Introduction
Success of a high impact deep tech projects is unpredictable. Nobody, expert or seasoned professional, is able to discriminate the future Google, from the many failures that will pop up at the same time. This hard observation, of course, questions the value of what can be brought in terms of learning, actionable knowledge, valuable class time, to the soon-to-be entrepreneur or the student who is just trying to understand the rule of a fascinating by uncontrollable game.
This module is designed around the idea that if success is unpredictable, there are some methods, framework and tools that can help and guide the innovator in this exciting as much as it is difficult exploration.
Based on a flipped classroom approach, this module walk students through the key steps of building a Deep Tech Innovative Project. It is by design a multi-disciplinary exercise that touches at each step of its growth very different domains, such as understanding application of technologies, sensing high impact opportunities, exploring untapped markets where traditional market study approaches fail because neither you nor the potential user you have in mind actually understand what you’re talking about, execution (prototyping, building the operational model), funding, and then scaling.
Teaching objectives
- Understand the specifics of Deep Tech Innovation.
- Master the steps for Managing a Deep Tech Innovative Venture
- Acquire specific methodologies and tools.
Core structure
• Introduction – course objective -access to the online platform – team building – Project selection
• The principles of Opportunity assessment.
• Mapping the addressable market
• Confirming feasibility and execution: Business Model
• Pitch Rehearsal
• Final Presentation
Teaching method
- Online teaching content (SPOC)
- Short live sessions
- Learning by doing : project work on a real case
Individual work
- Study the online lecture,
- Groupwork on a real project
Grading
In-class Participation (10%) + Groupwork (30%) + Final presentation of the group project (60%)
- Profesor: Martinaud Bruno