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Creative Problem Solving

Finding innovative solutions to challenges.

By the Mind Tools Content Team

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

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

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

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

About Creative Problem Solving

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

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

Why Use Creative Problem Solving?

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

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

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

Core Principles of Creative Problem Solving

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

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

How to Use the Tool

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

Figure 1 – CPS Learner's Model

Explore the Vision

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

Gather Data

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

Formulate Questions

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

Explore Ideas

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

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

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

Formulate Solutions

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

4. Implement

Formulate a plan.

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

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

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

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

Creative Problem Solving (CPS) Infographic

See our infographic on Creative Problem Solving .

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

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

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

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

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

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

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

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

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What Is Creative Problem-Solving & Why Is It Important?

• 01 Feb 2022

One of the biggest hindrances to innovation is complacency—it can be more comfortable to do what you know than venture into the unknown. Business leaders can overcome this barrier by mobilizing creative team members and providing space to innovate.

There are several tools you can use to encourage creativity in the workplace. Creative problem-solving is one of them, which facilitates the development of innovative solutions to difficult problems.

Here’s an overview of creative problem-solving and why it’s important in business.

Access your free e-book today.

What Is Creative Problem-Solving?

Research is necessary when solving a problem. But there are situations where a problem’s specific cause is difficult to pinpoint. This can occur when there’s not enough time to narrow down the problem’s source or there are differing opinions about its root cause.

In such cases, you can use creative problem-solving , which allows you to explore potential solutions regardless of whether a problem has been defined.

Creative problem-solving is less structured than other innovation processes and encourages exploring open-ended solutions. It also focuses on developing new perspectives and fostering creativity in the workplace . Its benefits include:

• Finding creative solutions to complex problems : User research can insufficiently illustrate a situation’s complexity. While other innovation processes rely on this information, creative problem-solving can yield solutions without it.
• Adapting to change : Business is constantly changing, and business leaders need to adapt. Creative problem-solving helps overcome unforeseen challenges and find solutions to unconventional problems.
• Fueling innovation and growth : In addition to solutions, creative problem-solving can spark innovative ideas that drive company growth. These ideas can lead to new product lines, services, or a modified operations structure that improves efficiency.

Creative problem-solving is traditionally based on the following key principles :

1. Balance Divergent and Convergent Thinking

Creative problem-solving uses two primary tools to find solutions: divergence and convergence. Divergence generates ideas in response to a problem, while convergence narrows them down to a shortlist. It balances these two practices and turns ideas into concrete solutions.

2. Reframe Problems as Questions

By framing problems as questions, you shift from focusing on obstacles to solutions. This provides the freedom to brainstorm potential ideas.

3. Defer Judgment of Ideas

When brainstorming, it can be natural to reject or accept ideas right away. Yet, immediate judgments interfere with the idea generation process. Even ideas that seem implausible can turn into outstanding innovations upon further exploration and development.

4. Focus on "Yes, And" Instead of "No, But"

Using negative words like "no" discourages creative thinking. Instead, use positive language to build and maintain an environment that fosters the development of creative and innovative ideas.

Creative Problem-Solving and Design Thinking

Whereas creative problem-solving facilitates developing innovative ideas through a less structured workflow, design thinking takes a far more organized approach.

Design thinking is a human-centered, solutions-based process that fosters the ideation and development of solutions. In the online course Design Thinking and Innovation , Harvard Business School Dean Srikant Datar leverages a four-phase framework to explain design thinking.

The four stages are:

• Clarify: The clarification stage allows you to empathize with the user and identify problems. Observations and insights are informed by thorough research. Findings are then reframed as problem statements or questions.
• Ideate: Ideation is the process of coming up with innovative ideas. The divergence of ideas involved with creative problem-solving is a major focus.
• Develop: In the development stage, ideas evolve into experiments and tests. Ideas converge and are explored through prototyping and open critique.
• Implement: Implementation involves continuing to test and experiment to refine the solution and encourage its adoption.

Creative problem-solving primarily operates in the ideate phase of design thinking but can be applied to others. This is because design thinking is an iterative process that moves between the stages as ideas are generated and pursued. This is normal and encouraged, as innovation requires exploring multiple ideas.

Creative Problem-Solving Tools

While there are many useful tools in the creative problem-solving process, here are three you should know:

Creating a Problem Story

One way to innovate is by creating a story about a problem to understand how it affects users and what solutions best fit their needs. Here are the steps you need to take to use this tool properly.

1. Identify a UDP

Create a problem story to identify the undesired phenomena (UDP). For example, consider a company that produces printers that overheat. In this case, the UDP is "our printers overheat."

2. Move Forward in Time

To move forward in time, ask: “Why is this a problem?” For example, minor damage could be one result of the machines overheating. In more extreme cases, printers may catch fire. Don't be afraid to create multiple problem stories if you think of more than one UDP.

3. Move Backward in Time

To move backward in time, ask: “What caused this UDP?” If you can't identify the root problem, think about what typically causes the UDP to occur. For the overheating printers, overuse could be a cause.

Following the three-step framework above helps illustrate a clear problem story:

• The printer is overused.
• The printer overheats.
• The printer breaks down.

You can extend the problem story in either direction if you think of additional cause-and-effect relationships.

4. Break the Chains

By this point, you’ll have multiple UDP storylines. Take two that are similar and focus on breaking the chains connecting them. This can be accomplished through inversion or neutralization.

• Inversion: Inversion changes the relationship between two UDPs so the cause is the same but the effect is the opposite. For example, if the UDP is "the more X happens, the more likely Y is to happen," inversion changes the equation to "the more X happens, the less likely Y is to happen." Using the printer example, inversion would consider: "What if the more a printer is used, the less likely it’s going to overheat?" Innovation requires an open mind. Just because a solution initially seems unlikely doesn't mean it can't be pursued further or spark additional ideas.
• Neutralization: Neutralization completely eliminates the cause-and-effect relationship between X and Y. This changes the above equation to "the more or less X happens has no effect on Y." In the case of the printers, neutralization would rephrase the relationship to "the more or less a printer is used has no effect on whether it overheats."

Even if creating a problem story doesn't provide a solution, it can offer useful context to users’ problems and additional ideas to be explored. Given that divergence is one of the fundamental practices of creative problem-solving, it’s a good idea to incorporate it into each tool you use.

Brainstorming

Brainstorming is a tool that can be highly effective when guided by the iterative qualities of the design thinking process. It involves openly discussing and debating ideas and topics in a group setting. This facilitates idea generation and exploration as different team members consider the same concept from multiple perspectives.

Hosting brainstorming sessions can result in problems, such as groupthink or social loafing. To combat this, leverage a three-step brainstorming method involving divergence and convergence :

• Have each group member come up with as many ideas as possible and write them down to ensure the brainstorming session is productive.
• Continue the divergence of ideas by collectively sharing and exploring each idea as a group. The goal is to create a setting where new ideas are inspired by open discussion.
• Begin the convergence of ideas by narrowing them down to a few explorable options. There’s no "right number of ideas." Don't be afraid to consider exploring all of them, as long as you have the resources to do so.

Alternate Worlds

The alternate worlds tool is an empathetic approach to creative problem-solving. It encourages you to consider how someone in another world would approach your situation.

For example, if you’re concerned that the printers you produce overheat and catch fire, consider how a different industry would approach the problem. How would an automotive expert solve it? How would a firefighter?

Be creative as you consider and research alternate worlds. The purpose is not to nail down a solution right away but to continue the ideation process through diverging and exploring ideas.

Continue Developing Your Skills

Whether you’re an entrepreneur, marketer, or business leader, learning the ropes of design thinking can be an effective way to build your skills and foster creativity and innovation in any setting.

If you're ready to develop your design thinking and creative problem-solving skills, explore Design Thinking and Innovation , one of our online entrepreneurship and innovation courses. If you aren't sure which course is the right fit, download our free course flowchart to determine which best aligns with your goals.

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Creativity is a crucial skill in today's changing world. Businesses, governments, and the academic community all recognize the value of creative thinking and the need for innovators who can take a new, fresh, and multilayered look at solving complex problems.

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Why Buffalo State?

It all started here.

The Center for Applied Imagination, and its academic unit the Creativity and Change Leadership Department, has researched and taught creativity, creative problem-solving, and change leadership for more than half a century. We are the pioneering academic program in the field of applied-creativity education. Our roots go back to Alex Osborn, the originator of brainstorming and the Creative Problem-Solving Process. It all started here in Buffalo and we are proud to carry his vision into the twenty-first century and beyond.

