Prescriptive Analytics

Mastering the Spreadsheet of Everything
2024
ISBN: 978-3-031-59352-9
Verlag: Springer Nature Switzerland

Buch, Englisch, 259 Seiten, Format (B × H): 215 mm x 285 mm, Gewicht: 952 g

Reihe: Springer Texts in Business and Economics

This book combines the quantitative decision-informing techniques of management science and operations research with the data-centric techniques found throughout the world of analytics. The material uses only standard Excel spreadsheet features and functions for creating models. Using a step-by-step approach, readers learn a unified architecture for sensitivity, scenario, simulation, decision, and optimization analysis. Spreadsheets with numerous screenshots support visual, hands-on learning (and provide some surprising innovations). Special influence diagrams and non-intimidating but accurate terminology help explain the logic of the models and calculations. Well-structured chapters include guideposts, enrichment, and curated links to valuable external resources. Readers are encouraged to own their learning and think about future trajectories for themselves and the field. This book helps all readers quickly learn tools and concepts to use right away and to expand throughout a career. The book includes access to a companion website featuring workbooks and other valuable materials to support learning.

Zielgruppe

Upper undergraduate

Autoren/Hrsg.

Keisler, Jeffrey M.

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung

Inhaltsverzeichnis

1. Modeling.- 2. Sensitivity Analysis.- 3. Indexed Sensitivity Analysis.- 4. Scenario Analysis.- 5. Simulation Analysis.- 6. Customized Input Distributions.- 7. Decision Analysis – Expected Value Maximization.- 8. Decision Analysis – Advanced Topic.- 9. Optimization: Decisions With Constraints.- 10. Optimization: Excel Solver.- 11. Epilogue.

Über Autor(innen)

Jeffrey M. Keisler (MBA Chicago, PhD Harvard) is Professor of Management Science & Information Systems at University of Massachusetts Boston. He was President of the INFORMS Decision Analysis Society and founding Secretary of the former Spreadsheet Research Section at INFORMS. He was named a Fellow of the Society for Risk Analysis, a Fellow of the Society for Decision Professionals, and a Fulbright Distinguished Chair. He has published nearly 90 journal articles and several books and is a long-time associate editor for several INFORMS and EURO journals. Over 30+ years in industry, government, consulting and academia, he has been applying, implementing, developing, teaching and preaching spreadsheet tools and prescriptive analytics techniques.