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What Are Problem-Solving Skills?

Definition & Examples of Problem-Solving Skills

technical and problem solving skills

  • Problem-solving skills help you determine why an issue is happening and how to resolve that issue.

Learn more about problem-solving skills and how they work.

Problem-solving skills help you solve issues quickly and effectively. It's one of the  key skills that employers  seek in job applicants, as employees with these skills tend to be self-reliant. Problem-solving skills require quickly identifying the underlying issue and implementing a solution.

Problem-solving is considered a  soft skill  (a personal strength) rather than a hard skill that's learned through education or training. You can improve your problem-solving skills by familiarizing yourself with common issues in your industry and learning from more experienced employees.

How Problem-Solving Skills Work

Problem-solving starts with identifying the issue. For example, a teacher might need to figure out how to improve student performance on a writing proficiency test. To do that, the teacher will review the writing tests looking for areas of improvement. They might see that students can construct simple sentences, but they're struggling with writing paragraphs and organizing those paragraphs into an essay.

To solve the problem, the teacher would work with students on how and when to write compound sentences, how to write paragraphs, and ways to organize an essay.

Theresa Chiechi / The Balance

There are five steps typically used in problem-solving.

1. Analyze Contributing Factors

To solve a problem, you must find out what caused it. This requires you to gather and evaluate data, isolate possible contributing circumstances, and pinpoint what needs to be addressed for a resolution.

To do this, you'll use skills like :

  • Data gathering
  • Data analysis
  • Fact-finding
  • Historical analysis

2. Generate Interventions

Once you’ve determined the cause, brainstorm possible solutions. Sometimes this involves teamwork since two (or more) minds are often better than one. A single strategy is rarely the obvious route to solving a complex problem; devising a set of alternatives helps you cover your bases and reduces your risk of exposure should the first strategy you implement fail.

This involves skills like :

  • Brainstorming
  • Creative thinking
  • Forecasting
  • Project design
  • Project planning

3. Evaluate Solutions

Depending on the nature of the problem and your chain of command, evaluating best solutions may be performed by assigned teams, team leads, or forwarded to corporate decision-makers. Whoever makes the decision must evaluate potential costs, required resources, and possible barriers to successful solution implementation.

This requires several skills, including:

  • Corroboration
  • Test development
  • Prioritizing

4. Implement a Plan

Once a course of action has been decided, it must be implemented along with benchmarks that can quickly and accurately determine whether it’s working. Plan implementation also involves letting personnel know about changes in standard operating procedures.

This requires skills like:

  • Project management
  • Project implementation
  • Collaboration
  • Time management
  • Benchmark development

5. Assess the Solution's Effectiveness

Once a solution is implemented, the best problem-solvers have systems in place to evaluate if and how quickly it's working. This way, they know as soon as possible whether the issue has been resolved or whether they’ll have to change their response to the problem mid-stream.

This requires:

  • Communication
  • Customer feedback
  • Follow-through
  • Troubleshooting

Here's an example of showing your problem-solving skills in a cover letter.

When I was first hired as a paralegal, I inherited a backlog of 25 sets of medical records that needed to be summarized, each of which was hundreds of pages long. At the same time, I had to help prepare for three major cases, and there weren’t enough hours in the day. After I explained the problem to my supervisor, she agreed to pay me to come in on Saturday mornings to focus on the backlog. I was able to eliminate the backlog in a month.

Here's another example of how to show your problem-solving skills in a cover letter:

When I joined the team at Great Graphics as Artistic Director, the designers had become uninspired because of a former director who attempted to micro-manage every step in the design process. I used weekly round-table discussions to solicit creative input and ensured that each designer was given full autonomy to do their best work. I also introduced monthly team-based competitions that helped build morale, spark new ideas, and improve collaboration.

Highlighting Problem-Solving Skills

  • Since this is a skill that's important to most employers, put them front and center on your resume, cover letter, and in interviews.

If you're not sure what to include, look to previous roles—whether in academic, work, or volunteer settings—for examples of challenges you met and problems you solved. Highlight relevant examples in your  cover letter and use bullet points in your resume to show how you solved a problem.

During interviews, be ready to describe situations you've encountered in previous roles, the processes you followed to address problems, the skills you applied, and the results of your actions. Potential employers are eager to hear a  coherent narrative of the ways you've used problem-solving skills .

Interviewers may pose hypothetical problems for you to solve. Base your answers on the five steps and refer to similar problems you've resolved, if possible. Here are tips for answering problem-solving interview questions , with examples of the best answers.

Key Takeaways

  • It's one of the key skills that employers seek in job applicants.
  • Problem-solving starts with identifying the issue, coming up with solutions, implementing those solutions, and evaluating their effectiveness. 

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What Are Problem-Solving Skills? (Definition, Examples, And How To List On A Resume)

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Summary. Problem-solving skills include analysis, creativity, prioritization, organization, and troubleshooting. To solve a problem, you need to use a variety of skills based on the needs of the situation.

Most jobs essentially boil down to identifying and solving problems consistently and effectively. That’s why employers value problem-solving skills in job candidates for just about every role.

We’ll cover problem-solving methods, ways to improve your problem-solving skills, and examples of showcasing your problem-solving skills during your job search .

Key Takeaways:

If you can show off your problem-solving skills on your resume , in your cover letter , and during a job interview, you’ll be one step closer to landing a job.

Companies rely on employees who can handle unexpected challenges, identify persistent issues, and offer workable solutions in a positive way.

It is important to improve problem solving skill because this is a skill that can be cultivated and nurtured so you can become better at dealing with problems over time.

What are problem solving skills (definition, examples, and how to list on a resume)

Types of Problem-Solving Skills

How to improve your problem-solving skills, example answers to problem-solving interview questions, how to show off problem-solving skills on a resume, example resume and cover letter with problem-solving skills, more about problem-solving skills, problem solving skills faqs.

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Problem-solving skills are skills that help you identify and solve problems effectively and efficiently . Your ability to solve problems is one of the main ways that hiring managers and recruiters assess candidates, as those with excellent problem-solving skills are more likely to autonomously carry out their responsibilities.

A true problem solver can look at a situation, find the cause of the problem (or causes, because there are often many issues at play), and then come up with a reasonable solution that effectively fixes the problem or at least remedies most of it.

The ability to solve problems is considered a soft skill , meaning that it’s more of a personality trait than a skill you’ve learned at school, on the job, or through technical training.

That being said, your proficiency with various hard skills will have a direct bearing on your ability to solve problems. For example, it doesn’t matter if you’re a great problem-solver; if you have no experience with astrophysics, you probably won’t be hired as a space station technician .

Problem-solving is considered a skill on its own, but it’s supported by many other skills that can help you be a better problem solver. These skills fall into a few different categories of problem-solving skills.

Problem recognition and analysis. The first step is to recognize that there is a problem and discover what it is or what the root cause of it is.

You can’t begin to solve a problem unless you’re aware of it. Sometimes you’ll see the problem yourself and other times you’ll be told about the problem. Both methods of discovery are very important, but they can require some different skills. The following can be an important part of the process:

Active listening

Data analysis

Historical analysis

Communication

Create possible solutions. You know what the problem is, and you might even know the why of it, but then what? Your next step is the come up with some solutions.

Most of the time, the first solution you come up with won’t be the right one. Don’t fall victim to knee-jerk reactions; try some of the following methods to give you solution options.

Brainstorming

Forecasting

Decision-making

Topic knowledge/understanding

Process flow

Evaluation of solution options. Now that you have a lot of solution options, it’s time to weed through them and start casting some aside. There might be some ridiculous ones, bad ones, and ones you know could never be implemented. Throw them away and focus on the potentially winning ideas.

This step is probably the one where a true, natural problem solver will shine. They intuitively can put together mental scenarios and try out solutions to see their plusses and minuses. If you’re still working on your skill set — try listing the pros and cons on a sheet of paper.

Prioritizing

Evaluating and weighing

Solution implementation. This is your “take action” step. Once you’ve decided which way to go, it’s time to head down that path and see if you were right. This step takes a lot of people and management skills to make it work for you.

Dependability

Teambuilding

Troubleshooting

Follow-Through

Believability

Trustworthiness

Project management

Evaluation of the solution. Was it a good solution? Did your plan work or did it fail miserably? Sometimes the evaluation step takes a lot of work and review to accurately determine effectiveness. The following skills might be essential for a thorough evaluation.

Customer service

Feedback responses

Flexibility

You now have a ton of skills in front of you. Some of them you have naturally and some — not so much. If you want to solve a problem, and you want to be known for doing that well and consistently, then it’s time to sharpen those skills.

Develop industry knowledge. Whether it’s broad-based industry knowledge, on-the-job training , or very specific knowledge about a small sector — knowing all that you can and feeling very confident in your knowledge goes a long way to learning how to solve problems.

Be a part of a solution. Step up and become involved in the problem-solving process. Don’t lead — but follow. Watch an expert solve the problem and, if you pay attention, you’ll learn how to solve a problem, too. Pay attention to the steps and the skills that a person uses.

Practice solving problems. Do some role-playing with a mentor , a professor , co-workers, other students — just start throwing problems out there and coming up with solutions and then detail how those solutions may play out.

Go a step further, find some real-world problems and create your solutions, then find out what they did to solve the problem in actuality.

Identify your weaknesses. If you could easily point out a few of your weaknesses in the list of skills above, then those are the areas you need to focus on improving. How you do it is incredibly varied, so find a method that works for you.

Solve some problems — for real. If the opportunity arises, step in and use your problem-solving skills. You’ll never really know how good (or bad) you are at it until you fail.

That’s right, failing will teach you so much more than succeeding will. You’ll learn how to go back and readdress the problem, find out where you went wrong, learn more from listening even better. Failure will be your best teacher ; it might not make you feel good, but it’ll make you a better problem-solver in the long run.

Once you’ve impressed a hiring manager with top-notch problem-solving skills on your resume and cover letter , you’ll need to continue selling yourself as a problem-solver in the job interview.

There are three main ways that employers can assess your problem-solving skills during an interview:

By asking questions that relate to your past experiences solving problems

Posing hypothetical problems for you to solve

By administering problem-solving tests and exercises

The third method varies wildly depending on what job you’re applying for, so we won’t attempt to cover all the possible problem-solving tests and exercises that may be a part of your application process.

Luckily, interview questions focused on problem-solving are pretty well-known, and most can be answered using the STAR method . STAR stands for situation, task, action, result, and it’s a great way to organize your answers to behavioral interview questions .

Let’s take a look at how to answer some common interview questions built to assess your problem-solving capabilities:

At my current job as an operations analyst at XYZ Inc., my boss set a quarterly goal to cut contractor spending by 25% while maintaining the same level of production and moving more processes in-house. It turned out that achieving this goal required hiring an additional 6 full-time employees, which got stalled due to the pandemic. I suggested that we widen our net and hire remote employees after our initial applicant pool had no solid candidates. I ran the analysis on overhead costs and found that if even 4 of the 6 employees were remote, we’d save 16% annually compared to the contractors’ rates. In the end, all 6 employees we hired were fully remote, and we cut costs by 26% while production rose by a modest amount.
I try to step back and gather research as my first step. For instance, I had a client who needed a graphic designer to work with Crello, which I had never seen before, let alone used. After getting the project details straight, I began meticulously studying the program the YouTube tutorials, and the quick course Crello provides. I also reached out to coworkers who had worked on projects for this same client in the past. Once I felt comfortable with the software, I started work immediately. It was a slower process because I had to be more methodical in my approach, but by putting in some extra hours, I turned in the project ahead of schedule. The client was thrilled with my work and was shocked to hear me joke afterward that it was my first time using Crello.
As a digital marketer , website traffic and conversion rates are my ultimate metrics. However, I also track less visible metrics that can illuminate the story behind the results. For instance, using Google Analytics, I found that 78% of our referral traffic was coming from one affiliate, but that these referrals were only accounting for 5% of our conversions. Another affiliate, who only accounted for about 10% of our referral traffic, was responsible for upwards of 30% of our conversions. I investigated further and found that the second, more effective affiliate was essentially qualifying our leads for us before sending them our way, which made it easier for us to close. I figured out exactly how they were sending us better customers, and reached out to the first, more prolific but less effective affiliate with my understanding of the results. They were able to change their pages that were referring us traffic, and our conversions from that source tripled in just a month. It showed me the importance of digging below the “big picture” metrics to see the mechanics of how revenue was really being generated through digital marketing.

You can bring up your problem-solving skills in your resume summary statement , in your work experience , and under your education section , if you’re a recent graduate. The key is to include items on your resume that speak direclty to your ability to solve problems and generate results.

If you can, quantify your problem-solving accomplishments on your your resume . Hiring managers and recruiters are always more impressed with results that include numbers because they provide much-needed context.

This sample resume for a Customer Service Representative will give you an idea of how you can work problem solving into your resume.

Michelle Beattle 111 Millennial Parkway Chicago, IL 60007 (555) 987-6543 [email protected] Professional Summary Qualified Customer Services Representative with 3 years in a high-pressure customer service environment. Professional, personable, and a true problem solver. Work History ABC Store — Customer Service Representative 01/2015 — 12/2017 Managed in-person and phone relations with customers coming in to pick up purchases, return purchased products, helped find and order items not on store shelves, and explained details and care of merchandise. Became a key player in the customer service department and was promoted to team lead. XYZ Store — Customer Service Representative/Night Manager 01/2018 — 03/2020, released due to Covid-19 layoffs Worked as the night manager of the customer service department and filled in daytime hours when needed. Streamlined a process of moving customers to the right department through an app to ease the burden on the phone lines and reduce customer wait time by 50%. Was working on additional wait time problems when the Covid-19 pandemic caused our stores to close permanently. Education Chicago Tech 2014-2016 Earned an Associate’s Degree in Principles of Customer Care Skills Strong customer service skills Excellent customer complaint resolution Stock record management Order fulfillment New product information Cash register skills and proficiency Leader in problem solving initiatives

You can see how the resume gives you a chance to point out your problem-solving skills and to show where you used them a few times. Your cover letter is your chance to introduce yourself and list a few things that make you stand out from the crowd.

Michelle Beattle 111 Millennial Parkway Chicago, IL 60007 (555) 987-6543 [email protected] Dear Mary McDonald, I am writing in response to your ad on Zippia for a Customer Service Representative . Thank you for taking the time to consider me for this position. Many people believe that a job in customer service is simply listening to people complain all day. I see the job as much more than that. It’s an opportunity to help people solve problems, make their experience with your company more enjoyable, and turn them into life-long advocates of your brand. Through my years of experience and my educational background at Chicago Tech, where I earned an Associate’s Degree in the Principles of Customer Care, I have learned that the customers are the lifeline of the business and without good customer service representatives, a business will falter. I see it as my mission to make each and every customer I come in contact with a fan. I have more than five years of experience in the Customer Services industry and had advanced my role at my last job to Night Manager. I am eager to again prove myself as a hard worker, a dedicated people person, and a problem solver that can be relied upon. I have built a professional reputation as an employee that respects all other employees and customers, as a manager who gets the job done and finds solutions when necessary, and a worker who dives in to learn all she can about the business. Most of my customers have been very satisfied with my resolution ideas and have returned to do business with us again. I believe my expertise would make me a great match for LMNO Store. I have enclosed my resume for your review, and I would appreciate having the opportunity to meet with you to further discuss my qualifications. Thank you again for your time and consideration. Sincerely, Michelle Beattle

You’ve no doubt noticed that many of the skills listed in the problem-solving process are repeated. This is because having these abilities or talents is so important to the entire course of getting a problem solved.

In fact, they’re worthy of a little more attention. Many of them are similar, so we’ll pull them together and discuss how they’re important and how they work together.

Communication, active listening, and customer service skills. No matter where you are in the process of problem-solving, you need to be able to show that you’re listening and engaged and really hearing what the problem is or what a solution may be.

Obviously, the other part of this is being able to communicate effectively so people understand what you’re saying without confusion. Rolled into this are customer service skills , which really are all about listening and responding appropriately — it’s the ultimate in interpersonal communications.

Analysis (data and historical), research, and topic knowledge/understanding. This is how you intellectually grasp the issue and approach it. This can come from studying the topic and the process or it can come from knowledge you’ve gained after years in the business. But the best solutions come from people who thoroughly understand the problem.

Creativity, brainstorming, troubleshooting, and flexibility. All of you creative thinkers will like this area because it’s when your brain is at its best.

Coming up with ideas, collaborating with others, leaping over hurdles, and then being able to change courses immediately, if need be, are all essential. If you’re not creative by nature, then having a team of diverse thinkers can help you in this area.

Dependability, believability, trustworthiness, and follow-through. Think about it, these are all traits a person needs to have to make change happen and to make you comfortable taking that next step with them. Someone who is shifty and shady and never follows through, well, you’re simply not going to do what they ask, are you?

Leadership, teambuilding, decision-making, and project management. These are the skills that someone who is in charge is brimming with. These are the leaders you enjoy working for because you know they’re doing what they can to keep everything in working order. These skills can be learned but they’re often innate.

Prioritizing, prediction, forecasting, evaluating and weighing, and process flow. If you love flow charts, data analysis, prediction modeling, and all of that part of the equation, then you might have some great problem-solving abilities.

These are all great skills because they can help you weed out bad ideas, see flaws, and save massive amounts of time in trial and error.

What is a good example of problem-solving skills?

Good examples of porblem-solving skills include research, analysis, creativity, communciation, and decision-making. Each of these skills build off one another to contribute to the problem solving process. Research and analysis allow you to identify a problem.

Creativity and analysis help you consider different solutions. Meanwhile, communication and decision-making are key to working with others to solve a problem on a large scale.

What are 3 key attributes of a good problem solver?

3 key attributes of a good problem solver are persistence, intellegince, and empathy. Persistence is crucial to remain motivated to work through challenges. Inellegince is needed to make smart, informed choices. Empathy is crucial to maintain positive relationships with others as well as yourself.

What can I say instead of problem-solving skills?

Instead of saying problem-solving skills, you can say the following:

Critical thinker

Solutions-oriented

Engineering

Using different words is helpful, especially when writing your resume and cover letter.

What is problem-solving in the workplace?

Problem-solving in the workplace is the ability to work through any sort of challenge, conflict, or unexpected situation and still achieve business goals. Though it varies by profession, roblem-solving in the workplace is very important for almost any job, because probelms are inevitable. You need to have the appropriate level of problem-solving skills if you want to succeed in your career, whatever it may be.

Department of Labor – Problem Solving and Critical Thinking

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Kristin Kizer is an award-winning writer, television and documentary producer, and content specialist who has worked on a wide variety of written, broadcast, and electronic publications. A former writer/producer for The Discovery Channel, she is now a freelance writer and delighted to be sharing her talents and time with the wonderful Zippia audience.

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35 problem-solving techniques and methods for solving complex problems

Problem solving workshop

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All teams and organizations encounter challenges as they grow. There are problems that might occur for teams when it comes to miscommunication or resolving business-critical issues . You may face challenges around growth , design , user engagement, and even team culture and happiness. In short, problem-solving techniques should be part of every team’s skillset.

Problem-solving methods are primarily designed to help a group or team through a process of first identifying problems and challenges , ideating possible solutions , and then evaluating the most suitable .

Finding effective solutions to complex problems isn’t easy, but by using the right process and techniques, you can help your team be more efficient in the process.

So how do you develop strategies that are engaging, and empower your team to solve problems effectively?

In this blog post, we share a series of problem-solving tools you can use in your next workshop or team meeting. You’ll also find some tips for facilitating the process and how to enable others to solve complex problems.

Let’s get started! 

How do you identify problems?

How do you identify the right solution.