"Nothing could give me more satisfaction than to teach people how to make greater use of their most priceless possession—their creative imagination."

The Art of Creative Problem Solving

What is creative problem-solving?

Table of Contents

An introduction to creative problem-solving.

Creative problem-solving is an essential skill that goes beyond basic brainstorming . It entails a holistic approach to challenges, melding logical processes with imaginative techniques to conceive innovative solutions. As our world becomes increasingly complex and interconnected, the ability to think creatively and solve problems with fresh perspectives becomes invaluable for individuals, businesses, and communities alike.

Importance of divergent and convergent thinking

At the heart of creative problem-solving lies the balance between divergent and convergent thinking. Divergent thinking encourages free-flowing, unrestricted ideation, leading to a plethora of potential solutions. Convergent thinking, on the other hand, is about narrowing down those options to find the most viable solution. This dual approach ensures both breadth and depth in the problem-solving process.

Emphasis on collaboration and diverse perspectives

No single perspective has a monopoly on insight. Collaborating with individuals from different backgrounds, experiences, and areas of expertise offers a richer tapestry of ideas. Embracing diverse perspectives not only broadens the pool of solutions but also ensures more holistic and well-rounded outcomes.

Nurturing a risk-taking and experimental mindset

The fear of failure can be the most significant barrier to any undertaking. It's essential to foster an environment where risk-taking and experimentation are celebrated. This involves viewing failures not as setbacks but as invaluable learning experiences that pave the way for eventual success.

The role of intuition and lateral thinking

Sometimes, the path to a solution is not linear. Lateral thinking and intuition allow for making connections between seemingly unrelated elements. These 'eureka' moments often lead to breakthrough solutions that conventional methods might overlook.

Stages of the creative problem-solving process

The creative problem-solving process is typically broken down into several stages. Each stage plays a crucial role in understanding, addressing, and resolving challenges in innovative ways.

Clarifying: Understanding the real problem or challenge

Before diving into solutions, one must first understand the problem at its core. This involves asking probing questions, gathering data, and viewing the challenge from various angles. A clear comprehension of the problem ensures that effort and resources are channeled correctly.

Ideating: Generating diverse and multiple solutions

Once the problem is clarified, the focus shifts to generating as many solutions as possible. This stage champions quantity over quality, as the aim is to explore the breadth of possibilities without immediately passing judgment.

Developing: Refining and honing promising solutions

With a list of potential solutions in hand, it's time to refine and develop the most promising ones. This involves evaluating each idea's feasibility, potential impact, and any associated risks, then enhancing or combining solutions to maximize effectiveness.

Implementing: Acting on the best solutions

Once a solution has been honed, it's time to put it into action. This involves planning, allocating resources, and monitoring the results to ensure the solution is effectively addressing the problem.

Techniques for creative problem-solving

Solving complex problems in a fresh way can be a daunting task to start on. Here are a few techniques that can help kickstart the process:

Brainstorming

Brainstorming is a widely-used technique that involves generating as many ideas as possible within a set timeframe. Variants like brainwriting (where ideas are written down rather than spoken) and reverse brainstorming (thinking of ways to cause the problem) can offer fresh perspectives and ensure broader participation.

Mind mapping

Mind mapping is a visual tool that helps structure information, making connections between disparate pieces of data. It is particularly useful in organizing thoughts, visualizing relationships, and ensuring a comprehensive approach to a problem.

SCAMPER technique

SCAMPER stands for Substitute, Combine, Adapt, Modify, Put to another use, Eliminate, and Reverse. This technique prompts individuals to look at existing products, services, or processes in new ways, leading to innovative solutions.

Benefits of creative problem-solving

Creative problem-solving offers numerous benefits, both at the individual and organizational levels. Some of the most prominent advantages include:

Finding novel solutions to old problems

Traditional problems that have resisted conventional solutions often succumb to creative approaches. By looking at challenges from fresh angles and blending different techniques, we can unlock novel solutions previously deemed impossible.

Enhanced adaptability in changing environments

In our rapidly evolving world, the ability to adapt is critical. Creative problem-solving equips individuals and organizations with the agility to pivot and adapt to changing circumstances, ensuring resilience and longevity.

Building collaborative and innovative teams

Teams that embrace creative problem-solving tend to be more collaborative and innovative. They value diversity of thought, are open to experimentation, and are more likely to challenge the status quo, leading to groundbreaking results.

Fostering a culture of continuous learning and improvement

Creative problem-solving is not just about finding solutions; it's also about continuous learning and improvement. By encouraging an environment of curiosity and exploration, organizations can ensure that they are always at the cutting edge, ready to tackle future challenges head-on.

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Creative problem solving (cps) overview.

• Proven. CPS has been used for more than 50 years by organizations throughout the world and is supported by research, with hundreds of published studies on its effectiveness and impact.
• Portable. CPS links your natural creativity and problem-solving approaches. It is an easy-to-learn process that can be readily applied by individuals and groups of many ages, in many organizations, settings, and cultures.
• Powerful. CPS can be integrated with many organizational activities, providing new or additional tools for making a real difference. It can stimulate important and lasting changes in your life and work.
• Practical. CPS can be used for dealing with everyday problems as well as long-term challenges and opportunities.
• Positive. CPS helps you to unleash your creative talent and to focus your thinking constructively. When applied by groups, CPS promotes teamwork, collaboration, and constructive diversity when dealing with complex opportunities and challenges.

Children, adolescents, and adults can learn and apply CPS, working independently or as part of a group or team.

Free Resources:

Click here to find a number of free resources that will explain CPS, to obtain articles that deal with both research and practice, and to obtain an extensive bibliography to give you direction for future reading and study.

Online Resources:

Click here for advanced online resources in PDF format to support your efforts to learn, apply, and teach CPS. These resources are available at a reasonable cost for immediate download. The cost of each one includes permission to duplicate the file for up to three other individuals at no additional charge.

Distance Learning Resources:

Click here for information about our extensive (newly revised and updated) distance learning modules on CPS.

Print Resources:

We also have print publications about problem-solving style that you can purchase.  Click here to view those publications.

Workshops, Training, Consulting Services:

Our CPS programs and services are custom-tailored to meet your needs and interests. We will confer with you, create a complete proposal to meet your unique needs, and work closely with you to carry out our collaborative plan. Click here for more.

We believe that all people have strengths and talents that are important to recognize, develop, and use throughout life.  Read more.

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Leadership Team

Our work builds on more than five decades of research, development, and practical experience in organizations. Learn more about our team .

Contact Information

Center for Creative Learning, LLC 2015 Grant Place Melbourne, Florida, 32901 USA Email: [email protected]

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• 2024 Keynote: Dr. Kiki Ramsey
• Registration
• CPSI Housing and Hotels
• Bringing Teams to CPSI
• Schedule At A Glance
• Core Programs
• Immersion Sessions
• Breakout Workshops
• CPS Level 1: Foundations of Creative Problem Solving
• CPS Level 2: Creative Problem Solving Tools
• CPS Level 3: Creative Problem Solving Facilitation Techniques
• CPS Level 4: Creative Problem Solving Instructor Training
• Sponsors/Partners
• What’s Included
• Creative Education Foundation

CPSI is a project of the Creative Education Foundation, the first authority on Creative Problem Solving training and education. Learn more about CEF

The Creative Education Foundation — the creators of “brainstorming” and original experts in creative problem solving — presents the annual Creative Problem Solving Institute (CPSI) Conference . We explore themes including innovation, entrepreneurship, change leadership, applied imagination, deliberate creativity, design thinking and more.

Our attendees come from all professions, including entrepreneurs, consultants, C-suites, educators and researchers. WHAT BONDS US? We are change makers, big thinkers, instigators and architects of innovation out to make a difference in our own worlds (at work and at home) and the world at large.

For First-Time Attendees

You’ll learn practical skills and tools to help you access your creativity and solve problems more effectively, both at work and at home.

For Returning Attendees

We’re live and in person again this year! The conference provides enhanced networking and deep-dives on our industry’s most pressing issues.

For Everyone

We guarantee you a refreshed sense of purpose, enlightened perspectives, a community of like-minded individuals, and the freedom to explore new ideas.

CPSI PRESENTED BY:

Don’t take our word for it!

