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10 Problem-solving strategies to turn challenges on their head

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What is an example of problem-solving?

What are the 5 steps to problem-solving, 10 effective problem-solving strategies, what skills do efficient problem solvers have, how to improve your problem-solving skills.

Problems come in all shapes and sizes — from workplace conflict to budget cuts.

Creative problem-solving is one of the most in-demand skills in all roles and industries. It can boost an organization’s human capital and give it a competitive edge. 

Problem-solving strategies are ways of approaching problems that can help you look beyond the obvious answers and find the best solution to your problem . 

Let’s take a look at a five-step problem-solving process and how to combine it with proven problem-solving strategies. This will give you the tools and skills to solve even your most complex problems.

Good problem-solving is an essential part of the decision-making process . To see what a problem-solving process might look like in real life, let’s take a common problem for SaaS brands — decreasing customer churn rates.

To solve this problem, the company must first identify it. In this case, the problem is that the churn rate is too high. 

Next, they need to identify the root causes of the problem. This could be anything from their customer service experience to their email marketing campaigns. If there are several problems, they will need a separate problem-solving process for each one. 

Let’s say the problem is with email marketing — they’re not nurturing existing customers. Now that they’ve identified the problem, they can start using problem-solving strategies to look for solutions. 

This might look like coming up with special offers, discounts, or bonuses for existing customers. They need to find ways to remind them to use their products and services while providing added value. This will encourage customers to keep paying their monthly subscriptions.

They might also want to add incentives, such as access to a premium service at no extra cost after 12 months of membership. They could publish blog posts that help their customers solve common problems and share them as an email newsletter.

The company should set targets and a time frame in which to achieve them. This will allow leaders to measure progress and identify which actions yield the best results.

Perhaps you’ve got a problem you need to tackle. Or maybe you want to be prepared the next time one arises. Either way, it’s a good idea to get familiar with the five steps of problem-solving. 

Use this step-by-step problem-solving method with the strategies in the following section to find possible solutions to your problem.

1. Identify the problem

The first step is to know which problem you need to solve. Then, you need to find the root cause of the problem. 

The best course of action is to gather as much data as possible, speak to the people involved, and separate facts from opinions. 

Once this is done, formulate a statement that describes the problem. Use rational persuasion to make sure your team agrees .

2. Break the problem down 

Identifying the problem allows you to see which steps need to be taken to solve it. 

First, break the problem down into achievable blocks. Then, use strategic planning to set a time frame in which to solve the problem and establish a timeline for the completion of each stage.

3. Generate potential solutions

At this stage, the aim isn’t to evaluate possible solutions but to generate as many ideas as possible. 

Encourage your team to use creative thinking and be patient — the best solution may not be the first or most obvious one.

Use one or more of the different strategies in the following section to help come up with solutions — the more creative, the better.

4. Evaluate the possible solutions

Once you’ve generated potential solutions, narrow them down to a shortlist. Then, evaluate the options on your shortlist. 

There are usually many factors to consider. So when evaluating a solution, ask yourself the following questions:

• Will my team be on board with the proposition?
• Does the solution align with organizational goals ?
• Is the solution likely to achieve the desired outcomes?
• Is the solution realistic and possible with current resources and constraints?
• Will the solution solve the problem without causing additional unintended problems?

5. Implement and monitor the solutions

Once you’ve identified your solution and got buy-in from your team, it’s time to implement it. 

But the work doesn’t stop there. You need to monitor your solution to see whether it actually solves your problem. 

Request regular feedback from the team members involved and have a monitoring and evaluation plan in place to measure progress.

If the solution doesn’t achieve your desired results, start this step-by-step process again.

There are many different ways to approach problem-solving. Each is suitable for different types of problems. 

The most appropriate problem-solving techniques will depend on your specific problem. You may need to experiment with several strategies before you find a workable solution.

Here are 10 effective problem-solving strategies for you to try:

• Use a solution that worked before
• Brainstorming
• Work backward
• Use the Kipling method
• Draw the problem
• Use trial and error
• Sleep on it
• Get advice from your peers
• Use the Pareto principle
• Add successful solutions to your toolkit

Let’s break each of these down.

1. Use a solution that worked before

It might seem obvious, but if you’ve faced similar problems in the past, look back to what worked then. See if any of the solutions could apply to your current situation and, if so, replicate them.

2. Brainstorming

The more people you enlist to help solve the problem, the more potential solutions you can come up with.

Use different brainstorming techniques to workshop potential solutions with your team. They’ll likely bring something you haven’t thought of to the table.

3. Work backward

Working backward is a way to reverse engineer your problem. Imagine your problem has been solved, and make that the starting point.

Then, retrace your steps back to where you are now. This can help you see which course of action may be most effective.

4. Use the Kipling method

This is a method that poses six questions based on Rudyard Kipling’s poem, “ I Keep Six Honest Serving Men .” 

• What is the problem?
• Why is the problem important?
• When did the problem arise, and when does it need to be solved?
• How did the problem happen?
• Where is the problem occurring?
• Who does the problem affect?

Answering these questions can help you identify possible solutions.

5. Draw the problem

Sometimes it can be difficult to visualize all the components and moving parts of a problem and its solution. Drawing a diagram can help.

This technique is particularly helpful for solving process-related problems. For example, a product development team might want to decrease the time they take to fix bugs and create new iterations. Drawing the processes involved can help you see where improvements can be made.

6. Use trial-and-error

A trial-and-error approach can be useful when you have several possible solutions and want to test them to see which one works best.

7. Sleep on it

Finding the best solution to a problem is a process. Remember to take breaks and get enough rest . Sometimes, a walk around the block can bring inspiration, but you should sleep on it if possible.

A good night’s sleep helps us find creative solutions to problems. This is because when you sleep, your brain sorts through the day’s events and stores them as memories. This enables you to process your ideas at a subconscious level. 

If possible, give yourself a few days to develop and analyze possible solutions. You may find you have greater clarity after sleeping on it. Your mind will also be fresh, so you’ll be able to make better decisions.

8. Get advice from your peers

Getting input from a group of people can help you find solutions you may not have thought of on your own. 

For solo entrepreneurs or freelancers, this might look like hiring a coach or mentor or joining a mastermind group. 

For leaders , it might be consulting other members of the leadership team or working with a business coach .

It’s important to recognize you might not have all the skills, experience, or knowledge necessary to find a solution alone. 

9. Use the Pareto principle

The Pareto principle — also known as the 80/20 rule — can help you identify possible root causes and potential solutions for your problems.

Although it’s not a mathematical law, it’s a principle found throughout many aspects of business and life. For example, 20% of the sales reps in a company might close 80% of the sales. 

You may be able to narrow down the causes of your problem by applying the Pareto principle. This can also help you identify the most appropriate solutions.

10. Add successful solutions to your toolkit

Every situation is different, and the same solutions might not always work. But by keeping a record of successful problem-solving strategies, you can build up a solutions toolkit. 

These solutions may be applicable to future problems. Even if not, they may save you some of the time and work needed to come up with a new solution.

Improving problem-solving skills is essential for professional development — both yours and your team’s. Here are some of the key skills of effective problem solvers:

• Critical thinking and analytical skills
• Communication skills , including active listening
• Decision-making
• Planning and prioritization
• Emotional intelligence , including empathy and emotional regulation
• Time management
• Data analysis
• Research skills
• Project management

And they see problems as opportunities. Everyone is born with problem-solving skills. But accessing these abilities depends on how we view problems. Effective problem-solvers see problems as opportunities to learn and improve.

Ready to work on your problem-solving abilities? Get started with these seven tips.

1. Build your problem-solving skills

One of the best ways to improve your problem-solving skills is to learn from experts. Consider enrolling in organizational training , shadowing a mentor , or working with a coach .

2. Practice

Practice using your new problem-solving skills by applying them to smaller problems you might encounter in your daily life. 

Alternatively, imagine problematic scenarios that might arise at work and use problem-solving strategies to find hypothetical solutions.

3. Don’t try to find a solution right away

Often, the first solution you think of to solve a problem isn’t the most appropriate or effective.

Instead of thinking on the spot, give yourself time and use one or more of the problem-solving strategies above to activate your creative thinking. 

4. Ask for feedback

Receiving feedback is always important for learning and growth. Your perception of your problem-solving skills may be different from that of your colleagues. They can provide insights that help you improve. 

5. Learn new approaches and methodologies

There are entire books written about problem-solving methodologies if you want to take a deep dive into the subject. 

We recommend starting with “ Fixed — How to Perfect the Fine Art of Problem Solving ” by Amy E. Herman. 

6. Experiment

Tried-and-tested problem-solving techniques can be useful. However, they don’t teach you how to innovate and develop your own problem-solving approaches. 

Sometimes, an unconventional approach can lead to the development of a brilliant new idea or strategy. So don’t be afraid to suggest your most “out there” ideas.

7. Analyze the success of your competitors

Do you have competitors who have already solved the problem you’re facing? Look at what they did, and work backward to solve your own problem. 

For example, Netflix started in the 1990s as a DVD mail-rental company. Its main competitor at the time was Blockbuster. 

But when streaming became the norm in the early 2000s, both companies faced a crisis. Netflix innovated, unveiling its streaming service in 2007. 

If Blockbuster had followed Netflix’s example, it might have survived. Instead, it declared bankruptcy in 2010.

Use problem-solving strategies to uplevel your business

When facing a problem, it’s worth taking the time to find the right solution. 

Otherwise, we risk either running away from our problems or headlong into solutions. When we do this, we might miss out on other, better options.

Use the problem-solving strategies outlined above to find innovative solutions to your business’ most perplexing problems.

If you’re ready to take problem-solving to the next level, request a demo with BetterUp . Our expert coaches specialize in helping teams develop and implement strategies that work.

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Elizabeth Perry, ACC

Elizabeth Perry is a Coach Community Manager at BetterUp. She uses strategic engagement strategies to cultivate a learning community across a global network of Coaches through in-person and virtual experiences, technology-enabled platforms, and strategic coaching industry partnerships. With over 3 years of coaching experience and a certification in transformative leadership and life coaching from Sofia University, Elizabeth leverages transpersonal psychology expertise to help coaches and clients gain awareness of their behavioral and thought patterns, discover their purpose and passions, and elevate their potential. She is a lifelong student of psychology, personal growth, and human potential as well as an ICF-certified ACC transpersonal life and leadership Coach.

8 creative solutions to your most challenging problems

5 problem-solving questions to prepare you for your next interview, 31 examples of problem solving performance review phrases, what are metacognitive skills examples in everyday life, what is lateral thinking 7 techniques to encourage creative ideas, leadership activities that encourage employee engagement, learn what process mapping is and how to create one (+ examples), how much do distractions cost 8 effects of lack of focus, 3 problem statement examples and steps to write your own, the pareto principle: how the 80/20 rule can help you do more with less, thinking outside the box: 8 ways to become a creative problem solver, 10 examples of principles that can guide your approach to work, contingency planning: 4 steps to prepare for the unexpected, stay connected with betterup, get our newsletter, event invites, plus product insights and research..

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

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.
• How to Resolve Employee Conflict at Work [Steps, Tips, Examples]
• How to Write Inspiring Core Values? 5 Steps with Examples
• 30 Employee Feedback Examples (Positive & Negative)

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• Turn your team into skilled problem sol ...

Turn your team into skilled problem solvers with these problem-solving strategies

Picture this, you're handling your daily tasks at work and your boss calls you in and says, "We have a problem." 

Unfortunately, we don't live in a world in which problems are instantly resolved with the snap of our fingers. Knowing how to effectively solve problems is an important professional skill to hone. If you have a problem that needs to be solved, what is the right process to use to ensure you get the most effective solution?

In this article we'll break down the problem-solving process and how you can find the most effective solutions for complex problems.

What is problem solving? 

Problem solving is the process of finding a resolution for a specific issue or conflict. There are many possible solutions for solving a problem, which is why it's important to go through a problem-solving process to find the best solution. You could use a flathead screwdriver to unscrew a Phillips head screw, but there is a better tool for the situation. Utilizing common problem-solving techniques helps you find the best solution to fit the needs of the specific situation, much like using the right tools.

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4 steps to better problem solving

While it might be tempting to dive into a problem head first, take the time to move step by step. Here’s how you can effectively break down the problem-solving process with your team:

1. Identify the problem that needs to be solved

One of the easiest ways to identify a problem is to ask questions. A good place to start is to ask journalistic questions, like:

Who : Who is involved with this problem? Who caused the problem? Who is most affected by this issue?

What: What is happening? What is the extent of the issue? What does this problem prevent from moving forward?

Where: Where did this problem take place? Does this problem affect anything else in the immediate area? 

When: When did this problem happen? When does this problem take effect? Is this an urgent issue that needs to be solved within a certain timeframe?

Why: Why is it happening? Why does it impact workflows?

How: How did this problem occur? How is it affecting workflows and team members from being productive?

Asking journalistic questions can help you define a strong problem statement so you can highlight the current situation objectively, and create a plan around that situation.

Here’s an example of how a design team uses journalistic questions to identify their problem:

Overarching problem: Design requests are being missed

Who: Design team, digital marketing team, web development team

What: Design requests are forgotten, lost, or being created ad hoc.

Where: Email requests, design request spreadsheet

When: Missed requests on January 20th, January 31st, February 4th, February 6th

How : Email request was lost in inbox and the intake spreadsheet was not updated correctly. The digital marketing team had to delay launching ads for a few days while design requests were bottlenecked. Designers had to work extra hours to ensure all requests were completed.

In this example, there are many different aspects of this problem that can be solved. Using journalistic questions can help you identify different issues and who you should involve in the process.

2. Brainstorm multiple solutions

If at all possible, bring in a facilitator who doesn't have a major stake in the solution. Bringing an individual who has little-to-no stake in the matter can help keep your team on track and encourage good problem-solving skills.

Here are a few brainstorming techniques to encourage creative thinking:

Brainstorm alone before hand: Before you come together as a group, provide some context to your team on what exactly the issue is that you're brainstorming. This will give time for you and your teammates to have some ideas ready by the time you meet.

Say yes to everything (at first): When you first start brainstorming, don't say no to any ideas just yet—try to get as many ideas down as possible. Having as many ideas as possible ensures that you’ll get a variety of solutions. Save the trimming for the next step of the strategy. 

Talk to team members one-on-one: Some people may be less comfortable sharing their ideas in a group setting. Discuss the issue with team members individually and encourage them to share their opinions without restrictions—you might find some more detailed insights than originally anticipated.

Break out of your routine: If you're used to brainstorming in a conference room or over Zoom calls, do something a little different! Take your brainstorming meeting to a coffee shop or have your Zoom call while you're taking a walk. Getting out of your routine can force your brain out of its usual rut and increase critical thinking.

3. Define the solution

After you brainstorm with team members to get their unique perspectives on a scenario, it's time to look at the different strategies and decide which option is the best solution for the problem at hand. When defining the solution, consider these main two questions: What is the desired outcome of this solution and who stands to benefit from this solution? 

Set a deadline for when this decision needs to be made and update stakeholders accordingly. Sometimes there's too many people who need to make a decision. Use your best judgement based on the limitations provided to do great things fast.

4. Implement the solution

To implement your solution, start by working with the individuals who are as closest to the problem. This can help those most affected by the problem get unblocked. Then move farther out to those who are less affected, and so on and so forth. Some solutions are simple enough that you don’t need to work through multiple teams.

After you prioritize implementation with the right teams, assign out the ongoing work that needs to be completed by the rest of the team. This can prevent people from becoming overburdened during the implementation plan . Once your solution is in place, schedule check-ins to see how the solution is working and course-correct if necessary.

Implement common problem-solving strategies

There are a few ways to go about identifying problems (and solutions). Here are some strategies you can try, as well as common ways to apply them:

Trial and error

Trial and error problem solving doesn't usually require a whole team of people to solve. To use trial and error problem solving, identify the cause of the problem, and then rapidly test possible solutions to see if anything changes. 

This problem-solving method is often used in tech support teams through troubleshooting.

The 5 whys problem-solving method helps get to the root cause of an issue. You start by asking once, “Why did this issue happen?” After answering the first why, ask again, “Why did that happen?” You'll do this five times until you can attribute the problem to a root cause. 

This technique can help you dig in and find the human error that caused something to go wrong. More importantly, it also helps you and your team develop an actionable plan so that you can prevent the issue from happening again.

Here’s an example:

Problem: The email marketing campaign was accidentally sent to the wrong audience.

“Why did this happen?” Because the audience name was not updated in our email platform.

“Why were the audience names not changed?” Because the audience segment was not renamed after editing. 

“Why was the audience segment not renamed?” Because everybody has an individual way of creating an audience segment.

“Why does everybody have an individual way of creating an audience segment?” Because there is no standardized process for creating audience segments. 

“Why is there no standardized process for creating audience segments?” Because the team hasn't decided on a way to standardize the process as the team introduced new members. 

In this example, we can see a few areas that could be optimized to prevent this mistake from happening again. When working through these questions, make sure that everyone who was involved in the situation is present so that you can co-create next steps to avoid the same problem. 

A SWOT analysis

A SWOT analysis can help you highlight the strengths and weaknesses of a specific solution. SWOT stands for:

Strength: Why is this specific solution a good fit for this problem? 

Weaknesses: What are the weak points of this solution? Is there anything that you can do to strengthen those weaknesses?

Opportunities: What other benefits could arise from implementing this solution?

Threats: Is there anything about this decision that can detrimentally impact your team?

As you identify specific solutions, you can highlight the different strengths, weaknesses, opportunities, and threats of each solution. 

This particular problem-solving strategy is good to use when you're narrowing down the answers and need to compare and contrast the differences between different solutions. 

Even more successful problem solving

After you’ve worked through a tough problem, don't forget to celebrate how far you've come. Not only is this important for your team of problem solvers to see their work in action, but this can also help you become a more efficient, effective , and flexible team. The more problems you tackle together, the more you’ll achieve. 

Looking for a tool to help solve problems on your team? Track project implementation with a work management tool like Asana .

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Struggling to overcome challenges in your life? We all face problems, big and small, on a regular basis.

So how do you tackle them effectively? What are some key problem-solving strategies and skills that can guide you?

Effective problem-solving requires breaking issues down logically, generating solutions creatively, weighing choices critically, and adapting plans flexibly based on outcomes. Useful strategies range from leveraging past solutions that have worked to visualizing problems through diagrams. Core skills include analytical abilities, innovative thinking, and collaboration.

Want to improve your problem-solving skills? Keep reading to find out 17 effective problem-solving strategies, key skills, common obstacles to watch for, and tips on improving your overall problem-solving skills.

Key Takeaways:

• Effective problem-solving requires breaking down issues logically, generating multiple solutions creatively, weighing choices critically, and adapting plans based on outcomes.
• Useful problem-solving strategies range from leveraging past solutions to brainstorming with groups to visualizing problems through diagrams and models.
• Core skills include analytical abilities, innovative thinking, decision-making, and team collaboration to solve problems.
• Common obstacles include fear of failure, information gaps, fixed mindsets, confirmation bias, and groupthink.
• Boosting problem-solving skills involves learning from experts, actively practicing, soliciting feedback, and analyzing others’ success.
• Onethread’s project management capabilities align with effective problem-solving tenets – facilitating structured solutions, tracking progress, and capturing lessons learned.

What Is Problem-Solving?

Problem-solving is the process of understanding an issue, situation, or challenge that needs to be addressed and then systematically working through possible solutions to arrive at the best outcome.

It involves critical thinking, analysis, logic, creativity, research, planning, reflection, and patience in order to overcome obstacles and find effective answers to complex questions or problems.

The ultimate goal is to implement the chosen solution successfully.

What Are Problem-Solving Strategies?

Problem-solving strategies are like frameworks or methodologies that help us solve tricky puzzles or problems we face in the workplace, at home, or with friends.

Imagine you have a big jigsaw puzzle. One strategy might be to start with the corner pieces. Another could be looking for pieces with the same colors. 

Just like in puzzles, in real life, we use different plans or steps to find solutions to problems. These strategies help us think clearly, make good choices, and find the best answers without getting too stressed or giving up.

Why Is It Important To Know Different Problem-Solving Strategies?

Knowing different problem-solving strategies is important because different types of problems often require different approaches to solve them effectively. Having a variety of strategies to choose from allows you to select the best method for the specific problem you are trying to solve.

This improves your ability to analyze issues thoroughly, develop solutions creatively, and tackle problems from multiple angles. Knowing multiple strategies also aids in overcoming roadblocks if your initial approach is not working.

Here are some reasons why you need to know different problem-solving strategies:

• Different Problems Require Different Tools: Just like you can’t use a hammer to fix everything, some problems need specific strategies to solve them.
• Improves Creativity: Knowing various strategies helps you think outside the box and come up with creative solutions.
• Saves Time: With the right strategy, you can solve problems faster instead of trying things that don’t work.
• Reduces Stress: When you know how to tackle a problem, it feels less scary and you feel more confident.
• Better Outcomes: Using the right strategy can lead to better solutions, making things work out better in the end.
• Learning and Growth: Each time you solve a problem, you learn something new, which makes you smarter and better at solving future problems.

Knowing different ways to solve problems helps you tackle anything that comes your way, making life a bit easier and more fun!

17 Effective Problem-Solving Strategies

Effective problem-solving strategies include breaking the problem into smaller parts, brainstorming multiple solutions, evaluating the pros and cons of each, and choosing the most viable option. 

Critical thinking and creativity are essential in developing innovative solutions. Collaboration with others can also provide diverse perspectives and ideas. 

By applying these strategies, you can tackle complex issues more effectively.

Now, consider a challenge you’re dealing with. Which strategy could help you find a solution? Here we will discuss key problem strategies in detail.

1. Use a Past Solution That Worked

This strategy involves looking back at previous similar problems you have faced and the solutions that were effective in solving them.

It is useful when you are facing a problem that is very similar to something you have already solved. The main benefit is that you don’t have to come up with a brand new solution – you already know the method that worked before will likely work again.

However, the limitation is that the current problem may have some unique aspects or differences that mean your old solution is not fully applicable.

The ideal process is to thoroughly analyze the new challenge, identify the key similarities and differences versus the past case, adapt the old solution as needed to align with the current context, and then pilot it carefully before full implementation.

An example is using the same negotiation tactics from purchasing your previous home when putting in an offer on a new house. Key terms would be adjusted but overall it can save significant time versus developing a brand new strategy.

2. Brainstorm Solutions

This involves gathering a group of people together to generate as many potential solutions to a problem as possible.

It is effective when you need creative ideas to solve a complex or challenging issue. By getting input from multiple people with diverse perspectives, you increase the likelihood of finding an innovative solution.

The main limitation is that brainstorming sessions can sometimes turn into unproductive gripe sessions or discussions rather than focusing on productive ideation —so they need to be properly facilitated.

The key to an effective brainstorming session is setting some basic ground rules upfront and having an experienced facilitator guide the discussion. Rules often include encouraging wild ideas, avoiding criticism of ideas during the ideation phase, and building on others’ ideas.

For instance, a struggling startup might hold a session where ideas for turnaround plans are generated and then formalized with financials and metrics.

3. Work Backward from the Solution

This technique involves envisioning that the problem has already been solved and then working step-by-step backward toward the current state.

This strategy is particularly helpful for long-term, multi-step problems. By starting from the imagined solution and identifying all the steps required to reach it, you can systematically determine the actions needed. It lets you tackle a big hairy problem through smaller, reversible steps.

A limitation is that this approach may not be possible if you cannot accurately envision the solution state to start with.

The approach helps drive logical systematic thinking for complex problem-solving, but should still be combined with creative brainstorming of alternative scenarios and solutions.

An example is planning for an event – you would imagine the successful event occurring, then determine the tasks needed the week before, two weeks before, etc. all the way back to the present.

4. Use the Kipling Method

This method, named after author Rudyard Kipling, provides a framework for thoroughly analyzing a problem before jumping into solutions.

It consists of answering six fundamental questions: What, Where, When, How, Who, and Why about the challenge. Clearly defining these core elements of the problem sets the stage for generating targeted solutions.

The Kipling method enables a deep understanding of problem parameters and root causes before solution identification. By jumping to brainstorm solutions too early, critical information can be missed or the problem is loosely defined, reducing solution quality.

Answering the six fundamental questions illuminates all angles of the issue. This takes time but pays dividends in generating optimal solutions later tuned precisely to the true underlying problem.

The limitation is that meticulously working through numerous questions before addressing solutions can slow progress.

The best approach blends structured problem decomposition techniques like the Kipling method with spurring innovative solution ideation from a diverse team. 

An example is using this technique after a technical process failure – the team would systematically detail What failed, Where/When did it fail, How it failed (sequence of events), Who was involved, and Why it likely failed before exploring preventative solutions.

5. Try Different Solutions Until One Works (Trial and Error)

This technique involves attempting various potential solutions sequentially until finding one that successfully solves the problem.

Trial and error works best when facing a concrete, bounded challenge with clear solution criteria and a small number of discrete options to try. By methodically testing solutions, you can determine the faulty component.

