nature of problem solving definition

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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• Section 3. Defining and Analyzing the Problem

Chapter 17 Sections

• Section 1. An Introduction to the Problem-Solving Process
• Section 2. Thinking Critically
• Section 4. Analyzing Root Causes of Problems: The "But Why?" Technique
• Section 5. Addressing Social Determinants of Health and Development
• Section 6. Generating and Choosing Solutions
• Section 7. Putting Your Solution into Practice
• Main Section

The nature of problems

Clarifying the problem, deciding to solve the problem, analyzing the problem.

We've all had our share of problems - more than enough, if you come right down to it. So it's easy to think that this section, on defining and analyzing the problem, is unnecessary. "I know what the problem is," you think. "I just don't know what to do about it."

Not so fast! A poorly defined problem - or a problem whose nuances you don't completely understand - is much more difficult to solve than a problem you have clearly defined and analyzed. The way a problem is worded and understood has a huge impact on the number, quality, and type of proposed solutions.

In this section, we'll begin with the basics, focusing primarily on four things. First, we'll consider the nature of problems in general, and then, more specifically, on clarifying and defining the problem you are working on. Then, we'll talk about whether or not you really want to solve the problem, or whether you are better off leaving it alone. Finally, we'll talk about how to do an in-depth analysis of the problem.

So, what is a problem? It can be a lot of things. We know in our gut when there is a problem, whether or not we can easily put it into words. Maybe you feel uncomfortable in a given place, but you're not sure why. A problem might be just the feeling that something is wrong and should be corrected. You might feel some sense of distress, or of injustice.

Stated most simply, a problem is the difference between what is , and what might or should be . "No child should go to bed hungry, but one-quarter of all children do in this country," is a clear, potent problem statement. Another example might be, "Communication in our office is not very clear." In this instance, the explanation of "what might or should be" is simply alluded to.

As these problems illustrate, some problems are more serious than others; the problem of child hunger is a much more severe problem than the fact that the new youth center has no exercise equipment, although both are problems that can and should be addressed. Generally, problems that affect groups of people - children, teenage mothers, the mentally ill, the poor - can at least be addressed and in many cases lessened using the process outlined in this Chapter.

Although your organization may have chosen to tackle a seemingly insurmountable problem, the process you will use to solve it is not complex. It does, however, take time, both to formulate and to fully analyze the problem. Most people underestimate the work they need to do here and the time they'll need to spend. But this is the legwork, the foundation on which you'll lay effective solutions. This isn't the time to take shortcuts.

Three basic concepts make up the core of this chapter: clarifying, deciding, and analyzing. Let's look at each in turn.

If you are having a problem-solving meeting, then you already understand that something isn't quite right - or maybe it's bigger than that; you understand that something is very, very wrong. This is your beginning, and of course, it makes most sense to...

• Start with what you know . When group members walk through the door at the beginning of the meeting, what do they think about the situation? There are a variety of different ways to garner this information. People can be asked in advance to write down what they know about the problem. Or the facilitator can lead a brainstorming session to try to bring out the greatest number of ideas. Remember that a good facilitator will draw out everyone's opinions, not only those of the more vocal participants.
• Decide what information is missing . Information is the key to effective decision making. If you are fighting child hunger, do you know which children are hungry? When are they hungry - all the time, or especially at the end of the month, when the money has run out? If that's the case, your problem statement might be, "Children in our community are often hungry at the end of the month because their parents' paychecks are used up too early."

Compare this problem statement on child hunger to the one given in "The nature of problems" above. How might solutions for the two problems be different?

• Facts (15% of the children in our community don't get enough to eat.)
• Inference (A significant percentage of children in our community are probably malnourished/significantly underweight.)
• Speculation (Many of the hungry children probably live in the poorer neighborhoods in town.)
• Opinion (I think the reason children go hungry is because their parents spend all of their money on cigarettes.)

When you are gathering information, you will probably hear all four types of information, and all can be important. Speculation and opinion can be especially important in gauging public opinion. If public opinion on your issue is based on faulty assumptions, part of your solution strategy will probably include some sort of informational campaign.

For example, perhaps your coalition is campaigning against the death penalty, and you find that most people incorrectly believe that the death penalty deters violent crime. As part of your campaign, therefore, you will probably want to make it clear to the public that it simply isn't true.

Where and how do you find this information? It depends on what you want to know. You can review surveys, interviews, the library and the internet.