Cpsi is a wonderful combination of expert knowledge and evocative exploration filled with extremely captivating and inspiring speakers..

— Mallori DeSalle, Faculty, Indiana University School of Public Health

The virtual conference came as a blessing since it allowed me to “taste” a ton of content. I’m walking away with ideas that I can apply to my practice and an introspective experience that will help with my self growth.

— Pascal Patenaude, President & Owner, Patenaude Research & Communications

This comprehensive conference addressees the whole person, from mindfulness to creative wellness to leadership and more. EVERYONE can benefit — personally and professionally — from developing creative problem solving skills.

— Kristen Lorenz, Director, Training & Culinary Innovation

Thank you to sponsors and partners for helping ignite creativity and innovation.

CPSI 2023 SPONSORS:

CPSI 2023 PARTNERS:

CPSI 2023 Photos by Onion Studio

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Connect with The CPSI Conference on Facebook, Twitter, LinkedIn, and Instagram.

• CPS Training
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Site Sponsor

Site author.

Paul Reali, MS, MBA OmniSkills Founder & Principal 336.926.8833 * E-mail Paul

PLEASE READ: Permissions to Use Site Content

We encourage you to use the content you find on this site, in accordance with the Creative Commons license specified here, and on each page:

Click the image above for a description of these terms. For additional permissions (e.g., to license the work for commercial use), e-mail us .

Read the Books

The author of this site, Paul Reali, has written two books on Creative Problem Solving. Click a cover to learn more, read an excerpt, or purchase a copy.

CREATIVE PROBLEM SOLVING

This site is for practitioners, new and experienced, of the Creative Problem Solving (CPS) process and tools.

WHAT IS CREATIVE PROBLEM SOLVING?

CPS is a form of deliberate creativity: a structured process for solving problems or finding opportunities, used when you want to go beyond conventional thinking and arrive at creative (novel and useful) solutions.

WHO ARE OSBORN AND PARNES?

In the 1950s, advertising executive Alex Osborn studied creative people to see how they came up with ideas and creative solutions. He called the process he observed “creative problem solving,” and documented it in his seminal book, Applied Imagination .

Osborn’s work soon caught the attention of a college professor who wanted to study and extend the work. Sidney Parnes , Ruth Noller, and their colleagues provided the academic scrutiny that confirmed that CPS works, that it can be taught, and that people can learn to improve the way they think and solve problems.

There are many processes that use the term "creative problem solving" that are not based on the work of Osborn and Parnes. Generally, when the name is written with capital letters ("Creative Problem Solving") or abbreviated "CPS," the work is based on the Osborn-Parnes model.

WHO OWNS CPS?

Unlike proprietary methodologies, no one owns CPS. Osborn put CPS into the public domain so that people could use it. He did not feel as if he owned it; everyone owned it, and anyone should be able to use it.

More than 60 years later, CPS is known and used worldwide, by hundreds of companies and professional practitioners, and thousands of individuals. Expansion and research continues. CPS is the cornerstone of the Osborn-founded Creative Education Foundation (CEF), and CEF’s annual conference, the Creative Problem Solving Institute; and CPS is at the core of the M.S. in Creativity from the International Center for Studies in Creativity at Buffalo State College.

Because no one owns CPS – it is a kind of open-source project – it has been researched and refined, extended and enhanced, for more than 60 years. The beneficiaries? Any of us who choose to use CPS today.

A WORD ABOUT TERMINOLOGY

A side effect of the continuing study and development of CPS is that the terminology - what the stages are called, primarily - can change from one model to another. These changes tend to be author/practitioner preference, and are not material changes. This site uses the terminology developed by Paul Reali of OmniSkills, with stages that are consistent with the latest thinking on CPS. (For more information, see the column to the right.)

BUT MORE IMPORTANTLY, IS IT A PROCESS OR NOT?

The word "process" implies, perhaps, that CPS is performed step by step. In actual practice, it's more organic. Yes, there are times when one might step through a fuzzy situation all the way (using the OmniSkills terminology) from "Imagine the Future" to "Plan for Action." More likely, though, you will "enter the process" wherever you need to be based on where you are in your problem-solving situation.

For example, if you have a clearly-articulated vision, you might begin with Finding the Question. Or, if you already have the question (that is, a clearly defined problem), you might begin with Generating Ideas. Generally, there are conditions that should be satisfied before you attempt any stage (for example, it's not all that sensible to generate ideas for a problem you can't clarify), but you are never required to do anything except whatever you need.

READER PLEASE NOTE: this is a work in progress...

We're continuously adding to this site, so please come on back, and let us know if there's anything you need or would like to see here.

CPS Process Stages: Multiple Approcahes, One Process

The Osborn-Parnes Creative Problem Solving process, once it reached maturity, looked like this:

Objective Finding Fact Finding Data Finding Problem Finding Solution Finding Acceptance Finding

Simplex (Basadur, 1994) identifies eight steps, numbered here because one is required to do all the steps, in order, every time (a point of disagreement with many other CPS practitioners and models):

1. Problem finding 2. Fact finding 3. Problem definition 4. Idea finding 5. Evaluating and selecting 6. Action planning 7. Gaining acceptance 8. Taking action

A plain-language version (Miller, Vehar, & Firestein, 2001) expressed the stages like this:

Identify the Goal, Wish     or Challenge Gather Data Clarify the Problem Generate Ideas Select & Strengthen Solutions Plan for Action

CPS: the Thinking Skills Model (Puccio, Murdock, & Mance, 2005) is a multi-faceted rework of the model. It adds a meta-step (the first on the list) which includes management of the process, and incorporates data gathering. It identifies these process steps:

Assessing the Situation Exploring the Vision Formulating Challenges Exploring Ideas Formulating Solutions Exploring Acceptance Formulating a Plan

The Productive Thinking Model (Hurson, 2008), notably, adds setting criteria as an explicit step:

What’s going on? What’s success? What’s the question? Generate answers Forge the solution Align resources

CPS: Competencies Model (Reali, 2009; the model described on this site) is based most closely on CPS: Thinking Skills Model. It looks like this:

Facilitate Imagine the Future Find the Questions Generate Ideas Craft Solutions Explore Acceptance Plan for Action

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Creative Thinking for Complex Problem Solving

The challenges businesses face today are increasingly complex and systemic, often resisting obvious and definitive solutions. This complexity is frequently met with oversimplification, over-analysis, and quick fixes. But complex problem solving requires unconventional thinking to make unexpected connections—connections that others might not see. You can create these connections by bringing play and rigor into your problem-solving process. The most effective problem solvers harness creative thinking to see problems from unique angles, experiment with new and innovative ideas, and maintain momentum throughout the problem-solving process to make measured progress and move from problems to possibilities. Launching March 2024, our newest course will help you become a dynamic problem solver, equipped to take on today’s most intricate challenges with creative thinking and confidence.

Course Outcomes

• Look at problems through different perspectives to open up many possibilities.
• Refine your instincts into actionable and innovative solutions.
• Learn how to de-risk and experiment to build resilient strategies.
• Balance creative thinking and rigor to get to breakthrough ideas and sustainable solutions.

Skills You’ll Gain

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What You'll Learn

Introduction: welcoming complexity, watch a sneak peek, 2 video lessons.

Welcome Complexity: An Introduction to Mindsets and Methods—Delve into the essential components of curiosity, experimentation, and iteration to welcome complexity as an opportunity.

1 Assignment

Articulate a Complex Problem: In your organization, reflect on how play and rigor show up.

2 Discussions

When have you seen the power of adding more imagination or creativity into addressing a complex problem? What was the impact?

What common complex problem-solving pitfall tends to happen most on your team: oversimplifying, overanalyzing, or quick fixes? Why and how could you counter it?

2 Resources

Mindsets that Drive Complex Problem Solving: This guide provides information on embracing the mindsets of exploration, empathetic curiosity, and experimentation.

Overcoming Common Pitfalls: Strategies to recognize and address common pitfalls such as oversimplification, overanalysis, and premature solution finding.

Week 1: Open Up the Problem With Curiosity

4 video lessons.

Expand the Question: Engage Stakeholders and Invite Fresh Perspectives—Learn to uncover and ask the right questions by involving diverse stakeholders

Build Empathy: Put Humans at the Center—Apply critical thinking strategies to understand the biases and needs of stakeholders using three IDEO case studies

Diverge and Converge: Generate Possibilities and Make Choices—Explore IDEO’s diverge/converge process, and the powerful role ambiguity plays in problem solving

The Science of Play: Why Creative Problem Solving Works—Explore the neuroscience behind imagination and play, and why these concepts are so vital in problem-solving spaces.