A limitation is that it can be time-intensive if the working solution set is large.

The key is limiting the variable set first. For technical problems, this boundary is inherent and each element can be iteratively tested. But for business issues, artificial constraints may be required – setting decision rules upfront to reduce options before testing.

Furthermore, hypothesis-driven experimentation is far superior to blind trial and error – have logic for why Option A may outperform Option B.

Examples include fixing printer jams by testing different paper tray and cable configurations or resolving website errors by tweaking CSS/HTML line-by-line until the code functions properly.

6. Use Proven Formulas or Frameworks (Heuristics)

Heuristics refers to applying existing problem-solving formulas or frameworks rather than addressing issues completely from scratch.

This allows leveraging established best practices rather than reinventing the wheel each time.

It is effective when facing recurrent, common challenges where proven structured approaches exist.

However, heuristics may force-fit solutions to non-standard problems.

For example, a cost-benefit analysis can be used instead of custom weighting schemes to analyze potential process improvements.

Onethread allows teams to define, save, and replicate configurable project templates so proven workflows can be reliably applied across problems with some consistency rather than fully custom one-off approaches each time.

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7. Trust Your Instincts (Insight Problem-Solving)

Insight is a problem-solving technique that involves waiting patiently for an unexpected “aha moment” when the solution pops into your mind.

It works well for personal challenges that require intuitive realizations over calculated logic. The unconscious mind makes connections leading to flashes of insight when relaxing or doing mundane tasks unrelated to the actual problem.

Benefits include out-of-the-box creative solutions. However, the limitations are that insights can’t be forced and may never come at all if too complex. Critical analysis is still required after initial insights.

A real-life example would be a writer struggling with how to end a novel. Despite extensive brainstorming, they feel stuck. Eventually while gardening one day, a perfect unexpected plot twist sparks an ideal conclusion. However, once written they still carefully review if the ending flows logically from the rest of the story.

8. Reverse Engineer the Problem

This approach involves deconstructing a problem in reverse sequential order from the current undesirable outcome back to the initial root causes.

By mapping the chain of events backward, you can identify the origin of where things went wrong and establish the critical junctures for solving it moving ahead. Reverse engineering provides diagnostic clarity on multi-step problems.

However, the limitation is that it focuses heavily on autopsying the past versus innovating improved future solutions.

An example is tracing back from a server outage, through the cascade of infrastructure failures that led to it finally terminating at the initial script error that triggered the crisis. This root cause would then inform the preventative measure.

9. Break Down Obstacles Between Current and Goal State (Means-End Analysis)

This technique defines the current problem state and the desired end goal state, then systematically identifies obstacles in the way of getting from one to the other.

By mapping the barriers or gaps, you can then develop solutions to address each one. This methodically connects the problem to solutions.

A limitation is that some obstacles may be unknown upfront and only emerge later.

For example, you can list down all the steps required for a new product launch – current state through production, marketing, sales, distribution, etc. to full launch (goal state) – to highlight where resource constraints or other blocks exist so they can be addressed.

Onethread allows dividing big-picture projects into discrete, manageable phases, milestones, and tasks to simplify execution just as problems can be decomposed into more achievable components. Features like dependency mapping further reinforce interconnections.

Using Onethread’s issues and subtasks feature, messy problems can be decomposed into manageable chunks.

10. Ask “Why” Five Times to Identify the Root Cause (The 5 Whys)

This technique involves asking “Why did this problem occur?” and then responding with an answer that is again met with asking “Why?” This process repeats five times until the root cause is revealed.

Continually asking why digs deeper from surface symptoms to underlying systemic issues.

It is effective for getting to the source of problems originating from human error or process breakdowns.

However, some complex issues may have multiple tangled root causes not solvable through this approach alone.

An example is a retail store experiencing a sudden decline in customers. Successively asking why five times may trace an initial drop to parking challenges, stemming from a city construction project – the true starting point to address.

11. Evaluate Strengths, Weaknesses, Opportunities, and Threats (SWOT Analysis)

This involves analyzing a problem or proposed solution by categorizing internal and external factors into a 2×2 matrix: Strengths, Weaknesses as the internal rows; Opportunities and Threats as the external columns.

Systematically identifying these elements provides balanced insight to evaluate options and risks. It is impactful when evaluating alternative solutions or developing strategy amid complexity or uncertainty.

The key benefit of SWOT analysis is enabling multi-dimensional thinking when rationally evaluating options. Rather than getting anchored on just the upsides or the existing way of operating, it urges a systematic assessment through four different lenses:

• Internal Strengths: Our core competencies/advantages able to deliver success
• Internal Weaknesses: Gaps/vulnerabilities we need to manage
• External Opportunities: Ways we can differentiate/drive additional value
• External Threats: Risks we must navigate or mitigate

Multiperspective analysis provides the needed holistic view of the balanced risk vs. reward equation for strategic decision making amid uncertainty.

However, SWOT can feel restrictive if not tailored and evolved for different issue types.

Teams should view SWOT analysis as a starting point, augmenting it further for distinct scenarios.

An example is performing a SWOT analysis on whether a small business should expand into a new market – evaluating internal capabilities to execute vs. risks in the external competitive and demand environment to inform the growth decision with eyes wide open.

12. Compare Current vs Expected Performance (Gap Analysis)

This technique involves comparing the current state of performance, output, or results to the desired or expected levels to highlight shortfalls.

By quantifying the gaps, you can identify problem areas and prioritize address solutions.

Gap analysis is based on the simple principle – “you can’t improve what you don’t measure.” It enables facts-driven problem diagnosis by highlighting delta to goals, not just vague dissatisfaction that something seems wrong. And measurement immediately suggests improvement opportunities – address the biggest gaps first.

This data orientation also supports ROI analysis on fixing issues – the return from closing larger gaps outweighs narrowly targeting smaller performance deficiencies.

However, the approach is only effective if robust standards and metrics exist as the benchmark to evaluate against. Organizations should invest upfront in establishing performance frameworks.

Furthermore, while numbers are invaluable, the human context behind problems should not be ignored – quantitative versus qualitative gap assessment is optimally blended.

For example, if usage declines are noted during software gap analysis, this could be used as a signal to improve user experience through design.

13. Observe Processes from the Frontline (Gemba Walk)

A Gemba walk involves going to the actual place where work is done, directly observing the process, engaging with employees, and finding areas for improvement.

By experiencing firsthand rather than solely reviewing abstract reports, practical problems and ideas emerge.

The limitation is Gemba walks provide anecdotes not statistically significant data. It complements but does not replace comprehensive performance measurement.

An example is a factory manager inspecting the production line to spot jam areas based on direct reality rather than relying on throughput dashboards alone back in her office. Frontline insights prove invaluable.

14. Analyze Competitive Forces (Porter’s Five Forces)

This involves assessing the marketplace around a problem or business situation via five key factors: competitors, new entrants, substitute offerings, suppliers, and customer power.

Evaluating these forces illuminates risks and opportunities for strategy development and issue resolution. It is effective for understanding dynamic external threats and opportunities when operating in a contested space.

However, over-indexing on only external factors can overlook the internal capabilities needed to execute solutions.

A startup CEO, for example, may analyze market entry barriers, whitespace opportunities, and disruption risks across these five forces to shape new product rollout strategies and marketing approaches.

15. Think from Different Perspectives (Six Thinking Hats)

The Six Thinking Hats is a technique developed by Edward de Bono that encourages people to think about a problem from six different perspectives, each represented by a colored “thinking hat.”

The key benefit of this strategy is that it pushes team members to move outside their usual thinking style and consider new angles. This brings more diverse ideas and solutions to the table.

It works best for complex problems that require innovative solutions and when a team is stuck in an unproductive debate. The structured framework keeps the conversation flowing in a positive direction.

Limitations are that it requires training on the method itself and may feel unnatural at first. Team dynamics can also influence success – some members may dominate certain “hats” while others remain quiet.

A real-life example is a software company debating whether to build a new feature. The white hat focuses on facts, red on gut feelings, black on potential risks, yellow on benefits, green on new ideas, and blue on process. This exposes more balanced perspectives before deciding.

Onethread centralizes diverse stakeholder communication onto one platform, ensuring all voices are incorporated when evaluating project tradeoffs, just as problem-solving should consider multifaceted solutions.

16. Visualize the Problem (Draw it Out)

Drawing out a problem involves creating visual representations like diagrams, flowcharts, and maps to work through challenging issues.

This strategy is helpful when dealing with complex situations with lots of interconnected components. The visuals simplify the complexity so you can thoroughly understand the problem and all its nuances.

Key benefits are that it allows more stakeholders to get on the same page regarding root causes and it sparks new creative solutions as connections are made visually.

However, simple problems with few variables don’t require extensive diagrams. Additionally, some challenges are so multidimensional that fully capturing every aspect is difficult.

A real-life example would be mapping out all the possible causes leading to decreased client satisfaction at a law firm. An intricate fishbone diagram with branches for issues like service delivery, technology, facilities, culture, and vendor partnerships allows the team to trace problems back to their origins and brainstorm targeted fixes.

17. Follow a Step-by-Step Procedure (Algorithms)

An algorithm is a predefined step-by-step process that is guaranteed to produce the correct solution if implemented properly.

Using algorithms is effective when facing problems that have clear, binary right and wrong answers. Algorithms work for mathematical calculations, computer code, manufacturing assembly lines, and scientific experiments.

Key benefits are consistency, accuracy, and efficiency. However, they require extensive upfront development and only apply to scenarios with strict parameters. Additionally, human error can lead to mistakes.

For example, crew members of fast food chains like McDonald’s follow specific algorithms for food prep – from grill times to ingredient amounts in sandwiches, to order fulfillment procedures. This ensures uniform quality and service across all locations. However, if a step is missed, errors occur.

The Problem-Solving Process

The problem-solving process typically includes defining the issue, analyzing details, creating solutions, weighing choices, acting, and reviewing results.

In the above, we have discussed several problem-solving strategies. For every problem-solving strategy, you have to follow these processes. Here’s a detailed step-by-step process of effective problem-solving:

Step 1: Identify the Problem

The problem-solving process starts with identifying the problem. This step involves understanding the issue’s nature, its scope, and its impact. Once the problem is clearly defined, it sets the foundation for finding effective solutions.

Identifying the problem is crucial. It means figuring out exactly what needs fixing. This involves looking at the situation closely, understanding what’s wrong, and knowing how it affects things. It’s about asking the right questions to get a clear picture of the issue. 

This step is important because it guides the rest of the problem-solving process. Without a clear understanding of the problem, finding a solution is much harder. It’s like diagnosing an illness before treating it. Once the problem is identified accurately, you can move on to exploring possible solutions and deciding on the best course of action.

Step 2: Break Down the Problem

Breaking down the problem is a key step in the problem-solving process. It involves dividing the main issue into smaller, more manageable parts. This makes it easier to understand and tackle each component one by one.

After identifying the problem, the next step is to break it down. This means splitting the big issue into smaller pieces. It’s like solving a puzzle by handling one piece at a time. 

By doing this, you can focus on each part without feeling overwhelmed. It also helps in identifying the root causes of the problem. Breaking down the problem allows for a clearer analysis and makes finding solutions more straightforward. 

Each smaller problem can be addressed individually, leading to an effective resolution of the overall issue. This approach not only simplifies complex problems but also aids in developing a systematic plan to solve them.

Step 3: Come up with potential solutions

Coming up with potential solutions is the third step in the problem-solving process. It involves brainstorming various options to address the problem, considering creativity and feasibility to find the best approach.

After breaking down the problem, it’s time to think of ways to solve it. This stage is about brainstorming different solutions. You look at the smaller issues you’ve identified and start thinking of ways to fix them. This is where creativity comes in. 

You want to come up with as many ideas as possible, no matter how out-of-the-box they seem. It’s important to consider all options and evaluate their pros and cons. This process allows you to gather a range of possible solutions. 

Later, you can narrow these down to the most practical and effective ones. This step is crucial because it sets the stage for deciding on the best solution to implement. It’s about being open-minded and innovative to tackle the problem effectively.

Step 4: Analyze the possible solutions

Analyzing the possible solutions is the fourth step in the problem-solving process. It involves evaluating each proposed solution’s advantages and disadvantages to determine the most effective and feasible option.

After coming up with potential solutions, the next step is to analyze them. This means looking closely at each idea to see how well it solves the problem. You weigh the pros and cons of every solution.

Consider factors like cost, time, resources, and potential outcomes. This analysis helps in understanding the implications of each option. It’s about being critical and objective, ensuring that the chosen solution is not only effective but also practical.

This step is vital because it guides you towards making an informed decision. It involves comparing the solutions against each other and selecting the one that best addresses the problem.

By thoroughly analyzing the options, you can move forward with confidence, knowing you’ve chosen the best path to solve the issue.

Step 5: Implement and Monitor the Solutions

Implementing and monitoring the solutions is the final step in the problem-solving process. It involves putting the chosen solution into action and observing its effectiveness, making adjustments as necessary.

Once you’ve selected the best solution, it’s time to put it into practice. This step is about action. You implement the chosen solution and then keep an eye on how it works. Monitoring is crucial because it tells you if the solution is solving the problem as expected. 

If things don’t go as planned, you may need to make some changes. This could mean tweaking the current solution or trying a different one. The goal is to ensure the problem is fully resolved. 

This step is critical because it involves real-world application. It’s not just about planning; it’s about doing and adjusting based on results. By effectively implementing and monitoring the solutions, you can achieve the desired outcome and solve the problem successfully.

Why This Process is Important

Following a defined process to solve problems is important because it provides a systematic, structured approach instead of a haphazard one. Having clear steps guides logical thinking, analysis, and decision-making to increase effectiveness. Key reasons it helps are:

• Clear Direction: This process gives you a clear path to follow, which can make solving problems less overwhelming.
• Better Solutions: Thoughtful analysis of root causes, iterative testing of solutions, and learning orientation lead to addressing the heart of issues rather than just symptoms.
• Saves Time and Energy: Instead of guessing or trying random things, this process helps you find a solution more efficiently.
• Improves Skills: The more you use this process, the better you get at solving problems. It’s like practicing a sport. The more you practice, the better you play.
• Maximizes collaboration: Involving various stakeholders in the process enables broader inputs. Their communication and coordination are streamlined through organized brainstorming and evaluation.
• Provides consistency: Standard methodology across problems enables building institutional problem-solving capabilities over time. Patterns emerge on effective techniques to apply to different situations.

The problem-solving process is a powerful tool that can help us tackle any challenge we face. By following these steps, we can find solutions that work and learn important skills along the way.

Key Skills for Efficient Problem Solving

Efficient problem-solving requires breaking down issues logically, evaluating options, and implementing practical solutions.

Key skills include critical thinking to understand root causes, creativity to brainstorm innovative ideas, communication abilities to collaborate with others, and decision-making to select the best way forward. Staying adaptable, reflecting on outcomes, and applying lessons learned are also essential.

With practice, these capacities will lead to increased personal and team effectiveness in systematically addressing any problem.

 Let’s explore the powers you need to become a problem-solving hero!

Critical Thinking and Analytical Skills

Critical thinking and analytical skills are vital for efficient problem-solving as they enable individuals to objectively evaluate information, identify key issues, and generate effective solutions. 

These skills facilitate a deeper understanding of problems, leading to logical, well-reasoned decisions. By systematically breaking down complex issues and considering various perspectives, individuals can develop more innovative and practical solutions, enhancing their problem-solving effectiveness.

Communication Skills

Effective communication skills are essential for efficient problem-solving as they facilitate clear sharing of information, ensuring all team members understand the problem and proposed solutions. 

These skills enable individuals to articulate issues, listen actively, and collaborate effectively, fostering a productive environment where diverse ideas can be exchanged and refined. By enhancing mutual understanding, communication skills contribute significantly to identifying and implementing the most viable solutions.

Decision-Making

Strong decision-making skills are crucial for efficient problem-solving, as they enable individuals to choose the best course of action from multiple alternatives. 

These skills involve evaluating the potential outcomes of different solutions, considering the risks and benefits, and making informed choices. Effective decision-making leads to the implementation of solutions that are likely to resolve problems effectively, ensuring resources are used efficiently and goals are achieved.

Planning and Prioritization

Planning and prioritization are key for efficient problem-solving, ensuring resources are allocated effectively to address the most critical issues first. This approach helps in organizing tasks according to their urgency and impact, streamlining efforts towards achieving the desired outcome efficiently.

Emotional Intelligence

Emotional intelligence enhances problem-solving by allowing individuals to manage emotions, understand others, and navigate social complexities. It fosters a positive, collaborative environment, essential for generating creative solutions and making informed, empathetic decisions.

Leadership skills drive efficient problem-solving by inspiring and guiding teams toward common goals. Effective leaders motivate their teams, foster innovation, and navigate challenges, ensuring collective efforts are focused and productive in addressing problems.

Time Management

Time management is crucial in problem-solving, enabling individuals to allocate appropriate time to each task. By efficiently managing time, one can ensure that critical problems are addressed promptly without neglecting other responsibilities.

Data Analysis

Data analysis skills are essential for problem-solving, as they enable individuals to sift through data, identify trends, and extract actionable insights. This analytical approach supports evidence-based decision-making, leading to more accurate and effective solutions.

Research Skills

Research skills are vital for efficient problem-solving, allowing individuals to gather relevant information, explore various solutions, and understand the problem’s context. This thorough exploration aids in developing well-informed, innovative solutions.

Becoming a great problem solver takes practice, but with these skills, you’re on your way to becoming a problem-solving hero. 

How to Improve Your Problem-Solving Skills?

Improving your problem-solving skills can make you a master at overcoming challenges. Learn from experts, practice regularly, welcome feedback, try new methods, experiment, and study others’ success to become better.

Learning from Experts

Improving problem-solving skills by learning from experts involves seeking mentorship, attending workshops, and studying case studies. Experts provide insights and techniques that refine your approach, enhancing your ability to tackle complex problems effectively.

To enhance your problem-solving skills, learning from experts can be incredibly beneficial. Engaging with mentors, participating in specialized workshops, and analyzing case studies from seasoned professionals can offer valuable perspectives and strategies. 

Experts share their experiences, mistakes, and successes, providing practical knowledge that can be applied to your own problem-solving process. This exposure not only broadens your understanding but also introduces you to diverse methods and approaches, enabling you to tackle challenges more efficiently and creatively.

Improving problem-solving skills through practice involves tackling a variety of challenges regularly. This hands-on approach helps in refining techniques and strategies, making you more adept at identifying and solving problems efficiently.

One of the most effective ways to enhance your problem-solving skills is through consistent practice. By engaging with different types of problems on a regular basis, you develop a deeper understanding of various strategies and how they can be applied. 

This hands-on experience allows you to experiment with different approaches, learn from mistakes, and build confidence in your ability to tackle challenges.

Regular practice not only sharpens your analytical and critical thinking skills but also encourages adaptability and innovation, key components of effective problem-solving.

Openness to Feedback

Being open to feedback is like unlocking a secret level in a game. It helps you boost your problem-solving skills. Improving problem-solving skills through openness to feedback involves actively seeking and constructively responding to critiques. 

This receptivity enables you to refine your strategies and approaches based on insights from others, leading to more effective solutions. 

Learning New Approaches and Methodologies

Learning new approaches and methodologies is like adding new tools to your toolbox. It makes you a smarter problem-solver. Enhancing problem-solving skills by learning new approaches and methodologies involves staying updated with the latest trends and techniques in your field. 

This continuous learning expands your toolkit, enabling innovative solutions and a fresh perspective on challenges.

Experimentation

Experimentation is like being a scientist of your own problems. It’s a powerful way to improve your problem-solving skills. Boosting problem-solving skills through experimentation means trying out different solutions to see what works best. This trial-and-error approach fosters creativity and can lead to unique solutions that wouldn’t have been considered otherwise.

Analyzing Competitors’ Success

Analyzing competitors’ success is like being a detective. It’s a smart way to boost your problem-solving skills. Improving problem-solving skills by analyzing competitors’ success involves studying their strategies and outcomes. Understanding what worked for them can provide valuable insights and inspire effective solutions for your own challenges. 

Challenges in Problem-Solving

Facing obstacles when solving problems is common. Recognizing these barriers, like fear of failure or lack of information, helps us find ways around them for better solutions.

Fear of Failure

Fear of failure is like a big, scary monster that stops us from solving problems. It’s a challenge many face. Because being afraid of making mistakes can make us too scared to try new solutions. 

How can we overcome this? First, understand that it’s okay to fail. Failure is not the opposite of success; it’s part of learning. Every time we fail, we discover one more way not to solve a problem, getting us closer to the right solution. Treat each attempt like an experiment. It’s not about failing; it’s about testing and learning.

Lack of Information

Lack of information is like trying to solve a puzzle with missing pieces. It’s a big challenge in problem-solving. Because without all the necessary details, finding a solution is much harder. 

How can we fix this? Start by gathering as much information as you can. Ask questions, do research, or talk to experts. Think of yourself as a detective looking for clues. The more information you collect, the clearer the picture becomes. Then, use what you’ve learned to think of solutions. 

Fixed Mindset

A fixed mindset is like being stuck in quicksand; it makes solving problems harder. It means thinking you can’t improve or learn new ways to solve issues. 

How can we change this? First, believe that you can grow and learn from challenges. Think of your brain as a muscle that gets stronger every time you use it. When you face a problem, instead of saying “I can’t do this,” try thinking, “I can’t do this yet.” Look for lessons in every challenge and celebrate small wins. 

Everyone starts somewhere, and mistakes are just steps on the path to getting better. By shifting to a growth mindset, you’ll see problems as opportunities to grow. Keep trying, keep learning, and your problem-solving skills will soar!

Jumping to Conclusions

Jumping to conclusions is like trying to finish a race before it starts. It’s a challenge in problem-solving. That means making a decision too quickly without looking at all the facts. 

How can we avoid this? First, take a deep breath and slow down. Think about the problem like a puzzle. You need to see all the pieces before you know where they go. Ask questions, gather information, and consider different possibilities. Don’t choose the first solution that comes to mind. Instead, compare a few options. 

Feeling Overwhelmed

Feeling overwhelmed is like being buried under a mountain of puzzles. It’s a big challenge in problem-solving. When we’re overwhelmed, everything seems too hard to handle. 

How can we deal with this? Start by taking a step back. Breathe deeply and focus on one thing at a time. Break the big problem into smaller pieces, like sorting puzzle pieces by color. Tackle each small piece one by one. It’s also okay to ask for help. Sometimes, talking to someone else can give you a new perspective. 

Confirmation Bias

Confirmation bias is like wearing glasses that only let you see what you want to see. It’s a challenge in problem-solving. Because it makes us focus only on information that agrees with what we already believe, ignoring anything that doesn’t. 

How can we overcome this? First, be aware that you might be doing it. It’s like checking if your glasses are on right. Then, purposely look for information that challenges your views. It’s like trying on a different pair of glasses to see a new perspective. Ask questions and listen to answers, even if they don’t fit what you thought before.

Groupthink is like everyone in a group deciding to wear the same outfit without asking why. It’s a challenge in problem-solving. It means making decisions just because everyone else agrees, without really thinking it through. 

How can we avoid this? First, encourage everyone in the group to share their ideas, even if they’re different. It’s like inviting everyone to show their unique style of clothes. 

Listen to all opinions and discuss them. It’s okay to disagree; it helps us think of better solutions. Also, sometimes, ask someone outside the group for their thoughts. They might see something everyone in the group missed.

Overcoming obstacles in problem-solving requires patience, openness, and a willingness to learn from mistakes. By recognizing these barriers, we can develop strategies to navigate around them, leading to more effective and creative solutions.

What are the most common problem-solving techniques?

The most common techniques include brainstorming, the 5 Whys, mind mapping, SWOT analysis, and using algorithms or heuristics. Each approach has its strengths, suitable for different types of problems.

What’s the best problem-solving strategy for every situation?

There’s no one-size-fits-all strategy. The best approach depends on the problem’s complexity, available resources, and time constraints. Combining multiple techniques often yields the best results.

How can I improve my problem-solving skills?

Improve your problem-solving skills by practicing regularly, learning from experts, staying open to feedback, and continuously updating your knowledge on new approaches and methodologies.

Are there any tools or resources to help with problem-solving?

Yes, tools like mind mapping software, online courses on critical thinking, and books on problem-solving techniques can be very helpful. Joining forums or groups focused on problem-solving can also provide support and insights.

What are some common mistakes people make when solving problems?

Common mistakes include jumping to conclusions without fully understanding the problem, ignoring valuable feedback, sticking to familiar solutions without considering alternatives, and not breaking down complex problems into manageable parts.

Final Words

Mastering problem-solving strategies equips us with the tools to tackle challenges across all areas of life. By understanding and applying these techniques, embracing a growth mindset, and learning from both successes and obstacles, we can transform problems into opportunities for growth. Continuously improving these skills ensures we’re prepared to face and solve future challenges more effectively.