• Define the problem in terms of needs, and not solutions. If you define the problem in terms of possible solutions, you're closing the door to other, possibly more effective solutions. "Violent crime in our neighborhood is unacceptably high," offers space for many more possible solutions than, "We need more police patrols," or, "More citizens should have guns to protect themselves."
• Define the problem as one everyone shares; avoid assigning blame for the problem. This is particularly important if different people (or groups) with a history of bad relations need to be working together to solve the problem. Teachers may be frustrated with high truancy rates, but blaming students uniquely for problems at school is sure to alienate students from helping to solve the problem.

You can define the problem in several ways; The facilitator can write a problem statement on the board, and everyone can give feedback on it, until the statement has developed into something everyone is pleased with, or you can accept someone else's definition of the problem, or use it as a starting point, modifying it to fit your needs.

After you have defined the problem, ask if everyone understands the terminology being used. Define the key terms of your problem statement, even if you think everyone understands them.

The Hispanic Health Coalition, has come up with the problem statement "Teen pregnancy is a problem in our community." That seems pretty clear, doesn't it? But let's examine the word "community" for a moment. You may have one person who defines community as "the city you live in," a second who defines it as, "this neighborhood" and a third who considers "our community" to mean Hispanics.

At this point, you have already spent a fair amount of time on the problem at hand, and naturally, you want to see it taken care of. Before you go any further, however, it's important to look critically at the problem and decide if you really want to focus your efforts on it. You might decide that right now isn't the best time to try to fix it. Maybe your coalition has been weakened by bad press, and chance of success right now is slim. Or perhaps solving the problem right now would force you to neglect another important agency goal. Or perhaps this problem would be more appropriately handled by another existing agency or organization.

You and your group need to make a conscious choice that you really do want to attack the problem. Many different factors should be a part of your decision. These include:

Importance . In judging the importance of the issue, keep in mind the f easibility . Even if you have decided that the problem really is important, and worth solving, will you be able to solve it, or at least significantly improve the situation? The bottom line: Decide if the good you can do will be worth the effort it takes. Are you the best people to solve the problem? Is someone else better suited to the task?

For example, perhaps your organization is interested in youth issues, and you have recently come to understand that teens aren't participating in community events mostly because they don't know about them. A monthly newsletter, given out at the high schools, could take care of this fairly easily. Unfortunately, you don't have much publishing equipment. You do have an old computer and a desktop printer, and you could type something up, but it's really not your forte. A better solution might be to work to find writing, design and/or printing professionals who would donate their time and/or equipment to create a newsletter that is more exciting, and that students would be more likely to want to read.

Negative impacts . If you do succeed in bringing about the solution you are working on, what are the possible consequences? If you succeed in having safety measures implemented at a local factory, how much will it cost? Where will the factory get that money? Will they cut salaries, or lay off some of their workers?

Even if there are some unwanted results, you may well decide that the benefits outweigh the negatives. As when you're taking medication, you'll put up with the side effects to cure the disease. But be sure you go into the process with your eyes open to the real costs of solving the problem at hand.

Choosing among problems

You might have many obstacles you'd like to see removed. In fact, it's probably a pretty rare community group that doesn't have a laundry list of problems they would like to resolve, given enough time and resources. So how do you decide which to start with?

A simple suggestion might be to list all of the problems you are facing, and whether or not they meet the criteria listed above (importance, feasibility, et cetera). It's hard to assign numerical values for something like this, because for each situation, one of the criteria may strongly outweigh the others. However, just having all of the information in front of the group can help the actual decision making a much easier task.

Now that the group has defined the problem and agreed that they want to work towards a solution, it's time to thoroughly analyze the problem. You started to do this when you gathered information to define the problem, but now, it's time to pay more attention to details and make sure everyone fully understands the problem.

Answer all of the question words.

The facilitator can take group members through a process of understanding every aspect of the problem by answering the "question words" - what, why, who, when, and how much. This process might include the following types of questions:

What is the problem? You already have your problem statement, so this part is more or less done. But it's important to review your work at this point.

Why does the problem exist? There should be agreement among meeting participants as to why the problem exists to begin with. If there isn't, consider trying one of the following techniques.

• The "but why" technique. This simple exercise can be done easily with a large group, or even on your own. Write the problem statement, and ask participants, "Why does this problem exist?" Write down the answer given, and ask, "But why does (the answer) occur?"

"Children often fall asleep in class," But why? "Because they have no energy." But why? "Because they don't eat breakfast." But why?

