This book is an exploration of the reasons, biases, and blind spots that result in people making assumptions and jumping to conclusions during problem-solving. It delves deep into why, even experts, often make errors in judgment when problem-solving.

Through a combination of behavioral science, data science, and real-world examples, this project is aimed at equipping the reader with a deeper understanding and awareness and a practical toolset to allow them to separate speculation from fact and get to the true root cause.

The book applies principles of lean thinking, scientific method, and statistical analysis to problem-solving scenarios. By introducing concepts such as Attribute agreement analysis, Cognitive biases, Hypothesis testing, and Special cause vs Common cause, the book provides the reader with a structure that enables them to navigate complex problems. The narrative is enriched with stories and anecdotes that reinforce the concepts and demonstrate how the tools were and can be successfully used. In addition, the book demonstrates through some of these stories the negative impact that assumptions have had in various fields ranging from medicine to Engineering.

Essentially, the book makes rigorous problem-solving methodologies and the application of the scientific method engaging and accessible. The book employs humor, storytelling, and relatable anecdotes to illustrate abstract concepts, making it an effective learning tool for both professionals and general readers. Readers are encouraged to actively challenge their own biases, improving their ability to validate assumptions before acting on them.