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The Art of Effective Problem Solving: A Step-by-Step Guide

Whether we realise it or not, problem solving skills are an important part of our daily lives. From resolving a minor annoyance at home to tackling complex business challenges at work, our ability to solve problems has a significant impact on our success and happiness. However, not everyone is naturally gifted at problem-solving, and even those who are can always improve their skills. In this blog post, we will go over the art of effective problem-solving step by step.

Problem Solving Methodologies

Methodology of 8D (Eight Discipline) Problem Solving:

A3 Problem Solving Method:

The A3 problem solving technique is a visual, team-based problem-solving approach that is frequently used in Lean Six Sigma projects. The A3 report is a one-page document that clearly and concisely outlines the problem, root cause analysis, and proposed solution.

Subsequently, in the Lean Six Sigma framework, the 8D and A3 problem solving methodologies are two popular approaches to problem solving. Both methodologies provide a structured, team-based problem-solving approach that guides individuals through a comprehensive and systematic process of identifying, analysing, and resolving problems in an effective and efficient manner.

Step 1 – Define the Problem

By repeatedly asking “ why ,” you’ll eventually get to the bottom of the problem. This is an important step in the problem-solving process because it ensures that you’re dealing with the root cause rather than just the symptoms.

Step 2 – Gather Information and Brainstorm Ideas

Gathering information and brainstorming ideas is the next step in effective problem solving. This entails researching the problem and relevant information, collaborating with others, and coming up with a variety of potential solutions. This increases your chances of finding the best solution to the problem.

Next, work with others to gather a variety of perspectives. Brainstorming with others can be an excellent way to come up with new and creative ideas. Encourage everyone to share their thoughts and ideas when working in a group, and make an effort to actively listen to what others have to say. Be open to new and unconventional ideas and resist the urge to dismiss them too quickly.

Once you’ve compiled a list of potential solutions, it’s time to assess them and select the best one. This is the next step in the problem-solving process, which we’ll go over in greater detail in the following section.

Step 3 – Evaluate Options and Choose the Best Solution

Once you’ve compiled a list of potential solutions, it’s time to assess them and select the best one. This is the third step in effective problem solving, and it entails weighing the advantages and disadvantages of each solution, considering their feasibility and practicability, and selecting the solution that is most likely to solve the problem effectively.

You’ll be able to tell which solutions are likely to succeed and which aren’t by assessing their feasibility and practicability.

Step 4 – Implement and Monitor the Solution

When you’ve decided on the best solution, it’s time to put it into action. The fourth and final step in effective problem solving is to put the solution into action, monitor its progress, and make any necessary adjustments.

Finally, make any necessary modifications to the solution. This could entail changing the solution, altering the plan of action, or delegating different tasks. Be willing to make changes if they will improve the solution or help it solve the problem more effectively.

You can increase your chances of success in problem solving by following these steps and considering factors such as the pros and cons of each solution, their feasibility and practicability, and making any necessary adjustments. Furthermore, keep in mind that problem solving is an iterative process, and there may be times when you need to go back to the beginning and restart. Maintain your adaptability and try new solutions until you find the one that works best for you.

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Learn Creative Problem Solving Techniques to Stimulate Innovation in Your Organization

By Kate Eby | October 20, 2017 (updated August 27, 2021)

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In today’s competitive business landscape, organizations need processes in place to make strong, well-informed, and innovative decisions. Problem solving - in particular creative problem solving (CPS) - is a key skill in learning how to accurately identify problems and their causes, generate potential solutions, and evaluate all the possibilities to arrive at a strong corrective course of action. Every team in any organization, regardless of department or industry, needs to be effective, creative, and quick when solving problems. 

In this article, we’ll discuss traditional and creative problem solving, and define the steps, best practices, and common barriers associated. After that, we’ll provide helpful methods and tools to identify the cause(s) of problematic situations, so you can get to the root of the issue and start to generate solutions. Then, we offer nearly 20 creative problem solving techniques to implement at your organization, or even in your personal life. Along the way, experts weigh in on the importance of problem solving, and offer tips and tricks. 

What Is Problem Solving and Decision Making?

Problem solving is the process of working through every aspect of an issue or challenge to reach a solution. Decision making is choosing one of multiple proposed solutions  — therefore, this process also includes defining and evaluating all potential options. Decision making is often one step of the problem solving process, but the two concepts are distinct. 

Collective problem solving is problem solving that includes many different parties and bridges the knowledge of different groups. Collective problem solving is common in business problem solving because workplace decisions typically affect more than one person. 

Problem solving, especially in business, is a complicated science. Not only are business conflicts multifaceted, but they often involve different personalities, levels of authority, and group dynamics. In recent years, however, there has been a rise in psychology-driven problem solving techniques, especially for the workplace. In fact, the psychology of how people solve problems is now studied formally in academic disciplines such as psychology and cognitive science.

Joe Carella is the Assistant Dean for Executive Education at the University of Arizona . Joe has over 20 years of experience in helping executives and corporations in managing change and developing successful business strategies. His doctoral research and executive education engagements have seen him focus on corporate strategy, decision making and business performance with a variety of corporate clients including Hershey’s, Chevron, Fender Musical Instruments Corporation, Intel, DP World, Essilor, BBVA Compass Bank.

He explains some of the basic psychology behind problem solving: “When our brain is engaged in the process of solving problems, it is engaged in a series of steps where it processes and organizes the information it receives while developing new knowledge it uses in future steps. Creativity is embedded in this process by incorporating diverse inputs and/or new ways of organizing the information received.”

Laura MacLeod is a Professor of Social Group Work at City University of New York, and the creator of From The Inside Out Project® , a program that coaches managers in team leadership for a variety of workplaces. She has a background in social work and over two decades of experience as a union worker, and currently leads talks on conflict resolution, problem solving, and listening skills at conferences across the country. 

MacLeod thinks of problem solving as an integral practice of successful organizations. “Problem solving is a collaborative process — all voices are heard and connected, and resolution is reached by the group,” she says. “Problems and conflicts occur in all groups and teams in the workplace, but if leaders involve everyone in working through, they will foster cohesion, engagement, and buy in. Everybody wins.”

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What Is the First Step in Solving a Problem?

Although problem solving techniques vary procedurally, experts agree that the first step in solving a problem is defining the problem. Without a clear articulation of the problem at stake, it is impossible to analyze all the key factors and actors, generate possible solutions, and then evaluate them to pick the best option. 

Dr. Elliott Jaffa is a behavioral and management psychologist with over 25 years of problem solving training and management experience. “Start with defining the problem you want to solve,” he says, “And then define where you want to be, what you want to come away with.” He emphasizes these are the first steps in creating an actionable, clear solution. 

Bryan Mattimore is Co-Founder of Growth Engine, an 18-year old innovation agency based in Norwalk, CT. Bryan has facilitated over 1,000 ideation sessions and managed over 200 successful innovation projects leading to over $3 billion in new sales. His newest book is 21 Days to a Big Idea . When asked about the first critical component to successful problem solving, Mattimore says, “Defining the challenge correctly, or ‘solving the right problem’ … The three creative techniques we use to help our clients ‘identify the right problem to be solved’ are questioning assumptions, 20 questions, and problem redefinition. A good example of this was a new product challenge from a client to help them ‘invent a new iron. We got them to redefine the challenge as first: a) inventing new anti-wrinkle devices, and then b) inventing new garment care devices.”

What Are Problem Solving Skills?

To understand the necessary skills in problem solving, you should first understand the types of thinking often associated with strong decision making. Most problem solving techniques look for a balance between the following binaries:

• Convergent vs. Divergent Thinking: Convergent thinking is bringing together disparate information or ideas to determine a single best answer or solution. This thinking style values logic, speed, and accuracy, and leaves no chance for ambiguity. Divergent thinking is focused on generating new ideas to identify and evaluate multiple possible solutions, often uniting ideas in unexpected combinations. Divergent thinking is characterized by creativity, complexity, curiosity, flexibility, originality, and risk-taking.
• Pragmatics vs. Semantics: Pragmatics refer to the logic of the problem at hand, and semantics is how you interpret the problem to solve it. Both are important to yield the best possible solution.
• Mathematical vs. Personal Problem Solving: Mathematical problem solving involves logic (usually leading to a single correct answer), and is useful for problems that involve numbers or require an objective, clear-cut solution. However, many workplace problems also require personal problem solving, which includes interpersonal, collaborative, and emotional intuition and skills. 

The following basic methods are fundamental problem solving concepts. Implement them to help balance the above thinking models.

• Reproductive Thinking: Reproductive thinking uses past experience to solve a problem. However, be careful not to rely too heavily on past solutions, and to evaluate current problems individually, with their own factors and parameters. 
• Idea Generation: The process of generating many possible courses of action to identify a solution. This is most commonly a team exercise because putting everyone’s ideas on the table will yield the greatest number of potential solutions. 

However, many of the most critical problem solving skills are “soft” skills: personal and interpersonal understanding, intuitiveness, and strong listening. 

Mattimore expands on this idea: “The seven key skills to be an effective creative problem solver that I detail in my book Idea Stormers: How to Lead and Inspire Creative Breakthroughs are: 1) curiosity 2) openness 3) a willingness to embrace ambiguity 4) the ability to identify and transfer principles across categories and disciplines 5) the desire to search for integrity in ideas, 6) the ability to trust and exercise “knowingness” and 7) the ability to envision new worlds (think Dr. Seuss, Star Wars, Hunger Games, Harry Potter, etc.).”

“As an individual contributor to problem solving it is important to exercise our curiosity, questioning, and visioning abilities,” advises Carella. “As a facilitator it is essential to allow for diverse ideas to emerge, be able to synthesize and ‘translate’ other people’s thinking, and build an extensive network of available resources.”

MacLeod says the following interpersonal skills are necessary to effectively facilitate group problem solving: “The abilities to invite participation (hear all voices, encourage silent members), not take sides, manage dynamics between the monopolizer, the scapegoat, and the bully, and deal with conflict (not avoiding it or shutting down).” 

Furthermore, Jaffa explains that the skills of a strong problem solver aren’t measurable. The best way to become a creative problem solver, he says, is to do regular creative exercises that keep you sharp and force you to think outside the box. Carella echoes this sentiment: “Neuroscience tells us that creativity comes from creating novel neural paths. Allow a few minutes each day to exercise your brain with novel techniques and brain ‘tricks’ – read something new, drive to work via a different route, count backwards, smell a new fragrance, etc.”

What Is Creative Problem Solving? History, Evolution, and Core Principles

Creative problem solving (CPS) is a method of problem solving in which you approach a problem or challenge in an imaginative, innovative way. The goal of CPS is to come up with innovative solutions, make a decision, and take action quickly. Sidney Parnes and Alex Osborn are credited with developing the creative problem solving process in the 1950s. The concept was further studied and developed at SUNY Buffalo State and the Creative Education Foundation. 

The core principles of CPS include the following:

• Balance divergent and convergent thinking
• Ask problems as questions
• Defer or suspend judgement
• Focus on “Yes, and…” rather than “No, but…”

According to Carella, “Creative problem solving is the mental process used for generating innovative and imaginative ideas as a solution to a problem or a challenge. Creative problem solving techniques can be pursued by individuals or groups.”

When asked to define CPS, Jaffa explains that it is, by nature, difficult to create boundaries for. “Creative problem solving is not cut and dry,” he says, “If you ask 100 different people the definition of creative problem solving, you’ll get 100 different responses - it’s a non-entity.”

Business presents a unique need for creative problem solving. Especially in today’s competitive landscape, organizations need to iterate quickly, innovate with intention, and constantly be at the cutting-edge of creativity and new ideas to succeed. Developing CPS skills among your workforce not only enables you to make faster, stronger in-the-moment decisions, but also inspires a culture of collaborative work and knowledge sharing. When people work together to generate multiple novel ideas and evaluate solutions, they are also more likely to arrive at an effective decision, which will improve business processes and reduce waste over time. In fact, CPS is so important that some companies now list creative problem solving skills as a job criteria.

MacLeod reiterates the vitality of creative problem solving in the workplace. “Problem solving is crucial for all groups and teams,” she says. “Leaders need to know how to guide the process, hear all voices and involve all members - it’s not easy.”

“This mental process [of CPS] is especially helpful in work environments where individuals and teams continuously struggle with new problems and challenges posed by their continuously changing environment,” adds Carella. 

Problem Solving Best Practices

By nature, creative problem solving does not have a clear-cut set of do’s and don’ts. Rather, creating a culture of strong creative problem solvers requires flexibility, adaptation, and interpersonal skills. However, there are a several best practices that you should incorporate:

• Use a Systematic Approach: Regardless of the technique you use, choose a systematic method that satisfies your workplace conditions and constraints (time, resources, budget, etc.). Although you want to preserve creativity and openness to new ideas, maintaining a structured approach to the process will help you stay organized and focused. 
• View Problems as Opportunities: Rather than focusing on the negatives or giving up when you encounter barriers, treat problems as opportunities to enact positive change on the situation. In fact, some experts even recommend defining problems as opportunities, to remain proactive and positive.
• Change Perspective: Remember that there are multiple ways to solve any problem. If you feel stuck, changing perspective can help generate fresh ideas. A perspective change might entail seeking advice of a mentor or expert, understanding the context of a situation, or taking a break and returning to the problem later. “A sterile or familiar environment can stifle new thinking and new perspectives,” says Carella. “Make sure you get out to draw inspiration from spaces and people out of your usual reach.”
• Break Down Silos: To invite the greatest possible number of perspectives to any problem, encourage teams to work cross-departmentally. This not only combines diverse expertise, but also creates a more trusting and collaborative environment, which is essential to effective CPS. According to Carella, “Big challenges are always best tackled by a group of people rather than left to a single individual. Make sure you create a space where the team can concentrate and convene.”
• Employ Strong Leadership or a Facilitator: Some companies choose to hire an external facilitator that teaches problem solving techniques, best practices, and practicums to stimulate creative problem solving. But, internal managers and staff can also oversee these activities. Regardless of whether the facilitator is internal or external, choose a strong leader who will value others’ ideas and make space for creative solutions.  Mattimore has specific advice regarding the role of a facilitator: “When facilitating, get the group to name a promising idea (it will crystalize the idea and make it more memorable), and facilitate deeper rather than broader. Push for not only ideas, but how an idea might specifically work, some of its possible benefits, who and when would be interested in an idea, etc. This fleshing-out process with a group will generate fewer ideas, but at the end of the day will yield more useful concepts that might be profitably pursued.” Additionally, Carella says that “Executives and managers don’t necessarily have to be creative problem solvers, but need to make sure that their teams are equipped with the right tools and resources to make this happen. Also they need to be able to foster an environment where failing fast is accepted and celebrated.”
• Evaluate Your Current Processes: This practice can help you unlock bottlenecks, and also identify gaps in your data and information management, both of which are common roots of business problems.

MacLeod offers the following additional advice, “Always get the facts. Don’t jump too quickly to a solution – working through [problems] takes time and patience.”

Mattimore also stresses that how you introduce creative problem solving is important. “Do not start by introducing a new company-wide innovation process,” he says. “Instead, encourage smaller teams to pursue specific creative projects, and then build a process from the ground up by emulating these smaller teams’ successful approaches. We say: ‘You don’t innovate by changing the culture, you change the culture by innovating.’”

Barriers to Effective Problem Solving

Learning how to effectively solve problems is difficult and takes time and continual adaptation. There are several common barriers to successful CPS, including:

• Confirmation Bias: The tendency to only search for or interpret information that confirms a person’s existing ideas. People misinterpret or disregard data that doesn’t align with their beliefs.
• Mental Set: People’s inclination to solve problems using the same tactics they have used to solve problems in the past. While this can sometimes be a useful strategy (see Analogical Thinking in a later section), it often limits inventiveness and creativity.
• Functional Fixedness: This is another form of narrow thinking, where people become “stuck” thinking in a certain way and are unable to be flexible or change perspective.
• Unnecessary Constraints: When people are overwhelmed with a problem, they can invent and impose additional limits on solution avenues. To avoid doing this, maintain a structured, level-headed approach to evaluating causes, effects, and potential solutions.
• Groupthink: Be wary of the tendency for group members to agree with each other — this might be out of conflict avoidance, path of least resistance, or fear of speaking up. While this agreeableness might make meetings run smoothly, it can actually stunt creativity and idea generation, therefore limiting the success of your chosen solution.
• Irrelevant Information: The tendency to pile on multiple problems and factors that may not even be related to the challenge at hand. This can cloud the team’s ability to find direct, targeted solutions.
• Paradigm Blindness: This is found in people who are unwilling to adapt or change their worldview, outlook on a particular problem, or typical way of processing information. This can erode the effectiveness of problem solving techniques because they are not aware of the narrowness of their thinking, and therefore cannot think or act outside of their comfort zone.

According to Jaffa, the primary barrier of effective problem solving is rigidity. “The most common things people say are, ‘We’ve never done it before,’ or ‘We’ve always done it this way.’” While these feelings are natural, Jaffa explains that this rigid thinking actually precludes teams from identifying creative, inventive solutions that result in the greatest benefit.

“The biggest barrier to creative problem solving is a lack of awareness – and commitment to – training employees in state-of-the-art creative problem-solving techniques,” Mattimore explains. “We teach our clients how to use ideation techniques (as many as two-dozen different creative thinking techniques) to help them generate more and better ideas. Ideation techniques use specific and customized stimuli, or ‘thought triggers’ to inspire new thinking and new ideas.” 

MacLeod adds that ineffective or rushed leadership is another common culprit. “We're always in a rush to fix quickly,” she says. “Sometimes leaders just solve problems themselves, making unilateral decisions to save time. But the investment is well worth it — leaders will have less on their plates if they can teach and eventually trust the team to resolve. Teams feel empowered and engagement and investment increases.”

Strategies for Problem Cause Identification

As discussed, most experts agree that the first and most crucial step in problem solving is defining the problem. Once you’ve done this, however, it may not be appropriate to move straight to the solution phase. Rather, it is often helpful to identify the cause(s) of the problem: This will better inform your solution planning and execution, and help ensure that you don’t fall victim to the same challenges in the future. 

Below are some of the most common strategies for identifying the cause of a problem:

• Root Cause Analysis: This method helps identify the most critical cause of a problem. A factor is considered a root cause if removing it prevents the problem from recurring. Performing a root cause analysis is a 12 step process that includes: define the problem, gather data on the factors contributing to the problem, group the factors based on shared characteristics, and create a cause-and-effect timeline to determine the root cause. After that, you identify and evaluate corrective actions to eliminate the root cause.

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Problem Solving Techniques and Strategies

In this section, we’ll explain several traditional and creative problem solving methods that you can use to identify challenges, create actionable goals, and resolve problems as they arise. Although there is often procedural and objective crossover among techniques, they are grouped by theme so you can identify which method works best for your organization.

Divergent Creative Problem Solving Techniques

Brainstorming: One of the most common methods of divergent thinking, brainstorming works best in an open group setting where everyone is encouraged to share their creative ideas. The goal is to generate as many ideas as possible – you analyze, critique, and evaluate the ideas only after the brainstorming session is complete. To learn more specific brainstorming techniques, read this article . 

Mind Mapping: This is a visual thinking tool where you graphically depict concepts and their relation to one another. You can use mind mapping to structure the information you have, analyze and synthesize it, and generate solutions and new ideas from there. The goal of a mind map is to simplify complicated problems so you can more clearly identify solutions.

Appreciative Inquiry (AI): The basic assumption of AI is that “an organization is a mystery to be embraced.” Using this principle, AI takes a positive, inquisitive approach to identifying the problem, analyzing the causes, and presenting possible solutions. The five principles of AI emphasize dialogue, deliberate language and outlook, and social bonding. 

Lateral Thinking: This is an indirect problem solving approach centered on the momentum of idea generation. As opposed to critical thinking, where people value ideas based on their truth and the absence of errors, lateral thinking values the “movement value” of new ideas: This means that you reward team members for producing a large volume of new ideas rapidly. With this approach, you’ll generate many new ideas before approving or rejecting any.

Problem Solving Techniques to Change Perspective

Constructive Controversy: This is a structured approach to group decision making to preserve critical thinking and disagreement while maintaining order. After defining the problem and presenting multiple courses of action, the group divides into small advocacy teams who research, analyze, and refute a particular option. Once each advocacy team has presented its best-case scenario, the group has a discussion (advocacy teams still defend their presented idea). Arguing and playing devil’s advocate is encouraged to reach an understanding of the pros and cons of each option. Next, advocacy teams abandon their cause and evaluate the options openly until they reach a consensus. All team members formally commit to the decision, regardless of whether they advocated for it at the beginning. You can learn more about the goals and steps in constructive controversy here . 

Carella is a fan of this approach. “Create constructive controversy by having two teams argue the pros and cons of a certain idea,” he says. “It forces unconscious biases to surface and gives space for new ideas to formulate.”

Abstraction: In this method, you apply the problem to a fictional model of the current situation. Mapping an issue to an abstract situation can shed extraneous or irrelevant factors, and reveal places where you are overlooking obvious solutions or becoming bogged down by circumstances. 

Analogical Thinking: Also called analogical reasoning , this method relies on an analogy: using information from one problem to solve another problem (these separate problems are called domains). It can be difficult for teams to create analogies among unrelated problems, but it is a strong technique to help you identify repeated issues, zoom out and change perspective, and prevent the problems from occurring in the future. .

CATWOE: This framework ensures that you evaluate the perspectives of those whom your decision will impact. The factors and questions to consider include (which combine to make the acronym CATWOE):

• Customers: Who is on the receiving end of your decisions? What problem do they currently have, and how will they react to your proposed solution?
• Actors: Who is acting to bring your solution to fruition? How will they respond and be affected by your decision?
• Transformation Process: What processes will you employ to transform your current situation and meet your goals? What are the inputs and outputs?
• World View: What is the larger context of your proposed solution? What is the larger, big-picture problem you are addressing?
• Owner: Who actually owns the process? How might they influence your proposed solution (positively or negatively), and how can you influence them to help you?
• Environmental Constraints: What are the limits (environmental, resource- and budget-wise, ethical, legal, etc.) on your ideas? How will you revise or work around these constraints?

Complex Problem Solving

Soft Systems Methodology (SSM): For extremely complex problems, SSM can help you identify how factors interact, and determine the best course of action. SSM was borne out of organizational process modeling and general systems theory, which hold that everything is part of a greater, interconnected system: This idea works well for “hard” problems (where logic and a single correct answer are prioritized), and less so for “soft” problems (i.e., human problems where factors such as personality, emotions, and hierarchy come into play). Therefore, SSM defines a seven step process for problem solving: 

• Begin with the problem or problematic situation 
• Express the problem or situation and build a rich picture of the themes of the problem 
• Identify the root causes of the problem (most commonly with CATWOE)
• Build conceptual models of human activity surrounding the problem or situation
• Compare models with real-world happenings
• Identify changes to the situation that are both feasible and desirable
• Take action to implement changes and improve the problematic situation

SSM can be used for any complex soft problem, and is also a useful tool in change management . 

Failure Mode and Effects Analysis (FMEA): This method helps teams anticipate potential problems and take steps to mitigate them. Use FMEA when you are designing (redesigning) a complex function, process, product, or service. First, identify the failure modes, which are the possible ways that a project could fail. Then, perform an effects analysis to understand the consequences of each of the potential downfalls. This exercise is useful for internalizing the severity of each potential failure and its effects so you can make adjustments or safeties in your plan. 

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Problem Solving Based on Data or Logic (Heuristic Methods)

TRIZ: A Russian-developed problem solving technique that values logic, analysis, and forecasting over intuition or soft reasoning. TRIZ (translated to “theory of inventive problem solving” or TIPS in English) is a systematic approach to defining and identifying an inventive solution to difficult problems. The method offers several strategies for arriving at an inventive solution, including a contradictions matrix to assess trade-offs among solutions, a Su-Field analysis which uses formulas to describe a system by its structure, and ARIZ (algorithm of inventive problem solving) which uses algorithms to find inventive solutions. 

Inductive Reasoning: A logical method that uses evidence to conclude that a certain answer is probable (this is opposed to deductive reasoning, where the answer is assumed to be true). Inductive reasoning uses a limited number of observations to make useful, logical conclusions (for example, the Scientific Method is an extreme example of inductive reasoning). However, this method doesn’t always map well to human problems in the workplace — in these instances, managers should employ intuitive inductive reasoning , which allows for more automatic, implicit conclusions so that work can progress. This, of course, retains the principle that these intuitive conclusions are not necessarily the one and only correct answer. 

Process-Oriented Problem Solving Methods

Plan Do Check Act (PDCA): This is an iterative management technique used to ensure continual improvement of products or processes. First, teams plan (establish objectives to meet desired end results), then do (implement the plan, new processes, or produce the output), then check (compare expected with actual results), and finally act (define how the organization will act in the future, based on the performance and knowledge gained in the previous three steps). 

