Overcoming Overconfidence in a Madrid D2C Cosmetics Startup
Overview
What this challenge is about.
Analyze a founder's overconfidence in a Madrid cosmetics startup and propose a better decision process. Earn a verifiable certificate.
The scenario
Luz Natural is a 50-employee D2C cosmetics startup in Madrid, with €10M annual revenue. The founder has a strong track record but recently launched three new product lines that underperformed, resulting in €500K in unsold inventory.
The Brief
What you'll do, and what you'll demonstrate.
How can Glow Naturals reduce overconfidence-driven overproduction in product launches without stifling innovation?
Earning criteria — what you'll demonstrate
- Identify and analyze overconfidence bias in real-world financial decisions
- Apply reference class forecasting to improve estimation accuracy
- Design debiasing mechanisms for organizational decision-making
- Communicate behavioral insights to non-expert stakeholders
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Overconfidence Bias
Apply overconfidence bias to solve real industry problems and demonstrate production-level capability.
- Prospect Theory
Apply prospect theory to solve real industry problems and demonstrate production-level capability.
- Decision Framing
Apply decision framing to solve real industry problems and demonstrate production-level capability.
- Reference Class Forecasting
Apply reference class forecasting to solve real industry problems and demonstrate production-level capability.
- Pre Mortem Analysis
Apply pre mortem analysis to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles: