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26 Expert-Backed Problem Solving Examples – Interview Answers

Published: February 13, 2023

Interview Questions and Answers

Actionable advice from real experts:

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Biron Clark

Former Recruiter

3 examples of problem solving

Contributor

Dr. Kyle Elliott

Career Coach

3 examples of problem solving

Hayley Jukes

Editor-in-Chief

Biron Clark

Biron Clark , Former Recruiter

Kyle Elliott , Career Coach

Image of Hayley Jukes

Hayley Jukes , Editor

As a recruiter , I know 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 are more likely to hire you if you seem like you can handle unexpected challenges while staying calm and logical.

But how do they measure this?

Hiring managers will ask you interview questions about your problem-solving skills, and they might also look for examples of problem-solving on your resume and cover letter. 

In this article, I’m going to share a list of problem-solving examples and sample interview answers to questions like, “Give an example of a time you used logic to solve a problem?” and “Describe a time when you had to solve a problem without managerial input. How did you handle it, and what was the result?”

  • Problem-solving involves identifying, prioritizing, analyzing, and solving problems using a variety of skills like critical thinking, creativity, decision making, and communication.
  • Describe the Situation, Task, Action, and Result ( STAR method ) when discussing your problem-solving experiences.
  • Tailor your interview answer with the specific skills and qualifications outlined in the job description.
  • Provide numerical data or metrics to demonstrate the tangible impact of your problem-solving efforts.

What are Problem Solving Skills? 

Problem-solving is the ability to identify a 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 encompasses other skills that can be showcased in an interview response and your resume. Problem-solving skills examples include:

  • Critical thinking
  • Analytical skills
  • Decision making
  • Research skills
  • Technical skills
  • Communication skills
  • Adaptability and flexibility

Why is Problem Solving Important in the Workplace?

Problem-solving is essential in the workplace because it directly impacts productivity and efficiency. Whenever you encounter a problem, tackling it head-on prevents minor issues from escalating into bigger ones that could disrupt the entire workflow. 

Beyond maintaining smooth operations, your ability to solve problems fosters innovation. It encourages you to think creatively, finding better ways to achieve goals, which keeps the business competitive and pushes the boundaries of what you can achieve. 

Effective problem-solving also contributes to a healthier work environment; it reduces stress by providing clear strategies for overcoming obstacles and builds confidence within teams. 

Examples of Problem-Solving 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

How To Answer “Tell Us About a Problem You Solved”

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 mentions problem-solving as a necessary skill), I recommend using the STAR method.

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. 

Start by briefly describing the general situation and the task at hand. 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 the positive result you achieved.

Note: Our sample answers below are structured following the STAR formula. Be sure to check them out!

EXPERT ADVICE

3 examples of problem solving

Dr. Kyle Elliott , MPA, CHES Tech & Interview Career Coach caffeinatedkyle.com

How can I communicate complex problem-solving experiences clearly and succinctly?

Before answering any interview question, it’s important to understand why the interviewer is asking the question in the first place.

When it comes to questions about your complex problem-solving experiences, for example, the interviewer likely wants to know about your leadership acumen, collaboration abilities, and communication skills, not the problem itself.

Therefore, your answer should be focused on highlighting how you excelled in each of these areas, not diving into the weeds of the problem itself, which is a common mistake less-experienced interviewees often make.

Tailoring Your Answer Based on the Skills Mentioned in the Job Description

As a recruiter, one of the top tips I can give you when responding to the prompt “Tell us about a problem you solved,” is to tailor your answer to the specific skills and qualifications outlined in the job description. 

Once you’ve pinpointed the skills and key competencies the employer is seeking, craft your response to highlight experiences where you successfully utilized or developed those particular abilities. 

For instance, if the job requires strong leadership skills, focus on a problem-solving scenario where you took charge and effectively guided a team toward resolution. 

By aligning your answer with the desired skills outlined in the job description, you demonstrate your suitability for the role and show the employer that you understand their needs.

Amanda Augustine expands on this by saying:

“Showcase the specific skills you used to solve the problem. Did it require critical thinking, analytical abilities, or strong collaboration? Highlight the relevant skills the employer is seeking.”  

Interview Answers to “Tell Me About a Time You Solved 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,” or “Tell me about a time you solved a problem,” since you’re likely to hear different versions of this interview question in all sorts of industries.

The example interview responses are structured using the STAR method and are categorized into the top 5 key problem-solving skills recruiters look for in a candidate.

1. Analytical Thinking

3 examples of problem solving

Situation: In my previous role as a data analyst , our team encountered a significant drop in website traffic.

Task: I was tasked with identifying the root cause of the decrease.

Action: I conducted a thorough analysis of website metrics, including traffic sources, user demographics, and page performance. Through my analysis, I discovered a technical issue with our website’s loading speed, causing users to bounce. 

Result: By optimizing server response time, compressing images, and minimizing redirects, we saw a 20% increase in traffic within two weeks.

2. Critical Thinking

3 examples of problem solving

Situation: During a project deadline crunch, our team encountered a major technical issue that threatened to derail our progress.

Task: My task was to assess the situation and devise a solution quickly.

Action: I immediately convened a meeting with the team to brainstorm potential solutions. Instead of panicking, I encouraged everyone to think outside the box and consider unconventional approaches. We analyzed the problem from different angles and weighed the pros and cons of each solution.

Result: By devising a workaround solution, we were able to meet the project deadline, avoiding potential delays that could have cost the company $100,000 in penalties for missing contractual obligations.

3. Decision Making

3 examples of problem solving

Situation: As a project manager , I was faced with a dilemma when two key team members had conflicting opinions on the project direction.

Task: My task was to make a decisive choice that would align with the project goals and maintain team cohesion.

Action: I scheduled a meeting with both team members to understand their perspectives in detail. I listened actively, asked probing questions, and encouraged open dialogue. After carefully weighing the pros and cons of each approach, I made a decision that incorporated elements from both viewpoints.

Result: The decision I made not only resolved the immediate conflict but also led to a stronger sense of collaboration within the team. By valuing input from all team members and making a well-informed decision, we were able to achieve our project objectives efficiently.

4. Communication (Teamwork)

3 examples of problem solving

Situation: During a cross-functional project, miscommunication between departments was causing delays and misunderstandings.

Task: My task was to improve communication channels and foster better teamwork among team members.

Action: I initiated regular cross-departmental meetings to ensure that everyone was on the same page regarding project goals and timelines. I also implemented a centralized communication platform where team members could share updates, ask questions, and collaborate more effectively.

Result: Streamlining workflows and improving communication channels led to a 30% reduction in project completion time, saving the company $25,000 in operational costs.

5. Persistence 

Situation: During a challenging sales quarter, I encountered numerous rejections and setbacks while trying to close a major client deal.

Task: My task was to persistently pursue the client and overcome obstacles to secure the deal.

Action: I maintained regular communication with the client, addressing their concerns and demonstrating the value proposition of our product. Despite facing multiple rejections, I remained persistent and resilient, adjusting my approach based on feedback and market dynamics.

Result: After months of perseverance, I successfully closed the deal with the client. By closing the major client deal, I exceeded quarterly sales targets by 25%, resulting in a revenue increase of $250,000 for the company.

Tips to Improve Your Problem-Solving Skills

Throughout your career, being able to showcase and effectively communicate your problem-solving skills gives you more leverage in achieving better jobs and earning more money .

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.

Don’t just say you’re good at solving problems. Show it with specifics. How much did you boost efficiency? Did you save the company money? Adding numbers can really make your achievements stand out.

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 improve researching and analyzing a situation, how you can get better at communicating, and deciding on 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.

More Interview Resources

  • 3 Answers to “How Do You Handle Stress?”
  • How to Answer “How Do You Handle Conflict?” (Interview Question)
  • Sample Answers to “Tell Me About a Time You Failed”

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About the Author

Biron Clark is a former executive recruiter who has worked individually with hundreds of job seekers, reviewed thousands of resumes and LinkedIn profiles, and recruited for top venture-backed startups and Fortune 500 companies. He has been advising job seekers since 2012 to think differently in their job search and land high-paying, competitive positions. Follow on Twitter and LinkedIn .

Read more articles by Biron Clark

About the Contributor

Kyle Elliott , career coach and mental health advocate, transforms his side hustle into a notable practice, aiding Silicon Valley professionals in maximizing potential. Follow Kyle on LinkedIn .

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About the Editor

Hayley Jukes is the Editor-in-Chief at CareerSidekick with five years of experience creating engaging articles, books, and transcripts for diverse platforms and audiences.

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39 Best Problem-Solving Examples

39 Best Problem-Solving Examples

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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problem-solving examples and definition, explained below

Problem-solving is a process where you’re tasked with identifying an issue and coming up with the most practical and effective solution.

This indispensable skill is necessary in several aspects of life, from personal relationships to education to business decisions.

Problem-solving aptitude boosts rational thinking, creativity, and the ability to cooperate with others. It’s also considered essential in 21st Century workplaces.

If explaining your problem-solving skills in an interview, remember that the employer is trying to determine your ability to handle difficulties. Focus on explaining exactly how you solve problems, including by introducing your thoughts on some of the following frameworks and how you’ve applied them in the past.

Problem-Solving Examples

1. divergent thinking.

Divergent thinking refers to the process of coming up with multiple different answers to a single problem. It’s the opposite of convergent thinking, which would involve coming up with a singular answer .

The benefit of a divergent thinking approach is that it can help us achieve blue skies thinking – it lets us generate several possible solutions that we can then critique and analyze .

In the realm of problem-solving, divergent thinking acts as the initial spark. You’re working to create an array of potential solutions, even those that seem outwardly unrelated or unconventional, to get your brain turning and unlock out-of-the-box ideas.

This process paves the way for the decision-making stage, where the most promising ideas are selected and refined.

Go Deeper: Divervent Thinking Examples

2. Convergent Thinking

Next comes convergent thinking, the process of narrowing down multiple possibilities to arrive at a single solution.

This involves using your analytical skills to identify the best, most practical, or most economical solution from the pool of ideas that you generated in the divergent thinking stage.

In a way, convergent thinking shapes the “roadmap” to solve a problem after divergent thinking has supplied the “destinations.”

Have a think about which of these problem-solving skills you’re more adept at: divergent or convergent thinking?

Go Deeper: Convergent Thinking Examples

3. Brainstorming

Brainstorming is a group activity designed to generate a multitude of ideas regarding a specific problem. It’s divergent thinking as a group , which helps unlock even more possibilities.

A typical brainstorming session involves uninhibited and spontaneous ideation, encouraging participants to voice any possible solutions, no matter how unconventional they might appear.

It’s important in a brainstorming session to suspend judgment and be as inclusive as possible, allowing all participants to get involved.

By widening the scope of potential solutions, brainstorming allows better problem definition, more creative solutions, and helps to avoid thinking “traps” that might limit your perspective.

Go Deeper: Brainstorming Examples

4. Thinking Outside the Box

The concept of “thinking outside the box” encourages a shift in perspective, urging you to approach problems from an entirely new angle.

Rather than sticking to traditional methods and processes, it involves breaking away from conventional norms to cultivate unique solutions.

In problem-solving, this mindset can bypass established hurdles and bring you to fresh ideas that might otherwise remain undiscovered.

Think of it as going off the beaten track when regular routes present roadblocks to effective resolution.

5. Case Study Analysis

Analyzing case studies involves a detailed examination of real-life situations that bear relevance to the current problem at hand.

For example, if you’re facing a problem, you could go to another environment that has faced a similar problem and examine how they solved it. You’d then bring the insights from that case study back to your own problem.

This approach provides a practical backdrop against which theories and assumptions can be tested, offering valuable insights into how similar problems have been approached and resolved in the past.

See a Broader Range of Analysis Examples Here

6. Action Research

Action research involves a repetitive process of identifying a problem, formulating a plan to address it, implementing the plan, and then analyzing the results. It’s common in educational research contexts.

The objective is to promote continuous learning and improvement through reflection and action. You conduct research into your problem, attempt to apply a solution, then assess how well the solution worked. This becomes an iterative process of continual improvement over time.

For problem-solving, this method offers a way to test solutions in real-time and allows for changes and refinements along the way, based on feedback or observed outcomes. It’s a form of active problem-solving that integrates lessons learned into the next cycle of action.

Go Deeper: Action Research Examples

7. Information Gathering

Fundamental to solving any problem is the process of information gathering.

This involves collecting relevant data , facts, and details about the issue at hand, significantly aiding in the understanding and conceptualization of the problem.

In problem-solving, information gathering underpins every decision you make.

This process ensures your actions are based on concrete information and evidence, allowing for an informed approach to tackle the problem effectively.

8. Seeking Advice

Seeking advice implies turning to knowledgeable and experienced individuals or entities to gain insights on problem-solving.

It could include mentors, industry experts, peers, or even specialized literature.

The value in this process lies in leveraging different perspectives and proven strategies when dealing with a problem. Moreover, it aids you in avoiding pitfalls, saving time, and learning from others’ experiences.

9. Creative Thinking

Creative thinking refers to the ability to perceive a problem in a new way, identify unconventional patterns, or produce original solutions.

It encourages innovation and uniqueness, often leading to the most effective results.

When applied to problem-solving, creative thinking can help you break free from traditional constraints, ideal for potentially complex or unusual problems.

Go Deeper: Creative Thinking Examples

10. Conflict Resolution

Conflict resolution is a strategy developed to resolve disagreements and arguments, often involving communication, negotiation, and compromise.

When employed as a problem-solving technique, it can diffuse tension, clear bottlenecks, and create a collaborative environment.

Effective conflict resolution ensures that differing views or disagreements do not become roadblocks in the process of problem-solving.

Go Deeper: Conflict Resolution Examples

11. Addressing Bottlenecks

Bottlenecks refer to obstacles or hindrances that slow down or even halt a process.

In problem-solving, addressing bottlenecks involves identifying these impediments and finding ways to eliminate them.

This effort not only smooths the path to resolution but also enhances the overall efficiency of the problem-solving process.

For example, if your workflow is not working well, you’d go to the bottleneck – that one point that is most time consuming – and focus on that. Once you ‘break’ this bottleneck, the entire process will run more smoothly.

12. Market Research

Market research involves gathering and analyzing information about target markets, consumers, and competitors.

In sales and marketing, this is one of the most effective problem-solving methods. The research collected from your market (e.g. from consumer surveys) generates data that can help identify market trends, customer preferences, and competitor strategies.

In this sense, it allows a company to make informed decisions, solve existing problems, and even predict and prevent future ones.

13. Root Cause Analysis

Root cause analysis is a method used to identify the origin or the fundamental reason for a problem.

Once the root cause is determined, you can implement corrective actions to prevent the problem from recurring.

As a problem-solving procedure, root cause analysis helps you to tackle the problem at its source, rather than dealing with its surface symptoms.

Go Deeper: Root Cause Analysis Examples

14. Mind Mapping

Mind mapping is a visual tool used to structure information, helping you better analyze, comprehend and generate new ideas.

By laying out your thoughts visually, it can lead you to solutions that might not have been apparent with linear thinking.

In problem-solving, mind mapping helps in organizing ideas and identifying connections between them, providing a holistic view of the situation and potential solutions.

15. Trial and Error

The trial and error method involves attempting various solutions until you find one that resolves the problem.

It’s an empirical technique that relies on practical actions instead of theories or rules.

In the context of problem-solving, trial and error allows you the flexibility to test different strategies in real situations, gaining insights about what works and what doesn’t.

16. SWOT Analysis

SWOT is an acronym standing for Strengths, Weaknesses, Opportunities, and Threats.

It’s an analytic framework used to evaluate these aspects in relation to a particular objective or problem.

In problem-solving, SWOT Analysis helps you to identify favorable and unfavorable internal and external factors. It helps to craft strategies that make best use of your strengths and opportunities, whilst addressing weaknesses and threats.

Go Deeper: SWOT Analysis Examples

17. Scenario Planning

Scenario planning is a strategic planning method used to make flexible long-term plans.

It involves imagining, and then planning for, multiple likely future scenarios.

By forecasting various directions a problem could take, scenario planning helps manage uncertainty and is an effective tool for problem-solving in volatile conditions.

18. Six Thinking Hats

The Six Thinking Hats is a concept devised by Edward de Bono that proposes six different directions or modes of thinking, symbolized by six different hat colors.

Each hat signifies a different perspective, encouraging you to switch ‘thinking modes’ as you switch hats. This method can help remove bias and broaden perspectives when dealing with a problem.

19. Decision Matrix Analysis

Decision Matrix Analysis is a technique that allows you to weigh different factors when faced with several possible solutions.

After listing down the options and determining the factors of importance, each option is scored based on each factor.

Revealing a clear winner that both serves your objectives and reflects your values, Decision Matrix Analysis grounds your problem-solving process in objectivity and comprehensiveness.

20. Pareto Analysis

Also known as the 80/20 rule, Pareto Analysis is a decision-making technique.

It’s based on the principle that 80% of problems are typically caused by 20% of the causes, making it a handy tool for identifying the most significant issues in a situation.

Using this analysis, you’re likely to direct your problem-solving efforts more effectively, tackling the root causes producing most of the problem’s impact.

21. Critical Thinking

Critical thinking refers to the ability to analyze facts to form a judgment objectively.

It involves logical, disciplined thinking that is clear, rational, open-minded, and informed by evidence.

For problem-solving, critical thinking helps evaluate options and decide the most effective solution. It ensures your decisions are grounded in reason and facts, and not biased or irrational assumptions.

Go Deeper: Critical Thinking Examples

22. Hypothesis Testing

Hypothesis testing usually involves formulating a claim, testing it against actual data, and deciding whether to accept or reject the claim based on the results.

In problem-solving, hypotheses often represent potential solutions. Hypothesis testing provides verification, giving a statistical basis for decision-making and problem resolution.

Usually, this will require research methods and a scientific approach to see whether the hypothesis stands up or not.

Go Deeper: Types of Hypothesis Testing

23. Cost-Benefit Analysis

A cost-benefit analysis (CBA) is a systematic process of weighing the pros and cons of different solutions in terms of their potential costs and benefits.

It allows you to measure the positive effects against the negatives and informs your problem-solving strategy.

By using CBA, you can identify which solution offers the greatest benefit for the least cost, significantly improving efficacy and efficiency in your problem-solving process.

Go Deeper: Cost-Benefit Analysis Examples

24. Simulation and Modeling

Simulations and models allow you to create a simplified replica of real-world systems to test outcomes under controlled conditions.

In problem-solving, you can broadly understand potential repercussions of different solutions before implementation.

It offers a cost-effective way to predict the impacts of your decisions, minimizing potential risks associated with various solutions.

25. Delphi Method

The Delphi Method is a structured communication technique used to gather expert opinions.

The method involves a group of experts who respond to questionnaires about a problem. The responses are aggregated and shared with the group, and the process repeats until a consensus is reached.

This method of problem solving can provide a diverse range of insights and solutions, shaped by the wisdom of a collective expert group.

26. Cross-functional Team Collaboration

Cross-functional team collaboration involves individuals from different departments or areas of expertise coming together to solve a common problem or achieve a shared goal.

When you bring diverse skills, knowledge, and perspectives to a problem, it can lead to a more comprehensive and innovative solution.

In problem-solving, this promotes communal thinking and ensures that solutions are inclusive and holistic, with various aspects of the problem being addressed.

27. Benchmarking

Benchmarking involves comparing one’s business processes and performance metrics to the best practices from other companies or industries.

In problem-solving, it allows you to identify gaps in your own processes, determine how others have solved similar problems, and apply those solutions that have proven to be successful.

It also allows you to compare yourself to the best (the benchmark) and assess where you’re not as good.

28. Pros-Cons Lists

A pro-con analysis aids in problem-solving by weighing the advantages (pros) and disadvantages (cons) of various possible solutions.

This simple but powerful tool helps in making a balanced, informed decision.

When confronted with a problem, a pro-con analysis can guide you through the decision-making process, ensuring all possible outcomes and implications are scrutinized before arriving at the optimal solution. Thus, it helps to make the problem-solving process both methodical and comprehensive.

29. 5 Whys Analysis

The 5 Whys Analysis involves repeatedly asking the question ‘why’ (around five times) to peel away the layers of an issue and discover the root cause of a problem.

As a problem-solving technique, it enables you to delve into details that you might otherwise overlook and offers a simple, yet powerful, approach to uncover the origin of a problem.

For example, if your task is to find out why a product isn’t selling your first answer might be: “because customers don’t want it”, then you ask why again – “they don’t want it because it doesn’t solve their problem”, then why again – “because the product is missing a certain feature” … and so on, until you get to the root “why”.

30. Gap Analysis

Gap analysis entails comparing current performance with potential or desired performance.

You’re identifying the ‘gaps’, or the differences, between where you are and where you want to be.

In terms of problem-solving, a Gap Analysis can help identify key areas for improvement and design a roadmap of how to get from the current state to the desired one.

31. Design Thinking

Design thinking is a problem-solving approach that involves empathy, experimentation, and iteration.

The process focuses on understanding user needs, challenging assumptions , and redefining problems from a user-centric perspective.

In problem-solving, design thinking uncovers innovative solutions that may not have been initially apparent and ensures the solution is tailored to the needs of those affected by the issue.

32. Analogical Thinking

Analogical thinking involves the transfer of information from a particular subject (the analogue or source) to another particular subject (the target).

In problem-solving, you’re drawing parallels between similar situations and applying the problem-solving techniques used in one situation to the other.

Thus, it allows you to apply proven strategies to new, but related problems.

33. Lateral Thinking

Lateral thinking requires looking at a situation or problem from a unique, sometimes abstract, often non-sequential viewpoint.

Unlike traditional logical thinking methods, lateral thinking encourages you to employ creative and out-of-the-box techniques.

In solving problems, this type of thinking boosts ingenuity and drives innovation, often leading to novel and effective solutions.

Go Deeper: Lateral Thinking Examples

34. Flowcharting

Flowcharting is the process of visually mapping a process or procedure.

This form of diagram can show every step of a system, process, or workflow, enabling an easy tracking of the progress.

As a problem-solving tool, flowcharts help identify bottlenecks or inefficiencies in a process, guiding improved strategies and providing clarity on task ownership and process outcomes.

35. Multivoting

Multivoting, or N/3 voting, is a method where participants reduce a large list of ideas to a prioritized shortlist by casting multiple votes.

This voting system elevates the most preferred options for further consideration and decision-making.

As a problem-solving technique, multivoting allows a group to narrow options and focus on the most promising solutions, ensuring more effective and democratic decision-making.

36. Force Field Analysis

Force Field Analysis is a decision-making technique that identifies the forces for and against change when contemplating a decision.

The ‘forces’ represent the differing factors that can drive or hinder change.

In problem-solving, Force Field Analysis allows you to understand the entirety of the context, favoring a balanced view over a one-sided perspective. A comprehensive view of all the forces at play can lead to better-informed problem-solving decisions.

TRIZ, which stands for “The Theory of Inventive Problem Solving,” is a problem-solving, analysis, and forecasting methodology.

It focuses on finding contradictions inherent in a scenario. Then, you work toward eliminating the contraditions through finding innovative solutions.

So, when you’re tackling a problem, TRIZ provides a disciplined, systematic approach that aims for ideal solutions and not just acceptable ones. Using TRIZ, you can leverage patterns of problem-solving that have proven effective in different cases, pivoting them to solve the problem at hand.

38. A3 Problem Solving

A3 Problem Solving, derived from Lean Management, is a structured method that uses a single sheet of A3-sized paper to document knowledge from a problem-solving process.

Named after the international paper size standard of A3 (or 11-inch by 17-inch paper), it succinctly records all key details of the problem-solving process from problem description to the root cause and corrective actions.

