Drawing on vast experience, the authors show how to apply state-of-the-art decision science, statistical modeling, benchmarking, and process modeling techniques together to create a robust analytical framework for better decision making. They integrate both new and time-tested techniques into a logical structured approach for assessing issues, developing solutions and making decisions that drive the successful achievement of business goals.
This book integrates new and existing methods to provide a comprehensive and holistic approach for assessing company performance and identifying areas for corporate improvement efforts. The goal is to get people to think of the big picture, understand the tools and techniques and put together the conceptual and analytical pieces to solve corporate-wide problems. The difficulty is to know when and where you should use these concepts. This book focuses on structured analysis processes that you can use to quantify, explore, and solve problems from a cross-functional perspective.
Coverage includes defining objectives; exploring the environment; scoping and prioritizing problems; applying data mining and statistical analysis; selecting the appropriate methods and tools; 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.
|Publisher:||Pioneering Partnerships LLC|
|Product dimensions:||6.00(w) x 9.00(h) x 0.62(d)|
About the Author
Deandra T. Cassone is a Senior Professor of Practice at Kansas State University. She has spent more than 25 years in industry consulting and management roles in Fortune 100 companies. Her interest include building structured decision-making models and she has been awarded numerous business process patents.
Table of Contents
About the Authors
PART I: The Method
1: Define Objectives and Identify Metrics
2: Explore the Environment
3: Explore the Scope of the Problem and Its Importance
4: Data Mining and Statistical Analysis
5: Solve the Problem and Measure the Results
6: Evaluate the Results and Do Sensitivity Analysis
7: Rules for Building Effective Decision Models
PART II: Case Studies
8: Logistics Service Provider
9: New Product Development
10: Airline Merger
Appendix A: Overview of Methodologies
Appendix B: Detailed Methodologies