Continue down the line until participants can comfortably agree on the root cause of the problem . Agreement is essential here; if people don't even agree about the source of the problem, an effective solution may well be out of reach.

• Start with the definition you penned above.
• Draw a line down the center of the paper. Or, if you are working with a large group of people who cannot easily see what you are writing, use two pieces.
• On the top of one sheet/side, write "Restraining Forces."
• On the other sheet/side, write, "Driving Forces."
• Under "Restraining Forces," list all of the reasons you can think of that keep the situation the same; why the status quo is the way it is. As with all brainstorming sessions, this should be a "free for all;" no idea is too "far out" to be suggested and written down.
• In the same manner, under "Driving Forces," list all of the forces that are pushing the situation to change.
• When all of the ideas have been written down, group members can edit them as they see fit and compile a list of the important factors that are causing the situation.

Clearly, these two exercises are meant for different times. The "but why" technique is most effective when the facilitator (or the group as a whole) decides that the problem hasn't been looked at deeply enough and that the group's understanding is somewhat superficial. The force field analysis, on the other hand, can be used when people are worried that important elements of the problem haven't been noticed -- that you're not looking at the whole picture.

Who is causing the problem, and who is affected by it? A simple brainstorming session is an excellent way to determine this.

When did the problem first occur, or when did it become significant? Is this a new problem or an old one? Knowing this can give you added understanding of why the problem is occurring now. Also, the longer a problem has existed, the more entrenched it has become, and the more difficult it will be to solve. People often get used to things the way they are and resist change, even when it's a change for the better.

How much , or to what extent, is this problem occurring? How many people are affected by the problem? How significant is it? Here, you should revisit the questions on importance you looked at when you were defining the problem. This serves as a brief refresher and gives you a complete analysis from which you can work.

If time permits, you might want to summarize your analysis on a single sheet of paper for participants before moving on to generating solutions, the next step in the process. That way, members will have something to refer back to during later stages in the work.

Also, after you have finished this analysis, the facilitator should ask for agreement from the group. Have people's perceptions of the problem changed significantly? At this point, check back and make sure that everyone still wants to work together to solve the problem.

The first step in any effective problem-solving process may be the most important. Take your time to develop a critical definition, and let this definition, and the analysis that follows, guide you through the process. You're now ready to go on to generating and choosing solutions, which are the next steps in the problem-solving process, and the focus of the following section.

Print Resources

Avery, M., Auvine, B., Streibel, B., & Weiss, L. (1981). A handbook for consensus decision making: Building united judgement . Cambridge, MA: Center for Conflict Resolution.

Dale, D., & Mitiguy, N. Planning, for a change: A citizen's guide to creative planning and program development .

Dashiell, K. (1990). Managing meetings for collaboration and consensus . Honolulu, HI: Neighborhood Justice Center of Honolulu, Inc.

Interaction Associates (1987). Facilitator institute . San Francisco, CA: Author.

Lawson, L., Donant, F., & Lawson, J. (1982). Lead on! The complete handbook for group leaders . San Luis Obispo, CA: Impact Publishers.

Meacham, W. (1980). Human development training manual . Austin, TX: Human Development Training.

Morrison, E. (1994). Leadership skills: Developing volunteers for organizational success . Tucson, AZ: Fisher Books.  

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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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Article • 7 min read

What Is Problem Solving?

By the Mind Tools Content Team

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

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

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

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

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

How Well Do You Solve Problems?

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

Define Every Problem

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

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

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

Understanding Complexity

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

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

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

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

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

General Problem-Solving Tools

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

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

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

Specific Problem-Solving Systems

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

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

Further Problem-Solving Strategies

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

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

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

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

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

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

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

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

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

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

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Creative Problem Solving

Finding Innovative Solutions to Challenges

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Problem Solving Skills for the Digital Age

Lucid Content

Reading time: about 6 min

Let’s face it: Things don’t always go according to plan. Systems fail, wires get crossed, projects fall apart.

Problems are an inevitable part of life and work. They’re also an opportunity to think critically and find solutions. But knowing how to get to the root of unexpected situations or challenges can mean the difference between moving forward and spinning your wheels.

Here, we’ll break down the key elements of problem solving, some effective problem solving approaches, and a few effective tools to help you arrive at solutions more quickly.

So, what is problem solving?

Broadly defined, problem solving is the process of finding solutions to difficult or complex issues. But you already knew that. Understanding problem solving frameworks, however, requires a deeper dive.

