can’t be clarified, it may be eliminated. As a caution though, it may be wise to not throw out off-the-wall ideas that are hard to categorize and to instead put them in a miscellaneous or “wild and crazy” category.

Discussion before Decision Making

The nominal group technique guides decision making through a four-step process that includes idea generation and evaluation and seeks to elicit equal contributions from all group members (Delbecq & Ven de Ven, 1971). This method is useful because the procedure involves all group members systematically, which fixes the problem of uneven participation during discussions. Since everyone contributes to the discussion, this method can also help reduce instances of social loafing. To use the nominal group technique, do the following:

• Silently and individually list ideas.
• Create a master list of ideas.
• Clarify ideas as needed.
• Take a secret vote to rank group members’ acceptance of ideas.

During the first step, have group members work quietly, in the same space, to write down every idea they have to address the task or problem they face. This shouldn’t take more than twenty minutes. Whoever is facilitating the discussion should remind group members to use brainstorming techniques, which means they shouldn’t evaluate ideas as they are generated. Ask group members to remain silent once they’ve finished their list so they do not distract others.

During the second step, the facilitator goes around the group in a consistent order asking each person to share one idea at a time. As the idea is shared, the facilitator records it on a master list that everyone can see. Keep track of how many times each idea comes up, as that could be an idea that warrants more discussion. Continue this process until all the ideas have been shared. As a note to facilitators, some group members may begin to edit their list or self-censor when asked to provide one of their ideas. To limit a person’s apprehension with sharing his or her ideas and to ensure that each idea is shared, I have asked group members to exchange lists with someone else so they can share ideas from the list they receive without fear of being personally judged.

During step three, the facilitator should note that group members can now ask for clarification on ideas on the master list. Do not let this discussion stray into evaluation of ideas. To help avoid an unnecessarily long discussion, it may be useful to go from one person to the next to ask which ideas need clarifying and then go to the originator(s) of the idea in question for clarification.

During the fourth step, members use a voting ballot to rank the acceptability of the ideas on the master list. If the list is long, you may ask group members to rank only their top five or so choices. The facilitator then takes up the secret ballots and reviews them in a random order, noting the rankings of each idea. Ideally, the highest ranked idea can then be discussed and decided on. The nominal group technique does not carry a group all the way through to the point of decision; rather, it sets the group up for a roundtable discussion or use of some other method to evaluate the merits of the top ideas.

Specific Decision-Making Techniques

Some decision-making techniques involve determining a course of action based on the level of agreement among the group members. These methods include majority, expert, authority, and consensus rule. Table 14.1 “Pros and Cons of Agreement-Based Decision-Making Techniques” reviews the pros and cons of each of these methods.

Majority rule is a simple method of decision making based on voting. In most cases a majority is considered half plus one.

Becky McCray – Voting – CC BY-NC-ND 2.0.

Majority rule is a commonly used decision-making technique in which a majority (one-half plus one) must agree before a decision is made. A show-of-hands vote, a paper ballot, or an electronic voting system can determine the majority choice. Many decision-making bodies, including the US House of Representatives, Senate, and Supreme Court, use majority rule to make decisions, which shows that it is often associated with democratic decision making, since each person gets one vote and each vote counts equally. Of course, other individuals and mediated messages can influence a person’s vote, but since the voting power is spread out over all group members, it is not easy for one person or party to take control of the decision-making process. In some cases—for example, to override a presidential veto or to amend the constitution—a super majority of two-thirds may be required to make a decision.

Minority rule is a decision-making technique in which a designated authority or expert has final say over a decision and may or may not consider the input of other group members. When a designated expert makes a decision by minority rule, there may be buy-in from others in the group, especially if the members of the group didn’t have relevant knowledge or expertise. When a designated authority makes decisions, buy-in will vary based on group members’ level of respect for the authority. For example, decisions made by an elected authority may be more accepted by those who elected him or her than by those who didn’t. As with majority rule, this technique can be time saving. Unlike majority rule, one person or party can have control over the decision-making process. This type of decision making is more similar to that used by monarchs and dictators. An obvious negative consequence of this method is that the needs or wants of one person can override the needs and wants of the majority. A minority deciding for the majority has led to negative consequences throughout history. The white Afrikaner minority that ruled South Africa for decades instituted apartheid, which was a system of racial segregation that disenfranchised and oppressed the majority population. The quality of the decision and its fairness really depends on the designated expert or authority.

Consensus rule is a decision-making technique in which all members of the group must agree on the same decision. On rare occasions, a decision may be ideal for all group members, which can lead to unanimous agreement without further debate and discussion. Although this can be positive, be cautious that this isn’t a sign of groupthink. More typically, consensus is reached only after lengthy discussion. On the plus side, consensus often leads to high-quality decisions due to the time and effort it takes to get everyone in agreement. Group members are also more likely to be committed to the decision because of their investment in reaching it. On the negative side, the ultimate decision is often one that all group members can live with but not one that’s ideal for all members. Additionally, the process of arriving at consensus also includes conflict, as people debate ideas and negotiate the interpersonal tensions that may result.

Table 14.1 Pros and Cons of Agreement-Based Decision-Making Techniques

“Getting Critical”

Six Hats Method of Decision Making

Edward de Bono developed the Six Hats method of thinking in the late 1980s, and it has since become a regular feature in decision-making training in business and professional contexts (de Bono, 1985). The method’s popularity lies in its ability to help people get out of habitual ways of thinking and to allow group members to play different roles and see a problem or decision from multiple points of view. The basic idea is that each of the six hats represents a different way of thinking, and when we figuratively switch hats, we switch the way we think. The hats and their style of thinking are as follows:

• White hat. Objective—focuses on seeking information such as data and facts and then processes that information in a neutral way.
• Red hat. Emotional—uses intuition, gut reactions, and feelings to judge information and suggestions.
• Black hat. Negative—focuses on potential risks, points out possibilities for failure, and evaluates information cautiously and defensively.
• Yellow hat. Positive—is optimistic about suggestions and future outcomes, gives constructive and positive feedback, points out benefits and advantages.
• Green hat. Creative—tries to generate new ideas and solutions, thinks “outside the box.”
• Blue hat. Philosophical—uses metacommunication to organize and reflect on the thinking and communication taking place in the group, facilitates who wears what hat and when group members change hats.

