Cognitive Biases & Decision-Making Pitfalls
These cognitive biases and decision traps can lead to poor choices in Agile development, planning, and execution. Agile teams must be aware of them to make better, more informed decisions.
| Concept | Agile Relevance | Usage in Agile |
|---|---|---|
| Dunning-Kruger Effect | People with low competence overestimate their abilities, while experts underestimate theirs. | Encourages Agile coaching, mentorship, and psychological safety to foster growth and self-awareness. |
| Hanlon's Razor | Misunderstandings, mistakes, or lack of information are more likely explanations than malice. | Promotes trust, psychological safety, and constructive problem-solving by discouraging blame and focusing on process improvements. |
| Einstellung Effect | Fixation on old solutions, even when better alternatives exist. | Encourages continuous learning, a culture of experimentation, and innovation. |
| Law of the Instrument (Hammer) | "If all you have is a hammer, everything looks like a nail." | Reinforces the need to choose the right Agile framework (Scrum vs. Kanban vs. SAFe) instead of blindly applying one method everywhere. |
| Streetlight Effect (Looking Under the Lamppost) | Looking for solutions only where it's easiest. | Encourages deep retrospectives and real problem-solving. |
| Icebergs of Ignorance | Leadership is often unaware of most frontline problems, while teams may not see strategic challenges. | Highlights the importance of bidirectional communication, feedback loops, and transparency. Ensures Leadership understands team challenges and teams grasp business priorities. |
| Humphrey's Law | Users don't know what they want until they see it. | Drives iterative development, prototyping, and frequent feedback. |
| Weinberg's Law | Software built without discipline and engineering rigor becomes fragile, making small issues lead to major failures. | Emphasizes the need for technical excellence, continuous refactoring, test automation, and strong Agile engineering practices to build resilient systems. |
| McNamara (Quantitative) Fallacy | "What can't be measured doesn't matter, and what is measured becomes the only thing that matters." | Warns against over-reliance on Agile metrics without considering qualitative factors like customer satisfaction, innovation, and team morale. |
| Dead Horse Theory | Persisting with failing initiatives instead of recognizing when to stop. | Encourages teams and leaders to recognize when a process, tool, or project is no longer adding value and pivot accordingly. Promotes continuous improvement and avoiding waste. |
| Bias Blind Spot | Recognizing biases in others but failing to see them in oneself. | Encourages self-awareness in Retrospectives, decision-making, and leadership. Promotes data-driven insights and psychological safety to challenge assumptions. |