A risk management model that illustrates how multiple layers of defense (like slices of Swiss cheese) can prevent failures, despite each layer having its own weaknesses. Crucial for understanding and mitigating risks in complex systems.
The process of running a system for an extended period to detect early failures and ensure reliability. Important for ensuring the stability and performance of digital products before full-scale deployment.
A cognitive bias that occurs when conclusions are drawn from a non-representative sample, focusing only on successful cases and ignoring failures. Crucial for making accurate assessments and designing systems that consider both successes and failures.
A cognitive bias where people perceive past events as having been more predictable than they actually were. Important for understanding and mitigating biases in user feedback and decision-making.
A cognitive bias where people underestimate the complexity and challenges involved in scaling systems, processes, or businesses. Important for understanding the difficulties of scaling and designing systems that address these challenges.
The risk that users will find the product difficult or confusing to use, preventing them from effectively utilizing its features. Crucial for making sure the product is user-friendly and intuitive, enhancing the user experience and adoption.