Specific sequences or combinations of hats can be used to encourage strategic thinking. For example, the group leader may start off wearing the Blue Hat and suggest that the group start their decision-making process with some “White Hat thinking” in order to process through facts and other available information. During this stage, the group could also process through what other groups have done when faced with a similar problem. Then the leader could begin an evaluation sequence starting with two minutes of “Yellow Hat thinking” to identify potential positive outcomes, then “Black Hat thinking” to allow group members to express reservations about ideas and point out potential problems, then “Red Hat thinking” to get people’s gut reactions to the previous discussion, then “Green Hat thinking” to identify other possible solutions that are more tailored to the group’s situation or completely new approaches. At the end of a sequence, the Blue Hat would want to summarize what was said and begin a new sequence. To successfully use this method, the person wearing the Blue Hat should be familiar with different sequences and plan some of the thinking patterns ahead of time based on the problem and the group members. Each round of thinking should be limited to a certain time frame (two to five minutes) to keep the discussion moving.

• This decision-making method has been praised because it allows group members to “switch gears” in their thinking and allows for role playing, which lets people express ideas more freely. How can this help enhance critical thinking? Which combination of hats do you think would be best for a critical thinking sequence?
• What combinations of hats might be useful if the leader wanted to break the larger group up into pairs and why? For example, what kind of thinking would result from putting Yellow and Red together, Black and White together, or Red and White together, and so on?
• Based on your preferred ways of thinking and your personality, which hat would be the best fit for you? Which would be the most challenging? Why?

Influences on Decision Making

Many factors influence the decision-making process. For example, how might a group’s independence or access to resources affect the decisions they make? What potential advantages and disadvantages come with decisions made by groups that are more or less similar in terms of personality and cultural identities? In this section, we will explore how situational, personality, and cultural influences affect decision making in groups.

Situational Influences on Decision Making

A group’s situational context affects decision making. One key situational element is the degree of freedom that the group has to make its own decisions, secure its own resources, and initiate its own actions. Some groups have to go through multiple approval processes before they can do anything, while others are self-directed, self-governing, and self-sustaining. Another situational influence is uncertainty. In general, groups deal with more uncertainty in decision making than do individuals because of the increased number of variables that comes with adding more people to a situation. Individual group members can’t know what other group members are thinking, whether or not they are doing their work, and how committed they are to the group. So the size of a group is a powerful situational influence, as it adds to uncertainty and complicates communication.

Access to information also influences a group. First, the nature of the group’s task or problem affects its ability to get information. Group members can more easily make decisions about a problem when other groups have similarly experienced it. Even if the problem is complex and serious, the group can learn from other situations and apply what it learns. Second, the group must have access to flows of information. Access to archives, electronic databases, and individuals with relevant experience is necessary to obtain any relevant information about similar problems or to do research on a new or unique problem. In this regard, group members’ formal and information network connections also become important situational influences.

The urgency of a decision can have a major influence on the decision-making process. As a situation becomes more urgent, it requires more specific decision-making methods and types of communication.

Judith E. Bell – Urgent – CC BY-SA 2.0.

The origin and urgency of a problem are also situational factors that influence decision making. In terms of origin, problems usually occur in one of four ways:

• Something goes wrong. Group members must decide how to fix or stop something. Example—a firehouse crew finds out that half of the building is contaminated with mold and must be closed down.
• Expectations change or increase. Group members must innovate more efficient or effective ways of doing something. Example—a firehouse crew finds out that the district they are responsible for is being expanded.
• Something goes wrong and expectations change or increase. Group members must fix/stop and become more efficient/effective. Example—the firehouse crew has to close half the building and must start responding to more calls due to the expanding district.
• The problem existed from the beginning. Group members must go back to the origins of the situation and walk through and analyze the steps again to decide what can be done differently. Example—a firehouse crew has consistently had to work with minimal resources in terms of building space and firefighting tools.

In each of the cases, the need for a decision may be more or less urgent depending on how badly something is going wrong, how high the expectations have been raised, or the degree to which people are fed up with a broken system. Decisions must be made in situations ranging from crisis level to mundane.

Personality Influences on Decision Making

A long-studied typology of value orientations that affect decision making consists of the following types of decision maker: the economic, the aesthetic, the theoretical, the social, the political, and the religious (Spranger, 1928).

• The economic decision maker makes decisions based on what is practical and useful.
• The aesthetic decision maker makes decisions based on form and harmony, desiring a solution that is elegant and in sync with the surroundings.
• The theoretical decision maker wants to discover the truth through rationality.
• The social decision maker emphasizes the personal impact of a decision and sympathizes with those who may be affected by it.
• The political decision maker is interested in power and influence and views people and/or property as divided into groups that have different value.
• The religious decision maker seeks to identify with a larger purpose, works to unify others under that goal, and commits to a viewpoint, often denying one side and being dedicated to the other.

In the United States, economic, political, and theoretical decision making tend to be more prevalent decision-making orientations, which likely corresponds to the individualistic cultural orientation with its emphasis on competition and efficiency. But situational context, as we discussed before, can also influence our decision making.

Personality affects decision making. For example, “economic” decision makers decide based on what is practical and useful.

One Way Stock – Tough Decisions Ahead – CC BY-ND 2.0.

The personalities of group members, especially leaders and other active members, affect the climate of the group. Group member personalities can be categorized based on where they fall on a continuum anchored by the following descriptors: dominant/submissive, friendly/unfriendly, and instrumental/emotional (Cragan & Wright, 1999). The more group members there are in any extreme of these categories, the more likely that the group climate will also shift to resemble those characteristics.

• Dominant versus submissive. Group members that are more dominant act more independently and directly, initiate conversations, take up more space, make more direct eye contact, seek leadership positions, and take control over decision-making processes. More submissive members are reserved, contribute to the group only when asked to, avoid eye contact, and leave their personal needs and thoughts unvoiced or give into the suggestions of others.
• Friendly versus unfriendly. Group members on the friendly side of the continuum find a balance between talking and listening, don’t try to win at the expense of other group members, are flexible but not weak, and value democratic decision making. Unfriendly group members are disagreeable, indifferent, withdrawn, and selfish, which leads them to either not invest in decision making or direct it in their own interest rather than in the interest of the group.
• Instrumental versus emotional. Instrumental group members are emotionally neutral, objective, analytical, task-oriented, and committed followers, which leads them to work hard and contribute to the group’s decision making as long as it is orderly and follows agreed-on rules. Emotional group members are creative, playful, independent, unpredictable, and expressive, which leads them to make rash decisions, resist group norms or decision-making structures, and switch often from relational to task focus.

