04101nam a22005895i 4500 978-3-031-72255-4 DE-He213 20251030114646.0 cr nn 008mamaa 241228s2024 sz | s |||| 0|eng d 9783031722554 978-3-031-72255-4 10.1007/978-3-031-72255-4 doi Q336 UN bicssc COM021000 bisacsh UN thema Cheong, Michelle L. F. author. aut http://id.loc.gov/vocabulary/relators/aut 89752 Data and Decision Analytics for Business Operations [electronic resource] : Principles, Problems, and Practice / by Michelle L. F. Cheong, Ma Nang Laik. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XVIII, 323 p. 186 illus., 59 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda 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. 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. Artificial intelligence Data processing. Business Data processing. 59544 Production management. 67141 Operations research. 57943 Business information services. Information technology Management. 57223 Data Science. Business Analytics. 66186 Operations Management. 67304 Operations Research and Decision Theory. 67143 Business Information Systems. 66184 Computer Application in Administrative Data Processing. 66531 Ma Nang Laik. author. aut http://id.loc.gov/vocabulary/relators/aut 89753 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031722547 Printed edition: 9783031722561 https://doi.org/10.1007/978-3-031-72255-4 ZDB-2-CWD ZDB-2-SXPC 66133 66133