  • Tips for more effective problem-solving

Complete problem-solving methods

  • Problem-solving techniques to identify and analyze problems
  • Problem-solving techniques for developing solutions

Problem-solving warm-up activities

Closing activities for a problem-solving process.

Before you can move towards finding the right solution for a given problem, you first need to identify and define the problem you wish to solve. 

Here, you want to clearly articulate what the problem is and allow your group to do the same. Remember that everyone in a group is likely to have differing perspectives and alignment is necessary in order to help the group move forward. 

Identifying a problem accurately also requires that all members of a group are able to contribute their views in an open and safe manner. It can be scary for people to stand up and contribute, especially if the problems or challenges are emotive or personal in nature. Be sure to try and create a psychologically safe space for these kinds of discussions.

Remember that problem analysis and further discussion are also important. Not taking the time to fully analyze and discuss a challenge can result in the development of solutions that are not fit for purpose or do not address the underlying issue.

Successfully identifying and then analyzing a problem means facilitating a group through activities designed to help them clearly and honestly articulate their thoughts and produce usable insight.

With this data, you might then produce a problem statement that clearly describes the problem you wish to be addressed and also state the goal of any process you undertake to tackle this issue.  

Finding solutions is the end goal of any process. Complex organizational challenges can only be solved with an appropriate solution but discovering them requires using the right problem-solving tool.

After you’ve explored a problem and discussed ideas, you need to help a team discuss and choose the right solution. Consensus tools and methods such as those below help a group explore possible solutions before then voting for the best. They’re a great way to tap into the collective intelligence of the group for great results!

Remember that the process is often iterative. Great problem solvers often roadtest a viable solution in a measured way to see what works too. While you might not get the right solution on your first try, the methods below help teams land on the most likely to succeed solution while also holding space for improvement.

Every effective problem solving process begins with an agenda . A well-structured workshop is one of the best methods for successfully guiding a group from exploring a problem to implementing a solution.

In SessionLab, it’s easy to go from an idea to a complete agenda . Start by dragging and dropping your core problem solving activities into place . Add timings, breaks and necessary materials before sharing your agenda with your colleagues.

The resulting agenda will be your guide to an effective and productive problem solving session that will also help you stay organized on the day!

technical and problem solving skills

Tips for more effective problem solving

Problem-solving activities are only one part of the puzzle. While a great method can help unlock your team’s ability to solve problems, without a thoughtful approach and strong facilitation the solutions may not be fit for purpose.

Let’s take a look at some problem-solving tips you can apply to any process to help it be a success!

Clearly define the problem

Jumping straight to solutions can be tempting, though without first clearly articulating a problem, the solution might not be the right one. Many of the problem-solving activities below include sections where the problem is explored and clearly defined before moving on.

This is a vital part of the problem-solving process and taking the time to fully define an issue can save time and effort later. A clear definition helps identify irrelevant information and it also ensures that your team sets off on the right track.

Don’t jump to conclusions

It’s easy for groups to exhibit cognitive bias or have preconceived ideas about both problems and potential solutions. Be sure to back up any problem statements or potential solutions with facts, research, and adequate forethought.

The best techniques ask participants to be methodical and challenge preconceived notions. Make sure you give the group enough time and space to collect relevant information and consider the problem in a new way. By approaching the process with a clear, rational mindset, you’ll often find that better solutions are more forthcoming.  

Try different approaches  

Problems come in all shapes and sizes and so too should the methods you use to solve them. If you find that one approach isn’t yielding results and your team isn’t finding different solutions, try mixing it up. You’ll be surprised at how using a new creative activity can unblock your team and generate great solutions.

Don’t take it personally 

Depending on the nature of your team or organizational problems, it’s easy for conversations to get heated. While it’s good for participants to be engaged in the discussions, ensure that emotions don’t run too high and that blame isn’t thrown around while finding solutions.

You’re all in it together, and even if your team or area is seeing problems, that isn’t necessarily a disparagement of you personally. Using facilitation skills to manage group dynamics is one effective method of helping conversations be more constructive.

Get the right people in the room

Your problem-solving method is often only as effective as the group using it. Getting the right people on the job and managing the number of people present is important too!

If the group is too small, you may not get enough different perspectives to effectively solve a problem. If the group is too large, you can go round and round during the ideation stages.

Creating the right group makeup is also important in ensuring you have the necessary expertise and skillset to both identify and follow up on potential solutions. Carefully consider who to include at each stage to help ensure your problem-solving method is followed and positioned for success.

Document everything

The best solutions can take refinement, iteration, and reflection to come out. Get into a habit of documenting your process in order to keep all the learnings from the session and to allow ideas to mature and develop. Many of the methods below involve the creation of documents or shared resources. Be sure to keep and share these so everyone can benefit from the work done!

Bring a facilitator 

Facilitation is all about making group processes easier. With a subject as potentially emotive and important as problem-solving, having an impartial third party in the form of a facilitator can make all the difference in finding great solutions and keeping the process moving. Consider bringing a facilitator to your problem-solving session to get better results and generate meaningful solutions!

Develop your problem-solving skills

It takes time and practice to be an effective problem solver. While some roles or participants might more naturally gravitate towards problem-solving, it can take development and planning to help everyone create better solutions.

You might develop a training program, run a problem-solving workshop or simply ask your team to practice using the techniques below. Check out our post on problem-solving skills to see how you and your group can develop the right mental process and be more resilient to issues too!

Design a great agenda

Workshops are a great format for solving problems. With the right approach, you can focus a group and help them find the solutions to their own problems. But designing a process can be time-consuming and finding the right activities can be difficult.

Check out our workshop planning guide to level-up your agenda design and start running more effective workshops. Need inspiration? Check out templates designed by expert facilitators to help you kickstart your process!

In this section, we’ll look at in-depth problem-solving methods that provide a complete end-to-end process for developing effective solutions. These will help guide your team from the discovery and definition of a problem through to delivering the right solution.

If you’re looking for an all-encompassing method or problem-solving model, these processes are a great place to start. They’ll ask your team to challenge preconceived ideas and adopt a mindset for solving problems more effectively.

  • Six Thinking Hats
  • Lightning Decision Jam
  • Problem Definition Process
  • Discovery & Action Dialogue
Design Sprint 2.0
  • Open Space Technology

1. Six Thinking Hats

Individual approaches to solving a problem can be very different based on what team or role an individual holds. It can be easy for existing biases or perspectives to find their way into the mix, or for internal politics to direct a conversation.

Six Thinking Hats is a classic method for identifying the problems that need to be solved and enables your team to consider them from different angles, whether that is by focusing on facts and data, creative solutions, or by considering why a particular solution might not work.

Like all problem-solving frameworks, Six Thinking Hats is effective at helping teams remove roadblocks from a conversation or discussion and come to terms with all the aspects necessary to solve complex problems.

2. Lightning Decision Jam

Featured courtesy of Jonathan Courtney of AJ&Smart Berlin, Lightning Decision Jam is one of those strategies that should be in every facilitation toolbox. Exploring problems and finding solutions is often creative in nature, though as with any creative process, there is the potential to lose focus and get lost.

Unstructured discussions might get you there in the end, but it’s much more effective to use a method that creates a clear process and team focus.

In Lightning Decision Jam, participants are invited to begin by writing challenges, concerns, or mistakes on post-its without discussing them before then being invited by the moderator to present them to the group.

From there, the team vote on which problems to solve and are guided through steps that will allow them to reframe those problems, create solutions and then decide what to execute on. 

By deciding the problems that need to be solved as a team before moving on, this group process is great for ensuring the whole team is aligned and can take ownership over the next stages. 

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

3. Problem Definition Process

While problems can be complex, the problem-solving methods you use to identify and solve those problems can often be simple in design. 

By taking the time to truly identify and define a problem before asking the group to reframe the challenge as an opportunity, this method is a great way to enable change.

Begin by identifying a focus question and exploring the ways in which it manifests before splitting into five teams who will each consider the problem using a different method: escape, reversal, exaggeration, distortion or wishful. Teams develop a problem objective and create ideas in line with their method before then feeding them back to the group.

This method is great for enabling in-depth discussions while also creating space for finding creative solutions too!

Problem Definition   #problem solving   #idea generation   #creativity   #online   #remote-friendly   A problem solving technique to define a problem, challenge or opportunity and to generate ideas.

4. The 5 Whys 

Sometimes, a group needs to go further with their strategies and analyze the root cause at the heart of organizational issues. An RCA or root cause analysis is the process of identifying what is at the heart of business problems or recurring challenges. 

The 5 Whys is a simple and effective method of helping a group go find the root cause of any problem or challenge and conduct analysis that will deliver results. 

By beginning with the creation of a problem statement and going through five stages to refine it, The 5 Whys provides everything you need to truly discover the cause of an issue.

The 5 Whys   #hyperisland   #innovation   This simple and powerful method is useful for getting to the core of a problem or challenge. As the title suggests, the group defines a problems, then asks the question “why” five times, often using the resulting explanation as a starting point for creative problem solving.

5. World Cafe

World Cafe is a simple but powerful facilitation technique to help bigger groups to focus their energy and attention on solving complex problems.

World Cafe enables this approach by creating a relaxed atmosphere where participants are able to self-organize and explore topics relevant and important to them which are themed around a central problem-solving purpose. Create the right atmosphere by modeling your space after a cafe and after guiding the group through the method, let them take the lead!

Making problem-solving a part of your organization’s culture in the long term can be a difficult undertaking. More approachable formats like World Cafe can be especially effective in bringing people unfamiliar with workshops into the fold. 

World Cafe   #hyperisland   #innovation   #issue analysis   World Café is a simple yet powerful method, originated by Juanita Brown, for enabling meaningful conversations driven completely by participants and the topics that are relevant and important to them. Facilitators create a cafe-style space and provide simple guidelines. Participants then self-organize and explore a set of relevant topics or questions for conversation.

6. Discovery & Action Dialogue (DAD)

One of the best approaches is to create a safe space for a group to share and discover practices and behaviors that can help them find their own solutions.

With DAD, you can help a group choose which problems they wish to solve and which approaches they will take to do so. It’s great at helping remove resistance to change and can help get buy-in at every level too!

This process of enabling frontline ownership is great in ensuring follow-through and is one of the methods you will want in your toolbox as a facilitator.

Discovery & Action Dialogue (DAD)   #idea generation   #liberating structures   #action   #issue analysis   #remote-friendly   DADs make it easy for a group or community to discover practices and behaviors that enable some individuals (without access to special resources and facing the same constraints) to find better solutions than their peers to common problems. These are called positive deviant (PD) behaviors and practices. DADs make it possible for people in the group, unit, or community to discover by themselves these PD practices. DADs also create favorable conditions for stimulating participants’ creativity in spaces where they can feel safe to invent new and more effective practices. Resistance to change evaporates as participants are unleashed to choose freely which practices they will adopt or try and which problems they will tackle. DADs make it possible to achieve frontline ownership of solutions.

7. Design Sprint 2.0

Want to see how a team can solve big problems and move forward with prototyping and testing solutions in a few days? The Design Sprint 2.0 template from Jake Knapp, author of Sprint, is a complete agenda for a with proven results.

Developing the right agenda can involve difficult but necessary planning. Ensuring all the correct steps are followed can also be stressful or time-consuming depending on your level of experience.

Use this complete 4-day workshop template if you are finding there is no obvious solution to your challenge and want to focus your team around a specific problem that might require a shortcut to launching a minimum viable product or waiting for the organization-wide implementation of a solution.

8. Open space technology

Open space technology- developed by Harrison Owen – creates a space where large groups are invited to take ownership of their problem solving and lead individual sessions. Open space technology is a great format when you have a great deal of expertise and insight in the room and want to allow for different takes and approaches on a particular theme or problem you need to be solved.

Start by bringing your participants together to align around a central theme and focus their efforts. Explain the ground rules to help guide the problem-solving process and then invite members to identify any issue connecting to the central theme that they are interested in and are prepared to take responsibility for.

Once participants have decided on their approach to the core theme, they write their issue on a piece of paper, announce it to the group, pick a session time and place, and post the paper on the wall. As the wall fills up with sessions, the group is then invited to join the sessions that interest them the most and which they can contribute to, then you’re ready to begin!

Everyone joins the problem-solving group they’ve signed up to, record the discussion and if appropriate, findings can then be shared with the rest of the group afterward.

Open Space Technology   #action plan   #idea generation   #problem solving   #issue analysis   #large group   #online   #remote-friendly   Open Space is a methodology for large groups to create their agenda discerning important topics for discussion, suitable for conferences, community gatherings and whole system facilitation

Techniques to identify and analyze problems

Using a problem-solving method to help a team identify and analyze a problem can be a quick and effective addition to any workshop or meeting.

While further actions are always necessary, you can generate momentum and alignment easily, and these activities are a great place to get started.

We’ve put together this list of techniques to help you and your team with problem identification, analysis, and discussion that sets the foundation for developing effective solutions.

Let’s take a look!

  • The Creativity Dice
  • Fishbone Analysis
  • Problem Tree
  • SWOT Analysis
  • Agreement-Certainty Matrix
  • The Journalistic Six
  • LEGO Challenge
  • What, So What, Now What?
  • Journalists

Individual and group perspectives are incredibly important, but what happens if people are set in their minds and need a change of perspective in order to approach a problem more effectively?

Flip It is a method we love because it is both simple to understand and run, and allows groups to understand how their perspectives and biases are formed. 

Participants in Flip It are first invited to consider concerns, issues, or problems from a perspective of fear and write them on a flip chart. Then, the group is asked to consider those same issues from a perspective of hope and flip their understanding.  

No problem and solution is free from existing bias and by changing perspectives with Flip It, you can then develop a problem solving model quickly and effectively.

Flip It!   #gamestorming   #problem solving   #action   Often, a change in a problem or situation comes simply from a change in our perspectives. Flip It! is a quick game designed to show players that perspectives are made, not born.

10. The Creativity Dice

One of the most useful problem solving skills you can teach your team is of approaching challenges with creativity, flexibility, and openness. Games like The Creativity Dice allow teams to overcome the potential hurdle of too much linear thinking and approach the process with a sense of fun and speed. 

In The Creativity Dice, participants are organized around a topic and roll a dice to determine what they will work on for a period of 3 minutes at a time. They might roll a 3 and work on investigating factual information on the chosen topic. They might roll a 1 and work on identifying the specific goals, standards, or criteria for the session.

Encouraging rapid work and iteration while asking participants to be flexible are great skills to cultivate. Having a stage for idea incubation in this game is also important. Moments of pause can help ensure the ideas that are put forward are the most suitable. 

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.

11. Fishbone Analysis

Organizational or team challenges are rarely simple, and it’s important to remember that one problem can be an indication of something that goes deeper and may require further consideration to be solved.

Fishbone Analysis helps groups to dig deeper and understand the origins of a problem. It’s a great example of a root cause analysis method that is simple for everyone on a team to get their head around. 

Participants in this activity are asked to annotate a diagram of a fish, first adding the problem or issue to be worked on at the head of a fish before then brainstorming the root causes of the problem and adding them as bones on the fish. 

Using abstractions such as a diagram of a fish can really help a team break out of their regular thinking and develop a creative approach.

Fishbone Analysis   #problem solving   ##root cause analysis   #decision making   #online facilitation   A process to help identify and understand the origins of problems, issues or observations.

12. Problem Tree 

Encouraging visual thinking can be an essential part of many strategies. By simply reframing and clarifying problems, a group can move towards developing a problem solving model that works for them. 

In Problem Tree, groups are asked to first brainstorm a list of problems – these can be design problems, team problems or larger business problems – and then organize them into a hierarchy. The hierarchy could be from most important to least important or abstract to practical, though the key thing with problem solving games that involve this aspect is that your group has some way of managing and sorting all the issues that are raised.

Once you have a list of problems that need to be solved and have organized them accordingly, you’re then well-positioned for the next problem solving steps.

Problem tree   #define intentions   #create   #design   #issue analysis   A problem tree is a tool to clarify the hierarchy of problems addressed by the team within a design project; it represents high level problems or related sublevel problems.

13. SWOT Analysis

Chances are you’ve heard of the SWOT Analysis before. This problem-solving method focuses on identifying strengths, weaknesses, opportunities, and threats is a tried and tested method for both individuals and teams.

Start by creating a desired end state or outcome and bare this in mind – any process solving model is made more effective by knowing what you are moving towards. Create a quadrant made up of the four categories of a SWOT analysis and ask participants to generate ideas based on each of those quadrants.

Once you have those ideas assembled in their quadrants, cluster them together based on their affinity with other ideas. These clusters are then used to facilitate group conversations and move things forward. 

SWOT analysis   #gamestorming   #problem solving   #action   #meeting facilitation   The SWOT Analysis is a long-standing technique of looking at what we have, with respect to the desired end state, as well as what we could improve on. It gives us an opportunity to gauge approaching opportunities and dangers, and assess the seriousness of the conditions that affect our future. When we understand those conditions, we can influence what comes next.

14. Agreement-Certainty Matrix

Not every problem-solving approach is right for every challenge, and deciding on the right method for the challenge at hand is a key part of being an effective team.

The Agreement Certainty matrix helps teams align on the nature of the challenges facing them. By sorting problems from simple to chaotic, your team can understand what methods are suitable for each problem and what they can do to ensure effective results. 

If you are already using Liberating Structures techniques as part of your problem-solving strategy, the Agreement-Certainty Matrix can be an invaluable addition to your process. We’ve found it particularly if you are having issues with recurring problems in your organization and want to go deeper in understanding the root cause. 

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.

Organizing and charting a team’s progress can be important in ensuring its success. SQUID (Sequential Question and Insight Diagram) is a great model that allows a team to effectively switch between giving questions and answers and develop the skills they need to stay on track throughout the process. 

Begin with two different colored sticky notes – one for questions and one for answers – and with your central topic (the head of the squid) on the board. Ask the group to first come up with a series of questions connected to their best guess of how to approach the topic. Ask the group to come up with answers to those questions, fix them to the board and connect them with a line. After some discussion, go back to question mode by responding to the generated answers or other points on the board.

It’s rewarding to see a diagram grow throughout the exercise, and a completed SQUID can provide a visual resource for future effort and as an example for other teams.

SQUID   #gamestorming   #project planning   #issue analysis   #problem solving   When exploring an information space, it’s important for a group to know where they are at any given time. By using SQUID, a group charts out the territory as they go and can navigate accordingly. SQUID stands for Sequential Question and Insight Diagram.

16. Speed Boat

To continue with our nautical theme, Speed Boat is a short and sweet activity that can help a team quickly identify what employees, clients or service users might have a problem with and analyze what might be standing in the way of achieving a solution.

Methods that allow for a group to make observations, have insights and obtain those eureka moments quickly are invaluable when trying to solve complex problems.

In Speed Boat, the approach is to first consider what anchors and challenges might be holding an organization (or boat) back. Bonus points if you are able to identify any sharks in the water and develop ideas that can also deal with competitors!   

Speed Boat   #gamestorming   #problem solving   #action   Speedboat is a short and sweet way to identify what your employees or clients don’t like about your product/service or what’s standing in the way of a desired goal.

17. The Journalistic Six

Some of the most effective ways of solving problems is by encouraging teams to be more inclusive and diverse in their thinking.

Based on the six key questions journalism students are taught to answer in articles and news stories, The Journalistic Six helps create teams to see the whole picture. By using who, what, when, where, why, and how to facilitate the conversation and encourage creative thinking, your team can make sure that the problem identification and problem analysis stages of the are covered exhaustively and thoughtfully. Reporter’s notebook and dictaphone optional.

The Journalistic Six – Who What When Where Why How   #idea generation   #issue analysis   #problem solving   #online   #creative thinking   #remote-friendly   A questioning method for generating, explaining, investigating ideas.

18. LEGO Challenge

Now for an activity that is a little out of the (toy) box. LEGO Serious Play is a facilitation methodology that can be used to improve creative thinking and problem-solving skills. 

