design thinking and its application to problem solving

How to solve problems with design thinking

May 18, 2023 Is it time to throw out the standard playbook when it comes to problem solving? Uniquely challenging times call for unique approaches, write Michael Birshan , Ben Sheppard , and coauthors in a recent article , and design thinking offers a much-needed fresh perspective for leaders navigating volatility. Design thinking is a systemic, intuitive, customer-focused problem-solving approach that can create significant value and boost organizational resilience. The proof is in the pudding: From 2013 to 2018, companies that embraced the business value of design had TSR that were 56 percentage points higher than that of their industry peers. Check out these insights to understand how to use design thinking to unleash the power of creativity in strategy and problem solving.

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What is Design Thinking and Why Is It So Popular?

Design Thinking is not an exclusive property of designers—all great innovators in literature, art, music, science, engineering, and business have practiced it. So, why call it Design Thinking? What’s special about Design Thinking is that designers’ work processes can help us systematically extract, teach, learn and apply these human-centered techniques to solve problems in a creative and innovative way—in our designs, in our businesses, in our countries, in our lives.

Some of the world’s leading brands, such as Apple, Google and Samsung, rapidly adopted the design thinking approach, and leading universities around the world teach the related methodology—including Stanford, Harvard, Imperial College London and the Srishti Institute in India. Before you incorporate design thinking into your own workflows, you need to know what it is and why it’s so popular. Here, we’ll cut to the chase and tell you what design thinking is all about and why it’s so in demand.

What is Design Thinking?

Design thinking is an iterative and non-linear process that contains five phases: 1. Empathize , 2. Define, 3. Ideate, 4. Prototype and 5. Test.

Design thinking is an iterative process in which you seek to understand your users, challenge assumptions , redefine problems and create innovative solutions which you can prototype and test. The overall goal is to identify alternative strategies and solutions that are not instantly apparent with your initial level of understanding.

Design thinking is more than just a process; it opens up an entirely new way to think, and it offers a collection of hands-on methods to help you apply this new mindset.

In essence, design thinking:

Revolves around a deep interest to understand the people for whom we design products and services.

Helps us observe and develop empathy with the target users.

Enhances our ability to question: in design thinking you question the problem, the assumptions and the implications.

Proves extremely useful when you tackle problems that are ill-defined or unknown.

Involves ongoing experimentation through sketches, prototypes, testing and trials of new concepts and ideas.

• Transcript loading…

In this video, Don Norman , the Grandfather of Human-Centered Design , explains how the approach and flexibility of design thinking can help us tackle major global challenges.

What Are the 5 Phases of Design Thinking?

Hasso-Platner Institute Panorama

Ludwig Wilhelm Wall, CC BY-SA 3.0 <https://creativecommons.org/licenses/by-sa/3.0>, via Wikimedia Commons

Design thinking is an iterative and non-linear process that contains five phases: 1. Empathize, 2. Define, 3. Ideate, 4. Prototype and 5. Test. You can carry these stages out in parallel, repeat them and circle back to a previous stage at any point in the process.

The core purpose of the process is to allow you to work in a dynamic way to develop and launch innovative ideas.

Design thinking is an iterative and non-linear process that contains five phases: 1. Empathize, 2. Define, 3. Ideate, 4. Prototype and 5. Test.

Design Thinking Makes You Think Outside the Box

Design thinking can help people do out-of-the-box or outside-the-box thinking. People who use this methodology:

Attempt to develop new ways of thinking —ways that do not abide by the dominant or more common problem-solving methods.

Have the intention to improve products, services and processes. They seek to analyze and understand how users interact with products to investigate the conditions in which they operate.

Ask significant questions and challenge assumptions . One element of outside-the-box / out-of-the-box thinking is to falsify previous assumptions—i.e., make it possible to prove whether they’re valid or not.

As you can see, design thinking offers us a means to think outside the box and also dig that bit deeper into problem-solving. It helps us carry out the right kind of research, create prototypes and test our products and services to uncover new ways to meet our users’ needs.

The Grand Old Man of User Experience , Don Norman, who also coined the very term User Experience , explains what Design Thinking is and what’s so special about it:

“…the more I pondered the nature of design and reflected on my recent encounters with engineers, business people and others who blindly solved the problems they thought they were facing without question or further study, I realized that these people could benefit from a good dose of design thinking. Designers have developed a number of techniques to avoid being captured by too facile a solution. They take the original problem as a suggestion, not as a final statement, then think broadly about what the real issues underlying this problem statement might really be (for example by using the " Five Whys " approach to get at root causes). Most important of all, is that the process is iterative and expansive. Designers resist the temptation to jump immediately to a solution to the stated problem. Instead, they first spend time determining what the basic, fundamental (root) issue is that needs to be addressed. They don't try to search for a solution until they have determined the real problem, and even then, instead of solving that problem, they stop to consider a wide range of potential solutions. Only then will they finally converge upon their proposal. This process is called "Design Thinking." — Don Norman, Rethinking Design Thinking

Design Thinking is for Everybody

How many people are involved in the design process when your organization decides to create a new product or service? Teams that build products are often composed of people from a variety of different departments. For this reason, it can be difficult to develop, categorize and organize ideas and solutions for the problems you try to solve. One way you can keep a project on track, and organize the core ideas, is to use a design thinking approach—and everybody can get involved in that!

Tim Brown, CEO of the celebrated innovation and design firm IDEO, emphasizes this in his successful book Change by Design when he says design thinking techniques and strategies belong at every level of a business.

Design thinking is not only for designers but also for creative employees, freelancers and leaders who seek to infuse it into every level of an organization. This widespread adoption of design thinking will drive the creation of alternative products and services for both business and society.

“Design thinking begins with skills designers have learned over many decades in their quest to match human needs with available technical resources within the practical constraints of business. By integrating what is desirable from a human point of view with what is technologically feasible and economically viable, designers have been able to create the products we enjoy today. Design thinking takes the next step, which is to put these tools into the hands of people who may have never thought of themselves as designers and apply them to a vastly greater range of problems.” — Tim Brown, Change by Design, Introduction

Design thinking techniques and strategies belong at every level of a business. You should involve colleagues from a wide range of departments to create a cross-functional team that can utilize knowledge and experience from different specialisms.

Tim Brown also shows how design thinking is not just for everybody—it’s about everybody, too. The process is firmly based on how you can generate a holistic and empathic understanding of the problems people face. Design thinking involves ambiguous, and inherently subjective, concepts such as emotions , needs, motivations and drivers of behavior.

In a solely scientific approach (for example, analyzing data), people are reduced to representative numbers, devoid of emotions. Design thinking, on the other hand, considers both quantitative as well as qualitative dimensions to gain a more complete understanding of user needs . For example, you might observe people performing a task such as shopping for groceries, and you might talk to a few shoppers who feel frustrated with the checkout process at the store (qualitative data). You can also ask them how many times a week they go shopping or feel a certain way at the checkout counter (quantitative data). You can then combine these data points to paint a holistic picture of user pain points, needs and problems.

Tim Brown sums up that design thinking provides a third way to look at problems. It’s essentially a problem-solving approach that has crystallized in the field of design to combine a holistic user-centered perspective with rational and analytical research—all with the goal to create innovative solutions.

“Design thinking taps into capacities we all have but that are overlooked by more conventional problem-solving practices. It is not only human-centered; it is deeply human in and of itself. Design thinking relies on our ability to be intuitive, to recognize patterns, to construct ideas that have emotional meaning as well as functionality , to express ourselves in media other than words or symbols. Nobody wants to run a business based on feeling, intuition, and inspiration, but an overreliance on the rational and the analytical can be just as dangerous. The integrated approach at the core of the design process suggests a ‘third way.’” — Tim Brown, Change by Design, Introduction

Design Thinking Has a Scientific Side

Design thinking is both an art and a science. It combines investigations into ambiguous elements of the problem with rational and analytical research —the scientific side in other words. This magical concoction reveals previously unknown parameters and helps to uncover alternative strategies which lead to truly innovative solutions.

The scientific activities analyze how users interact with products, and investigate the conditions in which they operate. They include tasks which:

Research users’ needs.

Pool experience from previous projects.

Consider present and future conditions specific to the product.

Test the parameters of the problem.

Test the practical application of alternative problem solutions.

Once you arrive at a number of potential solutions, the selection process is then underpinned by rationality. As a designer, you are encouraged to analyze and falsify these solutions to arrive at the best available option for each problem or obstacle identified during phases of the design process.

With this in mind, it may be more correct to say design thinking is not about thinking outside the box, but on its edge, its corner, its flap, and under its bar code—as Clint Runge put it.

Clint Runge is Founder and Managing Director of Archrival, a distinguished youth marketing agency, and adjunct Professor at the University of Nebraska-Lincoln.

Resetting Our Mental Boxes and Developing a Fresh Mindset

Thinking outside of the box can provide an innovative solution to a sticky problem. However, thinking outside of the box can be a real challenge as we naturally develop patterns of thinking that are modeled on the repetitive activities and commonly accessed knowledge we surround ourselves with.

Some years ago, an incident occurred where a truck driver tried to pass under a low bridge. But he failed, and the truck was lodged firmly under the bridge. The driver was unable to continue driving through or reverse out.

The story goes that as the truck became stuck, it caused massive traffic problems, which resulted in emergency personnel, engineers, firefighters and truck drivers gathering to devise and negotiate various solutions for dislodging the trapped vehicle.

Emergency workers were debating whether to dismantle parts of the truck or chip away at parts of the bridge. Each spoke of a solution that fitted within his or her respective level of expertise.

A boy walking by and witnessing the intense debate looked at the truck, at the bridge, then looked at the road and said nonchalantly, “Why not just let the air out of the tires?” to the absolute amazement of all the specialists and experts trying to unpick the problem.

When the solution was tested, the truck was able to drive free with ease, having suffered only the damage caused by its initial attempt to pass underneath the bridge. The story symbolizes the struggles we face where oftentimes the most obvious solutions are the ones hardest to come by because of the self-imposed constraints we work within.

It’s often difficult for us humans to challenge our assumptions and everyday knowledge because we rely on building patterns of thinking in order to not have to learn everything from scratch every time. We rely on doing everyday processes more or less unconsciously—for example, when we get up in the morning, eat, walk, and read—but also when we assess challenges at work and in our private lives. In particular, experts and specialists rely on their solid thought patterns, and it can be very challenging and difficult for experts to start questioning their knowledge.

Stories Have the Power to Inspire

Why did we tell you this story about the truck and the bridge? Well, it’s because stories can help us inspire opportunities, ideas and solutions. Stories are framed around real people and their lives and are important because they’re accounts of specific events, not general statements. They provide us with concrete details which help us imagine solutions to particular problems.

Stories also help you develop the eye of a designer. As you walk around the world, you should try to look for the design stories that are all around you. Say to yourself “that’s an example of great design” or “that's an example of really bad design ” and try to figure out the reasons why.

When you come across something particularly significant, make sure you document it either through photos or video. This will prove beneficial not only to you and your design practice but also to others—your future clients, maybe.

The Take Away

Design Thinking is an iterative and non-linear process. This simply means that the design team continuously uses their results to review, question and improve their initial assumptions, understandings and results. Results from the final stage of the initial work process inform our understanding of the problem, help us determine the parameters of the problem, enable us to redefine the problem, and, perhaps most importantly, provide us with new insights so we can see any alternative solutions that might not have been available with our previous level of understanding.

Design thinking is a non-linear, iterative process that consists of 5 phases: 1. Empathize, 2. Define, 3. Ideate, 4. Prototype and 5. Test. You can carry out the stages in parallel, repeat them and circle back to a previous stage at any point in the process—you don’t have to follow them in order.

It’s a process that digs a bit deeper into problem-solving as you seek to understand your users, challenge assumptions and redefine problems. The design thinking process has both a scientific and artistic side to it, as it asks us to understand and challenge our natural, restrictive patterns of thinking and generate innovative solutions to the problems our users face.

