Design Thinking

The "Design Thinking" diplomas certify that their holder maintains an up-to-date and verifiable level of competence in design thinking applied to ill-defined problems: understanding and reframing the problem, diverging with method, prototyping to learn, co-creating with the people affected, and widening the view from the user to the system, choosing and combining practices according to what the team needs.

This diploma does not assess "theoretical knowledge" of design frameworks and techniques, but the ability to reframe a problem before solving it, generate varied alternatives and make them tangible to learn from real people, and design your own design process, with judgment about the role of artificial intelligence in each mode of work.

Accredited Competencies

Holding these up-to-date diplomas certifies that the holder is able to:

1) Recognize when a problem calls for Design Thinking

Distinguish ill-defined problems from complicated and chaotic ones, place Design Thinking as a discovery technique and a cross-cutting ability within agility, delimit it against user experience, product discovery, and service design, and recognize the whole-approach antipatterns that the critique of the approach has documented.

2) Read the frameworks as maps and choose practices

Explain the d.school's five modes and their rereading as eight abilities, the Double Diamond with its extensions, the systems of methods of IDEO, LUMA, and IBM, and Liedtka's four questions, and use them to choose the practice that answers what the team needs to understand, imagine, make tangible, or learn, including the Design Sprint as a format.

3) Reframe the problem

Separate symptoms, causes, constraints, and assumptions in a stated problem, detect solutions disguised as problems, apply the reframing practices and the abstraction ladders, and look for a better frame instead of "the real problem."

4) Observe with intent and empathize within limits

Distinguish what people say, do, and make, apply an observation scaffold that separates facts from interpretations, choose extreme users and analogous contexts to inspire, and replace imagined empathy with real contact and participation.

5) Synthesize as a team up to the insight

Organize the immediate download and the silent affinity clustering, read themes and tensions, formulate insights that change the team's perspective and distinguish them from observations, and use the AI's automatic clustering as a proposal that the team reviews.

6) Define the point of view and the generative question

Formulate the design challenge before researching and the point of view after synthesizing, write "How might we…?" questions with the right breadth, revise the definition of the problem after testing, and choose which challenge to explore with explicit criteria.

7) Diverge with method

Separate generation and evaluation, measure an ideation session by its variety and not only by its quantity, recognize design fixation and the other blocks, and facilitate ideation in hybrid mode, alone first and then together, with the protocol and the levers that the evidence supports, bringing AI in after the human round.

8) Converge with criteria

Cluster before voting, set explicit criteria and use matrices, mitigate the biases of dot voting, distinguish voting from deciding, and take two or three different ideas to prototype instead of one.

9) Prototype to think and to learn

Treat the prototype as a question, place it in the three kinds of questions of role, look and feel, and implementation, choose fidelity by dimensions according to the question, prototype interfaces, services, processes, and policies with the appropriate technique, and test in design mode to learn about the problem and the direction, not only about the solution.

10) Prototype with artificial intelligence without confusing prototype and product

Decide the fidelity of an AI-generated prototype by the question and the willingness to throw it away, degrade it on purpose when appropriate, keep the line between building to learn and building to earn, and recognize the risks of anchoring, generic patterns, and complacency.

11) Co-create, facilitate, and communicate design work

Check the three conditions of real participation and recognize tokenism, design and facilitate a design session in the room and remote while declaring roles, practice critique on ideas and prototypes with its formats, use visual thinking, and communicate findings and prototypes to those who decide.

12) Widen the focus from the user to the system

Recognize the limits of the user-centered approach, map actors and incentives, apply a minimum of systems thinking, ask who wins, who loses, and who is missing with a consequence-scanning practice, apply the inclusion lens, and decide with a complexity framework when Design Thinking pays off, is superfluous, or arrives too late.

13) Design your own design process

Choose the entry point according to uncertainty, combine practices with the seven questions, close an activity when it stops contributing, place your own work in the design abilities and in the levels of expertise, and decide in each mode who leads, the person or the AI, knowing the risks specific to AI in design.