Think about a recent problem you faced. Maybe it was an interpersonal issue. Or it could have been a major creative challenge you needed to solve for a client at work. How did you feel as you approached the issue? Stressed? Confused? Optimistic? Most importantly, which problem solving techniques did you use to tackle the situation head-on? How did you organize thoughts to arrive at the best possible solution?

Solve your problem-solving problem  

Here’s the good news: Good problem solving skills can be learned. By its nature, problem solving doesn’t adhere to a clear set of do’s and don’ts—it requires flexibility, communication, and adaptation. However, most problems you face, at work or in life, can be tackled using four basic steps.

First, you must define the problem . This step sounds obvious, but often, you can notice that something is amiss in a project or process without really knowing where the core problem lies. The most challenging part of the problem solving process is uncovering where the problem originated.

Second, you work to generate alternatives to address the problem directly. This should be a collaborative process to ensure you’re considering every angle of the issue.

Third, you evaluate and test potential solutions to your problem. This step helps you fully understand the complexity of the issue and arrive at the best possible solution.

Finally, fourth, you select and implement the solution that best addresses the problem.

Following this basic four-step process will help you approach every problem you encounter with the same rigorous critical and strategic thinking process, recognize commonalities in new problems, and avoid repeating past mistakes.

In addition to these basic problem solving skills, there are several best practices that you should incorporate. These problem solving approaches can help you think more critically and creatively about any problem:

You may not feel like you have the right expertise to resolve a specific problem. Don’t let that stop you from tackling it. The best problem solvers become students of the problem at hand. Even if you don’t have particular expertise on a topic, your unique experience and perspective can lend itself to creative solutions.

Challenge the status quo

Standard problem solving methodologies and problem solving frameworks are a good starting point. But don’t be afraid to challenge assumptions and push boundaries. Good problem solvers find ways to apply existing best practices into innovative problem solving approaches.

Think broadly about and visualize the issue

Sometimes it’s hard to see a problem, even if it’s right in front of you. Clear answers could be buried in rows of spreadsheet data or lost in miscommunication. Use visualization as a problem solving tool to break down problems to their core elements. Visuals can help you see bottlenecks in the context of the whole process and more clearly organize your thoughts as you define the problem.  

Hypothesize, test, and try again

It might be cliche, but there’s truth in the old adage that 99% of inspiration is perspiration. The best problem solvers ask why, test, fail, and ask why again. Whether it takes one or 1,000 iterations to solve a problem, the important part—and the part that everyone remembers—is the solution.

Consider other viewpoints

Today’s problems are more complex, more difficult to solve, and they often involve multiple disciplines. They require group expertise and knowledge. Being open to others’ expertise increases your ability to be a great problem solver. Great solutions come from integrating your ideas with those of others to find a better solution. Excellent problem solvers build networks and know how to collaborate with other people and teams. They are skilled in bringing people together and sharing knowledge and information.

4 effective problem solving tools

As you work through the problem solving steps, try these tools to better define the issue and find the appropriate solution.

Root cause analysis

Similar to pulling weeds from your garden, if you don’t get to the root of the problem, it’s bound to come back. A root cause analysis helps you figure out the root cause behind any disruption or problem, so you can take steps to correct the problem from recurring. The root cause analysis process involves defining the problem, collecting data, and identifying causal factors to pinpoint root causes and arrive at a solution.

Less structured than other more traditional problem solving methods, the 5 Whys is simply what it sounds like: asking why over and over to get to the root of an obstacle or setback. This technique encourages an open dialogue that can trigger new ideas about a problem, whether done individually or with a group. Each why piggybacks off the answer to the previous why. Get started with the template below—both flowcharts and fishbone diagrams can also help you track your answers to the 5 Whys.

Brainstorming

A meeting of the minds, a brain dump, a mind meld, a jam session. Whatever you call it, collaborative brainstorming can help surface previously unseen issues, root causes, and alternative solutions. Create and share a mind map with your team members to fuel your brainstorming session.

Gap analysis

Sometimes you don’t know where the problem is until you determine where it isn’t. Gap filling helps you analyze inadequacies that are preventing you from reaching an optimized state or end goal. For example, a content gap analysis can help a content marketer determine where holes exist in messaging or the customer experience. Gap analysis is especially helpful when it comes to problem solving because it requires you to find workable solutions. A SWOT analysis chart that looks at a problem through the lens of strengths, opportunities, opportunities, and threats can be a helpful problem solving framework as you start your analysis.