Used in problem-solving, this provides a straightforward and logical structure for addressing the problem, facilitating communication between team members, ensuring all critical details are included, and providing a record of decisions made.

39. Scenario Analysis

Scenario Analysis is all about predicting different possible future events depending upon your decision.

To do this, you look at each course of action and try to identify the most likely outcomes or scenarios down the track if you take that course of action.

This technique helps forecast the impacts of various strategies, playing each out to their (logical or potential) end. It’s a good strategy for project managers who need to keep a firm eye on the horizon at all times.

When solving problems, Scenario Analysis assists in preparing for uncertainties, making sure your solution remains viable, regardless of changes in circumstances.

How to Answer “Demonstrate Problem-Solving Skills” in an Interview

When asked to demonstrate your problem-solving skills in an interview, the STAR method often proves useful. STAR stands for Situation, Task, Action, and Result.

Situation: Begin by describing a specific circumstance or challenge you encountered. Make sure to provide enough detail to allow the interviewer a clear understanding. You should select an event that adequately showcases your problem-solving abilities.

For instance, “In my previous role as a project manager, we faced a significant issue when our key supplier abruptly went out of business.”

Task: Explain what your responsibilities were in that situation. This serves to provide context, allowing the interviewer to understand your role and the expectations placed upon you.

For instance, “It was my task to ensure the project remained on track despite this setback. Alternative suppliers needed to be found without sacrificing quality or significantly increasing costs.”

Action: Describe the steps you took to manage the problem. Highlight your problem-solving process. Mention any creative approaches or techniques that you used.

For instance, “I conducted thorough research to identify potential new suppliers. After creating a shortlist, I initiated contact, negotiated terms, assessed samples for quality and made a selection. I also worked closely with the team to re-adjust the project timeline.”

Result: Share the outcomes of your actions. How did the situation end? Did your actions lead to success? It’s particularly effective if you can quantify these results.

For instance, “As a result of my active problem solving, we were able to secure a new supplier whose costs were actually 10% cheaper and whose quality was comparable. We adjusted the project plan and managed to complete the project just two weeks later than originally planned, despite the major vendor setback.”

Remember, when you’re explaining your problem-solving skills to an interviewer, what they’re really interested in is your approach to handling difficulties, your creativity and persistence in seeking a resolution, and your ability to carry your solution through to fruition. Tailoring your story to highlight these aspects will help exemplify your problem-solving prowess.

Go Deeper: STAR Interview Method Examples

Benefits of Problem-Solving

Problem-solving is beneficial for the following reasons (among others):

  • It can help you to overcome challenges, roadblocks, and bottlenecks in your life.
  • It can save a company money.
  • It can help you to achieve clarity in your thinking.
  • It can make procedures more efficient and save time.
  • It can strengthen your decision-making capacities.
  • It can lead to better risk management.

Whether for a job interview or school, problem-solving helps you to become a better thinking, solve your problems more effectively, and achieve your goals. Build up your problem-solving frameworks (I presented over 40 in this piece for you!) and work on applying them in real-life situations.

Chris

  • Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 101 Hidden Talents Examples
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  • Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 15 Signs you're Burnt Out, Not Lazy
  • Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 15 Toxic Things Parents Say to their Children

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Status.net

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

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

What Is Problem Solving?

Definition and importance.

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

Problem-Solving Steps

The problem-solving process typically includes the following steps:

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

Defining the Problem

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

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

Generating Solutions

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

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

Evaluating and Selecting Solutions

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

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

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

Implementing and Monitoring the Solution

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

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

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

Problem-Solving Techniques

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

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

Brainstorming

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

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

When brainstorming, remember to:

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

Root Cause Analysis

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

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

SWOT Analysis

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

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

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

Mind Mapping

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

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

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

Examples of Problem Solving in Various Contexts

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

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

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

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

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

  • Overcoming a personal obstacle, such as improving your fitness level, by establishing achievable goals, measuring progress, and adjusting your approach accordingly
  • Navigating a new environment or city by researching your surroundings, asking for directions, or using technology like GPS to guide you
  • Dealing with a sudden change, like a change in your work schedule, by assessing the situation, identifying potential impacts, and adapting your plans to accommodate the change.
  • How to Resolve Employee Conflict at Work [Steps, Tips, Examples]
  • How to Write Inspiring Core Values? 5 Steps with Examples
  • 30 Employee Feedback Examples (Positive & Negative)

The Future World of Work

5 Examples of Problem-Solving in The Workplace

Christina J Colclough

By Christina Colclough

Last updated: January 12, 2024

When you’re in a job interview, you can almost bet on being asked about your problem-solving experiences. This skill is always high on employers’ wish lists. Walk in with a few solid examples up your sleeve and talk about them with confidence – that’s what grabs their attention.

Problem-Solving discussion

In this post, I’ll guide you through picking the right problem-solving in workplace examples and articulating them in a way that will make you stand out.

In this article:

What is problem solving.

At its core, this skill is all about spotting issues and then working out the smartest ways to sort them out. In the workplace, this skill keeps things running smoothly because challenges always pop up.

In any job, you’re bound to bump into a range of problems. It could be meeting a tight deadline, handling customer complaints, or resolving misunderstandings among team members. Each of these difficult situations needs a cool head and a clear strategy.

Dealing with these issues well is crucial because it keeps the wheels turning. Effective problem-solving means fewer hiccups in projects, better teamwork, and happier customers. It’s like oiling the cogs of a machine.

That is why interviewers like myself often drill down into the candidates’ problem-solving abilities with questions like “ Tell me about a time you solved a problem ” or “ Can you describe a situation where you had to overcome a significant challenge? “

We want to know if you’re the kind of person who faces challenges head-on or if you tend to sweep them under the rug. We’re looking for someone who not only spots issues but also comes up with smart solutions and puts them into action. It’s all about ensuring that, when the going gets tough, you’ve got the skills to keep things on track.

How to Answer Problem-Solving Interview Questions

Close up interviewer

When you’re in an interview and asked about problem-solving, it’s a golden opportunity to show your skills. In my experience, a great approach is to use the STAR technique. This strategy helps structure your answer in a clear and compelling way.

Let’s break down what each part of STAR stands for:

  • Situation : Describe the context within which you had to solve a problem.
  • Task : Explain the actual problem or challenge you were facing.
  • Action : Describe the actions you took to address the problem.
  • Result : Share the outcomes of your actions.

In this step, your goal is to give the interviewer a snapshot of your scenario.

Let’s say you had to deal with a significant drop in team morale and productivity. At the beginning of your response, you want to set the context for your story. This should include where you were working, your role, and the initial problem.

The key here is to be concise but provide enough detail to paint a clear picture like this:

“In my previous role as a team leader, I noticed a sudden drop in team morale and productivity. This was unusual for our normally energetic and efficient team.”

Common Situations

Here are some other common situations you can mention in your answer:

  • Resolving an issue with a difficult client when they complain about a product or service
  • Figuring out a solution when equipment or technology breaks down or fails
  • Dealing with a mistake you’ve made on an important project
  • Handling a tight deadline when unexpected challenges threaten completion
  • Settling a dispute between colleagues who aren’t getting along
  • Improving productivity for a team that is underperforming
  • Persuading colleagues to get on board with an idea they are resistant to

How to Answer With Limited Experience

answering questions during an interview

Don’t worry if you just graduated or have little work experience. Think about examples from school group projects, internships, or part-time jobs like these:

  • Coordinating schedules for a group presentation when everyone has different availabilities
  • Resolving a disagreement over roles for a big class project
  • Finding ways to improve your team’s process when a professor gives feedback
  • Managing deadlines and deliverables with classmates who had competing priorities
  • Convincing peers to adopt your proposed solution for an assignment
  • Addressing complaints from a classmate about unequal workloads

Clarify the problem you had to tackle. What was expected of you? What complex challenge did you need to address? Here, you’re setting up the specific problem that you were tasked with solving.

Remember, the focus is on the problem, not yet on your actions. Using the above example, here is what you can talk about:

“My task was to identify the causes of this decline and implement a strategy to boost morale and productivity. I needed to make sure our team could return to its usual high-performance level.”

Describe the steps you took to solve the problem. Think about how you analyzed the situation, decided on a course of action, and implemented it. It should show your critical thinking and analytical skills.

“To tackle this, I first conducted one-on-one meetings with team members to understand their concerns and gather feedback. Based on these insights, I realized that a recent change in company policy was causing stress.

I advocated for my team’s concerns with upper management and worked with them to modify the policy. At the same time, I initiated team-building activities and regular check-ins to foster a more supportive and open team environment.”

Finally, talk about the outcomes of your actions. Employers want to know your problem-solving drives real improvements. Also, highlight any positive feedback from your boss or team members, and if possible, quantify the success.

“As a result of these actions, we saw a significant improvement in team morale within a month. Productivity levels bounced back, and the team’s overall satisfaction with their work environment increased.

This experience not only taught me valuable lessons about team dynamics but also reinforced the importance of proactive communication and advocacy for team needs.”

Here are some other outcomes to highlight in your answer:

  • Resolving an issue with a difficult client : Client satisfaction restored, future business secured
  • Fixing broken equipment : Equipment operational again, no more disruptions to operations
  • Dealing with a mistake : Error corrected, a new process implemented to prevent recurrence
  • Handling a deadline : Project completed on time, client received deliverable as promised
  • Settling a dispute : Conflict resolved, team collaboration and morale improved
  • Boosting team productivity : Increased output, goals reached, performance metrics improved
  • Persuading colleagues : Proposal approved, a new initiative launched successfully

5 Examples Of Problem-Solving Skills

Problem-Solving Skills

1. Improving Collaboration in a Stalled Project

Here is a sample you can use when explaining how you improved team collaboration on a project:

“Our team was tasked with developing a new financial management web application. However, we hit a snag and missed two crucial milestones. The core issue was a breakdown in communication – team members were not proactively sharing updates on delays or challenges they encountered.

To address this, I instituted daily 15-minute standup meetings. These sessions provided a platform for everyone to voice concerns and update the team on their progress. We also started tracking tasks in a shared spreadsheet so everyone had more visibility into the project.

Within two weeks, collaboration and communication improved significantly. We renegotiated the timeline with stakeholders, and the project team delivered the web app only 1 week after the original deadline.

The processes we put in place didn’t just help us with this project but also significantly boosted our efficiency on later projects.”

2. Revitalizing a Marketing Campaign

This is how you can describe a time you turned around a marketing campaign:

“In my last marketing role, I was responsible for a campaign promoting a new line of eco-friendly skincare products. Midway through, we found that our engagement metrics were dismal, particularly with our targeted demographic of people aged 20-30.

Upon reviewing our approach, I realized our messaging was too generic and failed to connect with this specific group’s interests and values. I spearheaded a strategy shift, focusing on the environmental benefits and ethical sourcing, aspects we found resonated more with a slightly older demographic, females aged 25-35, who were more invested in sustainable living.

We also pivoted our advertising to platforms popular with this demographic, like eco-conscious lifestyle blogs and organic beauty forums. This shift led to a 40% increase in engagement and contributed greatly to the success of our product launch, exceeding our initial sales targets.”

3. Streamlining Operational Processes

Here’s an example to illustrate how you tackled inefficiencies in operational processes:

“As an operations manager at a mid-sized electronics manufacturer, I noticed our product delivery was consistently delayed.

I identified the root cause as a bottleneck in our supply chain. In particular, a stage where manual data entry from manufacturing to logistics was causing significant hold-ups.

Realizing the need for efficiency, I proposed automating this stage. We collaborated with the IT department and implemented a barcode scanning system that integrated manufacturing output with our logistics database.

This change cut down the processing time by 30%, drastically improving our on-time delivery rate. It not only led to an upswing in customer satisfaction but also streamlined our inventory management, reducing both operational delays and costs.”

4. Resolving Communication Barriers Between Teams

This example demonstrates a solution for inter-departmental communication issues:

“In my previous role, I observed recurring conflicts between the sales and product development teams. These were mainly due to misunderstandings and a lack of clear communication about product updates. This led to promises being made to customers that the product team couldn’t fulfill.

To bridge this gap, I proposed and facilitated a series of joint workshops between the two teams. These sessions focused on aligning the teams’ understanding of product capabilities and timelines. Additionally, I initiated a bi-weekly newsletter and a shared digital workspace where both teams could update each other on developments and feedback.

The result was a significant improvement in inter-team collaboration. The sales team was better informed about product limitations and timelines, leading to more realistic commitments to customers.

Meanwhile, the product team received valuable market feedback directly from the sales team. It helped them tailor developments to customer needs. This collaborative approach not only reduced conflicts but also led to better product-market alignment.”

5. Resolving Customer Complaints and Enhancing Service Quality

customer service

This highlights an approach to customer service challenges:

“In my role as a customer service manager, I was faced with increasing customer complaints regarding delayed response times. This issue was affecting customer satisfaction and had the potential to harm our company’s reputation.

I started by analyzing our customer service processes and discovered that our response system was outdated and inefficient. To rectify this, I led the implementation of a new customer relationship management (CRM) system that streamlined our customer service workflow.

This system included automated responses for common queries and a more efficient ticketing process for complex issues. I also organized a series of training sessions for the customer service team to ensure they were well-versed in using the new system and could provide more effective solutions to customers.

Implementing these changes led to a huge reduction in response time and a significant drop in customer complaints. Our team also received positive feedback for improved service quality, which was reflected in our customer satisfaction surveys.”

Tips on Improving Problem-Solving Skills

Problem-solving is a career-long skill, not just needed for some interviews. Whether you’re a newbie or a seasoned pro, honing these skills can make a big difference in how you handle challenges at work.

Understand Before Assuming

Jumping to conclusions can be a trap. When a problem arises, take a step back and get a clear picture of what’s actually going on. This means holding off on assumptions until you’ve gathered all the facts.

Sometimes, the real issue isn’t what it seems at first glance. Doing a bit of digging to understand the root cause can lead you to a more effective solution.

Research and Learn from the Past

History often repeats itself, and this is true for workplace problems, too. When faced with a challenge, look into whether similar issues have popped up before.

How were they handled? What worked and what didn’t? Learning from past experiences, whether your own or someone else’s, can be a goldmine of insights.

Brainstorm With Creative Thinking

When thinking about potential solutions, avoid locking yourself into the first idea that comes to mind. Brainstorming can open up a world of possibilities and creative solutions. Don’t be afraid to think outside the box. Sometimes, the most unconventional ideas turn out to be the best solutions.

Always Have a Plan B

Even the best-laid plans can go awry. That’s why having a contingency plan is a must.

Think about what could go wrong and how to contain any further issues. This doesn’t mean you’re expecting the worst, but rather, you’re prepared to handle it efficiently if it does happen.

Team Decisions and Communication

Solving problems isn’t a solo mission. Make decisions as a team and keep everyone in the loop.

Clear communication is a valuable soft skill that helps everyone understand the plan and their role in it. Plus, this is how you can bring new perspectives and ideas to the table and make your solution even stronger.

Timeframe and Flexibility

Set a timeframe for your action plan, but be flexible. If something isn’t working, be ready to pivot and try a different approach. Sticking rigidly to a plan that’s not delivering results won’t do anyone any favors.

See more interview tips: How To Write A Follow-Up Email After Interview 3 Examples For Thank-You Email After Interview 8 Examples of Challenges You Have Overcome At Work 6 sample answers of accomplishments at work 5 Examples of Problem-Solving in The Workplace How To Ask for Feedback After Job Rejection How to Explain The Reason for Leaving a Job on Applications For Interview Question: What Do You Like To Do For Fun? What Are You Most Passionate About? What Are You Looking For In Your Next Job? Why Are You Interested In This Position? What Accomplishments Are You Most Proud Of?

Frequently Asked Questions

Are problem-solving skills that important.

Absolutely. No matter where you work, there’s always a curveball now and then. Having the knack to quickly think on your feet, break down a problem, and come up with a solution is a game-changer.

How Do I Sell Myself as a Problem Solver?

Storytelling is your best bet here. The trick is to paint a picture where you’re the person who spots the problem and then creatively solves it, not just someone who follows instructions.

How Do I Choose Good Examples for a Job Interview?

Pick examples that show you’re not just a one-trick pony. What I find impressive is when someone can demonstrate their thought process – how they analyzed the issue, got creative with solutions, and then put their plan into action.

What Are the Key Attributes of a Good Problem Solver?

They’re the kind of people who don’t rush to conclusions. Instead, they take their time to understand the problem, explore different angles, and weigh their options.

Adaptability is also key – they can roll with the punches and adjust their plans as needed. And, of course, they’re great at getting their point across, ensuring everyone’s on the same page.

What Are the Major Obstacles to Problem Solving?

From what I’ve seen, the big hurdles are often not having enough info, sticking too rigidly to old mindsets, and letting biases lead the way. It’s easy to get tunnel vision, especially if you’re used to doing things a certain way.

Also, not bringing different perspectives to the table can really limit your options.

As you step into the next interview, remember two key things: confidence and clarity. Trust in your abilities and the experiences you bring to the table. Learn how the above problem-solving examples can paint a vivid picture of your challenge and how you tackled it. Most importantly, let those stories reflect your skills and how you can be an asset to any team.

Christina J. Colclough

Dr Christina J. Colclough is an expert on The Future World of Work and the politics of digital technology advocating globally for the importance of the workers’ voice. She has extensive regional and global labour movement experience, is a sought-after keynote speaker, coach, and strategist advising progressive governments and worker organisations.

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10 Problem-solving strategies to turn challenges on their head

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What is an example of problem-solving?

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

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

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

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

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

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

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

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

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

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

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

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

team-meeting-problem-solving-strategies

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

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

1. Identify the problem

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

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

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

2. Break the problem down 

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

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

3. Generate potential solutions

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

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

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

4. Evaluate the possible solutions

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

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

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

woman-helping-her-colleague-problem-solving-strategies

5. Implement and monitor the solutions

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

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

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

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

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

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

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

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

Let’s break each of these down.

1. Use a solution that worked before

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

2. Brainstorming

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

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

3. Work backward

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

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

4. Use the Kipling method

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

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

Answering these questions can help you identify possible solutions.

5. Draw the problem

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

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

woman-drawing-mind-map-problem-solving-strategies

6. Use trial-and-error

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

7. Sleep on it

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

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

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

8. Get advice from your peers

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

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

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

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

9. Use the Pareto principle

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

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

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

10. Add successful solutions to your toolkit

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

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

three-colleagues-looking-at-computer-problem-solving-strategies

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

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

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

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

1. Build your problem-solving skills

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

2. Practice

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

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

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

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

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

two-colleagues-talking-at-corporate-event-problem-solving-strategies

4. Ask for feedback

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

5. Learn new approaches and methodologies

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

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

6. Experiment

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

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

7. Analyze the success of your competitors

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

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

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

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

Use problem-solving strategies to uplevel your business

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

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

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

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

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Elizabeth Perry, ACC

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

8 creative solutions to your most challenging problems

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

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40 problem-solving techniques and processes

Problem solving workshop

All teams and organizations encounter challenges. Approaching those challenges without a structured problem solving process can end up making things worse.

Proven problem solving techniques such as those outlined below can guide your group through a process of identifying problems and challenges , ideating on possible solutions , and then evaluating and implementing the most suitable .

In this post, you'll find problem-solving tools you can use to develop effective solutions. You'll also find some tips for facilitating the problem solving process and solving complex problems.

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What is problem solving?

Problem solving is a process of finding and implementing a solution to a challenge or obstacle. In most contexts, this means going through a problem solving process that begins with identifying the issue, exploring its root causes, ideating and refining possible solutions before implementing and measuring the impact of that solution.

For simple or small problems, it can be tempting to skip straight to implementing what you believe is the right solution. The danger with this approach is that without exploring the true causes of the issue, it might just occur again or your chosen solution may cause other issues.

Particularly in the world of work, good problem solving means using data to back up each step of the process, bringing in new perspectives and effectively measuring the impact of your solution.

Effective problem solving can help ensure that your team or organization is well positioned to overcome challenges, be resilient to change and create innovation. In my experience, problem solving is a combination of skillset, mindset and process, and it’s especially vital for leaders to cultivate this skill.

A group of people looking at a poster with notes on it

What is the seven step problem solving process?

A problem solving process is a step-by-step framework from going from discovering a problem all the way through to implementing a solution.

With practice, this framework can become intuitive, and innovative companies tend to have a consistent and ongoing ability to discover and tackle challenges when they come up.

You might see everything from a four step problem solving process through to seven steps. While all these processes cover roughly the same ground, I’ve found a seven step problem solving process is helpful for making all key steps legible.

We’ll outline that process here and then follow with techniques you can use to explore and work on that step of the problem solving process with a group.

The seven-step problem solving process is:

1. Problem identification 

The first stage of any problem solving process is to identify the problem(s) you need to solve. This often looks like using group discussions and activities to help a group surface and effectively articulate the challenges they’re facing and wish to resolve.

Be sure to align with your team on the exact definition and nature of the problem you’re solving. An effective process is one where everyone is pulling in the same direction – ensure clarity and alignment now to help avoid misunderstandings later.

2. Problem analysis and refinement

The process of problem analysis means ensuring that the problem you are seeking to solve is  the   right problem . Choosing the right problem to solve means you are on the right path to creating the right solution.

At this stage, you may look deeper at the problem you identified to try and discover the root cause at the level of people or process. You may also spend some time sourcing data, consulting relevant parties and creating and refining a problem statement.

Problem refinement means adjusting scope or focus of the problem you will be aiming to solve based on what comes up during your analysis. As you analyze data sources, you might discover that the root cause means you need to adjust your problem statement. Alternatively, you might find that your original problem statement is too big to be meaningful approached within your current project.

Remember that the goal of any problem refinement is to help set the stage for effective solution development and deployment. Set the right focus and get buy-in from your team here and you’ll be well positioned to move forward with confidence.

3. Solution generation

Once your group has nailed down the particulars of the problem you wish to solve, you want to encourage a free flow of ideas connecting to solving that problem. This can take the form of problem solving games that encourage creative thinking or techniquess designed to produce working prototypes of possible solutions. 

The key to ensuring the success of this stage of the problem solving process is to encourage quick, creative thinking and create an open space where all ideas are considered. The best solutions can often come from unlikely places and by using problem solving techniques that celebrate invention, you might come up with solution gold. 

3 examples of problem solving

4. Solution development

No solution is perfect right out of the gate. It’s important to discuss and develop the solutions your group has come up with over the course of following the previous problem solving steps in order to arrive at the best possible solution. Problem solving games used in this stage involve lots of critical thinking, measuring potential effort and impact, and looking at possible solutions analytically. 

During this stage, you will often ask your team to iterate and improve upon your front-running solutions and develop them further. Remember that problem solving strategies always benefit from a multitude of voices and opinions, and not to let ego get involved when it comes to choosing which solutions to develop and take further.

Finding the best solution is the goal of all problem solving workshops and here is the place to ensure that your solution is well thought out, sufficiently robust and fit for purpose. 

5. Decision making and planning

Nearly there! Once you’ve got a set of possible, you’ll need to make a decision on which to implement. This can be a consensus-based group decision or it might be for a leader or major stakeholder to decide. You’ll find a set of effective decision making methods below.

Once your group has reached consensus and selected a solution, there are some additional actions that also need to be decided upon. You’ll want to work on allocating ownership of the project, figure out who will do what, how the success of the solution will be measured and decide the next course of action.

Set clear accountabilities, actions, timeframes, and follow-ups for your chosen solution. Make these decisions and set clear next-steps in the problem solving workshop so that everyone is aligned and you can move forward effectively as a group. 

Ensuring that you plan for the roll-out of a solution is one of the most important problem solving steps. Without adequate planning or oversight, it can prove impossible to measure success or iterate further if the problem was not solved. 