Cultural Context and Decision Making

Just like neighborhoods, schools, and countries, small groups vary in terms of their degree of similarity and difference. Demographic changes in the United States and increases in technology that can bring different people together make it more likely that we will be interacting in more and more heterogeneous groups (Allen, 2011). Some small groups are more homogenous, meaning the members are more similar, and some are more heterogeneous, meaning the members are more different. Diversity and difference within groups has advantages and disadvantages. In terms of advantages, research finds that, in general, groups that are culturally heterogeneous have better overall performance than more homogenous groups (Haslett & Ruebush, 1999). Additionally, when group members have time to get to know each other and competently communicate across their differences, the advantages of diversity include better decision making due to different perspectives (Thomas, 1999). Unfortunately, groups often operate under time constraints and other pressures that make the possibility for intercultural dialogue and understanding difficult. The main disadvantage of heterogeneous groups is the possibility for conflict, but given that all groups experience conflict, this isn’t solely due to the presence of diversity. We will now look more specifically at how some of the cultural value orientations we’ve learned about already in this book can play out in groups with international diversity and how domestic diversity in terms of demographics can also influence group decision making.

International Diversity in Group Interactions

Cultural value orientations such as individualism/collectivism, power distance, and high-/low-context communication styles all manifest on a continuum of communication behaviors and can influence group decision making. Group members from individualistic cultures are more likely to value task-oriented, efficient, and direct communication. This could manifest in behaviors such as dividing up tasks into individual projects before collaboration begins and then openly debating ideas during discussion and decision making. Additionally, people from cultures that value individualism are more likely to openly express dissent from a decision, essentially expressing their disagreement with the group. Group members from collectivistic cultures are more likely to value relationships over the task at hand. Because of this, they also tend to value conformity and face-saving (often indirect) communication. This could manifest in behaviors such as establishing norms that include periods of socializing to build relationships before task-oriented communication like negotiations begin or norms that limit public disagreement in favor of more indirect communication that doesn’t challenge the face of other group members or the group’s leader. In a group composed of people from a collectivistic culture, each member would likely play harmonizing roles, looking for signs of conflict and resolving them before they become public.

Power distance can also affect group interactions. Some cultures rank higher on power-distance scales, meaning they value hierarchy, make decisions based on status, and believe that people have a set place in society that is fairly unchangeable. Group members from high-power-distance cultures would likely appreciate a strong designated leader who exhibits a more directive leadership style and prefer groups in which members have clear and assigned roles. In a group that is homogenous in terms of having a high-power-distance orientation, members with higher status would be able to openly provide information, and those with lower status may not provide information unless a higher status member explicitly seeks it from them. Low-power-distance cultures do not place as much value and meaning on status and believe that all group members can participate in decision making. Group members from low-power-distance cultures would likely freely speak their mind during a group meeting and prefer a participative leadership style.

How much meaning is conveyed through the context surrounding verbal communication can also affect group communication. Some cultures have a high-context communication style in which much of the meaning in an interaction is conveyed through context such as nonverbal cues and silence. Group members from high-context cultures may avoid saying something directly, assuming that other group members will understand the intended meaning even if the message is indirect. So if someone disagrees with a proposed course of action, he or she may say, “Let’s discuss this tomorrow,” and mean, “I don’t think we should do this.” Such indirect communication is also a face-saving strategy that is common in collectivistic cultures. Other cultures have a low-context communication style that places more importance on the meaning conveyed through words than through context or nonverbal cues. Group members from low-context cultures often say what they mean and mean what they say. For example, if someone doesn’t like an idea, they might say, “I think we should consider more options. This one doesn’t seem like the best we can do.”

In any of these cases, an individual from one culture operating in a group with people of a different cultural orientation could adapt to the expectations of the host culture, especially if that person possesses a high degree of intercultural communication competence (ICC). Additionally, people with high ICC can also adapt to a group member with a different cultural orientation than the host culture. Even though these cultural orientations connect to values that affect our communication in fairly consistent ways, individuals may exhibit different communication behaviors depending on their own individual communication style and the situation.

Domestic Diversity and Group Communication

While it is becoming more likely that we will interact in small groups with international diversity, we are guaranteed to interact in groups that are diverse in terms of the cultural identities found within a single country or the subcultures found within a larger cultural group.

Gender stereotypes sometimes influence the roles that people play within a group. For example, the stereotype that women are more nurturing than men may lead group members (both male and female) to expect that women will play the role of supporters or harmonizers within the group. Since women have primarily performed secretarial work since the 1900s, it may also be expected that women will play the role of recorder. In both of these cases, stereotypical notions of gender place women in roles that are typically not as valued in group communication. The opposite is true for men. In terms of leadership, despite notable exceptions, research shows that men fill an overwhelmingly disproportionate amount of leadership positions. We are socialized to see certain behaviors by men as indicative of leadership abilities, even though they may not be. For example, men are often perceived to contribute more to a group because they tend to speak first when asked a question or to fill a silence and are perceived to talk more about task-related matters than relationally oriented matters. Both of these tendencies create a perception that men are more engaged with the task. Men are also socialized to be more competitive and self-congratulatory, meaning that their communication may be seen as dedicated and their behaviors seen as powerful, and that when their work isn’t noticed they will be more likely to make it known to the group rather than take silent credit. Even though we know that the relational elements of a group are crucial for success, even in high-performance teams, that work is not as valued in our society as the task-related work.

Despite the fact that some communication patterns and behaviors related to our typical (and stereotypical) gender socialization affect how we interact in and form perceptions of others in groups, the differences in group communication that used to be attributed to gender in early group communication research seem to be diminishing. This is likely due to the changing organizational cultures from which much group work emerges, which have now had more than sixty years to adjust to women in the workplace. It is also due to a more nuanced understanding of gender-based research, which doesn’t take a stereotypical view from the beginning as many of the early male researchers did. Now, instead of biological sex being assumed as a factor that creates inherent communication differences, group communication scholars see that men and women both exhibit a range of behaviors that are more or less feminine or masculine. It is these gendered behaviors, and not a person’s gender, that seem to have more of an influence on perceptions of group communication. Interestingly, group interactions are still masculinist in that male and female group members prefer a more masculine communication style for task leaders and that both males and females in this role are more likely to adapt to a more masculine communication style. Conversely, men who take on social-emotional leadership behaviors adopt a more feminine communication style. In short, it seems that although masculine communication traits are more often associated with high status positions in groups, both men and women adapt to this expectation and are evaluated similarly (Haslett & Ruebush, 1999).

Other demographic categories are also influential in group communication and decision making. In general, group members have an easier time communicating when they are more similar than different in terms of race and age. This ease of communication can make group work more efficient, but the homogeneity may sacrifice some creativity. As we learned earlier, groups that are diverse (e.g., they have members of different races and generations) benefit from the diversity of perspectives in terms of the quality of decision making and creativity of output.