Design thinking is essentially a problem-solving approach that has the intention to improve products. It helps you assess and analyze known aspects of a problem and identify the more ambiguous or peripheral factors that contribute to the conditions of a problem. This contrasts with a more scientific approach where the concrete and known aspects are tested in order to arrive at a solution.

The iterative and ideation -oriented nature of design thinking means we constantly question and acquire knowledge throughout the process. This helps us redefine a problem so we can identify alternative strategies and solutions that aren’t instantly apparent with our initial level of understanding.

Design thinking is often referred to as outside-the-box thinking, as designers attempt to develop new ways of thinking that do not abide by the dominant or more common problem-solving methods—just like artists do.

The design thinking process has become increasingly popular over the last few decades because it was key to the success of many high-profile, global organizations. This outside-the-box thinking is now taught at leading universities across the world and is encouraged at every level of business.

“The ‘Design Thinking’ label is not a myth. It is a description of the application of well-tried design process to new challenges and opportunities, used by people from both design and non-design backgrounds. I welcome the recognition of the term and hope that its use continues to expand and be more universally understood, so that eventually every leader knows how to use design and design thinking for innovation and better results.” — Bill Moggridge, co-founder of IDEO, in Design Thinking: Dear Don

References & Where to Learn More

Enroll in our engaging course, “Design Thinking: The Ultimate Guide”

Here are some examples of good and bad designs to inspire you to look for examples in your daily life.

Read this informative article “What Is Design Thinking, and How Can SMBs Accomplish It?” by Jackie Dove.

Read this insightful article “Rethinking Design Thinking” by Don Norman.

Check out Tim Brown’s book “Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation Introduction,” 2009.

Learn more about Design Thinking in the article “Design Thinking: Dear Don” by Bill Moggridge.

© Interaction Design Foundation, CC BY-SA 3.0

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Impact of design thinking in higher education: a multi-actor perspective on problem solving and creativity

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• Volume 33 , pages 217–240, ( 2023 )

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This study investigates the effects of using design thinking on students’ problem solving and creativity skills, applying a constructivist learning theory. A course where students use design thinking for analyzing real problems and proposing a solution, was evaluated. The study involved 910 novice university students from different disciplines who worked in teams throughout the semester. Data were collected at three times during the semester, i.e. at the beginning (t0), in the middle (t1) and at the end (t2), after solving a short case study. Each time the problem solving and creativity skill of each student was rated by three different actors, i.e. the students themselves (self-evaluation), one peer and one teacher (facilitator). The objective of this study is to investigate whether the problem solving skills and creativity skills improved along the course, as rated by the three actors. A repeated measures ANOVA was used for the data analysis of this within-subjects design. Results show a significant improvement on students’ problem solving and creativity skills, according to the three raters. Effect sizes were also calculated; in all cases the effect sizes from t0 to t1 were larger than t1 to t2. The multi-actor perspective of this study, the adoption of reliable and valid measures and the large sample size provide robust evidence that supports the implementation of design thinking in higher education curriculum for promoting key skills such as problem solving and creativity, demanded by labor markets. Finally, a discussion that puts forward an agenda for future research is presented.

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Introduction

Higher Education Institutions (HEIs) face the challenge of promoting in their curricula the demands of labor markets in a world that is constantly changing, more technologically-driven and presenting ill-defined problems (Griffin et al., 2012 ; Wan and Gut 2011 ). Among the top five skills in demand for 2025 are problem-solving and creativity (World Economic Forum, 2020 ), often referred to as twenty-first century skills in terms of the new abilities students should be able to do to surpass the basic skills and knowledge expectations of the past, especially when considering the implementation of new technologies (Binkley et al., 2012 ; Lemke, 2002 ). One educational approach that fosters the development of these key skills, is labeled as design thinking (Luka, 2020 ; Scheer et al., 2012 ). Design thinking has been used as a means for value creation and innovation in different fields including business, medicine, science and various stages of education (Pande & Bharathi, 2020 ).

Design thinking was first coined by Simon ( 1969 ) and it has during recent decades gained popularity in HEIs contexts (Kleinsmann et al., 2017 ; Liedtka, 2014 ; Matthews & Wrigley, 2017 ; Razzouk & Shute, 2012 ; Spee & Basaiawmoit, 2016 ). Moreover, HEIs perceive the curriculum implementation of design thinking as a safe learning space where students can work in multidisciplinary teams boosting their skills and knowledge beyond their fields of study (Wrigley & Straker, 2015 ). Results from a recent design thinking review study show that it is mostly associated with skills in educational settings in terms of: collaboration/teamwork, creativity, problem solving, and empathy (Guaman-Quintanilla et al., 2018 ).

Nevertheless, researchers criticize the lack of a systematic assessment of design thinking results (Liedtka, 2014 ), as well as the lack of accurate, performance-based measures to study its impact (Razzouk & Shute, 2012 ). Moreover, Steinbeck ( 2011 ) criticizes the lack of comprehensive design thinking assessment approaches that fit the complex nature of design thinking and its application in multidisciplinary settings. In addition, Spee and Basaiawmoit ( 2016 ) point at the absence of statistically robust empirical studies to underpin design thinking effectiveness.

In this study, we assessed the impact of a compulsory first-year course called ‘Analysis and Problem Solving’ in an Ecuadorian University. In this compulsory course students learn how to analyze and solve a real-life problem using design thinking. This course offers as such as an promising opportunity for measuring students’ problem solving and creativity skills, as a result of using design thinking in university settings. Data were collected at three time points during a semester taking into account three raters: students as self-evaluators, peers and facilitators. To the best of our knowledge, no studies have adopted a multi-actor perspective to study design thinking impact. Therefore, the present study sheds light on the impact of design thinking, motivated by: (a) the HEIs growing interest on design thinking; (b) problem solving and creativity, as the most-mentioned skills related to design thinking; and the (c) lack of robust empirical studies to measure the impact of design thinking.

The remaining part of the paper proceeds as follows: First, we review the literature to define design thinking guidelines on a conceptual and theoretical framework. Next, the research method and description of the quasi-experimental procedure is provided. Finally, based on our findings, a discussion that puts forward an agenda for future research and implications for universities curricula is presented.

Conceptual and theoretical framework

• Design thinking

Authors argue regarding a clear definition of design thinking (Blizzard et al., 2015 ; Goldschmidt & Rodgers, 2013 ; Johansson-Sköldberg et al., 2013 ; Kimbell, 2011 ). One of the most cited definition of design thinking is: “A discipline that uses the designer’s sensibility and methods to match people’s needs with what is technologically feasible and what a viable business strategy can convert into customer value and market opportunity.” (Brown, 2008 , p. 2). A detailed analysis of design thinking literature in Higher Education settings, helped defining the following main characteristics: human-centered approach, solution of ill-defined problems, creativity, teamwork/collaboration, prototype-driven (Carlgren et al., 2016 ; Fleury et al., 2016 ; Ito et al., 2015 ; Lugmayr et al., 2014 ; Patel & Mehta, 2017 ; Razzouk & Shute, 2012 ; Wrigley & Straker, 2015 ). Design thinking supports dealing with complex real-life problems, following a human-centered approach and demands students to be avid interdisciplinary collaborators (Brown, 2008 ; Scheer et al., 2012 ). Literature also shows that the teachers’ role in design thinking is to be seen as a facilitator, rather than an instructor (Scheer et al., 2012 ). In a design thinking intervention, the facilitator presents students with the context that comprises of the challenges, collaborative groups, and tools and activities (Pande & Bharathi, 2020 ). Furthermore, facilitators stimulate students to unleash their creative potential promoting a conducive environment to develop reflection about what worked and what can be learned from things that did not work (e.g. Kelley & Kelley, 2013 ).

In addition, Wrigley and Straker ( 2015 ) propose five-steps along an ‘Educational Design Ladder’ to foster the development of design thinking. The authors point out that by following these steps, students acquire knowledge and skills to apply design thinking in different contexts and projects. Moreover, building on their approach about ‘design-based learning’ (Luka, 2020 ) or ‘design methodology’ (Huang et al., 2019 ), the scholars put forward approaches such as: the four-stage process – also called the ‘Double Diamond’ – proposed by the UK Design Council ( 2007 ); the popular five-stage model of the Hasso Plattner Institute of Design at Stanford University (d.school) ( 2010 ), among others. The stages/models help developing operational interventions to attain the aforementioned impact on problem solving and creativity.

Based on the literature, we propose the following definition of design thinking: Design thinking is a way of working and thinking that goes beyond the pure design context, as it is a way of solving ill-defined problems using methods and mindsets typically associated with designers, but adapting them to different real contexts and applying a human-centered and prototype-driven approach, which fosters creativity and promotes the value of teamwork.

In the following sections we analyze the learning theory that helps describing and explaining the impact of design thinking, as well as how it is connected to the development of problem solving and creativity skills.

Constructivism and its relation to design thinking

Design thinking challenges the teacher-centered approach. The latter is also known as ‘the sage on the stage’ teaching delivery method where a teacher transmit their knowledge (by lecturing) to students who passively absorb the content (King, 1993 ). In contrast, design thinking is linked to constructivist learning theory (Noweski et al., 2012 ; Pande & Bharathi, 2020 ; Scheer et al., 2012 ). Constructivism serves as an umbrella term to bring together a diversity of views sharing two main ideas: (a) learning is not seen as transmission of knowledge but as an active process of constructing knowledge; and (b) instruction is a process of supporting the knowledge construction process (Duffy & Cunningham, 1996 ). Jonassen et al. ( 1995 ) argue that constructivism raises the assumption that knowledge depends on how people create meaning from their experiences. In addition, the aforementioned authors also emphasize the importance of the social context in the design thinking learning environment based on the socio-cultural constructivist approach of Vygotsky ( 1978 ).

Constructivism beliefs about learning assert the need for embedding students in real-world situations where they function as a part of a community that contributes to solving real-world problems (Lave & Wenger, 1991 ). Furthermore, constructivist environments should engage students in their construction of knowledge through collaboration that insert learning in a meaningful context and reflection on what has been learned (Jonassen et al., 1995 ). Regarding to evaluation, constructivism focuses on the thinking process and the students’ abilities to argue and support decisions that are related to the development of self-reflection and metacognitive skills (Karagiorgi & Symeou, 2005 ).

Since the learner is at the center of the constructivist teaching–learning process, teachers are seen as facilitators rather than instructors (Murphy, 1997 ; Noweski et al., 2012 ; Pande & Bharathi, 2020 ). This role implies guiding and supporting students in their construction of knowledge, providing instruction and feedback, monitoring progress and evaluating (Neo, 2003 ). Additionally, Duffy and Cunningham ( 1996 ) state that teachers should play the role of coaches to guide learners and support them as scaffolds.

The link between design thinking and constructivist learning theory remains fuzzy. Pande and Bharathi ( 2020 ) tried to map constructivist tenets to design thinking phases. Design thinking main characteristics (human-centered approach, solution of ill-defined problems, creativity, teamwork/collaboration, prototype-driven) can also be linked to constructivist tenets (Jonassen, 1994 ); we explain these connections as follows: Constructivist tenets provide multiple representations of reality, represent the natural complexity of the real world, provide real-world, case-based learning environment, rather than pre-determined instructional sequences. In this regard, design thinking enables students to deal with complex real-life problems (Scheer et al., 2012 ). Moreover, design thinking uses a human-centered (also known as user-centered, user-driven, customer-oriented) approach, therefore students are encouraged to develop more empathy towards different views and feelings (d.school 2018 ), providing the means to bring out real users’ perspectives while analyzing the problem and testing possible solutions. Other key characteristic of design thinking found in most of the literature is the focus on prototyping; in this sense, prototyping develops the skills and competences of students by encouraging them to work on authentic real-life problems (Jussila et al., 2020 ).

