A Professional's Guide to Decision Science and Problem Solving provides an integrated, start-to-finish framework for more effective problem solving and decision making in corporations. Drawing on vast experience in the field, the authors show how to apply state-of-the-art decision science, statistical modeling, benchmarking, and processing modeling techniques together to create a robust analytical framework for better decision making in any field, especially those that rely on advanced operations management. They integrate both newly-developed and time-tested techniques into a logical, structured approach for assessing corporate issues, developing solutions, and making decisions that drive the successful achievement of corporate objectives. Coverage includes: defining objectives, exploring the environment; scoping problems and evaluating their importance; bringing data mining and statistical analysis to bear; solving problems and measuring the results; evaluating the results and performing sensitivity analysis, and more. The book concludes with three case study chapters that walk through the effective use of its methods, step-by-step. Representing a wide variety of corporate environments, these case studies underscore and demonstrate the method's exceptional adaptability. This book will be valuable in a wide range of industries, notably finance, pharmaceutical, healthcare, economics, and manufacturing.