Means-End Analysis (MEA): The MEA strategy is to reduce the difference between the current (problematic) state and the goal state. To do so, teams compile information on the multiple factors that contribute to the disparity between the current and goal states. Then they try to change or eliminate the factors one by one, beginning with the factor responsible for the greatest difference in current and goal state. By systematically tackling the multiple factors that cause disparity between the problem and desired outcome, teams can better focus energy and control each step of the process. 

Hurson’s Productive Thinking Model: This technique was developed by Tim Hurson, and is detailed in his 2007 book Think Better: An Innovator’s Guide to Productive Thinking . The model outlines six steps that are meant to give structure while maintaining creativity and critical thinking: 1) Ask “What is going on?” 2) Ask “What is success?” 3) Ask “What is the question?” 4) Generate answers 5) Forge the solution 6) Align resources. 

Control Influence Accept (CIA): The basic premise of CIA is that how you respond to problems determines how successful you will be in overcoming them. Therefore, this model is both a problem solving technique and stress-management tool that ensures you aren’t responding to problems in a reactive and unproductive way. The steps in CIA include:

• Control: Identify the aspects of the problem that are within your control.
• Influence: Identify the aspects of the problem that you cannot control, but that you can influence.
• Accept: Identify the aspects of the problem that you can neither control nor influence, and react based on this composite information. 

GROW Model: This is a straightforward problem solving method for goal setting that clearly defines your goals and current situation, and then asks you to define the potential solutions and be realistic about your chosen course of action. The steps break down as follows:

• Goal: What do you want?
• Reality: Where are you now?
• Options: What could you do?
• Will: What will you do?

OODA Loop: This acronym stands for observe, orient, decide, and act. This approach is a decision-making cycle that values agility and flexibility over raw human force. It is framed as a loop because of the understanding that any team will continually encounter problems or opponents to success and have to overcome them.

There are also many un-named creative problem solving techniques that follow a sequenced series of steps. While the exact steps vary slightly, they all follow a similar trajectory and aim to accomplish similar goals of problem, cause, and goal identification, idea generation, and active solution implementation.

MacLeod offers her own problem solving procedure, which echoes the above steps:

“1. Recognize the Problem: State what you see. Sometimes the problem is covert. 2. Identify: Get the facts — What exactly happened? What is the issue? 3. and 4. Explore and Connect: Dig deeper and encourage group members to relate their similar experiences. Now you're getting more into the feelings and background [of the situation], not just the facts.  5. Possible Solutions: Consider and brainstorm ideas for resolution. 6. Implement: Choose a solution and try it out — this could be role play and/or a discussion of how the solution would be put in place.  7. Evaluate: Revisit to see if the solution was successful or not.”

Many of these problem solving techniques can be used in concert with one another, or multiple can be appropriate for any given problem. It’s less about facilitating a perfect CPS session, and more about encouraging team members to continually think outside the box and push beyond personal boundaries that inhibit their innovative thinking. So, try out several methods, find those that resonate best with your team, and continue adopting new techniques and adapting your processes along the way. 

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8 Effective Problem-Solving Strategies

Categories Cognition

If you need to solve a problem, there are a number of different problem-solving strategies that can help you come up with an accurate decision. Sometimes the best choice is to use a step-by-step approach that leads to the right solution, but other problems may require a trial-and-error approach. 

Some helpful problem-solving strategies include: Brainstorming Step-by-step algorithms Trial-and-error Working backward Heuristics Insight Writing it down Getting some sleep

Table of Contents

Why Use Problem-Solving Strategies

While you can always make a wild guess or pick at random, that certainly isn’t the most accurate way to come up with a solution. Using a more structured approach allows you to:

• Understand the nature of the problem
• Determine how you will solve it
• Research different options
• Take steps to solve the problem and resolve the issue

There are many tools and strategies that can be used to solve problems, and some problems may require more than one of these methods in order to come up with a solution.

Problem-Solving Strategies

The problem-solving strategy that works best depends on the nature of the problem and how much time you have available to make a choice. Here are eight different techniques that can help you solve whatever type of problem you might face.

Brainstorming

Coming up with a lot of potential solutions can be beneficial, particularly early on in the process. You might brainstorm on your own, or enlist the help of others to get input that you might not have otherwise considered.

Step-by-Step

Also known as an algorithm, this approach involves following a predetermined formula that is guaranteed to produce the correct result. While this can be useful in some situations—such as solving a math problem—it is not always practical in every situation.

On the plus side, algorithms can be very accurate and reliable. Unfortunately, they can also be time-consuming.

And in some situations, you cannot follow this approach because you simply don’t have access to all of the information you would need to do so.

Trial-and-Error

This problem-solving strategy involves trying a number of different solutions in order to figure out which one works best. This requires testing steps or more options to solve the problem or pick the right solution. 

For example, if you are trying to perfect a recipe, you might have to experiment with varying amounts of a certain ingredient before you figure out which one you prefer.

On the plus side, trial-and-error can be a great problem-solving strategy in situations that require an individualized solution. However, this approach can be very time-consuming and costly.

Working Backward

This problem-solving strategy involves looking at the end result and working your way back through the chain of events. It can be a useful tool when you are trying to figure out what might have led to a particular outcome.

It can also be a beneficial way to play out how you will complete a task. For example, if you know you need to have a project done by a certain date, working backward can help you figure out the steps you’ll need to complete in order to successfully finish the project.

Heuristics are mental shortcuts that allow you to come up with solutions quite quickly. They are often based on past experiences that are then applied to other situations. They are, essentially, a handy rule of thumb.

For example, imagine a student is trying to pick classes for the next term. While they aren’t sure which classes they’ll enjoy the most, they know that they tend to prefer subjects that involve a lot of creativity. They utilize this heuristic to pick classes that involve art and creative writing.

The benefit of a heuristic is that it is a fast way to make fairly accurate decisions. The trade-off is that you give up some accuracy in order to gain speed and efficiency.

Sometimes, the solution to a problem seems to come out of nowhere. You might suddenly envision a solution after struggling with the problem for a while. Or you might abruptly recognize the correct solution that you hadn’t seen before. 

No matter the source, insight-based problem-solving relies on following your gut instincts. While this may not be as objective or accurate as some other problem-solving strategies, it can be a great way to come up with creative, novel solutions.

Write It Down

Sometimes putting the problem and possible solutions down in paper can be a useful way to visualize solutions. Jot down whatever might help you envision your options. Draw a picture, create a mind map, or just write some notes to clarify your thoughts.

Get Some Sleep

If you’re facing a big problem or trying to make an important decision, try getting a good night’s sleep before making a choice. Sleep plays an essential role in memory consolidation, so getting some rest may help you access the information or insight you need to make the best choice.

Other Considerations

Even with an arsenal of problem-solving strategies at your disposal, coming up with solutions isn’t always easy. Certain challenges can make the process more difficult. A few issues that might emerge include:

• Mental set : When people form a mental set, they only rely on things that have worked in the last. Sometimes this can be useful, but in other cases, it can severely hinder the problem-solving process.
• Cognitive biases : Unconscious cognitive biases can make it difficult to see situations clearly and objectively. As a result, you may not consider all of your options or ignore relevant information.
• Misinformation : Poorly sourced clues and irrelevant details can add more complications. Being able to sort out what’s relevant and what’s not is essential for solving problems accurately.
• Functional fixedness : Functional fixedness happens when people only think of customary solutions to problems. It can hinder out-of-the-box thinking and prevents insightful, creative solutions.

Important Problem-Solving Skills

Becoming a good problem solver can be useful in a variety of domains, from school to work to interpersonal relationships. Important problem-solving skills encompass being able to identify problems, coming up with effective solutions, and then implementing these solutions.

According to a 2023 survey by the National Association of Colleges and Employers, 61.4% of employers look for problem-solving skills on applicant resumes.

Some essential problem-solving skills include:

• Research skills
• Analytical abilities
• Decision-making skills
• Critical thinking
• Communication
• Time management 
• Emotional intelligence

Solving a problem is complex and requires the ability to recognize the issue, collect and analyze relevant data, and make decisions about the best course of action. It can also involve asking others for input, communicating goals, and providing direction to others.

How to Become a Better Problem-Solver

If you’re ready to strengthen your problem-solving abilities, here are some steps you can take:

Identify the Problem

Before you can practice your problem-solving skills, you need to be able to recognize that there is a problem. When you spot a potential issue, ask questions about when it started and what caused it.

Do Your Research

Instead of jumping right in to finding solutions, do research to make sure you fully understand the problem and have all the background information you need. This helps ensure you don’t miss important details.

Hone Your Skills

Consider signing up for a class or workshop focused on problem-solving skill development. There are also books that focus on different methods and approaches.

The best way to strengthen problem-solving strategies is to give yourself plenty of opportunities to practice. Look for new challenges that allow you to think critically, analytically, and creatively.

Final Thoughts

If you have a problem to solve, there are plenty of strategies that can help you make the right choice. The key is to pick the right one, but also stay flexible and willing to shift gears.

In many cases, you might find that you need more than one strategy to make the choices that are right for your life.

Brunet, J. F., McNeil, J., Doucet, É., & Forest, G. (2020). The association between REM sleep and decision-making: Supporting evidences. Physiology & Behavior , 225, 113109. https://doi.org/10.1016/j.physbeh.2020.113109

Chrysikou, E. G, Motyka, K., Nigro, C., Yang, S. I. , & Thompson-Schill, S. L. (2016). Functional fixedness in creative thinking tasks depends on stimulus modality. Psychol Aesthet Creat Arts , 10(4):425‐435. https://doi.org/10.1037/aca0000050

Sarathy, V. (2018). Real world problem-solving. Front Hum Neurosci , 12:261. https://doi.org/10.3389/fnhum.2018.00261

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Overview of the Problem-Solving Mental Process

• 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.

Get Advice From The Verywell Mind Podcast

Hosted by therapist Amy Morin, LCSW, this episode of The Verywell Mind Podcast shares how you can stop dwelling in a negative mindset.

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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."

10 Best Ways to Become a Problem-Solver (Tips & Strategies)

Do you want to be a better problem-solver? Explore the skills you need to become more effective and confident at improving things for the better.

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Are you human? Then you face problems every day! 

Whether you’re trying to figure out where to go to lunch with a group of friends who have varying dietary issues, or you can’t figure out why your customer management system at work keeps shutting down, your problems throughout your life will range from major to minor, and everything in between.

Do you want to be a better problem solver? It’s not too late to gain the skills you need to become more effective and confident at improving things for the better.

In this article, we’ll look at problem-solving, its importance, and ten tips and strategies to become a better problem-solver. 

What is Problem-Solving? (Definition)

Problem-solving is the process of breaking down challenges to find solutions. Typically it is a four-stage process of 1) identifying an issue, 2) establishing a plan, 3) executing the plan, and 4) finding a resolution. However, problem-solving can begin before a problem even occurs. For example, crisis management includes pre-planning for situations that could arise. 

What is the Importance of Problem-Solving? (Examples)

Problem-solving is important because it allows people to evaluate a problem, seek greater understanding, develop execution plans, overcome obstacles, and ultimately find a resolution. 

Those resolutions lead to many benefits, including:

• Fixing what’s broken
• Improving performance
• Increasing productivity
• Building confidence
• Avoiding risk

Here are some examples of common problems.

In the workplace: One familiar workplace problem leaders deal with is the lack of employee engagement . With good problem-solving skills, you can determine the root cause, where there may be a lack of understanding, the steps required to improve engagement, and how to get others involved in solving the issue. 

In a crisis: One crisis situation you might find yourself in is discovering your significant other has just been in a car accident. With good problem-solving skills, you can quickly assess the situation and identify steps to contact authorities, get them to a hospital within their insurance network, and sort out the insurance details while also balancing what to do about the family details at home.

In everyday life: An everyday life problem you might deal with is what you’re having for dinner! (Depending on your household, this can sometimes turn into a crisis, right?!) With good problem-solving skills, you can assess what you have on hand already, how much time you have, what others might prefer, who’s cooking, when you’ll eat, and make a decision. 

What Are the Characteristics of a Good Problem Solver?

The characteristics and qualities of a good problem solver include the ability to understand the issue, rally others together, and empower appropriate players to execute a solution. 

To do this well, problem solvers often have a knack for these skills:

• Identifying risk and opportunity
• Communicating clearly
• Listening well
• Emotional Intelligence
• Planning ahead
• Recognizing individuals’ strengths
• Accountability and discipline
• Collaborating with others
• Thinking objectively
• Getting creative
• Making smart decisions

Let’s look at how good problem solvers put these skills into action!

10 Tips and Strategies to Become a Better Problem Solver

Get clear about what the problem is.

If the problem you’re trying to solve involves multiple people—and most likely it does—it’s important to get clear about what the problem is before you start trying to solve it. People often go around in circles trying to solve a problem until they realize they weren’t on the same page from the start. It’s a time-waster!

To clarify the problem, start with clarifying questions:

• What is your perspective on the problem we’re trying to solve?
• What is your perspective on how we got here?
• What do you perceive that I’m thinking about the issue?
• What are your motives for solving the problem?

After you get clarity, you may discover multiple problems on the table. If you come to this realization, solve one of them at a time.

 Identify what needs to happen

Once you’re clear about the problem, start identifying your next steps and the goal to solve the problem. To do this, you’ll want to identify your ideal outcome and the method to reach that outcome.

For example, your problem, outcome, and method might look something like this:

Problem: Our sales team is upset that they don’t get enough sales leads from marketing.

Ideal outcome: Our marketing system and process generates enough leads to increase sales over the next year.

Method: Analyze what’s not working in the current system and reorganize or implement a new lead-generating system.

To help you set better goals as you solve problems, check out this helpful resource:

How To Set Better Goals Using Science

Do you set the same goals over and over again? If you’re not achieving your goals – it’s not your fault! Let me show you the science-based goal-setting framework to help you achieve your biggest goals.

Ask open-ended questions 

Often, there needs to be more clarity and communication at the root of many problems. To identify where something went wrong and how to solve it, gather data with questions for everyone involved. Try keeping your questions open-ended to avoid the risk of sounding accusatory with closed-ended, yes or no questions. Allow people to process and explain how they understand the issue. 

Some open-ended questions you can ask to start solving a problem include:

• What is your perspective on what happened?
• What is your perspective on this issue? 
• Where do you think this problem stems from?
• What do you think would help solve this problem?
• What feels unclear about the problem?
• What do you think is misunderstood by others?
• What story might you be telling yourself regarding this problem?

Bonus Tip: If you’re a leader, it is especially important not to limit your questions to fellow senior leaders, especially if the problem affects the organization or a wider group. Ask questions at all levels.  

Often, in hierarchically structured organizations, the employees working in the everyday processes know the issues but may feel unsure about how to bring them up. Ask! But be sure not to shoot the messenger; reward them for their feedback and support. 

Avoid the knee-jerk reaction

When you’re presented with a problem, it’s best to take a beat to assess the situation before you react. That is unless you’re facing a life-threatening situation like a house fire, physical attack, or baseball heading straight for your head. For the sake of this article, we’ll stick to solving general problems, not life-threatening problems. 

Common knee-jerk reactions include:

• Putting the blame on someone else
• Getting defensive 
• Jumping to conclusions
• Baseless anger
• Making regrettable decisions

To avoid reacting or making a decision you’ll regret later, try a centering activity like:

• Taking deep breaths
• Taking a walk to clear your head and get your blood moving
• Analyzing your initial reactions 
• Writing down what you know, don’t know, and what might be confusing

Think and plan proactively

No one is immune to problems. As much as you can, plan for potential problems down the road, even if you don’t think they’ll happen. You never know! 

Generally, we like to think positively, but in this case, the question, “What’s the worst that can happen?” can help you prepare for all kinds of situations. This is where lessons from crisis management are beneficial in your problem-solving process. 

In the readiness stage of crisis management, you’ll want to:

• Identify potential threats. What could make things harder?
• Identify weaknesses. If something were to happen, do we have the ability to face it?
• Plan your response to various scenarios. If this…then that…
• Set up your communication channels. If something happens, X is in charge of communicating X through X. 

Stay open to feedback and ideas

When you’re presented with a problem, your initial reaction may be to want to solve it as quickly as possible so that you can move past it and move on. However, when you get reactive to problems, you will more likely end up with bandaid solutions and even more issues down the road. Give yourself time to stay open to feedback and ideas as you investigate solutions.

To remain open, prime your brain to think objectively and creatively. There may be solutions in places you haven’t considered, even outside your industry or network.

• Ask for perspectives from people outside of your team. For example, maybe someone in IT has an idea for an issue you’re dealing with in HR.
• Expose yourself to authors and leaders facing similar issues. What kind of things do they do to solve similar issues?
• Expose yourself to authors and leaders facing different issues. Often, thinking through how someone else solved a problem in a situation entirely outside yours helps you see things from a new perspective.

Fun Bonus Tip: Ask a child what they would do! You might hear an outside-of-the-box idea you would never have come up with on your own. And while you may not use their idea, it could help get your juices flowing to come up with a solution!

Identify the best players to solve the problem

Not all problems need to be solved by the leader. One of the most empowering things a leader can do is provide resources and space to allow people with the strengths and skills to do what needs to be done. 

To identify the best players to solve the problem, ask yourself and others these questions:

• What skills and strengths are needed to solve the problem?
• Who on our team best fits those skill sets and strengths? 
• If the skills and strengths are outside the team, where can we outsource talent?
• How can we collaborate and complement each other’s strengths?
• What resources are needed to help solve the problem?
• What must we learn more about to solve this problem well?

Create execution plans

Once you’ve identified the problem, figured out what needs to happen, and determined the best players to solve the problem, it’s time to create the execution plan and get started. 

If you’re the leader, and you’ve determined who the best players are to solve the problem, it’s best to delegate the execution and resource them well. Micromanagement in this stage may create a whole new set of problems!

Chris McChesney identifies four disciplines of execution 1 https://pages.franklincovey.com/4d-landing-pages-execute-goals-create-breakthrough-results-guide-nw.html which include:

• Focus on the wildly important goal. What is the most important thing that must be achieved to solve the problem?
• Act on lead measures. What are the tasks and activities that will drive results?
• Keep a compelling scoreboard. What will determine whether we are moving closer to our goal?
• Create a cadence of accountability. How will we report, review, and plan for ongoing success?

Lead courageously and humbly

One thing that separates a good problem solver from an average one is that a good problem solver doesn’t ignore, run away from, deflect, or deny the problem exists. They face it head-on with humility and curiosity. You can do just that whether or not you have a leadership title.

“A leader is anyone who takes responsibility for finding the potential in people and processes and has the courage to develop that potential. Leadership is not about titles or the corner office. It’s about the willingness to step up, put yourself out there, and lean into courage.” –Brené Brown, Ph.D., MSW.

In Brené Brown’s book, Dare to Lead , she identifies four leadership skill sets of daring leaders:

• Rumbling with vulnerability: A willingness to be all in, even in the face of uncertainty
• Living into our values: Walking the talk about what we believe
• Braving trust: Being someone who has boundaries, is reliable and accountable, is a safe space to share things with, has integrity, and is non-judgmental and generous
• Learning to rise: Getting curious about what you feel and why

Are you a courageous leader? Take Brené Brown’s Daring Leadership Assessment .

Train for the future

To be human is to have problems occasionally. But equipping yourself with problem-solving skills will make you far better off when they arise. Be good to your future self and train yourself to be ready with helpful resources and books, including:

• The 4 Disciplines of Execution
• Fixed: How to Perfect the Fine Art of Problem Solving
• Upstream: The Quest to Solve Problems Before They Happen
• Problem-Solving 101: A Simple Book for Smart People

Problem-Solving Takeaways

In summary, take note of these tips to become a better problem solver:

• Avoid the knee-jerk reaction. Take a moment before you jump to conclusions.
• Ask open-ended questions. Gather data and perspectives from everyone involved.
• Think and plan proactively. Apply crisis management principles to plan ahead.
• Stay open to feedback and ideas. Listen to different perspectives to think creatively.
• Get clear about what the problem is. Ask clarifying questions to identify the issue.
• Identify what needs to happen. Determine the ideal outcome or end goal.
• Identify the best players to solve the problem. Empower those who can make it happen.
• Create execution plans. A plan of action should be as clear as possible.
• Lead courageously and humbly. Don’t be afraid to face problems head-on.
• Train for the future. Get equipped to become a better problem solver.

For more support to become a better problem solver, check out our article How to Master Strategic Thinking Skills in 7 Simple Steps .

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Effective problem solving is all about using the right process and following a plan tailored to the issue at hand. Recognizing your team or organization has an issue isn’t enough to come up with effective problem solving strategies. 

To truly understand a problem and develop appropriate solutions, you will want to follow a solid process, follow the necessary problem solving steps, and bring all of your problem solving skills to the table.   We’ll forst look at what problem solving strategies you can employ with your team when looking for a way to approach the process. We’ll then discuss the problem solving skills you need to be more effective at solving problems, complete with an activity from the SessionLab library you can use to develop that skill in your team.

Let’s get to it! 

Problem solving strategies

What skills do i need to be an effective problem solver, how can i improve my problem solving skills.

Problem solving strategies are methods of approaching and facilitating the process of problem-solving with a set of techniques , actions, and processes. Different strategies are more effective if you are trying to solve broad problems such as achieving higher growth versus more focused problems like, how do we improve our customer onboarding process?

Broadly, the problem solving steps outlined above should be included in any problem solving strategy though choosing where to focus your time and what approaches should be taken is where they begin to differ. You might find that some strategies ask for the problem identification to be done prior to the session or that everything happens in the course of a one day workshop.

The key similarity is that all good problem solving strategies are structured and designed. Four hours of open discussion is never going to be as productive as a four-hour workshop designed to lead a group through a problem solving process.

Good problem solving strategies are tailored to the team, organization and problem you will be attempting to solve. Here are some example problem solving strategies you can learn from or use to get started.

Use a workshop to lead a team through a group process

Often, the first step to solving problems or organizational challenges is bringing a group together effectively. Most teams have the tools, knowledge, and expertise necessary to solve their challenges – they just need some guidance in how to use leverage those skills and a structure and format that allows people to focus their energies.

Facilitated workshops are one of the most effective ways of solving problems of any scale. By designing and planning your workshop carefully, you can tailor the approach and scope to best fit the needs of your team and organization. 

Problem solving workshop

• Creating a bespoke, tailored process
• Tackling problems of any size
• Building in-house workshop ability and encouraging their use

Workshops are an effective strategy for solving problems. By using tried and test facilitation techniques and methods, you can design and deliver a workshop that is perfectly suited to the unique variables of your organization. You may only have the capacity for a half-day workshop and so need a problem solving process to match. 

By using our session planner tool and importing methods from our library of 700+ facilitation techniques, you can create the right problem solving workshop for your team. It might be that you want to encourage creative thinking or look at things from a new angle to unblock your groups approach to problem solving. By tailoring your workshop design to the purpose, you can help ensure great results.

One of the main benefits of a workshop is the structured approach to problem solving. Not only does this mean that the workshop itself will be successful, but many of the methods and techniques will help your team improve their working processes outside of the workshop. 

We believe that workshops are one of the best tools you can use to improve the way your team works together. Start with a problem solving workshop and then see what team building, culture or design workshops can do for your organization!

Run a design sprint

Great for: 

• aligning large, multi-discipline teams
• quickly designing and testing solutions
• tackling large, complex organizational challenges and breaking them down into smaller tasks

By using design thinking principles and methods, a design sprint is a great way of identifying, prioritizing and prototyping solutions to long term challenges that can help solve major organizational problems with quick action and measurable results.

Some familiarity with design thinking is useful, though not integral, and this strategy can really help a team align if there is some discussion around which problems should be approached first. 

The stage-based structure of the design sprint is also very useful for teams new to design thinking.  The inspiration phase, where you look to competitors that have solved your problem, and the rapid prototyping and testing phases are great for introducing new concepts that will benefit a team in all their future work. 

It can be common for teams to look inward for solutions and so looking to the market for solutions you can iterate on can be very productive. Instilling an agile prototyping and testing mindset can also be great when helping teams move forwards – generating and testing solutions quickly can help save time in the long run and is also pretty exciting!

Break problems down into smaller issues

Organizational challenges and problems are often complicated and large scale in nature. Sometimes, trying to resolve such an issue in one swoop is simply unachievable or overwhelming. Try breaking down such problems into smaller issues that you can work on step by step. You may not be able to solve the problem of churning customers off the bat, but you can work with your team to identify smaller effort but high impact elements and work on those first.

This problem solving strategy can help a team generate momentum, prioritize and get some easy wins. It’s also a great strategy to employ with teams who are just beginning to learn how to approach the problem solving process. If you want some insight into a way to employ this strategy, we recommend looking at our design sprint template below!

Use guiding frameworks or try new methodologies

Some problems are best solved by introducing a major shift in perspective or by using new methodologies that encourage your team to think differently.

