Technological innovation is increasingly a source of sustainable competitive advantage for companies around the world. However, building an organization capable of successfully and repeatedly bringing technological innovations to market is a major management challenge. This course focuses on the practices and processes that managers use to manage innovation effectively. The course will work from a human perspective, understanding students’ own creativity and skills, as well as those of users; and from a strategic perspective, examining the tools, techniques, and processes used to create and manage innovation.
Titular Professors
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By the end of this course, students should have achieved the objectives set for the course and developed the skills listed below. In summary, students will have acquired a solid foundation in creativity and innovation applied to management contexts, understanding why technological innovation is a key driver of sustainable competitive advantage and how organizations can improve their ability to turn opportunities into market-ready solutions in a repeatable way. Students will be able to structure managerial challenges, generate and evaluate alternatives, validate assumptions through experimentation and user feedback, and communicate an innovation proposal with clear strategic logic and a practical roadmap under real-world constraints.
1. Challenge discovery and definition
1.1. Introduction to the creative process and the Innovation Challenge.
1.2. Divergent and convergent thinking.
1.3. Neuroscience applied to creativity.
1.4. Observation, research, and problem understanding.
1.5. Problem framing through Mind Maps and Insight Statements.
2. Idea generation, selection, and development
2.1. Ten Types of Innovation as a framework for identifying opportunities.
2.2. Brainstorming and structured generation of alternatives.
2.3. SCAMPER and idea transformation techniques.
2.4. Forced connections and Creative Brief development.
2.5. Idea Portfolio development.
2.6. Selection criteria: value, feasibility, novelty, risk, and testability.
2.7. Use of the AI Challenger to question assumptions and decisions.
2.8. Lo-fi prototyping and hypothesis formulation.
2.9. Gate 1 — Concept Pitch: presentation and defence of the concept.
3. Innovation strategy, validation, and scalability
3.1. Disruptive Innovation and analysis of the competitive landscape.
3.2. Blue Ocean Strategy: ERRC Grid and Strategy Canvas.
3.3. User Innovation and the Lead User methodology.
3.4. Open Innovation and co-creation strategies.
3.5. Platforms, ecosystems, and the Pentagrowth Model.
3.6. Innovation adoption and diffusion: Rogers’ factors.
3.7. Prototyping, user validation, and learning documentation.
3.8. Growth, adoption, and scaling strategies.
4. Innovation culture, implementation, and communication
4.1. Innovation culture and organisational models.
4.2. Creative roles and high-performance team development.
4.3. Implementation Roadmap: resources, risks, milestones, and metrics.
4.4. Boardroom Critique: review and defence of key decisions.
4.5. Gate 2 — Innovation Proposal: final presentation, Q&A, and implementation proposal.
Readings and preparation: Students must review the assigned materials before each session and come prepared to apply the concepts to the Innovation Challenge. Readings, cases, and supporting resources will provide the basis for discussions, practical exercises, and project decision-making.
Classes, workshops, and participation: The course carries 3 ECTS credits and includes 30 contact hours delivered over two hours per week. Sessions combine short lectures, guided discussion, case analysis, practical exercises, and applied workshops. The course follows the sequence DISCOVER → FRAME → IDEATE → SELECT → PROTOTYPE → TEST → SCALE. Active participation is expected through high-quality contributions, feedback to other teams, and the defence of project decisions.
Challenge-based learning and teamwork: Throughout the semester, students will work in teams on a real Innovation Challenge assigned at the beginning of the course. The project will be developed progressively through individual and group activities, maps, idea portfolios, selection matrices, prototypes, user testing, and evidence documentation. The process includes two main milestones: Gate 1 — Concept Pitch (mid-term) and Gate 2 — Innovation Proposal (Final Presentation).
Integration of artificial intelligence: AI is integrated as a learning tool following the Human-First AI-Second principle: students research, think, generate, and decide first; AI is then used to expand alternatives, challenge assumptions, or improve clarity. Depending on the activity, AI may act as a Variator, Challenger, or Clarity Editor. Every use must be documented in the Artefact Log, including the tool, prompt, relevant output, and human decision made. AI outputs are not considered evidence and may not replace validation with real people.
Attendance and monitoring: Students are expected to attend all sessions, arrive on time, and remain for the full class period. Participation will also be monitored through contributions to the team Kanban, workshops, peer feedback, and individual questions during the Gates. Students are responsible for catching up on any content or activities missed due to absence.
The course is assessed through continuous assessment, combining individual assignments, teamwork, and two main presentations.