Another tenet of constructivism focuses on knowledge construction, not reproduction. Jonassen ( 1997 ) argues that students facing ill-defined problems synthesize their own understanding of the situation rather than find a straightforward solution for an already defined problem. Since design thinking is characterized by working with ill-defined problems, this suggests a connection with this tenet. Besides, according to Scheer et al. ( 2012 ) the design thinking process pushes the teacher to become a facilitator of a constructive learning; i.e. designing the space to let students experiment different mental models and methods, balancing instruction and construction, so pupils can convert abstract and general principles into meaningful practice.

Constructivism also builds on working on authentic and contextualized task. In this sense, during a design thinking intervention, the facilitator introduces students with a context that includes the real-life problem (Pande & Bharathi, 2020 ). Moreover, contextualizing may be also manifested through the focus on a human-centered approach within a design thinking process, which helps identifying insights and delivering innovation that reflects what users want (Brown, 2008 ).

Additionally, design thinking entails “for different situations apply different perspectives and new perspectives generate new situations” (Scheer et al., 2012 , p. 13) which reveals another key tenet of constructivism: Enable context-and content dependent knowledge construction. Moreover, prototyping (as a design thinking main characteristic) requires students, users and others to experience and interact with prototypes for building successful solutions (d.school 2018 ) which means the knowledge is constructed by students based not only in the content (e.g. prototyping techniques) but also in the context through validation of those prototypes.

Fostering reflective practice is a next constructivist tenet promoted by design thinking. Design thinking promotes students to reflect on their problem solving approach (Scheer et al., 2012 ). Besides, as part of the human-centered approach of design thinking, students try developing empathy with the actors involved in the situation, empathy involves emotion and logic, which stimulates insights, inspiration and intuition (Glen et al., 2015 ). Prototyping is another opportunity to foster reflection as students explore ways to turn prototype failures into opportunities (d.school, n.d.).

Finally, the last constructivist tenet is about supporting collaborative construction of knowledge through social negotiation. In this regard, most of the design thinking literature points at collaboration (or teamwork) as one of its main characteristics. For instance, Brown ( 2008 ) suggests a design thinker needs to be an enthusiastic interdisciplinary collaborator. Both the collaboration and human-centered approach of design thinking supports the Kanselaar's ( 2002 ) idea of learning as the negotiation of meaning since shared ideas among users and/or other stakeholders, as well as teammates (knowledge-building community), should be accepted and agreed upon. For instance, prototyping helps to overcome the boundaries between different stakeholders, reducing miscommunication, as well as the amount of effort required to discuss and share ideas (Björklund et al., 2017 ). Furthermore, in design thinking, team competences are promoted to express opinions and share knowledge; also, students and teachers build trust (Scheer et al., 2012 ).

• Problem solving

In the education context, problem solving promotes higher-order skills and it is positioned as one of the key skills learners have to develop (Jonassen, 1997 ). Hesse et al. ( 2015 ) provide the following definition for problem solving: “an activity in which a learner perceives a discrepancy between a current state and a desired goal state, recognizes that this discrepancy does not have an obvious or routine solution, and subsequently tries to act upon the given situation in order to achieve that goal state. It is accompanied by a number of mental and behavioral processes that might not necessarily take place in sequential order but can run in parallel” (p. 38). The authors emphasize the collaborative nature of problem solving by working on intertwined activities and building on each other’s contributions. Building on the scope and nature of the present study, we especially build on the rephrasing of the above definition by Rhodes ( 2010 ): “The process of designing, evaluating and implementing a strategy to answer an open-ended question or achieve a desired goal.” (p. 41).

Constructivism consistently emphasizes problem-solving as a key learning outcome (Kanselaar, 2002 ; Murphy, 1997 ; Neo, 2003 ). Since design thinking is aligned with constructivism, problem-solving is clearly an associated skill (Alhamdani, 2016 ; Anand et al., 2015 ; Bhatnagar & Badke-Schaub, 2017 ; Khalaf et al., 2012 ; Lugmayr et al., 2014 ; Taajamaa et al., 2013 ). This connection can be explained as follows. One of the main characteristics of design thinking is working with real and ill-defined problem. According to Voss and Post ( 1988 ) working with these type of problems challenge students’ problem- solving skills. This is confirmed by Jonassen ( 1997 ) who argues that when dealing with ill-defined problems, students must (re)frame the design problem, recognize divergent perspectives, and collect evidence to support or reject the alternative proposals. Moreover, in instructional approaches to implement constructivist learning principles, the focus is mainly on developing the skills related to solving the problem in an authentic context (Duffy & Cunningham, 1996 ), as also happens in design thinking. During the process for solving problems, students establish a reflective practice with the situation. Reflection is one of the tenets of Constructivism, and as explained in the previous section, design thinking also promotes reflection while dealing with ill-defined problems, developing empathy, and testing prototypes. As mentioned earlier, other common aspect of constructivism and design thinking is the emphasis on collaboration. In this regard, during a problem-solving process the achievement of a group is considered to be more effective because it brings together different abilities and skills, which might lead to better collective outcomes (Siemon et al., 2019 ).

As mentioned earlier, creativity is a dominant skill in the design thinking literature. However, the concept also introduces conceptual confusion (Egan et al., 2017 ; Hernández-Torrano & Ibrayeva, 2020 ). Psychology-driven definitions of creativity stress originality and usefulness (Runco & Jaeger, 2012 ; Stein, 1953 ). However, Sawyer ( 2006 ) goes beyond this approach by stating that creativity is “the emergence of something novel and appropriate, from a person, a group, or a society” (p. 33). Sawyer adds that creativity consists of combining divergent and convergent thinking and switching back and forth at different points in the creation process. This is reiterated by Lindberg et al. ( 2011 ) who put forward a problem space and solution space in design thinking. Both spaces include diverging and converging activities. Based on the scope and nature of the present study, the creativity definition of Rhodes ( 2010 ) defines our approach in the best way: “It is both the capacity to combine or synthesize existing ideas, images, or expertise in original ways and the experience of thinking, reacting, and working in an imaginative way characterized by a high degree of innovation, divergent thinking, and risk taking.” (p. 27).

The literature stresses the linkages between constructivism and creativity (Asmar & Mady, 2013 ; Lim, 2014 ; Neo, 2003 ). Creativity is mentioned in the design thinking literature either as a characteristic of the process (e.g. Lewrick et al., 2020 ), or as one of the skills being developed throughout the process (Alhamdani, 2016 ; Clemente et al., 2017 ; West et al., 2012 ). The constructivist framework helps to understand the link between creativity and design thinking. For instance, divergent thinking —one well-studied aspect of creativity (Caughron et al., 2011 )—is fostered in design thinking since students need to explore and be flexible for handling real-world information they often have to collect themselves. Another example stresses how during the ideation process students have to make choices (IDEO n.d.). And during brainstorming, a technique commonly used in design thinking (Lewrick et al., 2020 ), students create and build on a pool of choices, and develop argumentations in relation to a final choice (IDEO n.d.). Moreover, in design thinking courses, facilitators help students to unleash their creative potential promoting a conducive environment to develop reflection. This helps them to learn from things what did (not) work (Kelley & Kelley, 2013 ). The link with creativity also pushes the instructional design of related environments. According to Caughron et al. ( 2011 ) systematic reviews of literature about creativity training stress the provision of challenging materials, real world exercises, along with multiple opportunities for practice by trainees, among others. These design guidelines reflect both constructivist and design thinking characteristics, as explained in previous sections.

Additionally, some scholars have put forward the linkage between problem-solving and creativity (Caughron et al., 2011 ; Martz et al., 2016 ; R. K. Sawyer, 2006 ). Sawyer ( 2006 ) points out that creative processes involve problem solving and decision making; similarly, decision making requires creative inspiration. Sawyer additionally stresses that creativity involves both problem solving and problem finding. Martz et al. ( 2016 ) suggest an interdependence between problem solving and creativity; and Star and Rittle-Johnson ( 2008 ) found that problem solvers show flexibility -one of the creativity dimensions (Torrance, 1974 )- when dealing with a challenging part of a problem.

Building on the available theoretical and empirical literature, the authors of this study put forward the following two hypotheses:

Hypothesis 1 (H1)

Students who participated in a design thinking course improve their problem solving skills.

Hypothesis 2 (H2)

Students who participated in a design thinking course improve their creativity skills.

The present study was set up as a field experiment in which university first-year students, regardless of their major, enrolled in the course ‘Analysis and Problem Solving’ (also referred to as the design thinking course), in an Ecuadorian University. This compulsory course seeks to develop in students their problem solving and creativity skills when developing solutions for real-life problems by applying design thinking. The study was set up throughout a complete academic term (from May to August 2019) and included administration of a pretest (t0), a mid-semester test (t1) and a post test (t2). During 14 weeks of classes students received a wide range of in-class training tasks and work in cooperative teams (five to six students) to find a solution for a real problem presented by an Ecuadorian organization (e.g. NGO, small business, etc.), called ‘sponsor’. At the end of the course, teams were expected to present a prototype solution to tackle the problem. In this study, students’ progress in terms of problem solving and creativity was investigated by analyzing their answers when solving a case study (see Research instrument section). Students tackled such case at the start (t0), in the middle (t1) and at end of the course (t2). On the base of a rubric, students, the facilitator, and student peers rated the case solution. In other words, the research data emerged from three different actors at three data points in time.

About the course

The Analysis and Problem Solving course adopts a design thinking approach (Fig.  1 ) based on the combination of both the model of the Hasso Plattner Institute of Design at Stanford University (d.school) ( 2010 ) and the “Double Diamond” model (Design Council, 2007 ); reported by Santos Ordóñez, González Lema, Puga, Párraga Lema, & Vega, ( 2017 ). The latter follows 6 stages.

Design thinking approach used in the Analysis and Problem Solving course

The first diamond of the design thinking approach clusters three stages: Research, Empathy and Define; while the second diamond consists of the other three stages: Ideate, Prototype and Validation. Each diamond represents the divergent (left side) and convergent (right side) thinking the students are expected to adopt. Moreover, the students were informed of the possibility of iterating through all design thinking stages; for example, students could do additional exploratory research at any stage, or re-define the problem after discovering a new insight while testing an early prototype.

Meeting one of the tenets of constructivism, and at the same time one main characteristic of design thinking, each facilitator searched for real problems (5 or 6) before starting the semester. Those problems were proposed mainly by NGOs or small businesses (called ‘sponsors’). During the first week of classes, facilitators presented the problems to their students and students indicated their interest about each problem by ranking them. Next, facilitators set up multi-disciplinary teams and assigned teams one of the problems to work upon during the semester, i.e. each team worked on a different problem. Students worked collaboratively in the same team during the whole semester analyzing the problem and proposing a solution (called course project) following the design thinking approach presented in Fig.  1 . Collaboration is also one of the tenets of constructivism and a characteristic of design thinking.

During the course, students applied specific techniques and tools in each design thinking stage, guided by the facilitator. They immediately applied those techniques and tools to tackle their projects during the class and when doing related homework. The course outline that includes the description of each design thinking stage as well as the techniques and tools learned in each stage is presented in Online Resource 1. Class sessions were very active and alive with plenty of time for students to apply and discuss the techniques and tools learned. Classrooms were equipped with a projector, rounded tables (one table per team), whiteboards, markers, post-its and other provisions to boost group communication. The course was divided into two large subparts, in the first part students worked along the three stages of the first diamond (Fig.  1 ). By the end of the third stage, the teams presented the progress on their course projects applying explicitly the three design thinking stages: they presented what (and how) they learned about the context of the problem and the stakeholders involved, insights discovered and how they (re)frame the problem. In the second part of the course, students adopted the three stages of the second diamond. They subsequently used their creativity to ideate as many solutions as possible to the defined problem. Next, they evaluated and filtered those ideas. In a next step they built prototypes to materialize the best ideas, testing them with real potential users. By the end of the course, the teams presented their projects, explaining their solution process and presenting an argumentation as to the adequacy of their problem solution. All the sponsors were invited to attend these presentations. Online Resource 2 depicts an example of the development of a prototype solution proposed by one team, during the course. Their sponsor was Asperger Foundation – Ecuador who supports parents of children with Asperger’s syndrome. In this case, they focused on “clients” who had limited access to the services provided by the foundation. From the many ideas being generated in the Ideate stage, the best idea was selected to develop an app for parents of children with Asperger’s syndrome. Next, they built a low-fidelity prototype using basic materials to outline the data flow and to check the usefulness and usability of their proposed functionality. This helped validating their prototype with the sponsor and potential users. This stage helped getting feedback in view of making adjustments. By the end of the course, the team built a high-fidelity prototype using an online tool that aimed at delivering a close instantiation of the final product. This was presented during the final exam in the presence of the sponsor, facilitator and classmates. The sponsor – in the case of the Asperger foundation – was very satisfied with the results.