A better way to problem solve

Beyond these practical tips and tools, there are myriad methodical and creative approaches to move a project forward or resolve a conflict. The right approach will depend on the scope of the issue and your desired outcome.

Depending on the problem, Lucidchart offers several templates and diagrams that could help you identify the cause of the issue and map out a plan to resolve it.  Learn more about how Lucidchart can help you take control of your problem solving process .

Lucidchart, a cloud-based intelligent diagramming application, is a core component of Lucid Software's Visual Collaboration Suite. This intuitive, cloud-based solution empowers teams to collaborate in real-time to build flowcharts, mockups, UML diagrams, customer journey maps, and more. Lucidchart propels teams forward to build the future faster. Lucid is proud to serve top businesses around the world, including customers such as Google, GE, and NBC Universal, and 99% of the Fortune 500. Lucid partners with industry leaders, including Google, Atlassian, and Microsoft. Since its founding, Lucid has received numerous awards for its products, business, and workplace culture. For more information, visit lucidchart.com.

Related articles

Sometimes you're faced with challenges that traditional problem solving can't fix. Creative problem solving encourages you to find new, creative ways of thinking that can help you overcome the issue at hand more quickly.

Root cause analysis refers to any problem-solving method used to trace an issue back to its origin. Learn how to complete a root cause analysis—we've even included templates to get you started.

Bring your bright ideas to life.

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

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Are You Solving the Right Problem?

• Dwayne Spradlin

Most firms aren’t, and that undermines their innovation efforts.

Reprint: R1209F

The rigor with which a problem is defined is the most important factor in finding a good solution. Many organizations, however, are not proficient at articulating their problems and identifying which ones are crucial to their strategies.

They may even be trying to solve the wrong problems—missing opportunities and wasting resources in the process. The key is to ask the right questions.

The author describes a process that his firm, InnoCentive, has used to help clients define and articulate business, technical, social, and policy challenges and then present them to an online community of more than 250,000 solvers. The four-step process consists of asking a series of questions and using the answers to create a problem statement that will elicit novel ideas from an array of experts.

• Establish the need for a solution. What is the basic need? Who will benefit from a solution?
• Justify the need. Why should your organization attempt to solve this problem? Is it aligned with your strategy? If a solution is found, who will implement it?
• Contextualize the problem. What have you and others already tried? Are there internal and external constraints to implementing a solution?
• Write the problem statement. What requirements must a solution meet? What language should you use to describe the problem? How will you evaluate solutions and measure success?

EnterpriseWorks/VITA, a nonprofit organization, used this process to find a low-cost, lightweight, and convenient product that expands access to clean drinking water in the developing world.

“If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it,” Albert Einstein said.

• DS Dwayne Spradlin is the president and CEO of InnoCentive , an online marketplace that connects organizations with freelance problem solvers in a multitude of fields. He is a coauthor, with Alpheus Bingham, of The Open Innovation Marketplace: Creating Value in the Challenge Driven Enterprise (FT Press, 2011).

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From problem solving to problem definition: scrutinizing the complex nature of clinical practice

Sayra cristancho.

1 Centre for Education Research & Innovation, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada

Lorelei Lingard

Glenn regehr.

2 Centre for Health Education Scholarship, Faculty of Medicine, University of British Columbia, Vancouver, Canada

In medical education, we have tended to present problems as being singular, stable, and solvable. Problem solving has, therefore, drawn much of medical education researchers’ attention. This focus has been important but it is limited in terms of preparing clinicians to deal with the complexity of the 21st century healthcare system in which they will provide team-based care for patients with complex medical illness. In this paper, we use the Soft Systems Engineering principles to introduce the idea that in complex, team-based situations, problems usually involve divergent views and evolve with multiple solution iterations. As such we need to shift the conversation from (1) problem solving to problem definition, and (2) from a problem definition derived exclusively at the level of the individual to a definition derived at the level of the situation in which the problem is manifested. Embracing such a focus on problem definition will enable us to advocate for novel educational practices that will equip trainees to effectively manage the problems they will encounter in complex, team-based healthcare.