The LEGO Challenge includes giving each member of the team an assignment that is hidden from the rest of the group while they create a structure without speaking.

What the LEGO challenge brings to the table is a fun working example of working with stakeholders who might not be on the same page to solve problems. Also, it’s LEGO! Who doesn’t love LEGO! 

LEGO Challenge   #hyperisland   #team   A team-building activity in which groups must work together to build a structure out of LEGO, but each individual has a secret “assignment” which makes the collaborative process more challenging. It emphasizes group communication, leadership dynamics, conflict, cooperation, patience and problem solving strategy.

19. What, So What, Now What?

If not carefully managed, the problem identification and problem analysis stages of the problem-solving process can actually create more problems and misunderstandings.

The What, So What, Now What? problem-solving activity is designed to help collect insights and move forward while also eliminating the possibility of disagreement when it comes to identifying, clarifying, and analyzing organizational or work problems. 

Facilitation is all about bringing groups together so that might work on a shared goal and the best problem-solving strategies ensure that teams are aligned in purpose, if not initially in opinion or insight.

Throughout the three steps of this game, you give everyone on a team to reflect on a problem by asking what happened, why it is important, and what actions should then be taken. 

This can be a great activity for bringing our individual perceptions about a problem or challenge and contextualizing it in a larger group setting. This is one of the most important problem-solving skills you can bring to your organization.

W³ – What, So What, Now What?   #issue analysis   #innovation   #liberating structures   You can help groups reflect on a shared experience in a way that builds understanding and spurs coordinated action while avoiding unproductive conflict. It is possible for every voice to be heard while simultaneously sifting for insights and shaping new direction. Progressing in stages makes this practical—from collecting facts about What Happened to making sense of these facts with So What and finally to what actions logically follow with Now What . The shared progression eliminates most of the misunderstandings that otherwise fuel disagreements about what to do. Voila!

20. Journalists  

Problem analysis can be one of the most important and decisive stages of all problem-solving tools. Sometimes, a team can become bogged down in the details and are unable to move forward.

Journalists is an activity that can avoid a group from getting stuck in the problem identification or problem analysis stages of the process.

In Journalists, the group is invited to draft the front page of a fictional newspaper and figure out what stories deserve to be on the cover and what headlines those stories will have. By reframing how your problems and challenges are approached, you can help a team move productively through the process and be better prepared for the steps to follow.

Journalists   #vision   #big picture   #issue analysis   #remote-friendly   This is an exercise to use when the group gets stuck in details and struggles to see the big picture. Also good for defining a vision.

Problem-solving techniques for developing solutions 

The success of any problem-solving process can be measured by the solutions it produces. After you’ve defined the issue, explored existing ideas, and ideated, it’s time to narrow down to the correct solution.

Use these problem-solving techniques when you want to help your team find consensus, compare possible solutions, and move towards taking action on a particular problem.

  • Improved Solutions
  • Four-Step Sketch
  • 15% Solutions
  • How-Now-Wow matrix
  • Impact Effort Matrix

21. Mindspin  

Brainstorming is part of the bread and butter of the problem-solving process and all problem-solving strategies benefit from getting ideas out and challenging a team to generate solutions quickly. 

With Mindspin, participants are encouraged not only to generate ideas but to do so under time constraints and by slamming down cards and passing them on. By doing multiple rounds, your team can begin with a free generation of possible solutions before moving on to developing those solutions and encouraging further ideation. 

This is one of our favorite problem-solving activities and can be great for keeping the energy up throughout the workshop. Remember the importance of helping people become engaged in the process – energizing problem-solving techniques like Mindspin can help ensure your team stays engaged and happy, even when the problems they’re coming together to solve are complex. 

MindSpin   #teampedia   #idea generation   #problem solving   #action   A fast and loud method to enhance brainstorming within a team. Since this activity has more than round ideas that are repetitive can be ruled out leaving more creative and innovative answers to the challenge.

22. Improved Solutions

After a team has successfully identified a problem and come up with a few solutions, it can be tempting to call the work of the problem-solving process complete. That said, the first solution is not necessarily the best, and by including a further review and reflection activity into your problem-solving model, you can ensure your group reaches the best possible result. 

One of a number of problem-solving games from Thiagi Group, Improved Solutions helps you go the extra mile and develop suggested solutions with close consideration and peer review. By supporting the discussion of several problems at once and by shifting team roles throughout, this problem-solving technique is a dynamic way of finding the best solution. 

Improved Solutions   #creativity   #thiagi   #problem solving   #action   #team   You can improve any solution by objectively reviewing its strengths and weaknesses and making suitable adjustments. In this creativity framegame, you improve the solutions to several problems. To maintain objective detachment, you deal with a different problem during each of six rounds and assume different roles (problem owner, consultant, basher, booster, enhancer, and evaluator) during each round. At the conclusion of the activity, each player ends up with two solutions to her problem.

23. Four Step Sketch

Creative thinking and visual ideation does not need to be confined to the opening stages of your problem-solving strategies. Exercises that include sketching and prototyping on paper can be effective at the solution finding and development stage of the process, and can be great for keeping a team engaged. 

By going from simple notes to a crazy 8s round that involves rapidly sketching 8 variations on their ideas before then producing a final solution sketch, the group is able to iterate quickly and visually. Problem-solving techniques like Four-Step Sketch are great if you have a group of different thinkers and want to change things up from a more textual or discussion-based approach.

Four-Step Sketch   #design sprint   #innovation   #idea generation   #remote-friendly   The four-step sketch is an exercise that helps people to create well-formed concepts through a structured process that includes: Review key information Start design work on paper,  Consider multiple variations , Create a detailed solution . This exercise is preceded by a set of other activities allowing the group to clarify the challenge they want to solve. See how the Four Step Sketch exercise fits into a Design Sprint

24. 15% Solutions

Some problems are simpler than others and with the right problem-solving activities, you can empower people to take immediate actions that can help create organizational change. 

Part of the liberating structures toolkit, 15% solutions is a problem-solving technique that focuses on finding and implementing solutions quickly. A process of iterating and making small changes quickly can help generate momentum and an appetite for solving complex problems.

Problem-solving strategies can live and die on whether people are onboard. Getting some quick wins is a great way of getting people behind the process.   

It can be extremely empowering for a team to realize that problem-solving techniques can be deployed quickly and easily and delineate between things they can positively impact and those things they cannot change. 

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.

25. How-Now-Wow Matrix

The problem-solving process is often creative, as complex problems usually require a change of thinking and creative response in order to find the best solutions. While it’s common for the first stages to encourage creative thinking, groups can often gravitate to familiar solutions when it comes to the end of the process. 

When selecting solutions, you don’t want to lose your creative energy! The How-Now-Wow Matrix from Gamestorming is a great problem-solving activity that enables a group to stay creative and think out of the box when it comes to selecting the right solution for a given problem.

Problem-solving techniques that encourage creative thinking and the ideation and selection of new solutions can be the most effective in organisational change. Give the How-Now-Wow Matrix a go, and not just for how pleasant it is to say out loud. 

How-Now-Wow Matrix   #gamestorming   #idea generation   #remote-friendly   When people want to develop new ideas, they most often think out of the box in the brainstorming or divergent phase. However, when it comes to convergence, people often end up picking ideas that are most familiar to them. This is called a ‘creative paradox’ or a ‘creadox’. The How-Now-Wow matrix is an idea selection tool that breaks the creadox by forcing people to weigh each idea on 2 parameters.

26. Impact and Effort Matrix

All problem-solving techniques hope to not only find solutions to a given problem or challenge but to find the best solution. When it comes to finding a solution, groups are invited to put on their decision-making hats and really think about how a proposed idea would work in practice. 

The Impact and Effort Matrix is one of the problem-solving techniques that fall into this camp, empowering participants to first generate ideas and then categorize them into a 2×2 matrix based on impact and effort.

Activities that invite critical thinking while remaining simple are invaluable. Use the Impact and Effort Matrix to move from ideation and towards evaluating potential solutions before then committing to them. 

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.

27. Dotmocracy

If you’ve followed each of the problem-solving steps with your group successfully, you should move towards the end of your process with heaps of possible solutions developed with a specific problem in mind. But how do you help a group go from ideation to putting a solution into action? 

Dotmocracy – or Dot Voting -is a tried and tested method of helping a team in the problem-solving process make decisions and put actions in place with a degree of oversight and consensus. 

One of the problem-solving techniques that should be in every facilitator’s toolbox, Dot Voting is fast and effective and can help identify the most popular and best solutions and help bring a group to a decision effectively. 

Dotmocracy   #action   #decision making   #group prioritization   #hyperisland   #remote-friendly   Dotmocracy is a simple method for group prioritization or decision-making. It is not an activity on its own, but a method to use in processes where prioritization or decision-making is the aim. The method supports a group to quickly see which options are most popular or relevant. The options or ideas are written on post-its and stuck up on a wall for the whole group to see. Each person votes for the options they think are the strongest, and that information is used to inform a decision.

All facilitators know that warm-ups and icebreakers are useful for any workshop or group process. Problem-solving workshops are no different.

Use these problem-solving techniques to warm up a group and prepare them for the rest of the process. Activating your group by tapping into some of the top problem-solving skills can be one of the best ways to see great outcomes from your session.

  • Check-in/Check-out
  • Doodling Together
  • Show and Tell
  • Constellations
  • Draw a Tree

28. Check-in / Check-out

Solid processes are planned from beginning to end, and the best facilitators know that setting the tone and establishing a safe, open environment can be integral to a successful problem-solving process.

Check-in / Check-out is a great way to begin and/or bookend a problem-solving workshop. Checking in to a session emphasizes that everyone will be seen, heard, and expected to contribute. 

If you are running a series of meetings, setting a consistent pattern of checking in and checking out can really help your team get into a groove. We recommend this opening-closing activity for small to medium-sized groups though it can work with large groups if they’re disciplined!

Check-in / Check-out   #team   #opening   #closing   #hyperisland   #remote-friendly   Either checking-in or checking-out is a simple way for a team to open or close a process, symbolically and in a collaborative way. Checking-in/out invites each member in a group to be present, seen and heard, and to express a reflection or a feeling. Checking-in emphasizes presence, focus and group commitment; checking-out emphasizes reflection and symbolic closure.

29. Doodling Together  

Thinking creatively and not being afraid to make suggestions are important problem-solving skills for any group or team, and warming up by encouraging these behaviors is a great way to start. 

Doodling Together is one of our favorite creative ice breaker games – it’s quick, effective, and fun and can make all following problem-solving steps easier by encouraging a group to collaborate visually. By passing cards and adding additional items as they go, the workshop group gets into a groove of co-creation and idea development that is crucial to finding solutions to problems. 

Doodling Together   #collaboration   #creativity   #teamwork   #fun   #team   #visual methods   #energiser   #icebreaker   #remote-friendly   Create wild, weird and often funny postcards together & establish a group’s creative confidence.

30. Show and Tell

You might remember some version of Show and Tell from being a kid in school and it’s a great problem-solving activity to kick off a session.

Asking participants to prepare a little something before a workshop by bringing an object for show and tell can help them warm up before the session has even begun! Games that include a physical object can also help encourage early engagement before moving onto more big-picture thinking.

By asking your participants to tell stories about why they chose to bring a particular item to the group, you can help teams see things from new perspectives and see both differences and similarities in the way they approach a topic. Great groundwork for approaching a problem-solving process as a team! 

Show and Tell   #gamestorming   #action   #opening   #meeting facilitation   Show and Tell taps into the power of metaphors to reveal players’ underlying assumptions and associations around a topic The aim of the game is to get a deeper understanding of stakeholders’ perspectives on anything—a new project, an organizational restructuring, a shift in the company’s vision or team dynamic.

31. Constellations

Who doesn’t love stars? Constellations is a great warm-up activity for any workshop as it gets people up off their feet, energized, and ready to engage in new ways with established topics. It’s also great for showing existing beliefs, biases, and patterns that can come into play as part of your session.

Using warm-up games that help build trust and connection while also allowing for non-verbal responses can be great for easing people into the problem-solving process and encouraging engagement from everyone in the group. Constellations is great in large spaces that allow for movement and is definitely a practical exercise to allow the group to see patterns that are otherwise invisible. 

Constellations   #trust   #connection   #opening   #coaching   #patterns   #system   Individuals express their response to a statement or idea by standing closer or further from a central object. Used with teams to reveal system, hidden patterns, perspectives.

32. Draw a Tree

Problem-solving games that help raise group awareness through a central, unifying metaphor can be effective ways to warm-up a group in any problem-solving model.

Draw a Tree is a simple warm-up activity you can use in any group and which can provide a quick jolt of energy. Start by asking your participants to draw a tree in just 45 seconds – they can choose whether it will be abstract or realistic. 

Once the timer is up, ask the group how many people included the roots of the tree and use this as a means to discuss how we can ignore important parts of any system simply because they are not visible.

All problem-solving strategies are made more effective by thinking of problems critically and by exposing things that may not normally come to light. Warm-up games like Draw a Tree are great in that they quickly demonstrate some key problem-solving skills in an accessible and effective way.

Draw a Tree   #thiagi   #opening   #perspectives   #remote-friendly   With this game you can raise awarness about being more mindful, and aware of the environment we live in.

Each step of the problem-solving workshop benefits from an intelligent deployment of activities, games, and techniques. Bringing your session to an effective close helps ensure that solutions are followed through on and that you also celebrate what has been achieved.

Here are some problem-solving activities you can use to effectively close a workshop or meeting and ensure the great work you’ve done can continue afterward.

  • One Breath Feedback
  • Who What When Matrix
  • Response Cards

How do I conclude a problem-solving process?

All good things must come to an end. With the bulk of the work done, it can be tempting to conclude your workshop swiftly and without a moment to debrief and align. This can be problematic in that it doesn’t allow your team to fully process the results or reflect on the process.

At the end of an effective session, your team will have gone through a process that, while productive, can be exhausting. It’s important to give your group a moment to take a breath, ensure that they are clear on future actions, and provide short feedback before leaving the space. 

The primary purpose of any problem-solving method is to generate solutions and then implement them. Be sure to take the opportunity to ensure everyone is aligned and ready to effectively implement the solutions you produced in the workshop.

Remember that every process can be improved and by giving a short moment to collect feedback in the session, you can further refine your problem-solving methods and see further success in the future too.

33. One Breath Feedback

Maintaining attention and focus during the closing stages of a problem-solving workshop can be tricky and so being concise when giving feedback can be important. It’s easy to incur “death by feedback” should some team members go on for too long sharing their perspectives in a quick feedback round. 

One Breath Feedback is a great closing activity for workshops. You give everyone an opportunity to provide feedback on what they’ve done but only in the space of a single breath. This keeps feedback short and to the point and means that everyone is encouraged to provide the most important piece of feedback to them. 

One breath feedback   #closing   #feedback   #action   This is a feedback round in just one breath that excels in maintaining attention: each participants is able to speak during just one breath … for most people that’s around 20 to 25 seconds … unless of course you’ve been a deep sea diver in which case you’ll be able to do it for longer.

34. Who What When Matrix 

Matrices feature as part of many effective problem-solving strategies and with good reason. They are easily recognizable, simple to use, and generate results.

The Who What When Matrix is a great tool to use when closing your problem-solving session by attributing a who, what and when to the actions and solutions you have decided upon. The resulting matrix is a simple, easy-to-follow way of ensuring your team can move forward. 

Great solutions can’t be enacted without action and ownership. Your problem-solving process should include a stage for allocating tasks to individuals or teams and creating a realistic timeframe for those solutions to be implemented or checked out. Use this method to keep the solution implementation process clear and simple for all involved. 

Who/What/When Matrix   #gamestorming   #action   #project planning   With Who/What/When matrix, you can connect people with clear actions they have defined and have committed to.

35. Response cards

Group discussion can comprise the bulk of most problem-solving activities and by the end of the process, you might find that your team is talked out! 

Providing a means for your team to give feedback with short written notes can ensure everyone is head and can contribute without the need to stand up and talk. Depending on the needs of the group, giving an alternative can help ensure everyone can contribute to your problem-solving model in the way that makes the most sense for them.

Response Cards is a great way to close a workshop if you are looking for a gentle warm-down and want to get some swift discussion around some of the feedback that is raised. 

Response Cards   #debriefing   #closing   #structured sharing   #questions and answers   #thiagi   #action   It can be hard to involve everyone during a closing of a session. Some might stay in the background or get unheard because of louder participants. However, with the use of Response Cards, everyone will be involved in providing feedback or clarify questions at the end of a session.

Save time and effort discovering the right solutions

A structured problem solving process is a surefire way of solving tough problems, discovering creative solutions and driving organizational change. But how can you design for successful outcomes?

With SessionLab, it’s easy to design engaging workshops that deliver results. Drag, drop and reorder blocks  to build your agenda. When you make changes or update your agenda, your session  timing   adjusts automatically , saving you time on manual adjustments.

Collaborating with stakeholders or clients? Share your agenda with a single click and collaborate in real-time. No more sending documents back and forth over email.

Explore  how to use SessionLab  to design effective problem solving workshops or  watch this five minute video  to see the planner in action!

technical and problem solving skills

Over to you

The problem-solving process can often be as complicated and multifaceted as the problems they are set-up to solve. With the right problem-solving techniques and a mix of creative exercises designed to guide discussion and generate purposeful ideas, we hope we’ve given you the tools to find the best solutions as simply and easily as possible.

Is there a problem-solving technique that you are missing here? Do you have a favorite activity or method you use when facilitating? Let us know in the comments below, we’d love to hear from you! 

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15 Common Problem-Solving Interview Questions

Ebook: How to Build a Tech Talent Brand: The Definitive Guide

In an interview for a big tech company, I was asked if I’d ever resolved a fight — and the exact way I went about handling it. I felt blindsided, and I stammered my way through an excuse of an answer.

It’s a familiar scenario to fellow technical job seekers — and one that risks leaving a sour taste in our mouths. As candidate experience becomes an increasingly critical component of the hiring process, recruiters need to ensure the problem-solving interview questions they prepare don’t dissuade talent in the first place. 

Interview questions designed to gauge a candidate’s problem-solving skills are more often than not challenging and vague. Assessing a multifaceted skill like problem solving is tricky — a good problem solver owns the full solution and result, researches well, solves creatively and takes action proactively. 

It’s hard to establish an effective way to measure such a skill. But it’s not impossible.

We recommend taking an informed and prepared approach to testing candidates’ problem-solving skills . With that in mind, here’s a list of a few common problem-solving interview questions, the science behind them — and how you can go about administering your own problem-solving questions with the unique challenges of your organization in mind.

Key Takeaways for Effective Problem-Solving Interview Questions

  • Problem solving lies at the heart of programming. 
  • Testing a candidate’s problem-solving skills goes beyond the IDE. Problem-solving interview questions should test both technical skills and soft skills.
  • STAR, SOAR and PREP are methods a candidate can use to answer some non-technical problem-solving interview questions.
  • Generic problem-solving interview questions go a long way in gauging a candidate’s fit. But you can go one step further by customizing them according to your company’s service, product, vision, and culture. 

Technical Problem-Solving Interview Question Examples

Evaluating a candidates’ problem-solving skills while using coding challenges might seem intimidating. The secret is that coding challenges test many things at the same time — like the candidate’s knowledge of data structures and algorithms, clean code practices, and proficiency in specific programming languages, to name a few examples.

Problem solving itself might at first seem like it’s taking a back seat. But technical problem solving lies at the heart of programming, and most coding questions are designed to test a candidate’s problem-solving abilities.