Props and tools such as Methodkit , which uses a card-based toolkit for facilitation, or Lego Serious Play can be great ways to engage your team and find an inclusive, democratic problem solving strategy. Remember that play and creativity are great tools for achieving change and whatever the challenge, engaging your participants can be very effective where other strategies may have failed.

LEGO Serious Play

• Improving core problem solving skills
• Thinking outside of the box
• Encouraging creative solutions

LEGO Serious Play is a problem solving methodology designed to get participants thinking differently by using 3D models and kinesthetic learning styles. By physically building LEGO models based on questions and exercises, participants are encouraged to think outside of the box and create their own responses. 

Collaborate LEGO Serious Play exercises are also used to encourage communication and build problem solving skills in a group. By using this problem solving process, you can often help different kinds of learners and personality types contribute and unblock organizational problems with creative thinking. 

Problem solving strategies like LEGO Serious Play are super effective at helping a team solve more skills-based problems such as communication between teams or a lack of creative thinking. Some problems are not suited to LEGO Serious Play and require a different problem solving strategy.

Card Decks and Method Kits

• New facilitators or non-facilitators 
• Approaching difficult subjects with a simple, creative framework
• Engaging those with varied learning styles

Card decks and method kids are great tools for those new to facilitation or for whom facilitation is not the primary role. Card decks such as the emotional culture deck can be used for complete workshops and in many cases, can be used right out of the box. Methodkit has a variety of kits designed for scenarios ranging from personal development through to personas and global challenges so you can find the right deck for your particular needs.

Having an easy to use framework that encourages creativity or a new approach can take some of the friction or planning difficulties out of the workshop process and energize a team in any setting. Simplicity is the key with these methods. By ensuring everyone on your team can get involved and engage with the process as quickly as possible can really contribute to the success of your problem solving strategy.

Source external advice

Looking to peers, experts and external facilitators can be a great way of approaching the problem solving process. Your team may not have the necessary expertise, insights of experience to tackle some issues, or you might simply benefit from a fresh perspective. Some problems may require bringing together an entire team, and coaching managers or team members individually might be the right approach. Remember that not all problems are best resolved in the same manner.

If you’re a solo entrepreneur, peer groups, coaches and mentors can also be invaluable at not only solving specific business problems, but in providing a support network for resolving future challenges. One great approach is to join a Mastermind Group and link up with like-minded individuals and all grow together. Remember that however you approach the sourcing of external advice, do so thoughtfully, respectfully and honestly. Reciprocate where you can and prepare to be surprised by just how kind and helpful your peers can be!

Mastermind Group

• Solo entrepreneurs or small teams with low capacity
• Peer learning and gaining outside expertise
• Getting multiple external points of view quickly

Problem solving in large organizations with lots of skilled team members is one thing, but how about if you work for yourself or in a very small team without the capacity to get the most from a design sprint or LEGO Serious Play session? 

A mastermind group – sometimes known as a peer advisory board – is where a group of people come together to support one another in their own goals, challenges, and businesses. Each participant comes to the group with their own purpose and the other members of the group will help them create solutions, brainstorm ideas, and support one another. 

Mastermind groups are very effective in creating an energized, supportive atmosphere that can deliver meaningful results. Learning from peers from outside of your organization or industry can really help unlock new ways of thinking and drive growth. Access to the experience and skills of your peers can be invaluable in helping fill the gaps in your own ability, particularly in young companies.

A mastermind group is a great solution for solo entrepreneurs, small teams, or for organizations that feel that external expertise or fresh perspectives will be beneficial for them. It is worth noting that Mastermind groups are often only as good as the participants and what they can bring to the group. Participants need to be committed, engaged and understand how to work in this context. 

Coaching and mentoring

• Focused learning and development
• Filling skills gaps
• Working on a range of challenges over time

Receiving advice from a business coach or building a mentor/mentee relationship can be an effective way of resolving certain challenges. The one-to-one format of most coaching and mentor relationships can really help solve the challenges those individuals are having and benefit the organization as a result.

A great mentor can be invaluable when it comes to spotting potential problems before they arise and coming to understand a mentee very well has a host of other business benefits. You might run an internal mentorship program to help develop your team’s problem solving skills and strategies or as part of a large learning and development program. External coaches can also be an important part of your problem solving strategy, filling skills gaps for your management team or helping with specific business issues. 

Now we’ve explored the problem solving process and the steps you will want to go through in order to have an effective session, let’s look at the skills you and your team need to be more effective problem solvers.

Problem solving skills are highly sought after, whatever industry or team you work in. Organizations are keen to employ people who are able to approach problems thoughtfully and find strong, realistic solutions. Whether you are a facilitator , a team leader or a developer, being an effective problem solver is a skill you’ll want to develop.

Problem solving skills form a whole suite of techniques and approaches that an individual uses to not only identify problems but to discuss them productively before then developing appropriate solutions.

Here are some of the most important problem solving skills everyone from executives to junior staff members should learn. We’ve also included an activity or exercise from the SessionLab library that can help you and your team develop that skill. 

If you’re running a workshop or training session to try and improve problem solving skills in your team, try using these methods to supercharge your process!

Active listening

Active listening is one of the most important skills anyone who works with people can possess. In short, active listening is a technique used to not only better understand what is being said by an individual, but also to be more aware of the underlying message the speaker is trying to convey. When it comes to problem solving, active listening is integral for understanding the position of every participant and to clarify the challenges, ideas and solutions they bring to the table.

Some active listening skills include:

• Paying complete attention to the speaker.
• Removing distractions.
• Avoid interruption.
• Taking the time to fully understand before preparing a rebuttal.
• Responding respectfully and appropriately.
• Demonstrate attentiveness and positivity with an open posture, making eye contact with the speaker, smiling and nodding if appropriate. Show that you are listening and encourage them to continue.
• Be aware of and respectful of feelings. Judge the situation and respond appropriately. You can disagree without being disrespectful.   
• Observe body language. 
• Paraphrase what was said in your own words, either mentally or verbally.
• Remain neutral. 
• Reflect and take a moment before responding.
• Ask deeper questions based on what is said and clarify points where necessary.   

Active Listening   #hyperisland   #skills   #active listening   #remote-friendly   This activity supports participants to reflect on a question and generate their own solutions using simple principles of active listening and peer coaching. It’s an excellent introduction to active listening but can also be used with groups that are already familiar with it. Participants work in groups of three and take turns being: “the subject”, the listener, and the observer.

Analytical skills

All problem solving models require strong analytical skills, particularly during the beginning of the process and when it comes to analyzing how solutions have performed.

Analytical skills are primarily focused on performing an effective analysis by collecting, studying and parsing data related to a problem or opportunity. 

It often involves spotting patterns, being able to see things from different perspectives and using observable facts and data to make suggestions or produce insight. 

Analytical skills are also important at every stage of the problem solving process and by having these skills, you can ensure that any ideas or solutions you create or backed up analytically and have been sufficiently thought out.

Nine Whys   #innovation   #issue analysis   #liberating structures   With breathtaking simplicity, you can rapidly clarify for individuals and a group what is essentially important in their work. You can quickly reveal when a compelling purpose is missing in a gathering and avoid moving forward without clarity. When a group discovers an unambiguous shared purpose, more freedom and more responsibility are unleashed. You have laid the foundation for spreading and scaling innovations with fidelity.

Collaboration

Trying to solve problems on your own is difficult. Being able to collaborate effectively, with a free exchange of ideas, to delegate and be a productive member of a team is hugely important to all problem solving strategies.

Remember that whatever your role, collaboration is integral, and in a problem solving process, you are all working together to find the best solution for everyone. 

Marshmallow challenge with debriefing   #teamwork   #team   #leadership   #collaboration   In eighteen minutes, teams must build the tallest free-standing structure out of 20 sticks of spaghetti, one yard of tape, one yard of string, and one marshmallow. The marshmallow needs to be on top. The Marshmallow Challenge was developed by Tom Wujec, who has done the activity with hundreds of groups around the world. Visit the Marshmallow Challenge website for more information. This version has an extra debriefing question added with sample questions focusing on roles within the team.

Communication  

Being an effective communicator means being empathetic, clear and succinct, asking the right questions, and demonstrating active listening skills throughout any discussion or meeting. 

In a problem solving setting, you need to communicate well in order to progress through each stage of the process effectively. As a team leader, it may also fall to you to facilitate communication between parties who may not see eye to eye. Effective communication also means helping others to express themselves and be heard in a group.

Bus Trip   #feedback   #communication   #appreciation   #closing   #thiagi   #team   This is one of my favourite feedback games. I use Bus Trip at the end of a training session or a meeting, and I use it all the time. The game creates a massive amount of energy with lots of smiles, laughs, and sometimes even a teardrop or two.

Creative problem solving skills can be some of the best tools in your arsenal. Thinking creatively, being able to generate lots of ideas and come up with out of the box solutions is useful at every step of the process. 

The kinds of problems you will likely discuss in a problem solving workshop are often difficult to solve, and by approaching things in a fresh, creative manner, you can often create more innovative solutions.

Having practical creative skills is also a boon when it comes to problem solving. If you can help create quality design sketches and prototypes in record time, it can help bring a team to alignment more quickly or provide a base for further iteration.

The paper clip method   #sharing   #creativity   #warm up   #idea generation   #brainstorming   The power of brainstorming. A training for project leaders, creativity training, and to catalyse getting new solutions.

Critical thinking

Critical thinking is one of the fundamental problem solving skills you’ll want to develop when working on developing solutions. Critical thinking is the ability to analyze, rationalize and evaluate while being aware of personal bias, outlying factors and remaining open-minded.

Defining and analyzing problems without deploying critical thinking skills can mean you and your team go down the wrong path. Developing solutions to complex issues requires critical thinking too – ensuring your team considers all possibilities and rationally evaluating them. 

Agreement-Certainty Matrix   #issue analysis   #liberating structures   #problem solving   You can help individuals or groups avoid the frequent mistake of trying to solve a problem with methods that are not adapted to the nature of their challenge. The combination of two questions makes it possible to easily sort challenges into four categories: simple, complicated, complex , and chaotic .  A problem is simple when it can be solved reliably with practices that are easy to duplicate.  It is complicated when experts are required to devise a sophisticated solution that will yield the desired results predictably.  A problem is complex when there are several valid ways to proceed but outcomes are not predictable in detail.  Chaotic is when the context is too turbulent to identify a path forward.  A loose analogy may be used to describe these differences: simple is like following a recipe, complicated like sending a rocket to the moon, complex like raising a child, and chaotic is like the game “Pin the Tail on the Donkey.”  The Liberating Structures Matching Matrix in Chapter 5 can be used as the first step to clarify the nature of a challenge and avoid the mismatches between problems and solutions that are frequently at the root of chronic, recurring problems.

Data analysis 

Though it shares lots of space with general analytical skills, data analysis skills are something you want to cultivate in their own right in order to be an effective problem solver.

Being good at data analysis doesn’t just mean being able to find insights from data, but also selecting the appropriate data for a given issue, interpreting it effectively and knowing how to model and present that data. Depending on the problem at hand, it might also include a working knowledge of specific data analysis tools and procedures. 

Having a solid grasp of data analysis techniques is useful if you’re leading a problem solving workshop but if you’re not an expert, don’t worry. Bring people into the group who has this skill set and help your team be more effective as a result.

Decision making

All problems need a solution and all solutions require that someone make the decision to implement them. Without strong decision making skills, teams can become bogged down in discussion and less effective as a result. 

Making decisions is a key part of the problem solving process. It’s important to remember that decision making is not restricted to the leadership team. Every staff member makes decisions every day and developing these skills ensures that your team is able to solve problems at any scale. Remember that making decisions does not mean leaping to the first solution but weighing up the options and coming to an informed, well thought out solution to any given problem that works for the whole team.

Lightning Decision Jam (LDJ)   #action   #decision making   #problem solving   #issue analysis   #innovation   #design   #remote-friendly   The problem with anything that requires creative thinking is that it’s easy to get lost—lose focus and fall into the trap of having useless, open-ended, unstructured discussions. Here’s the most effective solution I’ve found: Replace all open, unstructured discussion with a clear process. What to use this exercise for: Anything which requires a group of people to make decisions, solve problems or discuss challenges. It’s always good to frame an LDJ session with a broad topic, here are some examples: The conversion flow of our checkout Our internal design process How we organise events Keeping up with our competition Improving sales flow

Dependability

Most complex organizational problems require multiple people to be involved in delivering the solution. Ensuring that the team and organization can depend on you to take the necessary actions and communicate where necessary is key to ensuring problems are solved effectively.

Being dependable also means working to deadlines and to brief. It is often a matter of creating trust in a team so that everyone can depend on one another to complete the agreed actions in the agreed time frame so that the team can move forward together. Being undependable can create problems of friction and can limit the effectiveness of your solutions so be sure to bear this in mind throughout a project. 

Team Purpose & Culture   #team   #hyperisland   #culture   #remote-friendly   This is an essential process designed to help teams define their purpose (why they exist) and their culture (how they work together to achieve that purpose). Defining these two things will help any team to be more focused and aligned. With support of tangible examples from other companies, the team members work as individuals and a group to codify the way they work together. The goal is a visual manifestation of both the purpose and culture that can be put up in the team’s work space.

Emotional intelligence

Emotional intelligence is an important skill for any successful team member, whether communicating internally or with clients or users. In the problem solving process, emotional intelligence means being attuned to how people are feeling and thinking, communicating effectively and being self-aware of what you bring to a room. 

There are often differences of opinion when working through problem solving processes, and it can be easy to let things become impassioned or combative. Developing your emotional intelligence means being empathetic to your colleagues and managing your own emotions throughout the problem and solution process. Be kind, be thoughtful and put your points across care and attention. 

Being emotionally intelligent is a skill for life and by deploying it at work, you can not only work efficiently but empathetically. Check out the emotional culture workshop template for more!

Facilitation

As we’ve clarified in our facilitation skills post, facilitation is the art of leading people through processes towards agreed-upon objectives in a manner that encourages participation, ownership, and creativity by all those involved. While facilitation is a set of interrelated skills in itself, the broad definition of facilitation can be invaluable when it comes to problem solving. Leading a team through a problem solving process is made more effective if you improve and utilize facilitation skills – whether you’re a manager, team leader or external stakeholder.

The Six Thinking Hats   #creative thinking   #meeting facilitation   #problem solving   #issue resolution   #idea generation   #conflict resolution   The Six Thinking Hats are used by individuals and groups to separate out conflicting styles of thinking. They enable and encourage a group of people to think constructively together in exploring and implementing change, rather than using argument to fight over who is right and who is wrong.

Flexibility 

Being flexible is a vital skill when it comes to problem solving. This does not mean immediately bowing to pressure or changing your opinion quickly: instead, being flexible is all about seeing things from new perspectives, receiving new information and factoring it into your thought process.

Flexibility is also important when it comes to rolling out solutions. It might be that other organizational projects have greater priority or require the same resources as your chosen solution. Being flexible means understanding needs and challenges across the team and being open to shifting or arranging your own schedule as necessary. Again, this does not mean immediately making way for other projects. It’s about articulating your own needs, understanding the needs of others and being able to come to a meaningful compromise.

The Creativity Dice   #creativity   #problem solving   #thiagi   #issue analysis   Too much linear thinking is hazardous to creative problem solving. To be creative, you should approach the problem (or the opportunity) from different points of view. You should leave a thought hanging in mid-air and move to another. This skipping around prevents premature closure and lets your brain incubate one line of thought while you consciously pursue another.

Working in any group can lead to unconscious elements of groupthink or situations in which you may not wish to be entirely honest. Disagreeing with the opinions of the executive team or wishing to save the feelings of a coworker can be tricky to navigate, but being honest is absolutely vital when to comes to developing effective solutions and ensuring your voice is heard. 

Remember that being honest does not mean being brutally candid. You can deliver your honest feedback and opinions thoughtfully and without creating friction by using other skills such as emotional intelligence. 

Explore your Values   #hyperisland   #skills   #values   #remote-friendly   Your Values is an exercise for participants to explore what their most important values are. It’s done in an intuitive and rapid way to encourage participants to follow their intuitive feeling rather than over-thinking and finding the “correct” values. It is a good exercise to use to initiate reflection and dialogue around personal values.

Initiative 

The problem solving process is multi-faceted and requires different approaches at certain points of the process. Taking initiative to bring problems to the attention of the team, collect data or lead the solution creating process is always valuable. You might even roadtest your own small scale solutions or brainstorm before a session. Taking initiative is particularly effective if you have good deal of knowledge in that area or have ownership of a particular project and want to get things kickstarted.

That said, be sure to remember to honor the process and work in service of the team. If you are asked to own one part of the problem solving process and you don’t complete that task because your initiative leads you to work on something else, that’s not an effective method of solving business challenges.

15% Solutions   #action   #liberating structures   #remote-friendly   You can reveal the actions, however small, that everyone can do immediately. At a minimum, these will create momentum, and that may make a BIG difference.  15% Solutions show that there is no reason to wait around, feel powerless, or fearful. They help people pick it up a level. They get individuals and the group to focus on what is within their discretion instead of what they cannot change.  With a very simple question, you can flip the conversation to what can be done and find solutions to big problems that are often distributed widely in places not known in advance. Shifting a few grains of sand may trigger a landslide and change the whole landscape.

Impartiality

A particularly useful problem solving skill for product owners or managers is the ability to remain impartial throughout much of the process. In practice, this means treating all points of view and ideas brought forward in a meeting equally and ensuring that your own areas of interest or ownership are not favored over others. 

There may be a stage in the process where a decision maker has to weigh the cost and ROI of possible solutions against the company roadmap though even then, ensuring that the decision made is based on merit and not personal opinion. 

Empathy map   #frame insights   #create   #design   #issue analysis   An empathy map is a tool to help a design team to empathize with the people they are designing for. You can make an empathy map for a group of people or for a persona. To be used after doing personas when more insights are needed.

Being a good leader means getting a team aligned, energized and focused around a common goal. In the problem solving process, strong leadership helps ensure that the process is efficient, that any conflicts are resolved and that a team is managed in the direction of success.

It’s common for managers or executives to assume this role in a problem solving workshop, though it’s important that the leader maintains impartiality and does not bulldoze the group in a particular direction. Remember that good leadership means working in service of the purpose and team and ensuring the workshop is a safe space for employees of any level to contribute. Take a look at our leadership games and activities post for more exercises and methods to help improve leadership in your organization.

Leadership Pizza   #leadership   #team   #remote-friendly   This leadership development activity offers a self-assessment framework for people to first identify what skills, attributes and attitudes they find important for effective leadership, and then assess their own development and initiate goal setting.

In the context of problem solving, mediation is important in keeping a team engaged, happy and free of conflict. When leading or facilitating a problem solving workshop, you are likely to run into differences of opinion. Depending on the nature of the problem, certain issues may be brought up that are emotive in nature. 

Being an effective mediator means helping those people on either side of such a divide are heard, listen to one another and encouraged to find common ground and a resolution. Mediating skills are useful for leaders and managers in many situations and the problem solving process is no different.

Conflict Responses   #hyperisland   #team   #issue resolution   A workshop for a team to reflect on past conflicts, and use them to generate guidelines for effective conflict handling. The workshop uses the Thomas-Killman model of conflict responses to frame a reflective discussion. Use it to open up a discussion around conflict with a team.

Planning 

Solving organizational problems is much more effective when following a process or problem solving model. Planning skills are vital in order to structure, deliver and follow-through on a problem solving workshop and ensure your solutions are intelligently deployed.

Planning skills include the ability to organize tasks and a team, plan and design the process and take into account any potential challenges. Taking the time to plan carefully can save time and frustration later in the process and is valuable for ensuring a team is positioned for success.

3 Action Steps   #hyperisland   #action   #remote-friendly   This is a small-scale strategic planning session that helps groups and individuals to take action toward a desired change. It is often used at the end of a workshop or programme. The group discusses and agrees on a vision, then creates some action steps that will lead them towards that vision. The scope of the challenge is also defined, through discussion of the helpful and harmful factors influencing the group.

Prioritization

As organisations grow, the scale and variation of problems they face multiplies. Your team or is likely to face numerous challenges in different areas and so having the skills to analyze and prioritize becomes very important, particularly for those in leadership roles.

A thorough problem solving process is likely to deliver multiple solutions and you may have several different problems you wish to solve simultaneously. Prioritization is the ability to measure the importance, value, and effectiveness of those possible solutions and choose which to enact and in what order. The process of prioritization is integral in ensuring the biggest challenges are addressed with the most impactful solutions.

Impact and Effort Matrix   #gamestorming   #decision making   #action   #remote-friendly   In this decision-making exercise, possible actions are mapped based on two factors: effort required to implement and potential impact. Categorizing ideas along these lines is a useful technique in decision making, as it obliges contributors to balance and evaluate suggested actions before committing to them.

Project management

Some problem solving skills are utilized in a workshop or ideation phases, while others come in useful when it comes to decision making. Overseeing an entire problem solving process and ensuring its success requires strong project management skills. 

While project management incorporates many of the other skills listed here, it is important to note the distinction of considering all of the factors of a project and managing them successfully. Being able to negotiate with stakeholders, manage tasks, time and people, consider costs and ROI, and tie everything together is massively helpful when going through the problem solving process. 

Record keeping

Working out meaningful solutions to organizational challenges is only one part of the process.  Thoughtfully documenting and keeping records of each problem solving step for future consultation is important in ensuring efficiency and meaningful change. 

For example, some problems may be lower priority than others but can be revisited in the future. If the team has ideated on solutions and found some are not up to the task, record those so you can rule them out and avoiding repeating work. Keeping records of the process also helps you improve and refine your problem solving model next time around!

Personal Kanban   #gamestorming   #action   #agile   #project planning   Personal Kanban is a tool for organizing your work to be more efficient and productive. It is based on agile methods and principles.

Research skills

Conducting research to support both the identification of problems and the development of appropriate solutions is important for an effective process. Knowing where to go to collect research, how to conduct research efficiently, and identifying pieces of research are relevant are all things a good researcher can do well. 

In larger groups, not everyone has to demonstrate this ability in order for a problem solving workshop to be effective. That said, having people with research skills involved in the process, particularly if they have existing area knowledge, can help ensure the solutions that are developed with data that supports their intention. Remember that being able to deliver the results of research efficiently and in a way the team can easily understand is also important. The best data in the world is only as effective as how it is delivered and interpreted.

Customer experience map   #ideation   #concepts   #research   #design   #issue analysis   #remote-friendly   Customer experience mapping is a method of documenting and visualizing the experience a customer has as they use the product or service. It also maps out their responses to their experiences. To be used when there is a solution (even in a conceptual stage) that can be analyzed.

Risk management

Managing risk is an often overlooked part of the problem solving process. Solutions are often developed with the intention of reducing exposure to risk or solving issues that create risk but sometimes, great solutions are more experimental in nature and as such, deploying them needs to be carefully considered. 

Managing risk means acknowledging that there may be risks associated with more out of the box solutions or trying new things, but that this must be measured against the possible benefits and other organizational factors. 

Be informed, get the right data and stakeholders in the room and you can appropriately factor risk into your decision making process. 

Decisions, Decisions…   #communication   #decision making   #thiagi   #action   #issue analysis   When it comes to decision-making, why are some of us more prone to take risks while others are risk-averse? One explanation might be the way the decision and options were presented.  This exercise, based on Kahneman and Tversky’s classic study , illustrates how the framing effect influences our judgement and our ability to make decisions . The participants are divided into two groups. Both groups are presented with the same problem and two alternative programs for solving them. The two programs both have the same consequences but are presented differently. The debriefing discussion examines how the framing of the program impacted the participant’s decision.

Team-building 

No single person is as good at problem solving as a team. Building an effective team and helping them come together around a common purpose is one of the most important problem solving skills, doubly so for leaders. By bringing a team together and helping them work efficiently, you pave the way for team ownership of a problem and the development of effective solutions. 

In a problem solving workshop, it can be tempting to jump right into the deep end, though taking the time to break the ice, energize the team and align them with a game or exercise will pay off over the course of the day.

Remember that you will likely go through the problem solving process multiple times over an organization’s lifespan and building a strong team culture will make future problem solving more effective. It’s also great to work with people you know, trust and have fun with. Working on team building in and out of the problem solving process is a hallmark of successful teams that can work together to solve business problems.

9 Dimensions Team Building Activity   #ice breaker   #teambuilding   #team   #remote-friendly   9 Dimensions is a powerful activity designed to build relationships and trust among team members. There are 2 variations of this icebreaker. The first version is for teams who want to get to know each other better. The second version is for teams who want to explore how they are working together as a team.

Time management 

The problem solving process is designed to lead a team from identifying a problem through to delivering a solution and evaluating its effectiveness. Without effective time management skills or timeboxing of tasks, it can be easy for a team to get bogged down or be inefficient.

By using a problem solving model and carefully designing your workshop, you can allocate time efficiently and trust that the process will deliver the results you need in a good timeframe.

Time management also comes into play when it comes to rolling out solutions, particularly those that are experimental in nature. Having a clear timeframe for implementing and evaluating solutions is vital for ensuring their success and being able to pivot if necessary.