The students attended 28 sessions of 90 min (3 h per week). The course structure, contents, activities and materials were the same for all sections and facilitators followed the same guidelines. Finally, it should be noted that the other courses taken by students in their first semester are mainly focused on the development of hard skills instead of skills such as problem solving and creativity.

Participants

In this study N = 910 freshmen students participated who were enrolled in the Analysis and Problem Solving course. The average age was 19 years (SD = 2.17). The students’ background information is presented in Table 1 . The majority of the students were men, coming from urban areas. As expected, since this course is offered to first-year studens, most of them did not have working experience. Most of the participants were enrolled in a Science and Engineering program.

Given the large number of students, the course was taught to subgroups of students (sections). Each section comprised 35 students -on average- from different disciplines. In total, 27 sections of the course guided by 26 facilitators were included in this study. The facilitators were informed about the research study beforehand to minimize risk of bias. Informed consent was signed by all students after ethical clearance from university authorities.

Research instruments

In this study the research instruments used were (a) a case study developed by the authors Footnote 1 that was followed by a series of tasks/questions to be answered by students individually; (b) a rubric based on case specific criteria to map the quality of the problem solving and creativity skills. The same case study was presented at t0, t1 and t2. This case was based on a real-life problem related to user-experiences of a new service for riding bicycles at a university campus. To observe the use of problem solving and creativity skills, students were asked to complete four tasks related to the case study using a paper-based form.

Identify and properly define the main problem of the case.

Before proposing a solution to the problem you defined, what would be your strategies or steps to follow?

Propose and describe at least one innovative solution for the problem defined in question 1.

Reflect on the solution process(es) resulting from the former task.

The case study and the tasks were not used as scaffolds of the design thinking process, they were never discussed during the classes and they did not have any influence in the students’ course grades. Students did not have access to the case or tasks beforehand, and they were not informed that the same case and tasks would be applied three times. The students received 25–30 min to read the case study and solve the tasks/questions. Next, the solutions to the case study proposed by each student for the 4 tasks/questions were rated by peers, by themselves, and by their facilitator. The students identified themselves with a code only; thus, rating by peers and by facilitators involves a blind process. The involvement of the three raters is critical to respect the underlying constructivist assumptions related to design thinking; i.e. given the emphasis on students’ personal involvement and engagement, the key role of collaboration with peers and the supportive role adopted by the facilitators, all three should put forward their measurement of the impact on problem solving and creativity. In addition, the answers posed by the students for the 4 tasks/questions were rated on the base of rubrics. The evaluation instrument used by the three referred raters was based on an adapted version of the VALUE (Valid Assessment of Learning in Undergraduate Education) rubrics Footnote 2 (Rhodes, 2010 ), and it focused on the identification and analysis of indicators related to problem solving and creativity. Each rubric criterion presents a description to be rated along five performance levels: A, B, C, D, E; where A represents the highest score and E the lowest. Given the scope of the course, the problem solving rubric used in the study focused on 4 out of the 6 original VALUE rubric criteria: (1) Define problem, (2) Identify strategies, (3) Propose solutions, (4) Evaluate potential solutions. The creativity rubric included 4 out of 6 of the original VALUE rubric items: (1) Acquiring competencies, (2) Taking risks, (3) Innovative thinking, (4) Connecting, synthesizing, transforming. Eight criteria were provided to develop a rubric to rate case solutions from a problem solving and creativity angle. The rubric started with the following instruction: “In order to use the rubric efficiently, we suggest you the following criteria to be applied to each of the answers about the case. Task 1 could be evaluated using the criterion Define problem; Task 2 with Identify strategies; Task 3 with Propose solutions, Innovative thinking, Taking risks; Task 4 with Evaluate Potential Solutions, Acquiring competencies, and Connecting, synthesizing, transforming”. The former induced a systematic approach in which raters first read the student input for each task and next applied the specific rubric criterion. This resulted in defining an explicit performance level (A, B, C, D, E). Some examples of the answers for question #3 (Propose and describe at least one innovative solution for the problem defined in question 1) were:

Example 1: “Students must take a cycling simulation test that recreates real-life campus’ road conditions to verify that students know how to use the bicycle correctly on different types of slopes. If a student passes the test, he will be allowed to use the bicycles” Example 2: “Visible and intuitive signs will be placed along the road of the bicycle lane to let cyclists know the moment and the type of gear shift that should be applied to the bicycle, depending on the peculiarity of each section of the road.” Example 3: “An online training for students embedded in one of the university’s technology platforms about the correct use of bicycles on campus. At the end of the training, students must take a test, and those who pass the test will be registered on a database of people allowed to borrow a bicycle on campus.”

Moreover, a pilot study collected feedback from course facilitators and undergraduate students (not involved in the present study) regarding the research instruments. Thus, this feedback allowed the authors to check the translation (from English to Spanish) and the consistency in interpretations. Note that these VALUE rubrics were not shared as part of the course; i.e. they were not part of the learning process.

Prior research has reported acceptable validity and reliability of VALUE rubrics (Finley, 2012 ; Mcconnell & Rhodes, 2017 ; Rhodes & Finley, 2013 ; Simper, 2018 ). Nevertheless, the translated and adapted versions of the instruments were reassessed in the context of the present study using univariate and multivariate techniques. Table 2 summarizes reliability analysis of the instruments at t0, t1 and t2 obtaining Cronbach’s alpha; i.e., how closely related rubric items are as a group. Given the use by three different raters, the coefficients suggest that the items for each skill (problem solving and creativity) have relatively acceptable internal consistency.

To check construct validity, the problem solving and creativity items were considered in an exploratory factor analysis (principal component analysis with Varimax rotation) by imposing a two-factor solution (see Table 3 ). The analysis was repeated on the base of data from students, peers, and the facilitators at t0, t1 and t2. The analysis results show how all four creativity items load on the same factor (Factor A) at t0, t1 and t2 based on data from the three actors, except when processing t0 student self-evaluation. The problem solving items loaded on the second factor (Factor B). However, two items often loaded on the creativity factor (“Propose Solutions” and “Evaluate Potential Solutions”). At t2, most of the items fitted the specific factor as expected. Thus, the results reiterate the conceptual overlap between problem solving and creativity as stated earlier (Sawyer, 2006 ). In sum, this factor analysis allow us to conclude that the instruments were valid in the present context.

Research procedures

Building on the course structure, data were collected three times (t0, t1, t2) during actual class time and using paper-based forms. During the first week the first data collection was carried out (t0), then 8 weeks later (week 9) for a second time (t1) and 6 weeks later (week 15) for the last time. Given the natural (or authentic) setting of this study, the number of students participating in each data collection point differed. Details about the number of participants and procedure of the data collection in each time point and per rater are presented in a chart that can be found at the Online Resource 3. Each data collection session lasted about 60–75 min. The data collected during this research did not affect students’course grades. Results of this study are not reported at the level of course’s sections.

Before the intervention, the 26 facilitators agreed to participate in this study. Prior to the study, they received a training session, which focused on data collection and the application of rubrics to evaluate students’ performance in terms of problem solving and creativity. Hence, a standardized procedure was followed by all facilitators as they received instructions and a “kit” with the forms for the collection sessions.

At t0, in each course section, the students signed an informed consent, filled out a background questionnaire, and received the case study next to a sheet with the tasks/questions to be answered. Once the time for reading the case and answering the tasks was up, the facilitator collected all the answers’ sheets. Immediately after this part of the session, the facilitator assigned randomly to each student one answer sheet from one of the classmates (blinded version) and a rubric (see Research Instrument section) to rate the answers. At that stage, the facilitator explained how to use the rubric. Once completed, the facilitator collected the original answer sheets and filled out rubrics. Next, students were given their own answer sheets (identified by a personal code) as well as the same rubric to rate their personal answers. At the end of the session, the facilitators collected all sheets. Afterwards, the facilitators applied the rubric themselves to evaluate the work of each student. To facilitate this part of the process, SurveyMonkey software was used. The same procedure was applied at t1 and t2. As stated earlier, students were not aware of when and how they would be evaluated.

Analysis approach

To test the two hypotheses on whether students would show a higher performance in their problem solving (H1) and creativity (H2) skills as a result of a design thinking course, the researchers adopted repeated measures ANOVA. In addition, the perspectives of the students, their peers, and the facilitator were considered. The analyses were carried out with SPSS version 25. A significance level of p < 0.05 was put forward. Effect sizes (Cohen’s d) were additionally calculated in view of interpreting the importance of the analysis results.

Descriptive data analysis

Table 4 summarizes descriptive data of the dependent variables at t0, t1, t2. The results of the attained average scores reflected an apparent improvement over the time in all cases.

Figure  2 illustrates a consistent increase in problem solving scores according to the raters (students’ self-evaluation, peers, facilitators). Figure  3 shows the students’ performance in creativity based on the three raters. Hence, there it is evident an overall improvement from t0 to t2.

Mean in “Problem solving” scores (N students = 693; N peers = 682; N facilitators = 607)

Mean of “Creativity” scores (N students = 691; N peers = 682; N facilitators = 607)

The results of a correlation analysis of the scores are presented in Table 5 . The correlation measures describe positive and significant correlations.

Hypothesis 1 (H1): students who participated in a design thinking course improve their problem solving skills.

Self-evaluation results: the repeated measures within-subjects ANOVA show a statistically significant effect on problem solving performance over the time, according to the students’ evaluation, as presented in Table 6 . When looking at the analysis of contrasts results, we find a significant change from t0 to t2, as well as from t0 to t1, and from t1 to t2. We observe an effect size of d = 0.85 in the change from t0 to t2. The effect size between t0 and t1 is larger than between t1 and t2.

Peers evaluation results: problem solving performance seems significantly affected over the time (see Table 6 ). Contrasts results reveal a statistically significant increase from t0 to t2, as well as from t0 to t1, and also from t1 to t2. In contrast to self-evaluation’s effect sizes, a smaller effect (d = 0.60) is observed when comparing t0 and t2. The effect size from t0 to t1 is larger compared to t1 to t2.

Facilitators evaluation results: repeated measures ANOVA reflect that problem solving performance shows a statistically significant improvement over the time (see Table 6 ). When zooming in the contrasts results, we observe significant changes from t0 to t2, as well as from t0 to t1, and also from t1 to t2. The ratings provided by facilitators show the largest effect size from t0 to t2 (d = 1.17), compared to the other two raters. The effect size between t0 and t1 is much larger than the change from t1 to t2.

Therefore, we can reject the null hypothesis and accept H1 : Students who participated in a design thinking course improve their problem solving skills .

Hypothesis 2 (H2): students who participated in a design thinking course improve their creativity skills

Self-evaluation results: the repeated measures within-subjects ANOVA results reveal a statistically significant increase in creativity performance over the time (see Table 7 ). When looking at the contrasts results, we observe statistically significant changes from t0 to t2, as well as from t0 to t1, and also from t1 to t2. We observe an effect size of d = 0.94 when comparing t0 to t2. The effect size of changes between t0 to t1 is larger than the changes observed from t1 to t2.

Peers evaluation results: following the above statistical analysis approach, Table 7 shows that creativity performance has a significant increase over the time. Moreover, contrasts results indicate statistically significant improvements from t0 to t2, as well as from t0 to t1, and also from t1 to t2. There is a slight smaller effect size related to changes from t0 to t2 (d = 0.79), compared to the one observed in students’ self-evaluation. The effect size from t0 to t1 is larger compared to t1 to t2.

