This workshop focuses on the Design, Build, Test, Learn (DBTL) methodology for deep-tech innovation and product development. Through case studies and hands-on exercises, participants will learn how to effectively prototype solutions to real-world problems and improve their solutions based on continuous feedback and data-driven decision-making. The workshop will cover a complete cycle of the innovation process, from problem definition to commercialization, emphasizing the importance of feedback loops, interdisciplinary collaboration, agile development, and continuous learning. Students will make plans for testing and evaluation, and learn how to accelerate product development by tracking where their plans succeeded, where they failed, and what tools and methods are available to help improve product performance and market fit on the next DBTL cycle. Additionally, participants will learn techniques for deciding between physical prototyping, digital prototyping, or hybrid approaches.
The course instructors will encourage participants to regularly examine their own cognitive biases and resource limitations, so the right questions can be asked and feasibly answered.
This workshop offers 8 different hybrid sessions and will be a “learning” workshop as we plan to develop our content and perfect each session prior to launching our First Annual Deep Tech Innovation Workshop in the Fall of 2023.