Improving your skills at problem solving is often a career-long pursuit though there are methods you can use to make the learning process more efficient and to supercharge your problem solving skillset.

Remember that the skills you need to be a great problem solver have a large overlap with those skills you need to be effective in any role. Investing time and effort to develop your active listening or critical thinking skills is valuable in any context. Here are 7 ways to improve your problem solving skills.

Share best practices

Remember that your team is an excellent source of skills, wisdom, and techniques and that you should all take advantage of one another where possible. Best practices that one team has for solving problems, conducting research or making decisions should be shared across the organization. If you have in-house staff that have done active listening training or are data analysis pros, have them lead a training session. 

Your team is one of your best resources. Create space and internal processes for the sharing of skills so that you can all grow together. 

Ask for help and attend training

Once you’ve figured out you have a skills gap, the next step is to take action to fill that skills gap. That might be by asking your superior for training or coaching, or liaising with team members with that skill set. You might even attend specialized training for certain skills – active listening or critical thinking, for example, are business-critical skills that are regularly offered as part of a training scheme.

Whatever method you choose, remember that taking action of some description is necessary for growth. Whether that means practicing, getting help, attending training or doing some background reading, taking active steps to improve your skills is the way to go.

Learn a process 

Problem solving can be complicated, particularly when attempting to solve large problems for the first time. Using a problem solving process helps give structure to your problem solving efforts and focus on creating outcomes, rather than worrying about the format. 

Tools such as the seven-step problem solving process above are effective because not only do they feature steps that will help a team solve problems, they also develop skills along the way. Each step asks for people to engage with the process using different skills and in doing so, helps the team learn and grow together. Group processes of varying complexity and purpose can also be found in the SessionLab library of facilitation techniques . Using a tried and tested process and really help ease the learning curve for both those leading such a process, as well as those undergoing the purpose.

Effective teams make decisions about where they should and shouldn’t expend additional effort. By using a problem solving process, you can focus on the things that matter, rather than stumbling towards a solution haphazardly. 

Create a feedback loop

Some skills gaps are more obvious than others. It’s possible that your perception of your active listening skills differs from those of your colleagues. 

It’s valuable to create a system where team members can provide feedback in an ordered and friendly manner so they can all learn from one another. Only by identifying areas of improvement can you then work to improve them. 

Remember that feedback systems require oversight and consideration so that they don’t turn into a place to complain about colleagues. Design the system intelligently so that you encourage the creation of learning opportunities, rather than encouraging people to list their pet peeves.

While practice might not make perfect, it does make the problem solving process easier. If you are having trouble with critical thinking, don’t shy away from doing it. Get involved where you can and stretch those muscles as regularly as possible. 

Problem solving skills come more naturally to some than to others and that’s okay. Take opportunities to get involved and see where you can practice your skills in situations outside of a workshop context. Try collaborating in other circumstances at work or conduct data analysis on your own projects. You can often develop those skills you need for problem solving simply by doing them. Get involved!

Use expert exercises and methods

Learn from the best. Our library of 700+ facilitation techniques is full of activities and methods that help develop the skills you need to be an effective problem solver. Check out our templates to see how to approach problem solving and other organizational challenges in a structured and intelligent manner.

There is no single approach to improving problem solving skills, but by using the techniques employed by others you can learn from their example and develop processes that have seen proven results. 

Try new ways of thinking and change your mindset

Using tried and tested exercises that you know well can help deliver results, but you do run the risk of missing out on the learning opportunities offered by new approaches. As with the problem solving process, changing your mindset can remove blockages and be used to develop your problem solving skills.

Most teams have members with mixed skill sets and specialties. Mix people from different teams and share skills and different points of view. Teach your customer support team how to use design thinking methods or help your developers with conflict resolution techniques. Try switching perspectives with facilitation techniques like Flip It! or by using new problem solving methodologies or models. Give design thinking, liberating structures or lego serious play a try if you want to try a new approach. You will find that framing problems in new ways and using existing skills in new contexts can be hugely useful for personal development and improving your skillset. It’s also a lot of fun to try new things. Give it a go!

Encountering business challenges and needing to find appropriate solutions is not unique to your organization. Lots of very smart people have developed methods, theories and approaches to help develop problem solving skills and create effective solutions. Learn from them!

Books like The Art of Thinking Clearly , Think Smarter, or Thinking Fast, Thinking Slow are great places to start, though it’s also worth looking at blogs related to organizations facing similar problems to yours, or browsing for success stories. Seeing how Dropbox massively increased growth and working backward can help you see the skills or approach you might be lacking to solve that same problem. Learning from others by reading their stories or approaches can be time-consuming but ultimately rewarding.

A tired, distracted mind is not in the best position to learn new skills. It can be tempted to burn the candle at both ends and develop problem solving skills outside of work. Absolutely use your time effectively and take opportunities for self-improvement, though remember that rest is hugely important and that without letting your brain rest, you cannot be at your most effective. 

Creating distance between yourself and the problem you might be facing can also be useful. By letting an idea sit, you can find that a better one presents itself or you can develop it further. Take regular breaks when working and create a space for downtime. Remember that working smarter is preferable to working harder and that self-care is important for any effective learning or improvement process.

Want to design better group processes?

Over to you

Now we’ve explored some of the key problem solving skills and the problem solving steps necessary for an effective process, you’re ready to begin developing more effective solutions and leading problem solving workshops.

Need more inspiration? Check out our post on problem solving activities you can use when guiding a group towards a great solution in your next workshop or meeting. Have questions? Did you have a great problem solving technique you use with your team? Get in touch in the comments below. We’d love to chat!

James Smart is Head of Content at SessionLab. He’s also a creative facilitator who has run workshops and designed courses for establishments like the National Centre for Writing, UK. He especially enjoys working with young people and empowering others in their creative practice.

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How to master the seven-step problem-solving process

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

Podcast transcript

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

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

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

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

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

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

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

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

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

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

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

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Simon London: So this is a concise problem statement.

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

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

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

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Both: Yeah.

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

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

Simon London: Right. Right.

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

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

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

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

Simon London: Would you agree with that?

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

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

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

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

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

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

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

Charles Conn: Yeah.

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

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

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

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

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

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

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

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

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

Hugo Sarrazin: Every step of the process.

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

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

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

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

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

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

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

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

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

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

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

Hugo Sarrazin: Absolutely.

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

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

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

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

Hugo Sarrazin: It was a pleasure. Thank you.

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

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

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How to Solve Problems

• Laura Amico

To bring the best ideas forward, teams must build psychological safety.

Teams today aren’t just asked to execute tasks: They’re called upon to solve problems. You’d think that many brains working together would mean better solutions, but the reality is that too often problem-solving teams fall victim to inefficiency, conflict, and cautious conclusions. The two charts below will help your team think about how to collaborate better and come up with the best solutions for the thorniest challenges.

• Laura Amico is a former senior editor at Harvard Business Review.

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4 Main problem-solving strategies

In Psychology, you get to read about a ton of therapies. It’s mind-boggling how different theorists have looked at human nature differently and have come up with different, often somewhat contradictory, theoretical approaches.

Yet, you can’t deny the kernel of truth that’s there in all of them. All therapies, despite being different, have one thing in common- they all aim to solve people’s problems. They all aim to equip people with problem-solving strategies to help them deal with their life problems.

Problem-solving is really at the core of everything we do. Throughout our lives, we’re constantly trying to solve one problem or another. When we can’t, all sorts of psychological problems take hold. Getting good at solving problems is a fundamental life skill.

Problem-solving stages

What problem-solving does is take you from an initial state (A) where a problem exists to a final or goal state (B), where the problem no longer exists.

To move from A to B, you need to perform some actions called operators. Engaging in the right operators moves you from A to B. So, the stages of problem-solving are:

• Initial state

The problem itself can either be well-defined or ill-defined. A well-defined problem is one where you can clearly see where you are (A), where you want to go (B), and what you need to do to get there (engaging the right operators).

For example, feeling hungry and wanting to eat can be seen as a problem, albeit a simple one for many. Your initial state is hunger (A) and your final state is satisfaction or no hunger (B). Going to the kitchen and finding something to eat is using the right operator.

In contrast, ill-defined or complex problems are those where one or more of the three problem solving stages aren’t clear. For example, if your goal is to bring about world peace, what is it exactly that you want to do?

It’s been rightly said that a problem well-defined is a problem half-solved. Whenever you face an ill-defined problem, the first thing you need to do is get clear about all the three stages.

Often, people will have a decent idea of where they are (A) and where they want to be (B). What they usually get stuck on is finding the right operators.

Initial theory in problem-solving

When people first attempt to solve a problem, i.e. when they first engage their operators, they often have an initial theory of solving the problem. As I mentioned in my article on overcoming challenges for complex problems, this initial theory is often wrong.

But, at the time, it’s usually the result of the best information the individual can gather about the problem. When this initial theory fails, the problem-solver gets more data, and he refines the theory. Eventually, he finds an actual theory i.e. a theory that works. This finally allows him to engage the right operators to move from A to B.

Problem-solving strategies

These are operators that a problem solver tries to move from A to B. There are several problem-solving strategies but the main ones are:

• Trial and error

1. Algorithms

When you follow a step-by-step procedure to solve a problem or reach a goal, you’re using an algorithm. If you follow the steps exactly, you’re guaranteed to find the solution. The drawback of this strategy is that it can get cumbersome and time-consuming for large problems.

Say I hand you a 200-page book and ask you to read out to me what’s written on page 100. If you start from page 1 and keep turning the pages, you’ll eventually reach page 100. There’s no question about it. But the process is time-consuming. So instead you use what’s called a heuristic.

2. Heuristics

Heuristics are rules of thumb that people use to simplify problems. They’re often based on memories from past experiences. They cut down the number of steps needed to solve a problem, but they don’t always guarantee a solution. Heuristics save us time and effort if they work.

You know that page 100 lies in the middle of the book. Instead of starting from page one, you try to open the book in the middle. Of course, you may not hit page 100, but you can get really close with just a couple of tries.

If you open page 90, for instance, you can then algorithmically move from 90 to 100. Thus, you can use a combination of heuristics and algorithms to solve the problem. In real life, we often solve problems like this.

When police are looking for suspects in an investigation, they try to narrow down the problem similarly. Knowing the suspect is 6 feet tall isn’t enough, as there could be thousands of people out there with that height.

Knowing the suspect is 6 feet tall, male, wears glasses, and has blond hair narrows down the problem significantly.

3. Trial and error

When you have an initial theory to solve a problem, you try it out. If you fail, you refine or change your theory and try again. This is the trial-and-error process of solving problems. Behavioral and cognitive trial and error often go hand in hand, but for many problems, we start with behavioural trial and error until we’re forced to think.

Say you’re in a maze, trying to find your way out. You try one route without giving it much thought and you find it leads to nowhere. Then you try another route and fail again. This is behavioural trial and error because you aren’t putting any thought into your trials. You’re just throwing things at the wall to see what sticks.

This isn’t an ideal strategy but can be useful in situations where it’s impossible to get any information about the problem without doing some trials.

Then, when you have enough information about the problem, you shuffle that information in your mind to find a solution. This is cognitive trial and error or analytical thinking. Behavioral trial and error can take a lot of time, so using cognitive trial and error as much as possible is advisable. You got to sharpen your axe before you cut the tree.

When solving complex problems, people get frustrated after having tried several operators that didn’t work. They abandon their problem and go on with their routine activities. Suddenly, they get a flash of insight that makes them confident they can now solve the problem.

I’ve done an entire article on the underlying mechanics of insight . Long story short, when you take a step back from your problem, it helps you see things in a new light. You make use of associations that were previously unavailable to you.

You get more puzzle pieces to work with and this increases the odds of you finding a path from A to B, i.e. finding operators that work.

Pilot problem-solving

No matter what problem-solving strategy you employ, it’s all about finding out what works. Your actual theory tells you what operators will take you from A to B. Complex problems don’t reveal their actual theories easily solely because they are complex.

Therefore, the first step to solving a complex problem is getting as clear as you can about what you’re trying to accomplish- collecting as much information as you can about the problem.

This gives you enough raw materials to formulate an initial theory. We want our initial theory to be as close to an actual theory as possible. This saves time and resources.

Solving a complex problem can mean investing a lot of resources. Therefore, it is recommended you verify your initial theory if you can. I call this pilot problem-solving.

Before businesses invest in making a product, they sometimes distribute free versions to a small sample of potential customers to ensure their target audience will be receptive to the product.

Before making a series of TV episodes, TV show producers often release pilot episodes to figure out whether the show can take off.

Before conducting a large study, researchers do a pilot study to survey a small sample of the population to determine if the study is worth carrying out.

The same ‘testing the waters’ approach needs to be applied to solving any complex problem you might be facing. Is your problem worth investing a lot of resources in? In management, we’re constantly taught about Return On Investment (ROI). The ROI should justify the investment.

If the answer is yes, go ahead and formulate your initial theory based on extensive research. Find a way to verify your initial theory. You need this reassurance that you’re going in the right direction, especially for complex problems that take a long time to solve.

Getting your causal thinking right

Problem solving boils down to getting your causal thinking right. Finding solutions is all about finding out what works, i.e. finding operators that take you from A to B. To succeed, you need to be confident in your initial theory (If I do X and Y, they’ll lead me to B). You need to be sure that doing X and Y will lead you to B- doing X and Y will cause B.

All obstacles to problem-solving or goal-accomplishing are rooted in faulty causal thinking leading to not engaging the right operators. When your causal thinking is on point, you’ll have no problem engaging the right operators.

As you can imagine, for complex problems, getting our causal thinking right isn’t easy. That’s why we need to formulate an initial theory and refine it over time.

I like to think of problem-solving as the ability to project the present into the past or into the future. When you’re solving problems, you’re basically looking at your present situation and asking yourself two questions:

“What caused this?” (Projecting present into the past)

“What will this cause?” (Projecting present into the future)

The first question is more relevant to problem-solving and the second to goal-accomplishing.

If you find yourself in a mess , you need to answer the “What caused this?” question correctly. For the operators you’re currently engaging to reach your goal, ask yourself, “What will this cause?” If you think they cannot cause B, it’s time to refine your initial theory.

Hi, I’m Hanan Parvez (MA Psychology). I’ve published over 500 articles and authored one book. My work has been featured in Forbes , Business Insider , Reader’s Digest , and Entrepreneur .

How to Write a Problem Statement: Guide for Project Success

A clear problem statement is crucial for project success. It should describe the issue , its impact , and context without proposing solutions. Craft a concise statement that aligns stakeholders and guides research . Regularly review your problem statement to ensure solutions address the core issue .

Many people struggle to explain problems at work or in research projects. Research indicates that over two-thirds of projects don't succeed because the initial problem statement isn't clearly defined. Here, you'll learn how to create strong problem statements , setting your projects up for success from the start.

Every successful project or study relies on a clear explanation of the issue at hand. It guides teams toward a shared goal and prevents solving the wrong problem. A problem statement briefly describes an issue that needs fixing. It describes the present circumstances, the intended result, and the difference between them . It provides a brief overview of the issue without proposing any fixes.

Why Well-Crafted Problem Statements Matter

Defining a problem statement.

For example, a healthcare project's problem statement might be:

"In 2019, late filing caused 61.6% of denied insurance claims, leading to $7.8 million in lost profit."

This explanation highlights the problem , its effects, and paves the way for further investigation.

The Importance of Problem Statements

Problem statements serve a crucial purpose beyond mere procedure. They serve several important functions:

• Alignment : They make sure all stakeholders work towards the same goal.
• Focus : By clearly defining the problem, teams can avoid getting distracted by symptoms instead of addressing root causes.
• Prioritization : Measuring a problem's impact helps in ranking issues and using resources well.

"If I had an hour to solve a problem I'd spend 55 minutes thinking about the problem and five minutes thinking about solutions." — Albert Einstein

Einstein believed that most of the time spent solving a problem should be used to understand it, with only a small portion dedicated to finding solutions. Grasping the issue fully is crucial before attempting to resolve it.

Crafting a Clear Problem Statement

Having covered the importance of problem statements, we'll now explore techniques for developing one that boosts your project's chances of success.

Essential Elements of a Robust Problem Statement

An effective problem statement needs to have these parts:

• Explanation of the issue : It must be easy to grasp, precise, and free from confusion.
• How the issue affects things : When you can, use figures to show the scale of the problem.
• Context : Provide context to ensure readers grasp the full picture.
• Stakeholders : Specify the people impacted by the issue.
• Timeframe : Pinpoint when the issue first arose and its frequency.

Keep in mind, an effective problem statement is brief (typically two sentences max) and immediately captures the reader's interest. It should inspire and motivate without suggesting a specific solution.

Key Errors to Steer Clear Of

Despite good aims, people often make errors when describing problems. Watch out for these frequent mistakes:

• Addressing surface issues rather than underlying reasons : Dig deeper to uncover the true problems.
• Including solutions : A problem statement should explain the issue, not suggest solutions.
• Blaming others : Focus on the main issue, avoiding personal or departmental references in your statement.

Crafting a clear problem statement without these errors will set a strong foundation for your work.

Moving from Identifying the Problem to Taking Steps

An effective problem statement is only the beginning. True advancement occurs when you apply the statement to achieve concrete outcomes.

Letting Your Problem Statement Direct Your Investigation

A well-defined problem statement can act as a roadmap for your study or project . It assists you in:

• Find key areas to study : The elements of your problem statement point to areas where you need more information.
• Create research questions : These inquiries will help you explore the issue and its origins in greater depth.
• Choose the right methods : The nature of the issue will point you to the most suitable investigation techniques.

Keep in mind that your problem statement may evolve. Your understanding might grow, requiring adjustments to the statement . This back-and-forth process is normal and useful in research.

Turning Your Problem Statement into Solutions

While your problem statement shouldn't include solutions, it's the starting point for finding them. Here's a way to move forward:

• Brainstorming : Let your problem statement inspire new thoughts and concepts.
• Evaluation : Compare possible answers with the requirements in your problem statement.
• Implementation : Regularly review your problem outline to ensure your selected fix truly addresses the core issue.

Constantly checking your problem statement during problem-solving keeps your work targeted and aligned with your initial aims.

Problem Framing: Your Key to Success

Writing effective problem statements is a skill that can greatly improve the success rate of your projects and research. Clearly stating the problem paves the way for fresh ideas and valuable outcomes.

A good problem statement acts as your roadmap, guiding you through the tricky steps of solving issues. When you encounter a difficult situation, pause and consider if you've truly understood what the issue is. This approach will help you see things more clearly and know what to do next.

Which problem are you going to look at differently today?

How to Write a Scope of Work: Examples and Best Practices

Project Management Goals Boost Success with SMART Objectives

How to use the 1-3-1 rule for effective team problem-solving

How to minimize confusion in the workplace with clear communication and teamwork

Planning Goals 7 Steps to Achieve Success in Life and Work

10 Best Practices for Effective Brainstorming Sessions

Strategic Planning: Guide Your Company to Success

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How to Teach Problem-Solving Skills to Children and Preteens

• By Ashley Cullins

Whether it’s a toy-related conflict, a tough math equation, or negative peer pressure, kids of ALL ages face problems and challenges on a daily basis.

As parents or teachers, we can’t always be there to solve every problem for our children. In fact, this isn’t our job. Our job is to TEACH our children how to solve problems by themselves . This way, they can become confident , independent, and successful individuals.

Instead of giving up or getting frustrated when they encounter a challenge, kids with problem-solving skills manage their emotions, think creatively, and persist until they find a solution. Naturally, these abilities go hand-in-hand with a  growth mindset .

Before you continue, we thought you might like to download our FREE Your Words Matter Volume 2 Kit . With these 10 one-page parenting guides, you will know exactly how to speak to your child to help them stand up for themselves, be more confident, and develop a growth mindset.

So HOW do you teach problem-solving skills to kids?

Well, it depends on their age . As cognitive abilities and the size of the child’s challenges grow/evolve over time, so should your approach to teaching problem-solving skills.

Read on to learn key strategies for teaching problem-solving to kids, as well as some age-by-age ideas and activities.

3 General Strategies to Teach Problem-Solving at Any Age

1. model effective problem-solving .

When YOU encounter a challenge, do a “think-aloud” for the benefit of your child. MODEL how to apply the same problem-solving skills you’ve been working on together, giving the real-world examples that she can implement in her own life.

At the same time, show your child a willingness to make mistakes . Everyone encounters problems, and that’s okay. Sometimes the first solution you try won’t work, and that’s okay too!  

When you model problem-solving, explain that there are some things that are out of our control. As we're solving a problem at hand we should focus on the things we CAN actually control.

You and your child can listen to Episode 35  of the Big Life Kids Podcast to learn about focusing on what you can control.

2. Ask for Advice

Ask your kids for advice when you have a problem. This teaches them that it’s common to make mistakes and face challenges. It also gives them the opportunity to practice problem-solving skills.

Plus, when you indicate that their ideas are valued ,  they’ll gain the confidence to attempt solving problems on their own.

3. Don’t Provide “The Answer”

As difficult as it may be, allow your child to struggle, sometimes fail , and ultimately LEARN  from experiencing consequences.

Now, let’s take a look at some age-specific strategies and activities. The ages listed below are general guidelines, feel free to choose any strategies or activities that you feel will work for YOUR child.

Use Emotion Coaching

To step into a problem-solving mindset, young children need to first learn to  manage their emotions . After all, it’s difficult for a small child to logically consider solutions to a problem if he’s mid-tantrum.

One way to accomplish this is by using the  emotion coaching process  outlined by John Gottman.

First,  teach your kids that ALL emotions are acceptable. There are NO “bad” emotions. Even seemingly negative emotions like anger, sadness, and frustration can teach us valuable lessons. What matters is how we  respond  to these emotions.

Second,   follow this process:

• Step One: Naming and validating emotions.  When your child is upset, help her process the way she’s feeling. Say something like,  “I understand that you’re upset because Jessica is playing with the toy you wanted.”
• Step Two:   Processing  emotions.  Guide your child to her  calming space. If she doesn't have one, it's a good idea to create one.  Let her calm her body and process her emotions so she can problem-solve, learn, and grow. 
• Step Three: Problem Solving.  Brainstorm solutions with your child, doing more   LISTENING   than talking during the conversation. This allows your child to practice her problem-solving skills, and she’s more likely to actually implement the solutions she came up with herself.

Say, “Show Me the Hard Part”

When your child struggles or feels frustrated, try a technique suggested by mom and parenting blogger Lauren Tamm . Simply say, “Show me the hard part.”

This helps your child identify the ROOT   of the problem, making it less intimidating and easier to solve.

Repeat back what your child says,  “So you’re saying…”

Once you both understand the real problem, prompt your child to come up with solutions . “There must be some way you can fix that…” or  “There must be something you can do…”

Now that your child has identified “the hard part,” she’ll likely be able to come up with a solution. If not, help her brainstorm some ideas. You may try asking the question, “If you DID  know, what would you think?” and see what she comes up with.

Problem-Solve with Creative Play

Allow your child to choose activities and games based on her  interests . Free play provides plenty of opportunities to navigate and creatively solve problems.

Children often learn best through play. Playing with items like blocks, simple puzzles, and dress-up clothes can teach your child the process of problem-solving.

Even while playing, your child thinks critically:  Where does this puzzle piece fit? What does this do? I want to dress up as a queen. What should I wear?   Where did I put my tiara? Is it under the couch?

Problem-Solve with Storybooks

Read age-appropriate stories featuring characters who experience problems, such as:

• Ladybug Girl and Bumblebee Boy by Jacky Davis: The story of two friends who want to play together but can’t find a game to agree on. After taking turns making suggestions, they arrive at a game they both want to play: Ladybug Girl and Bumblebee Boy.
• The Curious George Series by Margaret and H.E. Rey: A curious little monkey gets into and out of dilemmas, teaching kids to find solutions to problems of their own.
• Ira Sleeps Over by Bernard Waber: Ira’s thrilled to have a sleepover at his friend Reggie’s house. But there’s one problem: Should he or should he not bring his teddy bear? It may seem small, but this is the type of early social problem your child might relate to.

Connect these experiences to similar events in your child’s own life, and ASK your child HOW the characters in these stories could solve their problems. Encourage a variety of solutions, and discuss the possible outcomes of each.

This is a form of dialogue reading , or actively ENGAGING   your child in the reading experience. Interacting with the text instead of passively listening can “turbocharge” the development of literacy skills such as comprehension in preschool-aged children.

By asking questions about the characters’ challenges, you can also give your child’s problem-solving abilities a boost.

You can even have your child role-play the problem and potential solutions to reinforce the lesson.  

For book suggestions, refer to our Top 85 Growth Mindset Books for Children & Adults list.