Problem solving has been one of the central areas of exploration for researchers studying medical expertise. This work has revealed some important insights into how medical experts grapple with addressing relatively stable, well-defined problems. However, in focusing on problems that are singular, stable, and solvable, these insights might have limited value in preparing clinicians to deal with the complexity of the 21st century healthcare system in which they will provide team-based care for patients with complex medical illness [ 1 ]. In the medical education literature, this concern is gaining recent attention as researchers begin to challenge taken-for-granted assumptions about clinical reasoning activities, such as diagnosis [ 2 ]. When activities such as diagnosis or treatment planning are framed as ongoing processes of meaning making, problem solving can no longer be thought of merely as converging on the correct solution. Consider the following example, derived from a research interview with a senior general surgeon:

Dr. Smith was scheduled to operate on a gentleman with a pelvic exoneration that required removing all the organs within the pelvis. Chemotherapy prior to surgery would likely increase the success of surgery. The patient was assessed by the oncologist who decided not to provide chemotherapy before the operation because the oncologist thought the patient was ‘not reliable’ . To determine what to do, Dr. Smith engaged in a series of conversations with the nurse, the social worker, the oncologist and a more senior colleague. Dr. Smith felt very strongly that ‘treating someone with less than the standard of care’ was inappropriate. Yet, the oncologist continued to resist. As the day of the surgery approached, Dr. Smith gathered support from the rest of the team members involved and essentially ‘ tricked the oncologist’ by admitting the patient to the hospital in advance. With this decision, Dr. Smith presented a new situation to the oncologist saying ‘ok, well, now he’s in hospital, he’s very reliable; he’s not going anywhere … now you can treat him’ . The oncologist reframed his concern, remarking back to the surgeon that ‘sometimes what is good for this patient may not necessarily be good for society’ . Notwithstanding this stance, the oncologist acknowledged that since the patient was already in the hospital, he had to fulfil his professional responsibility of providing chemotherapy. As this treatment was taking place, Dr. Smith felt ‘somewhat morally conflicted because I get what the oncologist is worried about …’. He now reported viewing the situation as ‘teetering’ between doing the right thing for one patient and imposing a significant cost on the system. In describing the shifting context that defined his efforts to help this patient, he characterized the situation as being one of making judgments like a rock climber: ‘very, very slow, inching your way … that feels like a solid hand-hold, ok, I’ll take that … or that doesn’t seem like it’s gonna go, so maybe I’ll try a different strategy, and often what you do at a certain moment in time, opens up what you can see at another moment … I think it’s like being in a constant evolution of finding your place.’

What does this story reveal about the nature of problem solving in every day clinical practice? First, there was not a single problem in play here, but rather a constellation of problems defined differently from different perspectives. For example, from the surgeon’s perspective the question of whether the patient should receive chemotherapy was an issue of pursuing optimal care for a successful outcome, whereas from the oncologist‘s perspective, it was an issue of whether the treatment could be successfully enacted given the patient’s unreliability. Second, in the eyes of the surgeon (and the oncologist), the problem was not stable, but rather constantly evolving over time. Dr. Smith started with a procedural problem (operating on a patient that required removing all organs within the pelvis and identifying chemotherapy as needed to maximize success), which shifted into a care access problem (convincing the oncologist that treating the patient with chemotherapy prior to surgery was the most appropriate action), then became a team dynamics problem (convincing others of the need to admit the patient and tricking the oncologist). Finally, it evolved into a moral problem (the dilemma of doing the right thing for the patient vs. the cost imposed on the system), one imposed by the oncologist’s efforts to respond to his own shifting definition of the problem. Thus, what on the surface appears to be a single central problem of care for the patient is in fact a constantly evolving constellation of problems: it looks different depending on whose point of view we take, and on which point in time we emphasize during the process. The complexity in this team interaction is, therefore, not only, or even primarily, one of problem solving – it is also one of problem defining.

This story of everyday, incremental problem solving and iterative problem definition is the sort that occurs regularly in healthcare, and it illustrates the fluidity of problems. In Dr. Smith’s story the issue of reframing problems was made explicit as he told the story during his interview, but in everyday practice most likely it happens largely tacitly as clinicians balance their various priorities [ 3 ]. Whether explicit or tacit, however, team members learn from such experiences. The next time this senior surgeon and oncologist interact regarding pre-surgical chemotherapy, each will make inferences about the other’s definition of the clinical problem based on this experience and adapt their behaviour accordingly. The surgeon might, for example, admit the patient before consulting with the oncologist, both in an attempt to manage the problem definition and its solution. Thus, through experience, clinicians become savvy definers of problems just as they become savvy solvers of problems. Yet such sophisticated considerations are seldom articulated, and when the pre-emptive solution is enacted the problem does not manifest. Thus, the complexity and multifaceted nature of the underlying problem definition is hidden (perhaps, over repeated enactments, even from the physician himself).