6. Solution implementation 

This is what we were waiting for! All problem solving processes have the end goal of implementing an effective and impactful solution that your group has confidence in.

Project management and communication skills are key here – your solution may need to adjust when out in the wild or you might discover new challenges along the way. For some solutions, you might also implement a test with a small group and monitor results before rolling it out to an entire company.

You should have a clear owner for your solution who will oversee the plans you made together and help ensure they’re put into place. This person will often coordinate the implementation team and set-up processes to measure the efficacy of your solution too.

7. Solution evaluation 

So you and your team developed a great solution to a problem and have a gut feeling it’s been solved. Work done, right? Wrong. All problem solving strategies benefit from evaluation, consideration, and feedback.

You might find that the solution does not work for everyone, might create new problems, or is potentially so successful that you will want to roll it out to larger teams or as part of other initiatives. 

None of that is possible without taking the time to evaluate the success of the solution you developed in your problem solving model and adjust if necessary.

Remember that the problem solving process is often iterative and it can be common to not solve complex issues on the first try. Even when this is the case, you and your team will have generated learning that will be important for future problem solving workshops or in other parts of the organization. 

It’s also worth underlining how important record keeping is throughout the problem solving process. If a solution didn’t work, you need to have the data and records to see why that was the case. If you go back to the drawing board, notes from the previous workshop can help save time.

What does an effective problem solving process look like?

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

The format of a workshop ensures that you can get buy-in from your group, encourage free-thinking and solution exploration before making a decision on what to implement following the session.

This Design Sprint 2.0 template is an effective problem solving process from top agency AJ&Smart. It’s a great format for the entire problem solving process, with four-days of workshops designed to surface issues, explore solutions and even test a solution.

Check it for an example of how you might structure and run a problem solving process and feel free to copy and adjust it your needs!

For a shorter process you can run in a single afternoon, this remote problem solving agenda will guide you effectively in just a couple of hours.

Whatever the length of your workshop, by using 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!

3 examples of problem solving

Complete problem-solving methods

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

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.

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

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   It doesn’t matter where you work and what your job role is, if you work with other people together as a team, you will always encounter the same challenges: Unclear goals and miscommunication that cause busy work and overtime Unstructured meetings that leave attendants tired, confused and without clear outcomes. Frustration builds up because internal challenges to productivity are not addressed Sudden changes in priorities lead to a loss of focus and momentum Muddled compromise takes the place of clear decision- making, leaving everybody to come up with their own interpretation. In short, a lack of structure leads to a waste of time and effort, projects that drag on for too long and frustrated, burnt out teams. AJ&Smart has worked with some of the most innovative, productive companies in the world. What sets their teams apart from others is not better tools, bigger talent or more beautiful offices. The secret sauce to becoming a more productive, more creative and happier team is simple: Replace all open discussion or brainstorming with a structured process that leads to more ideas, clearer decisions and better outcomes. When a good process provides guardrails and a clear path to follow, it becomes easier to come up with ideas, make decisions and solve problems. This is why AJ&Smart created Lightning Decision Jam (LDJ). It’s a simple and short, but powerful group exercise that can be run either in-person, in the same room, or remotely with distributed teams.

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.

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.

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.

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.
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.

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!

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.

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.

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.

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.

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.

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.

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.

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.

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!

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 brainstorming solutions

Now you have the context and background of the problem you are trying to solving, now comes the time to start ideating and thinking about how you’ll solve the issue.

Here, you’ll want to encourage creative, free thinking and speed. Get as many ideas out as possible and explore different perspectives so you have the raw material for the next step.

Looking at a problem from a new angle can be one of the most effective ways of creating an effective solution. TRIZ is a problem-solving tool that asks the group to consider what they must not do in order to solve a challenge.

By reversing the discussion, new topics and taboo subjects often emerge, allowing the group to think more deeply and create ideas that confront the status quo in a safe and meaningful way. If you’re working on a problem that you’ve tried to solve before, TRIZ is a great problem-solving method to help your team get unblocked.

Making Space with TRIZ   #issue analysis   #liberating structures   #issue resolution   You can clear space for innovation by helping a group let go of what it knows (but rarely admits) limits its success and by inviting creative destruction. TRIZ makes it possible to challenge sacred cows safely and encourages heretical thinking. The question “What must we stop doing to make progress on our deepest purpose?” induces seriously fun yet very courageous conversations. Since laughter often erupts, issues that are otherwise taboo get a chance to be aired and confronted. With creative destruction come opportunities for renewal as local action and innovation rush in to fill the vacuum. Whoosh!

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.

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.

Idea and Concept Development

Brainstorming without structure can quickly become chaotic or frustrating. In a problem-solving context, having an ideation framework to follow can help ensure your team is both creative and disciplined.

In this method, you’ll find an idea generation process that encourages your group to brainstorm effectively before developing their ideas and begin clustering them together. By using concepts such as Yes and…, more is more and postponing judgement, you can create the ideal conditions for brainstorming with ease.

Idea & Concept Development   #hyperisland   #innovation   #idea generation   Ideation and Concept Development is a process for groups to work creatively and collaboratively to generate creative ideas. It’s a general approach that can be adapted and customized to suit many different scenarios. It includes basic principles for idea generation and several steps for groups to work with. It also includes steps for idea selection and development.

Problem-solving techniques for developing and refining 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 develop and refine your ideas in order to bring them closer to a solution that actually solves the problem.

Use these problem-solving techniques when you want to help your team think through their ideas and refine them as part of your problem solving process.

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.

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

Ensuring that everyone in a group is able to contribute to a discussion is vital during any problem solving process. Not only does this ensure all bases are covered, but its then easier to get buy-in and accountability when people have been able to contribute to the process.

1-2-4-All is a tried and tested facilitation technique where participants are asked to first brainstorm on a topic on their own. Next, they discuss and share ideas in a pair before moving into a small group. Those groups are then asked to present the best idea from their discussion to the rest of the team.

This method can be used in many different contexts effectively, though I find it particularly shines in the idea development stage of the process. Giving each participant time to concretize their ideas and develop them in progressively larger groups can create a great space for both innovation and psychological safety.

1-2-4-All   #idea generation   #liberating structures   #issue analysis   With this facilitation technique you can immediately include everyone regardless of how large the group is. You can generate better ideas and more of them faster than ever before. You can tap the know-how and imagination that is distributed widely in places not known in advance. Open, generative conversation unfolds. Ideas and solutions are sifted in rapid fashion. Most importantly, participants own the ideas, so follow-up and implementation is simplified. No buy-in strategies needed! Simple and elegant!

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.

Problem-solving techniques for making decisions and planning

After your group is happy with the possible solutions you’ve developed, now comes the time to choose which to implement. There’s more than one way to make a decision and the best option is often dependant on the needs and set-up of your group.

Sometimes, it’s the case that you’ll want to vote as a group on what is likely to be the most impactful solution. Other times, it might be down to a decision maker or major stakeholder to make the final decision. Whatever your process, here’s some techniques you can use to help you make a decision during your problem solving process.

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.

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.

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.

Straddling the gap between decision making and planning, MoSCoW is a simple and effective method that allows a group team to easily prioritize a set of possible options.

Use this method in a problem solving process by collecting and summarizing all your possible solutions and then categorize them into 4 sections: “Must have”, “Should have”, “Could have”, or “Would like but won‘t get”.

This method is particularly useful when its less about choosing one possible solution and more about prioritorizing which to do first and which may not fit in the scope of your project. In my experience, complex challenges often require multiple small fixes, and this method can be a great way to move from a pile of things you’d all like to do to a structured plan.

MoSCoW   #define intentions   #create   #design   #action   #remote-friendly   MoSCoW is a method that allows the team to prioritize the different features that they will work on. Features are then categorized into “Must have”, “Should have”, “Could have”, or “Would like but won‘t get”. To be used at the beginning of a timeslot (for example during Sprint planning) and when planning is needed.

When it comes to managing the rollout of a solution, clarity and accountability are key factors in ensuring the success of the project. The RAACI chart is a simple but effective model for setting roles and responsibilities as part of a planning session.

Start by listing each person involved in the project and put them into the following groups in order to make it clear who is responsible for what during the rollout of your solution.

  • Responsibility  (Which person and/or team will be taking action?)
  • Authority  (At what “point” must the responsible person check in before going further?)
  • Accountability  (Who must the responsible person check in with?)
  • Consultation  (Who must be consulted by the responsible person before decisions are made?)
  • Information  (Who must be informed of decisions, once made?)

Ensure this information is easily accessible and use it to inform who does what and who is looped into discussions and kept up to date.

RAACI   #roles and responsibility   #teamwork   #project management   Clarifying roles and responsibilities, levels of autonomy/latitude in decision making, and levels of engagement among diverse stakeholders.

Problem-solving warm-up activities

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

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.

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.

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.

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.

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.

Closing activities for a problem-solving process

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

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.

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.

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.

Tips for 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.

Create psychologically safe spaces for discussion

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 tough for people to stand up and contribute if the problems or challenges are emotive or personal in nature. Try and create a psychologically safe space for these kinds of discussions and where possible, create regular opportunities for challenges to be brought up organically.

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!

Save time and effort creating an effective problem solving process

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!

3 examples of problem solving

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 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! 

3 examples of problem solving

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

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thank you very much for these excellent techniques

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Certainly wonderful article, very detailed. Shared!

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Your list of techniques for problem solving can be helpfully extended by adding TRIZ to the list of techniques. TRIZ has 40 problem solving techniques derived from methods inventros and patent holders used to get new patents. About 10-12 are general approaches. many organization sponsor classes in TRIZ that are used to solve business problems or general organiztational problems. You can take a look at TRIZ and dwonload a free internet booklet to see if you feel it shound be included per your selection process.

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3 examples of problem solving

Effective online tools are a necessity for smooth and engaging virtual workshops and meetings. But how do you choose the right ones? Do you sometimes feel that the good old pen and paper or MS Office toolkit and email leaves you struggling to stay on top of managing and delivering your workshop? Fortunately, there are plenty of great workshop tools to make your life easier when you need to facilitate a meeting and lead workshops. In this post, we’ll share our favorite online tools you can use to make your life easier and run better workshops and meetings. In fact, there are plenty of free online workshop tools and meeting…

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What Are Problem-Solving Skills? Definition and Examples

Zoe Kaplan

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Forage puts students first. Our blog articles are written independently by our editorial team. They have not been paid for or sponsored by our partners. See our full  editorial guidelines .

Why do employers hire employees? To help them solve problems. Whether you’re a financial analyst deciding where to invest your firm’s money, or a marketer trying to figure out which channel to direct your efforts, companies hire people to help them find solutions. Problem-solving is an essential and marketable soft skill in the workplace. 

So, how can you improve your problem-solving and show employers you have this valuable skill? In this guide, we’ll cover:

Problem-Solving Skills Definition

Why are problem-solving skills important, problem-solving skills examples, how to include problem-solving skills in a job application, how to improve problem-solving skills, problem-solving: the bottom line.

Problem-solving skills are the ability to identify problems, brainstorm and analyze answers, and implement the best solutions. An employee with good problem-solving skills is both a self-starter and a collaborative teammate; they are proactive in understanding the root of a problem and work with others to consider a wide range of solutions before deciding how to move forward. 

Examples of using problem-solving skills in the workplace include:

  • Researching patterns to understand why revenue decreased last quarter
  • Experimenting with a new marketing channel to increase website sign-ups
  • Brainstorming content types to share with potential customers
  • Testing calls to action to see which ones drive the most product sales
  • Implementing a new workflow to automate a team process and increase productivity

Problem-solving skills are the most sought-after soft skill of 2022. In fact, 86% of employers look for problem-solving skills on student resumes, according to the National Association of Colleges and Employers Job Outlook 2022 survey . 

It’s unsurprising why employers are looking for this skill: companies will always need people to help them find solutions to their problems. Someone proactive and successful at problem-solving is valuable to any team.

“Employers are looking for employees who can make decisions independently, especially with the prevalence of remote/hybrid work and the need to communicate asynchronously,” Eric Mochnacz, senior HR consultant at Red Clover, says. “Employers want to see individuals who can make well-informed decisions that mitigate risk, and they can do so without suffering from analysis paralysis.”

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Problem-solving includes three main parts: identifying the problem, analyzing possible solutions, and deciding on the best course of action.

>>MORE: Discover the right career for you based on your skills with a career aptitude test .

Research is the first step of problem-solving because it helps you understand the context of a problem. Researching a problem enables you to learn why the problem is happening. For example, is revenue down because of a new sales tactic? Or because of seasonality? Is there a problem with who the sales team is reaching out to? 

Research broadens your scope to all possible reasons why the problem could be happening. Then once you figure it out, it helps you narrow your scope to start solving it. 

Analysis is the next step of problem-solving. Now that you’ve identified the problem, analytical skills help you look at what potential solutions there might be.

“The goal of analysis isn’t to solve a problem, actually — it’s to better understand it because that’s where the real solution will be found,” Gretchen Skalka, owner of Career Insights Consulting, says. “Looking at a problem through the lens of impartiality is the only way to get a true understanding of it from all angles.”

Decision-Making

Once you’ve figured out where the problem is coming from and what solutions are, it’s time to decide on the best way to go forth. Decision-making skills help you determine what resources are available, what a feasible action plan entails, and what solution is likely to lead to success.

On a Resume

Employers looking for problem-solving skills might include the word “problem-solving” or other synonyms like “ critical thinking ” or “analytical skills” in the job description.

“I would add ‘buzzwords’ you can find from the job descriptions or LinkedIn endorsements section to filter into your resume to comply with the ATS,” Matthew Warzel, CPRW resume writer, advises. Warzel recommends including these skills on your resume but warns to “leave the soft skills as adjectives in the summary section. That is the only place soft skills should be mentioned.”

On the other hand, you can list hard skills separately in a skills section on your resume .

3 examples of problem solving

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In a Cover Letter or an Interview

Explaining your problem-solving skills in an interview can seem daunting. You’re required to expand on your process — how you identified a problem, analyzed potential solutions, and made a choice. As long as you can explain your approach, it’s okay if that solution didn’t come from a professional work experience.

“Young professionals shortchange themselves by thinking only paid-for solutions matter to employers,” Skalka says. “People at the genesis of their careers don’t have a wealth of professional experience to pull from, but they do have relevant experience to share.”

Aaron Case, career counselor and CPRW at Resume Genius, agrees and encourages early professionals to share this skill. “If you don’t have any relevant work experience yet, you can still highlight your problem-solving skills in your cover letter,” he says. “Just showcase examples of problems you solved while completing your degree, working at internships, or volunteering. You can even pull examples from completely unrelated part-time jobs, as long as you make it clear how your problem-solving ability transfers to your new line of work.”

Learn How to Identify Problems

Problem-solving doesn’t just require finding solutions to problems that are already there. It’s also about being proactive when something isn’t working as you hoped it would. Practice questioning and getting curious about processes and activities in your everyday life. What could you improve? What would you do if you had more resources for this process? If you had fewer? Challenge yourself to challenge the world around you.

Think Digitally

“Employers in the modern workplace value digital problem-solving skills, like being able to find a technology solution to a traditional issue,” Case says. “For example, when I first started working as a marketing writer, my department didn’t have the budget to hire a professional voice actor for marketing video voiceovers. But I found a perfect solution to the problem with an AI voiceover service that cost a fraction of the price of an actor.”

Being comfortable with new technology — even ones you haven’t used before — is a valuable skill in an increasingly hybrid and remote world. Don’t be afraid to research new and innovative technologies to help automate processes or find a more efficient technological solution.

Collaborate

Problem-solving isn’t done in a silo, and it shouldn’t be. Use your collaboration skills to gather multiple perspectives, help eliminate bias, and listen to alternative solutions. Ask others where they think the problem is coming from and what solutions would help them with your workflow. From there, try to compromise on a solution that can benefit everyone.

If we’ve learned anything from the past few years, it’s that the world of work is constantly changing — which means it’s crucial to know how to adapt . Be comfortable narrowing down a solution, then changing your direction when a colleague provides a new piece of information. Challenge yourself to get out of your comfort zone, whether with your personal routine or trying a new system at work.

Put Yourself in the Middle of Tough Moments

Just like adapting requires you to challenge your routine and tradition, good problem-solving requires you to put yourself in challenging situations — especially ones where you don’t have relevant experience or expertise to find a solution. Because you won’t know how to tackle the problem, you’ll learn new problem-solving skills and how to navigate new challenges. Ask your manager or a peer if you can help them work on a complicated problem, and be proactive about asking them questions along the way.

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Step 1 of 3

Companies always need people to help them find solutions — especially proactive employees who have practical analytical skills and can collaborate to decide the best way to move forward. Whether or not you have experience solving problems in a professional workplace, illustrate your problem-solving skills by describing your research, analysis, and decision-making process — and make it clear that you’re the solution to the employer’s current problems. 

Image Credit: Christina Morillo / Pexels 

Zoe Kaplan

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Overview of the Problem-Solving Mental Process

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

Frequently Asked Questions

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

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

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

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

The following steps include developing strategies and organizing knowledge.

1. Identifying the Problem

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

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

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

2. Defining the Problem

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

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

3. Forming a Strategy

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

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

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

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

4. Organizing Information

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

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

5. Allocating Resources

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

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

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

6. Monitoring Progress

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

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

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

7. Evaluating the Results

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

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

A Word From Verywell​

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

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You can become a better problem solving by:

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

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

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

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

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

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

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

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A guide to problem-solving techniques, steps, and skills

3 examples of problem solving

You might associate problem-solving with the math exercises that a seven-year-old would do at school. But problem-solving isn’t just about math — it’s a crucial skill that helps everyone make better decisions in everyday life or work.

A guide to problem-solving techniques, steps, and skills

Problem-solving involves finding effective solutions to address complex challenges, in any context they may arise.

Unfortunately, structured and systematic problem-solving methods aren’t commonly taught. Instead, when solving a problem, PMs tend to rely heavily on intuition. While for simple issues this might work well, solving a complex problem with a straightforward solution is often ineffective and can even create more problems.

In this article, you’ll learn a framework for approaching problem-solving, alongside how you can improve your problem-solving skills.

The 7 steps to problem-solving

When it comes to problem-solving there are seven key steps that you should follow: define the problem, disaggregate, prioritize problem branches, create an analysis plan, conduct analysis, synthesis, and communication.

1. Define the problem

Problem-solving begins with a clear understanding of the issue at hand. Without a well-defined problem statement, confusion and misunderstandings can hinder progress. It’s crucial to ensure that the problem statement is outcome-focused, specific, measurable whenever possible, and time-bound.

Additionally, aligning the problem definition with relevant stakeholders and decision-makers is essential to ensure efforts are directed towards addressing the actual problem rather than side issues.

2. Disaggregate

Complex issues often require deeper analysis. Instead of tackling the entire problem at once, the next step is to break it down into smaller, more manageable components.

Various types of logic trees (also known as issue trees or decision trees) can be used to break down the problem. At each stage where new branches are created, it’s important for them to be “MECE” – mutually exclusive and collectively exhaustive. This process of breaking down continues until manageable components are identified, allowing for individual examination.

The decomposition of the problem demands looking at the problem from various perspectives. That is why collaboration within a team often yields more valuable results, as diverse viewpoints lead to a richer pool of ideas and solutions.

3. Prioritize problem branches

The next step involves prioritization. Not all branches of the problem tree have the same impact, so it’s important to understand the significance of each and focus attention on the most impactful areas. Prioritizing helps streamline efforts and minimize the time required to solve the problem.

3 examples of problem solving

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3 examples of problem solving

4. Create an analysis plan

For prioritized components, you may need to conduct in-depth analysis. Before proceeding, a work plan is created for data gathering and analysis. If work is conducted within a team, having a plan provides guidance on what needs to be achieved, who is responsible for which tasks, and the timelines involved.

5. Conduct analysis

Data gathering and analysis are central to the problem-solving process. It’s a good practice to set time limits for this phase to prevent excessive time spent on perfecting details. You can employ heuristics and rule-of-thumb reasoning to improve efficiency and direct efforts towards the most impactful work.

6. Synthesis

After each individual branch component has been researched, the problem isn’t solved yet. The next step is synthesizing the data logically to address the initial question. The synthesis process and the logical relationship between the individual branch results depend on the logic tree used.

7. Communication

The last step is communicating the story and the solution of the problem to the stakeholders and decision-makers. Clear effective communication is necessary to build trust in the solution and facilitates understanding among all parties involved. It ensures that stakeholders grasp the intricacies of the problem and the proposed solution, leading to informed decision-making.

Exploring problem-solving in various contexts

While problem-solving has traditionally been associated with fields like engineering and science, today it has become a fundamental skill for individuals across all professions. In fact, problem-solving consistently ranks as one of the top skills required by employers.

Problem-solving techniques can be applied in diverse contexts:

  • Individuals — What career path should I choose? Where should I live? These are examples of simple and common personal challenges that require effective problem-solving skills
  • Organizations — Businesses also face many decisions that are not trivial to answer. Should we expand into new markets this year? How can we enhance the quality of our product development? Will our office accommodate the upcoming year’s growth in terms of capacity?
  • Societal issues — The biggest world challenges are also complex problems that can be addressed with the same technique. How can we minimize the impact of climate change? How do we fight cancer?

Despite the variation in domains and contexts, the fundamental approach to solving these questions remains the same. It starts with gaining a clear understanding of the problem, followed by decomposition, conducting analysis of the decomposed branches, and synthesizing it into a result that answers the initial problem.

Real-world examples of problem-solving

Let’s now explore some examples where we can apply the problem solving framework.

Problem: In the production of electronic devices, you observe an increasing number of defects. How can you reduce the error rate and improve the quality?

Electric Devices

Before delving into analysis, you can deprioritize branches that you already have information for or ones you deem less important. For instance, while transportation delays may occur, the resulting material degradation is likely negligible. For other branches, additional research and data gathering may be necessary.

Once results are obtained, synthesis is crucial to address the core question: How can you decrease the defect rate?

While all factors listed may play a role, their significance varies. Your task is to prioritize effectively. Through data analysis, you may discover that altering the equipment would bring the most substantial positive outcome. However, executing a solution isn’t always straightforward. In prioritizing, you should consider both the potential impact and the level of effort needed for implementation.

By evaluating impact and effort, you can systematically prioritize areas for improvement, focusing on those with high impact and requiring minimal effort to address. This approach ensures efficient allocation of resources towards improvements that offer the greatest return on investment.

Problem : What should be my next job role?

Next Job

When breaking down this problem, you need to consider various factors that are important for your future happiness in the role. This includes aspects like the company culture, our interest in the work itself, and the lifestyle that you can afford with the role.

However, not all factors carry the same weight for us. To make sense of the results, we can assign a weight factor to each branch. For instance, passion for the job role may have a weight factor of 1, while interest in the industry may have a weight factor of 0.5, because that is less important for you.

By applying these weights to a specific role and summing the values, you can have an estimate of how suitable that role is for you. Moreover, you can compare two roles and make an informed decision based on these weighted indicators.

