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Ideas Made to Matter

Design thinking, explained

Rebecca Linke

Sep 14, 2017

What is design thinking?

Design thinking is an innovative problem-solving process rooted in a set of skills.The approach has been around for decades, but it only started gaining traction outside of the design community after the 2008 Harvard Business Review article [subscription required] titled “Design Thinking” by Tim Brown, CEO and president of design company IDEO.

Since then, the design thinking process has been applied to developing new products and services, and to a whole range of problems, from creating a business model for selling solar panels in Africa to the operation of Airbnb .

At a high level, the steps involved in the design thinking process are simple: first, fully understand the problem; second, explore a wide range of possible solutions; third, iterate extensively through prototyping and testing; and finally, implement through the customary deployment mechanisms. 

The skills associated with these steps help people apply creativity to effectively solve real-world problems better than they otherwise would. They can be readily learned, but take effort. For instance, when trying to understand a problem, setting aside your own preconceptions is vital, but it’s hard.

Creative brainstorming is necessary for developing possible solutions, but many people don’t do it particularly well. And throughout the process it is critical to engage in modeling, analysis, prototyping, and testing, and to really learn from these many iterations.

Once you master the skills central to the design thinking approach, they can be applied to solve problems in daily life and any industry.

Here’s what you need to know to get started.

Understand the problem 

The first step in design thinking is to understand the problem you are trying to solve before searching for solutions. Sometimes, the problem you need to address is not the one you originally set out to tackle.

“Most people don’t make much of an effort to explore the problem space before exploring the solution space,” said MIT Sloan professor Steve Eppinger. The mistake they make is to try and empathize, connecting the stated problem only to their own experiences. This falsely leads to the belief that you completely understand the situation. But the actual problem is always broader, more nuanced, or different than people originally assume.

Take the example of a meal delivery service in Holstebro, Denmark. When a team first began looking at the problem of poor nutrition and malnourishment among the elderly in the city, many of whom received meals from the service, it thought that simply updating the menu options would be a sufficient solution. But after closer observation, the team realized the scope of the problem was much larger , and that they would need to redesign the entire experience, not only for those receiving the meals, but for those preparing the meals as well. While the company changed almost everything about itself, including rebranding as The Good Kitchen, the most important change the company made when rethinking its business model was shifting how employees viewed themselves and their work. That, in turn, helped them create better meals (which were also drastically changed), yielding happier, better nourished customers.

Involve users

Imagine you are designing a new walker for rehabilitation patients and the elderly, but you have never used one. Could you fully understand what customers need? Certainly not, if you haven’t extensively observed and spoken with real customers. There is a reason that design thinking is often referred to as human-centered design.

“You have to immerse yourself in the problem,” Eppinger said.

How do you start to understand how to build a better walker? When a team from MIT’s Integrated Design and Management program together with the design firm Altitude took on that task, they met with walker users to interview them, observe them, and understand their experiences.  

“We center the design process on human beings by understanding their needs at the beginning, and then include them throughout the development and testing process,” Eppinger said.

Central to the design thinking process is prototyping and testing (more on that later) which allows designers to try, to fail, and to learn what works. Testing also involves customers, and that continued involvement provides essential user feedback on potential designs and use cases. If the MIT-Altitude team studying walkers had ended user involvement after its initial interviews, it would likely have ended up with a walker that didn’t work very well for customers. 

It is also important to interview and understand other stakeholders, like people selling the product, or those who are supporting the users throughout the product life cycle.

The second phase of design thinking is developing solutions to the problem (which you now fully understand). This begins with what most people know as brainstorming.

Hold nothing back during brainstorming sessions — except criticism. Infeasible ideas can generate useful solutions, but you’d never get there if you shoot down every impractical idea from the start.

“One of the key principles of brainstorming is to suspend judgment,” Eppinger said. “When we're exploring the solution space, we first broaden the search and generate lots of possibilities, including the wild and crazy ideas. Of course, the only way we're going to build on the wild and crazy ideas is if we consider them in the first place.”

That doesn’t mean you never judge the ideas, Eppinger said. That part comes later, in downselection. “But if we want 100 ideas to choose from, we can’t be very critical.”

In the case of The Good Kitchen, the kitchen employees were given new uniforms. Why? Uniforms don’t directly affect the competence of the cooks or the taste of the food.

But during interviews conducted with kitchen employees, designers realized that morale was low, in part because employees were bored preparing the same dishes over and over again, in part because they felt that others had a poor perception of them. The new, chef-style uniforms gave the cooks a greater sense of pride. It was only part of the solution, but if the idea had been rejected outright, or perhaps not even suggested, the company would have missed an important aspect of the solution.

Prototype and test. Repeat.

You’ve defined the problem. You’ve spoken to customers. You’ve brainstormed, come up with all sorts of ideas, and worked with your team to boil those ideas down to the ones you think may actually solve the problem you’ve defined.

“We don’t develop a good solution just by thinking about a list of ideas, bullet points and rough sketches,” Eppinger said. “We explore potential solutions through modeling and prototyping. We design, we build, we test, and repeat — this design iteration process is absolutely critical to effective design thinking.”

Repeating this loop of prototyping, testing, and gathering user feedback is crucial for making sure the design is right — that is, it works for customers, you can build it, and you can support it.

“After several iterations, we might get something that works, we validate it with real customers, and we often find that what we thought was a great solution is actually only just OK. But then we can make it a lot better through even just a few more iterations,” Eppinger said.

Implementation

The goal of all the steps that come before this is to have the best possible solution before you move into implementing the design. Your team will spend most of its time, its money, and its energy on this stage.

“Implementation involves detailed design, training, tooling, and ramping up. It is a huge amount of effort, so get it right before you expend that effort,” said Eppinger.

Design thinking isn’t just for “things.” If you are only applying the approach to physical products, you aren’t getting the most out of it. Design thinking can be applied to any problem that needs a creative solution. When Eppinger ran into a primary school educator who told him design thinking was big in his school, Eppinger thought he meant that they were teaching students the tenets of design thinking.

“It turns out they meant they were using design thinking in running their operations and improving the school programs. It’s being applied everywhere these days,” Eppinger said.

In another example from the education field, Peruvian entrepreneur Carlos Rodriguez-Pastor hired design consulting firm IDEO to redesign every aspect of the learning experience in a network of schools in Peru. The ultimate goal? To elevate Peru’s middle class.

As you’d expect, many large corporations have also adopted design thinking. IBM has adopted it at a company-wide level, training many of its nearly 400,000 employees in design thinking principles .

What can design thinking do for your business?

The impact of all the buzz around design thinking today is that people are realizing that “anybody who has a challenge that needs creative problem solving could benefit from this approach,” Eppinger said. That means that managers can use it, not only to design a new product or service, “but anytime they’ve got a challenge, a problem to solve.”

Applying design thinking techniques to business problems can help executives across industries rethink their product offerings, grow their markets, offer greater value to customers, or innovate and stay relevant. “I don’t know industries that can’t use design thinking,” said Eppinger.

Ready to go deeper?

Read “ The Designful Company ” by Marty Neumeier, a book that focuses on how businesses can benefit from design thinking, and “ Product Design and Development ,” co-authored by Eppinger, to better understand the detailed methods.

Register for an MIT Sloan Executive Education course:

Systematic Innovation of Products, Processes, and Services , a five-day course taught by Eppinger and other MIT professors.

• Leadership by Design: Innovation Process and Culture , a two-day course taught by MIT Integrated Design and Management director Matthew Kressy.
• Managing Complex Technical Projects , a two-day course taught by Eppinger.
• Apply for M astering Design Thinking , a 3-month online certificate course taught by Eppinger and MIT Sloan senior lecturers Renée Richardson Gosline and David Robertson.

Steve Eppinger is a professor of management science and innovation at MIT Sloan. He holds the General Motors Leaders for Global Operations Chair and has a PhD from MIT in engineering. He is the faculty co-director of MIT's System Design and Management program and Integrated Design and Management program, both master’s degrees joint between the MIT Sloan and Engineering schools. His research focuses on product development and technical project management, and has been applied to improving complex engineering processes in many industries.

Read next: 10 agile ideas worth sharing

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How to solve problems using the design thinking process

The design thinking process is a problem-solving design methodology that helps you develop solutions in a human-focused way. Initially designed at Stanford’s d.school, the five stage design thinking method can help solve ambiguous questions, or more open-ended problems. Learn how these five steps can help your team create innovative solutions to complex problems.

As humans, we’re approached with problems every single day. But how often do we come up with solutions to everyday problems that put the needs of individual humans first?

This is how the design thinking process started.

What is the design thinking process?

The design thinking process is a problem-solving design methodology that helps you tackle complex problems by framing the issue in a human-centric way. The design thinking process works especially well for problems that are not clearly defined or have a more ambiguous goal.

One of the first individuals to write about design thinking was John E. Arnold, a mechanical engineering professor at Stanford. Arnold wrote about four major areas of design thinking in his book, “Creative Engineering” in 1959. His work was later taught at Stanford’s Hasso-Plattner Institute of Design (also known as d.school), a design institute that pioneered the design thinking process. 

This eventually led Nobel Prize laureate Herbert Simon to outline one of the first iterations of the design thinking process in his 1969 book, “The Sciences of the Artificial.” While there are many different variations of design thinking, “The Sciences of the Artificial” is often credited as the basis. 

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A non-linear design thinking approach

Design thinking is not a linear process. It’s important to understand that each stage of the process can (and should) inform the other steps. For example, when you’re going through user testing, you may learn about a new problem that didn’t come up during any of the previous stages. You may learn more about your target personas during the final testing phase, or discover that your initial problem statement can actually help solve even more problems, so you need to redefine the statement to include those as well. 

Why use the design thinking process

The design thinking process is not the most intuitive way to solve a problem, but the results that come from it are worth the effort. Here are a few other reasons why implementing the design thinking process for your team is worth it.

Focus on problem solving

As human beings, we often don’t go out of our way to find problems. Since there’s always an abundance of problems to solve, we’re used to solving problems as they occur. The design thinking process forces you to look at problems from many different points of view. 

The design thinking process requires focusing on human needs and behaviors, and how to create a solution to match those needs. This focus on problem solving can help your design team come up with creative solutions for complex problems. 

Encourages collaboration and teamwork

The design thinking process cannot happen in a silo. It requires many different viewpoints from designers, future customers, and other stakeholders . Brainstorming sessions and collaboration are the backbone of the design thinking process.

Foster innovation

The design thinking process focuses on finding creative solutions that cater to human needs. This means your team is looking to find creative solutions for hyper specific and complex problems. If they’re solving unique problems, then the solutions they’re creating must be equally unique.

The iterative process of the design thinking process means that the innovation doesn’t have to end—your team can continue to update the usability of your product to ensure that your target audience’s problems are effectively solved. 

The 5 stages of design thinking

Currently, one of the more popular models of design thinking is the model proposed by the Hasso-Plattner Institute of Design (or d.school) at Stanford. The main reason for its popularity is because of the success this process had in successful companies like Google, Apple, Toyota, and Nike. Here are the five steps designated by the d.school model that have helped many companies succeed.

1. Empathize stage

The first stage of the design thinking process is to look at the problem you’re trying to solve in an empathetic manner. To get an accurate representation of how the problem affects people, actively look for people who encountered this problem previously. Asking them how they would have liked to have the issue resolved is a good place to start, especially because of the human-centric nature of the design thinking process. 

Empathy is an incredibly important aspect of the design thinking process.  The design thinking process requires the designers to put aside any assumptions and unconscious biases they may have about the situation and put themselves in someone else’s shoes. 

For example, if your team is looking to fix the employee onboarding process at your company, you may interview recent new hires to see how their onboarding experience went. Another option is to have a more tenured team member go through the onboarding process so they can experience exactly what a new hire experiences.

2. Define stage

Sometimes a designer will encounter a situation when there’s a general issue, but not a specific problem that needs to be solved. One way to help designers clearly define and outline a problem is to create human-centric problem statements. 

A problem statement helps frame a problem in a way that provides relevant context in an easy to comprehend way. The main goal of a problem statement is to guide designers working on possible solutions for this problem. A problem statement frames the problem in a way that easily highlights the gap between the current state of things and the end goal. 

Tip: Problem statements are best framed as a need for a specific individual. The more specific you are with your problem statement, the better designers can create a human-centric solution to the problem. 

Examples of good problem statements:

We need to decrease the number of clicks a potential customer takes to go through the sign-up process.

We need to decrease the new subscriber unsubscribe rate by 10%. 

We need to increase the Android app adoption rate by 20%.

3. Ideate stage

This is the stage where designers create potential solutions to solve the problem outlined in the problem statement. Use brainstorming techniques with your team to identify the human-centric solution to the problem defined in step two. 

Here are a few brainstorming strategies you can use with your team to come up with a solution:

Standard brainstorm session: Your team gathers together and verbally discusses different ideas out loud.

Brainwrite: Everyone writes their ideas down on a piece of paper or a sticky note and each team member puts their ideas up on the whiteboard. 

Worst possible idea: The inverse of your end goal. Your team produces the most goofy idea so nobody will look silly. This takes out the rigidity of other brainstorming techniques. This technique also helps you identify areas that you can improve upon in your actual solution by looking at the worst parts of an absurd solution. 

It’s important that you don’t discount any ideas during the ideation phase of brainstorming. You want to have as many potential solutions as possible, as new ideas can help trigger even better ideas. Sometimes the most creative solution to a problem is the combination of many different ideas put together.

4. Prototype stage

During the prototype phase, you and your team design a few different variations of inexpensive or scaled down versions of the potential solution to the problem. Having different versions of the prototype gives your team opportunities to test out the solution and make any refinements. 

Prototypes are often tested by other designers, team members outside of the initial design department, and trusted customers or members of the target audience. Having multiple versions of the product gives your team the opportunity to tweak and refine the design before testing with real users. During this process, it’s important to document the testers using the end product. This will give you valuable information as to what parts of the solution are good, and which require more changes.

After testing different prototypes out with teasers, your team should have different solutions for how your product can be improved. The testing and prototyping phase is an iterative process—so much so that it’s possible that some design projects never end.

After designers take the time to test, reiterate, and redesign new products, they may find new problems, different solutions, and gain an overall better understanding of the end-user. The design thinking framework is flexible and non-linear, so it’s totally normal for the process itself to influence the end design. 

Tips for incorporating the design thinking process into your team

If you want your team to start using the design thinking process, but you’re unsure of how to start, here are a few tips to help you out. 