In terms of age, for the first time since industrialization began, it is common to have three generations of people (and sometimes four) working side by side in an organizational setting. Although four generations often worked together in early factories, they were segregated based on their age group, and a hierarchy existed with older workers at the top and younger workers at the bottom. Today, however, generations interact regularly, and it is not uncommon for an older person to have a leader or supervisor who is younger than him or her (Allen, 2011). The current generations in the US workplace and consequently in work-based groups include the following:

• The Silent Generation. Born between 1925 and 1942, currently in their midsixties to mideighties, this is the smallest generation in the workforce right now, as many have retired or left for other reasons. This generation includes people who were born during the Great Depression or the early part of World War II, many of whom later fought in the Korean War (Clarke, 1970).
• The Baby Boomers. Born between 1946 and 1964, currently in their late forties to midsixties, this is the largest generation in the workforce right now. Baby boomers are the most populous generation born in US history, and they are working longer than previous generations, which means they will remain the predominant force in organizations for ten to twenty more years.
• Generation X. Born between 1965 and 1981, currently in their early thirties to midforties, this generation was the first to see technology like cell phones and the Internet make its way into classrooms and our daily lives. Compared to previous generations, “Gen-Xers” are more diverse in terms of race, religious beliefs, and sexual orientation and also have a greater appreciation for and understanding of diversity.
• Generation Y. Born between 1982 and 2000, “Millennials” as they are also called are currently in their late teens up to about thirty years old. This generation is not as likely to remember a time without technology such as computers and cell phones. They are just starting to enter into the workforce and have been greatly affected by the economic crisis of the late 2000s, experiencing significantly high unemployment rates.

The benefits and challenges that come with diversity of group members are important to consider. Since we will all work in diverse groups, we should be prepared to address potential challenges in order to reap the benefits. Diverse groups may be wise to coordinate social interactions outside of group time in order to find common ground that can help facilitate interaction and increase group cohesion. We should be sensitive but not let sensitivity create fear of “doing something wrong” that then prevents us from having meaningful interactions. Reviewing Chapter 8 “Culture and Communication” will give you useful knowledge to help you navigate both international and domestic diversity and increase your communication competence in small groups and elsewhere.

Key Takeaways

• Every problem has common components: an undesirable situation, a desired situation, and obstacles between the undesirable and desirable situations. Every problem also has a set of characteristics that vary among problems, including task difficulty, number of possible solutions, group member interest in the problem, group familiarity with the problem, and the need for solution acceptance.

The group problem-solving process has five steps:

• Define the problem by creating a problem statement that summarizes it.
• Analyze the problem and create a problem question that can guide solution generation.
• Generate possible solutions. Possible solutions should be offered and listed without stopping to evaluate each one.
• Evaluate the solutions based on their credibility, completeness, and worth. Groups should also assess the potential effects of the narrowed list of solutions.
• Implement and assess the solution. Aside from enacting the solution, groups should determine how they will know the solution is working or not.
• Before a group makes a decision, it should brainstorm possible solutions. Group communication scholars suggest that groups (1) do a warm-up brainstorming session; (2) do an actual brainstorming session in which ideas are not evaluated, wild ideas are encouraged, quantity not quality of ideas is the goal, and new combinations of ideas are encouraged; (3) eliminate duplicate ideas; and (4) clarify, organize, and evaluate ideas. In order to guide the idea-generation process and invite equal participation from group members, the group may also elect to use the nominal group technique.
• Common decision-making techniques include majority rule, minority rule, and consensus rule. With majority rule, only a majority, usually one-half plus one, must agree before a decision is made. With minority rule, a designated authority or expert has final say over a decision, and the input of group members may or may not be invited or considered. With consensus rule, all members of the group must agree on the same decision.

Several factors influence the decision-making process:

• Situational factors include the degree of freedom a group has to make its own decisions, the level of uncertainty facing the group and its task, the size of the group, the group’s access to information, and the origin and urgency of the problem.
• Personality influences on decision making include a person’s value orientation (economic, aesthetic, theoretical, political, or religious), and personality traits (dominant/submissive, friendly/unfriendly, and instrumental/emotional).
• Cultural influences on decision making include the heterogeneity or homogeneity of the group makeup; cultural values and characteristics such as individualism/collectivism, power distance, and high-/low-context communication styles; and gender and age differences.
• Scenario 1. Task difficulty is high, number of possible solutions is high, group interest in problem is high, group familiarity with problem is low, and need for solution acceptance is high.
• Scenario 2. Task difficulty is low, number of possible solutions is low, group interest in problem is low, group familiarity with problem is high, and need for solution acceptance is low.
• Scenario 1: Academic. A professor asks his or her class to decide whether the final exam should be an in-class or take-home exam.
• Scenario 2: Professional. A group of coworkers must decide which person from their department to nominate for a company-wide award.
• Scenario 3: Personal. A family needs to decide how to divide the belongings and estate of a deceased family member who did not leave a will.
• Scenario 4: Civic. A local branch of a political party needs to decide what five key issues it wants to include in the national party’s platform.
• Group communication researchers have found that heterogeneous groups (composed of diverse members) have advantages over homogenous (more similar) groups. Discuss a group situation you have been in where diversity enhanced your and/or the group’s experience.

Adams, K., and Gloria G. Galanes, Communicating in Groups: Applications and Skills , 7th ed. (Boston, MA: McGraw-Hill, 2009), 220–21.

Allen, B. J., Difference Matters: Communicating Social Identity , 2nd ed. (Long Grove, IL: Waveland, 2011), 5.

Bormann, E. G., and Nancy C. Bormann, Effective Small Group Communication , 4th ed. (Santa Rosa, CA: Burgess CA, 1988), 112–13.

Clarke, G., “The Silent Generation Revisited,” Time, June 29, 1970, 46.

Cragan, J. F., and David W. Wright, Communication in Small Group Discussions: An Integrated Approach , 3rd ed. (St. Paul, MN: West Publishing, 1991), 77–78.

de Bono, E., Six Thinking Hats (Boston, MA: Little, Brown, 1985).

Delbecq, A. L., and Andrew H. Ven de Ven, “A Group Process Model for Problem Identification and Program Planning,” The Journal of Applied Behavioral Science 7, no. 4 (1971): 466–92.