Teach the Problem-Solving Steps

Come up with a simple problem-solving process for your child, one that you can consistently implement. For example, you might try the following five steps:

• Step 1: What am I feeling?  Help your child understand what she’s feeling in the moment (frustration, anger, curiosity, disappointment, excitement, etc.)  Noticing and naming emotions will diffuse  their charge and give your child a chance to take a step back.
• Step 2: What’s the problem?  Guide your child to identify the specific problem. In most cases, help her take responsibility for what happened rather than pointing fingers. For instance, instead of, “Joey got me in trouble at recess,” your child might say, “I got in trouble at recess for arguing with Joey.”
• Step 3:   What are the solutions?  Encourage your child to come up with as many solutions as possible. At this point, they don’t even need to be “good” solutions. They’re just brainstorming here, not yet evaluating the ideas they’ve generated.
• Step 4: What would happen if…? What would happen if your child attempted each of these solutions? Is the solution safe and fair? How will it make others feel? You can also try role-playing at this step. It’s important for your child to consider BOTH  positive and negative consequences of her actions.
• Step 5: Which one will I try?  Ask your child to pick one or more solutions to try. If the solution didn't work, discuss WHY and move on to another one. Encourage your child to keep trying until the problem is solved. 

Consistently practice these steps so that they become second nature, and model solving problems of your own the same way.  It's a good idea to   reflect :   What worked? What didn’t? What can you do differently next time?

Problem-Solve with Craft Materials

Crafting is another form of play that can teach kids to solve problems creatively.

Provide your child with markers, modeling clay, cardboard boxes, tape, paper, etc. They’ll come up with all sorts of interesting creations and inventive games with these simple materials.

These “open-ended toys” don’t have a “right way to play,” allowing your child to get creative and generate ideas independently .

Ask Open-Ended Questions

Asking open-ended questions improves a child’s ability to think critically and creatively, ultimately making them better problem-solvers. Examples of open-ended questions include:

• How could we work together to solve this?
• How did you work it out? or How do you know that?
• Tell me about what you built, made, or created.
• What do you think will happen next?
• What do you think would happen if…?
• What did you learn?
• What was easy? What was hard?
• What would you do differently next time?

Open-ended questions have no right answer and can’t be answered with a simple “Yes” or “No.”

You can ask open-ended questions even when your child isn’t currently solving a problem to help her practice her thinking skills, which will come in handy when she does have a problem to solve.

If you need some tips on how to encourage a growth mindset in your child, don't forget to download our FREE Your Words Matter Volume 2 Kit .

Break Down Problems into Chunks

This strategy is a more advanced version of “Show me the hard part.”

The bigger your child gets, the bigger her problems get too. When your child is facing a challenge that seems overwhelming or insurmountable, encourage her to break it into smaller, more manageable chunks.

For instance, let’s say your child has a poor grade in history class. Why is the grade so low? What are the causes of this problem?

As usual, LISTEN as your child brainstorms, asking open-ended questions to help if she gets stuck.

If the low grade is the result of missing assignments, perhaps your child can make a list of these assignments and tackle them one at a time. Or if tests are the issue, what’s causing your child to struggle on exams?

Perhaps she’s distracted by friends in the class, has trouble asking for help, and doesn’t spend enough time studying at home. Once you’ve identified these “chunks,” help your child tackle them one at a time until the problem is solved.

Show “ The Broken Escalator Video ”

Discuss the importance of embracing challenges and solving problems independently with the “broken escalator video.”

In the video, an escalator unexpectedly breaks. The people on the escalator are “stuck” and yelling for help. At this age, it’s likely that your child will find the video funny and immediately offer a solution: “Just walk! Get off the escalator!”

Tell your child that this is a simple example of how people sometimes act in difficult situations. Ask, “Why do you think they didn’t get off the escalator?” (they didn’t know how, they were waiting for help, etc.)

Sometimes, your child might feel “stuck” when facing problems. They may stop and ask for help before even attempting to find a solution. Encourage your child to embrace challenges and work through problems instead.

Problem-Solve with Prompts

Provide your child or a group of children with materials such as straws, cotton balls, yarn, clothespins, tape, paper clips, sticky notes, Popsicle sticks, etc.

With just these materials, challenge your kids to solve unusual problems like:

• Make a leprechaun trap
• Create a jump ramp for cars
• Design your own game with rules
• Make a device for two people to communicate with one another

This is a fun way to practice critical thinking and creative problem-solving. Most likely, it will take multiple attempts to find a solution that works, which can apply to just about any aspect of life.

Make Them Work for It

When your child asks for a new toy, technology, or clothes, have her make a plan to obtain the desired item herself. Not only will your child have to brainstorm and evaluate solutions, but she’ll also gain confidence .

Ask your child HOW she can earn the money for the item that she wants, and encourage her as she works toward her goal .

Put It on Paper

Have your child write out their problems on paper and brainstorm some potential solutions.

But now, she takes this process a step further: After attempting each solution, which succeeded? Which were unsuccessful? Why ?

This helps your child reflect on various outcomes, learning what works and what doesn’t. The lessons she learns here will be useful when she encounters similar problems in the future.

Play Chess Together

Learning to play chess is a great way for kids to learn problem-solving AND build their brains at the same time. It requires players to use critical thinking, creativity, analysis of the board, recognize patterns, and more. There are online versions of the game, books on how to play, videos, and other resources. Don’t know how to play? Learn with your teen to connect and problem solve together!

Have Them Learn To Code

Our teens and tweens are already tech-savvy and can use their skills to solve problems by learning to code. Coding promotes creativity, logic, planning, and persistence . There are many great tools and online or in-person programs that can boost your child’s coding skills.

Encourage to Start a Meaningful Project

This project has to be meaningful to your teen, for example starting a YouTube channel. Your teen will practice problem-solving skills as they’re figuring out how to grow their audience, how to have their videos discovered, and much more. 

In the Big Life Journal - Teen Edition , there’s a section that guides them through planning their YouTube channel and beginning the problem-solving process.

Apply the SODAS Method

Looking for a game plan that your teen can employ when faced with a problem? The SODAS method can be used for big or small problems. Just remember this simple acronym and follow these ideas:

• D isadvantages
• A dvantages

Encourage to Join Problem-Solving Groups

Does your teen enjoy solving problems in a team? Have them join a group or club that helps them hone their skills in a variety of settings--from science and robotics to debating and international affairs. Some examples of groups include: 

• Odyssey of the Mind
• Debate team
• Science Olympiad

Looking for additional resources?  The Bestseller’s Bundle includes our three most popular printable kits packed with science-based activities, guides, and crafts for children. Our Growth Mindset Kit, Resilience Kit, and Challenges Kit work together as a comprehensive system designed specifically for children ages 5-11.

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25 thoughts on “ How to Teach Problem-Solving Skills to Children and Preteens ”

I love, love, love the point about emotional coaching. It’s so important to identify how children are feeling about a problem and then approach the solutions accordingly.

Thank you for putting this together. I wrote an article on problem-solving specifically from the point of view of developing a STEM aptitude in kids, if you like to check it out – https://kidpillar.com/how-to-teach-problem-solving-to-your-kids-5-8-years/

I feel that these techniques will work for my kid.. Worthy.. Thank you

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A fast-flexible strategy based approach to solving employee scheduling problem considering soft work time

1 School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164 China

2 School of Information Science and Technology, Zhejiang Shuren University, Hangzhou, 310015 China

Changchun Yang

3 State Grid WenZhou Electric Power Supply Company, Wenzhou, 325035 China

Associated Data

The datasets generated and/or analysed during the current study are not publicly available due this study is going on but are available from the corresponding author on reasonable request.

Employee scheduling aims to assign employees to shifts to satisfy daily workload and constraints. Some employee scheduling problems and their variants have been proven NP-hard, and a series of works have been done. However, the existing algorithms consider the fixed work time, which may cause plenty of overstaffing and understaffing phenomenons. Hence, this paper proposes a fast-flexible strategy based approach (FFS) to solve it. FFS introduces the idea of soft work time, which allows the work time of employees can be adjusted in a range. Based on this, we set the flextime strategy to decide the specific work time of each employee every day. Besides, FFS adopts a pairwise-allocated strategy and proficiency average matrix to boost its efficiency and effectiveness. Finally, the extensive experimental evaluation shows that FFS is more effective and efficient than the baselines for solving the employee scheduling problem considering soft work time.

Introduction

Employee scheduling aims at assigning the right employees to the right shifts at the right time, for satisfying the constraints and achieving the optimization of goals 1 . It widely arises in real-life scenarios such as health care 2 – 4 , retail stores 5 , 6 , transportation 7 , job shops 8 and call centers 9 – 11 . In most existing works, employees perform their duties according to the fixed period, which is composed of fixed start and end time points. However, the workload of different periods varies as time goes by, and employee scheduling considering fixed work time can not satisfy the varied workload well, and causes a lot of understaffing and overstaffing problems. In the following, we consider one representative motivation example.

Motivation example ( call center )

In a call center, employees are assigned to shifts and serve the call arrivals as Fig.  1 a shows. In Fig.  1 a, three employees are assigned to the same shifts, suppose that the execution time of this shift is [7:30, 9:30], every 30 minutes is treated as a period and each one contains the number of call arrivals (treated as workload) as Fig.  1 b shows. Combined with these two figures, employee scheduling considering fixed work time causes some understaffing and overstaffing problems. For example, the period [7:30, 8:00] requires 2 employees to satisfy its workload, but there are 3 employees, which is over the requirement of workload and causes the overstaffing problem. Besides, the period [9:00, 9:30] asks for 4 employees, while it is assigned to 3 employees, and thus the understaffing problem arises. Hence, employee scheduling considering fixed work time can not satisfy the varied workload well. The execution time of a normal shift usually contains several hours, and the corresponding workload of different periods is even more drastic as Fig.  1 c shows, thus, the existing fixed work time scheduling causes plenty of overstaffing and understaffing phenomenons. In this paper, we introduce the idea of soft work time, which allows adjusting start and end time points. In real scenarios, there are several types of shifts with different execution times, and each one can adjust its start and end time points. When the number of assigned employees is over the requirement of workload, some employees can delay the start point of execution time or be earlier to end the work. Note that the adjustable periods exist at the start/end/meal point of the execution.

Illustration for motivation example.

However, the existing studies suffer from one or more drawbacks in solving such employee scheduling problems.

• The existing works rarely consider the soft work time, they stressed fixed work time.
• Employee scheduling problem involves more than one optimization goal, and they may contain potential conflicts. that means the improvement of one goal may lead to the performance degradation of another. Taking the number of employees and output in manufacturing, enterprises ask for the least number of employees and the most output. Reducing the number of employees will decrease the output, and increasing the output asks for more employees. Many studies convert multiple goals to one single objective by empirically using different weights over different goals 9 , 12 . However, too much domain knowledge is needed in this way and the generated schedule may fail if the weights are changed, hence, this type of method usually takes a lot of time.
• Some employee scheduling problems and their variants have been proven NP-hard 13 , traversing each potential schedule will cost prohibitive computation. Hence, there are plenty of pruning techniques such as sample averaging approximation (SAA) 14 , these techniques can effectively work in their problems. However, as far as we know, these problems rarely consider soft work time. Hence, these pruning techniques can not address our problem well.

In our work, we consider the soft work time. Specifically, we consider two types of soft work time, i.e. the number of consecutive working days and the working duration of one day. To address this issue, we propose FFS, a polynomial-time method to address it. Specifically, FFS is divided into four steps. In the first step, FFS proposes a scheduling-cycle-based hard constraints control mechanism, to decide the soft consecutive working days. In the second step, FFS uses the gradient descent projection to estimate the number of employees required for each shift, according to workload and work time of each sharing period. It can implement coarse-grained pruning of the search space. In the third step, based on the estimated number of employees in the second step, FFS uses the pairwise-allocated strategy to find the suitable employee combinations and establishes the proficiency average matrix to further boost its efficiency. Thus, we generate the feasible assignments for each day in the whole scheduling horizon. In the fourth step, according to the workload coverage of each period, a flextime strategy is proposed to decide the specific work time of each employee performing his assigned shift.

In a nutshell, the key contributions of our paper are listed below.

• We present a polynomial-time solution to efficiently solve employee scheduling considering soft work time. It provides several strategies to effectively shrink the number of potential schedules, and fast find high-quality employee assignments.
• We further consider two types of soft work time, and propose allocation strategies to decide the specific work time of each employee. It can alleviate the overstaffing and understaffing problems, and improve the quality of schedules.

The rest of this paper is organized as follows. Section " Preliminaries " introduces basic concepts and gives a formal definition of the problem. Section " Algorithm overview " elaborates on our approach FFS. Experimental results and our findings are reported in Sect. " Experiments ". Section " Related work " reviews related work. Finally, Sect. " Conclusion " concludes the paper with some directions for future work.

Preliminaries

In this section, we first present a series of decisions, i.e. scheduling horizon, shifts, and employees. Then we introduce the scheduling constraints. Finally, we define the optimization goals.

We start with the description of each decision.

Scheduling horizon

The scheduling horizon D is defined by

where d i ∈ D denotes a day. Each day has the same duration for work, and can be divided into ω same consecutive time periods, denoted by { t p i 1 , t p i 2 , ⋯ , t p i ω } . Each time period t p i j ∈ TP has a corresponding workload, denoted by W _ t p i j .

There are 5 types of shifts assigned to employees, each type of shift contains an execution time, they are denoted by,

Where i is the i th day; k is the k th employee; S F T k i is the assigned shift of k th employee for i th day; τ is the types of shifts which can be assigned to employees; in the { 1 , 2 , 3 , 4 , 5 , 0 } , { 1 , 2 , 3 , 4 , 5 } is the shifts for working and { 0 } is the rest day; T k i is the execution time for k th employee for i th day; T ks i is the start execution time for k th employee for i th day; T ke i is the end execution time for k th employee for i th day; T km i is the meal time for k th employee for i th day. One employee can be assigned to one shift at most. Each shift has an execution time, which contains a series of consecutive time periods. In addition, the execution time of each shift is unfixed. Specifically, the start and end time periods of execution time are selected in the first four time periods and the last four time periods.

There are t employees, each one has a proficiency, and each time period has a total proficiency, which is denoted by,

where k is the k th employee; p k is the proficiency of k th employee; t o t a l p _ t p i j is the total proficiency of time period t p i j for the employee assigned to working shifts.

Optimization objectives

(1) Average workload coverage Ave_Coverage . Ave_Coverage can be computed by the whole workload and total assigned employees’ proficiency (n days and each day ω time periods), which can be defined as below.

where t p i j is the j th time period of i th day; t o t a l p _ t p i j is the number of total assigned employee proficiency for t p i j ; W _ t p i j is the workload of t p i j ; n is the number of days in scheduling horizon; ω is the number of time periods in one day; t is the number of employees. No matter the average workload coverage of one day or one time period, it should be closest to 1. If coverage > 1, it means that the assigned proficiency is too much and more than the requirement of the workload, which causes the waste of employee proficiency. When coverage < 1, it means the assigned proficiency is too little and less than the requirement of the workload, where the workload can not be finished.

(2) Coverage fairness Coverage_Fairness can be computed by the whole workload and total assigned employees’ proficiency, which can be defined as below.

where t p i j is the j th time period of i th day; t o t a l p _ t p i j is the number of total assigned employee proficiency for t p i j ; W _ t p i j is the workload of t p i j ; Ave_Coverage is the average workload coverage for n days, which can be computed by Eq. ( 2 ); n is the number of days in scheduling horizon; ω is the number of time periods in one day; t is the number of employees. Coverage fairness should be minimal, which means the coverage fluctuation of time periods.

Constraints

(1) Each employee consecutively works max days at most, but no less than min days, which can be defined as below.

minimal day constraint:

maximal day constraint:

(2) Each employee should have r rest days for the whole scheduling horizon and any two consecutive rest days are not allowed, which can be defined as below.

Objective function

Traditional objective function gathers all objectives with weights, but the weights need more time to be adjusted. Hence, this paper used the TOPSIS to evaluate the indicated solutions without weights. More details are presented as our other work 15 .

Where function TOPSIS measures two optimization objectives to generate a score at the same time, here, the score is higher, the quality of the result is better, the score is lower the quality of the result is worse.

Algorithm overview

To generate a feasible schedule with flexible work time, a naive way to address this problem is to traverse all the potential schedules, and select the best result among them as the final solution. However, such a method requires prohibitive computation consumption, since the number of potential schedules grows exponentially as the number of employees increases.

Algorithm 1

The overview of our approach.

Hence, we propose a fast-flextime strategy based approach (FFS) to efficiently search for a feasible schedule, which is a polynomial-time method. For ease of understanding the main idea of FFS, the pseudo-code of algorithm overview is presented in Algorithm 1. To be more specific, we generate the employee assignment over days (line 1), and the employee assignment of each day is generated by four modules, namely, satisfying constraints SATISFY_CONSTRAINTS () (line 2), estimating employee number ESTIMATE_NUMBER () (line 3), searching feasible assignments SEARCH_ASSIGNMENT () (line 4) and deciding flexible work time DECIDE_FLEXTIME () (line 5).

Satisfying constraints

To ensure the availability of the generated schedule, SATISFY_CONSTRAINTS () is required to meet the hard constraints. Its pseudo-code is presented in Algorithm 2. SATISFY_CONSTRAINTS () takes a set of employees ( E ), the certain day ( d i ) and the number of days in scheduling horizon ( D ) as input, and output is available employee set ( available_E ).

Algorithm 2

SATISFY_CONSTRAINT ( E , d i ,| D |).

To achieve satisfying hard constraints, SATISFY_HCONSTRAINT () adopts the constraint control mechanism based on scheduling cycle ( SC ), which is composed of ξ consecutive workdays and a rest day, e.g. the shift sequence ( sft_1 , sft_2 , rest-day ) contains 2 working days and 1 rest-day, which can compose a SC . The types of such SC are dependent on max and min . Since H 2 asks each employee works max days at most, but no less than min days, we get ξ ∈ [ min , min ]. Suppose that min =2, max =4, the scheduling cycles contain three types, i.e. 2W+1R (2 workdays and 1 rest-day), 3W+1R (3 workdays and 1 rest-day) and 4W+1R (4 workdays and 1 rest-day).

Then SATISFY_CONSTRAINTS() computes the DCT of each employee (line 3), which can be divided into 3 categories: the number of days before the first rest-day q , the number of days in all types of scheduling cycles ∑ a g · G , and the left days t , as Fig.  2 shows.

Classification of time points in DCT.

Note that the first rest day of each employee does not belong to any type of scheduling cycle, and H 3 asks for r rest day for each employee in the scheduling horizon. Hence, the total number of scheduling cycles for each employee is r - 1 . Besides, as for t , due to the minimal number of consecutive workdays are set to min days, as long as t ≤ m i n , employees will be assigned to shifts in these t days, and the total number of rest-days for each employee are fixed to r days.

The formal for computing DCT is as below.

According to the above operations, SATISFY_HCONSTRAINT () module computes DCT of each employee. Since the serial number of rest days is different for each employee, their DCT is different. For each employee e k ∈ E , SATISFY_HCONSTRAINT () will check the return value ( sign(g) ), and identify the availability of employees. Here, SATISFY_HCONSTRAINT () traverses previous max shifts for each employee, and the number of workdays in this shift sequence is marked as NUM , which is treated as a trigger to search for suitable SC. There may exist three situations:

• N U M < m i n , all employees are available;
• m i n ≤ N U M ≤ m a x and N U M ∈ s i g n ( g ) and ∀ g ∈ s i g n ( g ) ≤ N U M , there exists the scheduling cycle whose number of work days equals to NUM , but that whose number of work days exceeds NUM does not exist. Thus, e k is unavailable;
• m i n ≤ N U M ≤ m a x and N U M ∈ s i g n ( g ) and ∃ g ∈ s i g n ( g ) > N U M , compared to situation 2, situation 3 exists that whose number of work days exceeds NUM . Thus, e k is available.

Estimating employee number

The available employees of d i are generated by SATISFY_HCONSTRAINT (). Suppose that the number of available employees is β , given five types of shifts (defined in Para.1 Page 3), if we assign directly available employees to shifts, each employee can be assigned to anyone in these five types of shifts, and thus, the number of potential assignments is 5 β , i.e. exponential. To avoid such a situation, we invoke the procedure ESTIMATE_NUMBER () (as algorithm 3 shows), which takes available employees and the workload of each time period in d i as inputs, and the output is the estimated number of employees required for each shift of d i . In the following, we give an example to show how it works, combined with Algorithm 3.

Algorithm 3

Estimate_number( available_E , W_tp i j ).

First, according to the work time of each shift, we count the sharing work time periods share_TP among different shifts. For instance, given three shifts of d i , i.e. sft_1 , sft_2 , sft_5 and their work time are [ t p i 1 , t p i 18 ], [ t p i 2 , t p i 22 ] and [ t p i 13 , t p i 30 ], respectively, These work time are divided into different share time periods as Fig.  3 shows (line 1), e.g. share_TP 1 =[ t p i 1 , t p i 2 ), share_TP 2 =[ t p i 2 , t p i 13 ). Then we compute the average workload AW_share_TP z of each sharing work time period share_TP z (line 2). Next, we establish the workload function as follows (line 3) to estimate the workload of each shift of d i .

Example of computing sharing work time among shifts.

Where AW_share_TP z represents the average workload of share_TP z , λ is a parameter for checking whether share_TP z belongs to the work time of the corresponding shift, W_sft_t is the workload of sft_t .

Note that if share_TP z belongs to the work time of sft_t , λ = 1 ; Otherwise, λ = 0 . Thus, Eq. ( 11 ) represents that the average workload of share_TP z is composed of the workload of each shift. However, estimating the workload of each shift by solving Eq. ( 11 ) is so strict that there may not exist a feasible solution, since the number of sharing work time periods is regularly larger than the type of shifts ( z ≥ t ), Eq. ( 11 ) is an overdetermined function 16 . Hence, we adopt the projected gradient methods to generate the solution of Eq. ( 11 ), where an error Δ b is introduced. Eq. ( 11 ) is converted into Δ b + A W _ s h a r e _ T P z = ∑ t = 1 5 λ W _ s f t _ t , where Δ b should follow that (1) the variance of any two sub-errors is the same, and (2) any two sub-errors are independent 16 . For easing to remember, we denote λ W _ s f t _ t and A W _ s h a r e _ T P z by Ax and B , where A is a matrix composed of λ , x is the estimated workload for each shift of d i and B denotes the workload of each sharing time period. Thus, we get Eq. ( 12 ) from Eq. ( 11 ).

Note that we vary the value of x and make the error Δ b as small as possible. Thus, we use the least square method to reach this goal, which is achieved as below.

where | | Δ b | | reaches the minimum, x is the feasible solution. To get the solution x , we introduce the projected gradient method, which is defined below.

where P C ( x ) denotes the projection operator, C represents the solution space for x , μ is the step length and ∇ f ( x k ) is the gradient vector. The workload of each sharing time period must be greater than 0, hence C = R + n . In this way, we estimate the workload for each shift EW_sft_t (line 4).

However, the proficiencies of all available employees may not satisfy the workloads of shifts. Hence, we need to confirm the total proficiency by total_AP and ∑ EW_sft_t as below.

where total_AP is the total proficiency of all available employees, and ∑ 1 5 E W _ s f t _ t is the total workload of all shifts for d i .

When t o t a l _ A P ≤ ∑ 1 5 E W _ s f t _ t , all the available employees can be assigned to shifts and the number of available proficiency totalap_d i is set to total_AP (lines 5-7). When t o t a l _ A P ≥ ∑ 1 5 E W _ s f t _ t , not all available employees can be assigned to shifts for satisfying S 1 , thus the number of available proficiency totalap_ d i is set to ∑ 1 5 E W _ s f t _ t (lines 7-8).

Based on these, we estimate the number of proficiency ap_sft_t for each shift according to the ratios among EW_sft_t (line 9), and compute the estimated number of employees required for each shift people_sft_t by ap_sft_t and the average proficiency of all available employees average_AP (lines 10-11), then return people_sft_t (line 12).

Searching feasible schedule

According to the estimated number of employees for each shift of d i , SEARCH_ASSIGNMENT () requires to select employees and assign them to the corresponding shifts, which should follow the principle that the average proficiency of employee combinations for each shift should be maximally close to average_AP , since the closer to average_AP the average proficiency of employee combinations is, the smaller the values of | 1 - A v e _ C o v e r a g e | and C o v e r a g e _ F a i r n e s s are. Hence, we adopt the pairwise-allocated strategy to achieve this goal, and introduce the proficiency average matrix to boost its efficiency. In the sequel, combined with the procedure SEARCH_ASSIGNMENT () as Algorithm 4 shows, we present more details with the following example as Fig.  4 shows, where there are 7 available employees and their proficiencies are 11, 13.4, 17.3, 12.7, 15.6, 16.1, 14.2, SEARCH_ASSIGNMENT () assigns the estimated number of employees to the corresponding shifts.

Dividing the proficiencies set into two subsets.

Algorithm 4

SEARCH_ASSIGNMENTS ( available_E , People_ d i ).