Start small: Similar to how you would test a prototype on a small group of people, you want to test out the design thinking process with a smaller team to see how your team functions. Give this test team some small projects to work on so you can see how this team reacts. If it works out, you can slowly start rolling this process out to other teams.

Incorporate cross-functional team members : The design thinking process works best when your team members collaborate and brainstorm together. Identify who your designer’s key stakeholders are and ensure they’re included in the small test team. 

Organize work in a collaborative project management software : Keep important design project documents such as user research, wireframes, and brainstorms in a collaborative tool like Asana . This way, team members will have one central source of truth for anything relating to the project they’re working on.

Foster collaborative design thinking with Asana

The design thinking process works best when your team works collaboratively. You don’t want something as simple as miscommunication to hinder your projects. Instead, compile all of the information your team needs about a design project in one place with Asana. 

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A complete guide to the design thinking process

Learn the five stages of the design thinking process, get practical tips to apply them, and get templates to seamlessly run design thinking exercises.

How many projects have you worked on that stalled because your team couldn’t align on the best path forward? How many more got shelved because they didn’t meet user needs or expectations? And how many got delayed in rounds and rounds of never-ending feedback? 

Thankfully, you don’t have to keep repeating those experiences month after month. The (not so) secret weapon: design thinking .

Design thinking gives teams a new way to approach their projects and overcome some of those well-known challenges. It can help teams understand their users' needs and challenges, then apply those learnings to solve problems in a creative, innovative way. Understanding design thinking can transform your team’s problem-solving approach — and how you work together.

What is design thinking?

Design thinking is an iterative process where teams seek to understand user needs, challenge assumptions, define complex problems to solve, and develop innovative solutions to prototype and test. The goal of design thinking is to come up with user-focused solutions tailored to the particular problem at hand.

While often used in product design, service design, and customer experience, you can use design thinking in virtually any situation, industry, or organization to create user-centric solutions to specific problems.

Design thinking process 101: Definitions and approaches

The design thinking process puts customers’ and users’ needs at the center and aims to solve challenges from their perspective.

Design thinking typically follows five distinct stages:

Empathize stage

The first stage of design thinking lays the foundation for the rest of the process because it focuses on the needs of the real people using your product. At this stage, you want to get familiar with the people experiencing the problems you’re trying to solve, understanding their point of view, and learning about their user experience. You want to understand their challenges and what they need from your product or company to address them.

The goal of this stage is for your team to develop a user-centered vision of the core problem you need to solve. The idea is to challenge any assumptions or biases teams have, instead using their customer perspective as a guiding source. This is important because it aligns the team on what needs to be considered during the rest of the design thinking process. 

To help you get a solid understanding of the problems you’re solving, you can ask a lot of questions to build empathy with your users. These will invite people to share their experiences and observations to help your team better understand the problem. Then, you can move on to some specific exercises for the empathy stage of the process.

As you build up your understanding of your users, it's helpful to visualize their experience. A common way to do this is to assemble a customer journey map . This helps identify areas of friction and understand customer preferences.

Learn more: 7 types of questions to build empathy for design thinking

Ideate stage

Your priority here is to think outside the box and source as many ideas as possible from all areas of the business. Bring in people from different departments so you benefit from a wider range of experiences and perspectives during ideation sessions. Don’t worry about coming up with concrete solutions or how to implement each one — you’ll build on that later. The goal is to explore new and creative ideas rather than come up with an actual plan.

Key steps in the ideation phase:

• Define your problem : Creating a problem statement ensures that your team can focus on solving the right problem and staying aligned with your end-user or customer’s problem
• Start ideating : Choose a brainstorming technique to help organize team participation that fits your goal (More on that in the next section.)
• Prioritize your ideas : Once you have several ideas, prioritize them based on how well they take into account the customer’s needs‍ ‍
• Choose the best solution : Choose the best ideas to move forward to either the define stage or the prototype stage

Learn more: The ideation stage of design thinking: What you need to know

Your priority here is to generate as many ideas as possible, without judging or evaluating them. This step encourages designers to think creatively and push the boundaries of what's possible. We’ve put together a list of different brainstorming techniques to help your teams come up with creative new ideas. 

Put it into practice: How to facilitate a brainstorming session

Prototyping stage

At this stage, your team’s goal is to remove uncertainty around your proposed solutions. This is where you start thinking about them in more detail, including how you’ll bring them to life. Your prototypes should help the team understand if the design or solution will work as it’s intended to. 

Here, the focus is on speed and efficiency — you don’t want to invest a ton of time or resources into these solutions yet because you’re not sure they’re the best ones for the problem you’re trying to solve. You just need a functional, interactive prototype that can prove your concept. These are learning opportunities to help you spot any issues or opportunities before you take it any further.

Learn more: A guide to prototyping: the 4th stage of design thinking

Testing stage

The testing stage is normally one of the last stages of the design thinking process. After you’ve developed a concept or prototype, you need to test it in the real-world to understand its viability and usability. It’s where your product, design, or development teams evaluate the creative solutions they’ve come up with, to see how real users interact with them. 

Testing your concepts and observing how people interact with them helps you understand whether or not the prototype solves real problems and meets their needs, before you invest in it fully.

However, design thinking is an iterative process: You may go through the ideation, prototyping, and testing phases multiple times to improve and refine your solutions as you learn more from your users.

Read the guide: Testing: A guide to the 5th stage of design thinking

The relationship between human-centered design and design thinking

These two terms are often used together, because they complement one another. However, they’re two different things, so understanding their differences is important. 

Simply put, design thinking is a working process, while human-centered design is a mindset or approach.

The first step in finding success with design thinking is to foster a culture of human-centered design within your team. This is because design thinking focuses so heavily on the users and customers — the people using your product or service.

To inspire your team, we’ve put together four human-centered design examples — and explain why they work so well.

Benefits of design thinking

For organizations who’ve never run a design thinking workshop before, it can feel like a big change in how you approach the design process. But it can offer many benefits for your business.

Foster a true design culture within your organization

Design thinking is an iterative process — it’s not something you do once and call it done. The more you do it, the more you’ll see a design-focused culture emerge within your organization, which is much more effective than going to one-off creative retreats or setting up expensive innovation centers that no one ever uses.

This mindset and cultural shift can help scale design thinking within the business. But it’s important to know how to avoid  some of the pitfalls companies can face when trying to create a design culture internally.

Learn more: How to use the LUMA System of Innovation for everyday design thinking

Encourage collaboration across departments

Design thinking isn’t just for the designers on the team. The earlier stages of the process — Empathize, Define, and Ideate — are perfect for bringing in people from across the business. In fact, bringing in varied viewpoints and perspectives can help you come up with more creative or effective solutions.

You can use the design thinking process to get more people involved, and help everyone contribute ideas.

Improve understanding of user needs

So many companies say they’re “customer focused,” but lack a clear understanding of what really matters most to their customers in the context of their product or service. Design thinking puts the user front and center, with the Empathize stage dedicated to understanding and discovering user needs.

Learn more: How to identify user needs and pain points

Skills and behaviors needed for successful design thinking

To get the most out of a design thinking exercise, you’ll need a collaborative and creative mindset within your team. The team needs to be willing to explore new ideas, and laser-focused on customer or user needs. 

Here are some specific skills to help your design thinking process run smoothly.

Divergent and convergent thinking

Divergence and convergence is a human-centered design approach to problem-solving. It switches between expansive and focused thinking, giving you a process that balances understanding people’s problems and developing solutions. 

It focuses on understanding a user's needs, behaviors, and motivations, to help you develop empathy for their problems. Then, it encourages experimentation and iteration to help you effectively design solutions to meet those needs.

Collaborative working

Design thinking isn’t a solo activity. You’ll bring in people from different teams or business areas. To get the most out of the process, everyone needs to collaborate and communicate effectively. Teams that are good at collaborating drive the best outcomes, while also making it an enjoyable experience working together.

There are several core collaboration skills your team needs to succeed:

• Open-mindedness
• Communication
• Adaptability
• Organization
• Time management

Learn more about why these skills are so important and how you can improve them individually or as a team: 7 collaboration skills your team needs to succeed

Participatory or collaborative design

For many design teams and creative folks, the idea of designing something with other people can be enough to make them shudder. “Design by committee” is their idea of a nightmare. But the design thinking process isn’t about “making the logo 10% bigger” or “using a different shade of blue.” It’s user- and solution-focused.

You’ll get the best outcomes if you bring insights, perspectives, and expertise from multiple stakeholders. That includes at the Prototype and Test stages, as everyone will have ideas to contribute to help you bring solutions to life.

Learn more: What is co-design? A primer on participatory design

Common challenges in design thinking

If your team hasn’t mastered or fully committed to each one of the design thinking steps, you may encounter problems that make it harder to reap the benefits of design thinking.

Here are 4 common challenges that teams face when implementing design thinking practices.

• A company culture that doesn't foster collaboration
• An inability to adjust to non-linear processes
• A lack of in-depth user research
• Getting too invested in a single idea

Learn how to address these in Mural's guide on design thinking challenges .

Design thinking tools and templates to help you get started

Using mural for design thinking.

There are lots of tools you can use to run design thinking workshops — including Mural. We help designers work as effectively as possible, so they can get to better solutions quicker. We’ve incorporated some design thinking shortcuts and “hidden” features into our application, making it perfect for in-person or remote (or even asynchronous) collaborative sessions. These include:

• Use the C-key shortcut to quickly connect ideas with arrows
• Seamlessly import existing information from spreadsheets
• Duplicate elements you already created for faster visualization
• Fit your canvas to your screen and zoom in
• Get even more options using the right-click menu

And to help you get started, we’ve hand-picked some Mural templates relevant to each stage of the design process below.

Templates for the Empathy stage

The empathy map template helps you visualize the thoughts, feelings, and actions of your customersto help you develop a better understanding of the their experiences. The map is divided into four quadrants, where you record the following:

• Thoughts: the customer’s internal dialogue and beliefs
• Feelings: the customer’s emotional responses
• Actions: the customer’s actions and behaviors
• Observations: what the customer is seeing and hearing.

Try Mural’s empathy map template

Templates for the Define stage

This exercise helps you understand a situation or problem by identifying what’s working, what’s not, and areas for improvement. You start by listing out the problem, then identifying the positive aspects (the rose), negatives (thorn), and possible solutions for improvement (the buds).

You can use this template to run the exercise individually or in groups. It gives you a way to gather new ideas and perspectives on the problem you’re solving in real-time.

Try Mural’s Rose, thorn, bud template

Templates for the Ideate stage

The round robin brainstorming exercise is a collaborative session where every person contributes multiple ideas. This is a great way to come up with lots of different ideas and solutions in the ideation stage of design thinking, where you’re focusing on quantity and creativity. 

Bringing in ideas from every team member encourages people to share their unique perspectives, and can also help you avoid groupthink. 

Try Mural’s Round robin template

Templates for the Prototype stage

This template helps you map out how an idea will work in practice, as a functional system. Schematic diagramming is very flexible, so it can be used in many types of projects to make sure your idea is  structurally sound. It can help you map out workflows and identify any decisions you need to make to bring your idea to life.

Try Mural’s Schematic diagramming template

Templates for the Test stage

In think aloud testing, users test out a product or prototype and talk through the relevant tasks as they complete them. You can use this template to record the feedback, insights, and experiences of your testers, and identify the success and failure points in your proposed solution.

Try Mural’s Think aloud testing template

Design thinking examples: What it looks like in practice

Design thinking is a very flexible approach that works for companies of any size, from large enterprises to small startups. 

Here are some examples of how companies use design thinking, for many types of creative projects.

IBM uses design thinking to design at scale

IBM was traditionally an engineering-led organization, but now it's shifting its focus onto design, working to spread a design culture throughout the business. One of the main ways of doing that is by launching IBM Design Camps.

These camps are comprehensive educational programs that help people understand the concept of design thinking and how it specifically works at IBM. 

Learn more about how IBM runs design thinking workshops with remote or distributed teams .

Somersault Innovation uses design thinking to transform its sales process

Somersault Innovation has used design thinking methods to help their sales team co-create solutions with their customers. It’s helped sellers become more customer-centric. 

Now, their sellers can create mutual success plans with their prospects, making it easier for them to find a path forward together.

Mural uses design thinking to drive growth

At Mural, our marketing team is constantly following new trends, evaluating metrics, and working to deliver the best experiences for our customers. Design thinking helps us adopt a customer-centric approach by ensuring that we're focused on the right problems. This helps us have the biggest impact on the company’s long-term growth while creating the most value for our users.

David J. Bland planned a book using the design thinking methodology

It’s not just visual creative projects that can benefit from the design thinking process. Founder, speaker, and author David J. Bland used the methodology to plan out his book and collaborate with other team members in the process. In addition to helping him refine and adjust the structure, Bland also used it to gather feedback from early readers and target audiences, which helped get the final product just right.

Support design thinking with tools that facilitate creative collaboration

While we’ve covered some of the skills and behaviors you need to successfully run design thinking exercises, having the right tools can help a lot, too. A collaborative platform helps teams communicate, share ideas, and turn those ideas into solutions together.

Mural helps teams visualize their ideas in a collaboration platform that unlocks teamwork . This helps everyone stay on the same page, while giving them the ability to add their own ideas freely and easily. Mural facilitates effective collaboration both in person and remotely, making it ideal for design thinking workshops for co-located and distributed teams. Plus, it has tons of ready-to-use templates (like the ones we listed above) to help you get started.

Ready to give it a try? Start your Free Forever account today, and run your next design thinking workshop in Mural.

About the authors

Bryan Kitch

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Design Thinking 101

July 31, 2016 2016-07-31

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In This Article:

Definition of design thinking, why — the advantage, flexibility — adapt to fit your needs, scalability — think bigger, history of design thinking.

Design thinking is an ideology supported by an accompanying process . A complete definition requires an understanding of both.

Definition: The design thinking ideology asserts that a hands-on, user-centric approach to problem solving can lead to innovation, and innovation can lead to differentiation and a competitive advantage. This hands-on, user-centric approach is defined by the design thinking process and comprises 6 distinct phases, as defined and illustrated below.

The design-thinking framework follows an overall flow of 1) understand, 2) explore, and 3) materialize. Within these larger buckets fall the 6 phases: empathize, define, ideate, prototype, test, and implement.

Conduct research in order to develop knowledge about what your users do, say, think, and feel .