Such examples challenge the conventional premise that problems are singular and stable, and that they can be ‘solved’ once and for all. A singular, stable definition and permanent solution of problems may hold in simple healthcare situations (e. g., a child with a minor ear infection brought to the family physician), but in complex, team-based situations like the one above, these premises are regularly challenged. Because different stakeholders may well approach the same issue differently, the major challenge lies not just in agreeing how to solve the problem, but in appreciating exactly what the problem is at any given moment in time.

If we acknowledge that clinical problem definition is not simple and straightforward, but multifaceted, evolving and iterative, then we require a new language for talking about problem solving . A number of other disciplines have grappled with this issue [ 4 ], and one that has developed a useful language is SSE [ 5 – 8 ]. Elsewhere we have discussed the implications of SSE in relation to other domains such as resilience [ 9 ] and learning [ 10 ]. For the purposes of this paper, we are exploring the value of SSE for reconsidering the construction of problem solving in the medical education literature. One of many concepts that Soft Systems Engineering posits [ 11 – 13 ] is the idea that because real-life problems usually involve divergent views and evolve with multiple solution iterations, the focus needs to shift in two ways. First, it needs to shift from problem solving to problem definition . Second, it needs to shift from a problem definition derived exclusively at the level of the individual to a definition derived at the level of the situation or system in which the problem is manifested [ 11 ].

SSE offers a vocabulary for making these shifts possible. First, SSE identifies the perspectives that are involved in a problem situation: who are the stakeholders in the problem and from what orientation does each define it? In the story above, different team members held different and conflicting perspectives on how to treat this particular patient prior to surgery. While the oncologist struggled with the idea of providing chemotherapy prior to the operation, the surgeon struggled with the consequences of admitting the patient earlier to the hospital. Second, SSE moves beyond a consideration of each isolated perspective to examine the interactions among them [ 11 – 13 ]. Although we might potentially interpret these differing perspectives as just a set of individual problems, in fact, these interacting perspectives collectively shape and reshape the situation in which each individual is enacting his or her part [ 14 , 15 ].

In the surgery story, the interactions among the surgeon’s and the oncologist’s perspectives resulted in a series of redefinitions of the problem for the surgeon: from attending to the procedural steps, to attending to the team dynamics, to attending to the moral dilemma. Thus, under the SSE approach, the construction of the situation becomes a cyclical process: the dynamic nature of the various perspectives a single team member holds and the interactions with other team members’ perspectives reshapes the situation, which in turn influences every team member’s understanding. As a research approach, SSE therefore enables us to ask questions such as:

• What are all the relevant perspectives for the definition of a problem? In the story above these included both the surgeon and the oncologist, but might also have included those of the nurses, social workers, hospital administrators, and patient. As the surgeon told it, these perspectives seemed to align with his, but it would be important to ask as an open question.
• How do those perspectives interact with one another to iteratively define the problem? The surgery story showed at least three redefinitions of the problem caused by the interactions among perspectives.
• How do new behaviours emerge as a consequence of those interactions and in response to the constantly changing nature of the problem? The surgeon-oncologist interaction depicted in the story might result in the surgeon implementing workarounds next time he faces a similar situation with the same oncologist.

Daily clinical problems are dynamic challenges defined multiply by individuals distributed across the system. Adopting an SSE lens can help us conceptualize a ‘problem’ not as singular and static, but as an entity that evolves, adapts and emerges across interactions and across time. Consistent with other recent innovations in medical education [ 4 ], we suggest that embracing a focus on the complexities of problem definition can enable novel educational practices that will equip trainees to effectively manage the problems they are likely to encounter in complex, team-based healthcare.

Biographies

is assistant professor at the Department of Surgery and Scientist, Centre for Education Research & Innovation, Western University, Canada. Her research programme investigates the organizational, social and personal factors that determine the evolution of complex clinical situations. Towards this end, she follows Qualitative and Systems Engineering approaches to research.

is the director of CERI. Her research programme investigates the nature of communication on inter-professional healthcare teams, including the operating room, the intensive care unit, and the internal medicine ward. She is particularly interested in how communication patterns influence patient safety and shapes the professional identity of novices.

is professor at the Department of Surgery and associate director of the Centre for Health Education Scholarship, University of British Columbia, Canada. His collaborative research programme utilizes a variety of quantitative and qualitative methodologies to explore the development, maintenance, enactment and assessment of both clinical expertise and professional identity.