Refine Your Problem Statement: Reflect on and apply techniques to deconstruct assumptions, broaden perspectives, refine your central problem statement based on human needs and resources.

3 Discussions

What “sacred myths” are present in your organization? How might they limit creativity and innovation?

Does your organization oversimplify, overanalyze, or jump to solutions when facing complexity? Why?

How can leaders nurture acceptance of uncertainty in the innovation process?

Uncover Assumptions: Tools to help you uncover starting points, hunches, and strong beliefs about your problem.

Right-Size the Question: Learn how to sharpen your problem statement with lessons from IDEO case studies.

Week 2: Get Tangible Through Experimentation

Level up Ideas—Techniques to evolve early hunches into tangible concepts

Build confidence—Learn to assess concepts using IDEO’s Desirability, Viability, and Feasibility framework

De-risk Through Experimentation—Learn how to use prototyping to de-risk your solutions

The Art of Observation—Techniques for capturing unbiased observations from your experiments

Create Prototypes: Bring your solutions to life with rapid prototyping, uncover hidden assumptions, and build resilience in your solutions.

What technique(s) helped you most in leveling up early ideas into testable concepts?

How might you increase the diversity of perspectives involved in shaping and assessing early prototypes?

In what ways can leaders nurture acceptance of uncertainty and nonlinearity in the early innovation process?

Tools for Prototyping and Experimentation: Guides on co-creation sessions, mock pitches, and boundary concepts.

Simulating Strategies and Solutions: Learn how to use strategy board games as tools for fostering problem-solving, creativity, and innovation.

Week 3: Iterate As You Learn

3 video lessons.

Meaning Making: Identify Patterns and Themes Through Synthesis—Balance playful synthesis with rigorous analysis to build compelling narratives

Pivot and Iterate—Techniques to adapt and evolve future solutions

Learn from The Future—Use future scenarios to pressure-test ideas and adapt to evolving concepts

Uncover Deep Insights: Apply the techniques of affinity clustering, stakeholder critiques, and working backward from future visioning to derive meaningful insights and identify moments to iterate or pivot.

What metrics would indicate you are making meaningful progress amidst complexity and uncertainty?

What insights challenged your assumptions about this problem space or audience?

In what ways can experiments that “fail” still provide value in complexity?

Find the Implications from Insights: Strategies for leveraging insights in problem-solving.

Measure Progress: Methods to track progress and align with future scenarios.

Conclusion: Maintain Momentum

1 video lesson.

Sustain Commitment—Learn how to inspire behavioral change and sustain commitment.

Reflect on the Mindsets and Methods to Drive Sustained Change: Determine everyday rituals that motivate teams and counter change fatigue. Adopt lenses assessing current strategies while envisioning aspirational futures.

Why is it important to define success by outcomes rather than only concrete outputs/deliverables? How might this shape your approach?

What everyday rituals can leaders employ to keep teams inspired and committed for the long haul of complex problem-solving?

Temperature Check: Evaluate your progress and strategize the next steps to enhance confidence in your problem-solving direction.

Meet Your Instructors

Kate Schnippering

Executive design director at ideo.

Kate Schnippering is an Executive Design Director at IDEO, with a focus on creative technology. Kate brings ‘build to learn' experimentation to make real the futures we imagine. She creates conditions for teams and partners to immerse in imagination as a collective act—uplifting dreams and rigor in equal measure. In nearly a decade at IDEO, Kate’s developed teams, leaders, and organizations.

Her work investigates pathways to positive, systemic change for people and nature—by harnessing expressive technologies to make science & data relatable, and grow the power of everyday people. She’s built a real-world ‘magic school bus’ that teaches rover engineering to middle schoolers on Mars, designed a product for patients to partner directly with medical researchers in the study of rare diseases, and guided a youth mental health platform from proof of concept to delivery.

Michelle Lee

Partner and executive managing director at ideo play lab.

Michelle Lee is a Partner and Managing Director at IDEO, where she has applied her passion for play to leading interdisciplinary teams of designers and researchers in bringing engaging, interactive, and playful experiences to market. She believes in leveraging the principles of play to connect with people on a deeper emotional level that captivates, delights, and empowers.

Through her work, she has helped clients enhance workplace culture, championed responsible digital design, inspired underrepresented students to pursue careers in STEM, and supported organizations as they adopted practices in line with a circular economy. Michelle has shared her passion for play at SXSW, The Delight Conference, The Culture Summit, Circularity 23 and through numerous podcasts and articles.

Frequently Asked Questions

How do ideo u cohort courses work does my time zone matter.

We offer three types of courses: self-paced courses, cohort courses, and certificate programs. Cohort courses run on a set calendar, with fixed start and end dates. Course learning is self-paced within those dates and requires approximately 4-5 hours per week over 5 weeks. Courses consist of videos, activities, assignments, access to course teaching teams, and feedback from a global community of learners. There are also optional 1-hour video Community Conversations, held weekly by the teaching team. 

All of our cohort courses are fully online, so you can take them from any time zone, anywhere in the world. With our cohort course experience , while you'll be learning alongside other learners, you'll still have the flexibility to work at the pace that fits your own schedule. There aren’t mandatory live components, so you don't have to worry about having to log in at a specific time. At the same time, you'll have access to a teaching team, which is composed of experts in the field who are there to provide you feedback, and there are also plenty of options to connect with your fellow learners.

What is the role of the instructor and teaching team? Will learners be able to get feedback?

Course instructors have a strong presence in the courses through the course videos, but they're not actively providing feedback or holding direct conversations with our learners. We have a teaching team to ensure that you have the feedback, guidance, and support you need to learn successfully in your course. Our teaching team members are design practitioners that have experience applying course methods and mindsets in a wide variety of contexts around the world.

Our teaching team consists of teaching leads and teaching assistants, who are experts in their fields. Many of them have been with IDEO U for many years, and we have selected those who have direct experience with applying the course methods and mindsets in all sorts of contexts around the world. They all go through multiple training sessions by our instructional designers on not only on the subject matter, but also on how to create safe and collaborative learning experiences and environments.

What are Community Conversations, and how are they related to the course material?

Community Conversations are one-hour live video conversations hosted by the teaching team on Zoom. These happen once per week, with each one having two to three time options to accommodate different time zones. Each week focuses on the lesson that you’ve just gone through, so the output and the content depend on the specific lessons. You'll have the opportunity if you work together with your peers on the tools and mindsets from the course, reflect on what you’ve learned, and also address any challenges that you might be going through.

What will I have access to during and after my course?

All course materials, including videos, activities, and assignments will be available while you are enrolled in a course. During the 5 weeks of the course, you will have full access to our learning platform and can refer back to it any time. You will only have access to the course materials while you are enrolled. 

Assignments must be submitted during the 5-week course duration in order for you to receive a certificate of completion.

Can I take the course with my team?

Absolutely! We have had many teams go through our courses together. For those taking our courses as a team, we provide a number of additional benefits:

1. A Team Learning Guide, developed to provide your team with resources to facilitate offline discussions that complement the in-course experience.

2. A Manage Learners function, which provides visibility into your team's progress within the course.

3. The ability to create a private Learning Circle, which is a closed space for discussion on the learning platform specifically for your team.

For more information, visit our Team Learning page.

Do you offer discounts?

We offer a discount when you enroll in multiple courses at the same time through some of our certificate programs, including Foundations in Design Thinking , Business Innovation , Human-Centered Strategy , and Communicating for Impact . 

You can also enter your email address at the bottom of this page in order to receive updates on future offers or possible discounts. 

Will I get a certificate after completing a course?

After completing a cohort course, you will be able to add it to your “licenses and certifications” on LinkedIn.

We also have certificate programs that consist of multiple courses. After completing a certificate, you will receive a certificate of completion via email as a downloadable PDF within 1-2 weeks of completing the final required course. Certificates are configured for uploading and sharing on LinkedIn.

How do I purchase a cohort course?

You can purchase a course on our website using a credit card, PayPal, or Shop Pay. For US customers, we also offer installment plans at checkout if you use the Shop Pay method of payment.

We typically are not able to accommodate bank transfer or invoicing. However, if your order includes 10 seats or more, please contact [email protected] and our team will be happy to review your request. 

