A Professional’s Guide to Decision Science and Problem Solving

05/10/2012 · No Responses

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.

From the Back Cover
A Powerful Roadmap for Making Decisions That Optimize Performance—Every Time

This professional reference combines the best decision science models and tools to deliver a time-tested approach to problem solving and decision making in corporations. The authors draw from their decades of experience in decision science and operations management, giving professionals a field-tested model for making decisions that meet corporate objectives in businesses that rely on process and operations management.

Their paradigm combines both new and classic techniques into an integrated approach for assessing issues, developing solutions, and making decisions that drive organizational success.

COVERAGE INCLUDES:

Defining objectives
Exploring the environment
Determining the scope of the problem
Applying data mining and statistical analysis
Selecting and executing solutions
Measuring and evaluating results and more

Case study chapters walk through the effective use of the authors’ framework in diverse corporate environments and demonstrate its exceptional adaptability.