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Encyclopedia of the Sciences of Learning pp 2683–2686 Cite as

Problem Typology

• David H. Jonassen 2  
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Learning outcomes ; Learning taxonomy ; Problem solving

Traditional models of problem solving, known as phase models (e.g., Bransford and Stein 1984 ), suggest that all problems can be solved if we (1) identify the problem, (2) generate alternative solutions, (3) evaluate those solutions, (4) implement the chosen solution, and (5) evaluate the effectiveness of the solution. However, problems and problem solving vary in several ways, including the skills and abilities of the problem solver, the nature of the problem itself, the context in which the problem occurs, and the way the problem is represented to the problem solver (Jonassen 2007 ). In this chapter, I describe how problems themselves vary.

Foremost among these differences is the continuum (see Fig.  1 ) between well-structured and ill-structured problems (Jonassen 1997 , 2000 ; Voss and Post 1988 ). Most problems encountered in formal education are well-structured problems. Well-structured problems typically present...

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Bransford, J., & Stein, B. S. (1984). The IDEAL problem solver: A guide for improving thinking, learning, and creativity . New York: WH Freeman.

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Mastering Problem-Solving Skills: Definition and Examples

Problem-solving skills – introduction.

Problem-solving skills are fundamental abilities that enable individuals to tackle complex challenges, overcome obstacles, and devise effective solutions. These skills are invaluable across various domains, from personal life to professional endeavors. As they empower individuals to analyze situations critically and implement strategies to achieve desired outcomes.

Definition of Problem-Solving Skills

Problem-solving skills encompass a range of cognitive processes and techniques aimed at identifying, analyzing, and resolving problems. These skills involve the application of logical reasoning, creativity, critical thinking, and decision-making to address issues and make sound judgments.

Understanding the Problem

Before attempting to solve a problem, it is essential to fully comprehend its nature and scope. This involves identifying the underlying issues, determining the goals to be achieved, and clarifying any constraints or limitations that may affect the solution.

Example: In a business context, understanding a decline in sales requires analyzing market trends. Customer feedback, and internal factors such as product quality and pricing strategies.

Analyzing Options

Once the problem is defined, individuals need to explore various solutions or approaches to address it. This stage involves brainstorming ideas, evaluating alternatives, and considering the potential outcomes of each option.

Example: When faced with a budget shortfall, a project manager may analyze different cost-cutting measures. Such as renegotiating contracts, reducing non-essential expenses, or reallocating resources.

Implementing Solutions

After selecting the most viable solution, the next step is implementing it effectively. This often requires planning, organization, and coordination to execute the chosen approach and monitor its progress toward achieving the desired results.

Example: To improve customer satisfaction, a restaurant manager may introduce a new training program for staff, streamline service processes, and solicit feedback from patrons to assess the impact of the changes.

Evaluating Results

Once the solution has been implemented, it is crucial to evaluate its effectiveness and identify any unforeseen consequences or areas for improvement. This feedback loop allows individuals to refine their problem-solving strategies and learn from their experiences.

Example: A teacher who introduces a new teaching method in the classroom may assess student performance, gather feedback from students and colleagues, and adjust the approach based on the observed outcomes.

Continuous Improvement

Problem-solving skills are not static but evolve through practice and experience. Individuals can enhance their abilities by seeking feedback, learning from failures, and continuously challenging themselves to solve increasingly complex problems.

Example: A software developer may regularly participate in coding challenges, attend workshops on emerging technologies, and collaborate with peers to stay updated and sharpen their programming skills.

In conclusion, problem-solving skills are essential competencies that enable individuals to navigate challenges, innovate solutions, and achieve their goals effectively. By understanding the problem, analyzing options, implementing solutions, evaluating results, and continuously improving. Individuals can develop mastery in problem-solving across diverse contexts. These skills benefit individuals in their personal and professional lives and contribute to the advancement of society as a whole.

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A "Teach Educator" is a specialized role focusing on training and empowering other teachers. This professional is dedicated to enhancing educators' skills through the latest teaching techniques, innovative technologies, and educational research. They conduct workshops, seminars, and coaching, promoting professional development within academic settings.

By improving teaching standards and fostering a culture of continuous learning among educators, Teach Educators ensure that classroom challenges are met with advanced strategies, leading to more effective teaching and richer student learning experiences.

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