Here are a few examples of technical problem-solving questions:

1. Mini-Max Sum  

This well-known challenge, which asks the interviewee to find the maximum and minimum sum among an array of given numbers, is based on a basic but important programming concept called sorting, as well as integer overflow. It tests the candidate’s observational skills, and the answer should elicit a logical, ad-hoc solution.

2. Organizing Containers of Balls  

This problem tests the candidate’s knowledge of a variety of programming concepts, like 2D arrays, sorting and iteration. Organizing colored balls in containers based on various conditions is a common question asked in competitive examinations and job interviews, because it’s an effective way to test multiple facets of a candidate’s problem-solving skills.

3. Build a Palindrome

This is a tough problem to crack, and the candidate’s knowledge of concepts like strings and dynamic programming plays a significant role in solving this challenge. This problem-solving example tests the candidate’s ability to think on their feet as well as their ability to write clean, optimized code.

4. Subarray Division

Based on a technique used for searching pairs in a sorted array ( called the “two pointers” technique ), this problem can be solved in just a few lines and judges the candidate’s ability to optimize (as well as basic mathematical skills).

5. The Grid Search 

This is a problem of moderate difficulty and tests the candidate’s knowledge of strings and searching algorithms, the latter of which is regularly tested in developer interviews across all levels.

Common Non-Technical Problem-Solving Interview Questions 

Testing a candidate’s problem-solving skills goes beyond the IDE . Everyday situations can help illustrate competency, so here are a few questions that focus on past experiences and hypothetical situations to help interviewers gauge problem-solving skills.

1. Given the problem of selecting a new tool to invest in, where and how would you begin this task? 

Key Insight : This question offers insight into the candidate’s research skills. Ideally, they would begin by identifying the problem, interviewing stakeholders, gathering insights from the team, and researching what tools exist to best solve for the team’s challenges and goals. 

2. Have you ever recognized a potential problem and addressed it before it occurred? 

Key Insight: Prevention is often better than cure. The ability to recognize a problem before it occurs takes intuition and an understanding of business needs. 

3. A teammate on a time-sensitive project confesses that he’s made a mistake, and it’s putting your team at risk of missing key deadlines. How would you respond?

Key Insight: Sometimes, all the preparation in the world still won’t stop a mishap. Thinking on your feet and managing stress are skills that this question attempts to unearth. Like any other skill, they can be cultivated through practice.

4. Tell me about a time you used a unique problem-solving approach. 

Key Insight: Creativity can manifest in many ways, including original or novel ways to tackle a problem. Methods like the 10X approach and reverse brainstorming are a couple of unique approaches to problem solving. 

5. Have you ever broken rules for the “greater good?” If yes, can you walk me through the situation?

Key Insight: “Ask for forgiveness, not for permission.” It’s unconventional, but in some situations, it may be the mindset needed to drive a solution to a problem.

6. Tell me about a weakness you overcame at work, and the approach you took. 

Key Insight: According to Compass Partnership , “self-awareness allows us to understand how and why we respond in certain situations, giving us the opportunity to take charge of these responses.” It’s easy to get overwhelmed when faced with a problem. Candidates showing high levels of self-awareness are positioned to handle it well.

7. Have you ever owned up to a mistake at work? Can you tell me about it?

Key Insight: Everybody makes mistakes. But owning up to them can be tough, especially at a workplace. Not only does it take courage, but it also requires honesty and a willingness to improve, all signs of 1) a reliable employee and 2) an effective problem solver.

8. How would you approach working with an upset customer?

Key Insight: With the rise of empathy-driven development and more companies choosing to bridge the gap between users and engineers, today’s tech teams speak directly with customers more frequently than ever before. This question brings to light the candidate’s interpersonal skills in a client-facing environment.

9. Have you ever had to solve a problem on your own, but needed to ask for additional help? How did you go about it? 

Key Insight: Knowing when you need assistance to complete a task or address a situation is an important quality to have while problem solving. This questions helps the interviewer get a sense of the candidate’s ability to navigate those waters. 

10. Let’s say you disagree with your colleague on how to move forward with a project. How would you go about resolving the disagreement?

Key Insight: Conflict resolution is an extremely handy skill for any employee to have; an ideal answer to this question might contain a brief explanation of the conflict or situation, the role played by the candidate and the steps taken by them to arrive at a positive resolution or outcome. 

Strategies for Answering Problem-Solving Questions

If you’re a job seeker, chances are you’ll encounter this style of question in your various interview experiences. While problem-solving interview questions may appear simple, they can be easy to fumble — leaving the interviewer without a clear solution or outcome. 

It’s important to approach such questions in a structured manner. Here are a few tried-and-true methods to employ in your next problem-solving interview.

1. Shine in Interviews With the STAR Method

S ituation, T ask, A ction, and R esult is a great method that can be employed to answer a problem-solving or behavioral interview question. Here’s a breakdown of these steps:

  • Situation : A good way to address almost any interview question is to lay out and define the situation and circumstances. 
  • Task : Define the problem or goal that needs to be addressed. Coding questions are often multifaceted, so this step is particularly important when answering technical problem-solving questions.
  • Action : How did you go about solving the problem? Try to be as specific as possible, and state your plan in steps if you can.
  • Result : Wrap it up by stating the outcome achieved. 

2. Rise above difficult questions using the SOAR method

A very similar approach to the STAR method, SOAR stands for S ituation, O bstacle, A ction, and R esults .

  • Situation: Explain the state of affairs. It’s important to steer clear of stating any personal opinions in this step; focus on the facts.
  • Obstacle: State the challenge or problem you faced.
  • Action: Detail carefully how you went about overcoming this obstacle.
  • Result: What was the end result? Apart from overcoming the obstacle, did you achieve anything else? What did you learn in the process? 

3. Do It the PREP Way

Traditionally used as a method to make effective presentations, the P oint, R eason, E xample, P oint method can also be used to answer problem-solving interview questions.  

  • Point : State the solution in plain terms. 
  • Reasons: Follow up the solution by detailing your case — and include any data or insights that support your solution. 
  • Example: In addition to objective data and insights, drive your answer home by contextualizing the solution in a real-world example.
  • Point : Reiterate the solution to make it come full circle.

How to Customize Problem-Solving Interview Questions 

Generic problem-solving interview questions go a long way in gauging a candidate’s skill level, but recruiters can go one step further by customizing these problem-solving questions according to their company’s service, product, vision, or culture. 

Here are some tips to do so:

  • Break down the job’s responsibilities into smaller tasks. Job descriptions may contain ambiguous responsibilities like “manage team projects effectively.” To formulate an effective problem-solving question, envision what this task might look like in a real-world context and develop a question around it.  
  • Tailor questions to the role at hand. Apart from making for an effective problem-solving question, it gives the candidate the impression you’re an informed technical recruiter. For example, an engineer will likely have attended many scrums. So, a good question to ask is: “Suppose you notice your scrums are turning unproductive. How would you go about addressing this?” 
  • Consider the tools and technologies the candidate will use on the job. For example, if Jira is the primary project management tool, a good problem-solving interview question might be: “Can you tell me about a time you simplified a complex workflow — and the tools you used to do so?”
  • If you don’t know where to start, your company’s core values can often provide direction. If one of the core values is “ownership,” for example, consider asking a question like: “Can you walk us through a project you owned from start to finish?” 
  • Sometimes, developing custom content can be difficult even with all these tips considered. Our platform has a vast selection of problem-solving examples that are designed to help recruiters ask the right questions to help nail their next technical interview.

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How to List Problem-Solving Skills on a Resume [List Included]

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Problem-solving skills are more in-demand than ever. 

Employers love candidates with problem-solving skills because, in 99% of cases, they guarantee you're also logical, creative, clear-headed, and a great decision-maker. 

But claiming you have organizational skills on your resume is not enough. 

To impress recruiters, you've got to prove that you possess them. 

This includes understanding which problem-solving skills you possess and adding them to your resume (the right way), among other things.

This is where this article comes in! We put together everything you need to know about problem-solving skills, including: 

  • 8 Essential Problem-Solving Skills for Your Resume

How to Add Problem-Solving Skills to Your Resume

  • Why Are Problem-Solving Skills Important
  • 6 Problem-Solving Steps

Let's dive right in! 

8 Problem-Solving Skills for Your Resume

Research shows that problem-solving skills consist of several facets : 

  • Identifying and analyzing a problem
  • Taking effective actions
  • Understanding the effect of the decisions
  • Coming up with creative and novel solutions
  • Transferring knowledge from one situation to another
  • Thinking abstractly about problems

As such, there is no single problem-solving skill. Problem-solving includes a set of skills, all of which are equally important in helping your personal and professional life. 

Below, we’ll cover the eight most important problem-solving skills that you can also list on your resume to impress recruiters: 

#1. Research skills

To properly identify and understand a problem, you need excellent research skills. 

Research skills involve being able to gather information from the right sources, reviewing that information in detail to extract the data you need, analyzing the data according to the context, and being able to apply the data to your situation. 

#2. Analytical skills

Analytical skills are required throughout the entire process of solving a problem. 

In a nutshell, analytical skills refer to being able to analyze a situation in depth and from different perspectives . Specifically, you need analytical skills to achieve all of the following while solving a problem:

  • Detect patterns
  • Interpret data
  • Analyze new information
  • Reach conclusions based on several factors

#3. Creativity

Being creative means being able to think outside of the box and look at situations and problems inventively. 

For most people, creativity is mainly associated with creative industries such as arts and crafts, architecture, design, etc. 

In reality, however, creativity is an essential success factor for every job and the data is here to support that. According to this Adobe study , problem-solving (51%) and creativity (47%) have gained the most value in driving salary increases in the last five years. 

When it comes to the process of solving a problem, creativity can help you consider more perspectives, think abstractly about problems, and come up with novel solutions that others haven’t thought of before.

#4. Critical thinking skills

Being able to think critically means that you’re good at rationalizing, understanding the connections between ideas or situations, and logically analyzing any given situation. 

As such, strong critical thinking skills can help you see beyond what’s at face value, make more informed decisions, and anticipate the outcomes of said decisions. 

People who have critical thinking skills share traits such as open-mindedness , cognitive flexibility , skepticism , clarity , and precision . 

#5. Decision-making skills

Before coming up with a single action plan to solve a problem, you’ll need to first brainstorm several possible solutions. 

After that, you need good decision-making skills to choose the best possible solution. Without decision-making skills, you risk prolonging finding a proper solution or aggravating a problem even more. 

#6. Communication skills

With strong communication skills , you’re able to successfully explain the problem to others and propose your solutions. In turn, you can be sure that everyone’s on the same page and that you’re carrying out the action plan accordingly. 

Some communication skills required for problem-solving include: 

  • Active listening
  • Written and verbal communication
  • Giving and receiving feedback

#7. Collaboration

Problem-solving is rarely a process you carry out alone. More often than not, you need to consult relevant stakeholders, give and receive feedback, and work with a team towards a common goal (i.e. solving the problem).

Well, collaboration entails exactly that - working well with others, cooperatively addressing problems, and putting a group’s goal ahead of personal goals. 

Some important collaboration skills that help with problem-solving include: 

  • Conflict resolution
  • Emotional intelligence 

#8. Attention to Detail 

Have you ever heard of the expression “the devil’s in the details?”

It means that something may seem simple on the surface, but in fact, the details make it complicated and are likely to cause problems.

Well, if you’re someone who shows great attention to detail, you’re not likely to let details keep you from solving a problem effectively. 

Not to mention, being able to spot and understand even the smallest details that make up a problem means you’ll be able to grasp the issue in its entire complexity and come up with even more inventive and workable solutions. 

Now that we covered the most important problem-solving skills, we’ll show you how to add them to your resume so that you can stand out from other candidates. 

Let us walk you through the process, step-by-step: 

#1. Mention Your Problem-Solving Skills on Your Resume Summary

The resume summary is a three or four-sentence paragraph positioned at the top of your resume that includes: 

  • Your profession and years of experience 
  • Your top skills (i.e. hard skills or soft skills)
  • One or two noteworthy achievements 

problem solving skills resume summary

The goal of the resume summary is to catch the hiring manager’s attention, show them you’re a relevant candidate and get them to go through the rest of your resume in detail. 

As such, it’s your first chance to highlight your problem-solving skills effectively. You can either do that by mentioning them among your top skills or by mentioning an achievement that proves you possess a given skill.

In the best-case scenario, you can even do both. 

Here is an example of how you can include problem-solving skills in your resume summary: 

  • Behavioral psychologist with 7+ years of experience in the field. Great research, analytical, and communication skills. Over the last eight years, I’ve worked closely with more than 100 patients with different behavioral disorders, helping them improve their personal and professional lives through different treatment methods. 

#2. Add the RIGHT Problem-Solving Skills Under Your Soft Skills

Secondly, you should list your problem-solving skills under your resume’s soft skills section . 

The listing part is pretty easy - simply create a section titled Skills and write down your problem-solving skills.

There is, however, one caveat: 

You don’t want to overkill your skills section by listing every problem-solving skill we covered in this article.

Not only will the hiring manager have trouble believing you possess each and every skill, but there’s also a high chance you don’t even need all those skills to begin with. 

To make your skills section as relevant as possile, do the following: 

  • Check the job description. The job description can show you exactly what skills you need for the job. If you’re applying for, say, a software engineering position, you’ll probably be required to have the following problem-solving skills: analytical skills, creativity, attention to detail, and cognitive flexibility. 
  • Identify the skills you possess. Think about which skills you can back up with actual experience from your previous jobs. Only list problem-solving skills that you actually possess and that you can prove you possess on your resume. 
  • Add those skills under your soft skills. Then, add the problem-solving skills that you have and that are required in the job under your resume’s “Soft Skills” section. 

#3. Prove Your Problem-Solving Skills In Your Work Experience Section

Finally, you should use the work experience section to prove that you’ve got the problem-solving skills you’ve mentioned throughout your resume. 

Anyone can just claim that they’ve got problem-solving skills on their resume - not everyone can back them up with experience.

Here’s what you can do to convey that you possess problem-solving skills and also make your work experience section as impactful as possible: 

  • Tailor your work experience to the job. Only add past jobs that are relevant to the position you are applying for now. If you’re applying for, say, a software engineering position, the hiring manager will be interested in your previous jobs in the field, but probably not too interested in the time you worked as a server at a restaurant. 
  • Focus on your achievements instead of your responsibilities. More often than not, hiring managers know exactly what your responsibilities consisted of in previous jobs. What they want to know is how you made a positive impact with your achievements. 
  • Make your achievements quantifiable. Speaking of achievements, you want to make them as quantifiable as possible. After all “treated ten patients in the course of a year using positive reinforcement” sounds much better than “treated ten patients.”
  • Use the Laszlo Bock formula . If you’re having trouble phrasing your achievements, the following formula will probably be of help: “Accomplished X as measured by Y doing X.” 
  • Leverage action verbs and keywords. There are hundreds of words and verbs you can use instead of “did,” “accomplished,” etc. The more descriptive you are of your achievements, the more impressive they can sound.

And here’s an example of a project manager describing their problem-solving skills in their work experience section:

  • Fixed company communication issues by implementing a new project management solution. 
  • Improved team productivity by implementing time-tracking software and doing daily stand-up calls.
  • Managed to meet all client deliverable deadlines in 2022.

Why Are Problem-Solving Skills Important?

Are you wondering what exactly is it that makes problem-solving skills so important? 

After all, there are hundreds of soft skills out there that you can master, improve, or learn how to add to your resume. So it’s normal to wonder “why should I focus on problem-solving?” 

Here is why problem-solving skills matter:

  • They can improve your employability. Problem-solving skills are among the most important skills to employers across a range of occupations. In short, employers are always looking for proactive thinkers who can address professional challenges.
  • They can help you grow in your career more easily. You’ll be more likely to get promoted if you can come up with creative solutions to the different problems that you’ll face throughout your career.
  • They can become an essential part of your personal brand . Your current employer, coworkers, and future employers alike will see you as someone creative, reliable, and helpful.
  • They are related to a range of other valuable skills. When you prove you’re a problem solver, you’re effectively saying you’re attentive to detail, logical, creative, analytical, curious, and other things employers are looking for in their employees.

10 Jobs That Require Problem-Solving Skills

As we’ve already mentioned, problem-solving skills come in handy for practically every job. 

Whether you’re a teacher who needs to solve a dispute between peers in your class or a customer representative who needs to help a client, knowing how to go about solving issues is definitely an asset. 

That said, some jobs are all about solving problems. In such cases, problem-solving skills are not just a nice addition to have on your resume - they’re crucial to getting hired. 

Here are the top 10 jobs requiring problem-solving skills in 2024: 

  • Software engineer
  • Air-traffic controller
  • Police officer
  • Social worker
  • Psychologist
  • UX designer

35 Action Verbs You Can Use to Highlight Your Problem-Solving Skills

The language you use to describe your problem-solving skills matters.  

Sure, you can use “ solved” to describe how you dealt with a problem throughout your entire resume and risk coming off as repetitive and unimaginative. 

Or , you can use any of the following action verbs and keywords and make your problem-solving skills pop out in the eyes of recruiters: 

  • Calculate  
  • Critically think 
  • Draw conclusions
  • Experiment 
  • Listen/Listen actively 

The Problem-Solving Process in 6 Steps

Problem-solving is a methodical process. It consists of certain steps that you always need to take if you want to find a good solution. 

The more you understand and practice this process, the better you can get at solving problems. 

Below, we cover the six main steps of problem-solving in detail:

#1. Identify the problem 

The first step to solving a problem is identifying exactly what’s causing it. 

After all, if you’re not focusing on the real underlying issue, you might come up with solutions that don’t fit the problem itself. 

Say, for example, that you’re a teacher that’s facing poor class performance. Identifying whether the problem comes from the students’ not studying enough or from your own teaching methods can make a big difference in the solutions you come up with. 

It typically happens that the faster you find the root cause of the problem, the easier it is to find a proper solution. 

#2. Understand the problem

Once you identify the problem, you’ve got to understand it completely. Here are some questions you can ask to make sure you properly understand a problem: 

  • What is the scale of the problem? 
  • What are its short and long-term effects? 
  • Have you faced something like this before?
  • Can the problem be solved by dividing it into smaller parts?

The better you understand the problem in its complexity, the more likely you are to come up with effective solutions. 

#3. Research the systems that make up the problem 

In many cases, solving a problem will be a complex undertaking. See, complex problems are often the result of several different underlying systems that you need to understand to find a dynamic solution. 

Let’s take the teacher example from above. 

If a certain student is not doing too well and keeps getting poor grades, you might be tempted to go the easy route and simply chastise them and tell them to study more.

This, in a lot of cases, might simply not work because you’re not addressing the root cause of the problem.

The student might, for example, be burned out , unmotivated by the curriculum, or simply struggling with specific topics.

A problem-solving solution that’s more likely to work would be to talk to the student (or their parents), try to understand the reason for their poor grades, and address the root cause behind the problem itself.

#4. Visualize the problem 

This may not apply to all situations, but it can definitely come in handy for most. 

Drawing a diagram to visualize the situation or your solution to the problem can help you grasp its complexity better - especially if the problem is multi-faceted. Anything from PowerPoint to a piece of white paper can be a good tool to visualize your problem, highlight the problem area, and tackle it more effectively.

#5. Brainstorm solutions 

After you’ve done all the above, it’s time to start thinking about solutions. 

This is another step of the problem-solving process that’s based on collaboration and effective communication. In the brainstorming phase, you should sit with team members or relevant stakeholders and come up with as many creative ideas and solutions as possible. 

This is not where you come up with your most refined, well-thought-out ideas. Instead, it’s where you discuss freely and combine diverse knowledge and analysis of the problem to come up with diverse solutions. 

Brainstorming is an essential part of problem-solving that can help you break out of boring or predictable ideas and thinking patterns. 