Haslett, B. B., and Jenn Ruebush, “What Differences Do Individual Differences in Groups Make?: The Effects of Individuals, Culture, and Group Composition,” in The Handbook of Group Communication Theory and Research , ed. Lawrence R. Frey (Thousand Oaks, CA: Sage, 1999), 133.

Napier, R. W., and Matti K. Gershenfeld, Groups: Theory and Experience , 7th ed. (Boston, MA: Houghton Mifflin, 2004), 292.

Osborn, A. F., Applied Imagination (New York: Charles Scribner’s Sons, 1959).

Spranger, E., Types of Men (New York: Steckert, 1928).

Stanton, C., “How to Deliver Group Presentations: The Unified Team Approach,” Six Minutes Speaking and Presentation Skills , November 3, 2009, accessed August 28, 2012, http://sixminutes.dlugan.com/group-presentations-unified-team-approach .

Thomas, D. C., “Cultural Diversity and Work Group Effectiveness: An Experimental Study,” Journal of Cross-Cultural Psychology 30, no. 2 (1999): 242–63.

Communication in the Real World Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Faculty & Staff Insights

The power—and discipline—of clearly articulating the problem

Learn how a clear problem statement, combined with the mind's natural conscious and automatic processing functions, can help your organization can achieve its goals more efficiently.

In Nelson Repenning’s article for MIT Sloan Management Review , “ The Most Underrated Skill in Management ," he and his co-authors share a proven way to improve organizations' methods and practices to stay relevant in today's world. While many leaders try to spearhead change through complete upheaval, continuous small improvements are what achieve these sought-after impacts. According to Repenning, by formulating a clear problem statement, organizations can give teams strategic direction and achieve company goals more efficiently.

How our minds solve problems

One reason we need a structure for problem solving is because our brains are prone to jump from problem to solution without complete knowledge. This hasty conclusion can prevent innovation, waste time and money, and create frustration.

Research conducted over the last few decades indicates that the human brain has at least two different methods for tackling problems, which psychologists and cognitive scientists sometimes call automatic processing and conscious processing (also sometimes known as system 1 and system 2). 

Conscious processing is part of your brain that you control. This process can be precise and powerful. This is the only process in the brain that is "capable of forming a mental picture of a situation at hand and then playing out different possible scenarios," even those that have not occurred before. This ability allows humans to innovate and learn. 

However, this processing technique has its downfalls. It is a slow process, and our finite physical capacity limits us to one problem at a time. With the high expense, the brain has evolved to minimize this so called “System 1” processing for specific instances.

Automatic processing represents the part of your brain you cannot control. We are only aware of the results, either when a thought pops into our head, or a physical response occurs. “System 2” processing works with association or pattern matching. The automatic processor attempts to match the current challenge to a previous comparable situation to use the experience(s) as a guide for how to act. This "associative machine" can identify subtle patterns in the environment to make split-second decisions. The downfall of automatic processing is that in guiding us to the status quo, it can impede innovation.

Structured problem-solving: Leverage the strengths of conscious processing 

To complement that fast thinking with a more deliberate approach, structured problem-solving entails developing a logical argument that links the observed data to root causes and, eventually, to a solution. “Developing this logical path increases the chance that you will leverage the strengths of conscious processing and may also create the conditions for generating and then evaluating an unconscious breakthrough,” instruct the authors. 

The basic elements of a good problem statement :

• It connects to a clear and specific goal within the organization
• It clearly articulates the gap between the current state and the goal
• The key variables—the target, current state, and the gap—are quantifiable
• It is neutral concerning possible diagnoses or solutions
• It is small in scope and easily tackled

Things to consider when creating a problem statement :

• Is this problem important? The problem statement should have a direct connection to the organization's overall mission and target.
• Is the gap between the future goal and the current situation clearly articulated? The steps to close this gap should be clear and easy to understand.
• Is your progress in closing the gap measurable/quantifiable? Being able to measure the gap between the current state and your target precisely will support an effective project. While “soft” variables like customer satisfaction and employee trust can be hard to measure, they can be quantified (e.g., more of both is better!).
• Is the stated problem neutral? Make sure the problem does not presuppose anything about the root cause or solution.
• Is your problem statement specific? The problem should focus on a specific manifestation of the larger issue that your organization cares about.

Common mistakes to look for :

• Failing to formulate the problem. Never assume that the entire team already agrees on the problem.
• Problem-statement as diagnoses or solutions. Make sure the problem statement focuses on the goal or target that aligns with the organization, not an assumption. Skipping steps in the logical chain means missing opportunities to engage in conscious and automatic processing.
• Lack of a clear gap. Make sure to fully articulate the gap between the current state and the future goal.
• Too broad. Broadly scoped problem statements lead to "large, costly, and slow initiatives." Make sure to focus on an acute problem to bring quick results. 

Structured Problem-Solving

Structured problem-solving mirrors the essential elements of the scientific method—testing hypotheses through controlled experimentation. 

In the last two decades, the authors have honed a hybrid approach to guiding and reporting on structured problem-solving that is both simple and effective. They capture their approach in a version of Toyota’s famous A3 form that they have modified to enable its use for work in settings other than manufacturing. You can learn the steps for the A3 process in their MIT SMR article. Their process takes advantage of the innate processes of the brain to define and tackle inefficiencies.

You can also learn more about good problem formulation and structured problem-solving in Repenning’s related Executive Education course, Visual Management for Competitive Advantage: MIT's Approach to Efficient and Agile Work . Repenning also teaches in Leading Strategic Change and in the self-paced online courses Business Process Design for Strategic Management and Business Sustainability Strategy .

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• A Step-by-Step Guide to A3 Problem Solving Methodology

• Learn Lean Sigma
• Problem Solving

Problem-solving is an important component of any business or organization. It entails identifying, analyzing, and resolving problems in order to improve processes, drive results, and foster a culture of continuous improvement. A3 Problem solving is one of the most effective problem-solving methodologies.

A3 Problem solving is a structured and systematic approach to problem-solving that originated with the lean manufacturing methodology. It visualizes the problem-solving process using a one-page document known as an A3 report. The A3 report provides an overview of the problem, data analysis, root causes, solutions, and results in a clear and concise manner.

A3 Problem Solving has numerous advantages, including improved communication, better decision-making, increased efficiency, and reduced waste. It is a powerful tool for businesses of all sizes and industries, and it is especially useful for solving complex and multi-faceted problems.

In this blog post, we will walk you through the A3 Problem Solving methodology step by step. Whether you are new to A3 Problem Solving or simply want to improve your skills, this guide will help you understand and apply the process in your workplace.

Table of Contents

What is a3 problem solving.