Collaborate with a Global Community

Work with expert coaches.

Our teaching team has extensive applied industry knowledge. They'll help deepen your understanding and application of the course content by facilitating written discussions, live video moments, and assignment feedback.

Expand Your Network

Join virtual live discussion groups for deeper conversation, reflection, and connection led by teaching team members and available multiple times a week across time zones.

Receive Feedback

Gain tips, techniques, and a downloadable feedback guide; and share and receive feedback on assignments from peers.

Loved by Learners Across the Globe

“Michelle has a passion for thinking BIG, addressing complexity with playful creativity, and somehow making it all fun! She understands deeply the importance and implications of play across contexts, industries, and solutions - and uses it masterfully in her own work and in helping others come up with solutions and innovations. I would 100% choose her as my teacher and mentor in this space every time - and have!”

"Kate and her team brought people together from across the Ranger Business to engage in complex strategy development through a playful and curious program of work. With prototypes and ideas in hand, we explored new places and met new people, growing and learning together as a team. These glimpses into the future continue to inspire us, have changed our approach to work and compel us to continuously adjust and refine our Ranger strategy to support future generations."

Learners Also Purchased

Human-Centered Systems Thinking

Foundations in Design Thinking Certificate

Designing Strategy

Enroll As a Team

The practice and application of design thinking, innovation, and creativity is highly collaborative and team based—which is why we believe that learning is better together. Take a course as a team and develop new skills and mindsets, have deeper discussion during course kickoff and debrief sessions, and build a shared understanding.

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How Memory Replay in Sleep Boosts Creative Problem-Solving

Penelope a. lewis.

1 CUBRIC, School of Psychology, Cardiff University, Cardiff, UK

Günther Knoblich

2 Department of Cognitive Science, Central European University, Budapest, Hungary

3 Department of Integrative Biology and Physiology, UCLA, LA, USA

Creative thought relies on the reorganisation of existing knowledge. Sleep is known to be important for creative thinking, but there is a debate about which sleep stage is most relevant, and why. We address this issue by proposing that rapid eye movement sleep, or ‘REM’, and non-REM sleep facilitate creativity in different ways. Memory replay mechanisms in non-REM can abstract rules from corpuses of learned information, while replay in REM may promote novel associations. We propose that the iterative interleaving of REM and non-REM across a night boosts the formation of complex knowledge frameworks, and allows these frameworks to be restructured, thus facilitating creative thought. We outline a hypothetical computational model which will allow explicit testing of these hypotheses.

Sleep and Creativity

Creative problem-solving is critical for all spheres of innovation and pioneering thought. As such, it forms the foundation of a technology-based economy. Friedrich Kekulé, who discovered the chemical structure of benzene, realised the molecule was circular rather than acyclic based on a vision he had in a dream. Otto Loewi, who won the 1936 Nobel Prize for work on Chemical Transmission, was also inspired by a dream. Although it is commonly accepted that sleep promotes creative problem-solving [ 1 – 5 ], it is unclear how this occurs, and there is debate as to which sleep stage, rapid eye movement (REM) (see Glossary) sleep, or non-REM, is most critical.

Creative problem-solving often involves reorganisation of existing knowledge in order to identify general rules or structures ( Box 1 ). Work over the past 10 years has shown that sleep is critical for integrating memories into an ordered framework [ 6 ], assimilating new memories with older knowledge [ 7 , 8 ], and facilitating the abstraction of general rules [ 9 – 11 ]. Such processing can provide mental clarity and facilitate creative problem-solving by promoting the comprehension of an overall structure or the extraction of hidden regularities or ‘gist’ [ 4 , 11 , 12 ]. Paradoxically, creative problem-solving often also requires the discovery of unexpected solutions through seeing beyond such rules and building new associations, which lead to novel solutions via analogical reasoning. Such creative leaps can be actively blocked by preconceptions or prejudices, which prevent us from seeing otherwise obvious solutions [ 13 ]. Importantly, these insightful rule-breaking associations are also facilitated by sleep [ 1 , 2 , 5 , 13 , 14 ].

What Is Creative Problem-Solving?

Creative problem-solving enables us to overcome obstacles that may initially seem insurmountable. Problems requiring creative solutions are not only encountered in the process of scientific discovery but also in brain teasers that look trivial at the outset but quickly make most people despair ( Figure I ). Several aspects of creative problem-solving are puzzling. One puzzle is why people often need to take a break from working on a problem to go through a period of incubation before they can achieve creative breakthroughs [ 62 ]. Another puzzle is why creative solutions to difficult problems sometimes appear suddenly to solvers after conscious and effortful attempts to find a solution have failed, potentially prompting them to shout ‘Eureka’ or to say ‘Aha’.

Several cognitive theories of creative problem-solving [ 63 , 64 ] have proposed answers to these puzzles. Building on gestalt psychology [ 65 ] their key assumption is that creative problem-solving requires a restructuring of faulty problem representations resulting from cases when irrelevant prior knowledge is applied to problems that require new solutions, tricking solvers into exploring irrelevant solution paths. Restructuring is thought to be driven by unconscious processes that can only occur when solvers stop the conscious and effortful search for a solution and enter a period of incubation. Restructuring can improve a solver’s representation in different ways. They can remove unnecessary constraints on the goal of problem solving (e.g., if it is a spatial problem and the participant is thinking of it in only in 2D when it needs to be dealt with in 3D). They can result in revised perceptual interpretations of the problem, for example through chunk decomposition, in which elements of the problem which were seen as units are broken down into smaller parts (e.g., the pen strokes in a roman numeral). Or they can retrieve new knowledge elements, including new concepts, that were previously deemed irrelevant, or solution approaches to analogous problems with a similar underlying structure.

The unconscious search processes postulated in BiOtA provide a basis for explaining how restructuring can benefit from incubation periods across sleep. The active search for similarities in informational structures that are normally kept separate, which is proposed by this model, could provide a unitary process that is at the core of several different kinds of restructuring in creative problem-solving, including mapping of analogical problem structures, conceptual change, and removal of unnecessary constraints from the problem representation.

Solution: build a pyramid. Faulty representation is to constrain solutions to 2D; this solution can only be found in 3D.

How can sleep both promote the construction of general knowledge frameworks and facilitate the creative leaps which such knowledge actively suppresses? We hypothesise that the answer lies in the heterogeneity of sleep stages, as REM and non-REM are iteratively interleaved throughout the night in cycles of about 90 min. These two stages are very different and very likely have complementary functions [ 15 , 16 ]. This article describes a conceptual framework ( Figure 1 ) which integrates behavioural and physiological data about these two sleep stages to explain how they differentially assist in gist-based and analogical-based problem-solving. We also outline a potential computational model which could allow explicit examination of the complex interaction between these sleep stages and memory consolidation. This proposed framework may lend new importance to the study of memory processing in sleep, as it suggests that these two very distinct forms of offline processing provide the foundation for two major aspects of human thinking: both the formation of complex knowledge networks and the ability to flexibly restructure them.

(A,B) A simpler representation of the process also shown in detail in (C,D). (A) Consolidation of episodic memories of lessons in astronomy from teachers, books, and TV leads to formation of a semantic representation of the solar system in the neocortex (green spot on the purple 3D surface representing semantic knowledge space). (B) The new representation of the solar system is far away from pre-existing representations of the atom and of concentric circles in semantic space. If these schemas are replayed concurrently in REM sleep, the shared structure will be detected and semantic knowledge space will be restructured so they can be linked and mapped closer together. (C) Provides a more detailed representation of the above. In non-REM sleep the hippocampus controls replay in the neocortex (red arrow) ensuring that only memories relating to a specific state are replayed concurrently. Overlapping replay leads to potentiation of shared aspects of these memories, or gist abstraction. Forgetting may result in memory for only this gist (e.g., a basic schema). (D) In REM sleep the cortex replays salient schemas and PGO waves trigger activity in other randomly chosen schemas. This spreads across networks easily due to the high ACh, allowing coherence and resulting in a search process that allows detection of similarities between the target schema and cortical schemas stemming from very different tasks or experiences. When such commonalities are detected, novel links are formed between related concepts, leading to restructuring of semantic knowledge space. Abbreviations: Ach, acetylcholine; BiOtA, broader form of the information overlap to abstract framework; PGO, ponto-geniculo-occipital; REM, rapid eye movement.