#6. Choose the best answer(s)

This is where decision-making skills come in. With a list of different potential solutions, you can narrow down your options to finally choose the best one. 

To reach a solution more easily, take the following into consideration:

  • Your company’s/organization’s objectives
  • The budget and the timeframe at your disposal
  • The success outcomes
  • Potential risks linked to the solution 

Finally, discuss your solutions with relevant stakeholders and team members to gather all the possible feedback that can help you make the best possible decision. 

And remember - once you’ve chosen the best possible solution to a problem, your work is far from over. Being a problem solver also includes the following: 

  • Develop and implement an action plan
  • Monitor the progress of your plan 
  • Make necessary adjustments during the process
  • Evaluate the outcomes of your solution 

Problem-Solving Skills Resume Example

Problem-Solving Skills Resume Example

Want a resume that makes your problem-solving skills pop like the above example? 

Use one of our tried-and-tested resume templates . 

They’re free, modern, and created in collaboration with some of the best HR professionals from around the globe!

Key Takeaways 

And that's a wrap on problem-solving skills. By now, you should know everything there is to know on the topic. 

Before you go, here are the main points we covered in this article: 

  • Problem-solving skills are a set of soft skills that help you solve problems effectively. They involve critical thinking, analytical skills, creativity, communication skills, and attention to detail. 
  • Problem-solving skills can improve your employability, work performance, and personal brand. 
  • Add your problem-solving skills to your resume summary, under the soft skills section, and in your work history section. 
  • When you’re creating your work history section, make sure to tailor it to the job, focus on your achievements and make them quantifiable, and use action verbs and keywords from the job description. 
  • To get better at solving problems, follow these steps: identify and understand the problem, research the systems that make up the problem, visualize the problem, brainstorm, and choose the best possible solution. 
  • Once that’s done, create an action plan and make sure to monitor its progress as you’re implementing it. 

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26 Good Examples of Problem Solving (Interview Answers)

By Biron Clark

Published: November 15, 2023

Employers like to hire people who can solve problems and work well under pressure. A job rarely goes 100% according to plan, so hiring managers will be more likely to hire you if you seem like you can handle unexpected challenges while staying calm and logical in your approach.

But how do they measure this?

They’re going to ask you interview questions about these problem solving skills, and they might also look for examples of problem solving on your resume and cover letter. So coming up, I’m going to share a list of examples of problem solving, whether you’re an experienced job seeker or recent graduate.

Then I’ll share sample interview answers to, “Give an example of a time you used logic to solve a problem?”

Problem-Solving Defined

It is the ability to identify the problem, prioritize based on gravity and urgency, analyze the root cause, gather relevant information, develop and evaluate viable solutions, decide on the most effective and logical solution, and plan and execute implementation. 

Problem-solving also involves critical thinking, communication, listening, creativity, research, data gathering, risk assessment, continuous learning, decision-making, and other soft and technical skills.

Solving problems not only prevent losses or damages but also boosts self-confidence and reputation when you successfully execute it. The spotlight shines on you when people see you handle issues with ease and savvy despite the challenges. Your ability and potential to be a future leader that can take on more significant roles and tackle bigger setbacks shine through. Problem-solving is a skill you can master by learning from others and acquiring wisdom from their and your own experiences. 

It takes a village to come up with solutions, but a good problem solver can steer the team towards the best choice and implement it to achieve the desired result.

Watch: 26 Good Examples of Problem Solving

Examples of problem solving scenarios in the workplace.

  • Correcting a mistake at work, whether it was made by you or someone else
  • Overcoming a delay at work through problem solving and communication
  • Resolving an issue with a difficult or upset customer
  • Overcoming issues related to a limited budget, and still delivering good work through the use of creative problem solving
  • Overcoming a scheduling/staffing shortage in the department to still deliver excellent work
  • Troubleshooting and resolving technical issues
  • Handling and resolving a conflict with a coworker
  • Solving any problems related to money, customer billing, accounting and bookkeeping, etc.
  • Taking initiative when another team member overlooked or missed something important
  • Taking initiative to meet with your superior to discuss a problem before it became potentially worse
  • Solving a safety issue at work or reporting the issue to those who could solve it
  • Using problem solving abilities to reduce/eliminate a company expense
  • Finding a way to make the company more profitable through new service or product offerings, new pricing ideas, promotion and sale ideas, etc.
  • Changing how a process, team, or task is organized to make it more efficient
  • Using creative thinking to come up with a solution that the company hasn’t used before
  • Performing research to collect data and information to find a new solution to a problem
  • Boosting a company or team’s performance by improving some aspect of communication among employees
  • Finding a new piece of data that can guide a company’s decisions or strategy better in a certain area

Problem Solving Examples for Recent Grads/Entry Level Job Seekers

  • Coordinating work between team members in a class project
  • Reassigning a missing team member’s work to other group members in a class project
  • Adjusting your workflow on a project to accommodate a tight deadline
  • Speaking to your professor to get help when you were struggling or unsure about a project
  • Asking classmates, peers, or professors for help in an area of struggle
  • Talking to your academic advisor to brainstorm solutions to a problem you were facing
  • Researching solutions to an academic problem online, via Google or other methods
  • Using problem solving and creative thinking to obtain an internship or other work opportunity during school after struggling at first

You can share all of the examples above when you’re asked questions about problem solving in your interview. As you can see, even if you have no professional work experience, it’s possible to think back to problems and unexpected challenges that you faced in your studies and discuss how you solved them.

Interview Answers to “Give an Example of an Occasion When You Used Logic to Solve a Problem”

Now, let’s look at some sample interview answers to, “Give me an example of a time you used logic to solve a problem,” since you’re likely to hear this interview question in all sorts of industries.

Example Answer 1:

At my current job, I recently solved a problem where a client was upset about our software pricing. They had misunderstood the sales representative who explained pricing originally, and when their package renewed for its second month, they called to complain about the invoice. I apologized for the confusion and then spoke to our billing team to see what type of solution we could come up with. We decided that the best course of action was to offer a long-term pricing package that would provide a discount. This not only solved the problem but got the customer to agree to a longer-term contract, which means we’ll keep their business for at least one year now, and they’re happy with the pricing. I feel I got the best possible outcome and the way I chose to solve the problem was effective.

Example Answer 2:

In my last job, I had to do quite a bit of problem solving related to our shift scheduling. We had four people quit within a week and the department was severely understaffed. I coordinated a ramp-up of our hiring efforts, I got approval from the department head to offer bonuses for overtime work, and then I found eight employees who were willing to do overtime this month. I think the key problem solving skills here were taking initiative, communicating clearly, and reacting quickly to solve this problem before it became an even bigger issue.

Example Answer 3:

In my current marketing role, my manager asked me to come up with a solution to our declining social media engagement. I assessed our current strategy and recent results, analyzed what some of our top competitors were doing, and then came up with an exact blueprint we could follow this year to emulate our best competitors but also stand out and develop a unique voice as a brand. I feel this is a good example of using logic to solve a problem because it was based on analysis and observation of competitors, rather than guessing or quickly reacting to the situation without reliable data. I always use logic and data to solve problems when possible. The project turned out to be a success and we increased our social media engagement by an average of 82% by the end of the year.

Answering Questions About Problem Solving with the STAR Method

When you answer interview questions about problem solving scenarios, or if you decide to demonstrate your problem solving skills in a cover letter (which is a good idea any time the job description mention problem solving as a necessary skill), I recommend using the STAR method to tell your story.

STAR stands for:

It’s a simple way of walking the listener or reader through the story in a way that will make sense to them. So before jumping in and talking about the problem that needed solving, make sure to describe the general situation. What job/company were you working at? When was this? Then, you can describe the task at hand and the problem that needed solving. After this, describe the course of action you chose and why. Ideally, show that you evaluated all the information you could given the time you had, and made a decision based on logic and fact.

Finally, describe a positive result you got.

Whether you’re answering interview questions about problem solving or writing a cover letter, you should only choose examples where you got a positive result and successfully solved the issue.

Example answer:

Situation : We had an irate client who was a social media influencer and had impossible delivery time demands we could not meet. She spoke negatively about us in her vlog and asked her followers to boycott our products. (Task : To develop an official statement to explain our company’s side, clarify the issue, and prevent it from getting out of hand). Action : I drafted a statement that balanced empathy, understanding, and utmost customer service with facts, logic, and fairness. It was direct, simple, succinct, and phrased to highlight our brand values while addressing the issue in a logical yet sensitive way.   We also tapped our influencer partners to subtly and indirectly share their positive experiences with our brand so we could counter the negative content being shared online.  Result : We got the results we worked for through proper communication and a positive and strategic campaign. The irate client agreed to have a dialogue with us. She apologized to us, and we reaffirmed our commitment to delivering quality service to all. We assured her that she can reach out to us anytime regarding her purchases and that we’d gladly accommodate her requests whenever possible. She also retracted her negative statements in her vlog and urged her followers to keep supporting our brand.

What Are Good Outcomes of Problem Solving?

Whenever you answer interview questions about problem solving or share examples of problem solving in a cover letter, you want to be sure you’re sharing a positive outcome.

Below are good outcomes of problem solving:

  • Saving the company time or money
  • Making the company money
  • Pleasing/keeping a customer
  • Obtaining new customers
  • Solving a safety issue
  • Solving a staffing/scheduling issue
  • Solving a logistical issue
  • Solving a company hiring issue
  • Solving a technical/software issue
  • Making a process more efficient and faster for the company
  • Creating a new business process to make the company more profitable
  • Improving the company’s brand/image/reputation
  • Getting the company positive reviews from customers/clients

Every employer wants to make more money, save money, and save time. If you can assess your problem solving experience and think about how you’ve helped past employers in those three areas, then that’s a great start. That’s where I recommend you begin looking for stories of times you had to solve problems.

Tips to Improve Your Problem Solving Skills

Throughout your career, you’re going to get hired for better jobs and earn more money if you can show employers that you’re a problem solver. So to improve your problem solving skills, I recommend always analyzing a problem and situation before acting. When discussing problem solving with employers, you never want to sound like you rush or make impulsive decisions. They want to see fact-based or data-based decisions when you solve problems.

Next, to get better at solving problems, analyze the outcomes of past solutions you came up with. You can recognize what works and what doesn’t. Think about how you can get better at researching and analyzing a situation, but also how you can get better at communicating, deciding the right people in the organization to talk to and “pull in” to help you if needed, etc.

Finally, practice staying calm even in stressful situations. Take a few minutes to walk outside if needed. Step away from your phone and computer to clear your head. A work problem is rarely so urgent that you cannot take five minutes to think (with the possible exception of safety problems), and you’ll get better outcomes if you solve problems by acting logically instead of rushing to react in a panic.

You can use all of the ideas above to describe your problem solving skills when asked interview questions about the topic. If you say that you do the things above, employers will be impressed when they assess your problem solving ability.

If you practice the tips above, you’ll be ready to share detailed, impressive stories and problem solving examples that will make hiring managers want to offer you the job. Every employer appreciates a problem solver, whether solving problems is a requirement listed on the job description or not. And you never know which hiring manager or interviewer will ask you about a time you solved a problem, so you should always be ready to discuss this when applying for a job.

Related interview questions & answers:

  • How do you handle stress?
  • How do you handle conflict?
  • Tell me about a time when you failed

Biron Clark

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Problem-Solving Skills: Think Beyond the Whiteboard Test

technical and problem solving skills

Are you technically brilliant? Even a rock star? 

Sorry, that may not be good enough to get you hired or promoted, said Philippe Clavel, senior director of engineering at Roblox, a game development platform company based in San Mateo, California.

Mastering technical problem-solving skills involving data sets and algorithms are all fine and good, but getting a handle on these non-technical problem-solving skills are equally important, according to hiring managers.

Prior to joining Roblox, Clavel managed a technically brilliant engineer who had a toxic personality that constantly challenged others and failed to let them think, Clavel said. After giving feedback to the engineer about his behavior, Clavel paired him with someone more senior to ensure he and his teammates worked together in solving problems.

This engineer eventually started to change and realized it wasn’t so hard to temper his comments and even say hello to people. 

“The outcome was much better. He could do more with other people than what he could do alone,” Clavel told Built In. “It definitely speeded up the collaboration process by 20 percent because there was more discussion on the front end.”

More on people Management How to Make Your Next Meeting the Best Ever

How You Sabotage Yourself

Without possessing non-technical problem-solving skills, you are likely to miss out on landing your dream job or securing that promotion you’ve been seeking.

“Technical skills can be acquired. What I’m looking for when I hire someone is can they learn quickly? Technology changes very quickly and you have to stay on top of it,” said Igor Grinkin, a DevOps manager at San Francisco-based Newfront Insurance.

Roughly 50 to 60 percent of job candidates that come through Roblox’s door believe their technical prowess is the only thing of importance to land the job, Clavel said. He noted this belief is especially prevalent among new college graduates. However, Roblox’s interview process tends to weed people who lack non-technical problem-solving skills by the time they reach Clavel for an interview, he said.

“I would say a lot of people think these skills aren’t important. But I will be honest, they are wrong. We especially see this in new engineers, but even senior engineers think this way. They think, ‘I’m so good at technology, there’s nothing else I need to know.’ But, what this does is it prevents you from having the job you really want, because that will be one of the differentiators with you as a candidate. Or, if you get the job, it will block you in your career,” he warned.  

Amazon Web Services (AWS) also places a high importance on non-technical problem-solving skills, according to Caitlyn Shim, a general manager and director of AWS Organizations and Accounts at the Seattle-based company. “We don’t want brilliant jerks,” said Shim.

“You can be extremely smart, but if you can’t work with others, you’re gonna have a really hard time in the end. Ultimately, we’re trying to tackle problems that one person can’t solve alone.”

She added if you can’t work in a group, then you’re limiting yourself to solving one-person-sized problems and limiting your career. 

More on People Management Why Are Companies Still Offering Unpaid Internships?

Why These Non-Technical Problem-Solving Skills Are Needed

Effective communication and collaboration skills are an “absolute must” for any job at autonomous vehicle maker Waymo, said Annie Cheng, engineering director at Mountain View, California-based Waymo. She, like other hiring managers, notes that solving big problems takes more than one person.  

You also need to learn from your mistakes, as well as have an open mind, when tackling problems, Cheng added, noting these attributes rank high in non-technical problem-solving skills.

“Being able to think out of the box, looking at things from different angles and considering alternative solutions is an important problem-solving skill, especially if you’re working on a novel, or a moonshot project,” Cheng said.

10 Critical Non-Technical Problem-Solving Skills

  • Active listener
  • Good communicator
  • Collaborator
  • Open mindedness
  • Accepts feedback
  • Learns quickly and from mistakes
  • Attains consensus
  • Drive to see problems through

Making mistakes is not only inevitable but it’s a key part to developing your problem-solving ability, said Cheng, noting it leads to learning from one’s mistakes.

Driving consensus is another non-technical problem-solving skill you should master, said hiring managers.

“We have passionate people who have really strong opinions but you also have to listen to each other. Then, you have to be able to figure out how to pull the right things from everyone’s ideas so that you can all come to a good consensus in the end,” Shim said. “That’s a skill in and of itself.”

Embracing feedback will grease your problem-solving skills and prevent you from becoming stuck to one idea, no matter how much you love it and believe it smacks of brilliant innovation, said Shim, noting it’s a tough but important skill to develop.

Drive is also critical to problem-solving skills, especially complex ones.

“In computer science and software development, you have to push to the finish line. But there’s a lot of complexity that may get in your way. While it’s easy to say you want to finish, you need to go the extra mile,” Clavel said.

Curiosity is also needed for problem-solving, he added. Engineers progress by wanting to learn more and that, in turn, adds to the bench of tools you can call on to solve problems.

These non-technical problem-solving skills are important for all technical roles, hiring managers said, but they note some skills, like effective communication , have greater weight for some positions.

Engineers who work in the product feature area at Roblox, for example, need to have good communication skills because they are working closely with designers in determining what users want. Excellent communication skills can help explain your vision to product managers and designers, said Clavel.

Actionable Steps to Develop These Problem-Solving Skills

“There’s no silver bullet, as every person is unique,” Cheng said. “While some people naturally have good soft problem-solving skills, others might need to invest quite some time to develop those.”

Emotions also often overshadow the core problems you are trying to express, Cheng observed.

“One piece of advice I gave to a direct report years ago is first learn to detect whether they are in an emotional state and see if they can control their emotion while trying to express the core problem. When they find it challenging, use different communication methods, such as writing, so they can filter out emotions and focus on bringing clarity to the key problem statement,” Cheng said.

Talking to lay people in words they can understand can bolster your technical communication skills. This skill can also be developed by teaching courses or explaining your work to a fifth-grader, she added.

There are many different ways to develop your problem-solving skills — consider these five steps from authors John Bransford and Barry Stein detailed in their book, “The IDEAL Problem Solver: A Guide to Improved Thinking, Learning, and Creativity.”

IDEAL Steps

  • Identify the problem
  • Define the challenges
  • Examine potential strategies
  • Act on the strategies
  • Look at the results and evaluate whether other actions are needed

Broaden your collaboration skills by going beyond the day-to-day scope of your work and try collaborating with coworkers outside your team on projects across the company, such as forming an ERG group or working with interest-based groups like a cycling or yoga group, Cheng said. She added these efforts may also improve your communication skills too.

Matching employees with other employees to help them grow is an effective solution to develop their non-technical problem-solving skills, Clavel said. 

Managers can also take other steps to help employees develop their non-technical problem-solving skills too.

Rather than telling your employee, ‘Hey, you need to focus on communicating better or improving your creativity,’ try giving examples over time, Clavel said. The combination of knowing they need to change and having examples as a framework leads to more realistic outcomes where they can develop these problem-solving skills, Clavel said.

“Engineers are smart and it’s a matter of learning how to apply your smartness to other areas.”

“You may not get all of the skills at once, but that’s OK. You may not be very good at communication, but you can compensate by your drive or creativity, or other of those skills.”

Self-discovery in developing non-technical problem-solving skills yields the best results, hiring managers said. 

That is what Shim saw at AWS.

“Someone used to present their ideas with a bunch of attitude and was kind of aggressive. But he saw when someone else would restate his ideas in a more open way, others would listen to it and were far more receptive,” Shim said. “That really helped him see it’s not necessarily what you say, but how you say it. He started to experiment with different presentation styles and found one that worked and felt natural for him.”

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Everybody can benefit from having good problem solving skills as we all encounter problems on a daily basis. Some of these problems are obviously more severe or complex than others.

It would be wonderful to have the ability to solve all problems efficiently and in a timely fashion without difficulty, unfortunately though there is no one way in which all problems can be solved.

You will discover, as you read through our pages on problem solving, that the subject is complex.

However well prepared we are for problem solving, there is always an element of the unknown. Although planning and structuring will help make the problem solving process more likely to be successful, good judgement and an element of good luck will ultimately determine whether problem solving was a success.

Interpersonal relationships fail and businesses fail because of poor problem solving.

This is often due to either problems not being recognised or being recognised but not being dealt with appropriately.

Problem solving skills are highly sought after by employers as many companies rely on their employees to identify and solve problems.

A lot of the work in problem solving involves understanding what the underlying issues of the problem really are - not the symptoms. Dealing with a customer complaint may be seen as a problem that needs to be solved, and it's almost certainly a good idea to do so. The employee dealing with the complaint should be asking what has caused the customer to complain in the first place, if the cause of the complaint can be eliminated then the problem is solved.

In order to be effective at problem solving you are likely to need some other key skills, which include:

Creativity. Problems are usually solved either intuitively or systematically. Intuition is used when no new knowledge is needed - you know enough to be able to make a quick decision and solve the problem, or you use common sense or experience to solve the problem. More complex problems or problems that you have not experienced before will likely require a more systematic and logical approach to solve, and for these you will need to use creative thinking. See our page on Creative Thinking for more information.