First, the proficiencies of all available employees are sorted in ascending order (line 1), and they are divided into two subsets (i.e. AP_1 and AP_2 ) according to average_AP (line 2), where AP_1 ={11, 12.7, 13.4, 14.2} and AP_2 ={15.6, 16.1, 17.3}. Then we compute the available value of any two proficiency in AP to establish the proficiency average matrix ( PAM ) as Fig.  5 shows (line 3), which is defined as a square matrix of available_E . Next, we take the first proficiencies of AP_1 and AP_2 , denoted by { L 1, R1 }={11, 15.6} (lines 4-6). Subsequently, we sort People_sft_t in an ascending order, which stores the estimated number of each shift, and starts with the least number of shifts (lines 6-7).

The example of establishing the average proficiency matrix.

Subsequently, we get the corresponding employee combination ec 1 ={ e 1 , e 5 } (lines 8-9), and its the average proficiency average_ec 1 (= 11 + 15.6 2 = 13.3 ) is a trigger to find the next employee combination e c 2 . To ensure the average proficiency of e c 1 and e c 2 be as close to average_AP as possible, the expected average proficiency of e c 2 E p 2 = 2 × a v e r a g e _ A P - a v e r a g e _ e c 1 = 15.4 (line 10). Pairwise-allocated strategy searches the value that is closest to Ep 2 (=15.4) in this PAM . It is worth noting that for satisfying the hard constraint H 1 (i.e. each employee is assigned to at most one shift per day ), the employees in e c 2 are selected from the available employees except e 1 and e 5 (lines 11, 13) as Fig.  6 shows, and based on this, e c 2 = { e 6 , e 7 } , since the average proficiency of e 6 and e 7 is 15.15, which is closet to E p 2 (= 15.4 line 10) (line 12).

The example of searching e c 2 .

In the sequel, the pairwise-allocated strategy computes the expected average proficiency of e c i ( i ≥ 3 ) and locates e c i in the same way until the total number of employees in the selected groups equals the estimated number (line 14). Note that, if the estimated number of employees is odd, the last employee is treated as a group, whose selection way also follows the principle that the average proficiency of this group should be maximally close to the expected average proficiency (lines 15-16).

Then, we select the first proficiency in A P _ 1 and the second proficiency A P _ 2 , denoted by { L 1, R 2}={11, 16.1}, and the corresponding employee group e c 1 = { e 1 , e 6 } is utilized to generate the next candidate assignment until all combinations of proficiency between AP_1 and AP_2 are listed.

In the end, we introduce the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution, TOPSIS 17 ) to evaluate the selected assignments, where each one will be scored by TOPSIS. The assignment with the highest score is treated as the feasible schedule (line 17). Traditional multiple-objective optimization algorithms usually use the linear weighted method, which uses weights to transform different optimization objectives into one. However, weight setting requires a large amount of domain knowledge and expert experience, and needs a lot of time to choose suitable weights. Compared with these, TOPSIS rarely considers the weights among the optimization objectives, and this is the reason for choosing TOPSIS. The more details are explained in reference 17 .

Deciding flexible work time

To maximally satisfy the workload of each time period for each day, the assignments generated from Sect. " Searching feasible schedule " require deciding the flexible work time of each shift. To achieve this goal, we invoke the procedure DECIDE_FLEXTIME () (as Algorithm 5 shows), which takes the feasible assignment ( fa ) as the input, and the output is the feasible schedule with flexible work time ( fs ).

First, according to the feasible assignment fa , we compute the total average proficiency of fa (lines 1-2). Based on these, we compute the coverage of each time period for the assignment of d i , and get the employee sets for each shift, i.e. E_sft_t (lines 3-5). Next, we get the corresponding proficiency sets for these employee sets, and sort the proficiencies of them in ascending order (line 6).

Then we need to confirm the flexible work time of each shift (lines 7-8), which is divided into three categories, i.e. the start work time periods, the end work time periods and the meal break, hence we propose three corresponding strategies to deal with these.

Algorithm 5

DECIDE_FLEXTIME ( available_E , ap , fs ).

Strategy 1: (The flexible start work time periods) The time periods for flexible start work are [ t p i 1 , t p i 4 ], we need to compare the coverages of these time periods with Average_fs in turn. For each coverage C i j of the time period t p i j ∈ [ t p i 1 , t p i 4 ], if C i j ≥ A v e r a g e _ f s , we remove the proficiency in P_sft_t in turn. The reason is that the workloads of these time periods are small, and removing the proficiency from smallest to largest will make coverage maximally get close to Average_fa , on the premise of decreasing the influence on the coverage of these time periods (lines 9-10). In addition, if e k is working in the time period t p i j - 1 , he can not be set to rest in t p i j .

Strategy 2: (flexible end work time periods) The time periods for flexible end work are [ t p i 27 , t p i 30 ] and we compare coverages of these time periods with Average_fs in decreasing order in turn, then we do the same operations (lines 11-12) in strategy 1. Similarly, if e k is working in the time period t p i j + 1 , he can not be set to rest in t p i j .

Strategy 3: (flexible meal break) Different from the start and end work time periods, each employee must have a meal break, when he can have lunch or supper. In addition, the meal break is divided into lunch meal time and dinner meal time, hence we should identify which one belongs to the shift sft_t of e k (line 13-14,18). Based on these, if sft_t contains the lunch meal time, we select the higher coverage ratio of the time periods t p i 7 , t p i 8 , t p i 9 and t p i 10 , denoted by c i j (line 15). Next, we set employees in E_sft_t starting with the largest proficiency, the corresponding proficiency is removed, and C i j is renewed (lines 16-17). Then we check the adjacent time periods of t p i j to have a longer meal time (line 18). If sft_t contains the dinner meal time, we do the same operations on the time periods of the dinner meal, i.e, [ t p i 19 , t p i 21 ] (lines 19-23).

Thus, each employee assigned to shifts of d i has flexible work time and meal break, and is added to the assignment of d i in the feasible schedule ( fs ) (line 22). Finally, when the assignments of all days in the scheduling horizon are performed DECIDE_FLEXTIME (), fs is treated as the feasible schedule with flexible work time and returned (line 23).

This subsection discusses each module of our approach in terms of time complexities by the book with the title “New Generation Computer algorithm” 18 . Then, the existing algorithms are compared to our algorithm with time complexity.

SATISFY_CONSTRAINTS This module is composed of two parts: dynamic combination table (DCT) computation and DCT query. Since the dynamic combination tablets can be generated in advance, this part of time complexity is negligible. In the part of the DCT query, due to the number of types of scheduling cycles being constant, hence its time complexity is O (1).

ESTIMATED_NUMBER This module is composed of a sequential structure, where the highest time complexity is the Gradient Descent Projection (GDP). Although its time complexity is hard to evaluate, this computation can be processed in advance. As for other operations in this module, the computation is constant and the time complexity is O (1).

SEARCH_ASSIGNMENT In this module, the available employees are divided into two sub-sets. In the worst case, the number of first employee combinations is ( n 2 ) 2 . The next employee combination will be selected by whose proficiency can make the first one’s proficiency closest to the average proficiency O (1). Thus, the time complexity of this module is O ( n 2 ) .

DECIDE_FLEXTIME This module decides the work time of each employee in sequential order. Hence, its time complexity is O (n).

Based on these, the time complexity of our approach is O ( m · n 2 ), where m is the number of days on the scheduling horizon.

Our problem is a new one, the heuristic algorithm is designed for a specific problem, hence the existing heuristic algorithm is unsuitable for our problem, only general algorithms such as meta-heuristic algorithms can adapt to our problem. However, due to randomness of the generated results, the meta-heuristic algorithm (NSGA-II 19 , IPSO 20 , PICEA-g 21 , MOEAD 9 and GF 22 ) are required to run multiple times for deciding final results with rather high quality. Besides, they usually generate initial individuals and adopt evolutionary mechanisms to generate new individuals, then compare them to choose the better ones. Due to the mechanism of choosing, their time complexity is different. NSGA-II and MOEAD are O ( β · n 2 ) and O ( β n T ) , where β denotes the number of individuals of one generation, and T is the number of neighborhoods. IPSO is O ( n !), PICEA-g is O ( n 3 ) . GF is a novel general framework, which gathers the existing meta-heuristic algorithms whose time complexity ranges from O ( β n T ) to O ( n !). As for the MILP, we use the Gurobi solver 9.1 and the solution is a branch and bound method, the time complexity is O ( n !).

In general, the time complexity of our algorithm is less than others.

Experiments

In this section, we experimentally evaluate the efficiency and effectiveness of our proposed solution FFS against the state-of-the-art. We implement our algorithm in Python, and adopt the Python implementations of all competitors based on the following methods: Mixed-Integer Linear Programming (MILP 12 ), Improved Particle Swam Optimization (IPSO 20 ), A Fast and Elitist Multiobjective Genetic Algorithm (NSGA-II 19 ), the Preference-inspired Co-evolutionary Algorithm Using Goal Vectors (PICEA-g 21 ), Multi-objective Evolutionary Algorithm based Decomposition (MOEAD 9 ) and a general multi-objective algorithm framework (GF 22 ), which are listed in Table  1 . The MILP adopts Gurobi solver 9.1 23 to generate solutions. NSGA-II 19 , MOEAD 9 and PICEA-g 21 are three multi-objective evolutionary algorithms (MOEAs), and MILP 12 belongs to the mathematical methods, the IPSO 20 is the heuristic algorithms, and the GF 22 is one of novel general framework for solving multi-objective optimization problems.

The data sets used in experiments.

Besides, to compare the performance of FFS and five methods with the considerations of fairness and accuracy, we (1) report the response time of each method by generating the same feasible schedule results, and (2) report the TOPSIS score of each method under the same response time. all evaluations in this section are performed based on a mixture of real and synthetic data sets. The real part is provided by the call center of China Telecom company, which is the call arrivals of six months from July 2020 to Dec. 2020. The synthetic part is the employees, which are synthesized from the real employees of a call center in China Telecom company. Both of these parts are listed in Table  2 , where the number of employees is the real-life data. We synthesize five employee sets for each month, whose number of employees are 40, 60, 80, 100 and 120, respectively. We synthesize these employee sets by randomly choosing part of employees in real life as the added or reduced employees. In addition, each employee in these employee sets has a proficiency. Note that each experiment runs 10 times by randomly choosing the corresponding quantity of employees, and reports the average result. All the experiments are conducted on a server machine with an Intel Intel(R) Xeon(R) CPU E5-2637 3.50 GHz processor and 8GB RAM, running Windows 10 with Python 3.8.

Experiment setting

We totally set 6 sets of experiments to evaluate the performance of FFS and five alternatives, the parameters in each experiment are illustrated in Table  3 , where the same quality means that five alternatives aim at generating a schedule with the quality same to that of FFS generating and report their response time, same run-time means that their response time is set to be same to that of FFS generating a schedule and report the quality of their schedules. EXP1 to EXP4 evaluate the overall performance difference among FFS and five alternatives by varying the number of employees and datasets. EXP5 and EXP6 evaluate the internal performance difference by removing the flextime-strategy, pairwise-allocated strategy and proficiency in turn.

The parameters used in experiments.

Overall performance

Exp 1: search efficiency.

The first set of experiments verifies the performance of FFS by varying datasets, compared with the other six alternative methods. The result is shown in Fig.  7 a. The first observation is that FFS has the shortest response time in all cases, with MILP, GF and NSGA-II in the second place, and MOEAD, PICEA-g and IPSO are the worst. Specifically, FFS outperforms MILP, GF and NSGA-II by one order of magnitude, and is faster than PICEA-g, IPSO and MOEAD two orders of magnitudes. The reason is that MILP needs to consider all the potential assignments, and even if adopting a series of fast computing sub-algorithms such as the simplicissimum method, MILP remains to be time-consuming. GF adopts the universe methods to solve this problem, but they lack of optimization strategy for our problem. As for NSGA-II, it adopts a fast non-dominated sorted strategy to speed up the convergence of solutions. MOEAD, PICEA-g, and IPSO require enough generation operations to get the feasible solutions, due to their random nature of query strategies; while FFS adopts the pairwise-allocated strategy to effectively shrink the number of potential assignments, which makes the feasible assignment query execute in a small solution space. The second observation is that FFS achieves the most stable performance and MOEAD fluctuates most greatly. The reason is that FFS effectively reduces the number of potentially feasible assignments, owing to pairwise-allocated strategy. While MOEAD requires the operations of mutation and crossover to generate the new assignments, and select ones with the quality higher than old assignments. However, the operations of mutation and crossover contain the nature of randomness, which results in the instability of newly generated solutions.

Overall effectiveness and efficiency with different data sets.

EXP 2: Search effectiveness on running the same time

EXP 2 runs under the condition of running the same time and reports the TOPSIS score of each method as illustrated in Fig.  7 b. It is seen that when changing the datasets, the TOPSIS score of FFS changes slightly, and gets the highest TOPSIS score. It is because, the flextime strategy of FFS according to the coverage ratio of each time period changes the work time of each employee, which follows the principle that each employee should have r rest days for each month and can not be assigned to rest day for two consecutive days. Thus, it ensures that two optimization goals (i.e. Ave_Coverage and Coverage_Fairness ) can be closer to the optimal values. In addition, pairwise-allocated strategy in FFS selects suitable employee combinations according to the soft constraint S 1 , and assigns them to the corresponding shifts. Hence, the TOPSIS score performs best. As for the NSGA-II, MOEAD and PICEA-g, these MOEAs usually require a large number of generations to ensure the quality of their solutions, but the time cost of this experiment is little, which limits the number of generations and the solutions of MOEAs can not be guaranteed to be high-quality. The MILP also faces a similar situation, which considers all the potential schedules and requires enough computations to support its search sub-algorithms, but the limited time cost weakens the quality of its solution. As for the IPSO, it is easy to fall into local-optimal status, hence, when the first solution is high-quality, it will get some better solutions than MOEAD, NSGA-II, MILP and PICEA-g. However, when the quality of the initial solution is low, it may have low-quality solutions in the final. All of these deeply influence the quality of the generated schedule, and lead to that the quality of solutions from our approach is superior to that of others.

EXP 3: Effect of the number of employees on search efficiency

The third set of experiments evaluates the impact of the number of employees on search efficiency. The result is depicted in Fig.  8 a. The first observation is that the response time of FFS slightly increases as the number of employees grows. It is because that, for FFS , the search space shrunken by pairwise-allocated strategy gets larger with the increasing number of employees, and FFS spends more time searching the suitable employee groups. The second observation is that the time cost of MILP and GF increases as the number of employees grows. The reason is that the number of potential feasible schedules increases exponentially for MILP and GF, although they contain a series of pruning techniques to reduce the search space, it remains to be pretty large and the growth of employee number adds to their response time. The third observation is that the response time of MOEAD, NSGA-II and PICEA-g fluctuates with the increase in the number of employees. The reason is that, they randomly initialize individuals, and generate the feasible schedule based on the search strategy with the nature of randomness, which leads to unstably of their generated schedules. To reach the quality of a fixed schedule, they have to spend more generations to find a suitable schedule, and are presented in the fluctuation of response time. As for IPSO, it is easy to fall into local-optimal, the time cost of running one is pretty short, but the quality of the generated schedule can not reach the fixed schedule, it will run again until it does. Thus, the total time cost is comparatively higher than others.

Overall effectiveness and efficiency with the number of employees.

EXP 4: Effect of the number of employees on search effectiveness

Figure  8 b shows the result of each method by varying the number of employees. It is observed that the TOPSIS score of FFS increases as the number of employees grows. It is because more employees mean more potential employee combinations, and thus, there is a higher possibility for FFS selecting the employee groups whose proficiency is nearest to the workload of shifts. Hence, the TOPSIS of FFS will increase with the number of employees growing. However, since the time cost is limited to that of FFS costing and it is too short, all alternatives’ query strategies are time-consuming, which results in a low number of generations and computations for MOEAs, IPSO and MILP. Thus, their generated schedules are of low quality. In view of these, the TOPSIS score of FFS is the highest in all cases.

Internal performance

Exp 5: internal performance vs. different datasets.

The fifth set of experiments evaluates the internal impact of the performance of pairwise-allocated PA strategy and proficiency average matrix PAM by varying the datasets. We compare FFS with five alternative methods, i.e. FFS-NoFlextime , FFS-NoPAM and Enumeration , respectively. FFS-NoPAM removes the Average Proficiency Matrix PAM , and Enumeration enumerates all potential schedules. The result is illustrated in Fig.  9 a. It is observed that FFS is faster than FFS-NoPAM and Enumeration on all datasets. In particular, FFS is faster than FFS-NoPAM by two orders of magnitudes, and outperforms Enumeration by 3 orders of magnitude in average, respectively. This is because, compared to Enumeration , FFS and FFS-NoPAM contain PA , which greatly reduces the number of potential schedules. This indicates that PA effectively shrinks the search range and improves efficiency. In addition, FFS adopts the proficiency average matrix ( PAM ) to boost the efficiency, and based on PAM , FFS outperforms FFS-NoPAM one order of magnitude, which indicates that PAM further improve the efficiency of search.

EXP 6: Internal performance vs. the number of employees

The sixth set of experiments explores the internal effect for FFS by varying the number of employees. The result is plotted in Fig.  9 b. The first observation is that the response time of Enumeration is exponential, the reason is that the number of employee assignments grows exponentially as the number of employees increases, and the corresponding response time for Enumeration generating a schedule presents exponentially. The second observation is that the response time of FFS and FFS-NoPAM still remains low and stable, the reason lies in two aspects: first, they pre-estimate the number of employees for each shift of each day for pre-pruning a large number of potential schedules, which provides a pretty small range for searching the feasible schedule; second, they adopt the pairwise-allocated strategy to assign employees to shifts, where they only need few average proficiency computations instead of computing all employee combinations. The third observation is that the response time of FFS is less than that of FFS-NoPAM . The reason is that, FFS uses the proficiency average matrix to boost the efficiency of the pairwise-allocated strategy. PAM provides the average proficiency of all employees, which prunes the process of computing average proficiency among employees, and PA selects the suitable employee group with only a few computations.

EXP 7: Flextime strategy vs. datasets.

EXP 7 aims to explore the impact of the performance of flextime strategy on different datasets. The result is shown in Fig.  10 a. It is seen that FFS has a higher TOPSIS score than FFS-NOFlextime . The reason is that the flextime strategy sets the flexible work time for each employee, which makes the assigned proficiency satisfy the workloads of different time periods in a fine-grained way. Then more satisfying workloads will present with higher TOPSIS scores.

TOPSIS score of FFS by varying parameters.

EXP 8: Flextime strategy vs. the number of employees

The eighth set of experiments aims to explore the impact of the performance of the flextime strategy by varying the number of employees. The result is shown in Fig.  10 b. Similar to EXP7, FFS has a better TOPSIS score than FFS-NoFlextime , and it is because that FFS adopts the flextime strategy to adjust the work time of employees for each day, the understaffing and overstaffing phenomenons have been improved.

Related work

Employee scheduling problem is of significant importance in industries, such as healthcare, retail, and manufacturing. It made a great deal of progress in the past decades, and can be classified into three categories.

The first category is the mathematical methods, which model their employee scheduling problems and adopt open solvers such as LP 24 , 25 , IP 26 , 27 and MIP 28 solvers to generate feasible schedules. Basán et al. 29 proposed a novel MILP-based decomposition method, for solving employee scheduling problems arising in manufacturing environments. However, this method requires a large amount of domain knowledge to model the problem. Meng et al. 12 proposed four mixed integer linear programming (MILP) models as well as a constraint programming (CP) model to address the distributed flexible job shop scheduling problem with minimizing optimization goals. However, these works stressed the global result of the optimization objectives, but ignored the balance between the local result of each optimization objective on each day. Lunardi et al. 30 present mixed integer linear programming and constraint programming models to address a flexible job shop scheduling problem with sequence flexibility in which precedence constraints among operations of a job. Although this work is performed well on small, medium, and large-sized instances, it generates the schedule with a one-day scheduling horizon, which arises in certain scenarios. A longer scheduling horizon (i.e. a week, a month, or longer) is a more regular phenomenon for most scenarios, and it means more difficult challenges such as temporal constraints. Our approach sets the hard constraints for these temporal constraints, and adopts a series of strategies to address the employee scheduling problem effectively and efficiently.

Although this category of the method has high effectiveness, a large amount of computation leads to low efficiency and high responding time. These methods do not provide the allocated strategy and search strategy as FFS does, and limit themselves to similar trips or other mathematical methods.

The second category is the meta-heuristic algorithm (MHA), which is one type of general algorithm and is suitable for solving most employee scheduling problems. Hence it has been treated as one of the most used algorithms 31 – 33 . Plenty of meta-heuristic algorithms have been developed for searching the PARETO solutions and attracted an increasing number of interests 34 , 35 . The Non-dominated Sorting Genetic Algorithm (NSGA-II 19 ) and Multi-objective Evolutionary algorithm based on decomposition (MOEA/D 9 ) are two classical MHAs. The PARETO-based rank and crowding distance are proposed to assign the fitness values to each individual, while MOEA/D transforms a multi-objective optimization problem into several single-objective sub-problems, then EA searches the optimal solutions of these sub-problems in parallel 36 . Yuan et al. 37 proposed an improved Non-dominated Sorting Genetic Algorithm (NSGA-II) algorithm, which presents a novel evaluation function based on ranking level and crowding degree, then the variable proportion-based elitist retention is designed to help generate the optimal solution. However, this method continues to require a large number of generation operations for generating stable and high-quality PARETO solutions. Wang et al. 38 proposed a hybrid multi-objective evolutionary algorithm based on decomposition (HMOEA/D) to solve the problem. They set a cooperative search operator to generate new solutions, and design an adaptive selection strategy based on the reference point for using the local search operators to enhance exploitation ability.

However, MHAs usually have high time complexity, and due to the randomness of initial conditions and search strategy, they often need to run repeatedly to generate relatively stable results. Our approach adopts the pairwsie-allocated strategy to search for a high-quality schedule, establishes a proficiency average matrix to boost its efficiency, and optimizes the quality of the schedule by flextime strategy.

The third category is the heuristic method, which usually is designed for specific problems. It adopts a series of heuristic strategies to reduce the search space, which aims to speed up the search efficiency and is required to lose part of the result quality. Li et al. 39 propose a hybrid of iterated greedy and simulated annealing algorithms (IGSA algorithm) to address the flexible scheduling problem, where an improved construction heuristic considering the problem features is proposed to balance the exploration abilities and time complexity. Alzaqebah et al. 40 present an improved Bee Colony Optimization algorithm for the flexible work time scheduling problem, where a self-adaptive mechanism is used to adaptively select the neighborhood structure to enhance the local intensification capability of the algorithm and to help the algorithm escape from a local optimum. However, this method requires a large number of iteration operations to ensure the feasibility of the generated schedule, which is time-consuming. Khaniyev et al. 41 address the operating room scheduling problem with the conflicting priorities and preferences of various stakeholders and the inherent uncertainty of surgery duration. They propose a hybrid heuristic algorithm, which defines the objective function in terms of auxiliary functions with a recursive pattern to exactly analyze the optimal surgery duration. However, this method needs too much domain knowledge to build the heuristic models, and high time consumption.

However, heuristic algorithms can be used to solve specific problems, when the problem is changed, the existing algorithm may not be suitable for the new one.

This paper proposes FFS , a polynomial-time solution for soft work time scheduling problems. FFS uses the pairwise-allocated strategy to pre-estimate the number of employees for each shift of each day, which effectively shrinks the number of potential assignments, and the proficiency average matrix is established for boosting its efficiency. In addition, it proposes the flextime strategy to decide the soft work time of each employee for each day, which makes the assigned proficiency satisfy the workload of each time period for each day better. Extensive experimental evaluation shows that FFS is more effective and efficient than the baselines (i.e. MILP , IPSO and MOEAD ), as EXP1-EXP6 shows. Besides, we test the performance of flextime-strategy in improving the effectiveness of FFS , as EXP7-EXP8 shows. Hence, FFS outperforms the state-of-the-art in our problem.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 82011530399), the Zhejiang Province Key Research and Development Program (Grant No. 2021C01189), Leading talents of Science and Technology Innovation in Zhejiang Province (Grant No. 2020R52042), Zhejiang-Netherlands Joint Laboratory for Digital Diagnosis and Treatment of oral diseases, and Major Scientific Research Innovation (team) Project “Research and Application of Multi-objective Collaborative Intelligent Control Method”.

Author contributions

K.M.: Conceptualization, Investigation, Methodology, Data curation, Validation, and Writing-Original draft preparation. C.Y.: Data curation, Validation, Supervisor, Resources, Funding acquisition, and Writing-Reviewing and Editing. H.X.: Resources, Validation, Funding Acquisition, and Reviewing. H.L.: Resources, Funding acquisition and Validation. F.H.: Methodology, Validation, Data curation, Supervision, Funding acquisition, and Writing-Reviewing and Editing.

Data availibility

Competing interests.

The authors declare no competing interests.

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