Key problem-solving skills

This framework provides the foundation and guidance needed to effectively solve problems. However, successfully applying this framework requires the following:

  • Creativity — During the decomposition phase, it’s essential to approach the problem from various perspectives and think outside the box to generate innovative ideas for breaking down the problem tree
  • Decision-making — Throughout the process, decisions must be made, even when full confidence is lacking. Employing rules of thumb to simplify analysis or selecting one tree cut over another requires decisiveness and comfort with choices made
  • Analytical skills — Analytical and research skills are necessary for the phase following decomposition, involving data gathering and analysis on selected tree branches
  • Teamwork — Collaboration and teamwork are crucial when working within a team setting. Solving problems effectively often requires collective effort and shared responsibility
  • Communication — Clear and structured communication is essential to convey the problem solution to stakeholders and decision-makers and build trust

How to enhance your problem-solving skills

Problem-solving requires practice and a certain mindset. The more you practice, the easier it becomes. Here are some strategies to enhance your skills:

  • Practice structured thinking in your daily life — Break down problems or questions into manageable parts. You don’t need to go through the entire problem-solving process and conduct detailed analysis. When conveying a message, simplify the conversation by breaking the message into smaller, more understandable segments
  • Regularly challenging yourself with games and puzzles — Solving puzzles, riddles, or strategy games can boost your problem-solving skills and cognitive agility.
  • Engage with individuals from diverse backgrounds and viewpoints — Conversing with people who offer different perspectives provides fresh insights and alternative solutions to problems. This boosts creativity and helps in approaching challenges from new angles

Final thoughts

Problem-solving extends far beyond mathematics or scientific fields; it’s a critical skill for making informed decisions in every area of life and work. The seven-step framework presented here provides a systematic approach to problem-solving, relevant across various domains.

Now, consider this: What’s one question currently on your mind? Grab a piece of paper and try to apply the problem-solving framework. You might uncover fresh insights you hadn’t considered before.

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MindManager Blog

The 5 steps of the solving problem process

August 17, 2023 by MindManager Blog

Whether you run a business, manage a team, or work in an industry where change is the norm, it may feel like something is always going wrong. Thankfully, becoming proficient in the problem solving process can alleviate a great deal of the stress that business issues can create.

Understanding the right way to solve problems not only takes the guesswork out of how to deal with difficult, unexpected, or complex situations, it can lead to more effective long-term solutions.

In this article, we’ll walk you through the 5 steps of problem solving, and help you explore a few examples of problem solving scenarios where you can see the problem solving process in action before putting it to work.

Understanding the problem solving process

When something isn’t working, it’s important to understand what’s at the root of the problem so you can fix it and prevent it from happening again. That’s why resolving difficult or complex issues works best when you apply proven business problem solving tools and techniques – from soft skills, to software.

The problem solving process typically includes:

  • Pinpointing what’s broken by gathering data and consulting with team members.
  • Figuring out why it’s not working by mapping out and troubleshooting the problem.
  • Deciding on the most effective way to fix it by brainstorming and then implementing a solution.

While skills like active listening, collaboration, and leadership play an important role in problem solving, tools like visual mapping software make it easier to define and share problem solving objectives, play out various solutions, and even put the best fit to work.

Before you can take your first step toward solving a problem, you need to have a clear idea of what the issue is and the outcome you want to achieve by resolving it.

For example, if your company currently manufactures 50 widgets a day, but you’ve started processing orders for 75 widgets a day, you could simply say you have a production deficit.

However, the problem solving process will prove far more valuable if you define the start and end point by clarifying that production is running short by 25 widgets a day, and you need to increase daily production by 50%.

Once you know where you’re at and where you need to end up, these five steps will take you from Point A to Point B:

  • Figure out what’s causing the problem . You may need to gather knowledge and evaluate input from different documents, departments, and personnel to isolate the factors that are contributing to your problem. Knowledge visualization software like MindManager can help.
  • Come up with a few viable solutions . Since hitting on exactly the right solution – right away – can be tough, brainstorming with your team and mapping out various scenarios is the best way to move forward. If your first strategy doesn’t pan out, you’ll have others on tap you can turn to.
  • Choose the best option . Decision-making skills, and software that lets you lay out process relationships, priorities, and criteria, are invaluable for selecting the most promising solution. Whether it’s you or someone higher up making that choice, it should include weighing costs, time commitments, and any implementation hurdles.
  • Put your chosen solution to work . Before implementing your fix of choice, you should make key personnel aware of changes that might affect their daily workflow, and set up benchmarks that will make it easy to see if your solution is working.
  • Evaluate your outcome . Now comes the moment of truth: did the solution you implemented solve your problem? Do your benchmarks show you achieved the outcome you wanted? If so, congratulations! If not, you’ll need to tweak your solution to meet your problem solving goal.

In practice, you might not hit a home-run with every solution you execute. But the beauty of a repeatable process like problem solving is that you can carry out steps 4 and 5 again by drawing from the brainstorm options you documented during step 2.

Examples of problem solving scenarios

The best way to get a sense of how the problem solving process works before you try it for yourself is to work through some simple scenarios.

Here are three examples of how you can apply business problem solving techniques to common workplace challenges.

Scenario #1: Manufacturing

Building on our original manufacturing example, you determine that your company is consistently short producing 25 widgets a day and needs to increase daily production by 50%.

Since you’d like to gather data and input from both your manufacturing and sales order departments, you schedule a brainstorming session to discover the root cause of the shortage.

After examining four key production areas – machines, materials, methods, and management – you determine the cause of the problem: the material used to manufacture your widgets can only be fed into your equipment once the machinery warms up to a specific temperature for the day.

Your team comes up with three possible solutions.

  • Leave your machinery running 24 hours so it’s always at temperature.
  • Invest in equipment that heats up faster.
  • Find an alternate material for your widgets.

After weighing the expense of the first two solutions, and conducting some online research, you decide that switching to a comparable but less expensive material that can be worked at a lower temperature is your best option.

You implement your plan, monitor your widget quality and output over the following week, and declare your solution a success when daily production increases by 100%.

Scenario #2: Service Delivery

Business training is booming and you’ve had to onboard new staff over the past month. Now you learn that several clients have expressed concern about the quality of your recent training sessions.

After speaking with both clients and staff, you discover there are actually two distinct factors contributing to your quality problem:

  • The additional conference room you’ve leased to accommodate your expanding training sessions has terrible acoustics
  • The AV equipment you’ve purchased to accommodate your expanding workforce is on back-order – and your new hires have been making do without

You could look for a new conference room or re-schedule upcoming training sessions until after your new equipment arrives. But your team collaboratively determines that the best way to mitigate both issues at once is by temporarily renting the high-quality sound and visual system they need.

Using benchmarks that include several weeks of feedback from session attendees, and random session spot-checks you conduct personally, you conclude the solution has worked.

Scenario #3: Marketing

You’ve invested heavily in product marketing, but still can’t meet your sales goals. Specifically, you missed your revenue target by 30% last year and would like to meet that same target this year.

After collecting and examining reams of information from your sales and accounting departments, you sit down with your marketing team to figure out what’s hindering your success in the marketplace.

Determining that your product isn’t competitively priced, you map out two viable solutions.

  • Hire a third-party specialist to conduct a detailed market analysis.
  • Drop the price of your product to undercut competitors.

Since you’re in a hurry for results, you decide to immediately reduce the price of your product and market it accordingly.

When revenue figures for the following quarter show sales have declined even further – and marketing surveys show potential customers are doubting the quality of your product – you revert back to your original pricing, revisit your problem solving process, and implement the market analysis solution instead.

With the valuable information you gain, you finally arrive at just the right product price for your target market and sales begin to pick up. Although you miss your revenue target again this year, you meet it by the second quarter of the following year.

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Problem-solving skills and how to improve them (with examples)

What’s life without its challenges? All of us will at some point encounter professional and personal hurdles. That might mean resolving a conflict with coworkers or making a big life decision. With effective problem solving skills, you’ll find tricky situations easier to navigate, and welcome challenges as opportunities to learn, grow and thrive. 

In this guide, we dive into the importance of problem solving skills and look at examples that show how relevant they are to different areas of your life. We cover how to find creative solutions and implement them, as well as ways to refine your skills in communication and critical thinking. Ready to start solving problems? Read on.

What is problem solving? 

Before we cover strategies for improving problem solving skills, it’s important to first have a clear understanding of the problem solving process. Here are the steps in solving a problem:

  • Recognise the issue you are facing 
  • Take a look at all the information to gain insights
  • Come up with solutions
  • Look at the pros and cons of each solution and how it might play out
  • Plan, organise and implement your solution
  • Continuously assess the effectiveness of the solution and make adjustments as needed

Problem solving skills

There’s more to problem solving than coming up with a quick fix. Effective problem solving requires wide range of skills and abilities, such as:

  • Critical thinking: the ability to think logically, analyse information and look at situations from different perspectives.
  • Creativity: being able to come up with innovative, out-of-the-box solutions.
  • Decision-making:  making informed choices by considering all the available information.
  • Communication:  being able to express ideas clearly and effectively.
  • Analytical skills: breaking down complex problems into smaller parts and examining each one.
  • Time management:  allocating time and resources effectively to address problems.
  • Adaptability: being open to change and willing to adjust strategies.
  • Conflict resolution:  skillfully managing conflicts and finding solutions that work for all.

Examples of problem solving skills

Problem solving skills in the workplace are invaluable, whether you need them for managing a team, dealing with clients or juggling deadlines. To get a better understanding of how you might use these skills in real-life scenarios, here are some problem solving examples that are common in the workplace.

  • Analytical thinking

Analytical thinking is something that comes naturally to some, while others have to work a little harder. It involves being able to look at problem solving from a logical perspective, breaking down the issues into manageable parts. 

Example scenarios of analytical thinking

Quality control: in a manufacturing facility, analytical thinking helps identify the causes of product defects in order to pinpoint solutions.

Market research: marketing teams rely on analytical thinking to examine consumer data, identify market trends and make informed decisions on ad campaigns.

  • Critical thinking

Critical thinkers are able to approach problems objectively, looking at different viewpoints without rushing to a decision. Critical thinking is an important aspect of problem solving, helping to uncover biases and assumptions and weigh up the quality of the information before making any decisions. 

Example scenarios of critical thinking

  • Strategic planning:  in the boardroom, critical thinking is important for assessing economic trends, competitor threats and more. It guides leaders in making informed decisions about long-term company goals and growth strategies.
  • Conflict resolution: HR professionals often use critical thinking when dealing with workplace conflicts. They objectively analyse the issues at hand and find an appropriate solution.

Decision-making

Making decisions is often the hardest part of problem solving. How do you know which solution is the right one? It involves evaluating information, considering potential outcomes and choosing the most suitable option. Effective problem solving relies on making well-informed decisions.

Example scenarios of decision-making

  • Budget allocation: financial managers must decide how to allocate resources to various projects or departments. 
  • Negotiation:  salespeople and procurement professionals negotiate terms, pricing and agreements with clients, suppliers and partners.

Research skills

Research skills are pivotal when it comes to problem solving, to ensure you have all the information you need to make an informed decision. These skills involve searching for relevant data, critically evaluating information sources, and drawing meaningful conclusions. 

Example scenarios of research skills

  • Product development: a tech startup uses research skills to conduct market research to identify gaps and opportunities in the market. 
  • Employee engagement:  an HR manager uses research skills to conduct employee surveys and focus groups.

A little creative flair goes a long way. By thinking outside the box, you can approach problems from different angles. Creative thinking involves combining existing knowledge, experiences and perspectives in new and innovative ways to come up with inventive solutions. 

Example scenarios of creativity

  • Cost reduction: creative problem solvers within a manufacturing company might look at new ways to reduce production costs by using waste materials.
  • Customer experience: a retail chain might look at implementing interactive displays and engaging store layouts to increase customer satisfaction and sales.

Collaboration

It’s not always easy to work with other people, but collaboration is a key element in problem solving, allowing you to make use of different perspectives and areas of expertise to find solutions.

Example scenarios

  • Healthcare diagnosis: in a hospital setting, medical professionals collaborate to diagnose complex medical cases.
  • Project management: project managers coordinate efforts, allocate resources and address issues that may arise during a project's lifecycle.

Conflict Resolution

Being able to mediate conflicts is a great skill to have. It involves facilitating open communication, understanding different perspectives and finding solutions that work for everyone. Conflict resolution is essential for managing any differences in opinion that arise.

Example scenarios of conflict resolution

  • Client dispute: a customer might be dissatisfied with a product or service and demand a refund. The customer service representative addresses the issue through active listening and negotiation to reach a solution.
  • Project delay: a project manager might face resistance from team members about a change in project scope and will need to find a middle ground before the project can continue.

Risk management

Risk management is essential across many workplaces. It involves analysing potential threats and opportunities, evaluating their impact and implementing strategies to minimise negative consequences. Risk management is closely tied to problem solving, as it addresses potential obstacles and challenges that may arise during the problem solving process.

Example scenarios of risk management

  • Project risk management: in a construction project, risk management involves identifying potential delays, cost overruns and safety hazards. Risk mitigation strategies are developed, such as scheduling buffers and establishing safety protocols. 
  • Financial risk management: in financial institutions, risk management assesses and manages risks associated with investments and lending.

Communication

Effective communication is a skill that will get you far in all areas of life. When it comes to problem solving, communication plays an important role in facilitating collaboration, sharing insights and ensuring that all stakeholders have the same expectations. 

Example scenarios of communication

  • Customer service improvement:  in a retail environment, open communication channels result in higher customer satisfaction scores.
  • Safety enhancement:  in a manufacturing facility, a robust communication strategy that includes safety briefings, incident reporting and employee training helps minimise accidents and injuries.

How to improve problem solving skills 

Ready to improve your problem solving skills? In this section we explore strategies and techniques that will give you a head start in developing better problem solving skills. 

Adopt the problem solving mindset

Developing a problem solving mindset will help you tackle challenges effectively . Start by accepting problems as opportunities for growth and learning, rather than as obstacles or setbacks. This will allow you to approach every challenge with a can-do attitude.

Patience is also essential, because it will allow you to work through the problem and its various solutions mindfully. Persistence is also important, so you can keep adapting your approach until you find the right solution.

Finally, don’t forget to ask questions. What do you need to know? What assumptions are you making? What can you learn from previous attempts? Approach problem solving as an opportunity to  acquire new skills . Stay curious, seek out solutions, explore new possibilities and remain open to different problem solving approaches.

Understand the problem

There’s no point trying to solve a problem you don’t understand. To analyse a problem effectively, you need to be able to define it. This allows you to break it down into smaller parts, making it easier to find causes and potential solutions. Start with a well-defined problem statement that is precise and specific. This will help you focus your efforts on the core issue, so you don’t waste time and resources on the wrong concerns.

Strategies for problem analysis

  • Start with the problem statement and ask ‘Why?’ multiple times to dig deeper.
  • Gather relevant data and information related to the problem. 
  • Include those affected by the problem in the analysis process.
  • Compare the current problem with similar situations or cases to gain valuable insights.
  • Use simulations to explore potential outcomes of different solutions.
  • Continuously gather feedback during the problem solving process. 

Develop critical thinking and creativity skills

Critical thinking and creativity are both important when it comes to looking at the problem objectively and thinking outside the box. Critical thinking encourages you to question assumptions, recognise biases and seek evidence to support your conclusions. Creative thinking allows you to look at the problem from different angles to reveal new insights and opportunities.

Enhance research and decision-making skills

Research and decision-making skills are pivotal in problem solving as they enable you to gather relevant information, analyse options and choose the best course of action. Research provides the information and data needed, and ensures that you have a comprehensive understanding of the problem and its context. Effective decision-making is about selecting the solution that best addresses the problem.

Strategies to improve research and decision-making skills

  • Clearly define what you want to achieve through research.
  • Use a variety of sources, including books, articles, research papers, interviews, surveys and online databases.
  • Evaluate the credibility and reliability of your information sources.
  • Incorporate risk assessment into your decision-making process. 
  • Seek input from experts, colleagues and mentors when making important decisions. 
  • After making decisions, reflect on the outcomes and lessons learned. Use this to improve your decision-making skills over time.

Strengthen collaboration skills

Being able to work with others is one of the most important skills to have at work. Collaboration skills enable everyone to work effectively as a team, share their perspectives and collectively find solutions. 

Tips for improving teamwork and collaboration

  • Define people’s roles and responsibilities within the team. 
  • Encourage an environment of open communication where team members feel comfortable sharing ideas.
  • Practise active listening by giving full attention to others when they speak. 
  • Hold regular check-in sessions to monitor progress, discuss challenges and make adjustments as needed.
  • Use collaboration tools and platforms to facilitate communication and document progress. 
  • Acknowledge and celebrate team achievements and milestones. 

Learn from past experiences

Once you’ve overcome a challenge, take the time to look back with a critical eye. How effective was the outcome? Could you have tweaked anything in your process? Learning from past experiences is important when it comes to problem solving. It involves reflecting on both successes and failures to gain insights, refine strategies and make more informed decisions in the future. 

Strategies for learning from past mistakes

  • After completing a problem solving effort, gather your team for a debriefing session. Discuss what went well and what could have been better.
  • Conduct a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) of resolved problems. 
  • Evaluate the outcomes of past solutions. Did they achieve the desired results? 
  • Commit to continuous learning and improvement. 

Leverage problem solving tools and resources

Problem-solving tools and resources are a great help when it comes to navigating complex challenges. These tools offer structured approaches, methodologies and resources that can streamline the process. 

Tools and resources for problem solving

  • Mind mapping:  mind maps visually organise ideas, concepts and their relationships. 
  • SWOT (Strengths, Weaknesses, Opportunities, Threats) Analysis:  helps in strategic planning and decision-making.
  • Fishbone diagram (Ishikawa Diagram): this tool visually represents the potential root causes of a problem, helping you identify underlying factors contributing to an issue.
  • Decision matrices:  these assist in evaluating options by assigning weights and scores to criteria and alternatives.
  • Process flowcharts:  these allow you to see the steps of a process in sequence, helping identify where the problem is occuring.
  • Decision support software:  software applications and tools, such as data analytics platforms, can help in data-driven decision-making and problem solving.
  • Online courses and training: allow you to acquire new skills and knowledge.

Regular practice

Practice makes perfect! Using your skills in real life allows you to refine them, adapt to new challenges and build confidence in your problem solving capabilities. Make sure to try out these skills whenever you can.

Practical problem solving exercises 

  • Do puzzles, riddles and brainteasers regularly. 
  • Identify real-life challenges or dilemmas you encounter and practice applying problem solving techniques to these situations.
  • Analyse case studies or scenarios relevant to your field or industry. 
  • Regularly review past problem solving experiences and consider what you learned from them. 
  • Attend workshops, webinars or training sessions focused on problem solving. 

How to highlight problem solving skills on a resumé

Effectively showcasing your problem solving skills on your resumé is a great way to demonstrate your ability to address challenges and add value to a workplace. We'll explore how to demonstrate problem solving skills on your resumé, so you stand out from the crowd.

Incorporating problem solving skills in the resumé summary

A resumé summary is your introduction to potential employers and provides an opportunity to succinctly showcase your skills. The resumé summary is often the first section employers read. It offers a snapshot of your qualifications and sets the tone for the rest of your resumé.

Your resumé summary should be customised for different job applications, ensuring that you highlight the specific problem solving skills relevant to the position you’re applying for.

Example 1: Project manager with a proven track record of solving complex operational challenges. Skilled in identifying root causes, developing innovative solutions and leading teams to successful project completion.

Example 2:  Detail-oriented data analyst with strong problem solving skills. Proficient in data-driven decision-making, quantitative analysis and using statistical tools to solve business problems.

Highlighting problem solving skills in the experience section

The experience section of your resumé presents the perfect opportunity to demonstrate your problem solving skills in action. 

  • Start with action verbs: begin each bullet point in your job descriptions with strong action verbs such as, analysed, implemented, resolved and optimised.
  • Quantify achievements: use numbers and percentages to illustrate the impact of your solutions. For example: Increased efficiency by 25% by implementing a new workflow process.
  • Emphasise challenges: describe the specific challenges or problems you faced in your roles. 
  • Solution-oriented language: mention the steps you took to find solutions and the outcomes achieved.

Including problem solving skills in the skills section

The skills section of your resumé should showcase your top abilities, including problem solving skills. Here are some tips for including these skills.

  • Use a subsection:  within your skills section, you could create a subsection specifically dedicated to problem solving skills – especially if the role calls for these skills.
  • Be specific: when listing problem solving skills, be specific about the types of role-related problems you can address. 
  • Prioritise relevant skills:  tailor the list of problem solving skills to match the requirements of the job you're applying for. 

Examples of problem solving skills to include:

  • Creative problem solving
  • Decision making
  • Root cause analysis
  • Strategic problem solving
  • Data-driven problem solving
  • Interpersonal conflict resolution
  • Adaptability
  • Communication skills
  • Problem solving tools
  • Negotiation skills

Demonstrating problem solving skills in project sections or case studies

Including a dedicated section for projects or case studies in your resumé allows you to provide specific examples of your problem solving skills in action. It goes beyond simply listing skills, to demonstrate how you are able to apply those skills to real-world challenges.

Example – Data Analysis

Case Study: Market Expansion Strategy

  • Challenge:  the company was looking to expand into new markets but lacked data on consumer preferences and market dynamics.
  • Solution: conducted comprehensive market research, including surveys and competitor analysis. Applied this research to identify target customer segments and developed a data-driven market-entry strategy.
  • Result:  successfully launched in two new markets, reaching our target of 30% market share within the first year.

Using problem solving skills in cover letters

A well-crafted cover letter is your first impression on any potential employer. Integrating problem solving skills can support your job application by showcasing your ability to address challenges and contribute effectively to their team. Here’s a quick run-down on what to include:

  • Begin your cover letter by briefly mentioning the position you're applying for and your enthusiasm for it.
  • Identify a specific challenge or issue that the company may be facing, to demonstrate your research and understanding of their needs.
  • Include a brief story or scenario from your past experiences where you successfully applied problem solving skills to address a similar challenge. 
  • Highlight the positive outcomes or results achieved through your problem solving efforts. 
  • Explain how your skills make you the ideal person to address their specific challenges.

Problem solving skills are essential in all areas of life, enabling you to overcome challenges, make informed decisions, settle conflicts and drive innovation. We've explored the significance of problem solving skills and how to improve, demonstrate and leverage them effectively. It’s an ever-evolving skill set that can be refined over time. 

By actively incorporating problem solving skills into your day-to-day, you can become a more effective problem solver at work and in your personal life as well.

What are some common problem solving techniques?

Common problem solving techniques include brainstorming, root cause analysis, SWOT analysis, decision matrices, the scientific method and the PDCA (Plan-Do-Check-Act) cycle. These techniques offer structured approaches to identify, analyse and address problems effectively.

How can I improve my critical thinking skills?

Improving critical thinking involves practising skills such as analysis, evaluation and problem solving. It helps to engage in activities like reading, solving puzzles, debating and self-reflection.

What are some common obstacles to problem solving?

Common obstacles to problem solving include biases, lack of information or resources, and resistance to change. Recognising and addressing these obstacles is essential for effective problem solving.

How can I overcome resistance to change when implementing a solution?

To overcome resistance to change, it's essential to communicate the benefits of the proposed solution clearly, involve stakeholders in the decision-making process, address concerns and monitor the implementation's progress to demonstrate its effectiveness.

How can problem solving skills benefit my career?

Problem solving skills are highly valuable in a career as they enable you to navigate challenges, make informed decisions, adapt to change and contribute to innovation and efficiency. These skills enhance your professional effectiveness and can lead to career advancement and increased job satisfaction.

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3 examples of problem solving

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  • Turn your team into skilled problem sol ...

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

Sarah Laoyan contributor headshot

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

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

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

What is problem solving? 

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

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4 steps to better problem solving

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

1. Identify the problem that needs to be solved

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

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

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

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

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

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

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

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

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

Overarching problem: Design requests are being missed

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

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

Where: Email requests, design request spreadsheet

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

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

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

2. Brainstorm multiple solutions

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

Here are a few brainstorming techniques to encourage creative thinking:

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

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

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

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

3. Define the solution

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

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

4. Implement the solution

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

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

Implement common problem-solving strategies

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

Trial and error

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

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

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

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

Here’s an example:

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

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

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

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

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

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

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

A SWOT analysis

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

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

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

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

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

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

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

Even more successful problem solving

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

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

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Top 20 Problem Solving Interview Questions (Example Answers Included)

Mike Simpson 0 Comments

3 examples of problem solving

By Mike Simpson

When candidates prepare for interviews, they usually focus on highlighting their leadership, communication, teamwork, and similar crucial soft skills . However, not everyone gets ready for problem-solving interview questions. And that can be a big mistake.

