TY  - BOOK
AU  - Cheong,Michelle L.F.
AU  - Ma Nang Laik
ED  - SpringerLink (Online service)
TI  - Data and Decision Analytics for Business Operations: Principles, Problems, and Practice 
SN  - 9783031722554
AV  - Q336 
PY  - 2024///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Artificial intelligence
KW  - Data processing
KW  - Business
KW  - Production management
KW  - Operations research
KW  - Business information services
KW  - Information technology
KW  - Management
KW  - Data Science
KW  - Business Analytics
KW  - Operations Management
KW  - Operations Research and Decision Theory
KW  - Business Information Systems
KW  - Computer Application in Administrative Data Processing
N1  - 1. Introduction -- 2. Demand Forecasting -- 3. Inventory Management -- 4. Distribution Management -- 5. Capacity Planning -- 6. Optimization Theory -- 7. Special Optimization Problems -- 8. Workforce Planning And Scheduling -- 9. Heuristic Algorithms -- 10. Queuing Theory -- 11. Simulation
N2  - In this book, readers will be exposed to the Data and Decision Analytics Framework which helps a business analyst to first identify the root cause of business problems by collecting, preparing, and exploring data to gain business insights, before proposing what objectives and solutions should be developed to solve the problems. To guide the reader through the learning and application of this framework, several cases are included in the book to illustrate the typical operations management problems faced by businesses. These cases are based on experiences in business domains such as retail, healthcare, transportation and logistics operations, and banking, and they are related to demand forecasting, inventory management, distribution management, capacity planning, resource allocation, workforce scheduling, and service system management. For each case, a complete mapping of the case into the Data and Decision Analytics Framework was done to explain how the framework was applied to derive the data insights from data analytics, to define the business objectives, make the necessary assumptions, and then develop the solution to the business problem. This book aims at senior-year undergraduate or graduate students studying industrial engineering, business management with a focus on operations, or data science. They will learn how to use data analytics to first analyze problems to identify the root cause of problems, before developing the solutions supported by decision analytics
UR  - https://doi.org/10.1007/978-3-031-72255-4
ER  -