Facilitators evaluation results: creativity performance shows a statistically significant improvement over the time, as shown in Table 7 . When looking at contrasts results, we also found significant changes from t0 to t2, as well as from t0 to t1, and also from t1 to t2. Similar to what happened in Problem Solving results when analyzing facilitators’ ratings, this type of rater reflects the largest effect size from t0 to t2, (d = 1.28), compared to students’ self-assessment and peers. The effect size of changes from t0 to t1 is considerably larger than the effect size related to changes from t1 to t2.

Therefore, we reject the null hypothesis and accept H2 : Students who participated in a design thinking course improve their creativity skills .

The present study explored the effects of design thinking on problem solving and creativity skills in first-year university students at three points in time (t0, t1, t2). A key aspect of the present study is the multi-actor perspective since the data were collected from different sources: self-reports, from peers and from facilitators. In addition, a strength of the present study is the robust design based on an operational definition of design thinking and the adoption of reliable and valid measures to study the impact on problem solving and creativity.

According to the data collected from the raters, the design thinking intervention had a positive significant impact on students’ problem solving (H1) and creativity (H2) skills when comparing t0 vs t2, as well as the other time slots t0 vs t1, and t1 vs t2 (see Table 6 and Table 7 ). A relevant observation is that from t0 to t1 the effect size of related changes seems to be larger than from t1 to t2. Nevertheless, all the time slots show a positive and statistically significant improvement.

Note that by t1, students had experienced the three design thinking stages: Research, Empathy and Define. Thus, in general terms, students were expected to adopt a human-centered approach, develop insights into their project-related problems and (re)defined their specific problem focus. At t2, the students had finished the other three design thinking stages: Ideate, Prototype, Validation; i.e., in the second part of the course students were encouraged to generate as many solution ideas as possible and tested the best ones with real users until proposing one that better fits to the problem previously defined. The scope of this study does as such not allow to determine at what specific stage the strongest development in problem solving or creativity skills did occur. Nevertheless, based on the techniques and tools students adopted at each stage, we might conclude that the first diamond of design thinking (research, empathy, defined) could contribute to a larger extent to the development of problem solving skills; while the second diamond (ideate, prototype validation) might have contributed more to boost students’ creativity skills.

Regarding Hypothesis 1, the results can be linked to the main features of the design thinking design and characteristics that were inspired by constructivist learning theory (Pande & Bharathi, 2020 ). The systematic mapping of problem solving phases onto the design thinking phases might have offered students sufficient structure and support to deal successfully with the complex problem solving projects; or as Lindberg et al. ( 2011 ) pose: Design thinking promotes a problem exploration space where instead of creating general hypotheses or theories about the problem, people get an intuitive (not completely verbalized) understanding through observing exemplary use cases or scenarios; and synthesizes this information to point of views. Our findings about the positive impact on problem-solving skills after a design thinking intervention confirm earlier research (Alhamdani, 2016 ; Bhatnagar & Badke-Schaub, 2017 ; Khalaf et al., 2012 ; Lee & Benza, 2015 ; Linton & Klinton, 2019 ; Lugmayr et al., 2014 ; Matsushita et al., 2015 ; Taajamaa et al., 2013 ). In addition, the emphasis on structured collaboration, explicit reflection on experiences, plans and products and the explicit availability of feedback by the facilitators and ‘sponsors’ might have boosted the design thinking potential. The importance of structure in the adoption of constructivism is a constant in the literature (Alesandrini & Larson, 2002 ). However, the lack of structure is often used to explain failure in the adoption of constructivist learning theories (see Kirschner et al., 2006 ). Therefore, current constructivist approaches often explicitly stress and embrace a ‘guided discovery’ principle (Mayer, 2004 ).

Furthermore, hypothesis 2 was also accepted. Creativity is often looked at through a constructivist theoretical lens (Edwards-Schachter et al., 2015 ) and it is one of the main skills associated with the outcomes of design thinking (Tsai, 2021 ). Prior research reported a positive effect of design thinking on the development of creativity skills (Balakrishnan, 2021 ; Benson & Dresdow, 2015 ; Clemente et al., 2017 ; Lee & Benza, 2015 ; Saggar et al., 2017 ; West et al., 2012 ). To explain our positive results, we can refer to specific design thinking design guidelines that pushed students’ divergent thinking in a pre-structured way. As Lindberg et al. ( 2011 ) point out there is a ‘solution space’ in design thinking where people are asked for a vast number of ideas in parallel and to make these explicit through sketching and prototyping techniques. In this way, ideas are expected to be converted into cognitive representations. Both spaces, problem space and solution space, in design thinking generate “a system of checks and balances to ensure that the conclusive solution will be both innovative and suitable for the social system that the design problem addresses” (Lindberg et al., 2011 , p. 6). Since the design guidelines offer structure, Sawyer ( 2011 ) stresses the need to balance this structure with more open instructional approaches when pursuing an impact on creativity. For example, one study based on self-perception questionaries (Ohly et al., 2016 ) found no design thinking-impact on creative self-efficacy after an intervention (n = 69). According to the authors of that study, the group format used in that course as well as a weak focus on creativity (shorter than a third of the course) may be the cause. The latter reinforces the importance of a proper structure, planning and guidance by the facilitator during a design thinking course which is fundamental, especially for promoting creativity.

Our findings for both hypotheses show a decrease in effect size (Cohen’s d) in the facilitator scores when comparing t0 to t1 versus t1 to t2 (Table 6 and Table 7 ). Thus, the facilitator expectations might have introduced bias in students’ evaluation (Jussim, 1989 ). In fact, some facilitators reported that their expectations on students’ performance were higher at the end of the course than at the mid-term. Nevertheless, it is interesting that for both skills, changes in facilitators’ scores reflect the largest effect sizes from t0 to t2, compared to students’ self-evaluation and peers’ scores in the same time slot. The above suggests the largest effect sizes in both skills’ improvement is related to the level of experience of raters. In the context of this study, facilitators could be considered the best trained raters, not only because their knowledge and experience in design thinking; but also because of their experience as teachers in the Analysis and Problem Solving course and other courses.

A key limitation of the present study is the lack of a control group. This is difficult to achieve since all first-year students in this university must enroll in the Analysis and Problem Solving course. Hence, future research could compare first-year scores from students enrolled in a different university in comparable programs. A further limitation to be addressed in future research is the background variables of students (professional experiences, gender) and the potential impact of mediating variables, such as motivation and/or self-efficacy. Moreover, the multi-actor focus of the present study could also be enriched by adding data resulting from qualitative research. As exemplified above, perceptions of the facilitators might be biased due to their expectations of progress related to time. It would be also interesting to complement the results obtained with the projects developed by students’ teams as part of the course. However, since the projects represent a significant percentage of the course grade, we prefer not to include them as measurement instruments since this would violate the informed consent agreement and could have introduced bias. As mentioned earlier, there is research pointing at the validity and reliability of specific VALUE rubrics; nevertheless, in our current context an inter-rater reliability study could result in more convincing arguments to adopt the instruments used. Finally, some readers may have a concern about a potential Hawthorne effect; however we rule out that risk since (a) students were informed that their participation in this course would not affect their grades; (b) students did not know exactly when and how they would be evaluated; (c) students’ names and personal information remained anonymous during the entire process; (d) students did not have access to consult their case’s answers at any point of the study; and the instruments as well as the results related to the study were not discussed during the semester.

Conclusions

The current study was an attempt to address critical features of current and past empirical research to study the impact of design thinking on creativity and problem solving skills of students in higher education. Therefore, we aimed at answering the call of Razzouk and Shute ( 2012 ) to set up a new wave of design thinking research that builds on valid performance-based assessments to examine the effects of the design thinking process on various students’ skills. Building on data from a large sample size and an intervention that operationalized design thinking design principles in a replicable way, we added a multi-actor focus to the impact study by looking at the performance ratings from students, peers and facilitators. In addition, the researchers are open to exchange their approach, materials, procedures and research instruments to facilitate a wider adoption of design thinking in higher education and achieve the key aim of developing the skills demanded by labor markets.

Data availability

The researchers are open to exchange, upon request, their approach, materials, procedures and research instruments.

Code availability

Not applicable.

The case study can be shared upon request to the authors.

The adapted version of the VALUE rubrics used in this study can be shared upon request to authors. The original versions of the VALUE rubrics can be accessed at https://www.aacu.org/value-rubrics .

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Acknowledgements

We would like to acknowledge ESPOL’s i3lab-Entrepreneurship and Innovation Center for administrative support. Also, our acknowledgment to facilitators and students for the participation and valuable feedback to carry out the study.

This research was partially funded by Escuela Superior Politecnica del Litoral and VLIR Network Ecuador.

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Guaman-Quintanilla, S., Everaert, P., Chiluiza, K. et al. Impact of design thinking in higher education: a multi-actor perspective on problem solving and creativity. Int J Technol Des Educ 33 , 217–240 (2023). https://doi.org/10.1007/s10798-021-09724-z

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• How to solve problems using the design ...

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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• Josh Singer
• Jun 24, 2021

The Rise Of Design Thinking As A Problem Solving Strategy

• 18 min read
• UX , Design , Product Strategy
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About The Author

Josh Singer is a UX Designer and former Math Editor at Renaissance Learning , where he has worked on products and written content for educators and students … More about Josh ↬

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Having spent the last 20 years in the world of educational technology working on products for educators and students, I have learned to understand teachers and administrators as designers themselves, who use a wide set of tools and techniques to craft learning experiences for students. I have come to believe that by extending this model and framing all users as designers, we are able to mine our own experiences to gain a deeper empathy for their struggles. In doing so, we can develop strategies to set our user-designers up to successfully deal with change and uncertainty.

If you are a designer, or if you have worked with designers any time in the last decade, you are probably familiar with the term “design thinking.” Typically, design thinking is represented by a series of steps that looks something like this:

There are many variations of this diagram, reflective of the multitude of ways that the process can be implemented. It is typically a months-long undertaking that begins with empathy: we get to know a group of people by immersing ourselves in a specific context to understand their tasks, pain points, and motivations. From there, we take stock of our observations, looking for patterns, themes, and opportunities, solidifying the definition of the problem we wish to solve. Then, we iteratively ideate, prototype, and test solutions until we arrive at one we like (or until we run out of time).

Ultimately, the whole process boils down to a simple purpose: to solve a problem. This is not a new purpose, of course, and not unique to those of us with “Designer” in our job titles. In fact, while design thinking is not exactly the same as the scientific method we learned in school, it bears an uncanny resemblance:

By placing design thinking within this lineage, we equate the designer with the scientist, the one responsible for facilitating the discovery and delivery of the solution.

At its best, design thinking is highly collaborative. It brings together people from across the organization and often from outside of it, so that a diverse group, including those whose voices are not usually heard, can participate. It centers the needs and emotions of those we hope to serve. Hopefully, it pulls us out of our own experiences and biases, opening us up to new ways of thinking and shining a light on new perspectives. At its worst, when design thinking is dogmatically followed or cynically applied, it becomes a means of gatekeeping, imposing a rigid structure and set of rules that leave little room for approaches to design that do not conform to an exclusionary set of cultural standards.

Its relative merits, faults, and occasional high-profile critiques notwithstanding, design thinking has become orthodoxy in the world of software development, where not using it feels tantamount to malpractice. No UX Designer’s portfolio is complete without a well-lit photo capturing a group of eager problem solvers in the midst of the “Define” step, huddled together, gazing thoughtfully at a wall covered in colorful sticky notes . My colleagues and I use it frequently, sticky notes and all, as we work on products in EdTech.

Like “lean,” the design thinking methodology has quickly spread beyond the software industry into the wider world. Today you can find it in elementary schools , in nonprofits , and at the center of innovation labs housed in local governments .