Problem-solving is relevant to nearly any job on the planet. Yes, it’s more prevalent in certain industries, but it’s helpful almost everywhere.

Regardless of the role you want to land, you may be asked to provide problem-solving examples or describe how you would deal with specific situations. That’s why being ready to showcase your problem-solving skills is so vital.

If you aren’t sure who to tackle problem-solving questions, don’t worry, we have your back. Come with us as we explore this exciting part of the interview process, as well as some problem-solving interview questions and example answers.

What Is Problem-Solving?

When you’re trying to land a position, there’s a good chance you’ll face some problem-solving interview questions. But what exactly is problem-solving? And why is it so important to hiring managers?

Well, the good folks at Merriam-Webster define problem-solving as “the process or act of finding a solution to a problem.” While that may seem like common sense, there’s a critical part to that definition that should catch your eye.

What part is that? The word “process.”

In the end, problem-solving is an activity. It’s your ability to take appropriate steps to find answers, determine how to proceed, or otherwise overcome the challenge.

Being great at it usually means having a range of helpful problem-solving skills and traits. Research, diligence, patience, attention-to-detail , collaboration… they can all play a role. So can analytical thinking , creativity, and open-mindedness.

But why do hiring managers worry about your problem-solving skills? Well, mainly, because every job comes with its fair share of problems.

While problem-solving is relevant to scientific, technical, legal, medical, and a whole slew of other careers. It helps you overcome challenges and deal with the unexpected. It plays a role in troubleshooting and innovation. That’s why it matters to hiring managers.

How to Answer Problem-Solving Interview Questions

Okay, before we get to our examples, let’s take a quick second to talk about strategy. Knowing how to answer problem-solving interview questions is crucial. Why? Because the hiring manager might ask you something that you don’t anticipate.

Problem-solving interview questions are all about seeing how you think. As a result, they can be a bit… unconventional.

These aren’t your run-of-the-mill job interview questions . Instead, they are tricky behavioral interview questions . After all, the goal is to find out how you approach problem-solving, so most are going to feature scenarios, brainteasers, or something similar.

So, having a great strategy means knowing how to deal with behavioral questions. Luckily, there are a couple of tools that can help.

First, when it comes to the classic approach to behavioral interview questions, look no further than the STAR Method . With the STAR method, you learn how to turn your answers into captivating stories. This makes your responses tons more engaging, ensuring you keep the hiring manager’s attention from beginning to end.

Now, should you stop with the STAR Method? Of course not. If you want to take your answers to the next level, spend some time with the Tailoring Method , too.

With the Tailoring Method, it’s all about relevance. So, if you get a chance to choose an example that demonstrates your problem-solving skills, this is really the way to go.

We also wanted to let you know that we created an amazing free cheat sheet that will give you word-for-word answers for some of the toughest interview questions you are going to face in your upcoming interview. After all, hiring managers will often ask you more generalized interview questions!

Click below to get your free PDF now:

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Top 3 Problem-Solving-Based Interview Questions

Alright, here is what you’ve been waiting for: the problem-solving questions and sample answers.

While many questions in this category are job-specific, these tend to apply to nearly any job. That means there’s a good chance you’ll come across them at some point in your career, making them a great starting point when you’re practicing for an interview.

So, let’s dive in, shall we? Here’s a look at the top three problem-solving interview questions and example responses.

1. Can you tell me about a time when you had to solve a challenging problem?

In the land of problem-solving questions, this one might be your best-case scenario. It lets you choose your own problem-solving examples to highlight, putting you in complete control.

When you choose an example, go with one that is relevant to what you’ll face in the role. The closer the match, the better the answer is in the eyes of the hiring manager.

EXAMPLE ANSWER:

“While working as a mobile telecom support specialist for a large organization, we had to transition our MDM service from one vendor to another within 45 days. This personally physically handling 500 devices within the agency. Devices had to be gathered from the headquarters and satellite offices, which were located all across the state, something that was challenging even without the tight deadline. I approached the situation by identifying the location assignment of all personnel within the organization, enabling me to estimate transit times for receiving the devices. Next, I timed out how many devices I could personally update in a day. Together, this allowed me to create a general timeline. After that, I coordinated with each location, both expressing the urgency of adhering to deadlines and scheduling bulk shipping options. While there were occasional bouts of resistance, I worked with location leaders to calm concerns and facilitate action. While performing all of the updates was daunting, my approach to organizing the event made it a success. Ultimately, the entire transition was finished five days before the deadline, exceeding the expectations of many.”

2. Describe a time where you made a mistake. What did you do to fix it?

While this might not look like it’s based on problem-solving on the surface, it actually is. When you make a mistake, it creates a challenge, one you have to work your way through. At a minimum, it’s an opportunity to highlight problem-solving skills, even if you don’t address the topic directly.

When you choose an example, you want to go with a situation where the end was positive. However, the issue still has to be significant, causing something negative to happen in the moment that you, ideally, overcame.

“When I first began in a supervisory role, I had trouble setting down my individual contributor hat. I tried to keep up with my past duties while also taking on the responsibilities of my new role. As a result, I began rushing and introduced an error into the code of the software my team was updating. The error led to a memory leak. We became aware of the issue when the performance was hindered, though we didn’t immediately know the cause. I dove back into the code, reviewing recent changes, and, ultimately, determined the issue was a mistake on my end. When I made that discovery, I took several steps. First, I let my team know that the error was mine and let them know its nature. Second, I worked with my team to correct the issue, resolving the memory leak. Finally, I took this as a lesson about delegation. I began assigning work to my team more effectively, a move that allowed me to excel as a manager and help them thrive as contributors. It was a crucial learning moment, one that I have valued every day since.”

3. If you identify a potential risk in a project, what steps do you take to prevent it?

Yes, this is also a problem-solving question. The difference is, with this one, it’s not about fixing an issue; it’s about stopping it from happening. Still, you use problem-solving skills along the way, so it falls in this question category.

If you can, use an example of a moment when you mitigated risk in the past. If you haven’t had that opportunity, approach it theoretically, discussing the steps you would take to prevent an issue from developing.

“If I identify a potential risk in a project, my first step is to assess the various factors that could lead to a poor outcome. Prevention requires analysis. Ensuring I fully understand what can trigger the undesired event creates the right foundation, allowing me to figure out how to reduce the likelihood of those events occurring. Once I have the right level of understanding, I come up with a mitigation plan. Exactly what this includes varies depending on the nature of the issue, though it usually involves various steps and checks designed to monitor the project as it progresses to spot paths that may make the problem more likely to happen. I find this approach effective as it combines knowledge and ongoing vigilance. That way, if the project begins to head into risky territory, I can correct its trajectory.”

17 More Problem-Solving-Based Interview Questions

In the world of problem-solving questions, some apply to a wide range of jobs, while others are more niche. For example, customer service reps and IT helpdesk professionals both encounter challenges, but not usually the same kind.

As a result, some of the questions in this list may be more relevant to certain careers than others. However, they all give you insights into what this kind of question looks like, making them worth reviewing.

Here are 17 more problem-solving interview questions you might face off against during your job search:

  • How would you describe your problem-solving skills?
  • Can you tell me about a time when you had to use creativity to deal with an obstacle?
  • Describe a time when you discovered an unmet customer need while assisting a customer and found a way to meet it.
  • If you were faced with an upset customer, how would you diffuse the situation?
  • Tell me about a time when you had to troubleshoot a complex issue.
  • Imagine you were overseeing a project and needed a particular item. You have two choices of vendors: one that can deliver on time but would be over budget, and one that’s under budget but would deliver one week later than you need it. How do you figure out which approach to use?
  • Your manager wants to upgrade a tool you regularly use for your job and wants your recommendation. How do you formulate one?
  • A supplier has said that an item you need for a project isn’t going to be delivered as scheduled, something that would cause your project to fall behind schedule. What do you do to try and keep the timeline on target?
  • Can you share an example of a moment where you encountered a unique problem you and your colleagues had never seen before? How did you figure out what to do?
  • Imagine you were scheduled to give a presentation with a colleague, and your colleague called in sick right before it was set to begin. What would you do?
  • If you are given two urgent tasks from different members of the leadership team, both with the same tight deadline, how do you choose which to tackle first?
  • Tell me about a time you and a colleague didn’t see eye-to-eye. How did you decide what to do?
  • Describe your troubleshooting process.
  • Tell me about a time where there was a problem that you weren’t able to solve. What happened?
  • In your opening, what skills or traits make a person an exceptional problem-solver?
  • When you face a problem that requires action, do you usually jump in or take a moment to carefully assess the situation?
  • When you encounter a new problem you’ve never seen before, what is the first step that you take?

Putting It All Together

At this point, you should have a solid idea of how to approach problem-solving interview questions. Use the tips above to your advantage. That way, you can thrive during your next interview.

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  • What Is Your Greatest Weakness?
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  • Why Should We Hire You?

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3 examples of problem solving

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His advice and insights have been shared and featured by publications such as Forbes , Entrepreneur , CNBC and more as well as educational institutions such as the University of Michigan , Penn State , Northeastern and others.

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About The Author

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Co-Founder and CEO of TheInterviewGuys.com. Mike is a job interview and career expert and the head writer at TheInterviewGuys.com. His advice and insights have been shared and featured by publications such as Forbes , Entrepreneur , CNBC and more as well as educational institutions such as the University of Michigan , Penn State , Northeastern and others. Learn more about The Interview Guys on our About Us page .

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3 examples of problem solving

Creative Problem Solving in Large Language and Vision Models – What Would it Take?

We advocate for a strong integration of Computational Creativity (CC) with research in large language and vision models (LLVMs) to address a key limitation of these models, i.e., creative problem solving. We present preliminary experiments showing how CC principles can be applied to address this limitation. Our goal is to foster discussions on creative problem solving in LLVMs and CC at prestigious ML venues.

Lakshmi Nair Georgia Institute of Technology Atlanta, GA, USA                        Evana Gizzi Tufts University Medford, MA, USA                        Jivko Sinapov Tufts University Medford, MA, USA

1 Introduction

Creativity is “ …the ability to come up with an idea which, relative to the pre-existing domain-space in one’s mind, one could not have had before. Whether any other person (or system) has already come up with it on an earlier occasion is irrelevant. ” Boden ( 1998 ) , p.216. For artificial agents, Computational Creativity (CC) is a multi-disciplinary field (spanning Philosophy, Psychology, Neuroscience, and Computer Science) that seeks to develop computational methods capable of generating creative outcomes reminiscent of creative processes in humans Gizzi et al. ( 2022 ) . Within CC, creative problem solving is a sub-area that requires an agent to discover – from its perspective – novel and previously unseen ways to accomplish a task. For example, in the absence of a ladle to scoop ingredients, an agent might creatively choose to substitute a bowl in place of the ladle. In this sense, creative problem solving encompasses creativity that is specifically task-oriented , as opposed to the generation of creative artifacts e.g., music or images.

Refer to caption

While recent state-of-the-art large language models (LLMs) and vision-language models (VLMs) have demonstrated competency in artistic endeavours Rombach et al. ( 2021 ); Copet et al. ( 2023 ) , creative problem solving continues to be a shortcoming of these models (we use LLVM to denote the umbrella of both LLMs and VLMs). For instance, in Bubeck et al. ( 2023 ) , the authors point out that “discontinuous tasks” that require a certain “Eureka” idea, i.e., creative problem solving, is currently a limitation of models like GPT-4. Similar observations have been made in follow up work showing that state-of-the-art LLMs inherently possess poor creative problem solving capabilities compared to humans Tian et al. ( 2023 ); Naeini et al. ( 2023 ) . Given this obvious limitation, ongoing research in Machine Learning should seek to address the gap between LLVMs and creative problem solving, to further enhance the intelligent capabilities of these models. As defined in prior work, “ Intelligence is the ability to work and adapt to the environment with insufficient knowledge and resources. ” Pennachin and Goertzel ( 2007 ) , p.10. Demonstrated in hallmark examples of human ingenuity, like the makeshift C ⁢ O 2 𝐶 subscript 𝑂 2 CO_{2} italic_C italic_O start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT filter built onboard the Apollo-13 Cass ( 2005 ) , or the makeshift medical devices used to offset equipment shortages during COVID-19 Turner et al. ( 2020 ) , creative problem solving is especially important when dealing with resource-critical scenarios. Since humans may tend to “choke” under high pressure situations DeCaro et al. ( 2011 ) often limiting their CPS skills, autonomous agents equipped with LLVMs that have similar capabilities would be highly assistive and transformative to humans in high-stake environments. These include situations like rescue missions BBC ( 2012 ) or autonomous operation in human-inaccessible environments (e.g., space or underwater exploration) with limited resources Atkeson et al. ( 2018 ) . However, the exceptional degree of creative problem solving necessary for such assistance remains beyond the scope of LLVMs today, limiting their intelligence (See Appx. B.1 ).

We believe that a discussion of Computational Creativity is essential to addressing this limitation. It is our position that Machine Learning and Computational Creativity should be strongly integrated in research to enable effective creative problem solving in LLVMs and push the frontiers of their ingenuity.

2 Two Cultures Problem: Why does CC not receive a wider reception in ML?

Even though creative problem solving (CPS) is a shortcoming of existing LLVMs, Computational Creativity seldom finds its way into mainstream ML research. We believe this discrepancy aligns with the “two cultures” problem Hammond et al. ( 2013 ) (also corroborated in Van Heerden and Bas ( 2021 ); Lahikainen et al. ( 2024 ) ), and is motivated by three aspects of CC literature as it relates to creative problem solving: a) the lack of a precise definition of CPS makes it challenging to identify how existing approaches in LLVMs are deficient in CPS skills; b) the somewhat “abstract” computational descriptions of CPS in Computational Creativity is challenging to connect to practical algorithms in LLVMs; and c) the lack of standardized benchmarks make it harder to evaluate LLVMs for CPS. In our discussions relating to a) in Section 3.1 , b) in Section 4 , and c) Section 5 , we hope to address these gaps and encourage the ML community to think about how LLVMs can be augmented with creative problem solving skills through a deeper discussion of Computational Creativity.

To emphasize the applicability of principles from CC for creative problem solving in LLVMs, we discuss the seminal work of Margaret A. Boden from CC literature that introduces three forms of creativity, namely, “ exploratory ”, “ combinational ”, and “ transformational ” Boden ( 1998 ) . Prior work has discussed the extension of Boden’s forms of creativity to creative problem solving in AI Gizzi et al. ( 2022 ) , however, their work does not include recent advances in LLVMs nor how Boden’s principles can be extended to specific approaches for LLVMs.

Ongoing discussions by leading ML experts like Dr. Shane Legg, co-founder of DeepMind, have suggested that “search” could help such models perform creative problem solving, quote, “ … these foundational models are world models of a kind, and to do really creative problem solving, you need to start searching ” Patel ( 2023 ) . There has also been speculation that OpenAI’s Q ∗ superscript 𝑄 Q^{*} italic_Q start_POSTSUPERSCRIPT ∗ end_POSTSUPERSCRIPT search (described as a “significant breakthrough” in popular media) could be targeting a similar approach Wang ( 2023 ); Anna Tong and Hu ( 2023 ) . Interestingly, we note that “search” as described here, can be linked to Boden’s proposed “exploratory” approach (Section 4.1.1 ). However, in Section 4 , we posit that “combinational” and “transformational” modes should be equally emphasized to achieve creative problem solving in LLVMs.

Although we choose to expand on Boden’s work as the focal point to drive our arguments in the main paper, it is not the only theory in CC that is relevant to this discussion. For completeness, we elaborate on additional CC theories and their applicability to creative problem solving in LLVMs in Appx. B .

3 From Task Planning to Creative Problem Solving

Creative problem solving can be broadly described as the process through which agents discover novel ways of accomplishing a task that, prior to the discovery, was unsolvable. Computationally, creative problem solving can be achieved through planning, learning, or hybrid approaches Gizzi et al. ( 2022 ) . Following a review of the different definitions of creative problem solving that have been proposed (Appx. A ), we believe the following most closely connects to existing formalisms in ML.

3.1 Definition of Creative Problem Solving

Gizzi et al. ( 2022 ) define the notion of a concept , as a state (of the environment and/or agent) or action. More generally, the authors denote C X subscript 𝐶 𝑋 C_{X} italic_C start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT as the set of all concepts relating to X 𝑋 X italic_X ( X 𝑋 X italic_X denotes environment states S 𝑆 S italic_S or actions A 𝐴 A italic_A ). Hence, C S subscript 𝐶 𝑆 C_{S} italic_C start_POSTSUBSCRIPT italic_S end_POSTSUBSCRIPT denotes the set of all environmental states, and C A subscript 𝐶 𝐴 C_{A} italic_C start_POSTSUBSCRIPT italic_A end_POSTSUBSCRIPT denotes the set of agent actions. Formally, the authors state their definition as (Page 7, (Gizzi et al., 2022 ) ):

Given an un-achievable goal due to an insufficient conceptual space, CPS refers to the process by which the agent discovers a new conceptual space C X ′ ⊈ C X not-subset-of-nor-equals subscript superscript 𝐶 ′ 𝑋 subscript 𝐶 𝑋 C^{\prime}_{X}\nsubseteq C_{X} italic_C start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT ⊈ italic_C start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT , such that C X ′ = f ⁢ ( C X ) subscript superscript 𝐶 ′ 𝑋 𝑓 subscript 𝐶 𝑋 C^{\prime}_{X}=f(C_{X}) italic_C start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT = italic_f ( italic_C start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT ) is the result of applying some function f 𝑓 f italic_f on the current conceptual space, enabling the agent to solve the previously unsolvable task by using C X ′ subscript superscript 𝐶 ′ 𝑋 C^{\prime}_{X} italic_C start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT .

As a simplified example, let us assume a robot that has a goal G 𝐺 G italic_G of transferring beans from a jar to a cooker: G = 𝐺 absent G= italic_G = { i ⁢ n 𝑖 𝑛 in italic_i italic_n (beans, cooker)}. Here, the initial state is defined as C S = subscript 𝐶 𝑆 absent C_{S}= italic_C start_POSTSUBSCRIPT italic_S end_POSTSUBSCRIPT = { i ⁢ n 𝑖 𝑛 in italic_i italic_n (beans, jar), h ⁢ a ⁢ s ⁢ C ⁢ o ⁢ n ⁢ t ⁢ a ⁢ i ⁢ n ⁢ a ⁢ b ⁢ i ⁢ l ⁢ i ⁢ t ⁢ y ℎ 𝑎 𝑠 𝐶 𝑜 𝑛 𝑡 𝑎 𝑖 𝑛 𝑎 𝑏 𝑖 𝑙 𝑖 𝑡 𝑦 hasContainability italic_h italic_a italic_s italic_C italic_o italic_n italic_t italic_a italic_i italic_n italic_a italic_b italic_i italic_l italic_i italic_t italic_y (spoon)}. Let the actions be defined as C A = subscript 𝐶 𝐴 absent C_{A}= italic_C start_POSTSUBSCRIPT italic_A end_POSTSUBSCRIPT = { s ⁢ c ⁢ o ⁢ o ⁢ p 𝑠 𝑐 𝑜 𝑜 𝑝 scoop italic_s italic_c italic_o italic_o italic_p (beans, X 𝑋 X italic_X , l ⁢ o ⁢ c s 𝑙 𝑜 subscript 𝑐 𝑠 loc_{s} italic_l italic_o italic_c start_POSTSUBSCRIPT italic_s end_POSTSUBSCRIPT , l ⁢ o ⁢ c d 𝑙 𝑜 subscript 𝑐 𝑑 loc_{d} italic_l italic_o italic_c start_POSTSUBSCRIPT italic_d end_POSTSUBSCRIPT )}, where, X 𝑋 X italic_X refers to an object that satisfies h ⁢ a ⁢ s ⁢ C ⁢ o ⁢ n ⁢ t ⁢ a ⁢ i ⁢ n ⁢ a ⁢ b ⁢ i ⁢ l ⁢ i ⁢ t ⁢ y ⁢ ( ⋅ ) ℎ 𝑎 𝑠 𝐶 𝑜 𝑛 𝑡 𝑎 𝑖 𝑛 𝑎 𝑏 𝑖 𝑙 𝑖 𝑡 𝑦 ⋅ hasContainability(\cdot) italic_h italic_a italic_s italic_C italic_o italic_n italic_t italic_a italic_i italic_n italic_a italic_b italic_i italic_l italic_i italic_t italic_y ( ⋅ ) (e.g., spoon), to scoop beans from l ⁢ o ⁢ c s 𝑙 𝑜 subscript 𝑐 𝑠 loc_{s} italic_l italic_o italic_c start_POSTSUBSCRIPT italic_s end_POSTSUBSCRIPT to l ⁢ o ⁢ c d 𝑙 𝑜 subscript 𝑐 𝑑 loc_{d} italic_l italic_o italic_c start_POSTSUBSCRIPT italic_d end_POSTSUBSCRIPT . If the robot has access to a spoon, the robot can use it to scoop the beans from the jar to the cooker. However, what if the robot did not have a spoon, but had a glass instead? By the definition of C S subscript 𝐶 𝑆 C_{S} italic_C start_POSTSUBSCRIPT italic_S end_POSTSUBSCRIPT , the agent is unaware that h ⁢ a ⁢ s ⁢ C ⁢ o ⁢ n ⁢ t ⁢ a ⁢ i ⁢ n ⁢ a ⁢ b ⁢ i ⁢ l ⁢ i ⁢ t ⁢ y ℎ 𝑎 𝑠 𝐶 𝑜 𝑛 𝑡 𝑎 𝑖 𝑛 𝑎 𝑏 𝑖 𝑙 𝑖 𝑡 𝑦 hasContainability italic_h italic_a italic_s italic_C italic_o italic_n italic_t italic_a italic_i italic_n italic_a italic_b italic_i italic_l italic_i italic_t italic_y (glass) is true, making the goal un-achievable. By our definition, creative problem solving is the process by which the agent uses some function f ⁢ ( ⋅ ) 𝑓 ⋅ f(\cdot) italic_f ( ⋅ ) to discover a new conceptual space: f ⁢ ( C S ) = C S ′ = C S ⁢ ∪ 𝑓 subscript 𝐶 𝑆 subscript superscript 𝐶 ′ 𝑆 subscript 𝐶 𝑆 f(C_{S})=C^{\prime}_{S}=C_{S}\mathop{\cup} italic_f ( italic_C start_POSTSUBSCRIPT italic_S end_POSTSUBSCRIPT ) = italic_C start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_S end_POSTSUBSCRIPT = italic_C start_POSTSUBSCRIPT italic_S end_POSTSUBSCRIPT ∪ { h ⁢ a ⁢ s ⁢ C ⁢ o ⁢ n ⁢ t ⁢ a ⁢ i ⁢ n ⁢ a ⁢ b ⁢ i ⁢ l ⁢ i ⁢ t ⁢ y ℎ 𝑎 𝑠 𝐶 𝑜 𝑛 𝑡 𝑎 𝑖 𝑛 𝑎 𝑏 𝑖 𝑙 𝑖 𝑡 𝑦 hasContainability italic_h italic_a italic_s italic_C italic_o italic_n italic_t italic_a italic_i italic_n italic_a italic_b italic_i italic_l italic_i italic_t italic_y  (glass)}. This would allow the agent to solve the previously unsolvable task by using the glass to scoop the beans instead.