Imagine your goal is to improve an onboarding experience for new users. In this phase, you talk to a range of actual users.  Directly observe what they do, how they think, and what they want, asking yourself things like ‘what motivates or discourages users?’ or ‘where do they experience frustration?’ The goal is to gather enough observations that you can truly begin to empathize with your users and their perspectives.

Combine all your research and observe where your users’ problems exist. While pinpointing your users’ needs , begin to highlight opportunities for innovation.

Consider the onboarding example again. In the define phase, use the data gathered in the empathize phase to glean insights. Organize all your observations and draw parallels across your users’ current experiences. Is there a common pain point across many different users? Identify unmet user needs.

Brainstorm a range of crazy, creative ideas that address the unmet user needs identified in the define phase. Give yourself and your team total freedom; no idea is too farfetched and quantity supersedes quality.

At this phase, bring your team members together and sketch out many different ideas. Then, have them share ideas with one another, mixing and remixing, building on others' ideas.

Build real, tactile representations for a subset of your ideas. The goal of this phase is to understand what components of your ideas work, and which do not. In this phase you begin to weigh the impact vs. feasibility of your ideas through feedback on your prototypes.

Make your ideas tactile. If it is a new landing page, draw out a wireframe and get feedback internally.  Change it based on feedback, then prototype it again in quick and dirty code. Then, share it with another group of people.

Return to your users for feedback. Ask yourself ‘Does this solution meet users’ needs?’ and ‘Has it improved how they feel, think, or do their tasks?’

Put your prototype in front of real customers and verify that it achieves your goals. Has the users’ perspective during onboarding improved? Does the new landing page increase time or money spent on your site? As you are executing your vision, continue to test along the way.

Put the vision into effect. Ensure that your solution is materialized and touches the lives of your end users.

This is the most important part of design thinking, but it is the one most often forgotten. As Don Norman preaches, “we need more design doing.” Design thinking does not free you from the actual design doing. It’s not magic.

“There’s no such thing as a creative type. As if creativity is a verb, a very time-consuming verb. It’s about taking an idea in your head, and transforming that idea into something real. And that’s always going to be a long and difficult process. If you’re doing it right, it’s going to feel like work.”  - Milton Glaser

As impactful as design thinking can be for an organization, it only leads to true innovation if the vision is executed. The success of design thinking lies in its ability to transform an aspect of the end user’s life. This sixth step — implement — is crucial.

Why should we introduce a new way to think about product development? There are numerous reasons to engage in design thinking, enough to merit a standalone article, but in summary, design thinking achieves all these advantages at the same time.

Design thinking:

• Is a user-centered process that starts with user data, creates design artifacts that address real and not imaginary user needs, and then tests those artifacts with real users
• Leverages collective expertise and establishes a shared language, as well as buy-in amongst your team
• Encourages innovation by exploring multiple avenues for the same problem

Jakob Nielsen says “ a wonderful interface solving the wrong problem will fail ." Design thinking unfetters creative energies and focuses them on the right problem. 

The above process will feel abstruse at first. Don’t think of it as if it were a prescribed step-by-step recipe for success. Instead, use it as scaffolding to support you when and where you need it. Be a master chef, not a line cook: take the recipe as a framework, then tweak as needed.

Each phase is meant to be iterative and cyclical as opposed to a strictly linear process, as depicted below. It is common to return to the two understanding phases, empathize and define, after an initial prototype is built and tested. This is because it is not until wireframes are prototyped and your ideas come to life that you are able to get a true representation of your design. For the first time, you can accurately assess if your solution really works. At this point, looping back to your user research is immensely helpful. What else do you need to know about the user in order to make decisions or to prioritize development order? What new use cases have arisen from the prototype that you didn’t previously research?

You can also repeat phases. It’s often necessary to do an exercise within a phase multiple times in order to arrive at the outcome needed to move forward. For example, in the define phase, different team members will have different backgrounds and expertise, and thus different approaches to problem identification. It’s common to spend an extended amount of time in the define phase, aligning a team to the same focus. Repetition is necessary if there are obstacles in establishing buy-in. The outcome of each phase should be sound enough to serve as a guiding principle throughout the rest of the process and to ensure that you never stray too far from your focus.

The packaged and accessible nature of design thinking makes it scalable. Organizations previously unable to shift their way of thinking now have a guide that can be comprehended regardless of expertise, mitigating the range of design talent while increasing the probability of success. This doesn’t just apply to traditional “designery” topics such as product design, but to a variety of societal, environmental, and economical issues. Design thinking is simple enough to be practiced at a range of scopes; even tough, undefined problems that might otherwise be overwhelming. While it can be applied over time to improve small functions like search, it can also be applied to design disruptive and transformative solutions, such as restructuring the career ladder for teachers in order to retain more talent. 

It is a common misconception that design thinking is new. Design has been practiced for ages : monuments, bridges, automobiles, subway systems are all end-products of design processes. Throughout history, good designers have applied a human-centric creative process to build meaningful and effective solutions.

In the early 1900's husband and wife designers Charles and Ray Eames practiced “learning by doing,” exploring a range of needs and constraints before designing their Eames chairs, which continue to be in production even now, seventy years later. 1960's dressmaker Jean Muir was well known for her “common sense” approach to clothing design, placing as much emphasis on how her clothes felt to wear as they looked to others. These designers were innovators of their time. Their approaches can be viewed as early examples of design thinking — as they each developed a deep understanding of their users’ lives and unmet needs. Milton Glaser, the designer behind the famous I ♥ NY logo, describes this notion well: “We’re always looking, but we never really see…it’s the act of attention that allows you to really grasp something, to become fully conscious of it.”

Despite these (and other) early examples of human-centric products, design has historically been an afterthought in the business world, applied only to touch up a product’s aesthetics. This topical design application has resulted in corporations creating solutions which fail to meet their customers’ real needs. Consequently, some of these companies moved their designers from the end of the product-development process, where their contribution is limited, to the beginning. Their human-centric design approach proved to be a differentiator: those companies that used it have reaped the financial benefits of creating products shaped by human needs.

In order for this approach to be adopted across large organizations, it needed to be standardized. Cue design thinking, a formalized framework of applying the creative design process to traditional business problems.

The specific term "design thinking" was coined in the 1990's by David Kelley and Tim Brown of IDEO, with Roger Martin, and encapsulated methods and ideas that have been brewing for years into a single unified concept.

We live in an era of experiences , be they services or products, and we’ve come to have high expectations for these experiences. They are becoming more complex in nature as information and technology continues to evolve. With each evolution comes a new set of unmet needs. While design thinking is simply an approach to problem solving, it increases the probability of success and breakthrough innovation.

Learn more about design thinking in the full-day course Generating Big Ideas with Design Thinking .

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What is design thinking?

Design and conquer: in years past, the word “design” might have conjured images of expensive handbags or glossy coffee table books. Now, your mind might go straight to business. Design and design thinking are buzzing in the business community more than ever. Until now, design has focused largely on how something looks; these days, it’s a dynamic idea used to describe how organizations can adjust their problem-solving approaches to respond to rapidly changing environments—and create maximum impact and shareholder value. Design is a journey and a destination. Design thinking is a core way of starting the journey and arriving at the right destination at the right time.

Simply put, “design thinking is a methodology that we use to solve complex problems , and it’s a way of using systemic reasoning and intuition to explore ideal future states,” says McKinsey partner Jennifer Kilian. Design thinking, she continues, is “the single biggest competitive advantage that you can have, if your customers are loyal to you—because if you solve for their needs first, you’ll always win.”

Get to know and directly engage with senior McKinsey experts on design thinking

Tjark Freundt is a senior partner in McKinsey’s Hamburg office, Tomas Nauclér is a senior partner in the Stockholm office, Daniel Swan is a senior partner in the Stamford office, Warren Teichner is a senior partner in the New York office, Bill Wiseman is a senior partner in the Seattle office, and Kai Vollhardt is a senior partner in the Munich office.

And good design is good business. Kilian’s claim is backed up with data: McKinsey Design’s 2018 Business value of design report  found that the best design performers increase their revenues  and investor returns at nearly twice the rate of their industry competitors. What’s more, over a ten-year period, design-led companies outperformed  the S&P 500 by 219 percent.

As you may have guessed by now, design thinking goes way beyond just the way something looks. And incorporating design thinking into your business is more than just creating a design studio and hiring designers. Design thinking means fundamentally changing how you develop your products, services, and, indeed, your organization itself.

Read on for a deep dive into the theory and practice of design thinking.

Learn more about McKinsey’s Design Practice , and check out McKinsey’s latest Business value of design report here .

How do companies build a design-driven company culture?

There’s more to succeeding in business than developing a great product or service that generates a financial return. Empathy and purpose are core business needs. Design thinking means putting customers, employees, and the planet at the center of problem solving.

McKinsey’s Design Practice has learned that design-led organizations start with design-driven cultures. Here are four steps  to building success through the power of design:

Understand your audience. Design-driven companies go beyond asking what customers and employees want, to truly understanding why they want it. Frequently, design-driven companies will turn to cultural anthropologists and ethnographers to drill down into how their customers use and experience products, including what motivates them and what turns them away.

Makeup retailer Sephora provides an example. When marketing leaders actually watched  shoppers using the Sephora website, they realized customers would frequently go to YouTube to watch videos of people using products before making a purchase. Using this information, the cosmetics retailer developed its own line of demonstration videos, keeping shoppers on the site and therefore more likely to make a purchase.

• Bring design to the executive table. This leader can be a chief design officer, a chief digital officer, or a chief marketing officer. Overall, this executive should be the best advocate for the company’s customers and employees, bringing the point of view of the people, the planet, and the company’s purpose into strategic business decisions. The design lead should also build bridges between multiple functions and stakeholders, bringing various groups into the design iteration process.
• Design in real time. To understand how and why people—both customers and employees—use processes, products, or services, organizations should develop a three-pronged design-thinking model that combines design, business strategy, and technology. This approach allows business leaders to spot trends, cocreate using feedback and data, prototype, validate, and build governance models for ongoing investment.

Act quickly. Good design depends on agility. That means getting a product to users quickly, then iterating based on customer feedback. In a design-driven culture, companies aren’t afraid to release products that aren’t quite perfect. Designers know there is no end to the design process. The power of design, instead, lies in the ability to adopt and adapt as needs change. When designers are embedded within teams, they are uniquely positioned to gather and digest feedback, which can lead to unexpected revelations. Ultimately, this approach creates more impactful and profitable results than following a prescribed path.

Consider Instagram. Having launched an initial product in 2010, Instagram’s founders paid attention to what the most popular features were: image sharing, commenting, and liking. They relaunched with a stripped-down version a few months later, resulting in 100,000 downloads in less than a week and over two million users in under two months —all without any strategic promotion.

Learn more about McKinsey’s Design Practice .

What’s the relationship between user-centered design and design thinking?

Both processes are design led. And they both emphasize listening to and deeply understanding users and continually gathering and implementing feedback to develop, refine, and improve a service.

Where they are different is scale. User-centered design focuses on improving a specific product or service . Design thinking takes a broader view  as a way to creatively address complex problems—whether for a start-up, a large organization, or society as a whole.

User-centered design is great for developing a fantastic product or service. In the past, a company could coast on a superior process or product for years before competitors caught up. But now, as digitization drives more frequent and faster disruptions, users demand a dynamic mix of product and service. Emphasis has shifted firmly away  from features and functions toward purpose, lifestyle, and simplicity of use.

Introducing McKinsey Explainers : Direct answers to complex questions

McKinsey analysis has found that some industries—such as telecommunications, automotive, and consumer product companies— have already made strides toward combining product and service into a unified customer experience . Read on for concrete examples of how companies have applied design thinking to offer innovative—and lucrative—customer experiences.

Learn more about our Operations Practice .

What is the design-thinking process?

McKinsey analysis has shown that the design-thinking approach creates more value  than conventional approaches. The right design at the right price point spurs sustainability and resilience in a demonstrable way—a key driver of growth.

According to McKinsey’s Design  Practice, there are two key steps to the design-thinking process:

• Developing an understanding of behavior and needs that goes beyond what people are doing right now to what they will need in the future and how to deliver that. The best way to develop this understanding is to spend time with people.
• “Concepting,” iterating, and testing . First start with pen and paper, sketching out concepts. Then quickly put these into rough prototypes—with an emphasis on quickly. Get feedback, refine, and test again. As American chemist Linus Pauling said : “The way to get good ideas is to get lots of ideas and throw the bad ones away.”

What is D4VG versus DTV?

For more than a decade, manufacturers have used a design-to-value (DTV) model  to design and release products that have the features needed to be competitive at a low cost. During this time, DTV efforts were groundbreaking because they were based on data rather than experience. They also reached across functions, in contrast to the typical value-engineering approach.

The principles of DTV have evolved into design for value and growth (D4VG), a new way of creating products that provide exceptional customer experiences while driving both value and growth. Done right, D4VG efforts generate products with the features, form, and functionality that turn users into loyal fans .

D4VG products can cost more to build, but they can ultimately raise margins by delivering on a clear understanding of a product’s core brand attributes, insights into people’s motivations, and design thinking.

Learn more about our Consumer Packaged Goods Practice .

What is design for sustainability?

As consumers, companies, and regulators shift toward increased sustainability, design processes are coming under even more scrutiny. The challenge is that carbon-efficient production processes tend to be more complex and can require more carbon-intensive materials. The good news is that an increased focus on design for sustainability (DFS), especially at the research and development stage , can help mitigate some of these inefficiencies and ultimately create even more sustainable products.

For example, the transition from internal-combustion engines to electric-propulsion vehicles  has highlighted emissions-intensive automobile production processes. One study found that around 20 percent of the carbon generated by a diesel vehicle comes from its production . If the vehicle ran on only renewable energy, production emissions would account for 85 percent of the total. With more sustainable design, electric-vehicle (EV) manufacturers stand to reduce the lifetime emissions of their products significantly.

To achieve design for sustainability at scale, companies can address three interrelated elements at the R&D stage:

• rethinking the way their products use resources, adapting them to changing regulations, adopting principles of circularity, and making use of customer insights
• understanding and tracking emissions and cost impact of design decisions in support of sustainability goals
• fostering the right mindsets and capabilities to integrate sustainability into every product and design decision

What is ‘skinny design’?

