Problem Solving and Decision Making in Business offers a structured approach to navigating complex business challenges. The book examines the full cycle of problem identification, data gathering, analysis, developing decision alternatives, and implementation, providing practical frameworks suited to real-world business scenarios. Each chapter is designed to be self-contained and features examples, concepts, and tools for application in various organizational contexts.
The text walks through foundational and advanced topics, including defining problems and objectives, collecting and organizing data, applying probability and inferential analysis, and leveraging business research. It incorporates visual tools such as decision trees and explores the integration of machine learning, artificial intelligence, and data strategies in business decision-making. A dedicated chapter introduces Total Quality Management (TQM) principles and continuous improvement frameworks that support quality-driven decision-making, followed by a chapter offering a comprehensive toolkit of problem-solving frameworks. A capstone case study integrates and applies the skills developed throughout the text.
Problem Solving and Decision Making in Business is recommended for use in undergraduate and graduate courses in business, management, operations, and strategy. Its structure and content are suited both to classroom learning and to use as a standalone reference for business students and early-career professionals looking to develop analytical and decision-making skills.