Boden’s three forms of creativity denote three plausible functions for f ⁢ ( C X ) 𝑓 subscript 𝐶 𝑋 f(C_{X}) italic_f ( italic_C start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT ) . CPS arises when the agent uses what it knows, to discover something new and the newly discovered knowledge is applied to solve a previously impossible task. We revisit the notion of conceptual spaces in Section 3.

In the remainder of this section, we discuss how typical task planning is achieved with LLVMs. We divide the discussion into three subsections based on the level of task planning abstraction where LLVMs are applied: a) high-level task planning, b) low-level task planning, and c) hybrid task planning. While not exhaustive, our review is meant to offer a general insight into how LLVMs are used for task planning, to identify entry points for introducing creative problem solving capabilities.

3.2 LLVMs for high-level task planning

Approaches for high-level task planning often involve using LLVMs to identify high-level goals for accomplishing a task. Some approaches to task planning with LLMs often take a user input specifying the task, and generate high-level task plans for accomplishing it. These approaches often use LLMs as a form of “knowledge base”, to extract actionable task plans from the models via appropriate prompting Huang et al. ( 2022 ) , further iterating over the generated task plan with repeated calls to the LLM as needed Prasad et al. ( 2023 ) .

In the context of Reinforcement Learning (RL), prior work has focused on using LLMs to suggest high-level goals for an RL agent Du et al. ( 2023 ) . Dubbed as ELLMs (Exploring with LLMs), an RL agent provides its current state to an LLM via a prompt, and receives a goal suggestion from the LLM that is then used to shape the reward and the agent exploration. Further work has extended this approach to incorporate the use of experience memory Zhang et al. ( 2023a ) . Existing approaches have also used LLMs to generate directed acyclic graphs composed of sub-goal states to aid the exploration of an RL agent Shukla et al. ( 2023 ) .

3.3 LLVMs for low-level task planning

Approaches for low-level task planning involve using LLMs to generate low-level code for performing a task. In contrast to high-level planning, where high-level goals and sub-goals are generated, these approaches use LLMs to directly generate low-level execution code via appropriate API calls Liang et al. ( 2023 ) . Other approaches have also investigated the capacity of LLMs to generate task plans via a low-level planning language such as PDDL Silver et al. ( 2023 ) , including iterating over the generated plan descriptions in case of errors Guan et al. ( 2023 ) . In terms of low-level planning using VLMs, prior work has introduced an approach that uses a diffusion model to generate robot trajectories conditioned on language and the current visual state of the robot Chen et al. ( 2023 ) .

3.4 Hybrid high and low-level planning with LLVMs

Hybrid approaches use LLVMs both for high-level goal generation as well as low-level planning. For instance, in Li et al. ( 2023 ) , user inputs are passed as LLM prompts to generate high-level plans. The high-level plans are then converted to low-level plans for robot execution via LLMs specialized for coding. Other approaches have used a high-level LLM planner, a VLM perceiver, and a low-level LLM planner for re-planning with both visual and language inputs Skreta et al. ( 2024 ) .

3.5 Summary

Given this overview, we see that LLVMs both at the high-level and low-level, can be modified to incorporate creative problem solving into task planning. For instance, the high-level task plans generated can encompass a novel substitution for a missing object, whereas the low-level task plan can generate an appropriate trajectory for creatively using the object. While the above approaches could, in principle, be studied within the framework of creative problem solving, that is not usually how the problem is formulated; there is a lack of paradigms for studying creative problem solving beyond just, “do you solve the problem or not?” . Creative problem solving needs a fundamental rethinking of the typical problem formulations and approaches in ML. The next section is aimed at ways in which ML approaches in LLVMs can be reformulated from the perspective of CC.

4 Augmenting LLVM embedding spaces for creative problem solving

In this section, we discuss how principles from CC can be extended to LLVMs for creative problem solving. We begin with Boden’s definition of “conceptual spaces” as “ [conceptual space] is the generative system that underlies the domain and defines a certain range of possibilities: chess moves, or molecular structures, or jazz melodies ” Boden ( 2005 ) , p.18 and “ … in short, any reasonably disciplined way of thinking ” Boden ( 1998 ) , p.214. By this definition, the embedding space of an LLVM describes its conceptual space or “ its way of thinking ”. Some evidence for this also comes from existing work that introduces an approach for enabling LLMs to interpret continuous embedding spaces via natural language. Given an embedding vector representing an interpolation of different concepts, the model is able to interpret a text prompt in the context of the supplied embedding Tennenholtz et al. ( 2023 ) . The embedding thus determines the model’s way of thinking. Hence, a discussion of enabling creative problem solving in LLVMs should target their embedding space. To this end, we explore two questions: a) how can LLVM embedding spaces be augmented to achieve creative problem solving, and b) what information should they be augmented with? Aligning with our original position, we show that CC literature can offer insights into these questions.

4.1 How can LLVM embedding spaces be augmented?

In this section, we draw parallels between Boden’s three forms of creativity and existing approaches in LLVMs. We further elaborate on how the three forms of creativity may enhance the potential of LLVMs to perform creative problem solving. We note that the ML approaches discussed in this section do not specifically perform creative problem solving. However, we discuss how they could potentially be extended to do so, by leveraging references from the CC literature.

4.1.1 Exploratory Creativity

Exploratory approaches involve exploration within the conceptual or equivalently, the embedding space of the model, and most closely relates to “search”. Note that the term “exploration” here differs from its usage in RL, instead referring to exploration through the model’s embedding space . Several existing approaches in the ML literature involve searching the output space of LLMs with the goal of improving the performance of these models. The “tree-of-thought” model generates a “tree” of next possible LLM outputs, and searches through the states via Breadth-first or Depth-first search to reach the desired goal state, often guided by heuristics Yao et al. ( 2023 ) . Numerous other approaches have built upon a similar strategy, such as using Monte-Carlo Tree Search (MCTS) Zhou et al. ( 2023 ); Feng et al. ( 2023 ) , beam search Zhang et al. ( 2023b ) or integrating pruning to remove sub-par candidates Golovneva et al. ( 2023 ) .

Extension of exploratory creativity to LLVMs: An important point to note here is that these approaches involve searching exclusively within the output “solution space” of the LLMs rather than directly operating in the embedding space itself. In contrast to operating in the solution space of the LLM, exploratory approaches directly within the LLMs’ embedding space would not be limited by what the LLM can generate as output – “ Some exploration merely shows us the nature of the relevant conceptual space that we had not explicitly noticed before ” Boden ( 2005 ) , p.18. To effectively reveal the full extent of the conceptual space for creative problem solving, the approach should not be limited by the outputs the LLVM can generate. Rather, the generated (creative) outputs itself should be the result of heuristic or non-heuristic based search within the model’s embedding space. However, to the best of our knowledge current approaches have not focused on LLVMs from this perspective, and have also not applied search to embedding spaces of Vision-LMs. Regardless, exploratory approaches are still limited by the dimensions of the model’s embedding space. “ To overcome a limitation in the conceptual space, one must change it in some way ” Boden ( 2005 ) , p.18 - this leads us to combinational and transformational creativity.

4.1.2 Combinational Creativity

Combinational approaches involve combining two concepts to create something new - “ A novel combination of two familiar ideas is something which did not happen before. ” Boden ( 1998 ) , p.213. We can broadly translate this to a function that takes in multiple concepts within an LLVM’s embedding space to output a novel concept.

One way of extending this definition to LLVMs involves applying cross-attention layers. The attention operation is defined as Vaswani et al. ( 2017 ) :

where, Q 𝑄 Q italic_Q , K 𝐾 K italic_K and V 𝑉 V italic_V denote query, keys and values respectively, and d k subscript 𝑑 𝑘 d_{k} italic_d start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT denotes the dimensionality of the keys. Cross-attention involves passing K 𝐾 K italic_K and V 𝑉 V italic_V from a different model, e.g., in Flamingo Alayrac et al. ( 2022 ) , the keys and values represent visual input (from a separate vision encoder) and queries represent a language input. By applying cross attention in this manner, the embedding space of a model can be extended with capabilities of another model. In Bansal et al. ( 2024 ) the authors show that using cross-attention layers can help augment an anchor LLM with an augmenting LLM’s capabilities to perform a task that the anchor LLM was incapable of achieving before - hinting at some creative possibilities of this method.

Other approaches in LLVMs, while using “combinations” in some way, do not conform to the notion of combinational creativity . This includes, for instance, approaches that perform arithmetic combination of LLM weights to enhance the model performance Matena and Raffel ( 2022 ); Ilharco et al. ( 2022 ) . Or approaches that combine image and text embeddings via concatenation Kim et al. ( 2021 ) or a scaled dot product at the output Radford et al. ( 2021 ) . While these approaches may be useful in imparting multi-modal capabilities, however, they do not lead to combinational creativity since the combination occurs external to the models as opposed to within the model’s embedding space.

Extension of Combinational Creativity to LLVMs: The ML approaches described here involve combining embedding spaces across models. Existing approaches have not looked at combining concepts within the same model’s embedding space. The extension of combinational creativity to LLVMs is much more apparent in the sense of conceptual blending Fauconnier and Turner ( 2003 ) for generation of creative artifacts, e.g., via blending of artistic styles. However, the extension of combinational creativity to creative problem solving is less obvious, and CC literature offers us further insights for making this connection. Typical conceptual blending corresponds to a form of “aesthetic combination”, whereas creative problem solving would benefit from “functional combinations” Chen et al. ( 2018 ) . Functional combination combines the functions (as opposed to aesthetic) of two components, e.g., a coin combined with pliers could function as a makeshift screwdriver. The authors extend this framework to a combination of two nouns with a “base” noun (e.g., “pliers”) and “additive” noun (e.g., “coin”). An interesting possibility stems from this notion: Can a combination of embeddings of the same LLVM, corresponding to “base” and “additive” nouns (perhaps with some prior denoting the task), enable the LLVM to generate creative combinations of objects for solving a task? This question remains unexplored, and points to a potential research direction for LLVMs inspired by CC.

4.1.3 Transformational Creativity

Transformational approaches involve transforming existing conceptual spaces to produce new ones. Transforming conceptual spaces can involve “ altering existing rules ” Boden ( 1998 ) , p.216. One way of transforming a model’s embedding space involves fine-tuning or training Franceschelli and Musolesi ( 2023 ) . However, additional insight into transformational creative problem solving comes from prior work in CC, that describes creative problems as those with a poorly defined structure where a solution is not immediately apparent Olteteanu ( 2014 ) . And in such cases, “… re-representation being the process which transforms an ill-structured problem into a well-structured one with direct inference to a problem solution ” Olteteanu ( 2014 ) , p.1. The notion of “re-representing” or “redefining” the problem can be best captured in the input prompts provided to an LLVM. This most closely connects to prompt engineering and in-context learning (ICL).

Prompt engineering augments LLVMs with task specific hints, called prompts, to adapt the LLVM to new tasks Gu et al. ( 2023 ) . Relatedly, in-context learning is a prompting method that provides the LLVM with instructions for solving a new task without requiring additional training. Prior work has shown that in-context learning and gradient-based optimization are equivalent Von Oswald et al. ( 2023 ) , thus connecting ICL to training or fine-tuning.

Extension of transformational creativity to LLVMs: Task re-representations for creative problem solving, through prompting or ICL, has not been well explored within ML. Prompt engineering and ICL is a challenging task, since model performance depends strongly on the chosen prompts Rubin et al. ( 2021 ) , further compounded by the fact that creative problems are inherently poorly defined Olteteanu ( 2014 ) . However, useful insights can be derived from CC literature. For instance, regarding problems that require creatively re-purposing objects, the Object-replacement-object-composition (OROC) framework Olteţeanu and Falomir ( 2016 ) illustrates re-representations of tasks, that can be translated into prompts. The paper defines three different types of creative tasks involving objects, and their task re-representations as (from Olteţeanu and Falomir ( 2016 ) , p.16):

Replace an unfound object needed for a task with other objects present in the environment: “If I do not have an object X, which I would normally use because of its affordance 1 1 1 Affordance is defined as the relation between an agent, action and object, e.g., bowls have the “contain” affordance for humans. A ⁢ f X 𝐴 subscript 𝑓 𝑋 Af_{X} italic_A italic_f start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT , what other object Y could I use, so that I can get a similar affordance, A ⁢ f X ≈ A ⁢ f Y 𝐴 subscript 𝑓 𝑋 𝐴 subscript 𝑓 𝑌 Af_{X}\approx Af_{Y} italic_A italic_f start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT ≈ italic_A italic_f start_POSTSUBSCRIPT italic_Y end_POSTSUBSCRIPT ? ”

𝐴 subscript 𝑓 𝑌 1 𝐴 subscript 𝑓 𝑌 2 … 𝐴 subscript 𝑓 𝑌 𝑛 Af_{X}\approx Af_{X^{\prime}},Af_{X}\approx Af_{Y1}+Af_{Y2}+...+Af_{Yn} italic_A italic_f start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT ≈ italic_A italic_f start_POSTSUBSCRIPT italic_X start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT end_POSTSUBSCRIPT , italic_A italic_f start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT ≈ italic_A italic_f start_POSTSUBSCRIPT italic_Y 1 end_POSTSUBSCRIPT + italic_A italic_f start_POSTSUBSCRIPT italic_Y 2 end_POSTSUBSCRIPT + … + italic_A italic_f start_POSTSUBSCRIPT italic_Y italic_n end_POSTSUBSCRIPT ? ”

  • subscript 𝑌 1 subscript 𝑌 2 … subscript 𝑌 𝑛 Y_{1};Y_{2};...;Y_{n} italic_Y start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT ; italic_Y start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT ; … ; italic_Y start_POSTSUBSCRIPT italic_n end_POSTSUBSCRIPT which are components of object Y 𝑌 Y italic_Y could I use to obtain an object Y i ′ subscript superscript 𝑌 ′ 𝑖 Y^{\prime}_{i} italic_Y start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT with an equivalent or similar affordance, A ⁢ f X ≈ A ⁢ f Y ′ ⁢ i 𝐴 subscript 𝑓 𝑋 𝐴 subscript 𝑓 superscript 𝑌 ′ 𝑖 Af_{X}\approx Af_{Y^{\prime}i} italic_A italic_f start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT ≈ italic_A italic_f start_POSTSUBSCRIPT italic_Y start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT italic_i end_POSTSUBSCRIPT ? ”

For task re-representation, affordances can refer to object properties that are relevant to the task, e.g., in some cases the shape may be relevant and in other cases, the material Olteţeanu and Falomir ( 2016 ) . Within LLVMs, the affordances A ⁢ f X 𝐴 subscript 𝑓 𝑋 Af_{X} italic_A italic_f start_POSTSUBSCRIPT italic_X end_POSTSUBSCRIPT or A ⁢ f Y 𝐴 subscript 𝑓 𝑌 Af_{Y} italic_A italic_f start_POSTSUBSCRIPT italic_Y end_POSTSUBSCRIPT can be defined via natural language, or other modalities such as images. In the following section, we present preliminary experiments on using LLVMs for object replacement, with prompts that are inspired by the above task re-representations. However, an in-depth application of these re-representations as defined in CC to in-context learning in LLVMs remains unexplored.

4.1.4 Summary

In the previous sections, we drew parallels between Boden’s three forms of creativity and approaches in LLVMs, further emphasizing how principles from CC can potentially help enable creative problem solving skills in these models.

Integration with task planning: Given the three methods, we see that transformational and combinational approaches may be especially aligned with LLVMs for high-level task planning. In contrast, exploratory methods may be suited to low-level planning, e.g., trajectory generation.

Creative problem solving as a combination of the three methods: An effective approach to creative problem solving may require all the three methods described in this section. While papers have explored chaining of LLMs within frameworks (often via prompts) Karpas et al. ( 2022 ); Ling et al. ( 2023 ) , the individual LLMs themselves do not exhibit the characteristics described here. Existing frameworks in CC have shown that achieving creative problem solving would take a combination of all three methods, each of which is triggered in different contexts Olteteanu ( 2014 ) . This presents potential opportunities for ML approaches that develop frameworks using multiple LLVMs, e.g., extending CC frameworks such as “ CreaCogs ” Olteţeanu and Falomir ( 2016 ) can be highly beneficial for productive developments in ML.

Model Acc. % (no creativity)
CLIP-B-32 100.0%
CLIP-B-16 92.0%
CLIP-L-14 98.0%
CLIP-H-14-laion 98.0%
ViLT-B-32 68.0%
LLaVA 98.0%

4.2 What information should LLVM embeddings be augemented with?

In the previous section, we discussed three methods for augmenting LLVM embedding spaces. In this section, we explore the question: “What information should be targeted by the three methods when augmenting the embedding space for creative problem solving?”. In the previous section, we discussed this in the context of OROC. According to the OROC framework Olteţeanu and Falomir ( 2016 ) , information about object affordances could enable models to re-represent the task, such that the solution becomes evident. We propose a small experiment to validate whether the principles of transformational creativity from OROC are useful to LLVMs. We note that creativity can occur in various contexts, e.g., creatively solving a math problem or creatively playing a chess move, each of which would require different information. However, to facilitate the discussion in this paper, we focus our scope on tasks that require innovatively replacing missing objects (OROC Task #1).

Note on embeddings vs. concepts: Our work connects “conceptual spaces” (or “concepts”) as defined in Computational Creativity literature, to “embedding spaces” (or “embeddings”) as defined in typical LM literature. We use “concepts” and “embeddings” interchangeably in this context. We make this connection to note that existing methods in Computational Creativity that operate on conceptual spaces translate to ML algorithms that operate on the LM’s embedding space. In this section, we connect the concept of “affordances” to the “embeddings” of the LLVMs in our experiments. Our goal is to show how the model can be prompted via an approach inspired by transformational creativity, to connect affordances of two seemingly distinct objects, e.g., a bowl and a spoon that appear distinct, but share the containability affordance.

4.2.1 Experiment Setup

We create a simple experiment setup that tests the “object replacement” principle from OROC, where we create test sets composed of images of objects for replacing one of five core objects: “Scoop”, “Hammer”, “Spatula”, “Toothpick”, and “Pliers”. We create two groups of tests: a) a nominal group where the actual object itself is available in each test set and requires no replacement (which serves as a form of baseline), and b) an object replacement group, where the nominal tool is missing and a creative replacement object should be chosen.

For each group, we create test sets with 4 objects each, chosen from a set of RGB images of 16 objects (Appendix Figure 3 ). We create 10 such test sets per core object (total 50 samples per model). Each test set only includes one ground truth object, along with three other random objects that will not suit as an appropriate replacement. In the nominal group, the ground truth is the actual object itself. In the object replacement group, the replacements are chosen based on self-assessment of the authors as (core object → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW replacement): “Scoop” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Bowl”; “Hammer” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Saucepan”; “Spatula” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Knife”; “Toothpick” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Safety pin”; “Pliers” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Scissors”. For each test case, we pass the images in the test set along with a prompt. We record whether the ground truth object image was chosen by the model for the prompt (i.e., assigned highest output probability) 2 2 2 CLIP generates probabilities that given images correspond to a text. ViLT and LLaVA respond with a text, and we evaluate if the model responded “yes” with a high probability for the ground truth. .

The nominal group is subjected to one type of prompt: “ Can this object be used as a ⟨ c o r e _ o b j e c t ⟩ ? \bigl{\langle}core\_object\bigl{\rangle}? ⟨ italic_c italic_o italic_r italic_e _ italic_o italic_b italic_j italic_e italic_c italic_t ⟩ ? ”. In the object replacement group, each test case is subjected to four types of prompts:

Baseline (regular) prompt: Same prompt as used in the nominal cases to obtain a baseline.

Prompt prepended with affordance information: the prompt includes additional information about the desired object affordances specified as object features.

Prompt prepended with task information: the prompt includes additional information about the desired task.

Prompt prepended with task and affordance information: the prompt includes additional information on the task and object affordance.

Case #2 aligns with task re-representations of OROC, and we explore cases #3 and #4 for comparison. We formulate our affordance prompts as brief versions of OROC’s task re-representations. According to Olteţeanu and Falomir ( 2016 ) affordances can be defined using shape features, which we apply to the prompts here. The full set of prompts is shown in Appendix Table 2 . The models that we explore include versions of CLIP Radford et al. ( 2021 ) , LLaVA Liu et al. ( 2024 ) , and ViLT Kim et al. ( 2021 ) obtained from HuggingFace. We use different model sizes ( B ase, L arge, H uge) and patch sizes (14, 16, 32). The open-source code for reproducing our experiment results (including our dataset and test cases) is available at: https://github.com/lnairGT/creative-problem-solving-LLMs . Appendix C includes more details on the experiments.

4.2.2 Results

In Table 1 , we see the performances of the different models in the nominal test group, where the object requires no creative replacement. The models perform > 90 % absent percent 90 >90\% > 90 % in such cases (except for ViLT). In Figure 2 , we see the performances (accuracy shown on a 0.0 − 1.0 0.0 1.0 0.0-1.0 0.0 - 1.0 scale) of the models in the object replacement test cases, where the object requires a creative replacement. For reference, a model that randomly picks an object achieves about 30% overall accuracy. Figure 2 shows average accuracies for the different prompting strategies across random test sets. From Table 1 to Figure 2 (“regular”), the models perform poorly when they need to creatively reason about object replacements, highlighting their limitation. Comparing the “Regular” tab in Figure 2 to “Affordance”, we see a general improvement in model performances, when object affordance information is provided , consistent with description of the OROC framework Olteţeanu and Falomir ( 2016 ) . However, information about the task (Figure 2 , “Task” ) leads to mostly detrimental results. Information about task and affordances (Figure 2 , “Task + Affordance”) does not lead to substantial improvements either, and is also detrimental in certain cases. We note that there is quite a variance in performances across the different models, which may be partially attributed to the original training datasets of the models. These observations warrant further exploration beyond the scope of this paper. Appendix D includes a detailed, class-wise breakdown of the results.

Refer to caption

4.2.3 Summary

While the experiments that we conducted are only preliminary, they offer some validity that the extension of principles in Computational Creativity can help overcome limitations of LLVMs in creative problem solving. The notion of task re-representation via improved prompting warrants further investigation in LLVMs, with regards to how the prompts can be generated automatically based on the creative task.

The models used in our experiments have all been trained jointly in visual and text domains. Multi-modal prompting capabilities may be useful for achieving creative problem solving. It can be quite challenging to describe affordances in words (example of “hammers” in our tests) and they may be better described through other means, e.g., images or depth maps or spectral data for material properties Erickson et al. ( 2020 ) . This would require application of multi-modal LLVMs that can process a variety of data types Girdhar et al. ( 2023 ); Han et al. ( 2023 ) . Computational creativity can offer insights into meaningful representations of these different modalities that would help achieve creative problem solving, e.g., whether object material or shape matters more for one task vs. another Olteţeanu and Falomir ( 2016 ) .

It is also worth noting that the creative problem solving examples in our experiments are human-centric. For instance, robots may not have similar capabilities as humans to manipulate bowls for scooping. In such cases, LLVMs need to account for the affordances as described with respect to the agent , in order to derive creative solutions. However, that adds another level of complexity, yet to be explored, since these models are typically trained on human-centric data.