Skinny design is a less theoretical aspect of design thinking. It’s a method whereby consumer goods companies reassess the overall box size of products by reducing the total cubic volume of the package. According to McKinsey analysis , this can improve overall business performance in the following ways:

• Top-line growth of 4 to 5 percent through improvements in shelf and warehouse holding power. The ability to fit more stock into warehouses ultimately translates to growth.
• Bottom-line growth of more than 10 percent . Packing more product into containers and trucks creates the largest savings. Other cost reductions can come from designing packaging to minimize the labor required and facilitate automation.
• Sustainability improvements associated with reductions in carbon emissions through less diesel fuel burned per unit. Material choices can also confer improvements to the overall footprint.

Read more about skinny design and how it can help maximize the volume of consumer products that make it onto shelves.

Learn more about McKinsey’s Operations Practice .

How can a company become a top design performer?

The average person’s standard for design is higher than ever. Good design is no longer just a nice-to-have for a company. Customers now have extremely high expectations for design, whether it’s customer service, instant access to information, or clever products that are also aesthetically relevant in the current culture.

McKinsey tracked the design practices of 300 publicly listed companies  over a five-year period in multiple countries. Advanced regression analysis of more than two million pieces of financial data and more than 100,000 design actions revealed 12 actions most correlated to improved financial performance. These were then clustered into the following four themes:

• Analytical leadership . For the best financial performers, design is a top management issue , and design performance is assessed with the same rigor these companies use to approach revenue and cost. The companies with the top financial returns have combined design and business leadership through bold, design-centric visions. These include a commitment to maintain a baseline level of customer understanding among all executives. The CEO of one of the world’s largest banks, for example, spends one day a month with the bank’s clients and encourages all members of the company’s C-suite to do the same.
• Cross-functional talent . Top-performing companies make user-centric design everyone’s responsibility, not a siloed function. Companies whose designers are embedded within cross-functional teams have better overall business performance . Further, the alignment of design metrics with functional business metrics (such as financial performance, user adoption rates, and satisfaction results) is also correlated to better business performance.
• Design with people, not for people . Design flourishes best, according to our research, in environments that encourage learning, testing, and iterating with users . These practices increase the odds of creating breakthrough products and services, while at the same time reducing the risk of costly missteps.
• User experience (UX) . Top-quartile companies embrace the full user experience  by taking a broad-based view of where design can make a difference. Design approaches like mapping customer journeys can lead to more inclusive and sustainable solutions.

What are some real-world examples of how design thinking can improve efficiency and user experience?

Understanding the theory of design thinking is one thing. Seeing it work in practice is something else. Here are some examples of how elegant design created value for customers, a company, and shareholders:

• Stockholm’s international airport, Arlanda, used design thinking to address its air-traffic-control problem. The goal was to create a system that would make air traffic safer and more effective. By understanding the tasks and challenges of the air-traffic controllers, then collaboratively working on prototypes and iterating based on feedback, a working group was able to design a new departure-sequencing tool  that helped air-traffic controllers do their jobs better. The new system greatly reduced the amount of time planes spent between leaving the terminal and being in the air, which in turn helped reduce fuel consumption.
• When Tesla creates its electric vehicles , the company closely considers not only aesthetics but also the overall driving experience .
• The consumer electronics industry has a long history of dramatic evolutions lead by design thinking. Since Apple debuted the iPhone in 2007, for example, each new generation has seen additional features, new customers, and lower costs—all driven by design-led value creation .

Learn more about our Consumer Packaged Goods  and Sustainability  Practices.

For a more in-depth exploration of these topics, see McKinsey’s Agile Organizations collection. Learn more about our Design Practice —and check out design-thinking-related job opportunities if you’re interested in working at McKinsey.

Articles referenced:

• “ Skinny design: Smaller is better ,” April 26, 2022, Dave Fedewa , Daniel Swan , Warren Teichner , and Bill Wiseman
• “ Product sustainability: Back to the drawing board ,” February 7, 2022, Stephan Fuchs, Stephan Mohr , Malin Orebäck, and Jan Rys
• “ Emerging from COVID-19: Australians embrace their values ,” May 11, 2020, Lloyd Colling, Rod Farmer , Jenny Child, Dan Feldman, and Jean-Baptiste Coumau
• “ The business value of design ,” McKinsey Quarterly , October 25, 2018, Benedict Sheppard , Hugo Sarrazin, Garen Kouyoumjian, and Fabricio Dore
• “ More than a feeling: Ten design practices to deliver business value ,” December 8, 2017, Benedict Sheppard , John Edson, and Garen Kouyoumjian
• “ Creating value through sustainable design ,” July 25, 2017, Sara Andersson, David Crafoord, and Tomas Nauclér
• “ The expanding role of design in creating an end-to-end customer experience ,” June 6, 2017, Raffaele Breschi, Tjark Freundt , Malin Orebäck, and Kai Vollhardt
• “ Design for value and growth in a new world ,” April 13, 2017, Ankur Agrawal , Mark Dziersk, Dave Subburaj, and Kieran West
• “ The power of design thinking ,” March 1, 2016, Jennifer Kilian , Hugo Sarrazin, and Barr Seitz
• “ Building a design-driven culture ,” September 1, 2015, Jennifer Kilian , Hugo Sarrazin, and Hyo Yeon

Want to know more about design thinking?

Related articles.

Skinny design: Smaller is better

The business value of design

More than a feeling: Ten design practices to deliver business value

Stage 2 in the Design Thinking Process: Define the Problem

Once you’ve empathized with your users, you can move on to the second stage of the design thinking process and define the problem your users need you to solve..

If you’ve read our introduction to User Experience (UX) Design , you’ll know that UX is essentially about solving the problems that prevent users from accomplishing what they want to do with our product.

Before you can go into problem-solving mode, however, there is one very crucial step that you need to complete—one that will shape your entire design project from start to finish. In the Design Thinking process , this step is what’s known as the “define” stage.

As the second step in the Design Thinking process, the define stage is where you’ll establish a clear idea of exactly which problem you will solve for the user. You’ll then shape this into a problem statement which will act as your northern star throughout the design process.

In this guide, we’ll tell you everything you need to know about this stage in the Design Thinking process, as well as how to define a meaningful problem statement.

Here’s what we’ll cover:

• What is the define stage and why is it necessary?
• What is a problem statement?
• How to define a meaningful problem statement
• What comes after the define phase?

Before we dive in, though, if you’d like an overview of the entire Design Thinking process, check out this video:

1. What is the define stage and why is it necessary?

As the second step in the Design Thinking process, the define stage is dedicated to defining the problem: what user problem will you be trying to solve? In other words, what is your design challenge?

The define stage is preceded by the empathize phase , where you’ll have learned as much about your users as possible, conducting interviews and using a variety of immersion and observation techniques. Once you have a good idea of who your users are and, most importantly, their wants, needs, and pain-points, you’re ready to turn this empathy into an actionable problem statement.

The relationship between the empathize and define stages can best be described in terms of analysis and synthesis. In the empathize phase, we use analysis to break down everything we observe and discover about our users into smaller, more manageable components—dividing their actions and behaviour into “what”, “why” and “how” categories, for example. In the define stage, we piece these components back together, synthesising our findings to create a detailed overall picture.

Why is the define stage so important?

The define stage ensures you fully understand the goal of your design project. It helps you to articulate your design problem, and provides a clear-cut objective to work towards. A meaningful, actionable problem statement will steer you in the right direction, helping you to kick-start the ideation process (see Stage Three of the Design Thinking process ) and work your way towards a solution.

Without a well-defined problem statement, it’s hard to know what you’re aiming for. Your work will lack focus, and the final design will suffer. Not only that: in the absence of a clear problem statement, it’s extremely difficult to explain to stakeholders and team members exactly what you are trying to achieve.

With this in mind, let’s take a closer look at problem statements and how you can go about defining them.

2. What is a problem statement?

A problem statement identifies the gap between the current state (i.e. the problem) and the desired state (i.e. the goal) of a process or product . Within the design context, you can think of the user problem as an unmet need. By designing a solution that meets this need, you can satisfy the user and ensure a pleasant user experience.

A problem statement, or point of view (POV) statement, frames this problem (or need) in a way that is actionable for designers. It provides a clear description of the issue that the designer seeks to address, keeping the focus on the user at all times.

Problem or POV statements can take various formats, but the end goal is always the same: to guide the design team towards a feasible solution. Let’s take a look at some of the ways you might frame your design problem:

• From the user’s perspective: “I am a young working professional trying to eat healthily, but I’m struggling because I work long hours and don’t always have time to go grocery shopping and prepare my meals. This makes me feel frustrated and bad about myself.”
• From a user research perspective: “Busy working professionals need an easy, time-efficient way to eat healthily because they often work long hours and don’t have time to shop and meal prep.”
• Based on the four Ws—who, what, where, and why: “Our young working professional struggles to eat healthily during the week because she is working long hours. Our solution should deliver a quick and easy way for her to procure ingredients and prepare healthy meals that she can take to work.”

As you can see, each of these statements addresses the same issue—just in a slightly different way. As long as you focus on the user, what they need and why, it’s up to you how you choose to present and frame your design problem.

We’ll look at how to form your problem statement a little later on. Before we do, let’s consider some problem statement “do”s and “don’t”s.

What makes a good problem statement?

A good problem statement is human-centered and user-focused. Based on the insights you gathered in the empathize phase, it focuses on the users and their needs—not on product specifications or business outcomes. Here are some pointers that will help you create a meaningful problem statement:

• Focus on the user: The user and their needs should be front and center of your problem statement. Avoid statements that start with “we need to…” or “the product should”, instead concentrating on the user’s perspective: “Young working professionals need…”, as in the examples above.
• Keep it broad: A good problem statement leaves room for innovation and creative freedom. It’s important to keep it broad enough to invite a range of different ideas; avoid any references to specific solutions or technical requirements, for example.
• Make it manageable: At the same time, your problem statement should guide you and provide direction. If it’s too broad in terms of the user’s needs and goals, you’ll struggle to hone in on a suitable solution. So, don’t try to address too many user needs in one problem statement; prioritize and frame your problem accordingly.

Bearing these things in mind, let’s explore some useful methods for creating a meaningful problem statement.

3. How to write a meaningful problem statement

Writing a meaningful problem statement can be extremely challenging. How do you condense all the complexities of the user’s conscious and unconscious desires into one simple, actionable statement? Fortunately, there are some tried-and-tested methods that will help you do just that.

Space saturation and group

One of the first steps in defining a problem statement is to organize your findings from the empathize phase. Space saturation and group is a popular method used by design thinkers to collect and visually present all observations made in the empathize phase in one space. As the name suggests, you will literally “saturate” a wall or whiteboard with Post-It notes and images, resulting in a collage of artifacts from your user research.

As the Stanford d.school explains: “You space saturate to help you unpack thoughts and experiences into tangible and visual pieces of information that you surround yourself with to inform and inspire the design team. You group these findings to explore what themes and patterns emerge, and strive to move toward identifying meaningful needs of people and insights that will inform your design solutions.”

This method should involve anyone who took part in the empathize stage of the design project, and should take no longer than 20-30 minutes.

The four Ws

Asking the right questions will help you put your finger on the right problem statement. With all your findings from the empathize phase in one place, ask yourself the four Ws: Who , what , where , and why?

• Who is experiencing the problem? In other words, who is your target user; who will be the focus of your problem statement?
• What is the problem? Based on the observations you made during the empathize phase, what are the problems and pain-points that frequently came up? What task is the user trying to accomplish, and what’s standing in their way?
• Where does the problem present itself? In what space (physical or digital), situation or context is the user when they face this problem? Are there any other people involved?
• Why does it matter? Why is it important that this problem be solved? What value would a solution bring to the user, and to the business?

Approaching your observations with these four questions in mind will help you to identify patterns within your user research. In identifying the most prevalent issues, you’ll be one step closer to formulating a meaningful problem statement.

The five whys

Another question-based strategy, the five whys technique can help you delve deeper into the problem and drill down to the root cause. Once you’ve identified the root cause, you have something that you can act upon; somewhere specific to focus your problem-solving efforts.

Let’s take our previous example of the young working professional who wants to eat healthily, but finds it difficult to do so. Here’s how you might use the five whys to break the problem down and get to the root cause:

• Why is she not eating healthily? → She orders takeaway everyday.
• Why does she order takeaway everyday? → Her fridge and cupboards are empty.
• Why are the fridge and cupboards empty? → She hasn’t been grocery shopping in over a week.
• Why hasn’t she been grocery shopping? → She doesn’t have time to go to the supermarket.
• Why doesn’t she have time? → She works long hours and is exhausted.

The root cause here is a lack of time, so your solution might focus on efficiency and convenience. Your final problem statement might look something like this: “Young working professionals need a quick, convenient solution to eating healthily.”

4. What comes after the define phase?

By the end of the define phase, you’ll have turned your findings from the empathize stage into a meaningful, actionable problem statement. With your problem statement to hand, you’ll be ready to move on to the ideation phase , where you’ll turn your problem statement into “how might we” questions and generate as many potential solutions as possible.

As you move through the Design Thinking process, you’ll constantly refer back to your problem statement to make sure you’re moving in the right direction. A well-thought-out problem statement will keep you on track, help you communicate your objectives to key stakeholders, and ultimately lead you to that all-important user solution.

Want to learn more about designing user-friendly solutions? Check out these articles:

• UX Best Practices: How Can You Become A Better Designer?
• What Is User Experience Design? Everything You Need To Know To Get Started
• This Is Why Empathy Matters As A UX Designer
• What is lean UX?

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Stage 2 in the Design Thinking Process: Define the Problem and Interpret the Results

An integral part of the Design Thinking process is the definition of a meaningful and actionable problem statement, which the design thinker will focus on solving. This is perhaps the most challenging part of the Design Thinking process, as the definition of a problem (also called a design challenge) will require you to synthesise your observations about your users from the first stage in the Design Thinking process, which is called the Empathise stage.

When you learn how to master the definition of your problem, problem statement, or design challenge, it will greatly improve your Design Thinking process and result. Why? A great definition of your problem statement will guide you and your team’s work and kick start the ideation process in the right direction. It will bring about clarity and focus to the design space. On the contrary, if you don’t pay enough attention to defining your problem, you will work like a person stumbling in the dark.

In the Define stage you synthesise your observations about your users from the first stage, the Empathise stage. A great definition of your problem statement will guide you and your team’s work and kick start the ideation process (third stage) in the right direction. The five stages are not always sequential — they do not have to follow any specific order and they can often occur in parallel and be repeated iteratively. As such, the stages should be understood as different modes that contribute to a project, rather than sequential steps.