The final grade is distributed as follows:
- Class attendance: 10%
- Active participation: 10%
- Discovery & Framing Assignments — A1–A4: 15%
- Mid-term: Gate 1 — Concept Pitch: 20%
- Innovation Strategy Assignments — A5–A8: 15%
- Final: Gate 2 — Innovation Proposal: 20%
- Individual Team Peer Evaluation: 10%
Assignments A1, A2, A3, and A5 are individual. Assignments A4, A6, A7, and A8 are completed in teams. Gate 1 and Gate 2 consist of a team presentation and an individual Q&A directed to a randomly selected team member.
Participation is assessed through visible contributions to the team Kanban, the quality of feedback provided to other teams, preparation of assigned readings, and the ability to defend project decisions.
Three absences are allowed without penalty. The 4th absence results in a 0.5-point deduction, and the 5th absence results in a score of 0 for attendance. After 5 absences, the student may be at risk of failing the course.
The final grade is calculated through the weighted sum of all assessment components. As the course is experiential and team project-based, no make-up activities are available. Any confirmed case of plagiarism or breach of academic integrity may result in failure of the course.
Use of artificial intelligence
The course applies the AIAS scale:
- Participation and in-class activities: Level 1, no AI, unless expressly authorised.
- Assignments A1–A8, Gate 1, and Gate 2: Level 4. AI may be used for research, generating variations, challenging assumptions, organising information, supporting prototyping, and improving clarity. Decisions, idea selection, and final validation must remain human.
- Team Peer Evaluation: Level 3. AI may only be used to formally improve a comment already written by the student. It may not assign scores or generate the evaluation.
Every use of AI must be documented in the Artefact Log, including the tool used, the exact prompt, the relevant output, and the human decision made. AI-generated outputs are not considered evidence and may not replace observation, verifiable sources, or feedback from real users.
The following will be assessed:
- The ability to research, understand, and frame a real challenge using observations, verified sources, and relevant insights.
- The coherent application of the creative process: divergence, convergence, reframing, association, ideation, selection, and refinement.
- The variety, originality, and relevance of ideas generated through tools such as Mind Maps, SCAMPER, forced connections, and Ten Types of Innovation.
- The ability to evaluate and select ideas using explicit criteria related to value, feasibility, novelty, risk, and testability.
- The quality of the reasoning and evidence used to justify decisions throughout the project.
- The appropriate application of innovation frameworks such as Blue Ocean Strategy, Open Innovation, User Innovation, platforms, ecosystems, and innovation diffusion.
- The ability to formulate hypotheses, develop lo-fi prototypes, gather feedback from real people, and translate the results into learning and improvement.
- The coherence between the identified problem, value proposition, positioning, ecosystem, adoption strategy, and implementation roadmap.
- The clarity, structure, and professional quality of submissions, presentations, and oral defences.
- Each student’s ability to explain and defend the team’s decisions during the Gate 1 and Gate 2 Q&A sessions.
- Responsible contribution to teamwork, completion of assigned tasks, and the quality of feedback provided to other students.
- The responsible use of artificial intelligence in accordance with the Human-First AI-Second principle, including the documentation of prompts, outputs, verification, and human decisions. AI-generated outputs will not be considered evidence unless they have been properly verified.
The basic bibliography includes the main conceptual references used throughout the course to understand creativity processes, idea selection, innovation strategy, user innovation, platforms, and innovation adoption.
- Doblin / Deloitte. Ten Types of Innovation: Building Blocks of Breakthroughs.
- Kahneman, D., Lovallo, D., and Sibony, O. (2011). “Before You Make That Big Decision…”. Harvard Business Review.
- Kim, W. C., and Mauborgne, R. (2004). “Blue Ocean Strategy”. Harvard Business Review.
- Von Hippel, E. (2005). Democratizing Innovation. MIT Press.
- Parker, G. G., Van Alstyne, M. W., and Choudary, S. P. (2016). “Pipelines, Platforms, and the New Rules of Strategy”. Harvard Business Review.
- Rogers, E. M. (2003). Diffusion of Innovations. 5th edition. Free Press.
- Kelley, T., and Littman, J. (2005). The Ten Faces of Innovation. Doubleday.
To support the course sessions, students will have access to course-specific readings, academic articles, professional resources, and digital tools related to observation, insight development, ideation, prototyping, validation, and teamwork.
The main complementary materials include:
- Course readings on field observation, transforming data into insights, Open Innovation, innovation adoption, and innovation profiles.
- Elmansy, R. A Guide to the SCAMPER Technique for Creative Thinking.
- Stanford d.school. Prototype — Method Guide.
- IDEO Design Kit. Resources on prototyping and design mindsets.
- Gourville, J. T. (2006). “Eager Sellers and Stony Buyers”. Harvard Business Review.
- Cases, templates, videos, examples, and digital resources provided through eStudy to support assignments A1–A8, Gate 1, and Gate 2.
The specific readings and resources for each session will be available through eStudy and may be updated to incorporate relevant examples or materials connected to the Innovation Challenge.