5 Evaluation of Creativity

An important discussion in the context of creative problem solving is, how can creative problem solving be evaluated? . Prior work has proposed that creativity necessitates both novelty and value Boden ( 1998 ); Runco and Jaeger ( 2012 ) , where the former guarantees that the generated outputs of a creative process are original, and the latter ensures that the generated outputs are useful. In the context of CPS, novelty refers to the discovery of new concepts (as defined in section 3.1 ), whereas value insists that the newly discovered concepts successfully solve the task. Hence, benchmarks for CPS should specifically evaluate how the task was solved (novelty and value) rather than the typical ML evaluation of whether the task was successful or not (value only). Some existing approaches that make this distinction describe problem settings that can be used to measure CPS skills of LLMs through the implicit integration of novelty and value measurements Tian et al. ( 2023 ); Naeini et al. ( 2023 ); Bisk et al. ( 2020 ); Talmor et al. ( 2022 ) . In Tian et al. ( 2023 ) , the authors create a dataset of 1600 real-world problems that necessarily involve creative reasoning abilities. Their proposed benchmark involves identifying novel approaches that can accomplish the given task (value). Similarly, in Naeini et al. ( 2023 ) , the authors introduce the Only-Connect-Wall (OCW) dataset to measure CPS capabilities of LLMs. The authors in Bisk et al. ( 2020 ) explore physical commonsense reasoning that is more generally applicable, beyond object-based creative problems. The authors introduce Physical Interaction: Question Answering, or PIQA consisting of 16,000 QA pairs where each question is paired with two possible common-sense solutions with a ground truth. In Talmor et al. ( 2022 ) , the authors introduce CommonSenseQA 2.0 (CSQA2) dataset consisting of both object-based and non-object based creative problems. The dataset consists of 14,343 questions distributed across 1,868 distinct topics. Currently, to the best of our knowledge, there are no standard benchmarks available to measure CPS skills of VLMs, although our preliminary experiments show one way to measure this using the task of object substitution.

6 Conclusion and Future Work

In this paper, we argued that an effective approach for enabling creative problem solving – currently a key limitation of LLVMs – should derive from Computational Creativity literature. To emphasize this at each juncture, we discussed the specific principles from CC that can be extended to achieve creative problem solving in LLVMs, describing the potential for further research with these insights. It is rare to see special tracks or workshops targeted at Computational Creativity within more prestigious ML conferences. These programs typically focus on creative artifact generation and art (such as the NeurIPS Workshop on Machine Learning for Creativity and Design NeurIPS ( 2022 ) or the recent tutorial at EMNLP on Creative Natural Language Generation Chakrabarty et al. ( 2023 ) ), but do not discuss CPS, thus failing to bridge the gap between CC and ML. We hope to see a deeper integration of the CC communities at such strong ML venues. We hope to encourage the reader to view creative problem solving and ML holistically, through the lens of Computational Creativity.

7 Limitations

Literature outside of Computational Creativity that enables CPS is unexplored: Our paper predominantly focuses on CC literature. This work does not cover literature beyond CC that can potentially inform creative problem solving in LLVMs. Although CC literature broadly encompasses psychology, neuroscience and philosophy, our future work seeks to explore specific literature within these sub-domains and discuss their applicability to creative problem solving and ML.

Lack of an explicit creative problem solving algorithm for LLVMs: Since the scope of our work aligns with a position paper, we have not focused on developing a concrete algorithm for creative problem solving in LLVMs. The prompting strategies explored in our preliminary experiments are manually specified, and our work does not elaborate on how these prompts may be automatically discovered. While our paper seeks to address some of the key gaps that prevent the application of CC literature to ML, there are still several unanswered questions when it comes to the practical implementation of an ML approach: e.g., what is a good representation for concepts that facilitate creative problem solving (symbolic, non-symbolic, or hybrid)? What is a good problem formulation for a given creative problem solving task (planning or learning)? etc. However, these questions are not directly answered within the scope of our work.

8 Ethical Considerations

The authors do not have specific ethical considerations to be highlighted with respect to this work.

  • Alayrac et al. (2022) Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al. 2022. Flamingo: a visual language model for few-shot learning. Advances in Neural Information Processing Systems , 35:23716–23736.
  • Anna Tong and Hu (2023) Jeffrey Dastin Anna Tong and Krystal Hu. 2023. Openai researchers warned board of ai breakthrough ahead of ceo ouster, sources say. https://www.reuters.com/technology/sam-altmans-ouster-openai-was-precipitated-by-letter-board-about-ai-breakthrough-2023-11-22/. [Online; accessed 19-Jan-2024].
  • Atkeson et al. (2018) Christopher G Atkeson, PW Babu Benzun, Nandan Banerjee, Dmitry Berenson, Christoper P Bove, Xiongyi Cui, Mathew DeDonato, Ruixiang Du, Siyuan Feng, Perry Franklin, et al. 2018. What happened at the darpa robotics challenge finals. The DARPA robotics challenge finals: Humanoid robots to the rescue , pages 667–684.
  • Bansal et al. (2024) Rachit Bansal, Bidisha Samanta, Siddharth Dalmia, Nitish Gupta, Shikhar Vashishth, Sriram Ganapathy, Abhishek Bapna, Prateek Jain, and Partha Talukdar. 2024. Llm augmented llms: Expanding capabilities through composition. arXiv preprint arXiv:2401.02412 .
  • BBC (2012) BBC. 2012. Us navy funds ’macgyver’ robot that can create tools. https://www.bbc.com/news/technology-19902954 . [Online; accessed 9-April-2024].
  • Bisk et al. (2020) Yonatan Bisk, Rowan Zellers, Jianfeng Gao, Yejin Choi, et al. 2020. Piqa: Reasoning about physical commonsense in natural language. In Proceedings of the AAAI conference on artificial intelligence , volume 34, pages 7432–7439.
  • Boden (1998) Margaret A. Boden. 1998. Creativity and Artificial Intelligence. Artificial Intelligence , 1-2:347–356.
  • Boden (2005) Margaret A. Boden. 2005. What is creativity? Creativity in human evolution and prehistory .
  • Bubeck et al. (2023) Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al. 2023. Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv preprint arXiv:2303.12712 .
  • Cass (2005) Stephen Cass. 2005. Apollo 13, we have a solution. IEEE Spectrum On-line, 04 , 1.
  • Chakrabarty et al. (2023) Tuhin Chakrabarty, Vishakh Padmakumar, He He, and Nanyun Peng. 2023. Creative natural language generation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts , pages 34–40.
  • Chen et al. (2023) Lili Chen, Shikhar Bahl, and Deepak Pathak. 2023. Playfusion: Skill acquisition via diffusion from language-annotated play. In Conference on Robot Learning , pages 2012–2029. PMLR.
  • Chen et al. (2018) Liuqing Chen, Pan Wang, Feng Shi, Ji Han, Peter Childs, et al. 2018. A computational approach for combinational creativity in design. In DS 92: Proceedings of the DESIGN 2018 15th International Design Conference , pages 1815–1824.
  • Copet et al. (2023) Jade Copet, Felix Kreuk, Itai Gat, Tal Remez, David Kant, Gabriel Synnaeve, Yossi Adi, and Alexandre Défossez. 2023. Simple and controllable music generation. arXiv preprint arXiv:2306.05284 .
  • DeCaro et al. (2011) Marci S DeCaro, Robin D Thomas, Neil B Albert, and Sian L Beilock. 2011. Choking under pressure: multiple routes to skill failure. Journal of experimental psychology: general , 140(3):390.
  • Du et al. (2023) Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, and Jacob Andreas. 2023. Guiding pretraining in reinforcement learning with large language models. arXiv preprint arXiv:2302.06692 .
  • Erickson et al. (2020) Zackory Erickson, Eliot Xing, Bharat Srirangam, Sonia Chernova, and Charles C Kemp. 2020. Multimodal material classification for robots using spectroscopy and high resolution texture imaging. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , pages 10452–10459. IEEE.
  • Fauconnier and Turner (2003) Gilles Fauconnier and Mark Turner. 2003. Conceptual blending, form and meaning. Recherches en communication , 19:57–86.
  • Fei et al. (2022) Nanyi Fei, Zhiwu Lu, Yizhao Gao, Guoxing Yang, Yuqi Huo, Jingyuan Wen, Haoyu Lu, Ruihua Song, Xin Gao, Tao Xiang, et al. 2022. Towards artificial general intelligence via a multimodal foundation model. Nature Communications , 13(1):3094.
  • Feng et al. (2023) Xidong Feng, Ziyu Wan, Muning Wen, Ying Wen, Weinan Zhang, and Jun Wang. 2023. Alphazero-like tree-search can guide large language model decoding and training. arXiv preprint arXiv:2309.17179 .
  • Franceschelli and Musolesi (2023) Giorgio Franceschelli and Mirco Musolesi. 2023. On the creativity of large language models. arXiv preprint arXiv:2304.00008 .
  • Gilhooly (2016) Kenneth J Gilhooly. 2016. Incubation and intuition in creative problem solving. Frontiers in psychology , 7:1076.
  • Girdhar et al. (2023) Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, and Ishan Misra. 2023. Imagebind: One embedding space to bind them all .
  • Gizzi et al. (2022) Evana Gizzi, Lakshmi Nair, Sonia Chernova, and Jivko Sinapov. 2022. Creative problem solving in artificially intelligent agents: A survey and framework. Journal of Artificial Intelligence Research , 75:857–911.
  • Goertzel (2014) Ben Goertzel. 2014. Artificial general intelligence: concept, state of the art, and future prospects. Journal of Artificial General Intelligence , 5(1):1.
  • Golovneva et al. (2023) O. Golovneva, S. O’Brien, R. Pasunuru, T. Wang, L. Zettlemoyer, M. Fazel-Zarandi, and A. Celikyilmaz. 2023. Pathfinder: Guided search over multi-step reasoning paths. arXiv preprint arXiv:2312.05180 .
  • Grudin and Jacques (2019) Jonathan Grudin and Richard Jacques. 2019. Chatbots, humbots, and the quest for artificial general intelligence. In Proceedings of the 2019 CHI conference on human factors in computing systems , pages 1–11.
  • Gu et al. (2023) Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, and Philip Torr. 2023. A systematic survey of prompt engineering on vision-language foundation models. arXiv preprint arXiv:2307.12980 .
  • Guan et al. (2023) Lin Guan, Karthik Valmeekam, Sarath Sreedharan, and Subbarao Kambhampati. 2023. Leveraging pre-trained large language models to construct and utilize world models for model-based task planning. arXiv preprint arXiv:2305.14909 .
  • Guilford (1967) Joy P Guilford. 1967. Creativity: Yesterday, today and tomorrow. The Journal of Creative Behavior , 1(1):3–14.
  • Hammond et al. (2013) Adam Hammond, Julian Brooke, and Graeme Hirst. 2013. A tale of two cultures: Bringing literary analysis and computational linguistics together. In Proceedings of the Workshop on Computational Linguistics for Literature , pages 1–8.
  • Han et al. (2023) Jiaming Han, Kaixiong Gong, Yiyuan Zhang, Jiaqi Wang, Kaipeng Zhang, Dahua Lin, Yu Qiao, Peng Gao, and Xiangyu Yue. 2023. Onellm: One framework to align all modalities with language .
  • Hélie and Sun (2010) Sebastien Hélie and Ron Sun. 2010. Incubation, insight, and creative problem solving: a unified theory and a connectionist model. Psychological review , 117(3):994.
  • Huang et al. (2022) Wenlong Huang, Pieter Abbeel, Deepak Pathak, and Igor Mordatch. 2022. Language models as zero-shot planners: Extracting actionable knowledge for embodied agents. In International Conference on Machine Learning , pages 9118–9147. PMLR.
  • Ilharco et al. (2022) Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Suchin Gururangan, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi. 2022. Editing models with task arithmetic. arXiv preprint arXiv:2212.04089 .
  • Karpas et al. (2022) Ehud Karpas, Omri Abend, Yonatan Belinkov, Barak Lenz, Opher Lieber, Nir Ratner, Yoav Shoham, Hofit Bata, Yoav Levine, Kevin Leyton-Brown, Dor Muhlgay, Noam Rozen, Erez Schwartz, Gal Shachaf, Shai Shalev-Shwartz, Amnon Shashua, and Moshe Tenenholtz. 2022. Mrkl systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning .
  • Kim et al. (2021) Wonjae Kim, Bokyung Son, and Ildoo Kim. 2021. Vilt: Vision-and-language transformer without convolution or region supervision. In International Conference on Machine Learning , pages 5583–5594. PMLR.
  • Lahikainen et al. (2024) Joonas Lahikainen, Nadia M Ady, and Christian Guckelsberger. 2024. Creativity and markov decision processes. arXiv preprint arXiv:2405.14966 .
  • Li et al. (2023) Boyi Li, Philipp Wu, Pieter Abbeel, and Jitendra Malik. 2023. Interactive task planning with language models. arXiv preprint arXiv:2310.10645 .
  • Liang et al. (2023) Jacky Liang, Wenlong Huang, Fei Xia, Peng Xu, Karol Hausman, Brian Ichter, Pete Florence, and Andy Zeng. 2023. Code as policies: Language model programs for embodied control. In 2023 IEEE International Conference on Robotics and Automation (ICRA) , pages 9493–9500. IEEE.
  • Ling et al. (2023) Zhan Ling, Yunhao Fang, Xuanlin Li, Tongzhou Mu, Mingu Lee, Reza Pourreza, Roland Memisevic, and Hao Su. 2023. Unleashing the creative mind: Language model as hierarchical policy for improved exploration on challenging problem solving .
  • Liu et al. (2024) Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2024. Visual instruction tuning. Advances in neural information processing systems , 36.
  • Ma et al. (2023) Yuxi Ma, Chi Zhang, and Song-Chun Zhu. 2023. Brain in a vat: On missing pieces towards artificial general intelligence in large language models. arXiv preprint arXiv:2307.03762 .
  • Matena and Raffel (2022) Michael S Matena and Colin A Raffel. 2022. Merging models with fisher-weighted averaging. Advances in Neural Information Processing Systems , 35:17703–17716.
  • Moor et al. (2023) Michael Moor, Oishi Banerjee, Zahra Shakeri Hossein Abad, Harlan M Krumholz, Jure Leskovec, Eric J Topol, and Pranav Rajpurkar. 2023. Foundation models for generalist medical artificial intelligence. Nature , 616(7956):259–265.
  • Moruzzi (2020) Caterina Moruzzi. 2020. Artificial creativity and general intelligence. Journal of Science and Technology of the Arts .
  • Naeini et al. (2023) Saeid Naeini, Raeid Saqur, Mozhgan Saeidi, John Giorgi, and Babak Taati. 2023. Large language models are fixated by red herrings: Exploring creative problem solving and einstellung effect using the only connect wall dataset. arXiv preprint arXiv:2306.11167 .
  • NeurIPS (2022) NeurIPS. 2022. Workshop on machine learning for creativity and design. https://nips.cc/virtual/2022/workshop/49965. [Online; accessed 19-Jan-2024].
  • Olteteanu (2014) Ana-Maria Olteteanu. 2014. Two general classes in creative problem-solving? an account based on the cognitive processess involved in the problem structure-representation structure relationship. Publications of the Institute of Cognitive Science .
  • Olteţeanu and Falomir (2016) Ana-Maria Olteţeanu and Zoe Falomir. 2016. Object replacement and object composition in a creative cognitive system. towards a computational solver of the alternative uses test. Cognitive Systems Research , 39:15–32.
  • Patel (2023) Dwarkesh Patel. 2023. Llms need search for problem solving - shane legg (deepmind founder). https://www.youtube.com/watch?v=qulfo6-54k0. [Online; accessed 19-Jan-2024].
  • Pennachin and Goertzel (2007) Cassio Pennachin and Ben Goertzel. 2007. Contemporary approaches to artificial general intelligence. In Artificial general intelligence , pages 1–30. Springer.
  • Prasad et al. (2023) Archiki Prasad, Alexander Koller, Mareike Hartmann, Peter Clark, Ashish Sabharwal, Mohit Bansal, and Tushar Khot. 2023. Adapt: As-needed decomposition and planning with language models. arXiv preprint arXiv:2311.05772 .
  • Radford et al. (2021) Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning , pages 8748–8763. PMLR.
  • Rombach et al. (2021) Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2021. High-resolution image synthesis with latent diffusion models. 2022 ieee. In CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages 10674–10685.
  • Rubin et al. (2021) Ohad Rubin, Jonathan Herzig, and Jonathan Berant. 2021. Learning to retrieve prompts for in-context learning. arXiv preprint arXiv:2112.08633 .
  • Runco and Jaeger (2012) Mark A Runco and Garrett J Jaeger. 2012. The standard definition of creativity. Creativity research journal , 24(1):92–96.
  • Sarathy and Scheutz (2018) Vasanth Sarathy and Matthias Scheutz. 2018. Macgyver problems: Ai challenges for testing resourcefulness and creativity. Advances in Cognitive Systems , 6:31–44.
  • Shevlin et al. (2019) Henry Shevlin, Karina Vold, Matthew Crosby, and Marta Halina. 2019. The limits of machine intelligence: Despite progress in machine intelligence, artificial general intelligence is still a major challenge. EMBO reports , 20(10):e49177.
  • Shukla et al. (2023) Yash Shukla, Wenchang Gao, Vasanth Sarathy, Alvaro Velasquez, Robert Wright, and Jivko Sinapov. 2023. Lgts: Dynamic task sampling using llm-generated sub-goals for reinforcement learning agents. arXiv preprint arXiv:2310.09454 .
  • Silver et al. (2023) Tom Silver, Soham Dan, Kavitha Srinivas, Joshua B Tenenbaum, Leslie Pack Kaelbling, and Michael Katz. 2023. Generalized planning in pddl domains with pretrained large language models. arXiv preprint arXiv:2305.11014 .
  • Skreta et al. (2024) Marta Skreta, Zihan Zhou, Jia Lin Yuan, Kourosh Darvish, Alán Aspuru-Guzik, and Animesh Garg. 2024. Replan: Robotic replanning with perception and language models. arXiv preprint arXiv:2401.04157 .
  • Talmor et al. (2022) Alon Talmor, Ori Yoran, Ronan Le Bras, Chandra Bhagavatula, Yoav Goldberg, Yejin Choi, and Jonathan Berant. 2022. Commonsenseqa 2.0: Exposing the limits of ai through gamification. arXiv preprint arXiv:2201.05320 .
  • Tennenholtz et al. (2023) Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, and Craig Boutilier. 2023. Demystifying embedding spaces using large language models. arXiv preprint arXiv:2310.04475 .
  • Tian et al. (2023) Yufei Tian, Abhilasha Ravichander, Lianhui Qin, Ronan Le Bras, Raja Marjieh, Nanyun Peng, Yejin Choi, Thomas L Griffiths, and Faeze Brahman. 2023. Macgyver: Are large language models creative problem solvers? arXiv preprint arXiv:2311.09682 .
  • Turner et al. (2020) MC Turner, LV Duggan, BA Glezerson, and SD Marshall. 2020. Thinking outside the (acrylic) box: a framework for the local use of custom-made medical devices. Anaesthesia .
  • Van Heerden and Bas (2021) Imke Van Heerden and Anil Bas. 2021. Ai as author–bridging the gap between machine learning and literary theory. Journal of Artificial Intelligence Research , 71:175–189.
  • Vaswani et al. (2017) Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems , 30.
  • Ventura (2014) Dan Ventura. 2014. Can a computer be lucky? and other ridiculous questions posed by computational creativity. In Artificial General Intelligence: 7th International Conference, AGI 2014, Quebec City, QC, Canada, August 1-4, 2014. Proceedings 7 , pages 208–217. Springer.
  • Von Oswald et al. (2023) Johannes Von Oswald, Eyvind Niklasson, Ettore Randazzo, João Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, and Max Vladymyrov. 2023. Transformers learn in-context by gradient descent. In International Conference on Machine Learning , pages 35151–35174. PMLR.
  • Wallas (1926) Graham Wallas. 1926. The art of thought . 24. Harcourt, Brace.
  • Wang (2023) Brian Wang. 2023. Openai q* could be based upon a* search without expansions. https://www.nextbigfuture.com/2023/11/openai-q-could-be-based-upon-a-search-without-expansions.html. [Online; accessed 19-Jan-2024].
  • Wiggins (2006) Geraint A Wiggins. 2006. A preliminary framework for description, analysis and comparison of creative systems. Knowledge-based systems , 19(7):449–458.
  • Xi et al. (2023) Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al. 2023. The rise and potential of large language model based agents: A survey. arXiv preprint arXiv:2309.07864 .
  • Yao et al. (2023) Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L Griffiths, Yuan Cao, and Karthik Narasimhan. 2023. Tree of thoughts: Deliberate problem solving with large language models. arXiv preprint arXiv:2305.10601 .
  • Zhang et al. (2023a) Danyang Zhang, Lu Chen, Situo Zhang, Hongshen Xu, Zihan Zhao, and Kai Yu. 2023a. Large language model is semi-parametric reinforcement learning agent. arXiv preprint arXiv:2306.07929 .
  • Zhang et al. (2023b) Shun Zhang, Zhenfang Chen, Yikang Shen, Mingyu Ding, Joshua B Tenenbaum, and Chuang Gan. 2023b. Planning with large language models for code generation. arXiv preprint arXiv:2303.05510 .
  • Zhou et al. (2023) Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, and Yu-Xiong Wang. 2023. Language agent tree search unifies reasoning acting and planning in language models. arXiv preprint arXiv:2310.04406 .

Appendix A Alternate Definitions of Creative Problem Solving

Prior work by Olteţeanu Olteteanu ( 2014 ) defines CPS from an object affordance perspective, where affordances broadly refer to action possibilities for objects, e.g., cups are pour-able and doors are open-able. The authors in Olteteanu ( 2014 ) define creative problems as nominal problem solving tasks that have a poor representational structure, and as “ the ability of a cognitive, natural, or artificial system to use new objects to solve a problem, other than the ones that have been stored in its memory as tools for that specific purpose (if any), or to create those objects by putting together objects or parts of objects the system has access to. Depending on the problem, objects can be either physical or abstract/informational (concepts, problem templates, heuristics or other forms of representations) ”. However, this definition is primarily object-creativity centered, and does not cover a wider range of creative problems.

Follow-up work by Sarathy and Scheutz Sarathy and Scheutz ( 2018 ) , define “ Macgyver-esque ” creativity as a planning task that involves “ generating, executing, and learning strategies for identifying and solving seemingly unsolvable real-world problems ”. They introduce the “ MacGyver Problem ” (MGP) as a planning problem with an unreachable goal state. Through the modification of the agent’s domain knowledge (through domain expansion and domain contraction ), the agent must discover new information and incorporate it into its existing domain knowledge, allowing the agent to accomplish the task. The domain expansion and contraction processes align with the divergent-convergent model of creative problem solving Guilford ( 1967 ) . The definition of an MGP aligns well with the formulation of planning problems in ML, but less with learning or hybrid planning-learning approaches.

Appendix B Alternate theories on creative problem solving and their applications to ML

While there is exhaustive literature regarding theories on general creativity, we focus specifically on creative problem solving, with three well received works: Divergent-Convergent Thinking Guilford ( 1967 ) , Explicit-Implicit Interaction Theory Hélie and Sun ( 2010 ) , and the Creative Systems Framework Wiggins ( 2006 ) . We discuss their applicability to ML in addition to the literature discussed in the main body of this paper. Our goal in this section is to further widen the discussion on integrating CC and ML to achieve creative problem solving in LLVMs, with additional literature.

B.0.1 Divergent-Convergent Thinking

In Guilford ( 1967 ) , the authors discuss the notion of “divergent-convergent” thinking. Divergent thinking or “divergent-production” (DP) abilities involve a more open-ended generation of a variety of ideas, whereas convergent thinking focuses on applying specific ideas to solve the problem.

Applicability to CPS in LLVMs: Prior work by Tian et al. ( 2023 ) have demonstrated the applicability of “divergent-convergent” thinking towards solving Macgyver problems. Similar in spirit to our experiments with VLMs in Section 4.2.1 , the authors prompt LLMs with descriptions of objects to enable the LLMs to reason about solving the task. Their work is, to the best of our knowledge, the only direct example demonstrating the value of CC literature in enabling CPS in LLMs.