Analysis and Synthesis

Before we go into what makes a great problem statement, it’s useful to first gain an understanding of the relationship between analysis and synthesis that many design thinkers will go through in their projects. Tim Brown, CEO of the international design consultancy firm IDEO, wrote in his book Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation , that analysis and synthesis are “equally important, and each plays an essential role in the process of creating options and making choices.”

Analysis is about breaking down complex concepts and problems into smaller, easier-to-understand constituents. We do that, for instance, during the first stage of the Design Thinking process, the Empathise stage, when we observe and document details that relate to our users. Synthesis , on the other hand, involves creatively piecing the puzzle together to form whole ideas. This happens during the Define stage when we organise, interpret, and make sense of the data we have gathered to create a problem statement.

Although analysis takes place during the Empathise stage and synthesis takes place during the Define stage, they do not only happen in the distinct stages of Design Thinking. In fact, analysis and synthesis often happen consecutively throughout all stages of the Design Thinking process. Design thinkers often analyse a situation before synthesising new insights, and then analyse their synthesised findings once more to create more detailed syntheses.

What Makes a Good Problem Statement?

A problem statement is important to a Design Thinking project, because it will guide you and your team and provides a focus on the specific needs that you have uncovered. It also creates a sense of possibility and optimism that allows team members to spark off ideas in the Ideation stage, which is the third and following stage in the Design Thinking process. A good problem statement should thus have the following traits. It should be:

Human-centered. This requires you to frame your problem statement according to specific users, their needs and the insights that your team has gained in the Empathise phase. The problem statement should be about the people the team is trying to help, rather than focusing on technology, monetary returns or product specifications.

Broad enough for creative freedom. This means that the problem statement should not focus too narrowly on a specific method regarding the implementation of the solution. The problem statement should also not list technical requirements, as this would unnecessarily restrict the team and prevent them from exploring areas that might bring unexpected value and insight to the project.

Narrow enough to make it manageable. On the other hand, a problem statement such as , “Improve the human condition,” is too broad and will likely cause team members to easily feel daunted. Problem statements should have sufficient constraints to make the project manageable.

As well as the three traits mentioned above, it also helps to begin the problem statement with a verb, such as “Create”, “Define”, and “Adapt”, to make the problem become more action-oriented.

How to Define a Problem Statement

Methods of interpreting results and findings from the observation oriented Empathise phase include:

Space Saturate and Group and Affinity Diagrams – Clustering and Bundling Ideas and Facts

In space saturate and group, designers collate their observations and findings into one place, to create a collage of experiences, thoughts, insights, and stories. The term 'saturate' describes the way in which the entire team covers or saturates the display with their collective images, notes, observations, data, experiences, interviews, thoughts, insights, and stories in order to create a wall of information to inform the problem-defining process. It will then be possible to draw connections between these individual elements, or nodes, to connect the dots, and to develop new and deeper insights, which help define the problem(s) and develop potential solutions. In other words: go from analysis to synthesis.

Empathy Mapping

An empathy map consists of four quadrants laid out on a board, paper or table, which reflect the four key traits that the users demonstrated/possessed during the observation stage. The four quadrants refer to what the users: Said , Did , Thought , and Felt . Determining what the users said and did are relatively easy; however, determining what they thought and felt is based on careful observation of how they behaved and responded to certain activities, suggestions, conversations etc. (including subtle cues such as body language displayed and the tone of voice used).

Point Of View – Problem Statement

A Point Of view (POV) is a meaningful and actionable problem statement, which will allow you to ideate in a goal-oriented manner. Your POV captures your design vision by defining the RIGHT challenge to address in the ideation sessions. A POV involves reframing a design challenge into an actionable problem statement. You articulate a POV by combining your knowledge about the user you are designing for, his or her needs and the insights which you’ve come to know in your research or Empathise mode. Your POV should be an actionable problem statement that will drive the rest of your design work.

You articulate a POV by combining these three elements – user, need, and insight. You can articulate your POV by inserting your information about your user, the needs and your insights in the following sentence:

[ User . . . (descriptive)] needs [ need . . . (verb)] because [ insight. . . (compelling)]

“How Might We” Questions

When you’ve defined your design challenge in a POV, you can start to generate ideas to solve your design challenge. You can start using your POV by asking a specific question starting with: “ How Might We ” or “in what ways might we”. How Might We ( HMW ) questions are questions that have the potential to spark ideation sessions such as brainstorms. They should be broad enough for a wide range of solutions, but narrow enough that specific solutions can be created for them. “How Might We” questions should be based on the observations you’ve gathered in the Empathise stage of the Design Thinking process.

For example, you have observed that youths tend not to watch TV programs on the TV at home, some questions which can guide and spark your ideation session could be:

How might we make TV more social, so youths feel more engaged?

How might we enable TV programs to be watched anywhere, at anytime?

How might we make watching TV at home more exciting?

The HMW questions open up to Ideation sessions where you explore ideas, which can help you solve your design challenge in an innovative way.

Why-How Laddering

"As a general rule, asking 'why’ yields more abstract statements and asking 'how’yields specific statements. Often times abstract statements are more meaningful but not as directly actionable, and the opposite is true of more specific statements." – d.school, Method Card, Why-How Laddering

For this reason, during the Define stage designers seek to define the problem, and will generally ask why . Designers will use why to progress to the top of the so-called Why-How Ladder where the ultimate aim is to find out how you can solve one or more problems. Your How Might We questions will help you move from the Define stage and into the next stage in Design Thinking, the Ideation stage, where you start looking for specific innovative solutions . In other words you could say that the Why-How Laddering starts with asking Why to work out How they can solve the specific problem or design challenge.

The Take Away

The second stage in a typical Design Thinking process is called the Define phase. It involves collating data from the observation stage (first stage called Empathise ) to define the design problems and challenges. By using methods for synthesising raw data into a meaningful and usable body of knowledge — such as empathy mapping and space saturate and group — we will be able to create an actionable design problem statement or Point of View that inspire the generation of ideas to solve it. The How Might We questions open up to Ideation sessions where you explore ideas, which can help you solve your design challenge in an innovative way.

References & Where to Learn More

Course: “Design Thinking - The Ultimate Guide” .

d.school: Space Saturation and Group .

d.school: Empathy Map .

d.school: “How might we” questions .

Hero Image: Author/Copyright holder: gdsteam. Copyright terms and licence: CC BY 2.0

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How to create a design thinking problem statement to keep your product on track

We’ve all had days when we can’t decide what music mood we’re in, so we repeatedly hit 'skip' until the car ride is over. When we don’t know what we want, we can’t make a decision. 

For product teams, writing a design thinking problem statement isn’t all that different. 

If you don’t set a direction early in the design thinking process, you and your team will work in circles without any satisfaction or progress. But when you set the tone of your process early on, your team gets into the groove to create a user-first product. 

Last updated

Reading time.

Your design thinking problem statement needs to strike the right balance between focused and flexible to be effective.

This chapter of the design thinking guide reviews design thinking problem statement examples and strategies that will help your team work effectively to create products your users will love. 

Seeing is understanding

Stop guessing: let users show and tell you what they need with insights from Heatmaps, Recordings, and Feedback.

What is a design thinking problem statement?

A design thinking problem statement is a concise and actionable sentence or question that defines your UX purpose and direction. Product teams using design thinking develop problem statements to simplify complex problems and identify the gap between what your product has and what your users need .

Since the design thinking process is non-linear, a consolidated problem statement is essential to improve team collaboration and stay on task. Your problem statement is also helpful in getting stakeholder buy-in for new initiatives or for planning human-centered design products. 

5 examples of design thinking problem statements

Finding design thinking problem statement examples can be tricky since they're not always made public—but that won’t stop us! Let’s review five product design examples and case studies to break down their hypothetical problem statements. 

The following examples will use this problem statement formula: (User) needs a way to (outcome) because (driver). Since UX opportunities come in all shapes and sizes, we have more problem statement formulas further down on the page. 

1. Audiense

Problem: the Audiense team noticed a sudden uptick in people exiting the sign-up process without completing it. 

Example problem statement: New customers need an easier way to complete the sign-up process because they’re getting frustrated during the account setup.  

Solution: Juan Fernandez, Head of Product, used Hotjar Session Recordings to review failed sign-ups and saw that the password validator feature was broken. After they fixed the validator, sign-up rates increased.

Read Audiense's full story here.

2. Zenprint

Problem: the Zenprint team used Google Analytics to compare bounce rates across pages to discover which steps in the ordering process were underperforming. 

Example problem statement: Potential customers need a clearer understanding of next steps because the current page has a high bounce rate.

Solution: the team used Hotjar Heatmaps to see where people spent most of their time on a page, and assessed whether they should spend time there or not. They witnessed users lingering on the pricing page, so they A/B tested the page's UX design. Ultimately, they chose a design that provides clear steps on how to proceed when users hover over a price. As a result, Zenprint's team decreased the drop-off rate of the problematic page by 7% and increased conversions by 2%.

Read Zenprint's full story here.

3. Razorpay

Problem: Razorpay redesigned their dashboard and incrementally released it to small user segments. When users rated the design as 6.2/10, they knew they needed to improve it. 

Example problem statement: Users want an updated dashboard because they’re unhappy with the current version. 

Solution: traditional analytics showed the Razorpay team that engagement with the new dashboard was dropping, but they didn’t know why. They asked users who provided a low rating on the dashboard to explain their feelings in an open-ended survey. Based on user feedback, they improved the dashboard design, which resulted in a 40% increase in satisfaction.  

Read Razorpay's full story here.   

4. Spotahome

Problem: Spotahome heard from a segment of users that updating the in-app calendar was difficult, but the team wasn’t sure what the problem was. 

Example problem statement: The landlord user segment needs a simpler way to use the calendar function, but the cause of frustration is unclear. 

Solution: the team watched Hotjar Recordings to spot the features users struggled with, which convinced the product team to rework a solution and make the calendar easier for landlords to use. 

Read Spotahome's full story here.

Problem: Yatter is a lead generation agency that wanted to increase conversions on a client’s stem cell therapy website. Recordings revealed that visitors would diligently read the text describing the therapy but then exit the page, leading the agency to believe visitors didn’t trust the company. 

Example problem statement: Users need to see social proof because they don’t believe our information is trustworthy. 

Solution: the team used Hotjar Heatmaps to identify their most popular case studies, and placed them at the top of the sales page. After adding the case studies, the page’s conversion rate increased by 10%. 

Read Yatter's full story here.

3 steps to create a design thinking problem statement

Writing an effective design thinking problem statement requires research and brainstorming before you begin. 

Let's go through the three steps to create a problem statement with a mock project management software company to make the process easier to grasp.

1. Identify

Ongoing product discovery is the basis for design thinking problem statements.  

Establishing a product experimentation culture or sending out surveys about a particular job-to-be-done (JTBD) gives you a starting point. Ask yourself: what problems are users facing, and which are most important to them? How can we create customer delight ?

For our mock project management company, identifying user problems could look like this:

A product manager (PM) regularly reviews recordings of new users going through product onboarding. The PM notices that a particular user segment drops off more than others at Step 3 of onboarding, which is to migrate tasks from their current project management software into the new dashboard. 

The product team sends a survey to this user segment with open-ended questions to learn about their goals and challenges. 

💡 Pro tip: use the JTBD framework to stop assuming and start asking.

Kyle Luther Anderson , a product management leader and coach, explained that product teams use the jobs-to-be-done framework to identify, then confirm or deny, user assumptions. He says:

“Your organization has assumptions about what the customer wants, about their unmet needs, and what your customer considers a successful outcome. Oftentimes an org doesn't state assumptions explicitly, and many companies are pretty bad about putting those assumptions to the test. The value of using the JTBD framework is what comes from those questions you ask, what you learn in unbiased research, and really focusing on the customer problem or opportunity.”

Learn more about the JTBD framework here.

After identifying an opportunity, you need to investigate further to understand potential causes or paths forward. Nasko Terziev, a Senior Product Designer at Hotjar, recommends teams think of the product narrative and end-to-end user journey to home in on critical moments.

Where are the moments we are doing well? Where are the moments we are not doing well? We can build those moments into a framework that the whole company can contribute to with this storytelling approach. Get the storyboards and feed data from analytics, sales, customer success, and support.

Here’s how our mock project management app could approach this step:

Reference their previous onboarding flow plans

Look for UX trends in session recordings

Gather user feedback on the frustrating points

✍️ Class is in session!

Hotjar has free courses for product managers and UX designers. 

Learn how to find insights in Recordings or reveal patterns in Heatmaps , then use what you’ve learned to conduct research for your design thinking problem statement.

Now it’s time to consolidate everything into a design thinking problem statement. Here are five formulas you can use as a starting point:

(User) needs a way to (outcome) because (driver). For example: new users need a way to quickly migrate tasks because they'll cancel their trial if onboarding takes too long.

(Audience) wants (outcome), so we will deliver (product) to achieve (result). For example: new users want to add existing projects to their new account quickly, so we’ll create a way to import data so they spend less time onboarding.

‘How might we’ statement. For example: how might we make adding existing project information faster?

Our users want to (task). How can our product achieve (result)? For example: new users want to add current projects to the app. How can our product make setup easy and enjoyable?

Who, what, where, why. For example: new users want to migrate projects, but they’re dropping off at the current step because input options are limited.

Be open to adjusting your problem statement as you learn

Before we send you off to write the next great design thinking problem statement, we leave you with a few words of advice: be flexible and stay curious—your problem statement should leave room for imagination, experimentation, and change.

FAQs about design thinking problem statements

A design thinking problem statement is a tool used in the design thinking process to help product teams and UX designers establish their focus and direction. A practical problem statement gives teams the opportunity to start brainstorming and testing solutions, and is also helpful for communicating ideas to get stakeholder buy-in.

What are some design thinking problem statements?

Design thinking problem statements can take multiple forms. For example:

(User) needs a way to (outcome) because (driver)

(Audience) wants (outcome), so we will deliver (product) to achieve (result)

‘How might we’ statements

Our users want to (task). How can our product achieve (result)?

Who, what, where, why statements

How do you write a design thinking problem statement?

Teams need to complete three steps to create a design thinking problem statement:

Identify user challenges or opportunities.

Investigate the drivers and hurdles for those goals.

Combine the information into a sentence or question that summarizes the situation and has a prompt for thinking of solutions.