Amidst all of the hoopla, it is easy to overlook a central assumption of design thinking, which seems almost too obvious to mention: the existence of a solution . The process rests on the premise that, once the steps have been carried out, the state of the problem changes from ‘unsolved’ to ‘solved.’ While this problem-solution framework is undeniably effective, it is also incomplete. If we zoom out , we can see the limits of our power as designers, and then we can consider what those limits mean for how we approach our work.

Chaos And The Limits Of Problem Solving

An unchecked belief in our ability to methodically solve big problems can lead to some pretty grandiose ideas. In his book, Chaos: Making a New Science , James Gleick describes a period in the 1950s and ’60s when, as computing and satellite technologies continued to advance, a large, international group of scientists embarked on a project that, in hindsight, sounds absurd. Their goal was not only to accurately predict, but also to control the weather:

“There was an idea that human society would free itself from weather’s turmoil and become its master instead of its victim. Geodesic domes would cover cornfields. Airplanes would seed the clouds. Scientists would learn how to make rain and how to stop it.” — “Chaos: Making a New Science,” James Gleick

It is easy to scoff at their hubris now, but at the time it was a natural result of an ever-heightening faith that, with science, no problem is too big to solve. What those scientists did not account for is a phenomenon commonly known as the butterfly effect, which is now a central pillar of the field of chaos theory. The butterfly effect describes the inherent volatility that arises in complex and interconnected systems. It gets its name from a famous illustration of the principle: a butterfly flapping its wings and creating tiny disturbances in the air around it on one side of the globe today can cause a hurricane tomorrow on the other. Studies have shown that the butterfly effect impacts everything in society from politics and the economy to trends in fashion .

Our Chaotic Systems

If we accept that, like the climate, the social systems in which we design and build solutions are complex and unpredictable, a tension becomes apparent. Design thinking exists in a context that is chaotic and unpredictable by nature, and yet the act of predicting is central. By prototyping and testing , we are essentially gathering evidence about what the outcome of our design will be, and whether it will effectively solve the problem we have defined. The process ends when we feel confident in our prediction and happy with the result.

I want to take pains to point out again that this approach is not wrong! We should trust the process to confirm that our designs are useful and usable in the immediate sense. At the same time, whenever we deliver a solution, we are like the butterfly flapping its wings, contributing (along with countless others) to a constant stream of change. So while the short-term result is often predictable, the longer-term outlook for the system as a whole, and for how long our solution will hold as the system changes, is unknowable.

Impermanence

As we use design thinking to solve problems, how do we deal with the fact that our solutions are built to address conditions that will change in ways we can’t plan for?

One basic thing we can do is to maintain awareness of the impermanence of our work, recognizing that it was built to meet the needs of a specific moment in time . It is more akin to a tree fort constructed in the woods than to a castle fortress made from stone. While the castle may take years to build and last for centuries, impervious to the weather while protecting its inhabitants from all of the chaos that exists outside its walls, the tree fort, even if well-designed and constructed, is directly connected to and at the mercy of its environment. While a tree fort may shelter us from the rain, we do not build it with the expectation that it will last forever, only with the hope that it will serve us well while it’s here. Hopefully, through the experience of building it, we continue to learn and improve.

The fact that our work is impermanent does not diminish its importance, nor does it give us the license to be sloppy. It means that the ability to quickly and consistently adapt and evolve without sacrificing functional or aesthetic quality is core to the job, which is one reason why design systems , which provide consistent and high-quality reusable patterns and components, are crucial.

Designing For User-Designers

A more fundamental way to deal with the impermanence of our work is to rethink our self-image as designers. If we identify only as problem solvers, then our work becomes obsolete quickly and suddenly as conditions change, while in the meantime our users must wait helplessly to be rescued with the next solution. In reality, our users are compelled to adapt and design their own solutions, using whatever tools they have at their disposal. In effect, they are their own designers, and so our task shifts from delivering full, fixed solutions to providing our user-designers with useful and usable tools specific to their needs .

In thinking from this perspective, we can gain empathy for our users by understanding our place as equals on a continuum, each of us relying on others, just as others rely on us.

Key Principles To Center The Needs Of User-Designers

Below are some things to consider when designing for user-designers. In the spirit of the user-designer continuum and of finding the universal in the specific, in the examples below I draw on my experience from both sides of the relationship. First, from my work as a designer in the EdTech space, in which educators rely on people like me to produce tools that enable them to design learning experiences for students. Second, as a user of the products, I rely on them in my daily UX work.

1. Don’t Lock In The Value

It is crucial to have a clear understanding of why someone would use your product in the first place, and then make sure not to get in the way. While there is a temptation to keep that value contained so that users must remain in your product to reap all of the benefits, we should resist that mindset.

Remember that your product is likely just one tool in a larger set, and our users rely on their tools to be compatible with each other as they design their own coherent, holistic solutions. Whereas the designer-as-problem-solver is inclined to build a self-contained solution, jealously locking value within their product, the designer-for-designers facilitates the free flow of information and continuity of task completion between tools however our user-designers choose to use them. By sharing the value, not only do we elevate its source, we give our users full use of their toolbox.

An Example As A Designer Of EdTech Products:

In student assessment applications, like in many other types of applications, the core value is the data. In other words, the fundamental reason schools administer assessments is to learn about student achievement and growth. Once that data is captured, there are all sorts of ways we can then use it to make intelligent, research-based recommendations around tasks like setting student goals, creating instructional groups, and assigning practice. To be clear, we do try very hard to support all of it in our products, often by using design thinking. Ultimately, though, it all starts with the data.

In practice, teachers often have a number of options to choose from when completing their tasks, and they have their own valid reasons for their preferences. Anything from state requirements to school policy to personal working style may dictate their approach to, say, student goal setting. If — out of a desire to keep people in our product — we make it extra difficult for teachers to use data from our assessments to set goals outside of our product (say, in a spreadsheet), then instead of increasing our value, we have added inconvenience and frustration. The lesson, in this case, is not to lock up the data! Ironically, by hoarding it, we make it less valuable. By providing educators with easy and flexible ways to get it out, we unlock its power.

An Example As A User Of Design Tools:

I tend to switch between tools as I go through the design thinking process based on the core value each tool provides. All of these tools are equally essential to the process, and I count on them to work together as I move between phases so that I don’t have to build from scratch at every step. For example, the core value I get from Sketch is mostly in the “Ideation” phase, in that it allows me to brainstorm quickly and freely so that I can try out multiple ideas in a short amount of time. By making it easy for me to bring ideas from that product into a more heavy-duty prototyping application like Axure , instead of locking them inside, Sketch saves me time and frustration and increases my attachment to it. If, for competitive reasons, those tools ceased to cooperate, I would be much more likely to drop one or both.

2. Use Established Patterns

It is always important to remember Jakob’s Law , which states simply that users spend more time on other sites than they spend on yours. If they are accustomed to engaging with information or accomplishing a task a certain way and you ask them to do it differently, they will not view it as an exciting opportunity to learn something new. They will be resentful. Scaling the learning curve is usually painful and frustrating. While it is possible to improve or even replace established patterns, it’s a very tall order . In a world full of unpredictability, consistent and predictable patterns among tools create harmony between experiences.

By following conventions around data visualization in a given domain, we make it easy for users to switch and compare between sources. In the context of education, it is common to display student progress in a graph of test scores over time, with the score scale represented on the vertical axis and the timeline along the horizontal axis. In other words, a scatter plot or line graph, often with one or two more dimensions represented, maybe by color or dot size. Through repeated, consistent exposure, even the most data-phobic teachers can easily and immediately interpret this data visualization and craft a narrative around it.

You could hold a sketching activity during the “Ideate” phase of design thinking in which you brainstorm dozens of other ways to present the same information. Some of those ideas would undoubtedly be interesting and cool, and might even surface new and useful insights. This would be a worthwhile activity! In all likelihood, though, the best decision would not be to replace the accepted pattern. While it can be useful to explore other approaches, ultimately the most benefit is usually derived from using patterns that people already understand and are used to across a variety of products and contexts.

In my role, I often need to quickly learn new UX software, either to facilitate collaboration with designers from outside of my organization or when my team decides to adopt something new. When that happens, I rely heavily on established patterns of visual language to quickly get from the learning phase to the productive phase. Where there is consistency, there is relief and understanding. Where there is a divergence for no clear reason, there is frustration. If a product team decided to rethink the standard alignment palette, for example, in the name of innovation, it would almost certainly make the product more difficult to adopt while failing to provide any benefit.

3. Build For Flexibility

As an expert in your given domain, you might have strong, research-based positions on how certain tasks should be done, and a healthy desire to build those best practices into your product. If you have built up trust with your users, then adding guidance and guardrails directly into the workflow can be powerful. Remember, though, that it is only guidance. The user-designer knows when those best practices apply and when they should be ignored. While we should generally avoid overwhelming our users with choices , we should strive for flexibility whenever possible.

An Example As A Designer Of EdTech Products

Many EdTech products provide mechanisms for setting student learning goals. Generally, teachers appreciate being given recommendations and smart defaults when completing this task, knowing that there is a rich body of research that can help determine a reasonable range of expectations for a given student based on their historical performance and the larger data set from their peers. Providing that guidance in a simple, understandable format is generally beneficial and appreciated. But, we as designers are removed from the individual students and circumstances, as well as the ever-changing needs and requirements driving educators’ goal-setting decisions. We can build recommendations into the happy path and make enacting them as painless as possible, but the user needs an easy way to edit our guidance or to reject it altogether.

The ability to create a library of reusable objects in most UX applications has made them orders of magnitude more efficient. Knowing that I can pull in a pre-made, properly-branded UI element as needed, rather than creating one from scratch, is a major benefit. Often, in the “Ideate” phase of design thinking, I can use these pre-made components in their fully generic form simply to communicate the main idea and hierarchy of a layout. But, when it’s time to fill in the details for high-fidelity prototyping and testing, the ability to override the default text and styling, or even detach the object from its library and make more drastic changes, may become necessary. Having the flexibility to start quickly and then progressively customize lets me adapt rapidly as conditions change, and helps make moving between the design thinking steps quick and easy.

4. Help Your User-Designers Build Empathy For Their Users

When thinking about our users as designers, one key question is: who are they designing for? In many cases, they are designing solutions for themselves, and so their designer-selves naturally empathize with and understand the problems of their user-selves. In other cases, though, they are designing for another group of people altogether. In those situations, we can look for ways to help them think like designers and develop empathy for their users.

For educators, the users are the students. One way to help them center the needs of their audience when they design experiences is to follow the standards of Universal Design for Learning , equipping educators to provide instructional material with multiple means of engagement (i.e., use a variety of strategies to drive motivation for learning), multiple means of representation (i.e., accommodate students’ different learning styles and backgrounds), and multiple means of action and expression (i.e., support different ways for students to interact with instructional material and demonstrate learning). These guidelines open up approaches to learning and nudge users to remember that all of the ways their audience engages with practice and instruction must be supported.

Anything a tool can do to encourage design decisions that center accessibility is hugely helpful, in that it reminds us to consider those who face the most barriers to using our products. While some commonly-used UX tools do include functionality for creating alt-text for images, setting a tab order for keyboard navigation, and enabling responsive layouts for devices of various sizes, there is an opportunity for these tools to do much more. I would love to see built-in accessibility checks that would help us identify potential issues as early in the process as possible.

Hopefully, by applying the core principles of unlocking value, leveraging established patterns, understanding the individual’s need for flexibility , and facilitating empathy in our product design, we can help set our users up to adapt to unforeseen changes. By treating our users as designers in their own right, not only do we recognize and account for the complexity and unpredictability of their environment, we also start to see them as equals.

While those of us with the word “Designer” in our official job title do have a specific and necessary role, we are not gods, handing down solutions from on high, but fellow strugglers trying to navigate a complex, dynamic, stormy world. Nobody can control the weather , but we can make great galoshes, raincoats, and umbrellas.