A Role for Non-REM in Gist Abstraction

It is well established that non-REM sleep stabilizes memories for individual experiences and associations, and this memory enhancement is thought to be achieved through the active neural replay of recently learned representations (see [ 17 – 19 ] for reviews, Figure 2 , and Box 2 ). The information overlap to abstract (iOtA) framework proposes that memory replay in slow wave sleep (SWS) may also lead to the abstraction of gist or overarching rules [ 6 ]. Specifically, iOtA posits that when overlapping memories are replayed by the neocortex close together in time, areas of overlap between memories are strengthened through Hebbian plasticity, leading to extraction of the commonalities or gist ( Figure 1A , ​ ,C). C ). For instance, if you replay memories of many individual birthday parties, you may extract out a gist that these normally involve cake, presents, and balloons. When this strengthening of the overlap is combined with memory degradation, the abstracted representation of regularities may remain, even if memory for each individual birthday party, or details about that party, is lost via general forgetting, synaptic downscaling [ 20 ], or targeted depotentiation [ 21 ]. This abstraction process can create thematic networks of associated information or ‘schemas’ which form the building blocks of general knowledge [ 6 ].

(A) A rat traverses a track over about 20 s and encodes locations using hippocampal place cells (14 colour-coded units are shown). (B) The rat sleeps after running on the maze and a colour-coded Rasta plot shows the same place cells firing again in roughly the same order in which they were active during track running. Interestingly, the entire 20-s experience is replayed in about 200 ms during non-REM sleep. (C) A hypnogram showing a typical night of sleep, with sleep stages indicated on the y axis as: wake (W), REM with 4–9 Hz theta activity in the hippocampus, Stage 2 (N2) with a characteristic 14 Hz sleep spindle, and Stage 3 (N3) SWS. Time is on the x axis. Black ovals illustrate the morphology of slow oscillations, theta activity, and sleep spindles (from left to right). Abbreviations: REM, rapid eye movement; SWS, slow wave sleep.

Memory Replay in Sleep

The neural activity associated with performing a particular task is often spontaneously reinstated during subsequent rest, including both sleep and wake [ 66 ]. Such neural reactivation, or ‘replay’, is thought to be important for memory consolidation [ 67 ] and is frequently studied using place cells in the hippocampus. These cells fire preferentially when an animal is in a particular location and therefore fire in a specific, predictable, order as the rat moves through space. Such precise ordering based on location means it is possible to detect offline neural replay because the same place cells fire in roughly the same order when a rat rests after running repeatedly around a predictable maze. Such reinstatement of learned spatial trajectories occurs tens to hundreds of times across a normal night of sleep and is more likely to occur for information that is salient or recently encoded [ 43 ]. While replay is most commonly studied in the hippocampus, it has also been detected in other brain areas, such as the neocortex [ 68 ] and ventral tegmental area [ 69 ].

In non-REM sleep, hippocampal replay is embedded within very high-frequency (150–300 Hz) oscillations called sharp wave ripples and often occurs atop the peaks of the high-amplitude slow waves (around 0.8 Hz) that characterise SWS [ 70 ]. If sharp wave ripples are disrupted during consolidation of a spatial memory using electrical stimulation, there is a rebound, with more such ripples (and presumably replays) occurring after disruption [ 71 ], suggesting that this is a form of activity important enough to be conserved through homeostatic regulation.

REM replay is much less studied than non-REM replay, but its occurrence is supported not only by place cell recordings [ 72 ] and conditioning work in rats [ 73 ], but also by positron emission tomography [ 74 ] and electroencephalography studies in humans [ 75 ]. While non-REM replay occurs in a temporally compressed form, around 6–20 times faster than the real experience [ 76 ], replay in REM sleep is not compressed to this extent, and instead more closely reflects the real time involved in doing the task. Some authors even speculate that REM replay may be associated with the vivid dreaming that characterises this sleep stage [ 67 , 77 ].

Fascinatingly, recent work has demonstrated that novel (as yet untraveled) trajectories, which would allow an animal to reach food, are sometimes ‘preplayed’ by the hippocampus, potentially showing the neural basis of problem solving [ 78 , 79 ].

The basic idea that overlapping memory replay in SWS leads to gist abstraction has been strongly supported by work on statistical learning [ 9 , 10 , 22 ], generalisation of object properties [ 23 ], and novel grammar learning [ 24 , 25 ], showing that SWS predicts the abstraction of general rules or underlying statistics. Other work shows that infants can better generalise word-use after sleep [ 26 ]. The link between this type of abstraction and creativity or problem solving is illustrated by the number reduction task, in which non-REM-related abstraction of a hidden rule that was common to many separate experimental trials allowed participants to have a creative insight and skip irrelevant steps, thereby solving the task much more quickly [ 4 , 12 ]. This work has been supported by the observation that explicitly triggering the replay of an implicitly learned sequence memory during non-REM promotes the emergence of explicit knowledge of that sequence [ 27 ].

Notably, the Deese-Roediger-McDermott (DRM) paradigm, which tests gist abstraction by showing participants a set of thematically linked words (e.g., hospital, bandage, operation) then testing for false memory of unlearned ‘gist’ lures (e.g., doctor) which fit semantically into the list, has also been used to examine the impact of sleep on gist memory. Sleep has variously been shown to facilitate [ 28 – 31 ], suppress [ 32 ], and not change [ 33 ] gist memory in this paradigm.

Because the gist memories in the DRM were never learned in the first place, it is unlikely that this task tests the same mechanism for gist abstraction as the paradigms cited above, in which the gist information is seen in almost every trial. Nevertheless, the DRM results are broadly compatible with a role for sleep in gist abstraction, though one study [ 31 ] does show a negative correlation between SWS and false memory. One possible explanation for this correlation is that SWS may strengthen memory for the context of learned words, thus facilitating correct rejection of lures [ 31 ].

A Role for REM in Boosting Creativity

REM sleep has long been linked with problem solving [ 1 ], and there are multiple physiological reasons why it may facilitate the formation of novel associations. Firstly, the hippocampus (a fast-learning structure that captures episodic memories) and the neocortex (a slow-learning structure which stores semanticized knowledge of the world) do not show strong synchronization in REM [ 34 ]. This could relate to the high cortisol levels [ 35 , 36 ] or the low acetylcholine (ACh) [ 37 ] which occur in this sleep stage. As a result of the reduced synchronization with the hippocampus, in REM sleep the neocortex can only replay memories which have already been neocortically coded (and therefore partially semanticized) before the REM episode. Thus, unlike non-REM memory replay, which involves periods of high hippocampal-cortical synchrony and reverberation [ 33 ], REM replay has the potential to promote the recombination of existing cortically coded knowledge.

REM is also noisier than other states of consciousness. The apparently random activation caused by the massive ponto-geniculo-occipital (PGO) waves that characterise this stage may stimulate concurrent reactivation of randomly chosen cortical schemas. Furthermore, the unique pharmacology of REM means this sleep stage is ideally suited for plasticity. Cortical ACh concentrations can be much higher in REM than in waking [ 38 ] and the presence of ACh allows postsynaptic Ca 2+ influx, which is critical for both long-term potentiation and depotentiation. These high ACh levels therefore place the brain in a plastic state, where new synapses can be formed and/or strengthened and old ones can be degraded, as needed [ 21 ]. At the cognitive level, REM has been shown to allow semantic priming to percolate further through a schema of associated ideas [ 14 , 39 ], suggesting a higher degree of connectivity. Overall, the high excitation, plasticity, and connectivity of REM provide an ideal setting for the formation of novel, unexpected, connections within existing cortically coded knowledge ( Table 1 ).

Pharmacology and Electrophysiology of Waking, Non-REM, and REM Sleep

REM is also associated with the expression of immediate early genes, such as Zif-268 , which can trigger neuroplasticity related transcription. Interestingly, this occurs in waves that initiate in the hippocampus during the first episodes of REM, occurring earlier in the night, and percolate out to the somatosensory cortices during later REM episodes [ 40 ]. As these immediate early precursors to neuroplasticity are expressed in an activity-dependent manner during REM but not during non-REM, one model [ 41 ] suggests that replay in SWS may be important for pretranscriptional amplification of learning-related synaptic changes, while REM is responsible for transcription and de novo plasticity.