Researching Skills. Defining and solving problems often requires you to do some research: this may be a simple Google search or a more rigorous research project. See our Research Methods section for ideas on how to conduct effective research.

Team Working. Many problems are best defined and solved with the input of other people. Team working may sound like a 'work thing' but it is just as important at home and school as well as in the workplace. See our Team-Working page for more.

Emotional Intelligence. It is worth considering the impact that a problem and/or its solution has on you and other people. Emotional intelligence, the ability to recognise the emotions of yourself and others, will help guide you to an appropriate solution. See our Emotional Intelligence pages for more.

Risk Management. Solving a problem involves a certain amount of risk - this risk needs to be weighed up against not solving the problem. You may find our Risk Management page useful.

Decision Making . Problem solving and decision making are closely related skills, and making a decision is an important part of the problem solving process as you will often be faced with various options and alternatives. See Decision Making for more.

The measure of success is not whether you have a tough problem to deal with, but whether it is the same problem you had last year.

John Foster Dulles, Former US Secretary of State.

What is a Problem?

The Concise Oxford Dictionary (1995) defines a problem as:

“ A doubtful or difficult matter requiring a solution ”
“ Something hard to understand or accomplish or deal with.”

It is worth also considering our own view of what a problem is.

We are constantly exposed to opportunities in life, at work, at school and at home. However many opportunities are missed or not taken full advantage of. Often we are unsure how to take advantage of an opportunity and create barriers - reasons why we can't take advantage. These barriers can turn a potentially positive situation into a negative one, a problem.

Are we missing the 'big problem'? It is human nature to notice and focus on small, easy to solve problems but much harder to work on the big problems that may be causing some of the smaller ones.

It's useful to consider the following questions when faced with a problem.

Is the problem real or perceived?

Is this problem really an opportunity?

Does the problem need solving?

All problems have two features in common: goals and barriers.

Problems involve setting out to achieve some objective or desired state of affairs and can include avoiding a situation or event.

Goals can be anything that you wish to achieve, or where you want to be. If you are hungry then your goal is probably to eat something. If you are the head of an organisation (CEO), then your main goal may be to maximise profits and this main goal may need to be split into numerous sub-goals in order to fulfil the ultimate aim of increasing profits.

If there were no barriers in the way of achieving a goal, then there would be no problem. Problem solving involves overcoming the barriers or obstacles that prevent the immediate achievement of goals.

Following our examples above, if you feel hungry then your goal is to eat. A barrier to this may be that you have no food available - so you take a trip to the supermarket and buy some food, removing the barrier and thus solving the problem. Of course for the CEO wanting to increase profits there may be many more barriers preventing the goal from being reached. The CEO needs to attempt to recognise these barriers and remove them or find other ways to achieve the goals of the organisation.

Our problem solving pages provide a simple and structured approach to problem solving.

The approach referred to is generally designed for problem solving in an organisation or group context, but can also be easily adapted to work at an individual level at home or in education.

Trying to solve a complex problem alone however can be a mistake. The old adage " A problem shared is a problem halved " is sound advice.

Talking to others about problems is not only therapeutic but can help you see things from a different point of view, opening up more potential solutions.

Stages of Problem Solving

Effective problem solving usually involves working through a number of steps or stages, such as those outlined below.

Problem Identification:

This stage involves: detecting and recognising that there is a problem; identifying the nature of the problem; defining the problem.

The first phase of problem solving may sound obvious but often requires more thought and analysis. Identifying a problem can be a difficult task in itself. Is there a problem at all? What is the nature of the problem, are there in fact numerous problems? How can the problem be best defined? By spending some time defining the problem you will not only understand it more clearly yourself but be able to communicate its nature to others, which leads to the second phase.

Structuring the Problem:

This stage involves: a period of observation, careful inspection, fact-finding and developing a clear picture of the problem.

Following on from problem identification, structuring the problem is all about gaining more information about the problem and increasing understanding. This phase is all about fact finding and analysis, building a more comprehensive picture of both the goal(s) and the barrier(s). This stage may not be necessary for very simple problems but is essential for problems of a more complex nature.

Looking for Possible Solutions:

During this stage you will generate a range of possible courses of action, but with little attempt to evaluate them at this stage.

From the information gathered in the first two phases of the problem solving framework it is now time to start thinking about possible solutions to the identified problem. In a group situation this stage is often carried out as a brain-storming session, letting each person in the group express their views on possible solutions (or part solutions). In organisations different people will have different expertise in different areas and it is useful, therefore, to hear the views of each concerned party.

Making a Decision:

This stage involves careful analysis of the different possible courses of action and then selecting the best solution for implementation.

This is perhaps the most complex part of the problem solving process. Following on from the previous step it is now time to look at each potential solution and carefully analyse it. Some solutions may not be possible, due to other problems like time constraints or budgets. It is important at this stage to also consider what might happen if nothing was done to solve the problem - sometimes trying to solve a problem that leads to many more problems requires some very creative thinking and innovative ideas.

Finally, make a decision on which course of action to take - decision making is an important skill in itself and we recommend that you see our pages on decision making .

Implementation:

This stage involves accepting and carrying out the chosen course of action.

Implementation means acting on the chosen solution. During implementation more problems may arise especially if identification or structuring of the original problem was not carried out fully.

Monitoring/Seeking Feedback:

The last stage is about reviewing the outcomes of problem solving over a period of time, including seeking feedback as to the success of the outcomes of the chosen solution.

The final stage of problem solving is concerned with checking that the process was successful. This can be achieved by monitoring and gaining feedback from people affected by any changes that occurred. It is good practice to keep a record of outcomes and any additional problems that occurred.

Continue to: Identifying and Structuring Problems Social Problem Solving

See also: Project Management Risk Management Effective Decision Making

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The Universal Key to Success: Acquiring Technical and Programming Skills

I n today's rapidly evolving world, the acquisition of technical and programming skills has become more than just a career choice—it's a necessity for success. Regardless of your profession or background, these skills can unlock a world of opportunities, enhance your problem-solving abilities, and empower you to thrive in an increasingly digital age. In this article we will delve into why acquiring technical and programming skills is essential for success in any field.

Adapting to a Digital World

The digital transformation is revolutionizing industries across the globe. From healthcare to finance, agriculture to entertainment, almost every sector is integrating technology to streamline processes, analyze data, and make informed decisions. Those who possess technical and programming skills are better equipped to navigate and contribute to this evolving landscape.

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Enhanced Problem-Solving Abilities

Learning how to code and understanding technical concepts sharpens your problem-solving skills. Coding involves breaking down complex problems into smaller, manageable parts and developing step-by-step solutions. This logical approach to problem-solving can be applied to challenges in any profession, fostering innovation and efficiency.

Opening Doors to Diverse Career Paths

Technical and programming skills are not limited to specific careers. Whether you're an artist, marketer, biologist, or teacher, these skills can augment your capabilities. For instance, artists can create interactive digital art, marketers can analyze data to refine their strategies, biologists can use programming to process large datasets, and teachers can develop engaging educational tools.

Expand your horizons and discover how technical skills can amplify your career, no matter your field. Explore endless possibilities at TakeLessons.com

Future-Proofing Your Career

Automation and artificial intelligence are reshaping the job market. Many routine tasks are becoming automated, making technical skills increasingly valuable. By acquiring these skills, you future-proof your career by remaining relevant and adaptable in a constantly changing job market.

Entrepreneurship and Innovation

Entrepreneurship often requires a strong technical foundation. Whether you're launching a tech startup or a traditional business, having programming skills can help you develop and maintain your website, create digital marketing campaigns, and optimize your operations for efficiency.

Turn your entrepreneurial dreams into reality! Learn to code and innovate with confidence. Begin your journey at TakeLessons.com

Critical Thinking and Creativity

Learning to code fosters critical thinking and creativity. Programming challenges you to think logically and creatively to solve problems. These skills are transferable to various aspects of life and work, enabling you to approach challenges with a fresh perspective.

Empowerment and Independence

Acquiring technical and programming skills empowers you to take control of your digital life. You can build your own websites, automate repetitive tasks, and customize software to suit your needs. This independence can save you time and money while increasing your efficiency.

Take control of your digital world and gain independence. Learn to code and customize your tech life at TakeLessons.com

In a world driven by technology, the acquisition of technical and programming skills has become a universal key to success. Regardless of your profession or background, these skills offer you the ability to adapt, innovate, and thrive in a rapidly changing environment. They enhance your problem-solving abilities, open doors to diverse career paths, future-proof your career, and empower you to take control of your digital life. So, whether you're a student, a professional, or someone exploring new opportunities, consider investing in your future by acquiring these essential skills. Your success may depend on it.

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The Art of Problem Solving in Software Development: Beyond Technical Expertise Problem-solving in digital creation transcends basic coding skills, requiring a fusion of creativity, strategic thinking, and a deep understanding of technology and human needs.

By Vaibhav Sethi • Feb 20, 2024

Opinions expressed by Entrepreneur contributors are their own.

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Problem-solving in digital creation transcends basic coding skills, requiring a fusion of creativity, strategic thinking, and a deep understanding of technology and human needs. In this complex realm, developers navigate the nuances of each challenge, exploring uncharted territories to discover innovative solutions. Their journey is marked by continuous learning and adaptation, constantly reimagining technological possibilities to meet evolving demands.

At the heart of this process lies the ability to understand a challenge's core, envision a range of possible solutions, and then skillfully craft code that addresses the present problem and anticipates future scenarios. This iterative approach, enriched by ongoing data and feedback, guides developers in continuously refining their solutions. The overarching goal is to create software that stands out in terms of functionality, efficiency, resilience, scalability, and user engagement.

Embracing a Multifaceted Skill Set

Solving problems in digital development transcends coding prowess. It encompasses various skills, including analytical reasoning, inventiveness, and clear communication. Developers must excel at deconstructing complex problems, often needing imaginative and unconventional solutions. Jagan Mohanraj, a veteran software architect, highlights this aspect: "In digital development, problem-solving is as much about creativity and strategic thinking as it is about technical knowledge. My work with the Build Health framework utilizing Microsoft Azure Appinsights is a testament to this approach."

Effective communication is also vital, especially in conveying intricate technical issues to stakeholders with diverse backgrounds. This ability is crucial in collaborative settings where multidisciplinary teams address complex challenges. "Clear communication is key in problem-solving, ensuring all parties grasp both the challenge and the solution," Mohanraj adds.

The Vital Role of Teamwork and Dynamics

In digital development, effective teamwork is essential for innovative problem-solving. Collaborative efforts combine varied perspectives and skills, often leading to more comprehensive solutions. Mohanraj observes, "Teamwork in problem-solving unites diverse viewpoints, vital for the best solutions in complex digital challenges."

The dynamics within a team significantly impact the problem-solving approach. Teams that cultivate open dialogue, mutual respect, and innovation readiness often surmount obstacles. Each team member feels valued and encouraged to contribute their insights and expertise in such environments, fostering a rich and creative problem-solving culture.

Navigating an Evolving Technological Landscape

The digital development domain is in constant flux, with emerging technologies and methodologies reshaping the landscape. For developers, this reality necessitates adaptability and an unwavering commitment to continuous learning. Mohanraj notes, "Staying adaptable and continually learning is critical in the dynamic field of digital development. Regularly reviewing the source code of Microsoft products and participating in events and technical forums helps me stay abreast of the latest developments and understand the nuances of problem-solving in this field."

Developers need to maintain a mindset that embraces exploration and flexibility, key traits for adapting to rapidly evolving technologies. This means being willing to delve into new programming languages, adopt various development methodologies, and stay abreast of emerging fields such as machine learning and blockchain technology. Such agility is crucial in positioning developers at the cutting edge, fully prepared to effectively address new and complex challenges.

Prioritizing the User in the Development Process

At the crux of problem-solving in digital development is the end-user. Grasping user needs and expectations is fundamental in crafting effective digital solutions. This user-centric approach ensures the software functions optimally and delivers a positive user experience. Mohanraj emphasizes, "Every solution we develop in digital development should always aim to serve the user, addressing their specific needs and expectations. Understanding the big picture and looking beyond immediate challenges to how solutions fit into the broader context of a project or system is key to effective problem-solving."

Engaging with users, understanding their challenges, and empathizing with their experiences are integral to this approach. It often involves user research, iterative testing, and feedback mechanisms to align the software with user requirements. By centering on the user, developers craft technically robust solutions while also being intuitive and engaging.

A Holistic View of Problem Solving in Digital Development

The art of problem-solving in digital development extends far beyond coding expertise and technical know-how. It involves a comprehensive approach that blends creativity, strategic vision, teamwork, adaptability, and a profound understanding of user needs.

As this field continues to evolve, these skills will become increasingly pivotal, guiding developers in their mission to forge impactful, innovative, and user-centric digital solutions.

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  • Published: 22 February 2024

Problem-solving skills are predicted by technical innovations in the wild and brain size in passerines

  • Jean-Nicolas Audet   ORCID: orcid.org/0000-0002-0511-183X 1 , 2 , 3 ,
  • Mélanie Couture   ORCID: orcid.org/0000-0002-6169-8225 1 , 4 ,
  • Louis Lefebvre   ORCID: orcid.org/0000-0002-6445-0292 5 , 6 &
  • Erich D. Jarvis   ORCID: orcid.org/0000-0001-8931-5049 1 , 2 , 3 , 4  

Nature Ecology & Evolution ( 2024 ) Cite this article

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  • Evolutionary ecology
  • Learning and memory

Behavioural innovations can provide key advantages for animals in the wild, especially when ecological conditions change rapidly and unexpectedly. Innovation rates can be compared across taxa by compiling field reports of novel behaviours. Large-scale analyses have shown that innovativeness reduces extinction risk, increases colonization success and is associated with increased brain size and pallial neuron numbers. However, appropriate laboratory measurements of innovativeness, necessary to conduct targeted experimental studies, have not been clearly established, despite decades of speculation on the most suitable assay. Here we implemented a battery of cognitive tasks on 203 birds of 15 passerine species and tested for relationships at the interspecific and intraspecific levels with ecological metrics of innovation and brain size. We found that species better at solving extractive foraging problems had higher technical innovation rates in the wild and larger brains. By contrast, performance on other cognitive tasks often subsumed under the term behavioural flexibility, namely, associative and reversal learning, as well as self-control, were not related to problem-solving, innovation in the wild or brain size. Our study yields robust support for problem-solving as an accurate experimental proxy of innovation and suggests that novel motor solutions are more important than self-control or learning of modified cues in generating technical innovations in the wild.

Animals vary in their likelihood of inventing new behavioural solutions to ecological problems. Two approaches have been used to understand this variation: large-scale analyses of ecological, evolutionary and neural correlates of observational data taken from the wild 1 , 2 , 3 , 4 , 5 , 6 , 7 , and experimental studies on smaller numbers of species 8 , 9 , 10 , 11 . Integrating these approaches is crucial to obtain a more comprehensive and generalizable understanding of cognition. Innovations in the wild, as these novel solutions were first called by Kummer and Goodall 12 , are thought to involve three cognitive components: (1) inhibition of habitual responses when an animal realizes they do not work, (2) exploration of new actions to solve the problem and (3) learning of modified cues associated with the solution. Each component can be targeted experimentally using specific behavioural assays: (1) self-control tasks, which measure the ability to inhibit a prepotent but unproductive behaviour (for example, finding an alternative way to obtain a reward), assess inhibitory control 13 ; (2) puzzle boxes requiring extractive foraging and obstacle removal, sometimes with tools, assess novel problem-solving 14 ; and (3) association and reversal tasks, which measure the ability to discriminate between rewarded and unrewarded cues, target the efficiency of learning new cues 15 . All these assays have been considered measures of behavioural flexibility, the ability to adjust a behaviour in response to changing conditions 16 , for example, when colonizing new areas such as cities. Consistent with this notion, problem-solving speed is positively associated with the degree of urbanization (for example, refs. 10 , 17 ) and consumption of anthropogenic food 18 . By contrast, associative and reversal learning speed has been found to correlate negatively with urbanization 19 , 20 . A concept such as behavioural flexibility can only subsume different traits under a common denominator if their measures produce concordant patterns. Dozens of studies have been conducted on birds and yielded unclear results, partly because the vast majority have focused on a small number of species, most often one (for example, ref. 18 ), and/or only one or two of the three types of assay (for example, ref. 21 ). The correspondence between field measures of innovation and experimental assays of flexibility is thus an open question (Fig. 1 ).

figure 1

a , Foraging innovations, as well as dietary generalism, have been well documented in the field. Yet, the cognitive skills responsible for innovations are poorly understood, and their appropriate experimental measurement has not been clearly identified. b , Brain size has been shown to be associated with innovativeness and dietary generalism in the wild, but it is unclear how brain size varies with different experimental assays of cognition or their covariates across species. c , The most common experimental tasks assumed to be linked with innovativeness include problem-solving, associative learning, reversal learning and self-control. However, a link between performance on these tasks, their covariates and innovativeness across species has yet to be shown. All the traits measured by these assays, as well as innovativeness, are often considered components of behavioural flexibility. Solid black arrows show known relationships, and dashed grey arrows show untested or equivocal relationships across species. Image credits: Louis Lefebvre for the Barbados bullfinch in a , Christopher Torres (University of Texas at Austin) for the brain endocast in b and Jean-Nicolas Audet for the nuthatch solving a problem in captivity in c .

In this Article, we addressed these issues with a large sample of species and variables, testing interspecific and interindividual relationships between self-control, associative learning, reversal learning and problem-solving on 203 individuals from 15 passerine species, including 13 wild-caught and 2 domesticated species (Fig. 2a and Supplementary Table 1 ). We tested mainly male birds to reduce sex as a variable, except for 7 female birds in two species where it was difficult to obtain sufficient wild-caught sample sizes of male birds (Methods). We explored associations between performance on experimental assays of cognition and with measures of absolute and allometrically corrected brain size, innovation rates in the wild and several potential covariates; in a separate study 22 , we also explored associations with vocal learning complexity. If the assays are all valid measures of behavioural flexibility, then we expect them all to be positively associated with each other as well as with innovation rate in the wild and absolute and allometrically corrected brain size (Fig. 2b,c ). If, as some data suggest (reviewed in ref. 16 ), however, behavioural flexibility is a heterogeneous concept, not all assays will be correlated. In particular, persistence is one of the variables that favour solving an extractive foraging problem (for example, refs. 9 , 17 , 23 , 24 ), but it is also one of the primary sources of error in reversal learning 25 , which would lead to negative or non-significant relationships between assays, as well as with innovation and brain size (Fig. 2d ).

figure 2

a , We assessed cognitive skills in 203 birds from 15 species ( n  = 12–19 individuals per species). All species belong to the oscine (Passeri) sub-order (songbirds), except the eastern phoebe, a suboscine (Tyranni). Phylogenetic tree relationships were obtained from ref. 53 . b , Predicted interspecific relationships between field innovation rates and performance on the four cognitive assays tested in this study. According to current assumptions of behavioural flexibility, all cognitive traits should be more or less positively associated with field innovation rates, from non-innovative to highly innovative species; the lowest to highest cognitive performance in our laboratory assays (bottom to top). c , Similarly, given the known link between innovation rates and brain size, performance on all assays across species is predicted to be positively associated with brain size. d , Problem-solving, which requires persistence, is predicted to be negatively associated with reversal learning, for which persistence reduces performance. No relationships between problem-solving and associative learning or self-control are expected. The predictions in b and c are likely mutually exclusive of d , yet those predictions reflect current knowledge and assumptions. Image credits: Derrick Eidam for wild species and Mélanie Couture for domesticated species (zebra finch and canary) in a and Simon Ducatez for the innovative species in b ; other species’ silhouettes are from PhyloPic ( http://phylopic.org ; chipping sparrow, Ferran Sayol; blue jay, T. Michael Keesey; eastern phoebe, Andy Wilson). Scientific names and sample sizes for each species are provided in Supplementary Table 1 .

