Innovation Engineering
We develop and validate new methodologies for early-stage product and technology innovation by studying real-world innovation projects. Our focus is on „lean de-risking“ - an approach to efficent and fast identification and mitigation of uncertainties inherent to innovation ideas.
We believe that method development and teaching can only happen through active participation in real-world projects. Therefore, we engage students and industry partners in collaborative innovation programs, which build innovation skills while providing real-world research cases to refine our methodologies. Through this reciprocal process, our educational and research activities continuously enhance each other.
Our Programs
Programs we actively run, support, and analyze include:
- Innovation Project: A curricular robotics competition engaging over 500 third‑semester Bachelor students in Mechanical Engineering, designed to build foundational innovation skills (learn more).
- Exploration Lab: An academia‑industry matchmaking program where interdisciplinary Master student teams explore innovative ideas within industry settings, fostering connections between companies and ETH expertise (external page learn more).
- Focus Project Coaching: Mentors third‑year bachelor Focus Project teams, guiding agile concept development, iterative prototyping and stage‑gate reviews to strengthen engineering leadership skills.
- emba X – Agile Hardware & Technology (module): One‑week executive module where senior leaders experience agile hardware development through rapid prototyping, lean de‑risking and sprint testing in ETH makerspaces (external page learn more).
- CAS ETH Applied Manufacturing Technology – Product Development & Technology Implementation (module): Continuing‑education module led by Prof. Meboldt that lets participants apply agile principles and additive manufacturing to a real prototyping challenge, illustrating technology implementation pathways (learn more).
Group History
- Founded in 2019 by Prof. Mirko Meboldt and Stephan Fox as the Feasibility Lab for Healthcare Innovation to support clinicians in developing solutions. During COVID-19, led the Helpful ETH initiative.
- Since 2022, led by Kai von Petersdorff-Campen, the group adopted a technology-agnostic approach supporting diverse industry partners through our "lean de-risking" methodology, collaborating with companies such as Planted and Johnson & Johnson.
- From 2023 onward, emphasis shifted towards conducting the Exploration Lab Program, engaging industry partners such as Bühler, Bossard, VZUG, and VAT in exploratory innovation activities with ETH (links to 2023 and 2024 cohort videos forthcoming).
- From 2025, the Feasibility Lab was transferred from D-MAVT to the Vice Presidency for Industry Relations and Knowledge Transfer (VPWW) to scale the Exploration Lab format across other ETH departments and to support the development of new programs fostering academia-industry matchmaking through project-based education.
Methodology / Publications
Basics of De-Risking
The task of an engineer is to find the most efficient path from an idea to the product. It is all about “lean de-risking” - learning as much as possible with limited time and money. This booklet offers some basic concepts to aid the discussion on how to balance risk and progress in engineering projects.
The core messages are:
- Uncertainty can only be reduced by real-world testing.
- The more certain you are, the more you can invest before the next test.
- Minimize fidelity when uncertainty is high, to learn resource-efficiently.
Five Finger Formula
The formula is our cornerstone of problem-solving across all project scales, from interactive workshops to expansive initiatives. We use it to dissect technical challenges as well as to scrutinize business cases. It is “handy” to remember (T, I, M, R, L) and involves the following steps:
- Tackle Assumptions - Challenge assumptions and strive for the fundamental problem.
- Isolate the Pain - Relentlessly focus your efforts only on the one most critical uncertainty.
- Map Diverse Solutions - Explore a variety of approaches to maximize your chances and discover the unexpected.
- Run Lean Tests - Build minimal prototypes and fast test setups for rapid iteration and learning.
- Listen to Metrics - Define specific criteria and get experimental data to inform your decisions.