A3 Problem Solving is a structured and systematic approach to problem-solving that makes use of a one-page document called an A3 report to visually represent the process. The A3 report provides an overview of the problem, data analysis, root causes, solutions, and results in a clear and concise manner. The method was created within the framework of the Lean manufacturing methodology and is based on the principles of continuous improvement and visual management.

Looking for a A3 Problem solving template? Click here

Origin and History of A3 Problem Solving

A3 Problem Solving was developed by Toyota Motor Corporation and was first used in the manufacture of automobiles. The term “A3” refers to the size of the paper used to create the report, which is an ISO standard known as “A3”. The goal of the A3 report is to provide a visual representation of the problem-solving process that all members of the organisation can easily understand and share. A3 Problem Solving has been adopted by organisations in a variety of industries over the years, and it has become a widely used and recognised method for problem-solving.

Key Principles of A3 Problem Solving

The following are the key principles of A3 Problem Solving:

• Define the problem clearly and concisely
• Gather and analyze data to gain a deep understanding of the problem
• Identify the root causes of the problem
• Develop and implement effective solutions
• Evaluate results and continuously improve

These principles serve as the foundation of the A3 Problem Solving methodology and are intended to assist organisations in continuously improving and achieving their objectives. Organizations can effectively solve problems, identify areas for improvement, and drive results by adhering to these principles.

Step 1: Define the Problem

Importance of clearly defining the problem.

The first step in the A3 Problem Solving process is critical because it lays the groundwork for the remaining steps. To define the problem clearly and accurately, you must first understand the problem and identify the underlying root cause. This step is critical because if the problem is not correctly defined, the rest of the process will be based on incorrect information, and the solution developed may not address the issue effectively.

The significance of defining the problem clearly cannot be overstated. It aids in the collection and analysis of relevant data, which is critical for developing effective solutions. When the problem is clearly defined, the data gathered is more relevant and targeted, resulting in a more comprehensive understanding of the issue. This will enable the development of solutions that are more likely to be effective because they are founded on a thorough and accurate understanding of the problem.

However, if the problem is not clearly defined, the data gathered may be irrelevant or incorrect, resulting in incorrect conclusions and ineffective solutions. Furthermore, the process of collecting and analysing data can become time-consuming and inefficient, resulting in resource waste. Furthermore, if the problem is not accurately defined, the solutions developed may fail to address the root cause of the problem, resulting in ongoing issues and a lack of improvement.

Techniques for Defining the Problem

The first step in the A3 Problem Solving process is to clearly and accurately define the problem. This is an important step because a clearly defined problem will help to ensure that the appropriate data is collected and solutions are developed. If the problem is not clearly defined, incorrect data may be collected, solutions that do not address the root cause of the problem, and time and resources may be wasted.

A problem can be defined using a variety of techniques, including brainstorming , root cause analysis , process mapping , and Ishikawa diagrams . Each of these techniques has its own advantages and disadvantages and can be used in a variety of situations depending on the nature of the problem.

Best Practice for Defining the Problem

In addition to brainstorming, root cause analysis, process mapping, and Ishikawa diagram s, best practices should be followed when defining a problem in A3 Problem Solving. Among these best practices are:

• Define the issue in a specific and quantifiable way: It is critical to be specific and concise when defining the problem, as well as to quantify the problem in terms of its impact. This will help to ensure that all stakeholders understand the problem and that data collection is focused on the right areas.
• Focus on the problem’s root cause: The A3 Problem Solving methodology is intended to assist organisations in identifying and addressing the root cause of a problem, rather than just the symptoms. Organizations can ensure that their solutions are effective and long-lasting by focusing on the root cause of the problem.
• Ascertain that all stakeholders agree on the problem’s definition: All stakeholders must agree on the definition of the problem for the A3 Problem Solving process to be effective. This ensures that everyone is working towards the same goal and that the solutions developed are relevant and appropriate.
• Consider the problem’s impact on the organisation and its stakeholders: It is critical to consider the impact of the problem on the organisation and its stakeholders when defining it. This will assist in ensuring that the appropriate data is gathered and that the solutions developed are relevant and appropriate.

Organizations can ensure that their problem is defined in a way that allows for effective data collection, analysis, and solution development by following these best practices. This will aid in the development of appropriate solutions and the effective resolution of the problem, resulting in improvements in the organization’s processes and outcomes.

Step 2: Gather Data

Gathering data in a3 problem solving.

Data collection is an important step in the A3 Problem Solving process because it allows organisations to gain a thorough understanding of the problem they are attempting to solve. This step entails gathering pertinent information about the problem, such as data on its origin, impact, and any related factors. This information is then used to help identify root causes and develop effective solutions.

One of the most important advantages of data collection in A3 Problem Solving is that it allows organisations to identify patterns and trends in data, which can be useful in determining the root cause of the problem. This information can then be used to create effective solutions that address the problem’s root cause rather than just its symptoms.

In A3 Problem Solving, data collection is a collaborative effort involving all stakeholders, including those directly impacted by the problem and those with relevant expertise or experience. Stakeholders can ensure that all relevant information is collected and that the data is accurate and complete by working together.

Overall, data collection is an important step in the A3 Problem Solving process because it serves as the foundation for effective problem-solving. Organizations can gain a deep understanding of the problem they are attempting to solve and develop effective solutions that address its root cause by collecting and analysing relevant data.

Data Collection Methods

In A3 Problem Solving, several data collection methods are available, including:

• Observations
• Process diagrams

The best data collection method will be determined by the problem being solved and the type of data required. To gain a complete understanding of the problem, it is critical to use multiple data collection methods.

Tools for Data Analysis and Visualization

Once the data has been collected, it must be analysed and visualised in order to gain insights into the problem. This process can be aided by the following tools:

• Excel Spreadsheets
• Flow diagrams
• Pareto diagrams
• Scatter Plots
• Control diagrams

These tools can assist in organising data and making it easier to understand. They can also be used to generate visual representations of data, such as graphs and charts, to communicate the findings to others.

Finally, the data collection and analysis step is an important part of the A3 Problem Solving process. Organizations can gain a better understanding of the problem and develop effective solutions by collecting and analysing relevant data.

Step 3: Identify Root Causes

Identifying the root causes of the problem is the third step in the A3 Problem Solving process. This step is critical because it assists organisations in understanding the root causes of a problem rather than just its symptoms. Once the underlying cause of the problem is identified, it can be addressed more effectively, leading to more long-term solutions.