Behavioural assays measure distinct skills

We first compared performance on all cognitive assays for 12 to 19 individuals from each of the 15 passerine species. Passerines represent half of the world’s avian species. Our sample includes representatives of known high (for example, Corvidae, Turdidae, Sturnidae) and low (for example, Estrildidae, Passerellidae, Troglodytidae) innovation families that together account for 967 cases of innovation (out of 4,455) in ref. 26 . To measure problem-solving, we used four different obstacle-removal tasks, each requiring a different motor pattern to obtain a food reward: pulling/knocking, flipping/grabbing, piercing/tearing or dragging a moveable element of the apparatus to extract the food (Extended Data Fig. 1f–i and Supplementary Videos 1 – 4 ). Performance was significantly associated across all four problem-solving tasks between the 15 species (Extended Data Fig. 2 and Supplementary Table 2a ). Therefore, we used the average number of trials to solve the four tasks as our measure of problem-solving performance. To assess self-control, we used a detour-reaching paradigm in which the birds had to access a food reward from the open ends of a cylinder containing food visible behind a transparent barrier (Extended Data Fig. 1j and Supplementary Videos 5 and 6 ); a bird’s initial response to a task such as this is to approach the part where the food is visible behind the transparent barrier and peck at it; to be successful, the animal has to inhibit this first response and move away to the open end of the apparatus without pecking at the barrier. Associative (acquisition) learning was assessed by giving the birds a two-colour discrimination task, where they had to associate a food reward with a visual cue through repeated trials (Extended Data Fig. 1k and Supplementary Video 7 ). Reversal learning was then measured on the same apparatus by switching the rewarded colour 1 day after the initial learning test.

We compared the birds’ performance across all assays at two levels, within and between species. Phylogenetic Bayesian mixed models (MCMCglmm) conducted at the interspecific level using species’ mean performance revealed that a species’ proficiency on one assay was not associated with its performance on the others, except for associative and reversal learning, which showed a significant association (Fig. 3 and Supplementary Table 2b ). Species’ mean differences in shyness (latency to feed following human disturbance) or neophobia (latency to feed in the presence of a novel object) were not related to performance on any cognitive task (Extended Data Fig. 3 and Supplementary Table 2c ).

figure 3

a – c Problem-solving performance across species is not significantly associated with associative learning ( a ), reversal learning ( b ) or self-control (measured using the detour-reaching task) ( c ). d , Associative learning performance is associated with reversal learning performance across species. e , f , Self-control performance is not associated with reversal learning ( e ) or associative learning performances ( f ). Problem-solving performance is each species’ mean number of trials to solve the four different problems. Graphs illustrate mean species’ trial values with s.e.m., ranked predictors and lines of values predicted by Bayesian phylogenetic mixed models. Filled blue circles, wild-caught songbird species; empty blue circles, domesticated songbird species (zebra finch and canary); red circles, the suboscine (eastern phoebe); solid trend line, P MCMC.adj  < 0.05; dashed trend lines, P MCMC.adj  > 0.05; species’ two-letter codes are listed in Supplementary Table 1 ; detailed results of MCMCglmm modelling and FDR-corrected P values ( P MCMC.adj ) are provided in Supplementary Table 2b .

At the interindividual level, comparisons of each individual’s performance on the different cognitive tasks showed no coherent pattern when comparing all 203 individuals using linear mixed models (Supplementary Table 3 ) or individuals of each of the 15 species separately (Extended Data Figs. 4 – 8 and Supplementary Table 4 ). The only exception was the relationship between associative learning and reversal learning tasks that was significantly positive across the 203 individuals (Supplementary Table 3 ) and within 4 (2 after false discovery rate (FDR) adjustment) of the 15 species (Extended Data Fig. 9 and Supplementary Table 4d ), consistent with the interspecific association we found. Thus, testing 203 individuals from 15 species, we find robust support for the idea that the assays, except for the two learning tasks, measure distinct aspects of cognition.

Problem-solving, innovation rates and brain size

We then asked whether the species’ mean performance on the behavioural tests in captivity was predicted by published metrics of field innovations (number of cases of novel observed behaviours, corrected for research effort, that is, the number of articles published per species 3 , 26 ) and brain size (absolute or corrected for body size 27 ). We separately analysed food-type innovations (reports of novel food types eaten) and technical innovations (reports of novel foraging techniques 28 ). Food-type innovation is suspected to be a consequence of opportunistic generalist foraging 2 , whereas technical innovation likely requires problem-solving skills 3 . In line with this prediction, phylogenetic modelling revealed that technical innovation rate in the wild significantly predicted problem-solving performance in our laboratory experiments (Fig. 4a and Supplementary Table 2d ). However, we detected no significant association between problem-solving performance and food-type innovation rate (Fig. 4b and Supplementary Table 2d ). In addition, problem-solving performance was positively associated with both absolute (Fig. 4c and Supplementary Table 2d ) and relative brain size (Fig. 4d and Supplementary Table 2d ). The above relationships remained significant when Benjamini–Hochberg FDR corrections were applied (Supplementary Table 2d ). In contrast to problem-solving, associative learning, reversal learning and self-control were not associated with innovation rate or brain size (Extended Data Fig. 10 and Supplementary Table 2e–g ). These results suggest that the cognitive skills measured by problem-solving tasks in captivity are similar to the ones required to invent technical innovations in the wild and are linked with increased brain size but that these cognitive skills are distinct from those measured by assays of associative learning, reversal learning and self-control.

figure 4

a , b , Mean problem-solving performance across species is significantly associated with their technical innovation rates ( a ) but not with their food innovation rates ( b ). c , d , Problem-solving is positively associated with absolute brain size ( c ) and relative brain size across species ( d ). Problem-solving performance is each species’ mean number of trials to solve the four different problems; innovation rates are innovation reports corrected for investigator research effort obtained from refs. 3 , 26 ; relative brain sizes are the residuals of brain volumes with body weight, and absolute brain sizes are brain volumes; brain size and body weight data were obtained from ref. 27 . Graphs illustrate mean species’ trial values with s.e.m., ranked predictors and lines of values predicted by Bayesian phylogenetic mixed models. Filled blue circles, wild-caught songbird species; empty blue circles, domesticated songbird species (zebra finch and canary); red circles, the suboscine (eastern phoebe); solid trend lines, P MCMC.adj  < 0.05; dashed trend line, P MCMC.adj  > 0.05; species’ two-letter codes are listed in Supplementary Table 1 ; detailed results of MCMCglmm modelling and FDR-corrected P values ( P MCMC.adj ) are provided in Supplementary Table 2d . Image credits: Derrick Eidam for wild species and Mélanie Couture for domesticated species (zebra finch and canary).

Relationships are not driven by non-cognitive factors

We next examined whether non-cognitive variables were responsible for the relationships we found. We used the complete dataset of 203 individuals to implement phylogenetic Bayesian mixed models (MCMCglmm) that included variables of personality traits (shyness and neophobia), experimental testing conditions (wild-caught or domesticated, body condition, bird choice of food reward used in tests, capture site and fasting period), dietary generalism (number of food categories the species consumes in the wild 2 ) and phylogeny (Table 1 and Supplementary Table 5 ).

Full modelling analyses with all the above variables combined in the same model revealed that domesticated species were less shy than wild-caught species (Supplementary Table 5 ; models 1–4). Individual shyness was negatively associated with problem-solving performance but positively associated with reversal learning and self-control (Supplementary Table 5 ; models 9–12 and 17–24). In addition, neophobia was negatively associated with associative learning performance (Supplementary Table 5 ; models 13–16), fasting time was positively associated with neophobia (Supplementary Table 5 ; models 5–8) and food reward type was associated with reversal learning (Supplementary Table 5 ; models 17–20). However, the presence of these covariates in the models did not invalidate the previously found relationships between problem-solving, technical innovation and brain size, all of which remained significant (Supplementary Tables 1 and 5 ; models 9, 11 and 12). Finally, neophobia was positively associated with food innovation along with captive status, dietary generalism, reward type and fasting time (Supplementary Table 5 ; model 6), but the relationship with food innovation was not significant following the FDR correction (Table 1 ). In summary, full modelling analyses revealed that while a few covariates were associated with some cognitive measures, none accounted for the relationships between problem-solving, technical innovation in the wild and brain size.

Our results show that tests of problem-solving in captivity are an appropriate experimental assessment of technical innovativeness in the wild. The other cognitive traits we measured, namely, associative learning, reversal learning and self-control, were unrelated to innovation rates. Traits measured by these assays, as well as innovation in the wild, have all been considered components of behavioural flexibility 16 . Our results show that an umbrella term of this type is not homogeneous. The absence of relationships at the interindividual and interspecific levels suggests that the cognitive traits measured by our tasks are distinct and that only problem-solving assays measure, at least partially, the cognitive skills required to innovate in the wild.

Problem-solving is widely recognized as a hallmark of human executive functions 29 . Still, its assessment in animals has been the object of a number of questions concerning its cognitive nature, as well as its biological and ecological relevance (for example, ref. 30 ). Our results suggest that potential confounding variables such as shyness, neophobia or experimental conditions are not responsible per se for the interspecific variation observed, consistent with previous evidence at the intraspecific level (for example, ref. 10 ). Instead, technical innovation rate in the wild and brain size, both considered ecologically relevant metrics, are highly predictive of problem-solving performance. In fact, innovation rate is linked with a lower risk of extinction 3 and a greater colonization success 1 . Absolute and relative brain sizes are the only measures of a neural substrate available for our 15 species, but they are closely linked to finer measures such as neuron numbers 7 , 31 , the volume of the associative pallium 32 and expression levels of neurotransmitter receptors, which are all associated with innovation 7 , 33 , 34 .

Our study was conducted with the largest sample of avian species, individuals and assays thus far. Two notable studies on mammals have examined similar questions on large taxonomic samples. Performance on obstacle removal problems has been assessed in 39 species of captive carnivores and, as we found here, is associated with brain size 35 . Self-control performance was compared on a taxonomically heterogeneous sample of 36 species ranging from elephants to zebra finches 13 ; a subset of this analysis focused on a more homogeneous sample of 23 primate species and showed positive associations between self-control, brain size and innovation rate taken from a published database 5 . Given that the two mammal studies used only one type of assay, it is difficult to judge whether birds and mammals differ in the way brains, innovations and experimental assays are connected. Considering the remarkable degree of convergent evolution between birds and primates 36 , 37 , comparing primates on different assays is an obvious next step, given the known relationship between various experimental tasks 38 , 39 and field-based counts of cognition 6 .

In a review, Griffin and Guez 24 concluded that extractive foraging problems were a good experimental measure of innovativeness in the wild and that the diversity of the motor acts used in solving a problem was a critical factor in success 40 , 41 . In line with this hypothesis, diversity of technical innovations is a better predictor of relative brain size than any other measure on a broad sample of avian species from 76 families 28 . In our study, the fact that technical innovation rate in the wild is the only significant predictor of problem-solving suggests that trying out a diversity of motor solutions to a foraging problem in both captivity and the wild is more important than inhibiting an initial unproductive response (measured by self-control assays) or learning about cue changes (measured by associative and reversal learning assays). This is also the route, inspired by animal studies, taken by recent work in engineering, where motor diversity helps robots creatively solve problems for which they were not initially programmed 42 .

Taken together, our results validate long-standing but untested hypotheses concerning the links between problem-solving, innovation and the brain but question the assumption that behavioural flexibility can be concomitantly operationalized through innovation reports and assays of problem-solving, associative learning, reversal learning and self-control. The obvious next step is to examine in more detail which brain components are responsible for increased problem-solving skills in some species, which allow them to be more successful in changing environments.

Wild bird captures and acquisition of domestic birds

We caught 178 wild birds of 13 species between 2018 and 2020 (March to December) at the Rockefeller University Field Research Center (RUFRC) in Millbrook, NY, USA (latitude, 41° 46′ 3.0″ N; longitude, 73° 45′ 2.5″ W). Permits were obtained from all university and government instances for bird captures and experiments. Birds were captured using mist nets placed in 8 sites (4 open and 4 forested, each at 200 to 500 m) within a 30 ha area around the RUFRC main campus. The captured birds were weighed, measured, banded, sex-typed, and then placed into their behavioural cages.

In addition to the wild birds, we included 25 birds of 2 domesticated species. Twelve zebra finches aged between 9 and 15 months were obtained from the domestic colony at RUFRC, and 13 ‘American Singer’ canaries aged between 8 and 16 months were purchased from Stewart’s bird farms. Domesticated birds underwent the same processes as wild birds upon arrival at the behaviour laboratory.

Initially, only male birds were selected to enhance statistical power by minimizing potential variations in behaviour driven by sex. However, because capturing sufficient numbers of blue jays and European starlings proved challenging in our capture area, we included female birds of these species in the study ( n  = 3 for blue jays and n  = 4 for European starlings) as no significant cognitive differences were found compared to male birds of these species (Supplementary Table 6 ).

Morphometric measurements

Standard measurements were taken using the identical procedure described in ref. 10 . These measurements were taken by a single individual (J.-N.A.). To assess body condition, scaled mass index was calculated for each individual using wing length and body weight, following the procedure described in ref. 43 .

Housing conditions

Birds were housed individually in custom-designed aluminium cages measuring 81.3 cm × 55.9 cm × 68.6 cm in an indoor aviary at the RUFRC. Birds were visually (but not acoustically) isolated from each other by opaque plastic panels. A Brio 4K Ultra-HD camera (Logitech) was used to video-record and live-view all observations in an adjacent room where the birds could not see or hear the experimenter, which remained the same (J.-N.A.) throughout all behavioural tests.

To maintain the birds’ circadian rhythm and minimize stress, the daily lighting conditions in the aviary were adjusted to follow the natural light cycle. During the first three captivity days (Friday to Sunday), the birds were undisturbed, except for the daily replenishment of food and water. They had unrestricted access to water and food, which included sunflower seeds (Ultra Clean sunflowers, Kent Nutrition Group), mealworms (Bug Company), wax worms (Bug Company) and species-specific seed mix (blue jays and European starlings, wild bird mix of seeds, grain and nuts; canaries, canary seed mix; American goldfinches, half-and-half mix of thistle and canary seed mix; other species, finch seed mix (Blue Seal Neat Feast, Blue Seal Colours ‘n Chorus canary diet, Blue Seal Colours ‘n Chorus Finch Diet, Kent Nutrition Group)).

If any bird did not eat or displayed distress signs, it was immediately released. At the end of the captivity period, all birds, except for a few individuals killed for tissue sampling for another study, were released back to their initial capture site.

Molecular sexing

We determined the sex of all individuals, using a standard sex-typing PCR protocol 44 , 45 . Briefly, we collected approximately 20 µl of blood by puncturing the brachial vein. A PCR was run using 1 µl of DNA extracted from blood samples, and the amplified DNA was migrated on a 2% agarose gel.

Behavioural tests

General procedure.

Following the 3 day habituation period, the birds underwent our 6 day behavioural testing procedure in the same cage. They were food-deprived overnight before each testing day to ensure sufficient participation in the behavioural tests. We adjusted the deprivation period according to each bird’s body weight and night lengths throughout the seasons, both being expected to impact the fasting state. We used the following formula that we developed 22 : Deprivation time (h) = 2 × ln (Bodyweight (g)) + 0.2 × Night length (h) + 7. The same formula was applied each day to calculate the fasting period for each individual.

All feeding dishes and behavioural tasks were constructed in three different sizes and mounted on standardized white acrylic base plates: small (100 mm × 100 mm), medium (125 mm × 125 mm) and large (165 mm × 165 mm). Small apparatuses were used for birds weighing 10 to 20 g; medium, 21 to 40 g; and large, 41 to 85 g. On the first testing day, after food deprivation but before the behavioural tests, the birds were presented with three types of food (seed mix, mealworms and softened dog food pellets) to determine their preferred food, utilized as their reward in all behavioural tests. No bird chose dog food, 143 birds chose mealworms and 60 chose seeds.

The order of the behavioural tests was fixed for all birds to minimize the influence of test order on bird performance 46 . Only one cognitive test was conducted each day, except for the last day (see Cognitive tests). The first four days also included personality measurements before the cognitive tests. Problem-solving tasks considered ‘easier’ were presented at the beginning (days 1 and 2), while more challenging tasks were presented at the end of the captivity period (day 6) to increase the overall probability of success. The tests started between 7:00 and 11:00, depending on the calculated fasting period for each bird, and concluded no later than 16:00. Then, the birds were allowed to feed ad libitum until the start of the subsequent overnight deprivation. A 5 min pause was given between each trial for all tests.

Personality measurements

Shyness was the first measurement taken on the first four testing days. The feeding dish (Extended Data Fig. 1a ) was introduced into the cage, and the experimenter immediately left and started a stopwatch. The latency (in seconds) to feed was recorded when the birds first contacted the food. No maximum latency cap was set for shyness trials. The birds were allowed to feed for 15 s before the food was removed from the cage. Shyness was measured again after the neophobia assessment (see below). The average of the two shyness measurements was calculated for each day, and the shyness variable used in the analyses was the mean of these four shyness values. While shyness decreased from day 1 to day 4 due to habituation to the experimenter (means ± s.e.m.; day 1, 415.96 ± 65.80 s; day 2, 88.51 ± 33.41 s; day 3, 38.78 ± 8.90 s; day 4, 23.74 ± 5.23 s; n  = 203), the effect was consistent across all species (slope across 4 days for all species, mean ± s.e.m., −1.13 ± 0.12). Taking into account the effect of the test day and species, shyness measurements were repeatable 47 across the four days for each individual (Supplementary Table 7 ).

After a 5 min pause, neophobia was assessed by presenting a novel object beside the feeding dish and recording the latency to feed. The mean shyness latency for that day was subtracted from the neophobia latency to obtain a measure of ‘pure’ neophobia. This procedure was repeated for four consecutive days, with a different novel object introduced each day (day 1, four coloured cotton balls, Extended Data Fig. 1b ; day 2, two stacks of coloured Duplo blocks, Extended Data Fig. 1c ; day 3, two Erlenmeyer flasks with coloured tapes, Extended Data Fig. 1d ; day 4, one inflated purple glove, Extended Data Fig. 1e ). We used three sets (small/medium/large) of neophobia objects matched to the body mass category of the species (see General procedure). The maximum allotted latency to feed was 2 h; if the birds did not feed before this limit, their recorded latency was 7,201 s (which occurred 22 times out of the 812 neophobia trials). Neophobia measurements were repeatable across the four days (Supplementary Table 7 ). We used the average of the four neophobia measurements in statistical analyses.

Cognitive tests

To measure problem-solving, we presented the birds with novel problems that they had to solve on their own, without any previous training or shaping. This method differs from some studies that utilize training procedures on ‘novel foraging tasks’ (also known as ‘shaping’ or ‘stage-learning’; for example, ref. 48 ) and then assess how well the animals are capable of repeating the solution. Applying a previously learned solution likely involves different cognitive processes than solving a novel problem. To enhance the precision of our problem-solving measurement, we implemented four different problems, each built in three sizes to match the body mass category of each species.

On the first day, we presented the ‘lid-pulling’ problem-solving test, consisting of a glass flask containing a food reward, sealed with a loose cork lid that could be removed by pecking its sides or grabbing the top wooden tip (Extended Data Fig. 1f and Supplementary Video 1 ). To reduce neophobia toward the task, the apparatus was first presented open and left inside the cage until the birds consumed the reward. After a 5 min pause, the task was presented closed and left in the cage for 5 min or until the bird solved the problem. If unsuccessful, the birds were given a 5 min pause, after which the following trial commenced. Birds that failed to solve the task within 10 trials were considered unsuccessful and assigned an arbitrary value of 11 trials. Birds that succeeded underwent the task again to confirm their success. Of the successful birds, 91.3% (84/92) solved the problem a second time. The same testing procedure was used for the following problem-solving tasks.

