This chapter offers a comprehensive framework for detecting, understanding, and correcting valuation errors across diverse contexts. It integrates foundational principles, finite-horizon valuation, and narrative discipline to help analysts maintain coherence between assumptions, risk, and business economics. Drawing on the taxonomy of common mistakes, narrative logic, and practical insights from real-world valuation practice, the chapter equips readers with tools to assess input quality, model consistency, and scenario robustness. Valuation emerges not as a mechanical computation but as a disciplined, human process grounded in judgment and economic realism. Most valuation mistakes come from using yesterday's tools on today's business models.