Examples of design thinking

Previous chapter

Human-centered design thinking

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Design Thinking

What makes design thinking different.

Traditional courses progress the student learning from conceptual understanding towards demonstrations of skill and capacity in a linear, topically focused manner. Setting this scaffolding is set in place, fixes the problems, and the solutions are typically within a known range. But many course problems are research questions that defy simple explanations or right/wrong answers. For these courses, need a more dexterous approach. 

In Design Thinking, they are discovering knowledge through exploration. Students help define the problems, identify and develop potential solutions, and determine ways to assess the work. Instructors serve as facilitators and advisors to this learning. Embedded throughout the process is capacity-building through linked-learning experiences, collaborative exercises, and creative problem-solving [iii] . Learning often involves hands-on experiences focused on real-world challenges. By centering course activities around a problem and generating creative solutions, these courses support the development of essential competencies such as critical thinking, reflective learning, adaptability, effective collaboration, and systems thinking.

The Design Thinking Multi-Stage Model

Discovery (empathy, research, and problem definition), ideation (interpret, create, and make), experimentation (prototype, test and evaluate), evolution (re-think, re-make, repeat), deployment (socialize, pilot, and integrate).

The first stages are directed towards understanding and defining potential problems for solutions by asking, “What Is It?” The requisite foundation for all other design thinking stages is the ability to generate informed and empathetic work during this stage. How? Through literature reviews and consultations with experts along with the combined observations and engagements with people and physical environments relevant to the topic. Information gathered and documented during this stage can be aligned with course objectives and assessments. Students will gain a deeper understanding of the issues throughout the process.

Upon completing the information gathering, teams organize, interpret, and make sense of the data to define a problem scope. Doing so requires both analysis (i.e., breaking down complex concepts) and synthesis (i.e., creatively piecing information together to form whole ideas). A good problem statement should be human-centered, broad enough for creative freedom, but narrow enough to be manageable. As a general rule, consider using the Stanford d. school “Why-How Ladder” (a variation of the Sakichi Toyoda “5 Whys” technique) to refine the problem statement and to suggest how to move forwards with design problem-solving.

Unlike the traditional project-based learning method, instructors do not define the problem in design thinking. They can, and should, define a scope, but defining the actual problem is part of the student responsibility. 

At this stage, students interpret their research into a range of creative ideas and potential solutions. This step starts the “What If?” phase of the work. Instructors should encourage enthusiasm and collaborative participation by incorporating active-learning methods, visualization techniques of “systems-thinking,” and other image-oriented methods to document brainstorming.

Expert guidance is required to maintain enthusiasm in the ideation process by guiding proposals and bringing focus to the expectations. Instructors suggest practices to enhance the solutions and temper expectations (e.g., “your solution won’t solve world hunger as you proposed, but it can make a difference in one stage of food production—let’s use that to refocus the design effort.” Eventually a more narrow range of possible solutions is identified, and the work of making/designing begins.

In this stage, ideas become manifest. Students are deciding how and what to produce is of central importance. Iteration is essential. Align activities with course objectives and professional practice models. As ideation moves into prototyping, the expectation is that student groups produce several scaled-down versions or features of the final solution. Doing so allows students to understand better the constraints and benefits inherent to the solutions they’ve designed. The introduction of new tools and skills can occur during this stage, along with emphasizing collaborative efforts. 

Experimentation is only complete when identifying problems by breaking the project down through evaluation.

This process looks for failures and revelations that emerge through testing; profound learning opportunities arise when solutions don’t meet their objectives. 

Learning how to define and evaluate the relative value and efficacy of the prototypes follows is an essential skill. Students often return to the Discovery stage to identify the proper standards for evaluating success (Who does it work for? Does it work in the way you intended? How would you know?). At this stage, instructors can show how practical conditions affect evaluation (industry standards, code requirements, etc.) and how exigent forces would affect the solution (e.g., broader economic, sociological, and cultural conditions).

This stage isn’t the end of the process; ultimately, testing is a generative process for redesign as it reveals opportunities for improvement. By trying to determine how and why specific solutions are rejected, improved, or accepted, students develop clarity of how real users would behave, think, and feel when interacting with the solution. At this stage, alterations and refinements are expected to be more mature and technically developed. Collaborations may be extended into communities to expand testing and assessment.

The multi-stage process implies a linear direction of progress, but designing and learning are inherently more unpredictable, so the model is flexible. Information learned from testing helps refine the problem definition and the overall design. There is a perpetual loop of feedback. Ultimately, solutions are evolved and improved through reiteration and repetition, as fewer factors are considered for each iteration.

The challenge of design thinking is often knowing when this evolutionary process of redesigning is “done.” Solving a problem, particularly a vexing one, is unlikely within the constraints of school. Academic calendars and restrictions are quite different from practice, so there are often situations in which a “good enough for now” scenario is the goal.

Ideally, of course, the process can spark an interest in students to continue a life-long engagement in these research projects. This process is ultimately about joining on-going conversations and searching for new knowledge through design solutions. It isn’t about resolution. The passion of the search is what is essential to teach and learn.

Specific projects may have the opportunity to develop into real-world solutions. This stage of deployment focuses on ways that solutions become tangible, actionable, and ready for use. In the socializing phase, the ideas develop to the degree that buy-in occurs and teams built around the solution. This phase relies on the ability to tell compelling stories about the solution. Because these stories have naturally developed through a rigorous Design Thinking process, it is relatively easy to build a narrative around a solution based on the process.

In the piloting phase, the solution is introduced to a predetermined group to gain real-world feedback and reviews. Depending on the solution’s stage and scope, this may occur at a smaller scale during prototyping. In this phase, the focus is on identifying barriers to implementation of use and integration. Depending on the solution, these barriers to production and method may be profound. This work takes in-depth expertise and cross-disciplinary collaborations to understand markets, supply-chains, production, delivery models, and how the solution will enhance or disrupt existing models.

What is the Difference between Project-Based Learning (PBL), Understanding by Design (UbD), and Design Thinking (DT)?

Project-based learning (PBL) is a broader category of educational activities in which curricular activities are all centered around sustained engagement with a problem or project. Using PBL, a potentially important study narrowed down into a series of discrete activities using student-directed learning. A PBL approach can closely align with curricular checkpoints by defining a path of inquiry and production through essential guiding questions and required deliverables.

The Understanding by Design (UbD) model, is similar to PBL in its use of creative problem solving as the central learning activity. It differs mostly in the way of evaluating success. In UbD, educators help define the problem and develop a process of design-learning with the final result. In some courses, particularly those with complex topics, there may not be a readily available answer. The problem itself may not be easily defined, which complicates the PBL and UbD model.

Design Thinking is intentionally more open-ended than these other options. Students help to define the problem based on a generative topic that opens an area of research. Students are encouraged to align what they produce with their broader research questions. Assessment is related to prototyping and rebuilding intended to promote creative risk-taking.

Design Thinking Resources for Educators

• Kelley, T. (2016). The Art Of Innovation . London: Profile Books.
• O’Donnell Wicklund Pigozzi Peterson, Architects Inc, VS Furniture, & Bruce Mau Design. (2010). The third teacher : 79 ways you can use design to transform teaching & learning / OWP/P Architects, VS Furniture, Bruce Mau Design . New York: Abrams.
• Weinschenk, S. (2015). 100 MORE Things Every Designer Needs to Know About People (1st ed.) . New Riders.

Manuals / Toolkits

• IDEO.org. (2015). T he Field Guide to Human-Centered Design (Community Engagement Manual) . Retrieved from https://www.designkit.org/
• Riverdale Country School & IDEO.org. (2019). Design Thinking for Educators Toolkit (2 nd Edition). Retrieved from https://www.ideo.com/post/design-thinking-for-educators/

Organizations

• Institute of Design at Stanford (d.School) website  (Hasso-Plattner)
• RED lab: Research in Education and Design website (Stanford School of Education)
• TD4Ed: Teachers Design for Education website (Business Innovation Factory)
• Edutopia, Design Thinking Video Collection
• Design Thinking For Educators”  context  /  profession  /  practice  /  mindse

[i] Tim Brown, “Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation,” Harper Business, 2009. https://designthinking.ideo.com

[ii] Hasso-Plattner Institute of Design (d.school) at Stanford, “Design Thinking Mix Tapes,” 2018. https://dschool.stanford.edu/resources/chart-a-new-course-put-design-thinking-to-work

[iii] IDEO, “Design Thinking for Educators Toolkit” (2 nd Edition), IDEO + Riverdale Country School, 2019. https://www.ideo.com/post/design-thinking-for-educators

[iv] Herbert Simon, The Sciences of the Artificial (3 rd Ed.), 1996

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• Published: 10 June 2024

A meta-analysis of the effects of design thinking on student learning

• Qing Yu   ORCID: orcid.org/0000-0003-1889-1481 1 ,
• Kun Yu 1 &
• Rongri Lin 1  

Humanities and Social Sciences Communications volume  11 , Article number:  742 ( 2024 ) Cite this article

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Design thinking (DT) is becoming an innovative and popular teaching method. Recently, DT has been used as an unconventional method to develop skills of problem-solving, creativity, and innovation. However, its effects on student learning are unclear . This research aimed to examine the DT’s effects on student learning. The meta-analytic result based on 25 articles showed that DT positively affected student learning ( r  = 0.436, p  < 0.001). Moreover, the learning outcome, treatment duration, grade level, DT model, and region had moderating effects. Additionally, moderator analysis suggested that DT instruction was more effective: (1) when class size is <=30; (2) on multidiscipline; (3) with long-term duration (>=3 months); (4) for secondary school and university students; (5) on student learning engagement, motivation, problem-solving skills, and academic achievement; (6) with the model of Observe, Synthesize, Ideate, and Prototype, and Empathize, Define, Ideate, Prototype, Test; (7) when team size is <=7; (8) on African and Asian students.

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Introduction.

Design thinking (DT) is attracting more and more attention and interest worldwide (Aris et al., 2022 ). DT was introduced by Rowe ( 1987 ) and was first applied in education in 2005 (Çeviker-Çınar et al., 2017 ). Today, DT has been widely applied in nearly all stages of education (Pande and Bharathi, 2020 ), from formal to informal educational contexts (Aris et al., 2022 ). DT is a process, a method (Rowe, 1987 ), or a “philosophy” (Çeviker-Çınar et al., 2017 ). In education, DT is a teaching method and a learning orientation that enables learners to generate creative ideas and impactful change and actively explore problem solutions (Beckman and Barry, 2007 ; Lor, 2017 ; Retna, 2016 ). DT can help solve many fundamental educational issues (Koh et al., 2015 ). However, previous studies did not reach consensus about DT’s effects on student learning. Moreover, eliciting DT is not always easy because of its complexity and open-endedness (Becker and Mentzer, 2015 ). Therefore, this study carried out a meta-analysis to examine the relationship between DT and student learning.

Conceptual framework

Design thinking.

DT has various definitions. The most widely used definition in education is proposed by Razzouk and Shute ( 2012 ): “an analytic and creative process that engages a person in opportunities to experiment, create and prototype models, gather feedback, and redesign.” DT is a promising, practical method that can be applied to education (Brown, 2008 ; Rusmann and Ejsing-Duun, 2022 ). It is often integrated into the teaching process as an instructional method. DT consists of a set of logically organized stages or processes, each pointing to cultivating students’ key competencies. When students are engaged in DT instruction, they need to follow DT’s steps to move forward with their projects, thereby increasing their ability to perform better. DT also points to addressing problems in real situations (Xu et al., 2024 ), which could increase their interest, motivation, and engagement (Grau and Rockett, 2022 ; Lin et al., 2020a ). In sum, DT has become a dynamic, nonlinear, and spiraling process that can facilitate deep learning (Liu and Li, 2023 ) and eventually result in better student performance (Howard et al., 2021 ).

DT emphasizes learner-centeredness (Glen et al., 2014 ), which can help teachers and students cope with 21st century challenges and complex real-world problems (Gleason and Jaramillo Cherrez, 2021 ; Xu et al., 2024 ; Yande, 2023 ). For teachers , DT provides a framework for solving complex and emerging problems (Henriksen et al., 2020a ); DT also provides good solution strategies and guidance for teachers to design innovative instruction and improve instruction. For students , DT can improve students’ class participation and learning intention, create favorable atmospheres and enjoyment, enhance interaction between each other and creative confidence, deepen their discussion on projects, and eventually improve teachers’ instruction (Balakrishnan, 2022 ; Tu et al., 2018 ). Moreover, DT can also nurture the competencies necessary for students, such as communication, collaboration, teamwork, problem-solving skills, creativity, empathy, critical thinking, and metacognition (Abolhasani et al., 2021 ; Balakrishnan, 2022 ; Guaman-Quintanilla et al., 2023 ; Retna, 2016 ; Rusmann and Ejsing-Duun, 2022 ). In general, the value of DT in education is to help students grow, empower teachers’ development, and promote teaching change.

DT has gradually become the new normal, with students readily embracing the DT process and appreciating its merits (Retna, 2016 ). Meanwhile, a variety of DT models are proposed for use in different domains. Simon ( 1969 ) proposed the first DT model, which entails a one-way linear process of three steps: analysis, synthesis, and evaluation. The most widely applied model in education is that of the Stanford model (Liu et al., 2024a ), which has five stages: empathize, define, ideate, prototype, and test (EDIPT) (Plattner, 2009 ), especially in school and university educational settings. IDEO ( 2013 ) defined five stages of DT for educators: discovery, interpretation, ideation, experimentation, and evolution. To apply DT in K-12 (Liu and Li, 2023 ), Carroll et al. ( 2010 ) extend the EDIPT model to six stages, e.g., understand, observe, point of view, ideate, prototype, and test. Brown’s DT model has been widely used, with three stages: inspiration, ideation, and implementation (Brown, 2008 ). The Design Council’s DT model assists designers or non-designers in solving some of the most complex social, economic, and environmental problems. It has four stages: discover, define, develop, and implement (Design Council, 2015 ). The DT model selected should aim to meet both students’ needs and instructional goals (Brannon, 2022 ). It should be noted that the processes contained in different DT models may vary and therefore produce different results.

