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

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

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

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

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

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

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

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

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

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

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

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

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

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

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