In fact, the structure of a night of sleep, in which epochs of REM are interleaved with non-REM again and again as the night progresses, may also be critical for creative problem-solving. The simple fact that the same memory representations are processed separately by the decoupled neocortex and hippocampus during this sleep stage means that the two structures will arrive at slightly different end-points in each REM episode. An analogy would be two researchers who initially work on the same problem together, then go away and each think about it separately, then come back together to work on it further. The need to bring these disparate perspectives or outputs together during the next non-REM episode, when hippocampus and neocortex work together again, may force a valuable form of restructuring.

Interleaving REM and Non-REM Facilitates Creative Problem Solving

We will now propose a broader form of the iOtA framework (or BiOtA) which includes REM sleep and speaks directly to the question of how non-REM and REM combine to boost creative problem-solving.

The iOtA model explains how overlapping memory replay in SWS could promote gist abstraction and the formation of basic schemas. We suggest that this works particularly well because hippocampal input during SWS biases the neocortex to replay thematically linked memories. This idea is supported by observations that the hippocampus tends to fall into one representational state or another (e.g., representing one spatial environment) but does not blend such states [ 42 ]. Hippocampal input to the neocortex is heightened in non-REM sleep [ 34 ], so its bias towards thematically linked replay may explain why this stage is so useful for gist extraction within a set of related memories. As discussed above, activity in the hippocampus and neocortex is not so tightly synchronized in REM [ 34 , 42 ] and this lack of hippocampal input to the neocortex combines with random activation via PGO waves and high levels of plasticity to set the scene for the formation of novel connections between schemas.

Turning specifically to creative problem-solving, it is well established that more salient memories tend to be replayed more often [ 43 ], and we propose that when you are highly motivated to solve a difficult problem, schemas relating to that problem will be more likely to spontaneously reactivate in REM. Concurrently, PGO waves will trigger activity in randomly selected cortical schemas. This highly active state of REM sleep, with many different schemas reactivating in the same temporal epoch, provides ample opportunity for the formation of connections between schemas relating to the problem at hand and other, apparently unrelated schemas, especially given that the cortex is also primed for plasticity. Presumably, only connections which make some kind of sense (e.g., there is some overlap in structure) will be retained, so this could be thought of as an active (though still unconscious) search for existing schemas that share structure with the original problem-related schema.

To illustrate the BiOtA framework, we can think of the structure of the atom and the structure of the solar system, things that we have all had many experiences of hearing or learning about, but may not have related to in terms of their structure. Awareness of the structure of the solar system, in which the comparatively small planets orbit around a larger central sun, helped Earnest Rutherford to come up with a model of the atom in which negatively charged particles move around a positively charged core. This was arguably one of the biggest scientific discoveries in the 20th century. Under BiOtA, the structure for each (atom and solar system) is separately derived through replay of learning episodes in SWS, such that it is represented in the neocortex. However, the fact that these two different types of information also share a common structure is most easily abstracted in REM sleep, where the overlap between these very separate schemas is detected ( Figure 1A ). Thus, for efficiency, non-REM should come first to abstract the information into the cortex and REM second to detect structural similarities. Importantly, both forms of abstraction also allow for compression, since storage is more compact if similar concepts are coded together rather than separately [ 44 ].

We posit that the iterative alternation between generating cortically represented schemas in non-REM, and forming links between these and other cortically represented information in REM, is critical to the formation of the rich, highly interconnected representations that characterise human thought. The result of this process is a deeply interconnected form of semantic knowledge, with multiple, very different representations of the same memory coexisting, all in a highly compressed form that is nevertheless flexible and open to restructuring. This idea is perhaps expressed more clearly by the computational model that we propose in the next section ( Figure 3 ). Note that this idea is also in line with the work on immediate early genes [ 40 , 41 ], that we described above.

External stimuli, such as knowledge about astronomy, stemming from episodic experiences with books, teachers, and TV are coded into the hippocampus during wake. Replay during subsequent non-REM sleep (blue arrow) leads to formation of an abstracted representation of the solar system (green circles) in the neocortex. During subsequent REM, this cortical representation is replayed concurrently with other (older) cortical representations, for example, that of concentric circles (set of four purple circles). Commonalities between the solar system and the concentric circles will be coded in a still more abstracted form in a deeper layer (light blue circles). Each time such a representation is formed there is scope for detection of further overlap with other existing memories (e.g., the memory for the atom, set of three purple circles), or with new incoming memories. Thus, repeated cycles of non-REM and REM allow the memory to be represented in a more and more abstracted/integrated manner. Abbreviations: BiOtA, broader form of the information overlap to abstract framework; NREM, non-rapid eye movement; REM, rapid eye movement.

A Computational Model of BiOtA

The iterative alternation between memory replay in REM and non-REM leads to a complex multifaceted pattern of consolidation and is thus challenging to study. Building on existing ideas [ 45 ] we have designed a simple neural network model to formalise our proposed framework and facilitate understanding ( Figure 3 ). In this model, a series of learning episodes (think of them as memories built from astronomy classes on the solar system, and physics and chemistry classes on the atom, as well as specific times we watched TV documentaries and read books on both subjects) are coded in the hippocampus, which is represented by a set of neural network nodes. Next, in non-REM sleep, repeated reactivation of individual memories from each of these episodes in the hippocampus is used to train the strength of connections to the neocortex, which is represented by a second neural network layer. This initial cortical layer learns to represent commonalities or overlap between the various items replayed by the hippocampus, using the mechanism set out in the Rumelhart model. Note that this type of model uses backpropagation of errors across several layers of nodes to learn a sensible categorisation of items, automatically grouping those that have more similar properties (see [ 46 , 47 ] for details). Next, in REM sleep, the first level of cortical representation replays the information it has learned during the prior, non-REM period, training a third network layer, which then provides a still more compressed and thus more abstracted cortical representation. This second step of compression allows identification of commonalities between newly trained representations of overlap in the first network layer and other information that was already stored in the cortex, for instance older knowledge about atoms or sets of concentric circles. This step can represent complex statistics and could provide the basis for complex, highly abstracted schemata. Given the complexity of the human neocortex, it seems reasonable to expect many such secondary, tertiary, and so forth cortical regions to represent more and more abstracted versions of the memory [ 48 ]. Thus, the many iterations between non-REM and REM sleep episodes across multiple nights of sleep could potentially drive information deeper and deeper into this complex ‘cortical’ network, allowing extreme levels of abstraction and compression, and promoting detection of shared structure in apparently distinct memories.

As a possible addition to this model, we suggest that the replay of neocortical representations during REM sleep could also be used to determine whether these cortical representations are accurate representations of the original hippocampally coded episode. This can be achieved through a computational mechanism called an autoencoder. An autoencoder is a type of computational model, which first compresses an input and then tests the accuracy of this compressed representation by determining whether it can be used to reproduce a good approximation of the original input. Building on the suggestion that REM sleep is used to check how thoroughly memory representations have been consolidated in non-REM [ 49 ], we propose that the cortex could use an autoencoder-like process to determine which hippocampal memories have been accurately coded into the cortex and thus need no further non-REM replay. An existing computational model even suggests that circuitry between the hippocampus and entorhinal cortex is well suited to this function [ 50 ].

Implications of BiOtA for Predictive Models and Intelligence

Our general knowledge of the world is comprised of associative networks of information, such as our knowledge of birthday parties or solar systems. Newly learned facts, such as the concept of a birthday piñata, which are in keeping with this prior knowledge can be integrated easily into such a network, helping us to retain the gist [ 51 , 52 ]. In fact, a growing body of work suggests that sleep spindles, and the associated memory replay in non-REM sleep, may help new information to integrate with pre-existing knowledge frameworks [ 7 , 8 , 52 ]. Such associative networks of ideas, often referred to as schemas, form the basis of our conceptual knowledge, and thus allow predictions about our environment and the consequences of our actions; for instance, we know that it is important to take a present or card to a birthday party. New experiences which conflict with our prior knowledge typically stand out as unusual and are thus well remembered [ 53 ]. This can lead to an updating of the network, such that future predictions will be more accurate (e.g., if we attend birthday parties in Latin America, we may learn that it is important to do some blindfolded batting practice ahead of time in order to make the most of the piñata).

Some authors [ 54 ] have taken this a step further and argued that, in addition to the associative knowledge networks normally proposed as underpinning semantic memory [ 55 , 56 ], the brain also creates forward models, which draw on existing knowledge to make predictions about expected outcomes (measured as sensory feedback) given a particular set of circumstances, actions, or inputs. Such models would provide a high-level representation of our general knowledge and could potentially be thought of as a predictive form of semantic memory. One paper [ 57 ] theorised that such predictive models are tested in REM, a time when we are largely free of external inputs that might disrupt such testing. Running through various scenarios in REM would allow fine-tuning of these models by running through many combinations of parameters and choosing those that most efficiently predict the known outcomes of remembered scenarios, and thus presumably achieve good predictions in the simplest way possible.