Overview of the Root Cause Analysis Process

The process of determining the underlying causes of a problem is known as root cause analysis. This process can assist organisations in determining why a problem is occurring and what can be done to prevent it from recurring in the future. The goal of root cause analysis is to identify the underlying cause of a problem rather than just its symptoms, allowing it to be addressed more effectively.

To understand Root cause analysis in more detail check out RCA in our Lean Six Sigma Yellow Belt Course Root Cause Analysis section

Techniques for Identifying Root Causes

There are several techniques for determining the root causes of a problem, including:

• Brainstorming
• Ishikawa diagrams (also known as fishbone diagrams)
• Root Cause Tree Analysis

These methods can be used to investigate the issue in-depth and identify potential root causes. Organizations can gain a deeper understanding of the problem and identify the underlying causes that must be addressed by using these techniques.

Best Practices for Conducting Root Cause Analysis

It is critical to follow these best practices when conducting root cause analysis in A3 Problem Solving:

• Make certain that all stakeholders participate in the root cause analysis process.
• Concentrate on determining the root cause of the problem rather than just its symptoms.
• Take into account all potential root causes, not just the most obvious ones.
• To identify root causes, use a systematic approach, such as the 5 Whys or root cause tree analysis.

Organizations can ensure that root cause analysis is carried out effectively and that the root cause of the problem is identified by adhering to these best practises. This will aid in the development of appropriate solutions and the effective resolution of the problem.

Step 4: Develop Solutions

Developing solutions is the fourth step in the A3 Problem Solving process. This entails generating ideas and options for dealing with the problem, followed by selecting the best solution. The goal is to develop a solution that addresses the root cause of the problem and prevents it from recurring.

Solution Development in A3 Problem Solving

A3 solution development Problem solving is an iterative process in which options are generated and evaluated. The data gathered in the previous steps, as well as the insights and understanding gained from the root cause analysis, guide this process. The solution should be based on a thorough understanding of the problem and address the underlying cause.

Techniques for Developing Solutions

There are several techniques that can be used to develop solutions in A3 Problem Solving, including:

• Brainwriting
• Solution matrix
• Multi voting
• Force field analysis

These techniques can help to generate a range of options and to select the best solution.

Best Practice for Developing Solutions

It is critical to follow the following best practices when developing solutions in A3 Problem Solving:

• Participate in the solution development process with all stakeholders.
• Make certain that the solution addresses the underlying cause of the problem.
• Make certain that the solution is feasible and achievable.
• Consider the solution’s impact on the organisation and its stakeholders.

Organizations can ensure that the solutions they develop are effective and sustainable by adhering to these best practises. This will help to ensure that the problem is addressed effectively and that it does not reoccur.

Step 5: Implement Solutions

The final and most important step in the A3 Problem Solving methodology is solution implementation. This is the stage at which the identified and developed solutions are put into action to address the problem. This step’s goal is to ensure that the solutions are effective, efficient, and long-lasting.

The implementation Process

The implementation process entails putting the solutions developed in the previous step into action. This could include changes to processes, procedures, and systems, as well as employee training and education. To ensure that the solutions are effective, the implementation process should be well-planned and meticulously executed.

Techniques for Implementing Solutions

A3 Problem Solving solutions can be implemented using a variety of techniques, including:

• Piloting the solution on a small scale before broadening its application
• Participating in the implementation process with all relevant stakeholders
• ensuring that the solution is in line with the goals and objectives of the organisation
• Monitoring the solution to determine its effectiveness and make any necessary changes

Best Practice for Implementing Solutions

It is critical to follow these best practices when implementing solutions in A3 Problem Solving:

Make certain that all relevant stakeholders are involved and supportive of the solution. Have a clear implementation plan that outlines the steps, timeline, and resources required. Continuously monitor and evaluate the solution to determine its efficacy and make any necessary changes. Encourage all stakeholders to communicate and collaborate openly. Organizations can ensure that solutions are effectively implemented and problems are effectively addressed by adhering to these best practices. The ultimate goal is to find a long-term solution to the problem and improve the organization’s overall performance.

In conclusion, A3 Problem Solving is a comprehensive and structured methodology for problem-solving that can be applied in various industries and organisations. The A3 Problem Solving process’s five steps – Define the Problem, Gather Data, Identify Root Causes, Develop Solutions, and Implement Solutions – provide a road map for effectively addressing problems and making long-term improvements.

Organizations can improve their problem-solving skills and achieve better results by following the key principles, techniques, and best practices outlined in this guide. As a result, both the organisation and its stakeholders will benefit from increased efficiency, effectiveness, and satisfaction. So, whether you’re an experienced problem solver or just getting started, consider incorporating the A3 Problem Solving methodology into your work and start reaping the benefits right away.

Daniel Croft

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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Problem-Solving in Mathematics Education

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Introduction

Problem-solving approaches appear in all human endeavors. In mathematics, activities such as posing or defining problems and looking for different ways to solve them are central to the development of the discipline. In mathematics education, the systematic study of what the process of formulating and solving problems entails and the ways to structure problem-solving approaches to learn mathematics has been part of the research agenda in mathematics education. How have research and practicing problem-solving approaches changed and evolved in mathematics education, and what themes are currently investigated? Two communities have significantly contributed to the characterization and development of the research and practicing agenda in mathematical problem-solving: mathematicians who recognize that the process of formulating, representing, and solving problems is essential in the development of mathematical knowledge (Polya 1945 ; Hadamard 1945 ; Halmos 1980 ) and mathematics...

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Creative Problem Solving

Finding Innovative Solutions to Challenges

By the Mind Tools Content Team

Imagine that you're vacuuming your house in a hurry because you've got friends coming over. Frustratingly, you're working hard but you're not getting very far. You kneel down, open up the vacuum cleaner, and pull out the bag. In a cloud of dust, you realize that it's full... again. Coughing, you empty it and wonder why vacuum cleaners with bags still exist!

James Dyson, inventor and founder of Dyson® vacuum cleaners, had exactly the same problem, and he used creative problem solving to find the answer. While many companies focused on developing a better vacuum cleaner filter, he realized that he had to think differently and find a more creative solution. So, he devised a revolutionary way to separate the dirt from the air, and invented the world's first bagless vacuum cleaner. [1]

Creative problem solving (CPS) is a way of solving problems or identifying opportunities when conventional thinking has failed. It encourages you to find fresh perspectives and come up with innovative solutions, so that you can formulate a plan to overcome obstacles and reach your goals.

In this article, we'll explore what CPS is, and we'll look at its key principles. We'll also provide a model that you can use to generate creative solutions.