Further Reading

• If you’re interested in diving into the fascinating world of chaos theory, James Gleick’s book Chaos: Making a New Science , which I quoted in this article, is a wonderful place to start.
• Jon Kolko wrote a great piece in 2015 on the emergence of design thinking in business, in which he describes its main principles and benefits. In a subsequent article from 2017, he considers the growing backlash as organizations have stumbled and taken shortcuts when attempting to put theory into practice, and what the lasting impact may be. An important takeaway here is that, in treating everyone as a designer, we run the risk of downplaying the importance of the professional Designer’s specific skill set. We should recognize that, while it is useful to think of teachers (or any of our users) as designers, the day-to-day tools, methods, and goals are entirely different.
• In the article Making Sense in the Data Economy , Hugh Dubberly and Paul Pangaro describe the emerging challenges and complexities of the designer’s role in moving from the manufacture of physical products to the big data frontier. With this change, the focus shifts from designing finished products (solutions) to maintaining complex and dynamic platforms, and the concept of “meta-design” — designing the systems in which others operate — emerges.
• To keep exploring the ever-evolving strategies of designing for designers, search Smashing Magazine and your other favorite UX resources for ideas on interoperability, consistency, flexibility, and accessibility!

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A Breakdown of Each Step in The Design Thinking Process

Design thinking is an important approach to problem-solving. In this article, learn all about each step of the design thinking process, including how to implement it and why it matters.

Whatever problem you’re attempting to solve next, whether it is in the field of business, design, or something else, it can benefit significantly from the application of design thinking. That is because design thinking is a problem-solving methodology that places paramount emphasis on the core principles of empathy, creativity, and iterative processes, which often result in the generation of truly innovative and effective solutions.

This article will serve as your guide to understanding the definitive, 5-step design thinking process. We'll break down each step for you, offering a comprehensive understanding of its purpose and relevance, along with a brief guide on how to execute it.

What is the Design Thinking Process and Why is it so Popular?

• Next Steps to Learn Design Thinking

Design thinking is a human-centred and creative problem-solving approach that places a strong emphasis on understanding and addressing the unmet needs of users. It prioritises the use of empathy to delve deep into users' perspectives, and uncover latent desires and insights that are often overlooked by conventional problem-solving methods. 

Design thinking follows a five-step process - empathise, define, ideate, prototype, and test - in which iteration and continuous refinement play an important part. This can often make the process non-linear in its application, that is to say, these five steps are not always followed sequentially. You may frequently find yourself moving back and forth between steps, and therefore repeating one or more steps, in order to eventually reach the best possible solution.

The popularity of design thinking stems from its user-centricity, its applicability in situations where the problem itself may be ill-defined or unknown, and its capacity to fuel creative and innovative solutions. These give the process its transformative potential and wide application for problem-solving across industries.

Breakdown of Each Step of the Design Thinking Process

Let us now take a closer look at each of the five steps of the design thinking process, to better understand why they matter and how they can be implemented.

Step 1: Empathise 

Empathising is the foundational step in the design thinking process. It involves putting oneself in the shoes of the end-users to gain a deep understanding of their needs, desires, and pain points. Empathy is not just about understanding what users say but also about comprehending their unspoken emotions, frustrations, and aspirations. This step establishes the critical human-centric perspective that underpins the entire design thinking approach.

Why does this step matter?

Helps understand user needs: Empathy allows one to step into the shoes of the end-users and gain a deep understanding of their needs, desires, and pain points. This enables one to formulate solutions that genuinely address user needs.

Aids human-centred design: This step ensures that solutions go beyond just functionality and recognise the emotional and psychological aspects of the user experience. This makes it possible to create products that resonate deeply with the user.

Reduces assumptions: By empathising with users and collecting real-world data through reliable methods, problem-solvers can minimise assumptions and biases that might otherwise influence the design of the solution.

Enhances innovation: By understanding the problems and experiences of users, one can uncover opportunities for groundbreaking solutions that might not be apparent through a purely analytical approach. The extensive research involved at this stage allows one to identify hitherto unknown gaps, giving one an advantage when it comes to creating solutions. 

How to implement this step?

Putting oneself in the shoes of the user is a challenging task, especially when attempted on a large scale. This has given rise to various methods of data collection that can assist in making informed decisions and solving user problems. Let's briefly look at a few of these methods:

Step 2: Define

The second step in the design thinking process is to objectively define the core issue that one is trying to fix. At this stage, design thinkers delve deep into the issue at hand by studying the data collected, striving to understand it from the user's perspective and frame clear problem statements. This step serves as the bedrock upon which the rest of the journey is built.

For problem-framing: This step is essential for framing a clear and concise problem statement that is grounded in the needs and perspectives of the users. Without a well-defined and user-centric problem statement, the process to follow will lack direction, making it challenging to come up with a targeted solution that truly serves the user’s needs. 

For alignment: This step aligns the entire design thinking team and stakeholders by providing a common understanding of the problem to be solved and is essential to avoid miscommunication and misunderstandings as the design thinking process moves forward.

For evaluating success: Throughout the process, the problem statement can be used to assess whether the proposed solutions are effective. It provides a clear criteria for evaluating the success of the final solution / product / service / design.

For generating ideas: The problem statement generated in this step becomes a catalyst for idea generation in the subsequent step. It guides the team in brainstorming creative solutions that directly target the defined problem.

For reducing risk: By clearly defining the problem early in the process, this step helps reduce the risk of investing time and resources in developing a solution that ultimately doesn't address the core issue. It ensures that the design efforts are focused and purposeful.

Defining a concrete problem statement is the sole objective at this stage and there is a wide consensus on how to approach this. Here are key touchpoints to keep in mind while defining the problem statement:

Empathise with users: As you have probably picked up from what you have read thus far, empathising with the user is at the core of the process. Before you can create a meaningful problem statement, you must first deeply understand your users. This is where analysing the research from 'Step 1' comes into play. By immersing yourself in the users' world, you'll be better equipped to formulate a problem statement that truly resonates with their experiences.

Use the "How might we" framework: The "How might we" framework is a powerful tool for shaping your problem statement. It begins with the phrase "How might we..." and continues with a succinct description of the challenge you want to address. This open-ended format encourages creative thinking and brainstorming of diverse solutions. For example, instead of saying, 'We need a new website,' you might frame it as, 'How might we make it easier for users to find information on our website?' 

Focus on user-centric language: Your problem statement should revolve around the user. Use language that is drawn from their needs, challenges, and aspirations. Rather than a generic statement like, 'Develop a new product,' consider a user-centric approach such as, 'How might we create a product that simplifies daily tasks for busy professionals?' This approach ensures that the problem statement reflects the user's world.

Be specific: Avoid vague or overly broad statements. A well-defined problem statement should be specific and focused. The more precise it is, the easier it will be to brainstorm solutions and measure success. If your statement is too broad, it may lead to unclear, un-focused design efforts. For instance, instead of saying, 'Enhance customer experience,' consider specifying, 'How might we improve the checkout process to reduce cart abandonment rates on our e-commerce website?'

Step 3: Ideate

The ideate phase is a departure from the analytical stages that precede it. Ideation is where the magic happens in the design thinking process. It's the stage where the raw material for innovative solutions is gathered. By embracing creativity, utilising brainstorming techniques and fostering an open-minded atmosphere, one can harness the full potential of ideation.

Builds a diverse pool of ideas: Brainstorming is one of the most common ways to ideate freely and effectively and come up with a variety of innovative solutions. It is recommended to use all relevant means of collaboration at this stage to build a comprehensive and varied pool of ideas.

Helps with problem reframing, if necessary: During the ideation process, design thinkers may discover a weakness in the problem that has been defined. Since design thinking is an iterative and non-linear process, ideation can aid in closing any such gaps before one moves ahead with the rest of the process.

Produces refined ideas: Ideation is not just about generating ideas but also about refining and evolving them. Teams can combine, modify and build upon the best ideas from the ideation phase, leading to more refined and effective solutions.

Helps overcome biases: Ideation allows for the examination and mitigation of biases that might influence the problem-solving process. By actively encouraging diverse perspectives and ideas, teams can reduce the impact of cognitive biases on their decision-making.

Here are some ways in which the ideation step is implemented by design thinkers.

Classic brainstorming: This involves a group of people generating ideas through free association. The goal is to build upon each other's ideas, and generate a large and diverse pool of ideas. You can also use digital collaboration tools like Miro or MURAL for virtual brainstorming sessions, allowing team members to contribute remotely. 

Mind mapping: This method uses visual diagrams that connect ideas and concepts. It helps explore relationships between ideas and solutions and identify new possibilities.

SCAMPER technique: SCAMPER stands for Substitute, Combine, Adapt, Modify, Put to another use, Eliminate and Reverse. In this technique, all of these action verbs are used as questions to stimulate ideation.

Provocation: This method uses provocative questions like "What if we did the opposite?" or "How might we break all the rules?" to encourage out-of-the-box thinking.

Random word generation: This technique involves picking a random word and trying to relate it to your problem. This can lead to unexpected and creative associations.

Step 4: Prototype

The Prototype stage in the Design Thinking process is where your ideas take shape. It's the practical manifestation of the creative solutions you've generated during ideation. This stage involves creating tangible representations of your concepts and testing them to refine and improve your solution, product, or service. These tangible representations can range from simple sketches to high-fidelity, near-final products. 

For visualising ideas: Prototypes allow you to visualise and communicate complex ideas in a concrete and tangible way.

For reducing ambiguity: By providing a tangible representation of a concept, prototypes reduce misunderstandings and misinterpretations among team members and stakeholders.

For testing concepts: Using prototypes, you can test your design concepts with real users and stakeholders to gather feedback and insights.

For validating assumptions: Prototypes enable you to verify whether the envisioned solution aligns with real-world user needs and requirements, and thereby validate assumptions that were made in earlier stages of the process.

For refining solutions: Through iteration, prototyping helps in refining and improving ideas and solutions, by addressing issues and enhancing the user experience.

How to implement this step

There are various methods and techniques for prototyping in the design thinking process, and the choice of method depends on your specific needs and goals for a project . Here's an overview of some common ones:

Wireframes: Wireframes are widely used for creating simplified, visual representations of the layout and structure of an idea or solution. They are essential for defining the basic structure and content placement for digital interfaces and websites.

Interactive prototypes: Interactive prototypes are popular for simulating user interactions with a design. Tools like InVision , Figma and Adobe XD are widely used for creating interactive prototypes that allow users to click through and experience the functionality of the intended solution.

Paper prototyping: Paper prototyping is a low-tech, low-cost method that involves sketching ideas on paper and physically simulating user interactions. It's a simple yet effective way to ideate and test concepts.

High-fidelity prototypes: High-fidelity prototypes are often created with design tools like Sketch, Adobe XD or Figma, and they closely resemble the final product's appearance and interactions. These are used in later stages of the process for more polished and realistic user testing.

3D prototypes: In the realm of product and industrial design, 3D prototypes are commonly used to create tangible, physical models of products. 3D printing, CNC machining and other manufacturing processes are employed to bring these prototypes to life.

Step 5: Test

The Test stage in the design thinking process is where you evaluate your solutions to ensure they align with user needs and expectations. This step is pivotal in validating and refining your ideas, and turning them into effective, user-centric solutions.

Reduction of risk: By testing early and continuously, you minimise the risk of investing time and resources in a solution that doesn't meet user expectations. While testing incurs some initial costs, it can ultimately save resources by avoiding expensive late-stage re-designs and re-work. Testing helps you identify and address issues before they become costly problems.

Refinement: Testing provides valuable insights and feedback, which can be used to refine and improve the design. It's a fundamental aspect of the iterative nature of design thinking.

Market fit: Testing helps gauge the market fit of a product or solution. It ensures that the designed solution aligns with market needs and trends, increasing the chances of market success and product competence.

Several types of testing can be conducted to assess the effectiveness of your solutions.

Usability testing: This type of testing focuses on how easily users can interact with the design. Gathering direct feedback from users through surveys, interviews or user testing sessions is invaluable. This feedback provides insights into their preferences, frustrations, and suggestions for improvement.

