Designed for students, professors, researchers, and professionals in Organizational and Work Psychology, HR, and People Management, this textbook bridges the persistent gap between academic research and real-world practice through the lens of Evidence-Based Management (EBMgt). Grounded in scientific rigor and contextual sensitivity, the book guides readers through the six essential steps of evidence-based practice—asking, acquiring, appraising, aggregating, applying, and assessing—transforming complex organizational challenges into structured, data-informed decisions. Connecting theory and practice is a relevant and urgent demand to be met in the various learning spaces that prepare professionals to work in the field. Rather than offering abstract theory alone, this book presents 17 rich teaching cases drawn from public, private, and nonprofit contexts, including universities, hospitals, startups, NGOs, and industrial organizations – hypothetical, real or adapted from reality –, which allow readers to understand how, in practice, they can act in relation to various themes and phenomena in the field of organizational and work psychology. What sets this work apart is its strong emphasis on organizational diagnosis as the foundation of responsible intervention. Readers are introduced to validated instruments, quantitative and qualitative methods, and mixed approaches that expand technical expertise while reinforcing ethical and critical thinking. The cases function as “learning laboratories,” encouraging readers to adapt insights to their own contexts rather than replicate ready-made solutions. By integrating theory, assessment, and action, this book empowers professionals to make transparent, well-informed decisions that are both scientifically grounded and socially responsible. For anyone committed to elevating people management through evidence and reflection, this book is an indispensable resource. The original manuscript of this book was written in Brazilian Portuguese and translated into English with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.