About Creative Problem Solving

Alex Osborn, founder of the Creative Education Foundation, first developed creative problem solving in the 1940s, along with the term "brainstorming." And, together with Sid Parnes, he developed the Osborn-Parnes Creative Problem Solving Process. Despite its age, this model remains a valuable approach to problem solving. [2]

The early Osborn-Parnes model inspired a number of other tools. One of these is the 2011 CPS Learner's Model, also from the Creative Education Foundation, developed by Dr Gerard J. Puccio, Marie Mance, and co-workers. In this article, we'll use this modern four-step model to explore how you can use CPS to generate innovative, effective solutions.

Why Use Creative Problem Solving?

Dealing with obstacles and challenges is a regular part of working life, and overcoming them isn't always easy. To improve your products, services, communications, and interpersonal skills, and for you and your organization to excel, you need to encourage creative thinking and find innovative solutions that work.

CPS asks you to separate your "divergent" and "convergent" thinking as a way to do this. Divergent thinking is the process of generating lots of potential solutions and possibilities, otherwise known as brainstorming. And convergent thinking involves evaluating those options and choosing the most promising one. Often, we use a combination of the two to develop new ideas or solutions. However, using them simultaneously can result in unbalanced or biased decisions, and can stifle idea generation.

For more on divergent and convergent thinking, and for a useful diagram, see the book "Facilitator's Guide to Participatory Decision-Making." [3]

Core Principles of Creative Problem Solving

CPS has four core principles. Let's explore each one in more detail:

• Divergent and convergent thinking must be balanced. The key to creativity is learning how to identify and balance divergent and convergent thinking (done separately), and knowing when to practice each one.
• Ask problems as questions. When you rephrase problems and challenges as open-ended questions with multiple possibilities, it's easier to come up with solutions. Asking these types of questions generates lots of rich information, while asking closed questions tends to elicit short answers, such as confirmations or disagreements. Problem statements tend to generate limited responses, or none at all.
• Defer or suspend judgment. As Alex Osborn learned from his work on brainstorming, judging solutions early on tends to shut down idea generation. Instead, there's an appropriate and necessary time to judge ideas during the convergence stage.
• Focus on "Yes, and," rather than "No, but." Language matters when you're generating information and ideas. "Yes, and" encourages people to expand their thoughts, which is necessary during certain stages of CPS. Using the word "but" – preceded by "yes" or "no" – ends conversation, and often negates what's come before it.

How to Use the Tool

Let's explore how you can use each of the four steps of the CPS Learner's Model (shown in figure 1, below) to generate innovative ideas and solutions.

Figure 1 – CPS Learner's Model

Explore the Vision

Identify your goal, desire or challenge. This is a crucial first step because it's easy to assume, incorrectly, that you know what the problem is. However, you may have missed something or have failed to understand the issue fully, and defining your objective can provide clarity. Read our article, 5 Whys , for more on getting to the root of a problem quickly.

Gather Data

Once you've identified and understood the problem, you can collect information about it and develop a clear understanding of it. Make a note of details such as who and what is involved, all the relevant facts, and everyone's feelings and opinions.

Formulate Questions

When you've increased your awareness of the challenge or problem you've identified, ask questions that will generate solutions. Think about the obstacles you might face and the opportunities they could present.

Explore Ideas

Generate ideas that answer the challenge questions you identified in step 1. It can be tempting to consider solutions that you've tried before, as our minds tend to return to habitual thinking patterns that stop us from producing new ideas. However, this is a chance to use your creativity .

Brainstorming and Mind Maps are great ways to explore ideas during this divergent stage of CPS. And our articles, Encouraging Team Creativity , Problem Solving , Rolestorming , Hurson's Productive Thinking Model , and The Four-Step Innovation Process , can also help boost your creativity.

See our Brainstorming resources within our Creativity section for more on this.

Formulate Solutions

This is the convergent stage of CPS, where you begin to focus on evaluating all of your possible options and come up with solutions. Analyze whether potential solutions meet your needs and criteria, and decide whether you can implement them successfully. Next, consider how you can strengthen them and determine which ones are the best "fit." Our articles, Critical Thinking and ORAPAPA , are useful here.

4. Implement

Formulate a plan.

Once you've chosen the best solution, it's time to develop a plan of action. Start by identifying resources and actions that will allow you to implement your chosen solution. Next, communicate your plan and make sure that everyone involved understands and accepts it.

There have been many adaptations of CPS since its inception, because nobody owns the idea.

For example, Scott Isaksen and Donald Treffinger formed The Creative Problem Solving Group Inc . and the Center for Creative Learning , and their model has evolved over many versions. Blair Miller, Jonathan Vehar and Roger L. Firestien also created their own version, and Dr Gerard J. Puccio, Mary C. Murdock, and Marie Mance developed CPS: The Thinking Skills Model. [4] Tim Hurson created The Productive Thinking Model , and Paul Reali developed CPS: Competencies Model. [5]

Sid Parnes continued to adapt the CPS model by adding concepts such as imagery and visualization , and he founded the Creative Studies Project to teach CPS. For more information on the evolution and development of the CPS process, see Creative Problem Solving Version 6.1 by Donald J. Treffinger, Scott G. Isaksen, and K. Brian Dorval. [6]

Creative Problem Solving (CPS) Infographic

See our infographic on Creative Problem Solving .

Creative problem solving (CPS) is a way of using your creativity to develop new ideas and solutions to problems. The process is based on separating divergent and convergent thinking styles, so that you can focus your mind on creating at the first stage, and then evaluating at the second stage.

There have been many adaptations of the original Osborn-Parnes model, but they all involve a clear structure of identifying the problem, generating new ideas, evaluating the options, and then formulating a plan for successful implementation.

[1] Entrepreneur (2012). James Dyson on Using Failure to Drive Success [online]. Available here . [Accessed May 27, 2022.]

[2] Creative Education Foundation (2015). The CPS Process [online]. Available here . [Accessed May 26, 2022.]

[3] Kaner, S. et al. (2014). 'Facilitator′s Guide to Participatory Decision–Making,' San Francisco: Jossey-Bass.

[4] Puccio, G., Mance, M., and Murdock, M. (2011). 'Creative Leadership: Skils That Drive Change' (2nd Ed.), Thousand Oaks, CA: Sage.

[5] OmniSkills (2013). Creative Problem Solving [online]. Available here . [Accessed May 26, 2022].

[6] Treffinger, G., Isaksen, S., and Dorval, B. (2010). Creative Problem Solving (CPS Version 6.1). Center for Creative Learning, Inc. & Creative Problem Solving Group, Inc. Available here .

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