B.0.2 Explicit-Implicit Interaction Theory

In Hélie and Sun ( 2010 ) , the authors introduce the Explicit-Implicit Interaction (EII) theory, building upon the seminal work in Wallas ( 1926 ) , that describes four stages of creativity: Preparation, incubation, illumination (i.e., insight), and verification. Preparation refers to the initial stage of searching in many different directions, which may fail to find a solution (i.e., impasse) in case of ill-defined problems (as is the case with CPS). Following an impasse, the incubation phase begins, where attention is not devoted to solving the problem. Over a period of time, illumination is the manifestation of the solution to the problem within the conscious thought (i.e., “Aha” moment). Finally, verification involves using deliberative thinking to assess if the solution indeed solves the problem.

Applicability to CPS in LLVMs: The authors in Hélie and Sun ( 2010 ) incorporate the four stages via a concrete computational method into the CLARION cognitive architecture. Prior work has also introduced a CPS framework for ML approaches inspired by the four stages Gizzi et al. ( 2022 ) . In their work, “preparation” aligns with problem formulation, either task learning or planning. Incubation and illumination aligns with knowledge representation (symbolic, non-symbolic, or hybrid), and knowledge manipulation (functions that manipulate the conceptual space). Lastly, verification aligns with evaluation (via simulation, real-world platforms, or benchmarks). Although these works do not explicitly cover LLVMs and related algorithms, they demonstrate the value of integrating CC literature in ML, and can serve as useful starting points for ML approaches towards creative problem solving in LLVMs.

B.0.3 Creative Systems Framework

In Wiggins ( 2006 ) , the author expands on Boden’s levels further in the context of a framework that formalizes creative systems. The paper defines: a) creative system, b) creative behavior, c) novelty, and d) value. The paper also discusses formalized notion of a universe of possibilities , and conceptual spaces . Crucially, the work describes the characteristics of a creative agent, that can help distinguish modes of failures within a creative system, namely: a) hopeless uninspiration – where there are no valued concepts within the universe; b) conceptual uninspiration – where there are no valued concepts within the conceptual space of the agent; and c) generative uninspiration – where an agent is unable to find a valued concept owing to the specific method (e.g., search) employed.

Applicability to CPS in LLVMs: While the discussion of novelty, value and conceptual spaces in Wiggins ( 2006 ) aligns with our descriptions in Section 4 , the different modes of uninspiration offers potential ways to assess failure modes in LLVMs. This allows agents to distinguish between systems where creative problem solving is not possible (hopeless uninspiration), as compared to systems where the conceptual space or the methodology for searching the conceptual space, may be at fault (conceptual or generative uninspiration). Although this approach has not been expanded in existing literature, it presents a promising direction for an evaluation framework that can distinguish CPS from non-CPS problems.

B.1 A potential link between creative problem solving and general intelligence

Existing literature hints at a potential link between creative problem solving and Artificial General Intelligence (AGI) - systems that are broadly capable of solving almost all tasks that humans can Shevlin et al. ( 2019 ) . For instance, in Moruzzi ( 2020 ) , p.85., the author argues that there exists a strong correlation between creativity and AGI: “ … features that systems need to develop in order to achieve general intelligence are aspects that they need to possess also to earn the attribute creative ”. In Goertzel ( 2014 ) , the author compiles a list of competencies deemed essential for achieving AGI, including creative capacities like “ conceptual invention ” and “ creative constructive play with objects ”. The processes of “insight” or “incubation” often associated with creative problem solving Hélie and Sun ( 2010 ); Gilhooly ( 2016 ) is also considered important for AGI Ventura ( 2014 ) . Taken together, it is likely that any promising vision of AGI would be incomplete without creative problem solving .

Alongside the heavy ongoing discussion of AGI surrounding LLVMs Bubeck et al. ( 2023 ); Fei et al. ( 2022 ); Ma et al. ( 2023 ); Xi et al. ( 2023 ); Moor et al. ( 2023 ); Grudin and Jacques ( 2019 ) , there is often little to no discussion of creative problem solving or Computational Creativity within mainstream ML. As described in Moruzzi ( 2020 ) , p.96, “ The investigation on the nature of creativity and on how it manifests itself not only in human but also in animal and artificial systems should, thus, not be intended as a niche discussion but, rather, as a fundamental research which can lay the foundations for further studies in artificial intelligence and its relation to humans ”. We hope that this work will encourage discussions of creative problem solving and Computational Creativity alongside discussions on AGI.

Appendix C Experiment Settings

Prompt type Prompt
Regular
“can this object be used as a scoop?”
“can this object be used as a hammer?”
“can this object be used as a spatula?”
“can this object be used as a toothpick?”
“can this object be used as pliers?”
“scoops must be concave and hollow. can this object be used as a scoop?”
“hammers must be heavy and have a handle attached to a cylinder at the end.
can this object be used as a hammer?”
“spatulas must have a handle attached to a flat surface at the end.
can this object be used as a spatula?”
“toothpicks must have a pointed tip. can this object be used as a toothpick?”
“pliers must have two-prongs. can this object be used as pliers?”
“scoops can transfer beans from one jar to another jar. can this object be
used as a scoop?”
“hammers can hit a nail into the wall. can this object be used as a hammer?”
“spatulas can spread butter onto a pan. can this object be used as a spatula?”
“toothpicks can pick food caught between the teeth. can this object be used
as a toothpick?”
“pliers can grab a coin. can this object be used as pliers?”
“scoops can transfer beans from one jar to another jar. scoops are concave
and hollow. can this object be used as a scoop?”
“hammers can hit a nail into the wall. hammers have a handle attached to a
cylinder at the end. can this object be used as a hammer?”
“spatulas can spread butter onto a pan. spatulas have a handle attached to a
flat surface at the end. can this object be used as a spatula?”
“toothpicks can pick food caught between the teeth. toothpicks have a
pointed tip. can this object be used as a toothpick?”
“pliers can grab a coin. pliers have two-prongs. can this object be used as
pliers?”

Refer to caption

C.1 Data: Test images

Figure 3 shows the test set of 16 RGB images of objects used for the object substitution task. From the shown image dataset, we create test sets with 4 objects each, chosen from the set of 16 object images. We create 10 such test sets per core object (total 50 samples per model). Each test set only includes one ground truth object, along with three other random objects that will not suit as an appropriate replacement. In the nominal group, the ground truth is the actual object itself. In the object replacement group, the replacements are chosen based on self-assessment of the authors as (core object → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW replacement): “Scoop” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Bowl”; “Hammer” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Saucepan”; “Spatula” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Knife”; “Toothpick” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Safety pin”; “Pliers” → absent → \xrightarrow{} start_ARROW start_OVERACCENT end_OVERACCENT → end_ARROW “Scissors”.

C.2 Model: Checkpoints

For all the models, we use pre-trained HuggingFace checkpoints, with no additional training or fine-tuning. The models are of different architecture sizes and patch sizes: “CLIP-B-32” uses the “openai/clip-vit-base-patch32” which is a base model with a patch size of 32. “CLIP-B-16” uses “openai/clip-vit-base-patch16” – a base model with patch size of 16. “CLIP-L-14” uses “openai/clip-vit-large-patch14” – a large model with patch size of 14. “CLIP-H-14” uses “laion/CLIP-ViT-H-14-laion2B-s32B-b79K” which is a “huge” model, with a patch size of 14. This model is trained with the 2 billion sample English subset of LAION-5B. For LLaVA, we use the “llava-hf/llava-1.5-7b-hf” with 7B parameters, version 1.5. Lastly, “VILT-B-32” uses “dandelin/vilt-b32-finetuned-vqa” trained for visual question answering. However, there is limited data available on HuggingFace regarding the model.

C.3 Prompts used in testing

In this section, we discuss the prompts used in the different testing conditions (see Table 2 ). We explore four classes of prompts for the creative object substitution task: “Regular”, “Affordance”, “Task” and “Task and affordance”. Regular prompts involve a direct prompt as to whether a given object will suffice as a substitute for the missing object. Affordance prompts, adds information about the desired affordances that are essential for replacing the missing object. Task prompts adds additional information on the task to be performed as context for whether a given object can be used as replacement for the missing object. Lastly, task and affordance prompts combine the task and object affordance information within the prompt.

C.4 Testing Procedure

For each test case, we pass the images in the test set along with a prompt belonging to one of the four classes described in Table 2 . We record whether the ground truth object image was chosen by the model for the prompt (i.e., assigned highest output probability). CLIP generates probabilities that given images correspond to a text. ViLT responds with a text, and we evaluate if the model responded “yes” with a high probability for the ground truth.

C.5 Testing Infrastructure

We used NVIDIA-A100 GPUs to run the evaluation. However, the models are not too large and we have tested and confirmed that the code can be executed on CPU only as well.

Appendix D Continued Experiment Results

In this section, we show the class-wise breakdown of the different models for the different prompting strategies (Figures 4 - 7 ). We note that “hammers” present a particularly challenging case for all the models, perhaps due to the fact that correlating affordance of a hammer to a saucepan textually is difficult. In contrast, all models with the augmented prompts typically perform well in the case of creatively replacing “toothpick” with “safety pin” – presumably indicating that specifying the relevant affordance textually in this case provides sufficient information. We repeated each experiment across multiple random seeds and found similar performances, showing that our general findings hold across different random cases. Generally, specifying object affordance information in the prompts leads to improved model performance.

Refer to caption

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Design of diffractive neural networks for solving different classification problems at different wavelengths.

3 examples of problem solving

1. Introduction

2. design of spectral dnns for solving several classification problems, 3. gradient method for designing spectral dnns, 4. design examples of spectral dnns, 4.1. sequential solution of the classification problems, 4.2. parallel solution of the classification problems, 5. discussion and conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

  • Silva, A.; Monticone, F.; Castaldi, G.; Galdi, V.; Alù, A.; Engheta, N. Performing Mathematical Operations with Metamaterials. Science 2014 , 343 , 160–163. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Zhou, Y.; Zheng, H.; Kravchenko, I.I.; Valentine, J. Flat optics for image differentiation. Nat. Photonics 2020 , 14 , 316–323. [ Google Scholar ] [ CrossRef ]
  • Estakhri, N.M.; Edwards, B.; Engheta, N. Inverse-designed metastructures that solve equations. Science 2019 , 363 , 1333–1338. [ Google Scholar ] [ CrossRef ]
  • Kitayama, K.i.; Notomi, M.; Naruse, M.; Inoue, K.; Kawakami, S.; Uchida, A. Novel frontier of photonics for data processing—Photonic accelerator. APL Photonics 2019 , 4 , 090901. [ Google Scholar ] [ CrossRef ]
  • Shen, Y.; Harris, N.C.; Skirlo, S.; Prabhu, M.; Baehr-Jones, T.; Hochberg, M.; Sun, X.; Zhao, S.; Larochelle, H.; Englund, D.; et al. Deep learning with coherent nanophotonic circuits. Nat. Photonics 2017 , 11 , 441–446. [ Google Scholar ] [ CrossRef ]
  • Harris, N.C.; Carolan, J.; Bunandar, D.; Prabhu, M.; Hochberg, M.; Baehr-Jones, T.; Fanto, M.L.; Smith, A.M.; Tison, C.C.; Alsing, P.M.; et al. Linear programmable nanophotonic processors. Optica 2018 , 5 , 1623–1631. [ Google Scholar ] [ CrossRef ]
  • Zhu, H.H.; Zou, J.; Zhang, H.; Shi, Y.Z.; Luo, S.B.; Wang, N.; Cai, H.; Wan, L.X.; Wang, B.; Jiang, X.D.; et al. Space-efficient optical computing with an integrated chip diffractive neural network. Nat. Commun. 2022 , 13 , 1044. [ Google Scholar ] [ CrossRef ]
  • Zhang, H.; Gu, M.; Jiang, X.D.; Thompson, J.; Cai, H.; Paesani, S.; Santagati, R.; Laing, A.; Zhang, Y.; Yung, M.H.; et al. An optical neural chip for implementing complex-valued neural network. Nat. Commun. 2021 , 12 , 457. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Zhang, J.; Wu, B.; Cheng, J.; Dong, J.; Zhang, X. Compact, efficient, and scalable nanobeam core for photonic matrix-vector multiplication. Optica 2024 , 11 , 190–196. [ Google Scholar ] [ CrossRef ]
  • Lin, X.; Rivenson, Y.; Yardimci, N.T.; Veli, M.; Luo, Y.; Jarrahi, M.; Ozcan, A. All-optical machine learning using diffractive deep neural networks. Science 2018 , 361 , 1004–1008. [ Google Scholar ] [ CrossRef ]
  • Yan, T.; Wu, J.; Zhou, T.; Xie, H.; Xu, F.; Fan, J.; Fang, L.; Lin, X.; Dai, Q. Fourier-space Diffractive Deep Neural Network. Phys. Rev. Lett. 2019 , 123 , 023901. [ Google Scholar ] [ CrossRef ]
  • Zhou, T.; Fang, L.; Yan, T.; Wu, J.; Li, Y.; Fan, J.; Wu, H.; Lin, X.; Dai, Q. In situ optical backpropagation training of diffractive optical neural networks. Photon. Res. 2020 , 8 , 940–953. [ Google Scholar ] [ CrossRef ]
  • Zhou, T.; Lin, X.; Wu, J.; Chen, Y.; Xie, H.; Li, Y.; Fan, J.; Wu, H.; Fang, L.; Dai, Q. Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit. Nat. Photonics 2021 , 15 , 367–373. [ Google Scholar ] [ CrossRef ]
  • Chen, H.; Feng, J.; Jiang, M.; Wang, Y.; Lin, J.; Tan, J.; Jin, P. Diffractive Deep Neural Networks at Visible Wavelengths. Engineering 2021 , 7 , 1483–1491. [ Google Scholar ] [ CrossRef ]
  • Ferdman, B.; Saguy, A.; Xiao, D.; Shechtman, Y. Diffractive optical system design by cascaded propagation. Opt. Express 2022 , 30 , 27509–27530. [ Google Scholar ] [ CrossRef ]
  • Zheng, S.; Xu, S.; Fan, D. Orthogonality of diffractive deep neural network. Opt. Lett. 2022 , 47 , 1798–1801. [ Google Scholar ] [ CrossRef ]
  • Zheng, M.; Shi, L.; Zi, J. Optimize performance of a diffractive neural network by controlling the Fresnel number. Photon. Res. 2022 , 10 , 2667–2676. [ Google Scholar ]
  • Wang, T.; Ma, S.Y.; Wright, L.G.; Onodera, T.; Richard, B.C.; McMahon, P.L. An optical neural network using less than 1 photon per multiplication. Nat. Commun. 2022 , 13 , 123. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Soshnikov, D.V.; Doskolovich, L.L.; Motz, G.A.; Byzov, E.V.; Bezus, E.A.; Bykov, D.A.; Mingazov, A.A. Design of cascaded diffractive optical elements for optical beam shaping and image classification using a gradient method. Photonics 2023 , 10 , 766. [ Google Scholar ] [ CrossRef ]
  • Kulce, O.; Mengu, D.; Rivenson, Y.; Ozcan, A. All-optical synthesis of an arbitrary linear transformation using diffractive surfaces. Light. Sci. Appl. 2021 , 10 , 196. [ Google Scholar ] [ CrossRef ]
  • Li, J.; Gan, T.; Bai, B.; Luo, Y.; Jarrahi, M.; Ozcan, A. Massively parallel universal linear transformations using a wavelength-multiplexed diffractive optical network. Adv. Photonics 2023 , 5 , 016003. [ Google Scholar ] [ CrossRef ]
  • Mengu, D.; Tabassum, A.; Jarrahi, M.; Ozcan, A. Snapshot multispectral imaging using a diffractive optical network. Light. Sci. Appl. 2023 , 12 , 86. [ Google Scholar ] [ CrossRef ]
  • Luo, Y.; Mengu, D.; Yardimci, N.T.; Rivenson, Y.; Veli, M.; Jarrahi, M.; Ozcan, A. Design of task-specific optical systems using broadband diffractive neural networks. Light. Sci. Appl. 2019 , 8 , 112. [ Google Scholar ] [ CrossRef ]
  • Zhu, Y.; Chen, Y.; Negro, L.D. Design of ultracompact broadband focusing spectrometers based on diffractive optical networks. Opt. Lett. 2022 , 47 , 6309–6312. [ Google Scholar ] [ CrossRef ]
  • Shi, J.; Chen, Y.; Zhang, X. Broad-spectrum diffractive network via ensemble learning. Opt. Lett. 2022 , 47 , 605–608. [ Google Scholar ] [ CrossRef ]
  • Feng, J.; Chen, H.; Yang, D.; Hao, J.; Lin, J.; Jin, P. Multi-wavelength diffractive neural network with the weighting method. Opt. Express 2023 , 31 , 33113–33122. [ Google Scholar ] [ CrossRef ]
  • Fienup, J.R. Phase retrieval algorithms: A comparison. Appl. Opt. 1982 , 21 , 2758–2769. [ Google Scholar ] [ CrossRef ]
  • Soifer, V.A.; Kotlyar, V.; Doskolovich, L. Iterative Methods for Diffractive Optical Elements Computation ; CRC Press: Boca Raton, FL, USA, 1997. [ Google Scholar ]
  • Ripoll, O.; Kettunen, V.; Herzig, H.P. Review of iterative Fourier-transform algorithms for beam shaping applications. Opt. Eng. 2004 , 43 , 2549–2556. [ Google Scholar ]
  • Latychevskaia, T. Iterative phase retrieval in coherent diffractive imaging: Practical issues. Appl. Opt. 2018 , 57 , 7187–7197. [ Google Scholar ] [ CrossRef ]
  • Deng, X.; Chen, R.T. Design of cascaded diffractive phase elements for three-dimensional multiwavelength optical interconnects. Opt. Lett. 2000 , 25 , 1046–1048. [ Google Scholar ] [ CrossRef ]
  • Gülses, A.A.; Jenkins, B.K. Cascaded diffractive optical elements for improved multiplane image reconstruction. Appl. Opt. 2013 , 52 , 3608–3616. [ Google Scholar ] [ CrossRef ]
  • Wang, H.; Piestun, R. Dynamic 2D implementation of 3D diffractive optics. Optica 2018 , 5 , 1220–1228. [ Google Scholar ] [ CrossRef ]
  • Kingma, D.P.; Ba, J. Adam: A Method for Stochastic Optimization. arXiv 2014 , arXiv:1412.6980. [ Google Scholar ]
  • Shi, J.; Wei, D.; Hu, C.; Chen, M.; Liu, K.; Luo, J.; Zhang, X. Robust light beam diffractive shaping based on a kind of compact all-optical neural network. Opt. Express 2021 , 29 , 7084–7099. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Buske, P.; Völl, A.; Eisebitt, M.; Stollenwerk, J.; Holly, C. Advanced beam shaping for laser materials processing based on diffractive neural networks. Opt. Express 2022 , 30 , 22798–22816. [ Google Scholar ] [ CrossRef ]
  • Doskolovich, L.L.; Mingazov, A.A.; Byzov, E.V.; Skidanov, R.V.; Ganchevskaya, S.V.; Bykov, D.A.; Bezus, E.A.; Podlipnov, V.V.; Porfirev, A.P.; Kazanskiy, N.L. Hybrid design of diffractive optical elements for optical beam shaping. Opt. Express 2021 , 29 , 31875–31890. [ Google Scholar ] [ CrossRef ]
  • Doskolovich, L.L.; Skidanov, R.V.; Bezus, E.A.; Ganchevskaya, S.V.; Bykov, D.A.; Kazanskiy, N.L. Design of diffractive lenses operating at several wavelengths. Opt. Express 2020 , 28 , 11705–11720. [ Google Scholar ] [ CrossRef ]
  • Schmidt, J.D. Numerical Simulation of Optical Wave Propagation with Examples in MATLAB ; SPIE: Bellingham, WA, USA, 2010. [ Google Scholar ]
  • Cubillos, M.; Jimenez, E. Numerical simulation of optical propagation using sinc approximation. J. Opt. Soc. Am. A 2022 , 39 , 1403–1413. [ Google Scholar ] [ CrossRef ]

Click here to enlarge figure

Number of DOEsClassification ProblemWavelength (nm)Sequential RegimeParallel Regime
Overall Accuracy (%)Minimum ContrastOverall Accuracy (%)Minimum Contrast
One : MNIST45796.410.1796.250.18
: FMNIST53284.110.1083.710.11
: EMNIST63390.870.1390.560.14
Two : MNIST45797.860.1697.380.19
: FMNIST53286.930.1187.960.11
: EMNIST63393.070.1292.930.16
Three : MNIST45797.890.2097.410.21
: FMNIST53289.750.1189.100.13
: EMNIST63393.220.1992.950.17
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Share and Cite

Motz, G.A.; Doskolovich, L.L.; Soshnikov, D.V.; Byzov, E.V.; Bezus, E.A.; Golovastikov, N.V.; Bykov, D.A. Design of Diffractive Neural Networks for Solving Different Classification Problems at Different Wavelengths. Photonics 2024 , 11 , 780. https://doi.org/10.3390/photonics11080780

Motz GA, Doskolovich LL, Soshnikov DV, Byzov EV, Bezus EA, Golovastikov NV, Bykov DA. Design of Diffractive Neural Networks for Solving Different Classification Problems at Different Wavelengths. Photonics . 2024; 11(8):780. https://doi.org/10.3390/photonics11080780

Motz, Georgy A., Leonid L. Doskolovich, Daniil V. Soshnikov, Egor V. Byzov, Evgeni A. Bezus, Nikita V. Golovastikov, and Dmitry A. Bykov. 2024. "Design of Diffractive Neural Networks for Solving Different Classification Problems at Different Wavelengths" Photonics 11, no. 8: 780. https://doi.org/10.3390/photonics11080780

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    Related: 3 Problem-Solving Activities for Team Building Problem-solving skills examples To solve a problem effectively, you will likely use a few different skills. Here are a few examples of skills you may use when solving a problem: Research Researching is an essential skill related to problem-solving.

  23. Top 20 Problem Solving Interview Questions (Example Answers Included)

    Top 3 Problem-Solving-Based Interview Questions. Alright, here is what you've been waiting for: the problem-solving questions and sample answers. ... It lets you choose your own problem-solving examples to highlight, putting you in complete control. When you choose an example, go with one that is relevant to what you'll face in the role ...

  24. 5.6: Recognizing Patterns

    Problem-Solving Skills: Generalized rules serve as tools for problem-solving, enabling students to approach new problems with confidence. Critical Thinking: The process encourages critical thinking as students analyze patterns, make connections, and apply their understanding to different situations.

  25. 65 Problem-Solving Items To Help You Feel Accomplished

    65 Problem-Solving Products That'll Help You Feel Genuinely Accomplished. Small improvements that make a big difference in everyday life. ... Get a three-pack from Amazon for $12.99. 2.

  26. Creative Problem Solving in Large Language and Vision Models

    Creative problem solving as a combination of the three methods: An effective approach to creative problem solving may require all the three methods described in this section. ... It is also worth noting that the creative problem solving examples in our experiments are human-centric. For instance, robots may not have similar capabilities as ...

  27. Design of Diffractive Neural Networks for Solving Different ...

    For this DOE (not presented for brevity), the overall accuracy and minimum contrast amount to 92.69% and 0.12 (problem P 1), 81.96% and 0.07 (problem P 2), and 84.9% and 0.10 (problem P 3). One can see that the single DOE solving three classification problems at the same wavelength exhibits inferior performance compared to the spectral DOE.