On the second day, we presented the ‘lid-flipping’ problem, which consisted of a transparent plastic container loosely closed with a flat plastic lid (Extended Data Fig. 1g and Supplementary Video 2 ). The birds could solve this problem by grabbing the lid from the side or pecking it from bottom to top. Out of the birds that succeeded in solving the lid-flipping problem within 10 trials, 99.1% (107/108) solved it again upon the second presentation of the task.

On the third day, we evaluated self-control using a detour-reaching task (Extended Data Fig. 1j and Supplementary Videos 5 and 6 ), following a standard procedure 34 . The birds first underwent a training phase, during which they only had to consume a reward inside an opaque cylinder, without any time limit. After seven trials, they advanced to the testing phase, which used an identical but transparent cylinder. In this phase, the birds had to reach directly for the reward without pecking at any part of the cylinder to succeed. The success criterion was seven consecutive successful trials, and the maximum allotted trial number was 50; after that, the birds were given a score of 51 trials if unsuccessful.

On the fourth day, we presented a colour-discrimination associative learning task using an apparatus identical to the lid-flipping task but painted entirely yellow or green (Extended Data Fig. 1k and Supplementary Video 7 ). Before proceeding with the associative learning test, we ensured that all birds were capable of removing the lids from the containers. Birds that did not solve the task during the problem-solving procedure on day 2 were trained until they mastered it using the shaping procedure described in ref. 34 , without a maximum trial limit. In brief, the task was presented in progressively harder steps: open, half-closed, three-quarter closed, closed upside down and finally fully closed. Each step had to be completed twice before progressing to the next step. Finally, all birds were given five additional practice trials. At the end of this training phase, all birds could flip lids efficiently.

The associative learning procedure was similar to ref. 46 . To familiarize the birds with the task, two open lid-flipping apparatuses (one green, one yellow) were placed on each lateral end of the cage and left inside until the birds fed from both. After a 5 min pause, the apparatuses were presented in switched positions but with closed lids. They were left in the cage until the birds opened and fed from both. Next, the birds underwent a colour choice trial to account for potential colour preferences. The tasks were presented closed and were removed after the birds ate from the first opened apparatus, which was considered their preferred colour. The reward was placed in the non-preferred colour for the subsequent trials. The apparatuses were then presented closed in alternating positions for each trial and were removed immediately if the birds chose the non-rewarded colour or after allowing them to eat the reward (worm or seeds) for 10 s if they chose the rewarded colour. The success criterion for associative learning was 7 consecutive correct trials, excluding the training trials; thus, the best possible score was 7 trials. This task had no maximum trial number to ensure that all birds learned the initial colour before proceeding to the subsequent reversal learning test.

On the fifth day, a reversal learning test was conducted using the same associative learning apparatus and procedure. However, the colours were switched: the previously rewarded colour was now non-rewarded, and vice versa. The success criterion was seven consecutive correct trials. Birds that failed to meet this criterion within 100 trials were given a score of 101 trials.

On the sixth day, we presented two additional problem-solving tasks. First, the ‘lid-piercing’ problem consisted of a transparent plastic container covered with a piece of aluminium foil secured with a rubber band (Extended Data Fig. 1h and Supplementary Video 3 ). The birds had to pierce or tear the aluminium foil to access the reward. After the second presentation, all successful birds (139 out of 139) solved the lid-piercing problem again.

On the same day, we presented the ‘stick-pulling’ problem-solving task, a transparent plastic container attached to a wooden stick and inserted into a transparent plexiglass enclosure (Extended Data Fig. 1I and Supplementary Video 4 ). The birds had to pull the stick to access the container and remove the lid to obtain the reward. Among the successful birds, 88.8% (71/80) solved the stick-pulling problem a second time.

Innovation and brain size data

Innovation values were obtained from the most recent innovation database 3 , 49 . Innovations are published cases of novel feeding (incorporation of an unusual or previously unknown food source in the animal’s diet) or technical (use of a novel foraging technique) behaviours in the literature, based on the presence in the report of keywords such as ‘new’, ‘never observed’, ‘first report’, ‘opportunistic’ and so on. A standard practice when using innovation databases is to correct innovation rates with research effort, that is, the number of articles published for each species 3 , as the probability of observing an innovation increases with the time spent observing a species 28 . We used the residuals of a linear model with logged numbers of innovations (food type or technical) as the dependent variable and logged research effort as a fixed independent effect.

Species data for brain size and body mass (average for both sexes when available) were collected from ref. 27 . Relative brain sizes were calculated using the residuals from a linear model with logged brain volumes as the dependent variable and logged body mass as the fixed independent effect. Brain size data for the chipping sparrow ( Spizella passerina ) was unavailable. Therefore, we used the brain volume of its closest relative, the American tree sparrow ( Spizella arborea ) and scaled it proportionally with the body size difference between the two species. Excluding the chipping sparrow did not change the outcomes of our brain size analyses. Brain size data for individual sexes are not available.

Statistical analyses

All statistical analyses were conducted in R version 4.3.0 50 . Trial numbers to success criterion were used for all cognitive tasks. Using latencies instead yielded similar results. The average trial number to solve the four problems was used in our models as they were all strongly associated (Extended Data Fig. 2 and Supplementary Table 2a ).

The repeatability of the shyness and neophobia measurements were calculated with the RptR 0.9.22 package 51 using individual measurements as the dependent variable, the measurement day (1–4) and species as fixed effects, and the bird identity as the grouping variable and random effect ( n  = 203 individuals; each personality trait was measured 4 times).

All interspecific relationships were assessed with phylogenetic Bayesian models using the MCMCglmm 52 package in R. We conducted models with each species’ mean cognitive performance (trials) set as the dependent and independent variables (with no other covariables, as opposed to the full modelling strategy; see below), with phylogenetic distance and captive status (wild-caught or domesticated) set as random effects. The MCMCglmm parameters can be found in the available code. The models were repeated 100 times, and the values from all runs were averaged. A single consensus phylogenetic tree, obtained from ref. 53 , was used for phylogeny calculations in the models.

Interindividual relationships were assessed with linear mixed models (lmer) in R using the complete dataset of 203 values, with each trait set as either dependent or independent variables, and species as a random variable. The results were then validated using corresponding MCMCglmm with ‘species’ added as a random effect, in addition to the random ‘animal’ phylogenetic term to account for phylogeny. We also assessed interindividual relationships between cognitive traits within each species by running simple linear models (lm) in R for each species separately.

We then explored relationships between each trait of interest by performing full models using MCMCglmm, this time with the whole dataset of 203 individual logged values instead of species means, and with potential covariates included. Phylogenetic relationships (to account for non-equivalent phylogenetic distance among all species), species identity (to account for repeated testing of each species) and capture sites (eight levels for capture locations, to account for potential relatedness of the individuals or any other ecological factor linking individuals) were included as random effects. Fasting time, reward type, body condition, shyness, neophobia, captive status and dietary generalism 2 were included in all models as fixed effects. Because higher trial numbers represent lower performance in cognitive tasks, results of negative estimates with published metrics (innovation rates and brain size) represent positive relationships (for example, more innovative species solve problems in fewer trials). For all models, we verified that autocorrelation was below an acceptable threshold (all were <0.1) using the ‘autocorr.diag’ function and by visualizing the plots of the posterior distributions of the variance components of our models. Each full model was run 100 times, and we report the means of all values in Supplementary Table 5 (‘a’ models). We then removed non-significant fixed effects to increase the fit of the models. We first removed variables with the highest P values in the initial models, the models were rerun and the process was repeated until only significant variables ( P  < 0.05) remained in the final models. When only significant variables remained, we reran the models 100 times to report the final model mean values (Supplementary Table 5 , ‘b’ models). Table 1 reports model results for only variables of interest (metrics of innovation and brain size) obtained in final models (run with significant covariables, if any). When no variable of interest remained (thus being absent in Supplementary Table 5 , ‘b’ models), we reran the models 100 times with innovation and brain size variables re-added to obtain their estimates.

P values from all analyses (except the full MCMCglmm models of Supplementary Table 5 ) were adjusted to account for multiple testing with the Benjamini–Hochberg 54 FDR correction using the ‘p.adjust’ function in R, ‘BH’ method. P values were grouped by blocks of similar analysed data to perform the adjustments (each panel of Extended Tables 2–4 constituted a separate block; for example, Supplementary Table 2a constituted a block of 6 corrected P values; also see available code). The significance threshold was set at P  = 0.05.

Notes on study species selection

This study aimed to compare cognitive traits in songbird species, which show relatively homogenous morphologies. Our behavioural tasks required the birds to perform motor actions; therefore, including birds from more phylogenetically distant clades would likely increase morphological variation (for example, species with curved/thin beaks, species that rely on their legs to manipulate objects and so on), which would have complicated the interpretation of our results as the outcomes could have been influenced by morphology rather than cognition. We also added a closely related non-songbird species (eastern phoebe, a suboscine) as it was abundant in our capture area and its morphology was sufficiently similar to our other study species to allow it to perform in our behavioural tasks. However, we were cautious when interpreting data on this species; separate tests that excluded the suboscine did not change the outcome of our analyses. In addition, all analyses controlled for phylogenetic distance. The 13 wild-caught study species were chosen from a total of 21 species caught and tested during the first season, based on their feasibility of capture (sufficient number of caught birds per species to achieve a minimum of n  = 12 male birds), assessed at the end of the first year of capture. We did not include data from the species for which only one or two birds per species were tested because our study aimed to provide as robust a test as possible of the different behavioural assays, based on a large sample of subjects per species. In another study conducted in parallel focusing on the link between problem-solving and vocal learning complexity 22 , we included problem-solving data from all 21 wild-caught species to verify whether our conclusions held when looking at more species, but they were not included in the present study for the above reason. In addition to the 13 wild bird species, we tested two domesticated species, the canary and the zebra finch. These two species are by far the most studied songbirds. We believe that including well-characterized birds raised in the same conditions provided an opportunity to generate valuable knowledge. Still, we were also cautious when interpreting data from those species, as domestication could have affected relationships between traits. Performing all analyses without these two species did not change the outcomes. We also included a ‘captive status’ variable (wild-caught or domesticated) in our models to account for those potential differences.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The raw dataset is available at https://zenodo.org/records/10206756 .

Code availability

The code scripts are available at https://zenodo.org/records/10206756 .

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Acknowledgements

We thank S. Ducatez and F. Sayol for help with the statistical analyses and L. Cauchard for insightful discussions on the manuscript. This study was supported by the Howard Hughes Medical Institute and the Rockefeller University, a Banting postdoctoral fellowship and an Natural Sciences and Engineering Research Council postdoctoral fellowship to J.-N.A., and Howard Hughes Medical Institute funds and a National Institutes of Health Director’s Transformative Research Award to E.D.J.

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The Rockefeller University Field Research Center, Millbrook, NY, USA

Jean-Nicolas Audet, Mélanie Couture & Erich D. Jarvis

Howard Hughes Medical Institute, Chevy Chase, MD, USA

Jean-Nicolas Audet & Erich D. Jarvis

Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA

The Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA

Mélanie Couture & Erich D. Jarvis

Department of Biology, McGill University, Montreal, Quebec, Canada

Louis Lefebvre

CREAF, Autonomous University of Barcelona, Cerdanyola del Vallès, Spain

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Contributions

Conceptualization: J.-N.A., M.C., L.L., E.D.J. Methodology: J.-N.A., M.C., L.L. Investigation: J.-N.A., M.C. Visualization: J.-N.A., M.C. Funding acquisition: J.-N.A., E.D.J. Supervision: J.-N.A., E.D.J. Writing—original draft: J.-N.A., L.L. Writing—review and editing: J.-N.A., M.C., L.L., E.D.J.

Corresponding author

Correspondence to Jean-Nicolas Audet .

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Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Ecology & Evolution thanks Zoltán Barta, Claudia Mettke-Hofmann and David (R) Wilson for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended data fig. 1 behavioral tasks used to assess behaviour in the 15 species..

( a ) Feeding dish used throughout the captivity period, including for shyness assessment. ( b-e ) Novel objects used to assess neophobia on days 1 to 4, respectively. (F) ‘Lid-pulling’ problem-solving task. ( g ) ‘Lid-flipping’ problem-solving task. ( h ) ‘Lid-piercing’ problem-solving task. ( i ) ‘Stick-pulling’ problem-solving task. ( j ) Detour reaching task. An opaque cylinder was used for the training phase (left), and a transparent cylinder for the testing phase (right). ( k ) Color discrimination learning apparatus used to assess associative and reversal learning. All tasks have been constructed in three sizes, matching the body size of the tested birds. Image credits: Mélanie Couture and Jean-Nicolas Audet for all pictures.

Extended Data Fig. 2 Comparisons of the 15 species’ performance on each problem-solving task.

Species that solve the lid-flipping problem in fewer trials are also quicker to solve ( a ) lid-pulling, ( b ) lid-piercing, and ( c ) stick-pulling problems. Performance on the lid-pulling problem is also associated with ( d ) lid-piercing and ( e ) stick-pulling problems’ performance, and ( f ) stick-pulling with lid-piercing problems’ performance. Graphs illustrate mean species’ trial values with SEM and lines of values predicted by Bayesian phylogenetic mixed models. Filled blue circles, wild-caught songbird species; empty blue circles, domesticated songbird species (zebra finch and canary); red circles, the suboscine (Eastern phoebe); solid trend lines: P MCMC.adj  < 0.05; species’ two-letter codes are listed in Supplementary Table 1; detailed results of MCMCglmm modelling and FDR-corrected p-values ( P MCMC.adj ) are provided in Supplementary Table 2a.

Extended Data Fig. 3 Interspecific relationships between cognitive and personality traits.

Species’ average problem-solving performance is not associated with their average ( a ) shyness or ( b ) neophobia. Species’ average associative learning performance is not associated with their ( c ) shyness or ( d ) neophobia. Species’ average reversal learning performance is not associated with their ( e ) shyness or ( f ) neophobia. Self-control performance (detour-reaching task) is not associated with their ( g ) shyness or ( h ) neophobia. Graphs illustrate mean species’ trial values, logged personality latencies, and lines of values predicted by Bayesian phylogenetic mixed models. Filled blue circles, wild-caught songbird species; empty blue circles, domesticated songbird species (zebra finch and canary); red circles, the suboscine (Eastern phoebe); error bars: SEM; dashed trend lines: P MCMC.adj  > 0.05; species’ two-letter codes are listed in Supplementary Table 1; detailed results of MCMCglmm modelling and FDR-corrected p-values ( P MCMC.adj ) are provided in Supplementary Table 2c.

Extended Data Fig. 4 Intraspecific relationships between associative learning and problem-solving performance for each of the 15 species.

None of the species shows a significant association between associative learning and problem-solving (all P  > 0.05). P-values were obtained from linear models (details in Supplementary Table 4a); dashed regression lines: P  > 0.05.

Extended Data Fig. 5 Intraspecific relationships between reversal learning and problem-solving performance for each of the 15 species.

None of the species shows a significant association between reversal learning and problem-solving (all P  > 0.05). P-values were obtained from linear models (details in Supplementary Table 4b); dashed regression lines: P  > 0.05.

Extended Data Fig. 6 Intraspecific relationships between detour reaching and problem-solving performance for each of the 15 species.

None of the species shows a significant association between detour reaching and problem-solving (all P  > 0.05). P-values were obtained from linear models (details in Supplementary Table 4c); dashed regression lines: P  > 0.05.

Extended Data Fig. 7 Intraspecific relationships between reversal learning and self-control performance for each of the 15 species.

Individual performance in the reversal learning task is significantly and negatively associated with detour reaching performance in the blue jay ( R 2  = 0.351, P  = 0.0193), eastern phoebe ( R 2  = 0.338, P  = 0.0219), but not in the other species (all other P > 0.05). R 2 and P-values were obtained from linear models (details in Supplementary Table 4e); solid regression lines: P  < 0.05, dashed regression lines: P  > 0.05.

Extended Data Fig. 8 Intraspecific relationships between self-control and associative learning performance for each of the 15 species.

Individual performance in the detour reaching task is significantly and negatively associated with associative learning performance in the blue jay ( R 2  = 0.518, P  = 0.0034), positively in the house wren ( R 2  = 0.435, P  = 0.0085), but not in the other species (all other P  > 0.05). R 2 and P-values were obtained from linear models (details in Supplementary Table 4f); solid regression lines: P  < 0.05, dashed regression lines: P  > 0.05.

Extended Data Fig. 9 Intraspecific relationships between associative learning and reversal learning performance for each of the 15 species.

Individual performance in the associative learning task is significantly and positively associated with reversal learning performance in the blue jay ( R 2  = 0.691, P  = 0.0003), European starling ( R 2  = 0.631, P  = 0.0001), grey catbird ( R 2  = 0.229, P  = 0.0406) and white-breasted nuthatch ( R 2  = 0.260, P  = 0.0431), but not in the other species (all other P  > 0.05). R 2 and P-values were obtained from linear models (details in Supplementary Table 4d); solid regression lines: P  < 0.05, dashed regression lines: P  > 0.05.

Extended Data Fig. 10 Relationships between species’ performance on each cognitive task, innovation rates and brain size.

a – d , Associative learning performance between species is not significantly associated with their technical innovation rates ( a ), food innovation rates ( b ), absolute brain size ( c ) or relative brain size ( d ). e – h , Reversal learning performance between species is not significantly associated with their technical innovation rates ( e ), food innovation rates ( f ), absolute brain size ( g ) or relative brain size ( h ). i – l , Detour-reaching performance (self-control) between species is not significantly associated with their technical innovation rates ( i ), food innovation rates ( j ), absolute brain size ( k ) or relative brain size ( l ). Innovation values are residuals of innovation reports corrected for investigator research effort obtained from refs. 3 , 26 ; relative brain sizes are the residuals of brain volumes corrected for average species’ body weight, and absolute brain sizes are brain volumes; brain size and body weight data were obtained from ref. 27 . Graphs illustrate mean species’ trial values with s.e.m., ranked predictors and lines of values predicted by Bayesian phylogenetic mixed models. Filled blue circles, wild-caught songbird species; empty blue circles, domesticated songbird species (zebra finch and canary); red circles, the suboscine (eastern phoebe); dashed trend lines, P MCMC.adj  > 0.05; species’ two-letter codes are listed in Supplementary Table 1; detailed results of MCMCglmm modelling and FDR-corrected P values ( P MCMC.adj ) are provided in Supplementary Table 2e–g. Image credits: Derrick Eidam for wild species and Mélanie Couture for domesticated species (zebra finch and canary).

Supplementary information

Supplementary information.

Supplementary Tables 1–7.

Reporting Summary

Peer review file, supplementary video 1.

Bird performing the lid-pulling problem-solving task.

Supplementary Video 2

Bird performing the lid-flipping problem-solving task.

Supplementary Video 3

Bird performing the lid-piercing problem-solving task.

Supplementary Video 4

Bird performing the stick-pulling problem-solving task.

Supplementary Video 5

Bird failing a trial on the detour reaching task (self-control).

Supplementary Video 6

Bird succeeding a trial on the detour reaching task (self-control).

Supplementary Video 7

Bird performing the discrimination learning task (associative and reversal learning).

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Audet, JN., Couture, M., Lefebvre, L. et al. Problem-solving skills are predicted by technical innovations in the wild and brain size in passerines. Nat Ecol Evol (2024). https://doi.org/10.1038/s41559-024-02342-7

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