If they exist, the forward models described above should be critical not only for guiding our decisions and anticipating upcoming events, but also for framing our perception of reality. If the predictions of such models are consistently wrong, reality would be highly unpredictable. One condition in which the perception of reality can break down in this way is schizophrenia, where patients may feel disconnected from the real world, and thus unable to understand or predict it. Interestingly, there is a tight association between abnormal non-REM sleep spindles and a risk of schizophrenia [ 58 , 59 ], suggesting that this abnormal sleep may underpin a deeper problem whereby the brain’s forward models give inaccurate predictions. In addition to the example of mental illness, it seems plausible that the efficacy of our ability to integrate new information into existing knowledge, and the accuracy of the forward models that result from this, may be linked to cognitive performance, including scores on IQ tests. This idea is in keeping with the frequently observed correlation between sleep spindles and IQ (e.g., [ 60 ]), since the ability to construct a good forward model of the environment, which can be easily updated with incoming information, should be expected to increase performance on these tests.

Implications of BiOtA for Creative Problem-Solving

Turning back to the topic of creativity, while good general knowledge and strong predictive models are clearly beneficial in many ways, they do not necessarily enhance creativity. Instead, firmly entrenched beliefs can often get in the way of the creative process. For instance, if we strongly believe that a certain knitted object is used only for keeping our head warm, then this belief may reduce the likelihood that, when faced with the problem of how to keep a tiny kitten warm or, or how to safely carry a dozen eggs, we will think of other uses for it (e.g., as a mini kitten-bed or carry bag). This inhibitory impact of prior knowledge is known as functional fixedness [ 61 ] and can be overcome by emphasising the low level properties of an object, such as its size and shape, rather than one particular function [ 13 ]. Learning to think about such component properties can help people to see the commonalities between the object in question (hat) and other related objects (bag or kitten-bed), and seeing these analogies can cause a change in the way the objects are perceived, which might be construed as a change in the schema or forward model. Thus, functional fixedness provides an easy example of a case where the way our knowledge is structured can prevent us from thinking creatively; our knowledge therefore needs to be restructured in order to promote that creative thinking.

In BiOtA we propose that REM plays a role in this type of restructuring and thus promotes analogical thinking ( Figure 1 ). Importantly, we propose that replaying memories in REM does not just optimise forward models, it can also drastically change the shape and structure of these models as they come to be seen in new ways. This is due to the discovery of similarities or analogies between things which might not otherwise have been thought of as associated (like the structure of the hat and kitten-bed, or the solar system and the atom). Thus REM replay promotes analogical problem-solving and conceptual change. Furthermore, because detecting overlap in broader structures can lead to the discounting of idiosyncrasies that initially seem important (e.g., the fact that hats are for wearing on your head, or that atoms are tiny and the solar system is large), we argue that REM replay can also promote removal of unnecessary constraints.

Concluding Remarks and Future Perspectives

In this article we have drawn on knowledge of sleep physiology and the impacts of sleep on memory to propose how REM and non-REM sleep may each separately act to promote the restructuring of semantic knowledge. We argue that the synergistic interleaving of these states promotes the formation of a more strongly interlinked knowledge base, and demonstrate a potential mechanism for this using a hypothetical computational model. We posit that this synergistic system is critical for development of the complex predictive models which underpin our ability to understand the world around us and make predictions and decisions. Furthermore, we posit that REM sleep is critical for altering or restructuring these models in order to see problems from a different angle.

Future work should test the propositions of the BiOtA model at both behavioural and computational levels (see Outstanding Questions ). At the behavioural level we can examine the impact of replay in REM and non-REM sleep upon gist abstraction and formation of novel connections between very distinct concepts. At the computational level, we can implement the hypothetical model outlined above and test whether its outputs fit our expectations. It may also be interesting to implement offline processing stages equivalent to non-REM and REM sleep in other forms of artificial intelligence, in the hopes that this will allow them to develop more complex knowledge frameworks.

Outstanding Questions

Could the principles laid out in BiOtA also apply to nonsemantic forms of memory, such as perceptual or procedural memories?

Why do people who have no REM (e.g., patients or those taking antidepressants) often appear to have entirely normal cognition?

Does REM sleep play the same role in older people, who tend to have stronger schemas and less SWS?

What role do sleep spindles play in memory replay and does it matter that they are absent in REM?

What role does REM theta activity play in memory replay and consolidation?

Does transition to REM (the spindle-rich stage 2 sleep right before REM) play a critical role in memory consolidation?

Is the sleep of highly creative people noticeably different from the sleep of normal or noncreative people?

How does creativity relate to IQ and is this relationship somehow mediated by sleep?

If the interleaving of REM and non-REM processes is truly critical for the formation of complex semantic knowledge, what would implementation of these sleep stages do for artificial intelligence?

Although the mechanisms behind BiOtA are currently only apparent for the hippocampus and neocortex, and we have therefore focussed on episodic and semantic memory systems, we would like to finish by proposing that REM may potentially also facilitate integration across multiple domains. Perceptual and procedural memories are characterised by powerful schemas (e.g., the perceptual schema for the tonality of Western music, and the procedural schema for driving a car), and the flexible combination of information between domains could further boost creativity, as it apparently did for Friedrich Kekulé when he discovered the chemical structure of benzene. Future work should investigate this important question in detail.

It is commonly accepted that sleep promotes creative problem-solving, but there is debate about the role of rapid eye movement (REM) versus non-REM sleep.

Behavioural evidence increasingly suggests that memory replay in non-REM sleep is critical for abstracting gist information (e.g., the overarching rules that define a set of related memories).

The high excitation, plasticity, and connectivity of REM sleep provide an ideal setting for the formation of novel, unexpected, connections within existing cortically coded knowledge.

The synergistic interleaving of REM and non-REM sleep may promote complex analogical problem solving.

Acknowledgements

We note that the computational model arose out of discussions with Anna Schapiro, and we are very grateful for this. We are also grateful to Bob Stickgold, Dan Bendor, Isabel Hutchison, Cathy Rogers, Mark Van Rossum, and Dara Monogue for helpful discussions and comments on the manuscript. P.L. is supported by European Research Council (ERC) grant 681607 — Understanding creativity and problem solving through sleep-engineering (SolutionSleep), and by Cardiff University. G.P. is supported by UCLA and NIH grant MH60670, and G.K. was supported by the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013)/ERC (European Research Council) grant agreement no. 609819, SOMICS.

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Life and work in the beginning of the twenty-first century has been described as volatile, uncertain, complex, and ambiguous. In this fast changing, innovation-driven environment, Creative Problem-Solving has been identified as a fundamental skill for success. In contrast to routine problem-solving, with straightforward and repeatable solution paths, today’s problems are described as being complex and wicked. To generate the possibilities that can effectively address complex problems, individuals need to draw on the highest level of human thought – creativity. Creative Problem-Solving explicitly draws on, and promotes, effective creative thinking. The purpose of this entry is to describe and distinguish Creative Problem-Solving from other forms of problems-solving. Moreover, as Creative Problem-Solving is a deliberate creativity methodology, this chapter also provides a description of the more specific thinking skills that are embodied by the higher-order skill of creative thinking and are explicitly called on in Creative Problem-Solving. Complex problems require complex thinking, and Creative Problem-Solving provides a structured process that allows individuals to more easily and efficiently deploy their creative thinking skills.

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Gerard J. Puccio, Barry Klarman & Pamela A. Szalay

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Vlad Petre Glăveanu

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Puccio, G.J., Klarman, B., Szalay, P.A. (2022). Creative Problem-Solving. In: Glăveanu, V.P. (eds) The Palgrave Encyclopedia of the Possible. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-90913-0_41

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DOI : https://doi.org/10.1007/978-3-030-90913-0_41

Published : 26 January 2023

Publisher Name : Palgrave Macmillan, Cham

Print ISBN : 978-3-030-90912-3

Online ISBN : 978-3-030-90913-0

eBook Packages : Behavioral Science and Psychology Reference Module Humanities and Social Sciences Reference Module Business, Economics and Social Sciences

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