DT’s effects and research gaps

Recently, there have been gradually increasing explorations to investigate the impacts of DT on students’ learning performance in education. However, there is no consensus on the effectiveness of DT. The results can be classified into three types: (a) DT can promote students’ learning significantly (Albay and Eisma, 2021 ; Bawaneh and Alnamshan, 2023 ; Chang and Tsai, 2021 ; Dawbin et al., 2021 ; Hsiao et al., 2017 ; Kuo et al., 2022 ; Ladachart et al., 2022 ; Lin et al., 2020a ; Liu and Ko, 2021 ; Nazim and Mohammad, 2022 ; Padagas, 2021 ; Pratomo and Wardani, 2021 ; Simeon et al., 2022 ; Tsai, 2015 ; Ziadat and Sakarneh, 2021 ); (b) DT does not significantly enhance student learning (Khongprakob and Petsangsri, 2022 ; Kuo et al., 2022 ; Lin et al., 2020b ; Yalçın and Erden, 2021 ); (c) there are negative correlations between DT and learning outcomes (Chou and Shih, 2022 ; Lake et al., 2021 ).

It can be seen that DT’s effectiveness is still questionable . DT is an emerging topic that needs in-depth investigation (Baker III and Moukhliss, 2020 ). Some research gaps need to be addressed urgently. First , it lacks specific guidance and references on DT instruction. In-service teachers are unfamiliar with DT (Bressler and Annetta, 2022 ; Liu et al., 2024a ), which may reduce DT’s effects. Students may also undergo confusion and frustration when participating in DT courses (Glen et al., 2015 ; Razali et al., 2022 ). Therefore, it is crucial to explore where the DT approach may be more appropriate for the classroom setting (Lor, 2017 ). For instance, what is the most effective class size, team size, duration, or DT model? Second , DT’s effects are questioned (Rao et al., 2022 ). Namely, a systematic assessment of DT’s effectiveness is limited (Liedtka, 2015 ). There is no meta-analysis to deliver robust evidence on the effectiveness of DT in education. To summarize, with DT’s widespread introduction into education, performing a meta-analysis to reveal DT’s overall effects on student performance and possible influencing moderators is necessary and valuable.

Research purpose

Considering that there is no quantitative, comprehensive evidence on DT’s effects in education, we tried to solve the following questions:

RQ1 . What are the research characteristics of the included empirical studies of DT on student learning (e.g., publication year, research design, class size, grade level, duration, subject, team size, DT model, and region/countries)?

RQ2 . What is the overall effect of DT on student learning?

RQ3 . What are the DT’s effects on student learning under the potential moderators (e.g., learning outcome, class size, grade level, duration, subject, team size, DT model, and region)?

Compared to a mere literature review, meta-analysis can provide precise quantitative effects (Grant and Booth, 2009 ). Meta-analysis can integrate various empirical research results to calculate the overall effect value (Lipsey and Wilson, 2001 ). This research was conducted based on the process proposed by Field and Gillett ( 2010 ).

Literature searching

We mainly retrieved the documents from the Web of Science (Core Collection), Scopus, and Google Scholar. Some topic words, i.e., (“Design Thinking”) AND (“Learning Performance” OR “Learning Outcomes” OR “Academic Achievement” OR “Academic Performance”), were combined to search for the target documents. The search span was confined from January 2005 to June 2023. 1204 articles were retrieved preliminarily through the search, and 1059 articles were obtained after removing duplicated literature.

Selecting criteria and process

We selected literature based on the below criteria:

(1) It must report the relationship between DT and student learning performance;

(2) It must be empirical studies (experimental, quasi-experimental, or correlational research);

(3) The research participants should receive intervention through DT teaching;

(4) It should provide necessary data for calculating effect sizes in targeted papers (e.g., sample size, mean, standard deviation, the value of t or p );

(5) It should be peer-reviewed and published in English .

After the initial of screening of titles and abstracts and the removal of duplicates, 296 articles were selected. Whole-text articles were initially assessed for eligibility, and 84 articles that met the inclusion criteria remained. Finally, after the articles were read in full, 25 peer-reviewed studies were obtained. The literature searching and selection were conducted strictly according to the standard processes (Moher et al., 2009 ) (Fig. 1 ).

Flow diagram.

Literature Quality and Bias Assessment

One database cannot include all the published literature, so searching multiple authoritative databases can control the literature search bias (Stang, 2010 ). Higgins et al. ( 2019 ) recommend searching at least two databases. So, we selected three databases to reduce the search literature search bias (Kelley and Kelley, 2019 ).

The included criteria’s inaccuracy will result in literature selection bias (Sterne et al., 2016 ). We strictly drew up the selection criteria to reduce this bias, e.g., study purpose and design, intervention of DT, and published language (Liu et al., 2024b ).

We assessed the literature quality based on the criteria of Downs and Black ( 1998 ), which have 27 questions and five categories. We found that all selected studies got majority points in more than four of the above categories (range 18 to 21), so they were high-quality (Carter et al., 2017 ).

Coding potential moderators

Moderators are possible factors that influence DT’s effects. The eight moderators were divided into the background and method.

Background moderators

Learning outcome: DT’s learning outcomes are less examined. Examining DT’s effectiveness on different learning outcomes is necessary (Razzouk and Shute, 2012 ). It was coded into academic achievement, self-efficacy, learning motivation, problem-solving ability, creative thinking, and learning engagement.

Treatment duration: The DT process could take a long time to explore (Carroll et al., 2010 ), and it may moderate DT’s effect on learning. It was divided into <1, 1–3, and >3 months.

Class size: It is an important index of teaching effects (Retna, 2016 ). So, it may moderate DT’s effect on student learning. It was divided into 1–30, 31–50, 51–100, and >100.

Grade level: There should be a clear distinction regarding how DT is applied to different learning stages (Lor, 2017 ). It was divided into kindergarten, primary, junior high, high school, and university.

Subject: DT was not always useful across all subjects (Retna, 2016 ), and van de Grift and Kroeze ( 2016 ) found that it could enhance interdisciplinary education. Namely, the subject may moderate DT’s effects. It was divided into STEM, No-STEM, and multidiscipline.

Region: It refers to the area where the study was performed. The education system’s cultural context must also be considered when applying DT (Retna, 2016 ). So, the region is also considered a potential moderator. It was divided into Asia, America, Austria, Europe, and Africa.

Method moderators

DT model: It refers to DT’s specific processes or stages. The implementation of DT relies on specific models, and different models contain different operations. Therefore, the role of DT models should be considered. We coded the DT model into 9 types:

3IE =Inspiration, Ideation, Implementation, and Evaluation;

UOPIPT =Understand, Observe, Perspective, Imagination, Prototype, and Test;

EDIPT =Empathize, Define, Ideate, Prototype, and Test;

EDEIPT =Empathize, Define, Elaborate, Ideate, Prototype, and Test;

OSIP =Observation, Synthesis, Ideation, and Prototype;

PAS =Preparation, Assimilation, Strategic control;

2UPPI =User focus (User as an information source and User as a codeveloper), Problem framing, Prototype, and Iteration;

CTC =Copy, Tinker, and Create;

LAUNCH =Look, listen and learn, Ask, Understand, Navigate ideas, Create, and Highlight and fix.

Team size: This variable refers to the number of team members. DT pedagogy emphasizes the use of student teams (Beckman and Barry, 2007 ), and team size is one of the causes of conflicts around teamwork (Aflatoony et al., 2018 ). So, the team size may moderate DT’s effect. It was divided into 1–4, 5–7, and >=8.

Data analysis

CMA 3.0 was used to analyze the effect sizes and moderators’ effects. In order to overcome the differences in different studies, the Pearson correlation coefficient r was selected as the effect size (Borenstein et al., 2005 ). Since the paper sample sizes varied widely, the authors employed the Fisher Z -transformation based on the weighted study sample sizes to calculate the ultimate r and 95% confidence intervals (Lei et al., 2020 ).

Publication Bias

We used the funnel plot, classic fail-safe N , and trim-and-fill method to examine the publication bias. If there is no publication bias in the data, the scatter of the funnel would be spread symmetrically. First , the funnel plot showed that the samples in this study were not evenly distributed (Fig. 2 ). Second , fail-safe Nfs quantifies the threshold at which publication bias becomes an issue. CMA can calculate the threshold ( Nfs ). Next, the fail-safe Nfs indicated that Nfs  = 9179 was far larger than 220 (5* K  + 10, K = 42). Last , the trim-and-fill method can create plots of potentially missing studies to search for symmetry between the literature (Duval and Tweedie, 2000 ). This method found just five missing values on the right of the funnel plot (Fig. 3 ). In sum, it can be concluded that the data included were free from publication bias.

Funnel plot.

Funnel plot after trill-and-fill.

Actually, literature selection may cause publication bias. To minimize this bias, we strictly developed the selection criteria, e.g., study purpose and design, intervention of DT, necessary data, and peer-review. Especially, we limited the language of publication to English. This may exclude some potential literature published in other languages; it is one limitation of the current research and could be addressed in the future.

Homogeneity test and sensitivity analysis

The values of Q and I 2 can be used to determine whether heterogeneity exists. The result was Q  = 554.908 ( p  < 0.001) (Table 1 ), which was significant. Moreover, I 2  = 92.611% > 75%, according to Higgins et al. ( 2003 ), meant the heterogeneity was high. Thus, the random-effects model should be selected (Borenstein et al., 2009 ; Wilson et al., 2020 ). Moreover, moderating analyses were also necessary to be analyzed.

To confirm the robustness of this research, we used the one-study-removal method to examine the sensitivity. The result suggested that each overall effect size fell within a reasonable range (from 0.418 to 0.467). Thus, this study is robust.

General characteristics of the included 25 studies

To answer RQ1, reveal the current state of empirical research on DT, and provide complementary evidence for subsequent meta-analyses, a descriptive analysis of the included literature was conducted. The literature included was published between 2015 and 2023, e.g., 1 in 2015 (4.00%), 1 in 2017 (4.00%), 3 in 2020 (12.00%), 8 in 2021 (32.00%), 6 in 2022 (24.00%), and 6 in 2023 (24.00%). The result indicated a growing interest in empirical research on the use of DT for teaching and learning in education. In terms of study design, only 2 were correlational studies (Lin et al., 2020a ; Roth et al., 2020 ), while the other 23 were experimental studies (including pre-experiment, quasi-experiment, and true-experiment). Descriptive results are as follows:

(1) Grade level: kindergarten ( N  = 1, 4.00%), primary school ( N  = 3, 12.00%), junior high school ( N  = 2, 8.00%), high school ( N  = 9, 36.00%), and university ( N  = 10, 40.00%).

(2) Class size: 0–30 ( N  = 9, 36.00%), 31–50 ( N  = 10, 40.00%), and >=51( N  = 6, 24.00%).

(3) Duration: 0–1 month ( N  = 8, 32.00%), 1–3 months ( N  = 7, 28.00%), and =>3 months ( N  = 10, 40.00%).

(4) Subject: STEM ( N  = 16, 64.00%), No-STEM ( N  = 6, 24.00%), and multidiscipline ( N  = 3, 12.00%).

(5) DT model: EDIPT ( N  = 14, 56.00%), 3IE ( N  = 1, 4.00%), UOPIPT ( N  = 1, 4.00%), LAUNCH ( N  = 1, 4.00%), OSIP ( N  = 1, 4.00%), PAS ( N  = 1, 4.00%), PPI2U ( N  = 1, 4.00%), EDEIPT ( N  = 1, 4.00%), CTC ( N  = 1, 4.00%), and Unknown ( N  = 3, 12.00%) (Fig. 4 ).

(7) Team size : 0–4 ( N  = 7, 53.85%) and 5–7 ( N  = 6, 46.15%).

(8) Region : Asia ( N  = 21, 84.00%), America ( N  = 1, 4.00%), Australia ( N  = 1, 4.00%), Europe ( N  = 1, 4.00%), and Africa ( N  = 1, 4.00%) (Fig. 5 ).

(9) Countries : China ( N  = 12, 48.00%), Thailand ( N  = 2, 8.00%), Australia ( N  = 1, 4.00%), Austria ( N  = 1, 4.00%), Philippines ( N  = 2, 8.00%), Saudi Arabia ( N  = 2, 8.00%), Nigeria ( N  = 1, 4.00%), America ( N  = 1, 4.00%), Indonesia ( N  = 1, 4.00%), Jordan ( N  = 1, 4.00%), and Turkey ( N  = 1, 4.00%).

In general, the results revealed that most research used EDIPT ( N  = 14) as a DT model and focused primarily on the learning of STEM subjects ( N  = 16, 64.00%) by high school ( N  = 9, 36.00%) and university students ( N  = 10, 40.00%) in Asia ( N  = 21, 84.00%).

Overall effect size

When r  = 0.1, there is a small effect size; r  = 0.3 is a medium effect size; and r  = 0.5 is a large effect size (Cohen, 2013 ). The overall effect size of DT was upper-medium ( r  = 0.436, 95% CI [0.342, 0.525], p  < 0.001) (Table 1 ). Moreover, each study’s effect sizes were also provided (Fig. 6 ). The red diamond represents the overall effect size and its CI in the forest plot. Favours A meant the result was in favor of regular instruction, while Favours B meant the result was in support of DT instruction.

Forest plot.

Moderator analysis

Learning outcome.

The order of effect sizes from large to small was learning engagement ( r  = 0.740), learning motivation ( r  = 0.608), academic achievement ( r  = 0.450), problem-solving ability ( r  = 0.447), creative thinking ( r  = 0.329), and self-efficacy ( r  = 0.230) (Table 2 ). The between-groups effect ( p  < 0.01) indicated that the learning outcome had a moderating effect.

The order of effect sizes from large to small was <=30 ( r  = 0.609), 31–50 ( r  = 0.422), and >=51 ( r  = 0.389) (Table 2 ). The result of between-group effects was Q  = 0.856 ( p  > 0.05), indicating that the class size had no moderating effect.

Treatment duration

The result showed that the effect size of >=3 months ( r  = 0.535) was the largest, the next was <=1 month ( r  = 0.456), and 1–3 months ( r  = 0.245) was the smallest (Table 2 ). The between-groups effect ( p  < 0.001) indicated that the treatment had a moderating effect.

Grade level

The order of effect sizes from large to small was high school ( r  = 0.538), university ( r  = 0.463), junior high school ( r  = 0.443, p  > 0.05), primary school ( r  = 0.222), and kindergarten ( r  = 0.174) (Table 2 ). The between-groups effect ( p  < 0.01) indicated that the grade level had a moderating effect.

The order of effect sizes from large to small was multidiscipline ( r  = 0.604), No-STEM ( r  = 0.470), and STEM ( r  = 0.393) (Table 3 ). The between-groups effect indicated that the subject had no moderating effect.