A/B testing: A/B testing involves comparing two or more versions of a design to determine which one performs better in terms of user engagement, conversion rates, and/or other relevant metrics.

Prototype testing: Testing can start with low-fidelity prototypes and progress to high-fidelity versions as the design evolves. This allows for early feedback and refinement.

Next Steps To Learn Design Thinking

Through this exploration of the design thinking process, we have hopefully been able to illustrate the transformative potential of design thinking for problem-solving, and offered you a glimpse into its fascinating world. Now, it's time to take your journey further. 

To truly immerse yourself in the principles and practices of design thinking, you can begin by exploring our list of the best design thinking books . This collection provides in-depth insights, expert perspectives, and practical guidance, making it indispensable for anyone on the journey of creative problem-solving.

For those eager to take an active step towards mastering design thinking, we encourage you to consider enrolling in our UX UI Design courses . Our programs are designed to provide you with the knowledge, tools, and hands-on experience necessary to use design thinking to become a proficient UX UI designer.

To dive deeper into the world of UI/UX design itself, consider taking the following steps:

• Watch this session by Shiva Viswanathan, Design Head of Ogilvy Pennywise, and Naman Singh, Product Experience Designer at RED.
• Talk to a course advisor to discuss how you can transform your career with one of our courses.
• Pursue our UX UI Design courses - all courses are taught through live, interactive classes by industry experts, and some even offer a Job Guarantee.
• Take advantage of the scholarship and funding options that come with our courses to overcome any financial hurdle on the path of your career transformation.

Note: All information and/or data from external sources is believed to be accurate as of the date of publication.

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Design Thinking Defined

—tim brown, executive chair of ideo.

Thinking like a designer can transform the way organizations develop products, services, processes, and strategy. This approach, which is known as design thinking, brings together what is desirable from a human point of view with what is technologically feasible and economically viable. It also allows people who aren't trained as designers to use creative tools to address a vast range of challenges.

IDEO did not invent design thinking, but we have become known for practicing it and applying it to solving problems small and large. It’s fair to say that we were in the right place at the right time. When we looked back over our shoulder, we discovered that there was a revolutionary movement behind us.

This design thinking site is just one small part of the IDEO network. There’s much more, including full online courses we've developed on many topics related to design thinking and its applications. We fundamentally believe in the power of design thinking as a methodology for creating positive impact in the world—and we bring that belief into our client engagements as well as into creating open resources such as this.

At IDEO, we’re often asked to share what we know about design thinking. We’ve developed this website in response to that request. Here, we introduce design thinking, how it came to be, how it is being used, and steps and tools for mastering it. You’ll find our particular take on design thinking, as well as the perspectives of others. Everything on this site is free for you to use and share with proper attribution .

(From 2008-2018, designthinking.ideo.com was the home of IDEO's design thinking blog, written by our CEO, Tim Brown . You can find that blog here .)

We live and work in a world of interlocking systems, where many of the problems we face are dynamic, multifaceted, and inherently human. Think of some of the big questions being asked by businesses, government, educational and social organizations: How will we navigate the disruptive forces of the day, including technology and globalism? How will we grow and improve in response to rapid change? How can we effectively support individuals while simultaneously changing big systems? For us, design thinking offers an approach for addressing these and other big questions.

There’s no single definition for design thinking. It’s an idea, a strategy, a method, and a way of seeing the world. It’s grown beyond the confines of any individual person, organization or website. And as it matures, its history deepens and its impact evolves. For IDEO, design thinking is a way to solve problems through creativity. Certainly, it isn’t a fail-safe approach; nor is it the only approach. But based on the impact we are seeing in our work, the relevance of design thinking has never been greater.

Design thinking is maturing. It’s moving from a nascent practice to an established one, and with that comes interest and critique. People are debating its definition, pedigree, and value. As a leading and committed practitioner of design thinking, IDEO has a stake in this conversation—and a responsibility to contextualize its value in the present moment and, importantly, in the future.

We’ve learned a lot over the years, and we’d like to share our insights. We’ve seen design thinking transform lives and organizations, and on occasion we’ve seen it fall short when approached superficially, or without a solid foundation of study. Design thinking takes practice; and as a community of designers, entrepreneurs, engineers, teachers, researchers, and more, we’ve followed the journey to mastery, and developed maps that can guide others.

Designer's mindset

At IDEO, we are a community of designers who naturally share a mindset due to our profession. Our teams include people who've trained in applied fields such as industrial design, environmental architecture, graphic design, and engineering; as well as people from law, psychology, anthropology, and many other areas. Together, we have rallied around design thinking as a way of explaining design's applications and utility so that others can practice it, too. Design thinking uses creative activities to foster collaboration and solve problems in human-centered ways. We adopt a “beginner’s mind,” with the intent to remain open and curious, to assume nothing, and to see ambiguity as an opportunity.

To think like a designer requires dreaming up wild ideas, taking time to tinker and test, and being willing to fail early and often. The designer's mindset embraces empathy, optimism, iteration, creativity, and ambiguity. And most critically, design thinking keeps people at the center of every process. A human-centered designer knows that as long as you stay focused on the people you're designing for—and listen to them directly—you can arrive at optimal solutions that meet their needs.

Anyone can approach the world like a designer. But to unlock greater potential and to learn how to work as a dynamic problem solver, creative confidence is key. For IDEO founder David Kelley, creative confidence is the belief that everyone is creative, and that creativity isn’t the ability to draw or compose or sculpt, but a way of understanding the world.

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5 Examples of Design Thinking in Business

• 22 Feb 2022

Design thinking has become a business buzzword that’s changed how companies approach problem-solving . Countless brands, including GE Healthcare, Netflix, and UberEats, have utilized design thinking to develop effective solutions to challenges.

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What Is Design Thinking?

Design thinking is a user-centric, solutions-based approach to problem-solving that can be described in four stages :

• Clarify: This phase involves observing a situation without bias. It leans into design thinking’s user-centric element and requires empathizing with those affected by a problem, asking them questions about their pain points, and identifying what they solved. You can then use what you learn to create a problem statement or question that drives the rest of the design thinking process.
• Ideate: Begin brainstorming potential solutions. Take your problem statement or question and ideate based on patterns or observations collected in the clarify phase. This is the time to let your imagination and creativity run wild.
• Develop: Develop potential solutions using the ideas you generate, then test, experiment with, and reiterate to determine which are successful and which aren’t. Be ready to return to the ideation or clarification stage based on your results. Stepping back in the process is common—and encouraged—in design thinking.
• Implement: Finally, implement the solution you’ve developed. Again, it’s likely you’ll have to take a few steps back and reiterate your final solution, but that’s a central part of this phase. After several tests and edits, you’ll have a solution that can yield positive results.

Examples of Design Thinking

What does a properly executed design thinking process look like? Examining real-world examples is an effective way to answer that question. Here are five examples of well-known brands that have leveraged design thinking to solve business problems.

1. GE Healthcare

GE Healthcare is an example of a company that focused on user-centricity to improve a product that seemingly had no problems.

Diagnostic imaging has revolutionized healthcare, yet GE Healthcare saw a problem in how pediatric patients reacted to procedures. Many children were observed crying during long procedures in cold, dark rooms with flickering fluorescent lights. Considering this, GE Healthcare’s team observed children in various environments, spoke to experts, and interviewed hospital staff to gain more insight into their experiences.

After extensive user research, hospital pilots, and reiteration, GE Healthcare launched the “Adventure Series.” This redesign initiative focused on making magnetic resonance imaging (MRI) machines more child-friendly.

For example, the “Pirate Adventure” transforms MRI machines from dark, black holes to pirate ships with scenery of beaches, sandcastles, and the ocean. By empathizing with children’s pain points, GE Healthcare was able to craft a creative solution that was not only fun but increased patient satisfaction scores by 90 percent. This also yielded unexpected successes, including improved scan quality of pediatric patients, and ultimately saved customers time and resources.

Design thinking not only succeeds at finding effective solutions for companies but also at putting initiatives to the test before implementation.

When Oral B wanted to upgrade its electric toothbrush, it enlisted designers Kim Colin and Sam Hecht to help. The company’s request was to add more functions for electric toothbrush users, such as tracking brushing frequency, observing gum sensitivity, and playing music.

While clarifying the problem, however, Colin and Hecht pointed out that brushing teeth was a neurotic act for many people. Users didn’t want additional functionality and, in many cases, thought it could potentially cause more stress. Instead, they recommended two solutions that could improve user experience without adding gimmicks.

Their first recommendation was to make the toothbrush easier to charge, especially while users were on the road. Another was making it more convenient for users to order replacement heads by allowing toothbrushes to connect to phones and send reminder notifications. Both proposals were successful because they focused on what users wanted rather than what the company wanted to roll out.

Although many companies have successfully used design thinking, Netflix has repeatedly leveraged it to become an industry giant. During the company’s inception, its main competitor, Blockbuster, required customers to drive to brick-and-mortar stores to rent DVDs. The process was the same for returns, which was a major pain point for many. Netflix eliminated that inconvenience by delivering DVDs directly to customers’ homes with a subscription model.

While this revolutionized the movie industry, Netflix’s real success has been in its innovation over the years. For example, when the company realized DVDs were becoming outdated, it created an on-demand streaming service to stay ahead of the curve. This also inadvertently eliminated the inconvenience of having to wait for DVDs.

Subsequently, in 2011, Netflix took its design thinking one step further and responded to customers’ need for original, provocative content that wasn’t airing on traditional networks. Later, in 2016, it improved its user experience by adding short trailers to its interface. Each of Netflix’s major updates was in response to customers’ needs and driven by an effective design thinking process.

Another household name, Airbnb , started by only making around $200 a week. After some observation, its founders recognized that the advertising pictures hosts were posting online weren’t of a high enough quality, which often deterred customers from renting rooms.

To empathize with customers, the founders spent time traveling to each location, imagining what users look for in a temporary place to stay. Their solution? Invest in a high-quality camera and take pictures of what customers want to see, based on their travel observations. For example, showing every room rather than a select few, listing special features like a hot tub or pool in the description, and highlighting the neighborhood or areas in close proximity to the residence. The result? A week later, Airbnb’s revenue doubled.

Instead of focusing on reaching a bigger audience, Airbnb’s founders used design thinking to determine why their existing audience wasn’t utilizing their services. They realized that rather than focusing on traditional business values, like scalability, they needed to simply put themselves in users’ shoes to solve business problems.

5. UberEats

The go-to food delivery service app UberEats attributes its success to its ability to reiterate quickly and empathize with customers.

A prime example of this is UberEats’s Walkabout Program , where designers observe cities in which the company operates. Some elements they inspect are food culture, cuisine, infrastructure, delivery processes, and transportation. One of the innovations that came from their immersive research is the driver app, which focuses on delivery partners’ pain points around parking in highly populated urban areas. To address this, the driver app provides step-by-step directions from restaurant to customer to ensure smoother delivery processes.

Understanding that pain points vary between geographic locations helps UberEats implement effective upgrades to its service that solve problems in specific locations.

Practice Design Thinking

While these examples illustrate the kind of success design thinking can yield, you need to learn how to practice and use it before implementing it into your business model. Here are several ways to do so:

• Consider the Big Picture

In the examples above, it’s easy to say the solutions are obvious. Yet, try taking a step back to reflect on how each company thought about its customer base’s perspective and recognized where to employ empathy.

• Think Through Alternative Solutions

This is a useful exercise you can do with the examples above. Consider the problem each company faced and think through alternative solutions each could have tried. This can enable you to practice both empathy and ideation.

• Research Each Company’s Competitors

Another helpful exercise is to look at each company’s competitors. Did those competitors have similar problems? Did they find similar solutions? How would you compete? Remember to walk through the four design thinking phases.

Design thinking is a powerful tool you can use to solve difficult business problems. To use it successfully, however, you need to apply it to problems both big and small.

If you want to learn more about design thinking, explore our online course Design Thinking and Innovation —one of our online entrepreneurship and innovation courses —for more real-world case studies and opportunities to practice innovative problem-solving in your career.

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