The order of effect sizes from large to small was OSIP ( r  = 0.766), EDIPT ( r  = 0.522), 2UPPI ( r  = 0.346), PAS ( r  = 0.301), UOPIPT ( r  = 0.297), 3IE ( r  = 0.222), CTC ( r  = 0.191, p  > 0.05), EDEIPT ( r  = 0.174), and LAUNCH ( r  = 0.066, p  > 0.05) (Table 3 ). The Q test of the between-groups effect was significant ( p  < 0.001), indicating that the DT model had a moderating effect.

The order of effect sizes from large to small was 0–4 ( r  = 0.477) and 5–7 ( r  = 0.441) (Table 3 ). The between-groups effect ( p  > 0.05) indicated that the team size had no moderating effect.

The order of effect sizes from large to small was Africa ( r  = 0.690), Asia ( r  = 0.435), Australia ( r  = 0.355), Europe ( r  = 0.346), and America ( r  = 0.066, p  > 0.05) (Table 3 ). The between-groups effect ( Q  = 50.576, p  < 0.001) indicated that the region had a moderating effect.

Discussions and implications

This meta-analysis investigates DT’s effect on student learning with 42 validated effect sizes from 25 independent empirical articles. This research reveals that DT has an upper-medium effect on student learning. DT is the gaping link between the theoretical discoveries of social transformation pedagogy and the practical application of the skills needed for the future (Scheer et al., 2012 ). The DT process entails a set of logical stages that point to students’ key competencies. DT instruction can increase students’ involvement, establish a positive learning climate, and promote interaction and communication between teachers and students (Tu et al., 2018 ). Moreover, DT relies on teamwork and hands-on activities, which are beneficial for student learning (Holstermann et al., 2010 ; Oje, 2021 ; Sung et al., 2017 ; Swanson et al., 2019 ). Certainly, connecting DT with courses’ content may be a challenge (Hennessey and Mueller, 2020 ). Overall, if educators organize DT instruction appropriately, it will be effective in improving student learning.

It has a moderating effect. Specifically, DT can promote learners’ creative thinking, learning engagement, motivation, problem-solving ability, self-efficacy, and academic achievement. Notably, the effects of learning motivation, engagement, and academic achievement are large. The DT process entails a set of logical stages that point to students’ key competencies. DT is a dynamic, nonlinear, and spiraling process that can facilitate deep learning (Liu and Li, 2023 ), interest, motivation, creativity, and engagement, and eventually improve student learning (Howard et al., 2021 ; Rao et al., 2022 ). However, there are significant differences in the impacts of DT on student learning outcomes. DT models consist of a set of stages, and some models are complex and challenging. So, its effect on self-efficacy is smaller than other types of learning outcomes. In sum, DT still has great potential to enhance various learning outcomes.

It has no moderating effect. Specifically, <= 30 ( r  = 0.609) has a large effect, >= 51 ( r  = 0.389) and 31–50 ( r  = 0.422) have upper-medium effects. The result suggests that the smaller the class size, the better DT’s effects. DT is a guided, student-oriented process where learners need close supervision, guidance, and feedback (Retna, 2016 ). When the class size is large (>= 51), it is hard for teachers to provide prompt guidance and feedback. Moreover, large class sizes challenge teachers’ effective classroom management and interactions (Blatchford et al., 2009 ). Of course, >= 51 is broad. So, DT’s effects on larger class sizes (e.g., 51–80, etc.) need more exploration. Based on the result, we recommend that educators keep the class size below 51 students. Moreover, if conditions permit, more teachers could be involved in one class (e.g., two teachers) (Retna, 2016 ).

It has a moderating effect. Specifically, the effect of >= 3 months ( r  = 0.535) is large, <= 1 month ( r  = 0.456) has an upper-medium effect, and 1–3 months ( r  = 0.245) has an upper-small effect. Generally, the effect of 1–3 months is best (Yu et al., 2023 ), but our result is the smallest. The novelty effect may result in a larger effect at <=1 month than at 1–3 months. The decrease in the 1–3 months’ effect may be due to the novelty effect wearing off as students slowly familiarize themselves with DT and face learning challenges. Guaman-Quintanilla et al. ( 2023 ) noted that it is challenging to experience the entire process of DT within a limited time. Namely, time constraints are a challenge for students and educators (McLaughlin et al., 2023 ; Retna, 2016 ; Razali et al., 2022 ). Longer durations are needed for educators to conduct DT instruction to make students engage in DT (Razali et al., 2022 ). Actually, DT is a long-term journey to develop students’ abilities and skills, so enough time should be allocated. In short, though DT is effective for these durations, <=1 month or >= 3 months are more effective. More future research could examine the 1–3 months’ effect on DT.

It has a moderating effect. Specifically, high school ( r  = 0.538) has the best effect; university ( r  = 0.463) has an upper-medium effect; primary school ( r  = 0.222) and kindergarten ( r  = 0.174) have small effects; and junior high school ( r  = 0.443, p  > 0.05) has an insignificant effect. DT has been used in all stages of education, and DT is also effective. In this research, DT shows greater potential for high school and university students than for primary school and kindergarten students. DT is a task- and activity-oriented learning process that relies on team communication and collaboration, DT studies at different stages might yield different results due to cognitive-developmental differences (Mentzer et al., 2015 ). Given the complexity of DT, more DT instruction could be applied to university and secondary school students. Moreover, for researchers, more studies should be carried out at diverse grade levels, especially in kindergarten ( k  = 2) and junior high school ( k  = 4).

It has no moderating effect, but the effect of multidiscipline is better than that of STEM and No-STEM. This suggests that DT can foster multidisciplinary learning, consistent with previous studies (Chang and Tsai, 2021 ; de Figueiredo, 2021 ; van de Grift and Kroeze, 2016 ). DT has typical interdisciplinary features (Lugmayr et al., 2014 ) and can promote new solutions, innovation, and collaboration opportunities for complex problems in multidisciplinary areas (Cook and Bush, 2018 ; Gleason and Jaramillo Cherrez, 2021 ). At the same time, DT can be integrated into the subjects of STEM or No-STEM to promote learning and teaching (Hsiao et al., 2023 ). DT is taught as a concept rather than affiliated with a specific discipline (Lor, 2017 ). We recommend integrating DT into existing courses rather than adding additional add-on activities (Sandars and Goh, 2020 ), especially for multidisciplinary learning (Hsiao et al., 2023 ). Different disciplines or subjects have their own suitable design processes (Sung and Kelley, 2019 ), the result provides a broad subject division for reference. Future research could explore DT’s effects on more detailed subjects. Besides, most of DT was applied to STEM subjects ( k  = 32), fewer to No-STEM and multidiscipline. So, DT’s effects on both latter subjects should be viewed cautiously and pay more research attention.

It has a moderating effect, indicating that different DT models could generate heterogeneity. Specially, OSIP ( r  = 0.766) and EDIPT ( r  = 0.522) have large effects; PPI2U ( r  = 0.346) and PAS ( r  = 0.301) have lower-medium effects; UOPIPT ( r  = 0.297), 3IE ( r  = 0.222), EDEIPT ( r  = 0.174) have small effects; and CTC ( r  = 0.191, p  > 0.05) and LAUNCH ( r  = 0.066, p  > 0.05) have no significant effects. Before DT can be effectively implemented to solve complicated problems, it is essential to have a solid grasp and comprehension of the different stages of the DT process (Dam and Teo, 2019 ). Different DT models involve different steps or stages, which may affect the processes of cognition and learning. For instance, EDIPT is easier for middle school students (Sarooghi et al.m 2019 ). Based on the result of this meta-analysis, we recommend that educators adopt the models of EDIPT and OSIP in DT instruction. Importantly, educators should not rely too heavily on the pre-determined procedural DT processes, which may hinder the creative potential of DT (Wells, 2013 ). Educators can rationalize the DT model based on their actual situations (Li and Zhan, 2022 ). It is also necessary to mention that, with the exception of EDIPT, the numbers of effect sizes included in other DT models are small, so their results should be treated cautiously and more explorations are needed.

It has no moderating effect. Team sizes of 0–4 ( r  = 0.477) and 5–7 ( r  = 0.441) have upper-medium effects. Teamwork and team collaboration are great challenges for many students. DT could enhance students’ teamwork (Guaman-Quintanilla et al., 2022 ). Success in DT requires teamwork, and larger teams can enrich the diversity of perspectives and increase the likelihood of solutions (Sung et al., 2017 ). Moreover, the composition of teams is also important (Apedoe et al., 2012 ). Generally speaking, heterogeneous ability groups may be appropriate in DT (Lou et al., 1996 ), i.e., both low-ability and high-ability students, and both male and female students (Yu and Yu, 2023 ). From the result of this research, 2–7 members in one group are beneficial. A larger number of teams may limit the teachers’ ability to guide and facilitate each team’s, and individual students’ learning (Apedoe et al., 2012 ). We recommend having <=7 members in one group. Specifically, when the class size is large, 5–7 is better; otherwise, 2–4 will be better. However, the result shows a broad team size for reference only. So, future research could explore which specific composition of teams (from 2 to 7 or above) in DT instruction is better.

It has a moderating effect. Specifically, Africa ( r  = 0.690) has a large effect, Asia ( r  = 0.435), and Australia ( r  = 0.355), and Europe ( r  = 0.346) have upper-medium effects, while America has an insignificant effect. This may be due to differences in cultural and educational systems in different regions. Different from individualistic cultures (e.g., America, Australia, Austria), most Asian countries are collectivist (e.g., China, Thailand, Indonesia, etc.), and students in these countries tend to value team goals more than individual goals (De Mooij and Hofstede, 2010 ). So, DT has an upper-medium effect on Asian students. Since the study distribution between different regions was highly uneven, this result should be treated judiciously. For instance, except for Asia, other regions’ studies are small, e.g., Australia ( N  = 1), Europe ( N  = 1), Africa ( N  = 1), and America ( N  = 1), so these regions need more attention. In general, DT positively impacts student learning in diverse regions, and DT is recommended to enhance Asian students’ learning.

Implications for future practice and work

This meta-analysis makes an evidence-based analysis of DT’s effects on student learning, and we provide some meaningful suggestions for future practice and research. These are also major contributions to the existing literature.

First , though DT’s effects on different types of learning outcomes are significantly different, it is still an effective teaching method to improve student learning. Educators can apply DT to enhance student academic performance, creative thinking, learning engagement, motivation, and problem-solving ability. Due to the limited amount of learning engagement and self-efficacy, their effects should be treated cautiously.

Second , a smaller size means a larger DT’s effect. Educators should keep the class size <51. Future research could focus more on exploring DT’s effects on larger class sizes (e.g., 51–80, etc.).

Third , treatment duration is a critical factor. <= 1 month or >=3 months are more suggested. Particularly, DT’s effect is smallest when the duration is 1–3 months, and this needs more future research.

Fourth , grade level is a key factor. DT could be applied to university and high school students. DT’s effect on junior high school is insignificant . Researchers could carry out more studies at kindergarten ( k  = 2) and junior high school ( k  = 4).

Fifth , DT can be used in the subjects of STEM, No-STEM, or multidiscipline. Meanwhile,future research could explore more on No-STEM, multidiscipline, and more detailed subjects.

Sixth , the DT model is also a critical factor that should be considered. Based on the results of this study, we recommend that educators adopt the models of EDIPT. Importantly, except for EDIPT, other models’ effects need more exploration.

Seventh , in terms of team size, it is suggested to have <= 7 members in one group. Specifically, when the class size is large, 5–7 is better; otherwise, 2–4 will be preferred. However, the result shows a wide range. Future research could explore which specific composition of teams (from 2 to 7 or above) is better for DT instruction.

Eighth , regional analysis suggests that DT is most used in Asia and is most suggested to support Asian student learning. However, the number of effect sizes in other regions is very small. Thus, their results should be viewed with caution, and future researchers can take more steps to test DT’s effects in America, Africa, Australia, and Europe.

Conclusions, limitations and future research

Conclusions.

This meta-analytic evidence reveals DT’s effects in education based on 25 empirical studies. We find that DT has an upper-medium positive effect on students’ learning. Specifically, DT can lead to higher learners’ creative thinking, learning engagement, motivation, problem-solving ability, self-efficacy, and academic achievement. In comparison, DT has better effects on student learning motivation, engagement, and academic achievement. Furthermore, the learning outcome, grade level, treatment duration, DT model, and region moderate DT’s effects on student learning. Namely, these moderators will affect DT’s effectiveness.

DT is on-trend worldwide (Aris et al., 2022 ), and it has profoundly changed many educators’ thinking about how to instruct to support learning (Hubbard and Datnow, 2020 ). Teachers are vital in DT instruction; they should be facilitators and navigators, not lecturers (Henriksen et al., 2020b ; Retna, 2016 ; Rusmann and Ejsing-Duun, 2022 ). In sum, DT can potentially promote learning at different grade levels, but the effectiveness of DT in education depends upon the goals (Panke, 2019 ). It is critical to make teachers see the value of DT in classrooms (Carroll et al. 2010 ) and conduct DT instruction with guidance and rules. This paper provides evidence-based findings for educators and researchers.

Limitations, research gaps, and future directions

There are several limitations that should be solved for future work. First , the literature is distributed unevenly by region, grade level, and DT model, so more future studies could be taken at kindergarten ( k  = 2), junior high school ( k  = 4), America ( k  = 1), Australia ( k  = 1), Africa ( k  = 2), Europe ( k  = 2), learning engagement ( k  = 1), self-efficacy ( k  = 3), and DT model except EDIPT. Second , the literature included in this meta-analysis was published in English . Future work could include other language studies. Third , the heterogeneity is considerable, and some potential moderators may be overlooked. Future work could explore more factors that influence DT’s effectiveness, e.g., learning environments. Fourth , the included literature is not large; future research could focus on experimental design to explore DT’s effects on student learning. Last , a meta-analysis may not display the whole status and findings of DT in education. Future researchers could conduct a systematic literature review to compensate for the neglected aspects of the current research.

Data availability

All data is provided in the forest plot and references. The details are provided at https://doi.org/10.7910/DVN/EHGCGS .

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Yu, Q., Yu, K. & Lin, R. A meta-analysis of the effects of design thinking on student learning. Humanit Soc Sci Commun 11 , 742 (2024). https://doi.org/10.1057/s41599-024-03237-5

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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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